QK93S-
1978 i
 1
 vvEPA
             United States
             Environmental Protection
             Agency
             Environmental Monitoring
             and Support Laboratory
             P.O. Box 15027
             Las Vegas NV 89114
Distribution of
Phytoplankton in
South  Dakota
Lakes
600379069

Working
Paper 702

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DISTRIBUTION OF PHYTOPLANKTON IN SOUTH DAKOTA LAKES

                         by

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

             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. 702
          NATIONAL EUTROPHICATION SURVEY
        OFFICE OF RESEARCH AND DEVELOPMENT
       U.S.  ENVIRONMENTAL PROTECTION AGENCY
                  November 1978
         U.S. Environmental  Protection  Agency
         Region V, Library
         230 South  Dearborn Street   ^
         Chicago, Illinois  60604

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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.
                   U,'S. Environmental Protection Agenc?

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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
                                                                        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 South Dakota .  .  .'	    12
Appendix B.  Summary of Phytoplankton Data 	    17

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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
31 lakes sampled in the State of South Dakota  (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.
STORET No.
4601
4602
4603
4604
4605
4606
4607
4608
4609
4610
4611
4612
(Continued)
LAKES SAMPLED IN THE STATE
Lake Name
Lake Albert
Alvin Lake
Angostura Reservoir
Brant Lake
Lake Bryon
Clear Lake
Clear Lake
Cochrane
Cottonwood Lake
Deerfield Reservoir
Enemy Swim Lake
Lake Herman

OF SOUTH DAKOTA
County
Kingsbury, Ham! in
Lincoln
Fall River
Lake
Beadle
Marshall
Minnehaha
Deuel
Spink
Pennington
Day
Lake


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TABLE 1.  LAKES SAMPLED IN THE STATE OF SOUTH DAKOTA (Continued)
STORET No.
4613
4614
4615
4616
4617
4618
4619
4620
4621
4622
4623
4624
4625
4626
4627
4628
4629
4630
4631
Lake Name
John Lake
Lake Kampeska
Madison Lake
Lake Mitchell
Lake Norden
Oakwood Lake East
Oakwood Lake West
Pactola Reservoir
Pickerel Lake
Lake Poinsett
Lake Red Iron South
Richmond Lake
Roy Lake
Sand Lake
Sheridan Lake
Stockade Lake
East Vermill ion Lake
Wall Lake
Waubay Lake North
County
Ham! in
Codington
Lake
Davison
Haml i n
Brookings
Brookings
Pennington
Day
Haml in, Brookings
Marshall
Brown
Marshall
Brown
Pennington
Custer
McCook
Minnehaha
Day

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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-Lugo!'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 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 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 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-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)

                      Calculation
Index
Ollgotrophic     Eutrophic
Myxophycean


Chlorophycean


Di atom


Euglenophyte


Compound
                      Myxophyceae
                       Desmideae

                      Chlorococcales
                        Desmideae

                      Centric Diatoms
                      Pennate Diatoms

                       Euglenophyta
                Myxophyceae + Chi orococcales

                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 jenneri
Chlorella vulcjaris
Cyclotella meneghiniana
Euglena gracilis
Euglena viridis
Gomphonema parvulum
Melosira varians
Navicula cryptocephala
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.

     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  Brill ouin  (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  -  -2 Pj logx PI
 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 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.

                                      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:
               MinH  =  -
S-l
~TT
                                        N - (S-l)
                                           N
log.
given by Zand (1976).  The total diversity (D)  was calculated from HN (Pielou
1966).  Also given in Appendix B are L (the mean number of individuals per
taxa per milliliter) and K (the number of individuals per milliliter of the
most abundant taxon in the sample).

      The evenness component of diversity (J) was estimated from H/MaxH
(Pielou 1966).  Relative evenness (RJ) was calculated from the formula:
                              RJ  =
            H-MinH
           MaxH-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 !•  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 SOUTH DAKOTA
                        12

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Aohnanthes inflata
Aatinastrum graoilimum
Aatinastrum hantzsohia
Amphora ovalis
   v. affinis
Andbaena oiroinalis
Andbaena flos-aquae
Andbaena osoillarioides
Andbaena planotonioa
Andbaena subaylindrioa
Andbaenopsis oiroularis
Andbaenopsis elenkinii
Andbaenopsis raoiborskii
Andbaenopsis seriata
Anki strode sinus faloatus
Ankistrodesmus faloatus
   v. aoioularis
Ankistrodesmus faleatus
   v. mirabilis
Aphanizomenon flos-aquae
Aphanizomenon graoile
Aphanooapsa deliaatissima
Aphanooapsa elaohista
Aphanooapsa elaohista
   v. oonferta
Aphanooapsa elaohista
   v. planotonioa
Aphanotheoe nidulans
Aphanotheoe nidulans
   v. endophytioa
Aphanothece pulverulenta ?
Arthrospira jenneri
Asterionella formosa
Asterionella formosa
   v. graoillima
Binuolearia sp.
Botryooooous branuii
Caloneis ? lewisii
Caloneis amphisbaena
Carteria sp.
Ceratiim hirundinella
Ceratium hirundinella
   f. austriaawn
Ceratiim hirundinella
   f. braohyoeras
Ceratium hirundinella
   f. furooides
Ceratiim hirundinella
   f. soottiown
Chaetooeros elmorei
Charaoiwn sp.
Chlamydomonas globosa
Chroooocous dispersus
Chroooocous lirmetious
Chroomonas aouta
Chroomonas reflexa
Closteriopsis sp.
Closteriwn sp.
Cooooneis plaoentula
Cooooneis plaoentula
   v. lineata
Coelastrum oambrioum
Coelastnm oambrioum
   v. intermedium
Coelastnm mioroporwn
Coelastrum retioulatum
Coelosphaerium kuetzingianum
Coelosphaerium naegelianum
Coelosphaerium pallidum
Cosoinodisous rothii
   v. sub salsa
Cosmarium olepsydra
   v. nanum
Cruaigenia apioulata
Cruoigenia quadrata
Crueigenia reotangularis
Cruoigenia tetrapedia
Cryptomonas erosa
Cryptomonas erosa
   v. reflexa
Cryptomonas marssonii
Cryptomonas ovata
Cryptomonas reflexa
Cyolotella meneghiniana
Cyolotella miohiganiana
Cymatopleura elliptioa
Cymatopleura solea
Cymatopleura solea
   v. regula
Cymbella oymbiformis
Cymbella mexioana
Cymbella minuta
Cymbella minuta
   v. pseudograoi Us
Cymbella triangulum
Cymbella ventrioosa
Daotyloooooopsis irregularis
Diohotomocooous sp.
Diotyosphaeriwn pulohellum
Dinobryon divergens
                                     13

-------
Dinobryon pediforme
Dinobinjon sertularia
Dinobpyon sertutoria
   v. protuberans
Dinobryon soeiale
Diplopsatis acuta
Elakatothrix gelatinosa
Entomoneis alata
Entomoneis ovnata
Entomone-is paludosa
Epithemia sorex
Epithemia turgida
Eudorina elegans
Euglena aaus
Euglena charkowiensis ?
Euglena ehrenbergii
Euglena gracilis
Euglena osryuris
Euglena oxyuris
   v. minor
Euglena tT-iptez>is
Eunotia valida
Fragilaria biaapitata
Fragilaria brevistriata
   v. inflata
Fvagilaria aapuoina
Fragilaria oapucina
   v. mesolepta
Fragilaria constvuens
Fragilaria crotonensis
Franceia ovalis
Franeeia tuberoulata
Glenodinium gymnodinium
Glenodinium gyrnnodinium
   v. biscutellifoTme
Glenodinium ooulatum
Gloeooapsa aeruginosa
Gloeooystis sp.
Gloeoticidhia edhinulata
Gomphonema angustatwn
Gomphonema olivaoeum
Gomphonema parvulum
Gomphosphaeria aponina
Gonium sp.
Gyrmodinium albulum
Gymnodinium ovdinatum
Gyrosigma wovmleyi
Hantzsohia amphioxys'
Kirahneriella aontorta
K-ivahneriella lunaris
K-ivchneviella lunaris
   v.
Kirehneriella subsolitaria
Lagerheim-ia wratislaviensis
Lepocinolis fusiformis
Lyngbya birgei
Lyngbya oontorta
Lyngbya lagevheim-ii
Lyngbya subtilis
Mallomonas aoaroides
Melosira distans
Melosira gvanulata
Melosira granulata
   v. angustissima
Melosira italioa
Melosira varians
Merismopedia glauoa
Merismopedia minima
Merismopedia tenuissima
Mesostigma viridis
Micraotinium pusillum
MioTcooystis aeruginosa
Mievooystis incevta
Mierooystis marginata
Mougeotia sp .
Navicula oapitata
Navieula auspidata
Navicula gastmm
Navieula pupula
   v. elliptiaa
Naviaula pygmaea
Naviaula veirihardtii
Neidium sp.
Nitssohia aoiaularis
Nitzsehia amphibia
Nitzsohia commutata
Nitzsehia dissipata
Nitzsehia holsatiea
Nitzsehia hungariea  ?
Nitzsehia longissima
   v . reversa
Nitzsehia palea
Nitzsehia sigmoidea
Nitzsehia tryblionella
Nitzsehia vermieularis
Nodularia sp.
Nostoe sp.
Ooeystis borgei
Ooeystis eitriformis
Oseillatoria agardhii
                                     14

-------
OsoillatoTia angustiss-ima
OsoillatoTia limnetioa
Paradox-la multiseta
PediastTum boTyanum
PediastTum duplex
PediastTum duplex
   v. olathratum
Pediastrum duplex
   v. Tetiaulatum
PediastTum kawTaiskyi
PediastTum simplex
PediastTum simplex
   v. duodenarium
PediastTum tetTas
   v. tetTaodon
PeTidinium boTgei
PeTidinium cinctum
Peridin-iwn unibonatum
Peridin-iwn wi-lle-i
Phaaus astarrinatus
Phaeus acuminatus
   v. drezepolskii
Phaous aaudatus
Phaous helikoides
Phaous longicauda
Phaaus megalops-Ls
Phasus pleuroneetes
Phaeus pseudonordstedtii
Phaous tortus
Phormidium mueioola
Pinnularia miorostauron
Pleurosigma delioatulum
Pteromonas angulosa
Raphidiopsis curvata
Rhoioosphen-ia aurvata
Rhopalodia gibba
Soenedesmus abundans
Scenedesrms aouminatus
Soenedesmus areuatus
Saenedesmus arauatus
   v. capitatus
Soenedesmus arauatus
   v. platydisoa
Soenedesmus balatonious
Soenedesmus bemardii
Soenedesmus bioaudatus
Soenedesmus bijuga
Soenedesmus bijuga
   v. alternans
Soenedesmus bijuga
   v. flexuosus
Soenedesmus dimorphus
Soenedesmus intevmedius
Soenedesmus intexmedius
   v. balatonious
Soenedesmus inteicmedius
   v. bioaudatus
Soenedesmus opoliensis
Soenedesmus protuberans
Soenedesmus quadriaauda
Soenedesmus quadrioauda
   v. parvus
Soenedesmus racibovskii
   f. granulatus
Sohroederia judayi
Sohroederia setigera
Selenastrum sp.
Skeletonema po tamos
Spermatozoopsis exultans
Sphaevooystis sohroeteri
Spirogyra sp.
Spirulina sp.
Staurastrum astTaea
   v. minutula
Staurastrum tetracerum
Stawoneis anoeps
Stauroneis anoeps
   v . graoi Us
Stauroneis salina
Stephanodisous astTaea
Stephanodisous astTaea
   v. minutula
Stephanodisous niagarae
Stipitooooous sp.
SuTirella angusta
SuTiTella bTightuellii ?
SuTiTella linearis
SuTiTella ovata
          pesons
SuTiTella spiTalis
SynedTa aous
Synedra oyolopum
Synedra oyolopum
   v. Tobustum
Synedra delioatissima
   v. angustissima
SynedTa Tumpens
Synedra ulna
Synura uvella
Tabellaria fenestTata
TetTaedron oonstTiotum
TetTaedron gTaoile ?
                                     15

-------
Tetraedron hastatwn ?                     Tetraedron victoriae
Tetraedron limnetiawn                     Tetrastrwn elegans
Tetraedron minimum                        Tetrastrwn glabrum
Tetraedron minimum                        Tetrastnon heteraoanthum
   v. sorobiaulatum                       Tetrastrwn staurogeniaeforme
Tetraedron mutiown                        Traehelomonas intermedia
Tetraedron planotonieum                   Traehelomonas volvooina
Tetraedron trigonum                       Treubaria setigerum
Tetraedron trigomon                       Treubaria triappendioulata
   v. graoile                             Ulothrix ? sp.
Tetraedron trigonum
   v. papilliferum
                                     16

-------
                 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 PI, 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.
                                   17

-------
LAKE NA.1t:  LAKE AlbEhT
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                                         DIAIOM     C.'.'i I     0.75 fc     0.5'j fc
                                       COMPOUND     27.C t     8.33 t     1C.0 E
    PALMER'S ORGANIC  POLLUTION

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                                       18

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lAKt NA1E:  BRANT LAKE
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