United Suites Environmental Proln linn Agency Environmental Monitoring Systems Laboratory PO Box 15027 Las Vegas NV 89114 i-h ;md Development EPA Distribution of Phytoplankton in Missouri Lakes Working Paper 698 ------- DISTRIBUTION OF PHYTOPLANKTON IN MISSOURI LAKES by M. K. Morris*, W. D. Taylor, L. R. Williams, S. C. Hern, V. W. Lambou, and F. A. Morris* Water and Land Quality Branch Monitoring Operations Division Environmental Monitoring and Support Laboratory Las Vegas, Nevada 89114 *Department of Biological Sciences University of Nevada, Las Vegas Las Vegas, Nevada 89154 WORKING PAPER NO. 698 NATIONAL EUTROPHICATION SURVEY OFFICE OF RESEARCH AND DEVELOPMENT U.S. ENVIRONMENTAL PROTECTION AGENCY November 1978 ------- 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 ------- 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 ------- CONTENTS Page Foreword iii Introduction . . 1 Materials and Methods . 2 Lake and Site Selection . 2 Sample Preparation . 2 Examination 3 Quality Control 4 Results . 5 Nygaard’s Trophic State Indices . 5 Palmer’s Organic Pollution Indices . 5 Species Diversity and Abundance Indices . 7 Species Occurrence and Abundance . 9 Literature Cited . 10 Appendix A. Phytoplankton Species list for the State of Missouri 11 Appendix B. Summary of Phytoplankton Data 14 V ------- INTRODUCTION The collection and analysis of phytoplankton data were included in the National Eutrophication Survey in an effort to determine relationships between algal characteristics and trophic status of individual lakes. During spring, summer, and fall of 1974, the Survey sampled 179 lakes in 10 States. Over 700 algal species and varieties were identified and enumerated from the 573 water samples examined. This report presents the species and abundance of phytoplankton in the 6 lakes sampled in the State of Missouri (Table 1). The Nygaard’s Trophic State (Nygaard 1949), Palmer’s Organic Pollution (Palmer 1969), and species diversity and abundance indices are also included. TABLE 1 . LAKES SAMPLED IN THE STATE OF MISSOURI STORET No. Lake Name County 2901 Clearwater Lake Reynolds 2902 Pomme de Terre Reservoir Polk, Hickory 2903 Stockton Reservoir Dade, Polk, Cedar 2904 Lake Taneycomo Taney 2905 Thomas Hill Reservoir Macon, Randolph 2906 Wappepello Reservoir Wayne, Butler 1 ------- MATERIALS AND METHODS LAKE AND SITE SELECTION Lakes and reservoirs included in the Survey were selected through discussions with State water pollution agency personnel and U.S. Environmental Protection Agency Regional Offices (U.S. Environmental Protection Agency 1975). Screening and selection strongly emphasized lakes with actual or potential accelerated eutrophication problems. As a result, the selection was limited to lakes: (1) impacted by one or more municipal sewage treatment plant outfalls either directly into the lake or by discharge to an inlet tributary within approximately 40 kilometers of the lake; (2) 40 hectares or larger in size; and (3) with a mean hydraulic retention time of at least 30 days. Specific selection criteria were waived for some lakes of particular State interest. Sampling sites for a lake were selected based on available information on lake morphornetry, potential major sources of nutrient input, and on—site judgment of the field limnologist (U.S. Environmental Protection Agency 1975). Primary sampling sites were chosen to reflect the deepest portion of each major basin in a test lake. Where many basins were present, selection was guided by nutrient source information on hand. At each sampling site, a depth-integrated phytoplankton sample was taken. Depth-integrated samples were uniform mixtures of water from the surface to a depth of 15 feet (4.6 meters) or from the surface to the lower limit of the photic zone representing 1 percent of the incident light, whichever was greater. If the depth at the sampling site was less than 15 feet (4.6 meters), the sample was taken from just off the bottom to the surface. Normally, a lake was sampled three times in 1 year, providing information on spring, summer, and fall conditions. SAMPLE PREPARATION To preserve the sample 4 milliliters (ml) of Acid-Lugol’s solution (Prescott 1970) were added to each 130-mi sample from each site at the time of collection. The samples were shipped to the Environmental Monitoring and Support Laboratory, Las Vegas, Nevada, where equal volumes from each site 2 ------- were mixed to form two 130-mi composite samples for a given lake. One composite sample was put into storage and the other was used for the examination. Prior to examination, the composite samples were concentrated by the settling method. Solids were allowed to settle for at least 24 hours prior to siphoning off the supernate. The volume of the removed supernate and the volume of the remaining concentrate were measured and concentrations determined. A small (8-’.ml) library subsample of the concentrate was then taken. The remaining concentrate was gently agitated to resuspend the plankton and poured into a capped, graduated test tube. If a preliminary examination of a sample indicated the need for a more concentrated sample, the contents of the test tube were further concentrated by repeating the settling method. Final concentrations varied from 15 to 40 times the original Permanent slides were prepared from concentrated samples after analysis was complete. A ring of clear Karoe corn syrup with phenol (a few crystals of phenol were added to each 100 ml of syrup) was placed on a glass slide. A drop of superconcentrate from the bottom of the test tube was placed in the ring. This solution was thoroughly mixed and topped with a coverglass. After the syrup at the edges of the coverglass had hardened, the excess was scraped away and the mount was sealed with clear fingernail polish. Permanent diatom slides were prepared by drying sample material on a coverglass, heating in a muffle furnace at 400° C for 45 minutes, and mounting in Hyrax®. Finally, the mounts were sealed with clear fingernail polish. Backup samples, library samples, permanent sample slides, and Hyrax mounted diatom slides are being stored and maintained at the Environmental Monitoring and Support Laboratory—Las Vegas. EXAMINAT ION The phytoplankton samples were examined with the aid of binocular compound microscopes. A preliminary examination was performed to precisely identify and list all forms encountered. The length of this examination varied depending on the complexity of the sample. An attempt was made to find and identify all of the forms present in each sample. Often forms were observed which could not be identified to species or to genus. Abbreviated descriptions were used to keep a record of these forms (e.g., lunate cell, blue-green filament, Navicula #1). Diatom slides were examined using a standard light microscope. If greater resolution was essential to accurately identify the diatoms, a phase-contrast microscope was used. After the species list was compiled, phytoplankton were enumer ated using a Neubauer Counting Chamber with a 40X objective lens and a lox ocular lens. All forms within each field were counted. The count was continued until a minimum of 100 fields had been viewed, or until the dominant form had been observed a minimum of 100 times. Regi stered trademark 3 ------- QUALITY CONTROL Project phycologists performed internal quality control intercoinparisons regularly on 7 percent of the species identifications and counts. Although an individual had primary responsibility for analyzing a sample, taxonomic problems were discussed among the phycologists. Additional quality control checks were performed on the Survey samples by Dr. G. W. Prescott of the University of Montana at the rate of 5 percent. Quality control checks were made on 75 percent of these samples to verify species identifications while checks were made on the remaining 25 percent of the samples to verify genus counts. Presently, the agreement between quality control checks for species identification and genus enumerations is sati sfactory. 4 ------- RESULTS A phytoplankton species list forihe State is presented in Appendix A. Appendix B summarizes all of the phytoplankton data collected from the State by the Survey. The latter is organized by lake, and includes an alphabetical phytoplankton species list with concentrations for individual species given by sampling date. Results from the application of several indices are presented (Nygaard’s Trophic State, Palmer’s Organic Pollution, and species diversity and abundance). Each lake has been assigned a four—digit STORET number. (STORET (STOrage and RETrieval) is the U.S. Environmental Protection Agency’s computer system which processes and maintains water quality data.) The first two digits of the STORET number identify the State; the last two digits identify the lake. NYGAARD’S TROPHIC STATE INDICES Five indices devised by Nygaard (1949) were proposed under the assumption that certain algal groups are indicative of levels of nutrient enrichment. These indices were calculated in order to aid in determining the surveyed lakes’ trophic status. As a general rule, Cyanophyta, Euglenophyta, centric diatoms, and members of the Chiorococcales are found in waters that are eutrophic (rich in nutrients), while desmids and many pennate diatoms generally cannot tolerate high nutrient levels and so are found in oligotrophic waters (poor in nutrients). In applying the indices to the Survey data, the number of taxa in each major group was determined from the species list for each sample. The ratios of these groups give numerical values which can be used as a biological index of water richness. The five indices and the ranges of values established for Danish lakes by Nygaard for each trophic state are presented in Table 2. The appropriate symbol, (E) eutrophic and (0) oligotrophic, follows each calculated value in the tables in Appendix B. A question mark ( ) following a calculated value in these tables was entered when that value was within the range of both classifications. PALMER’S ORGANIC POLLUTION INDICES Palmer (1969) analyzed reports from 165 authors and developed algal pollution indices for use in rating water samples with high organic pollution. Two lists of organic pol1ution_to1erant forms were prepared, one containing 20 genera, the other, 20 species (Tables 3 and 4). Each form was assigned a pollution index number ranging from 1 for moderately tolerant forms to 6 for 5 ------- TABLE 2. NYGAARD’S TROPHIC STATE INDICES ADAPTED FROM HUTCHINSON (1967) Index Calculation Oligotrophic Eutrophic Myxophycean Myxophyceae 0.0-0.4 0.1-3.0 Desmideae Chiorophycean Chiorococcales 0.0-0.7 0.2-9.0 De smideae Diatom Centric Diatoms 0.0—0.3 0.0—1.75 Pennate Diatoms Euglenophyte Euglenophyta 0.0-0.2 0.0—1.0 Myxophyceae + Chlorococcales Compound Myxophyceae + Chiorococcales + Centric Diatoms + Euglenophyta 0.0-1.0 1.2-25 Desmideae TABLE 3. ALGAL GENUS POLLUTION INDEX TABLE 4. ALGAL SPECIES POLLUTION (Palmer 1969) INDEX (Palmer 1969) Genus Pollution Index Anacystis 1 Ankistrodesmus 2 4 3 Chiamydomonas Chiorella Closterium 1 Cyclotella 1 Euglena 5 Gomphonema 1 Lepocinclis 1 1 Melosira Micractinium 1 3 Navicula Nitzschia 3 Oscillatoria 5 1 Pandorina Phacus 2 Phormidium 1 Scenedesmus Stigeoclonium 4 2 2 Synedra Species Pollution Index Ankistrodesmus falcatus 3 2 2 Arthrospira ,jenneri Chlorella vulgaris Cyclotella meneghiniana 2 1 Euglena gracilis Euglena viridis 6 Gomphonema parvulum 1 Melosira varians 2 Navicula cryptocephala 1 1 5 Nitzschia acicularis Nitzschia palea Oscillatoria chlorina Oscillatoria limosa Oscillatoria princeps U?Eillatoria putrida Oscillatoria tenuis Pandorina morum 2 4 1 1 4 3 Scenedesmus guadricauda 4 3 3 Stigeoclonium tenue Synedraulna 6 ------- extremely tolerant foms. Palmer based the index numbers on occurrence records and/or where emphasized by the authors as being especially tolerant of organic pollution. In analyzing a water sample, any of the 20 genera or species of algae present in concentrations of 50 per milliliter or more are recorded. The pollution index numbers of the algae present are totaled, providing a genus score and a species score. Palmer determined that a score of 20 or more for either index can be taken as evidence of high organic pollution, while a score of 15 to 19 is taken as probable evidence of high organic pollution. Lower figures suggest that the organic pollution of the sample is not high, that the sample is not representative, or that some substance or factor interfering with algal persistence is present and active. SPECIES DIVERSITY AND ABUNDANCE INDICES “Information content” of biological samples is being used commonly by biologists as a measure of diversity. Diversity in this connection means the degree of uncertainty attached to the specific identity of any randomly selected individual. The greater the number of taxa and the more equal their proportions, the greater the uncertainty, and hence, the diversity (Pielou 1966). There are several methods of measuring diversity, e.g., the formulas given by Brillouin (1962) and Shannon and Weaver (1963). The method which is appropriate depends on the type of biological sample on hand. Pielou (1966) classifies the types of biological samples and gives the measure of diversity appropriate for each type. The Survey phytoplankton samples are what she classifies as larger samples (collections in Pielou’s terminology) from which random subsamples can be drawn. According to Pielou, the average diversity per individual (H) for these types of samples can be estimated from the Shannon-Wiener formula (Shannon and Weaver 1963): S H = — P. log, i=1 where P is the proportion of the ith taxon in the sample, which is calculated from ni/N; ni is the number of individuals per milliliter of the ith taxon; N is the total number of individuals per ml; and S is the total number of taxa. However, Basharin (1959) and Pielou (1966) have pointed out that H calculated from the subsample is a biased estimator of the sample H, and if this bias is to be accounted for, we must know the total number of taxa present in the sample since the magnitude of this bias depends on it. Pielou (1966) suggests that if the number of taxa in the subsample falls only slightly short of the number in the larger sample, no appreciable error will result in considering S. estimated from the subsample, as being equal to the sample value. Even though considerable effort was made to find and identify all taxa, the Survey samples undoubtedly contain a fair number of rare phytoplankton taxa which were not encountered. 7 ------- In the Shannon-Wiener formula, an increase in the number of taxa and/or an increase in the evenness of the distribution of individuals among taxa will increase the average diversity per individual from its minimal value of zero. Sager and Hasler (1969) found that the richness of taxa was of minor importance in determination of average diversity per individual for phytoplankton and they concluded that phytoplankton taxa in excess of the 10 to 15 most abundant ones have little effect on H. This was verified by our own calculations. Our counts are in number per milliliter and since logarithms to the base 2 were used in our calculations, H is expressed in units of bits per individual. When individuals of a taxon were so rare that they re not counted, a value of 1/130 per milliliter or 0.008 per milliliter was used in the calculations since at least one individual of the taxon must have been present in the collection. A Survey sample for a given lake represents a composite of all phytoplankton collected at different sampling sites on the lake during a given sampling period. Since the number of samples (M) making up a composite is a function of both the complexity of the lake sampled and its size, it should affect the richness-of-taxa component of the diversity of our phytoplankton collections. The maximum diversity (MaxH) (i.e., when the individuals are distributed among the taxa as evenly as possible was estimated from 1092 S (Pielou 1966), while the minimum diversity (M1nH , was estimated from the formula: = - • ! log . - [ N N ] log 2 [ N N ] given by Land (1976). The total diversity (D) was calculated from HN (Pielou 1966). Also given in Appendix B are L (the mean number of individuals per taxa per milliliter) and K (the number of individuals per milliliter of the most abundant taxon in the sample). The evenness component of diversity (J) was estimated from H/MaxH (Pielou 1966). Relative evenness (RJ) was calculated from the formula: RJ H-MinH Max H-Mi nH given by Zand (1976). Land suggests that RJ be used as a substitute for both J and the redundancy expression given by Wilhm and Dorris (1968). As pointed out by Zand, the redundancy expression given by Wilhm and Dorris does not properly express what it is intended to show, i.e., the position of H in the range between MaxH and MinH. RJ may range from 0 to 1; being 1 for the most even samples and 0 for the least even samples. Zand (1976) suggests that diversity indices be expressed in units of “sits”, i.e., in logarithms to base S (where S is the total number of taxa in the sample) instead of in “bits”, i.e., in logarithms to base 2. Zand points out that the diversity index in sits per individual is a normalized number ranging from 1 for the most evenly distributed samples to 0 for the least evenly distributed samples. Also, it can be used to compare different samples, independent of the number of taxa in each. The diversity in bits per 8 ------- individual should not be used in direct comparisons involving various samples which have different numbers of taxa. Since MaxH equals log S, the expression in sits is equal to logs S, or 1. Therefore diversity in sits per individual is numerically equivalent to J, the evenness component for the Shannon—Wiener fomula. SPECIES OCCURRENCE AND ABUNDANCE The alphabetic phytoplankton species list for each lake, presented in Appendix B, gives the concentrations of individual species by sampling date. Concentrations are in cells, colonies, or filaments (CEL, COL, FIL) per milliliter. An “X” after a species name indicates that the species identified in the preliminary examination was in such a low concentration that it did not appear in the count. A blank space indicates that the organism was not found in the sample collected on that date. Column S is used to designate the examiner’s subjective opinion of the five dominant taxa in a sample, based upon relative size and concentration of the organism. The percent column (SC) presents, by abundance, the percentage composition of each taxon. 9 ------- LITERATURE CITED Basharin, G. P. 1959. On a statistical estimate for the entropy of a sequence of independent random variables, pp. 333—336. In: Theory of Probability and Its Applications (translation of “Teoriya Veroyatnosei I ee Premeneniya”). N. Artin (ed). 4. Society for Industrial and Applied Mathematics, Philadelphia. Brillouin, L. 1962. Science and Information Theory (2nd ed.). Academic Press, New York. 351 pp. Hutchinson, G. E. 1967. A Treatise on Limnology. II. Introduction to Lake Biology and the Limnoplankton. John Wiley and Sons, Inc., New York. 1,115 pp. Nygaard, G. 1949. Hydrobiological studies of some Danish ponds and lakes. II. (K danske Vidensk. Seisk.) Biol. Sci. 7:293. Palmer, C. M. 1969. A composite rating of algae tolerating organic pollution. J. Phycol. 5:78—82. Pielou, E. C. 1966. The measurement of diversity in different types of biological collections. J. Theor. Biol. 13:131—144. Prescott, G. W. 1970. How to Know the Freshwater Algae. William C. Brown Company, Dubuque. 348 pp. Sager, P. E., and A. D. Hasler. 1969. Species diversity in lacustrine phytoplankton. I. The components of the index of diversity from Shannon’s formula. Pmer. Natur. 103(929):5]—59. Shannon, C. E., and W. Weaver. 1963. The Mathematical Theory of Commu- nication. University of Illinois Press, Urbana. 117 pp. U.S. Environmental Protection Agency. 1975. National Eutrophication Survey Methods 1973—1976. Working Paper No. 175. Environmental Monitoring and Support Laboratory, Las Vegas, Nevada, and Corvallis Environmental Research Laboratory, Corvallis, Oregon. 91 pp. Wilhm, V. L., and T. C. Dorris. 1968. Biological parameters for water quality criteria. Bio—Science. 18:477. Zand, S. M. 1976. Indexes associated with information theory in water quality. J. Water Pollut. Contr. Fed. 48(8):2026—2031. 10 ------- APPENDIX A PHYTOPLANKTON SPECIES FOR THE STATE OF MISSOURI 11 ------- Achnanthes microcephala Euastrwn denticulatwn Actinaetrwfl gracililfllAlfl uglena acue Anahasna SP. Euglena ehrenbergii Ankistrode8mus falcatus Eugl.ena g-rczci lie AnksitrodesmU8 falcatue Euglena O yurV8 v. aciculai’i-s v. minor AnkistrodeeflTu8 falcatus Eug Lena subehrenbergii v. r,rLrabilis Euglena triptez e Aphanizorne non floe-aquas Rragi Lana crotonensia Aphanothece sp. Franceia sp. AstenionelZ42 formosa Glenodiniuin a culifeDWfl Aaterzonella formosa Glenodinium gymnodiniurn v. gracillima GZ.enodiniwn gymnodiniuzn Cartenia sp. v. biscutel.liforme Ceratiwn hirundinella GlenodiniziJn ocuZa n f. brachyceras Glenodiniwn penardiforme Ceratiwn hirundineUa Gornphonema olivacewn f. furcoidee Gomphosphasnia C zloJnydcn7ona8 Sp. Gymnodiniu)fl albuiwn Chiorogonvuin SP. Gyrosigma sp. Chroon7Onas acuta Han tzschia csnphioxys Ciosteriwn sp. Kirchner iella lunaris Cocconeis SP. Eagerheimia chodati ? Coelastrum c ’nbricwn Lagerheimia quadniseta ? Coelastrum microporwfl Lepocinolis sp. Coelastrwn reticuiatwn Lynghya sp. Coelastrum reticulatwn Malloinonas sp. v. polychordon Meloaira dietans Coelaatrwn sphaer .cwn Melosira granulata CoeLosphaerw n pallidwn Melosira granulata Cosmaniwl? clepsydra v. an etiesima v. nwzwn Melosira vai’ms Crucigenia apiculata Meridion circuiare cruciqenia quadrata Merismopedia glauca crucigenia tetrapedia Meriamopedia minima Cryptomoflas eroca Merismopedia punctata CryptoinoflaS erosa Menamopedia tenuissima v. refle. a Meso8tvgma viridia Crijptomofla s refiexa Mi cractini urn ? sp. Cyclotelia meneghini via Microcy8tie aerugiflOsa Cyc lote 1 La ate 1 ligera Microcyatis incerta Cyn7atopleura so lea Mougeoti.a sp. Cymbella cymbiformia zVavicula saZ.inarum Cymbella turgigula Nitzschia acicuZaria Dacty L.ococcopeie sp. Ni tzachia fi liformis Diatorna vulgare Nitzechia tryblionella Dictyo8phaervwfl pulchellw77 v. debilis Dinobryon bavaricum Qocystis sp. Dinobryon divergene Oscillatoria liznnetica Dinobryon sociale Pandonna mcrwn 12 ------- Pediastrwn biradiatwn Pedias trwn biradiaturn v. longecornutwfl Pediastrwn duplex v. reticule ttwn Pedia.strum simplex Pediastrwn simplex v. duoden ’iwn Pediastrwfl tetrczs v. tetraodon Peridiniwn aciculiferwn ? Peridini urn inconspicuun Peridiniwn quadridens Phacus acwninatus Thacus caudatus Phacus curvicauda Phacue longicauda Phacue megalopsis Raphidiopais cur vata Scenedesnnss abundans Scenedesmus aCWlTflatUB Scenedesinus arcuatus Scenedesmus bicaudatus Scenede8rnue bijuga Scenedesraus denDicu Zatus Scenedesmus denticu latus v. lineci’is Scenedewnue dirnorphus Scenedesmus intermedius Scenedeslnu8 intez’,nedius v. bicaudatas ScenedesflTuB quadi’icazi’ Scenedesmus quadricaud.a v. quadrspna Schroederia setigera Ske letonerna pota’nos Sphaerocystis schroeteri Staurastrwn sp. Ste phanodiscua astraea V. fl?iflUtZa 2 Ste phonodiscus niagarae Surirella cznguata Syne4ra acus S ,’nedra capitata Synedra de licatis8ufla Synedra delicati8sima v. angustiesma Synedra ulna Te traedron cons trictw’n Te traedron graci le Te traedron limneticum Tetraedron mininnan Tetraedron nth2irnwn v. scrobicuiatwn Tetraedron rnuticwn Tetraedron trigonwn v. grac’ile Tetraedron trigonwn v. papilliferwn Tetrastrwn staurogeniaefoz ne T’rache 7,ornonaa fiuviati lie 2”rachelornonas hispida Trache lonionas interrnedia Trache lomonas jacuiata Trache lomonas ye ivocina Treubaria setigerwn Treu.baria triappendicUlat4 13 ------- APPENDIX B. SUMMARY OF PHYTOPLANKTON DATA This appendix was generated by computer. Because it was only possible to use upper case letters in the printout, all scientific names are printed in upper case and are not italicized. The alphabetic phytoplankton lists include taxa without species names (e.g., EUNOTIA, EUNOTIA #1, FLAGELLATE, FLAGELLATES, MICROCYSTIS INCERTA ‘, CHLOROPHYTAN COCCOID CELLED COLONY). When species determinations were not possible, symbols or descriptive phrases were used to separate taxa for enumeration purposes. Each name on a list, however, represents a unique species different from any other name on the same list, unless otherwise noted, for counting purposes. Numbers were used to separate unidentified species of the same genus. A generic name listed alone is also a unique species. A question mark ( ) is placed immediately after the portion of a name which was assigned with uncertainty. Numbered, questioned, or otherwise designated taxa were established on a lake—by-lake basis; therefore NAVICULA #2 from lake A cannot be compared to NAVICULA #2 from lake B. Pluralized categories (e.g., FLAGELLATES, CENTRIC DIATOMS, SPP.) were used for counting purposes when taxa could not be properly differentiated on the counting chamber. 14 ------- LAKE N IIE CLEAR A1ER LAKE STORE1 tw BEk; 2901 NVGAARO IROPHIC STAlE inDICES DATE C q 1 ’. 06 18 74 10 C8 74 YXLPHYCEAN 2.30 E 2.60 E 3JtJJ Q CHL0ROPHYCEA S 2. 0 E 7.00 1 ‘..C0 E EUGLENQPHYIE £ 3.56 1 1.75 1 DIATUII 0. 0 E 0.44 E 0.25 ? C0MPOU’ 0 9. 0 E 1b.0 I 12. L PALNER’S ORGANIC POLLUTION INDICES DATE 64 9 74 06 18 74 10 08 74 (,EPiUS 05 C2 31 SPECIES 00 60 00 SPIC1E DIVERSiTY AND ASUNDANCE INDICES DATE 64 C9 74 Gb 18 74 1.) (‘9 7” AVERAGE DIVERSITY H 2.79 2.6” 2.12 HUP 8 R OF TAXA S 20.00 35.C0 NUMBER OF SAMPLES COMPOS1J€0 N 3.00 3.00 3 .)0 NA 1MUN DIVEkSITY PAXII 4.32 .13 PUNUMUM 0 [ VERSITT PIINH 0.21 0.33 0.52 TOTAL DIVE S1TT 0 2843.01 3144.24 1349.40 TOTAL NUMbER OF IP’DIVICUAL INL N 1019.00 1191.00 EVEIEESS C0 PONfNT j C.b S 0.51 0.45 RELATiVE (VEP ’ESS kJ (‘.63 3•49 0.39 EAN NUIIIIEM OF INDIVLDUALSITAXA 50.95 34.03 HUM6ERIML UI MOST ABUNDANI TAXON K 266.00 ‘.26.00 165.00 15 ------- I L II HAIl I (II ARIA Ilk I All $10111 NuIldIlil 2 )1 1 1 o o 7 ala LI I I I LI HA A l l iS i i . U DL S MUS &NAI3II (UIIISIWS la((AIU$ AIIlIStRUU(SI (US I RICA IUS V. LCIC III&1 15 LSILRIIJI IIILA IUMlIj$A CIHIRIC 01111111 CII I ! IUN IIIRIJNUIHIILA I • FURCOIO(S (HLOR(IPHIIAH CUCCOIII (((LID COLONY CIIROOrU 1IAS aCUlA CIUSIINIWI II CIOSIIRIUII ‘2 COCCOIO CILL (flIIASIIUM (&IIBIIICUM C0A(ISIRUH RI IICUILIUI I V. Put YCHOROUM (05 11 11 lUll CR TPIOMUNA S CRYPIOIUIIIS (ROSA CR,PIUIUI,AS 1(11(8* (5(101111* SI*ttI lRA (7118 1(1* (71101(1* CYPIOIPUANIS (TRIBLILI 1UIGIDULA 01 11011* VUILARI DIN OR I V ON (UG IENA IUGLIPI* IRIP1LNIS 1 116 1 1*RIA CRUJUIIINSIS G(I IIIIIiINIUN U(Ut*IUII CI(HUIIHIUN PIHAROIIORIIL GVRUSI IRA I (110(111(1 IS II ILUSIMA 015 1*111 N( ((J SlIIA GIANULASA Il1 (USIR* LLRIANS PIll 101011 CIR(U(ARI rI(RUCYS IIS INCUIIA 110(161 I ii IA NAP ICU I A NI 115(11 18 N$IZ 5ClIIA SI NII2S(NI* 92 HItlSClIlI 93 nbc Ill IS DSC 111* 101 IA PIIJIASIRUM SIMPLER PFUIASIKWi 1(11*5 V. IIIN*UOON P(kIQIN$UIl IN(IIMSPl(UU$ PFIIIDINIUII OUADRIOLNS I’II*CUS CAUOATUS PIILCUS CURVICAUDA PHACUS IIINGICAUPA PHACUS PlIC*&UPSIS SCINIOISITUS BIJUCA S(IN(O(SPIUS DIPIOIPIIUS SCIN(D(SPIU S RUAUMI(AUOI 5711 10 1* 5711 101* II 5711 101* CAPIIAIA STN(UR* I)(IICAIISSIPIR V. 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