United States
Environmental Protection
Agency
Environmental Monitoring
and Support Laboratory
P.O. Box 15027
Las Vegas NV89114
v>EPA
Distribution of
Phytoplankton in
North Dakota
Lakes
Working
Paper 700
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DISTRIBUTION OF PHYTOPLANKTON IN NORTH DAKOTA LAKES
by
W. D. Taylor, L. R. Williams, S. C. Hern,
V. W. Lambou, F. A. Morris*, and M. K. 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. 700
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.
111
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CONTENTS
Page
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 North Dakota 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
14 lakes sampled in the State of North Dakota (Table 1). The Mygaard'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 NORTH DAKOTA
STORET No.
Lake Name
County
3801
3802
3803
3804
3805
3806
3807
3808
3809
3811
3812
Lake Ashtabula
Lake Audubon
Brush Lake
Lake Darling
Devils Lake
Jamestown Reservoir
Lake La Moure
Matejcek Lake
Lake Metigoshe
Pelican Lake
Lake Sakakawea
(Garrison Reservoir)
Barnes, Griggs
McLean
McLean
Renville
Benson, Ramsey
Stutsman, Foster
Stutsman
Walsh
Bottineau (part in Canada)
Bottineau
Mercer, McLean, Mountrail
Williams, McKenzie, Dunn
(Continued)
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TABLE 1. LAKES SAMPLED IN THE STATE OF NORTH DAKOTA (Continued)
STORET No. Lake Name County
3813 Spirit Hood Lake Stutsman
3814 Sweet Briar Reservoir Morton
3815 Whitman Lake Nelson, Walsh
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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-Lugol's 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 botton 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 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
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
Oligotrophic Eutrophlc
Myxophycean
Chlorophycean
Diatom
Euglenophyte
Compound
Myxophyceae
Desmideae
Chlorococcales
Desmideae
Centric Diatoms
Pennate Diatoms
Euglenophyta
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
Chlorella
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 ienneri
Chlorel la vulgaris
Cyclotella meneghiniana
Euglena gracilis
Euglena viridis
Gomphonema parvulum
Melosira varians
Navicula cryptocej>hala
Nitzschia acicularis
Nitzschia palea
Oscillatoria chlorina
Oscillatoria limosa
Oscillatoria princess
Oscillatoria putrida
Oscillatoria tenuis
Pandorina morum
Scenedesmus quadricauda
Stigeoclonium tenue
Synedra ulna
Poll ution
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.
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 - -X PI logx PI
1 = 1
where P is the proportion of the ith taxon in the sample, which is calculated
from rij/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.
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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 logg S
(Pielou 1966), while the minimum diversity (MinH), was estimated from the
formula:
MinH = -
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
MaxH-HinH
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 *• 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
millHiter. 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.
Hutchinsqn, 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 NORTH DAKOTA
12
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Actinastrum gracilimwn
Amphora sp.
Anabaena circinalis
Anabaena flos-aquae
Ankistrodesmus falcatus
Ankistrodesmus falcatus
v. acicularis
Ankistrodesmus falcatus
v. mirabilis
Aphanizomenon flos-aquae
Aphanothece sp.
Asterionella formosa
Asterionella formosa
v. gracillima
Carteria sp.
Ceratium hirundinella
Ceratium hirundinella
f. furcoides
Ceratium hirundinella
f. robustum
Ceratium hirundinella
f. scotticum
Chaetoceros elmorei
Chlamydomonas globosa
ChloTogoniim sp.
Chrooaoccus dispersus
Chroooocaus lirmeticus
Chroomonas acuta
Chroomonas reflexa
Closteriwn sp.
Cocconeis pediculus
Cocconeis placentula
Coelas trim micTOporum
Coelastrum reticulatum
Coeloephaerium kuetzingianum
Coelosphaerium naegelianum
Coscinodiscus lacustris
Cosmarium sp.
Crucigenia quadrata
Crucigenia tetrapedia
Cvyptomonas erosa
Cryptomonas marssonii
Cryptomonas reflexa
Cryptomonas rostrata
Cyclotella meneghiniana
Cymatopleura elliptica
Cymatopleura solea
Cymbella triangulum ?
Dactylococcopsis fascicularis
Dactylococcopsis irregularis
Diatoma vulgare
Dictyosphaerium ehreribergianum
Dictyosphaerium pulchellum
Dinobryan divergens
Dinobryon sertularia
Dinobryon sociale
Dinobryon sociale
v. americanwn
Diplopsalis acuta
Elakatothrix gelatinosa
Entomoneis alata
Entomoneis ornata
Epithemia sorex
Eudorina elegans
Euglena gracilis
Euglena tripteris
Fragilaria crotonensis
Frustulia rhombo-ides
Glenodinium gymnodinium
Glenodinium oculatum
Glenodinium penardiforme
Gloeocystis gigas
Gloeocystis major ?
Gloeotrichia echinulata
Gomphonema sp.
Gomphosphaeria aponina ?
Gomphosphaeria lacustris
Gymnodinium albulim
Gyrosigma wormleye
Hantzschia sp.
Kirchneriella contorta
Lepocinclis sp.
Lyngbya birgei
Mallomonas acaroides
Mallomonas caudata
Mallomonas pseudocoronata
Melosira distans
Melosira granulata
Melosira granulata
v. angustissima
Melosira varians
Merismopedia glauca
Merismopedia minima
Merismopedia tenuissima
Microcystis aeruginosa
Microcystis incerta
Mougeotia sp.
Navicula viridula
v. avenacea
Nitzschia closterium
Nitzschia filiformis
Nitzschia siamoidea
13
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Oocystis borgei
Oocystis eremosphaeria
Oocystis parva
Ophiocytium ? sp.
Oscillatoria agardhii
Oscillatoria amphibia
Pandorina morum
Pascherina tetras
Pediastrwn boryanum
Pediastrwn duplex
Pediastrwn duplex
v. clathratwn
Pediastrwn kawraiskyi
Pediastrwn tetras
Peridinium inoonspiauum
Peridiniwn quadridens
Peridiniwn willei ?
Phacus acwninatus
v. drezepolskii
Phacus caudatus
Phacus megalopsis
Phacus pleuronectes
Phacus pseudonordstedtii
Phacus pyrum
Phormidiwn mucicola
Pirmularia brevicostata
Quadrigula chodatii
Raphidiopsis sp.
Rhodomonas minuta ?
Rhoicosphenia curvata
Rhopalodia gibba
Scenedesmus abundans
Scenedesmus acuminatus
Scenedesmus bijuga
Scenedesmus dimovphus
Scenedesmus intermedius
Scenedesmus obliquus
Scenedesmus quadricauda
Scenedesmus setigera
Selenastrwn sp.
Spermatosoopsis sp.
Sphaerocystis schroeteri
Spirogyra sp.
Staurastrwn tetracerum
Stephanodiscus astraea
Stephanodiscus niagarae
Surirella angusta
Surirella ovalis
Surirella ovata
Synedra acus
Synedra delicatissima
Synedra ulna
Synura ? sp.
Tetraedron minimum
Tetraedron minimum
v. scrobiculatum
Tetraedron regulare
Tetraedron regulars
v. granulata
Tetraedron regulars
v. incus
Tetraedron trigonum
Tetrastrum staurogeniaeforme
Trachelomonas intermedia
Trachelomonas planctonica
Trachelomonas volvocina
Volvox sp.
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 IMCERTA ?,
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
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(.ARE NANEt flATEJCbK UKl
STCRET NUItBtR: 38C8
NYGAARD TROPHIC STATE IrtOICES
DATE 04 29 74 j7 It 74 09 16 74
: AN
CHLOROPHYCEAN
EUGLErtOPHYTE
OIAIQR
COMPOUND
01/0
J2/0
C..67
0.33
C6/0
03/0 t
0
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STOfcEl NUNBlRi 1808
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LAKE NAME: LAKE NEIIGJSHE
STC»ET NUMBER: 3»09
NYGAAPU TPuPHIC STATE INDICES
L*TE ,7 17 74 09 13 7".
MYXGPHYCtAN
CHIURUPHYCEAN
EU&lENUPHYrE
DIAIOM
COMPOUND
03/C t
08/C t
0.^7 I
0.2S ?
t
0-/C t
G«./0 t
o/oe ?
0.50 t
ic/o t
PALMER'S ORGANIC PULLUT10N INUICIS
DATE 07 17 74 09 13 74
GENUS
SPECIES
C.4
03
SPECIES DIVERSITY AND ABUNDANCE INDICES
OA1E
C7 17 74 09 13 Ti
AVERAGE OIVERSITT
NUMBIR OF TAXA
NUMBER OF SAMPLES COMPOSITED
HAX1KUM DIVERSITY
HINUMUH DIVERSITY
TOTAL DIVERSITY
TOTAL NUMBER Cf- IHD IV II)UALS/Hl
EVENESS COMPONENT
KELA1IVE lEVENESS
MEAN NUMBtH OF iNOIVIDUAtS/TAXA
NUMBER/ML OF HOST ABUNDANT TAXON
H
s
N
MAIN
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0
N
J
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L
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3
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I AM KAMI lAKt HET163SHI
SIllKEI HUB6t«t
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07 17 7»
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LAKE NANt: PELICAN LAKfc
STURET NUMBER: 38ii
NYtAAkO TROPHIC SlATb INDICES
DATE 07 17 7.00
flNUnUN DIVERSITY ft[NH 0.11 0.3b
RELATIVE EVENfSS RJ 0.
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LAKE hA«{: PIUCAH LAKt
siufcii Nu«ei*> sen
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LAXt MA1E« SAKAKAUtA
STUREI NuHUiR: 3612
NYGAARO TROPHIC SIAIE INDICES
DATE C4 3C •("• 07 IB 74 ;9 17 74
HTXOPHrCEAft 01/0
CHLOtOPHTCtAN 04/0
EUGLENOPHTIE 0.60
OlATOfl C.33
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t
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0.33 £
0.13 t
11/0 b
02/C t
03/0 t
0.20 ?
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10/0 E
PALMER'S ORGANIC POLLUTION INDICES
DATE 04 30 74 07 13 74 39 17 74
GENUS
13
04
00
SPtCIES ClVEASirt AND ABONCANCf INDUES
DATE 04 30 74 07 IB 74 09 17 74
AVCRAbE DIVERSITY
NUH6EF OF TAXA
NONBER UF JANPLES CCIPOSITfO
01VECSITT
DIVERSITY
TOTAL CIVE8SI1T
TOTAL NUH8EK CF I NO I» 1LU»li/Nl
EVENESS CC'NPOhENT
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NEAN NUHBCK OF INOIV1GUALS/TAXA
MUNBER/ML UF HOST AbUNUANT TAXON
H
s
n
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0
N
J
RJ
L
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3.:b
29. uo
9.00
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29
-------
IMf NAHt: SAKAftAllIt
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37
-------
LAKE NAME: SPIRIT UUUO LAKE
NUMBER: 3813
GATE
NYXUPHYCtAN
CHLOROPHYCEAN
EUGLENOPHYTE
D1AIUH
COMPOUND
TROPHIC STAIE INDICES
04 ib 74 07 17 74 09 17 74
02/0 k
c/o o
0/12 1
O.iO E
04/C E
34/0 E
0
?
0/0 ?
04/0 t
03/0
0/0
0/03
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PALMER'S OkGANlC POLLUTION INDICES
DATE 04 16 74 07 17 74 09 17 74
01
GENUS
SPECIES
13
03
Cl
30
SPECIES DIVERSITY AMU A6UNOANCE INDICES
DATE
AVERAGE UIVEkSITT
NUMBER Of TAXA
NUMBER OF SAMPLES COMPOSITED
MAXIMUM DIVERSITY MAXH
MINUHUH DIVERSITY KlMH
TOIAL DIVERSITY
TOTAL NUr.bER OF INUI VIDUALS/Ml
EVENtSS COMP3NENT
RELATIVE EVENESS
MEAN NUMBER OF I NO 1VIbUALS/TAXA
NUHBERVML 01 HOST AbUNOAM TAXON
C4 Zb 74 37 17 74 09 17 74
H
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0.15
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2.00
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1967.05
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10245.00
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7.00
2.00
2.81
0.07
1974.00
940.00
0.75
0.75
134.29
376.00
38
-------
LAKE KAMI SPIRIT 10(10 IAIE
SICJRCI NUMBER! Jail
CONIIMUEO
..* 26 7*
.7 17 7»
09 17 7*
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39
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LAKE NAME: SHtET 8RIAR RtS.
STORET NUMBERS
NTGAARO TROPHIC STATE INDICES
DATE 04 30 7* 07 16 74 -9 17 7*
HVXOPHYCEAN 02/0 E SWO £ 05/0 E
CHLOROPHYCE»N 0/0 0 Cl/0 E 01/0 E
EUGLENOPHYfE 0/02 ? 0/05 ? 0/06 ?
OIATUH 0/03 ? :/01 ? 0/0 ?
COMPOUND OZ/0 E 05/0 t 06/0 E
PALNEB'S ORGANIC POLLUTION INDICES
DATE Ot 30 74 07 lt> 74 09 17 74
GENUS
SPECIES
00
C3
00
00
SPECIES DIVERSITY AND ABUNDANCE INDICES
DATE 04 30 74 07 16 74 09 17 74
AVERAGE DIVERSITY H 2.81 1.12 G.U9
NUPCCR OF TAXA S 7.00 9.CO 8.00
NUtbER OF SAMPLES COnPOSITEO n l.uo 2.-0 c.OO
MAXIMUM DIVERSITY MAXH 2.81 3.17 3.00
HINUHUM DIVERSITY MINH C.C3 0.02 0.32
IOIAL DIVERSITY 0 0.00 4935.04 437).24
TOTAL NUflfaEK OF I NO IVIOUALS/KL N O.OC 4407.CJ 4916.00
EVENtSS COMPONENT J 1.00 0.35 0.30
RELATIVE EVCNESS RJ 0.54 0.35 0.30
,!£AN NUMBER OF INUIVICUALS/TAXA L o.co -.69.67 614.50
NUMBER/ML OF HUST ABUNDANT TAXON K 0.01 3415.CO 3997.00
40
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L*Ht l.*Hfl S«£IT BRUil RtS.
StOfcST NJA8CR: 381*
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LAKE NAME: WHITMAN LAKE
STORE! NUMBER: 381*
NYGAAHD TRCPH1C STATE INDICES
DAlt 04 £7 74 J7 16 74 '.<» Ib 74
NYXUPHYCEAN 4.10 fc '•.CO E 7.00 E
CHLOPOPMYCEAN 3.CC I 6.00 E 5.00 E
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DIATOM 1.00 fc 0.7) I 2.00 E
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PALMER'S ORGANIC POLLUTION INDICES
DATE 04 27 74 07 16 74 09 16 74
GENUS 13 01 02
SPECIES 00 00 00
SPECIES OlVtRSlTY AND ABUNDANCE INDICES
DATE 04 27 74 07 16 74 J9 16 74
AVLRAGc DIVEPSITY H 3.02 3.0J 1.J7
NUHOER OF 1AX* S 21.00 28.CO 16.00
NUMBER OF SAMPLES COMPOSITED M 2.00 2.iC 2.00
HAXIHUM DIVERSITY MAXH 4.39 4.61 4.17
MlNbHUH DIVERSITY MINti C.30 C.C8 C.02
TOTAL DIVERSITY 0 2222.72 12960.00
TOTAL NUf.BER OF INDIV IDUALS'ML N 736.00 4J20.CO
EVENESS CONPCHENl J C.69 C.62 0.2b
RELATIVE EVENESS RJ U.t7 3.62 0.26
MEAN NUMBER Qt 1NDIV1DUALS/TAXA L 35.OS 154.29 631.36
NUMBER/ML Of M3ST ABUNDANT TAXCN K 163.00 1006.00
42
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LAftl NANt : kHlTRAft LAKE
Stunt! nufiafll 381»
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