IDENTIFYING AND CONTROLLING SOME SOURCES OF ERROR FOR A STATEC ALGAL BIOASSAY WITH APPLICATMNS Thesis for {ha Degree of M. 3. MICHIGAN STATE UNWERSW THOMAS D. FURSYTHE 1973 , o - . . 0 fl ., . J . . .. ' t - o n r . - . . r . . . . ' l- r . - ’ ‘ I , . . - . , .n r , . u . . ., _ , . - u - ' a r . u.' - . -'.__ . ' - ‘ . . , . ~ - o o - ’ - I — ‘al ' I - l . ' 5‘. fl ’9. ll' ' ' ' ‘ ' V. l' ' - . I - 0 u a - ¢ .. ,.. . ..', . ' ‘ O ' . ' F 0 ' v v. -. .. — -r,. . . ., . .. ; , , -, “. ’ . ' . v - -. ‘ l 4-: ...‘.¢. - ' 3.,» f0 . '0 .l l I I ' ' - A ~4-. .- , I'.. a-g. , . , . l"... , , . o- I ,u . 1' .go. . . ,'.,I. ' . .. .. ‘ -. -,.. . l -" o~a-.. ‘- - r - . o. .. u’l 0" , . (" ‘_ '."' ,0 o . r. ~..p. ., . 9 I y'.-¢. . . , .. v .u-.. v .‘4‘ o .. otu a. ., 1 n0\ '.r - 'anl >‘ - - .ur—-f "' . ‘ovv ,a '- .1 vln'tr. ..".-"'.o-r '7' 'lrlvlp-oa-'n."0oc '7’. "'. a v-.. r-¢ol,-u.:p',(',.. . ‘ 'fl" l-.v ", , . ., ; ,..4‘ . . '4’ 1.. _, ...’r 'u, .1 t (r '.D"-".-., up.-. 4- I n I 11" l . ' Il'l.’ . . .- v . . . o . . - c- . . . v. - - n -’ ' .. ..-. . l . . . u..-., v - 1 c . v "Dlr tr—; 1- - ., n . G n I ‘ p ..n . I -»>. - .1 .. a . . . - . ." .. _. .al-v. , .l- , — - ... 1‘ . .. . ..o v. . - n .v 0.0 .- .,,.- -p—.1 , ," " -ou-t'c" r. ,- . . . _. , 1.“. II. v o ,. . . . ... I '0' l . O r u c. l o. r c'. . c r! - QM Univ-fishy {’4‘- “ ‘vv—n‘ w...- gr Mama 1 IIIIMI & SII 8' 300K BINDERI INC. LIBRARY BINDERS glittering}. menu?” A ‘I “$2! IDENTIFYI‘; FOR A S‘ This study 5&7! to conduct atic more wen 1h % The gm“ “1“ ”mm: at “tempt“ t0 met chlol“’I’hyll n1 1% In eI'I'or d ABSTRACT IDENTIFYING AND CONTROLLING SOME SOURCES OF ERROR FOR A STATIC ALGAL BIOASSAY WITH APPLICATIONS By Thomas D. Torsythe This study was for self-training in the methods neces- sary to conduct precise static algal bicassays. Some system- atic errors were identified, investigated, and controlled when.Selenastrum capricornutum cells were cultured using the Algal Assay Procedure: Bottle Test. The growth parameters used to Judge bioassay precision were Maximum.8pecific Growth Rates, Maximum.Standing Crops, and ”Cell Health" determined by cell counts and dry weights. Attempts to measure daily growth by optical density and EEHZEZQ chlorophyll fluorescence on cell suspensions were unsuccessful. The precision in cell counting was improved by eliminat- ing an error due to counting chamber preparation. The distri- bution of cell counts was Poisson and more apparent for low counts. The first attempt at conducting a bicassay of the effects of four low levels of phosphorus on Selenastrum growth gave high Coefficients cf‘Variation (above 13%). The algae responded to the lowest level of 0.01 mg P/l. Light intensity, initial cell concentration, and nutrient medium freshness, when uncontrolled, were found to effect algal growth and result in undue error for bioassays. Methods for insuring carbon availability were tested and yielded less precision in growth parameter determinations than no insurances. The "Cell Health" parameter (dry weight per million cells) showed cells cultured under carbon stress re- sponded by increasing cellular surface to volume ratios as noted from decreases in cell sizes and increases in cell num- bers. A high correlation existed between increasing available carbon and "Cell Health". In applications of the bioassay, three Michigan lake samples (Torch, Deep, and Lansing) were used after membrane filtration to dilute the nutrient stocks for a medium compared to the nutrient stocks diluted with distilled water. The latter treatment gave lower Maximum Specific Growth Rates, lower Maximum Standing Crops in dry weights, poorer "Cell Health", and higher Maximum Standing Crops in cell numbers. The re- sponses were attributed to less carbon stress when lake waters were the diluent due to added carbonate alkalinity. The same three lakes were bioassayed to determine the nutrient limiting algal production. In all three cases phosphorus stimulated algal growth while nitrogen did not. For all six experiments applying the bioassay, the pre- cision for the growth parameters was high according to reported "acceptable" precision levels. IDENTIFYING FOR A 8'33.l Dep IDENTIFYING AND CONTROLLING SOME SOURCES OF ERROR FOR A STATIC ALGAL BIOASSAY WITH APPLICATIONS By Thomas DfJForsythe A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of ‘MASTER.OF SCIENCE Department of Fisheries and Wildlife 1 973 1‘4 'fl 2: ‘ i' I e |'¥*"'“" m 1 I wish to for criticizim Appreciat f” their encc Student. Special 1 see through 4 Study, I am ‘ M “81-13% his my "filings by. My Stud: though a Tr A8621” . (BI Finan: C) ACKNOWLEDGEMENTS I wish to thank my major professor, Dr. Niles R. Kevern for criticizing and evaluating the manuscript. Appreciation is given to my mother and my wife's parents for their encouragement and support during my years as a student. Special thanks is expressed to my wife for her persever- ance through the neglect she received while I conducted this study. I am indebted to my four-year-old son for the liberty of using his room as a study and for his taking to the sofa many evenings when a noisy typewriter was too much to sleep by. My studies as a graduate student were made possible through a Traineeship from the'U.S. Environmental Protection Agency. (EPA Training Grant No. T-900331 ). Finally, I dedicate this thesis to the memory of my father. Much inspiration was gained by reflecting upon the qualities that made him outstanding. 11 momma . ms 03 ALGA]. 1 moms o? A? am 310mm EMS 12w m AIM Ems Experiment 1 Experiment Experiment Experimant Exminim; Experiment ExMultan: hperiment INTRODUCTION TABLE OF CONTENTS TYPES OF ALGAL BIOASSAY. . . . . . . . . . . PRINCIPLES OF ALGAL BIOASSAY . . . . . . . . . ALGAL BIOASSAY PROCEDURES . . . . . . . . . . EXPERIMENTS INVESTIGATING SOME SOURCES OF ERROR IN THE ALGAL BIOASSAY PROCEDURES. . . . . . . . . 1 - Cell counting error e e e e e 0 Experiment Experiment Experiment Experiment Experiment Experiment Experiment Expermment APPLICATIONS Experiment 2- 8- Correlations between cell counting, chlorophyll fluorescence, and optical density measured on Selenp astrum cell suspensions. . . . . Effects of four levels of ortho- phosphate on Selenastrum.growth for familiarizatIon wITE bioassay procedures 0 e e e e e e e 0 Effects of light intensity on Selenastrum growth . . . . . . Effects of three levels of initial cell concentration on Selenastrum growth during a bioassay . . . . Effects of light intensity on Selenp astrum growth (repeat of Exp. 15. . Effects of carbon availability on Selenastrum.growth during a bioassay Effects of culture medium.freshness on Selenastrum growth . . . . . OF ALGAL BIOASSAY . . . . . . . . 9 - Bioassay of Torch Lake for inhibi- tory substances . . . . . . . Experiment 10 - Bioassay of Deep Lake for inhibitory substances 0 e e e e e e e 0 Experiment 11 - Bioassay of Lake Lansing for inhibitory substances . . . . . 111 Page 24 26 32 38 49 56 62 69 85 89 90 100 108 '«1‘ #69 W?! no) Expertent 12 Experiment 1} Experiment 14 ”(If ‘ D Quid-“.1 LY . . . ' mfi|nvv . .‘erl‘fif. CITED 0““ " - wave l'r’ .e."‘d J.‘( A v C . 7"“ on U I ‘ . ., ,v\ A u.‘ “A‘J‘lt Page Experiment 12 - Bioassay of Torch Lake for limit- ing nutrient . . . . . . . . 119 Experiment 13 - Bioassay of Deep Lake for limiting nutrient e e e e e e e e e 1 29 Experiment 14 - Bioassay of Lake Lansing for limit- ing nutrient . . . . . . . . 137 SUMMARY . . . . . . . . . . . . . . . . 147 LITERATURE CITED . . . . . . . . . . . . . 151 APPENDIX A . . . . . . . . . . . . . . . 158 APPENDIX B . . . . . . . . . . . . . . . 160 iv Q ..-'.-n& b\ 2. la It T'tle Synthetic a given as 1‘: liter , . Synthetic a given as fj liter Cell count: Wine tlm Smouc 1; Variance '1 due to C01; and grid c I merical Table 4a. 4b. 5. 7. LIST OF TABLES Synthetic algal nutrient medium macronutrients given as final concentrations in milligrams per liter 0 O O O O O O O O O O O O 0 Synthetic algal nutrient medium micronutrients given as final concentrations in micrograms per liter 0 O O I O O O O O O O C O 0 Cell counts for a Nested Analysis of Variance showing the data are nested . . . . . . . Symbolic Nested Analysis of Variance to study the variance in cell counting by defining the effects due to counting chambers, samples within chambers, and grid cell counts within samples . . . . Numerical Nested Analysis of Variance to study the variance in cell counting by defining the effects due to counting chambers, samples within chambers, and grid cell counts within samples . Nested Analysis of Variance studying the variance in cell counting by defining the effects due to counting chambers, samples within chambers, grid cells within samples. The degrees of freedom were 4, 20, and 225 respectively compared to 4, 5, and 40 from Table 4b . . . . . . . . Nested Analysis of Variance studying the variance in cell counting by defining the effects due to counting chambers, samples within chambers, and cells within samples. The degrees of freedom were 4, 20, and 100 respectively . . . . . Data from cell counts, optical density, and in vivo chlorophyll fluorescence measured on ten dIIEtions of a Selenastrum cell suspension . . Correlations between expected cell counts, observed cell counts, in vivo chlorophyll fluores- cence, and optical denEIty measured on ten dilup tions of a Selenastrum cell suspension . . . Page 12 13 27 28 28 29 31 34 34 fable .._- m - Effects of fox: 0.02, and 0.0}. Specific Grovt. assay . . . Effects of fou 0.02, and 0.03 Specific Growt Effects of ion 0.02, and 0.03 Standing Crops Cell counts of day-old cults;- one of the sev Prepare AAP me est was 1mm Cell counts of day-Old cultur trace element in the stock c Effects of t tion (1.68110: 0n Selena: an elevm averaged and . Effects of t . non (1068X10 g: Selenastnz 1’2'3 reSpect Table 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. Effects of four levels of phosphorus (0. 00, 0. 01, 0. 02, and 0. 03 mg P/l) on Selenastrum daily Specific Growth Rates for a‘ten day static bio- assay e e e e e e e e e e e e e e 0 Effects of four levels of phosphorus (0.00, 0.01, 0.02, and 0.03 mg P/l) on Selenastrum Maximum Specific Growth Rates, witE Cv and f testing . . Effects of four levels of phosphorus (0.00, 0.01, 0. 02, and 0. 03 mg P/l) on Selenastrum Maximum Standing Crops in cells/ml, with Cv and 3 testing. Cell counts of seven aliquot portions of a seven- day-old culture. Each portion was treated with one of the seven nutrient stock solutions used to prepare AAP medium to determine if a stock nutri- ent was limiting growth . . . . . . . . . Cell counts of seven aliquot portions of a ten- day-old culture. Each portion was treated with a trace element solution to determine which element in the stock of TRACES was limiting growth . . . Effects of t ee levels3 of initial ce 1 concentra- tion (1.68x10, 6. 00x103 and 2.10x10 cells per ml) on Selenastrum daily Specific Growth Rates for an eleven day BIoassay with treatment replications averaged and 3 testing on the./‘ax values. The treatments are numbered as 1,2, respectively . . Effects of t ee levels of initia cell concentra- tion (1.68x10 , 6.00x1o3, 2.10x10 cells per ml) on Selenastrum.Maximum Standing Crops in cells per ml wIEH i Eesfing. The treatments are numbered 1, 2 ,3 respectively . . . . . . . . . . . Effects of two levels of light intensity (475 ft-c and 260 ft-c) on Selenastrum daily Specific Growth Rates for an eleven day static bioassay . . . . Effects of two levels of light intensity (475 ft-c and 260 ft-c) on Selenastrum Maximum Specific Growth Rates, witE va wd‘i testing . . . . . Effects of two levels of light intensity (475 ft-c and 260 ft-c) on Selenastrum Maximum Standing Crops, with Cv andpi testIfiE. . . . . . . . vi Page 46 47 47 54 54 60 60 66 67 67 fi 1...... *4 F I .331 10 In K) C) O is e Treatments vented shop to assess 1 carbon avai Effects of above or b: daily Spec: tion avers, Effects of astrum Iiax Wing Effects of astrum Ma: v V V 3. Effects 0‘ mm“: I-Ia: Crogram 38th:}: 91(- CQHB in I teatim &mary ‘ cehts f0. Table 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. Page Treatments of six levels of carbon dioxide vented above or bubbled into Selenastrum cultures to assess the AAP's suggested methods of insuring carbon availability in static bioassays . . . . 70 Effects of six levels of carbon dioxide vented above or bubbled into Selenastrum cultures on daily Specific Growth Rates. Shown are replica- tion average Cv values for the static bioassay. . 78 Effects of six levels of carbon dioxide on Selen- astrum Maximum Specific Growth Rates with C and §,testing . . . . . . . . . . . Y . . 79 Effects of six levels of carbon dioxide on Selen- astrum Maximum Standing Crops as cell numbers, wITE Cv and 3 testing . . . . . . . . . . 79 Effects of six levels of carbon dioxide on Selen- astrum Maximum Standing Crops as dry weight In mIcrograms/ml with Cv and 3 testing . . . . . 80 Effects of six levels of carbon dioxide on Selen- astrum."Cell Health" a dry weight per millIon ceIIs in micrograms/10 cells, with Cv and 2 1398th e e e e e e e e e e e e o e 80 Summary of the Coefficients of Variation as per- cents for Experiment 7. . . . . . . . . . 83 Correlation and confidence levels for comparisons between pH maximums reached during the bioassay (this reflects carbon availability) and the growth parameters determined. . . . . . . . 82 Com arison of fresh AAP medium to aged AAP medium by a) cell counts and (b) dry weights after ten days growth. Also shown are C and percent re- ductions in cell counts and dry weights due to medium freshness. . . . . . . . . . . . 86 Cell counts of Selenastrum cultured in aged medium (fourteenpday-oIdI. On day 10 the culture was divided into seven portions and each treated with one of the AAP nutrient stocks. Cell counts were made after five days of culturing . . . . . . 87 Effects of membrane filtered Torch Lake water as a diluent for AAP nutrients compared to the AAP nutrients diluted with distilled water on Selen- astrum daily Specific Growth Rates for a ten day staTIc bioassay . . . . . . . . . . . . 96 vii . Qnge .88. 300 r: 71: Us 36. \N \J o a U! Effects of me a diluent for MP nutrients Selenastrum y see are C,c Effects of me a diluent for MP nutrient: Selenastrum 1 DJ‘J‘ meets of m. a diluent f0: LAP nutrient: Selenastrum 1 Table 30. 31. 32. 33. 34. 35. 36. 37. 38. Effects of membrane filtered Torch Lake water as a diluent for the AAP nutrients compared to the AAP nutrients diluted with distilled water on Selenastrum Maximum Specific Growth Rates. Also 8 e are Cv and 3 testing data . . . . . . Effects of membrane filtered Torch Lake water as a diluent for the AAP nutrients compared to the AAP nutrients diluted with distilled water on Selenastrum Maximum Standing Crops in cell numbers wITH Cv and 3 testing . . . . . . . . . . Effects of membrane filtered Deep Lake water as a diluent for the AAP nutrients compared to the AAP nutrients diluted with distilled water on Selenastrum daily Specific Growth Rates for an eIgEteen day static bioassay. . . . . . . . Effects of membrane filtered Deep Lake water as a diluent for the AAP nutrients compared to the AAP nutrients diluted with distilled water on Selenastrum Maximum Specific Growth Rates, with an eating. . . . . . . . . . . . v - Effects of membrane filtered Deep Lake water as a diluent for the AAP nutrients compared to the AAP nutrients diluted with distilled water on Selenastrum Maximum Standing Crops in cell numbers v an ‘3 testing . . . . . . . . . . Effects of membrane filtered Lake Lansing water as a diluent for the AAP nutrients compared to the AAP nutrients diluted with distilled water on Selenastrum daily Specific Growth Rates for a our son ay static bioassay. . . . . . . . Effects of membrane filtered Lake Lansing water as a diluent for the AAP nutrients compared to the AAP nutrients diluted with distilled water on Selenastrum.Maximum Specific Growth Rates with CV and‘i Testing. . . . . . . . . . . . Effects of membrane filtered Lake Lansing water as a diluent for the AAP nutrients compared to the AAP nutrients diluted with distilled water on Selenastrum.Maximum Standing Crops in cell numbers WIEE C 8113 2 testing 0 e e e e e e e e e '17 Dry weight data for the treatments (1) AAP nutri- ents diluted with distilled water and (2) AAP nutrients diluted with.membrane filtered Lake viii Page 97 97 105 106 106 113 114 114 "9.1-1 .cuie 38 (cont' (1) . 41, 42 £30 44- 45. is given tions and “Cell Res cells for with dist with men‘: given for nents . Mary 1 ”max, Ma; Faxinun Health" Bx erizne (11m 12) m lake wet Torch 1,; Effects and 0.0: Hillier 01' for a S Table 38 (cont'd). Lansing water determined on day 14. C 39. 40. 41. 42. 43. 44. 45. 46. is given for precision of samples within replicX- tions and replications within treatments. . . . "Cell Health" parameter of dry weight per million cells for treatments (1) AAP nutrients diluted with distilled water and (2) AAP nutrients diluted with membrane filtered Lake Lansing water. C is given for precision of replications within trXat- ments 0 e e e e e e e e e e ‘ e e e 0 Summary of the determined growth parameters of ”max. Maximum Standing Crops in cell numbers, Maximum Standing Crops in dry weights, and "Cell Health" in dry weight per million cells for Ex eriments 9, 10, and 11. The treatments were (1? AAP nutrients diluted with distilled water and 2 AAP nutrients diluted with membrane filtered lake water sample. The lakes bioassayed were Torch Lake, Deep Lake, and Lake Lansing . . . . Effects of two nutrient treatments of 0.40 mg N/l and 0.05 mg P/l to membrane filtered Torch Lake water on Selenastrum daily Specific Growth Rates for a seven day static bioassay. . . . . . . Effects of two nutrient treatments of 0.40 mg N/l and 0.05 mg P/l to membrane filtered Torch Lake water on Selenastrum.Maximum Specific Growth Rates with Cv and'i festIEg . . . . . . . . . . Effects of two nutrient treatments of 0.40 mg N/l and 0.05 mg P/l to membrane filtered Torch Lake water on Selenastrum Maximum Standing Crops in cell numbers, w ‘v and 3 testing . . . . . Effects of two nutrient treatments of 0.40 mg N/l and 0.05 mg P/l to membrane filtered Deep Lake water on Selenastrum daily Specific Growth Rates for a ten day statIc bioassay . . . . . . . Effects of two nutrient treatments of 0.40 mg N/l and 0.05 mg P/l to membrane filtered Deep Lake water on Selenastrum Maximum Specific Growth Rates With CV aha .5 568 EIng e e e e e e e e e 0 Effects of two nutrient treatments of 0.40 mg N/l and 0.05 mg P/l to membrane filtered Deep Lake water on Selenastrum.Maximum.Standing Crops in cell numbers, w v and‘t testing . . . . . ix Page 115 115 116 126 127 127 134 135 135 v1 , . zecle 1'7 “Ho Effects of t N/l 000} E P/l,to me on Selenastr a ten day BI Effects of t 2511/1, 0.03 ng P/l to me on Selenastr CV and i tes ". Effects of t we N/l, 0.05 mg P/l to me on Selenastr AWEers, w} E Table 47. 48. 49. Effects of three nutrient treatments of 0.40 mg N/l, 0.05 mg P/l, and 0.40 mg N/l plus 0.05 mg P/l to membrane filtered Lake Lansing water on Selenastrum daily Specific Growth Rates for a ten day bioassay . . . . . Effects of three nutrient treatments of 0.40 mg N/l, 0.05 mg P/l, and 0.40 mg N/l plus 0.05 mg P/l to membrane filtered Lake Lansing water on Selenastrum Maximum Specific Growth Rates with 0 Cv and i testIng . . . . . Effects of three nutrient treatments of 0.40 mg N/l, 0.05 mg P/l, and 0.40 mg N/l plus 0.05 mg P/l to membrane filtered Lake Lansing water on Selenastrum Maximum Standing Crops as cell numBers, wItE Cv and 3 testing . Page 143 144 144 hare i h . Light lntens square on 1 The straighi cell counts With regress The straighi cell Counts eElation Growth curv1 assay of 1111 in the up n The 0.00 1 cations , The 0.01 I 03110113 , Cations , The 0-03 1 Cations . Gmth CUrv assa Figure 1. 2. 3. 4. 5. a. b. C. d. LIST OF FIGURES Light intensity in foot-candles reaching each square on the assay platform . . . . . . . The straight-line relationship between observed cell counts and i2 vivo chlorophyll fluorescence with regression equatIon . . . . . . . . . The straight-line relationship between observed cell counts and optical density with regression equation 0 e e e e e e e e e e e 0 Growth curves for Selenastrum from a ten day bio- assay of the effects of Tour levels of phosphorus in the AAP medium 0 e e e e e e e The 0.00 mg P/l treatment run in four repli— cations . C O C . . C O O O O O C C The 0.01 mg P/l treatment run in four repli- cations O C C C O O O O O O O O O O The 0.02 mg P/l treatment run in four repli- cations . . . . . . . . . . . . . . The 0.03 mg P/l treatment run in four repli- cations e e e e e e e s s' e s e e 0 Growth curves for Selenastrum from a six day bio- assay of the effecfs of Two Ievels of light inten- sity on growth. Differences were judged not de- tectable due to methodological errors. . . . . HIGH intensity treatment of 475 ft-c (5111 lux) run in five replications, showing poor precision for initial cell concentrations and no cultures going through a logarithmic growth phase except for one replication. The response to the TRACES stock added on day 6 is shown. The average re- sponse of the other stock nutrients is also shown. This suggests TRACES are limiting algal 31‘ O'th e e e e e e e e e e e e e 0 LOW intensity treatment of 260 ft-c (2798 lux) run in five replications, showing poor precision for initial cell concentration and no cultures going through a logarithmic growth phase . . . xi Page 16 35 36 41 42 43 44 45 51 52 53 Figxe 6O 9. 10. Growth cum bioassay of cell concen' 2.101104 ce Growth curv bioassay sh intensity ( the respons intensity t eity. . , Growth curv bioassay sh carbon die: during algs 8. Ho treatn 13- Air vents °° Air bubbi one repl: to be 50 do COZQRI-i‘ 25 cc/mi; coz-enri 5 CC/min cog-earl 5° cC/mi 2211? PH m Seeeing “Wee Growth C111 assay of 1 e Vate: a. The tree dietine Figure Page 6. Growth curves for Selenastrum from an eleven day bioassay of the effects of ‘hree leve s of initial cell concentration (1.68x10 , 6.00x10 , and 2.10x104 cells per ml) on growth . . . . . . 58 7. Growth curves for Selenastrum from an eleven day bioassay showing the effects of HIGH and LOW light intensity (475 ft-c and 260 ft-c). Also shown is the response when on day 4 a portion of the LOW intensity treatment was placed under HIGH inten- sity. O O O O O O O O O O O O O O O 65 8. Growth curves for Selenastrum from an eleven day bioassay showing the effects of six levels of carbon dioxide used to insure carbon availability during algal culturing. . . . . . . . . . 72 a. No treatment gas delivered to the culture. . . 73 b. Air vented above the culture at 25 cc/min. . . 73 0. Air bubbled into the culture at 5 cc/min, with one replication's flow rate in error and found to be 50 cc/min . . . . . . . . . . . 73 d. CO2-enriched air vented above the culture at 25 CC/min o o c o o o o o o o o o o 73 e. COz—enriched air bubbled into the culture at 5 cc/min. . . . . . . . . . . . . . 74 f. COZ-enriched air bubbled into the culture at 50 CC/min O O O O O O O O O O O O O 74 9. Daily pH measurements from an eleven day bioassay assessing the effects of suggested methods of insuring carbon availability to algal cultures. . 75 10. Growth curves for Selenastrum from a ten day bio- assay of the effects of membrane filtered Torch Lake water used to dilute the AAP stock nutrients. 93 a. The treatment was AAP nutrients diluted with distilled water (control) . . . . . . . . 94 b. The treatment was AAP nutrients diluted with membrane filtered Torch Lake water . . . . . 95 11. Growth curves for Selenastrum from an eighteen day bioassay of the effects of membrane filtered Deep Lake water used to dilute the AAP stock nutrients. 102 a. The treatment was AAP nutrients diluted with distilled water (control) . . . . . . . . 103 xii ' 14"”1— Home 11(cont'd). b. The treat: membrane 12. Growth curv bioassay of Busing wet ents. . . a. The treat distilled lation er b. The treat membrane 1‘30 Growth cm bioassay tr PTOduction Vater Bag-JP: a. The tree: water w11 1" The trea- co The treat assay to prOduCtion " The trea Water '1 The tree assay pr(Kinetic: Lang ‘2 The tre; With no Figure Page 11 (cont'd). b. The treatment was AAP nutrients diluted with membrane filtered Deep Lake water . . . . . 104 12. Growth curves for Selenastrum from a fourteen day bioassay of the effects of’membrane filtered Lake Lansing water used to dilute the AAP stock nutri- 10 ents. . . . . . . . . . . . . . . . 1 a. The treatment was AAP nutrients diluted with distilled water (control). Because of an inocu- lation error, only two replications were run. . 111 b. The treatment was AAP nutrients diluted with membrane filtered Lake Lansing water . . . . 112 13. Growth curves for Selenastrum from a seven day bioassay to determine the nutrient limiting algal production in a Torch Lake membrane filtered water sample . . . . . . . . . . . . . 121 a. The treatment was membrane filtered Torch Lake water with no nutrients added (control) . . . 122 b. The treatment was control plus 0.40 mg N/l . . 123 c. The treatment was control plus 0.05 mg P/l . . 124 14. Growth curves for Selenastrum from a ten day bio- assay to determine the nutrIent limiting algal production in a membrane filtered Deep Lake sample 130 a. The treatment was membrane filtered Deep Lake water with no nutrients added (control) . . . 131 b. The treatment was control plus 0.40 mg N/l . . 132 c. The treatment was control plus 0.05 mg P/l . . 133 15. Growth curves for Selenastrum from a ten day bio- assay to determine tEe nutrient limiting algal production in a membrane filtered sample of Lake Lansing water. . . . . . . . . . . . . 138 a. The treatment was membrane filtered Lake Lansing with no nutrients added (control) . . . . . 139 b. The treatment was control plus 0.40 mg N/l . . 140 c. The treatment was control plus 0.05 mg P/l . . 141 d. The treatment was control plus 0.40 mg N/l and 0005 mg P/lo o o o o o o o o o o o o 142 xiii -1 , " - '1, - £3 Cell count: treatment Phorus med marked as 3911 coum control pf 3 With ma- Cell Com} control I 3 with :32 Control Snug Cell Cox 167913 ‘ with cv Table B1. B2. B3. B5. B6. B7. LIST OF APPENDIX TABLES Cell counts as cells/grid and cells/ml for the treatment control of AAP nutrients minus phos- phorus medium of EXperiment 3 with maximums marked as * and with Cv . . . . . . . . . Cell counts as cells/grid and cells/ml for the control plus 0.01 mg P/l treatment of Experiment 3 with maximums marked as * and with Qv' . . . Cell counts as cells/grid and cells/ml for the control plus 0.02 mg P/l treatment of Experiment 3 with maximums marked as * and with Cv. . . . Cell counts as cells/grid and cells/ml for the control plus 0.03 mg P/l treatment of Experiment 3 with maximums marked as * and with Cv' . . . Cell counts from Experiment 4 bioassaying two levels of light intensity (260 ft-c and 475 ft-c) With CV O O O O O O O O O O O O O 0 Cell counts, average of three replications, from Experiment 5 bioassaying three I vels of nitial algal gall concentration (1.7110 , 6.0x10 , and 2.1110 cells/ml) with C between replications. Treatments are shown as I, II, and III respect- ively o o o o o o o o o o o o o o 0 Cell counts from Experiment 6 bioassaying (a) two levels of light intensity (260 ft-c and 475 ft-c) and (b) cell counts for a portion of the 260 ft-c treatment placed under 475 ft-c on day 4 and cultured through day 11. Both (a) and (b) with cv O O O O O O O O O O O O O O O 0 Cell counts and pH from Experiment 7 bioassaying six levels of carbon dioxide used to insure carbon availability in bottle tests as suggested inthem O O O O O O O O O O O O O xiv Page 160 161 162 163 164 165 166 167 39. Cell counts ' by bioassay 1 Lake nenbram diluted with as * . . 90. Cell counts, Daring by hi Jeep Lake m1 ents dilute marked as * 377. Cell counts by Moses E Lansing me: diluted wi 33 *. lno repliC'ztio “' 3511 Count the treat: Lake cont (‘3) contr are marhe 33, Cell C0“: vI‘Ea when COHtrol’ “rol Flu be '. C911 C03 tr reaffex Control' trOl pl. 0 :40 Pr~ Ki.‘ Table B9. B10. B11. B12. B13. B14. Cell counts and pH from Experiment 9 comparing by bioassay the AAP nutrients diluted with Torch Lake membrane filtered water to AAP nutrients diluted with distilled water. Maximums marked as * O O O O O O O O O O O O O O 0 Cell counts, C , and pH from Experiment 10 com- paring by bioagsay the AAP nutrients diluted with Deep Lake membrane filtered water to AAP nutri- ents diluted with distilled water. Maximums are marked as * O O O O O O O O O O O O 0 Cell counts and C from EXperiment 11 comparing by bioassay the AXP nutrients diluted with Lake Lansing membrane filtered water to AAP nutrients diluted with distilled water. Maximums marked as *. Inoculation error accounted for only two replications of the distilled water treatment. . Cell counts, C , and pH from Experiment 12 for the treatmentsvof (1) membrane filtered Torch Lake control, (2) control plus 0.40 mg N/l, and (3) control plus 0.05 mg P/l. Maximum counts are marked. as *0 o o o o o o o o o o 0 Cell counts and Cv from Experiment 13 for the treatments of (1) membrane filtered Deep Lake control, (2) control plus 0.40 mg N/l, and con- trol plus 0.05 mg P/l. Maximums are marked as *. Cell counts and C from Experiment 14 for the treatments (1) membrane filtered Lake Lansing control, (2) control plus 0.40 mg N/l, (3) con- trol plus 0.05 mg P/l, and (4) control plus 0.40 mg N/l and 0.05 mg P/l. Maximums are marked as * O O O O C O C C O O O O O Page 169 170 171 172 173 174 " i: L'VW’.’ .< u Pre A1. Figure of th. distribution counts per 3 counts of 1. expected P01 means , Figure A1. LIST OF APPENDIX FIGURES Page Figure of the relationship between observed distributions for cell counts (from fifty grid counts per sample and three samples with mean counts of 1.4, 3.2, and 5.3 cells per grid) and expected Poisson distributions for the given means 0 O O O O C O O O O O O O O O 1 59 xvi INTRODUCTION The main purpose of this study is to investigate, identify, and solve the technical problems associated with a static algal bioassay procedure so that systematic vari- ance will be minimized. Thus, by mastering the techniques, a maximum amount of confidence can be placed in results from subsequent practical applications of the bioassay pro- cedure. For this study bioassay is defined as biological assess- ments of measurable responses caused by a controlled treat- ment to a test organism. Some would say the word "controlled" be excluded from the definition. Their reason might be an example where caged fish are placed in a potentially pollut- ing water with responses measured. I would term such an example as inclined more toward biomonitoring than bioassay- ing the water. Controlled variables are an important condi- tion for proper bioassays. Bioassays have been used for many years in many areas of biology since most types of treatment-response experiments are bioassays. If it were not for treatment-response studies, most agricultural, microbiological, pharmacological, and medi- cal research would be in a primitive state. Aquatic biology compared to these areas is in a relatively less advanced state. "It“ ‘ there is a the 1:1" ditj t , L urea. cent-2 :irst used “fol n * .-y as S‘- ents" n. . d-~ diSSEI‘tLtig ‘s' a ~ “5J1 cf 1- 3'ng (C‘dlti with water pollution making demands of aquatic biology, there is a need for the aquatic biologist to apply fewer of the traditional descriptive investigations in proportion to treatment-response investigations. This study is concerned with static algal bioassay as a tool for the assessment of the enrichment of aquatic envi- ronments (often termed as eutrophication). Weber (1907) first used the terms "oligotrophic" and "eutrophic" respect- ively as synonyms for "poor in nutrients" and "rich in nutri- ents". Later, Naumann (1917) used Weber's terms in his dissertation thesis and thus the words were adopted into the field of limnology. Eutrophication may be natural or man- made (cultural). Hetzel (1966) would term very extreme types of eutrophication as "hypereutrophication". Hutchinson (1969) would question whether hypereutrophication and noxious blue- green algal blooms can ever be natural phenomena and are likely always mannmade. At the 1967 International Symposium on Eutrophication (see Introduction to Eutrophication: CausesI Consequences, Correctives; Rohlich, Chairman, 1969) it was stated, "Many participants called for a more thorough understanding of algal physiology and ecology. More algal culture studies, coupled with experiments in chemical alteration of lake waters, are needed to better understand the interaction between organisms and nutrients. Such studies require more sensitive analyti- cal techniques that distinguish between avail- able and nonavailable forms of the elements." The algal bioassay is such a technique holding considerable promise. It can distinguish between available and nonavailable nutrients and if Feloney and Barte “In many c more sen: ninetion: much mom data and if they ‘ Recognizing the z"J/Government Ta development of 1 (haeltman, 1959: which were (1) I chemostat test, evaluation tea: the W research PTOgre (Money, 197 1. M It 13 the is heped “as m become widely Fitzgerald, 1S 1973; LEe, 19.1 hovers 81: a and 1972), 1” will \’ the spel W nutrients and if performed properly can be very sensitive. Maloney and Bartsch (1969) stated, "In many cases these bioassays appear to be more sensitive than standard chemical deter- minations. Such assays, however, would have much more value with respect to comparing data amoung laboratories and geographic areas if they were standardized." Recognizing the need for standardization, the Joint Indust- ry/Government Task Force on Eutrophication sponsored the development of the Provisional Algal Assqy_Procedure (PAAP) (Bueltman, 1969). The procedure consisted of three tests which were (1) a static bottle test, (2) a continuous-flow chemostat test, and (3) an in gitu test. The PAAP static bottle test was further developed by an eight-laboratory evaluation team and the subsequent detailed publication was the Inter-LaboratoryPrecision Test, National Eutrophication Research Program (NERP), U.S. Environmental Protection Agency (Maloney, 1971). The refined static bottle test was the Algal Assay Procedure: Bottle Test (AAP) (Bartsch, 1971). It is the Algal Assay Procedure: Bottle Test (AAP) that is hoped was mastered in this study. The AAP has already become widely used (Brown, 1972; Brown and Porcella, 1972; Fitzgerald, 1970a,b, 1971, and 19728; Francisco and Weiss, 1973; Lee, 1973: Maloney 6t 81.. 1972; Malueg et a1., 1973; Powers et al., 1972; Toerien et al., 1971; and Tunzi, 1971 and 1972). All of these authors used Selenastrum capricorn- utum, the species used in this study. Selenastrum capricornutum has been extensively used as ”103.583! test 8: chenheriain and ST Fitzgerald and 19 1970 and 1972)- uced W to in this am? The w recogiized as a new edition of § ZEaticnal Eutrop'r. Protection .-'.gen< a bioassay test species outside the AAP (Berge, 1969; Chamberlain and Shapiro, 1969; Eyster, 1958; Fitzgerald, 1969; Fitzgerald and Lee, 1971; Pearson et al., 1969; and Skulberg, 1970 and 1972). Since capricornutum is the most commonly used Selenastrum.species for bioassay, it will be referred to in this study as just Selenastrum as it was in Murray et al. (1971). The Algal Assay Procedure: Bottle Test will indeed be recognized as a "standard" f and when it is placed in a new edition of Standard Methods, APHA. Maloney (1972), Chief, National Butrophication Research Program, U.S. Environmental Protection Agency, stated in a personal communication that it is anticipated the AAP will appear in the 14th Edition of Standard Methods, APHA. He also recommended the AAP be followed as closely as possible for this study. There are 1. Vi: T ES OF ALGAL BIOASSAY There are three parts to algal bioassay as outlined. 1. Variable test procedure, e.g. a. static bottle test, b. continuous-flow chemostat test, c. _i_z_1_ 533.33 test, and d. dialysis test. 2. Variable test organism, e.g. a. §gl§nastrum caprioornutum Printz (For AAP), b. Microczstis aeruginosa Kutz. emend Elenkin (Anacystis czanea Drouet and Daily) (For AAP), c. Anabaena flos-aquae (Lyngb.) De Brebisson (For RAP), d. other commonly used outside the AAP are Scenedesmus sp., Chlorella sp., and diatoms, and e. species indigenous to the test waters. 3. Variable test substance, 6.5. a. toxicants, b. stimulants, and c. unknowns. The choice of a test procedure depends upon the type of data desired, time considerations and economic factors, and the aquatic environment under study. The static bottle test used in this study is preferred when rapid information on algal response is needed, when many samples are processed, and when many possibilities in experimental design are desired. 5 Chenostet to when tine and fee not been standard ever, the Nations. rcmental Protect ing a procedure. for a chemostat 1 ized, it will 11‘; than the static ' The E m till probably be Ecvever, the 33+”; of the advantere The test 0: W. Plies without c size 1511103 611011 1 counter-3 h,“ 1 for tn 5 Spaci Chemostat tests are more suitable for long-term studies when time and facilities are ample. The chemostat test has not been standardized as has the static bottle test. How- ever, the National Eutrophication Research Center, U.S. Envi- ronmental Protection Agency, Corvallis, Oregon, is develop- ing a procedure. Toerien et al. (1971) gives a procedure for a chemostat test. When chemostat testing is standard- ized, it-will likely be more applicable for natural situations than the static test. The in £393 test has not been standardized. This test will probably be used with the most confidence someday. However, the static bottle test will always be useful because of the advantages mentioned previously. The test organism selected for this study was Selenastrum capricornutum. Unlike many other species, Selenastrum multi- plies without clumping and remains at reasonable uniform size throughout its life cycle. In fact, electronic particle counters have been used to determine cell numbers successfully for this species (Tunzi, 1972). The test substances studied in.many of the later experi- ments in this study were nitrogen and phosphorus since it has been shown they are "key elements" in.eutrophication (e.g., Shapiro, 1970). Although the bottletest requires simple set-up and common procedures, one can get very sophisticated in experi- mental design. For instance, bottle tests need not be limited to assaying one substance at a time. ‘Factorial experiments T?! can be used to 10 test substances . :1, 31 static al ent-hunic acid in Biological n movements requ orplerity of org experimentation. iar with bioassa: error before act1 is the primary 1: those areas in 1: high variances a can be used to look for interactions between two or more test substances. Geisy (personal communication) is using the KAT static algal bioassay to look at various algal-nutri- ent-humic acid interactions. Biological measurements even more so than chemical measurements require meticulous technique. Because of the complexity of organisms, many variables enter into biological experimentation. It is desirable to become thoroughly famil- iar with bioassay by looking for common sources of systematic error before actually applying it to research areas. This is the primary purpose of this study, that is, to look for those areas in the procedure which are most likely to yield high variances and to keep these "problem" variances at a minimum. 7”, .1 h a-v "7'! wrv w ’0. In order to essential mteri first ecological ”Growth 0 of foods minions This has beooze In his Paper, L1 PRINCIPLES OF ALGAL BIOASSAY In order to grow and reproduce an organism must have essential materials. Liebig (1840) expressed one of the first ecological principles. He said, "Growth of a plant is dependent on the amount of foodstuff which is presented to it in minimum quantities." This has become known as Liebig's "Law of the Minimum". In his paper, Liebig defined "foodstuff" as "nutrients". Shelford (1913) introduced the "Law of Tolerance" which included growth limitations due to maximum as well as minimum factors. Taylor (1934) and many others have expanded the "Law of the Minimum" to include factors other than nutrients, such as pH, light, and temperature. In regard to this, Odum (1971) states, "To avoid confusion it seems best to restrict the concept of the minimum to chemical materials necessary for physiological growth and reproduction, as was originally intended, and to include other factors and the limit- ing effect of the maximum in the "Law of Tolerance"..... Extensive work since the time of Liebig has shown that two subsidiary principles must be added to the concept if it is to be useful in practice. The first is a constraint that Liebig's law is strict- ly applicable only under steadyhstate condi- tions, that is, when inflows balance out- flows of energy and materials..... The second important consideration is factor interaction. Thus, high concentration or availability of some substance, or the action of some factor other than the minimum one may 8 modify t'r. Stun points out t under “steady-eta 31115th ”unstead- "tmnsient state“ 11312113" is of m The "11211.33 nu' Cm: because :31: my other nutri liming factor. Others have makes the "Law ‘ “My. 1963). The "L513 0 a Smposim by E. mil1r: the modify the rate of utilization of the latter." Odum points out that pristine, balanced ecosystems operate under "steady-state" conditions, however, man has caused a highly "unsteady" state. Regarding water bodies and the "transient state" due to man, Odum states the "Law of the Hinimum" is of no theoretical basis under such conditions. The "limiting nutrient" is likely irrelevant according to Odum, because phosphorus, nitrogen, carbon dioxide, and many other nutrients may rapidly replace one another as limiting factor. Others have stated the complexity of organisms alone makes the "Law of the Minimum" an oversimplifaction (e.g., Goldman, 1963). The "Law of the Minimum" was in so very much dispute, a symposium by the American Society of Limnology and Oceanp ography entitled Nutrients and Eutrophication: The Limiting Nutrient Controversy'(Likens, ed., 1972) was devoted to the dispute (see Preface). While the "Law of the Minimum" may be an.oversimplifica- tion for natural situations, it is easily realized for the static algal bottle tests. If one takes a bottle containing a medium having all essential nutrients and inoculates it with algae, growth will ensue until some nutrient becomes limiting to growth. it that time a steadybstate condition exi sts although maybe for only a short period of time. (For steady-state conditions for extended periods of time one would use continuous-flow chemostat tests). it first the algae will EN“ ‘ increasing, Win at which the 5'30' ing rate is tern Although t1". designed pecifi of the Elmira" experiments pro: of the 3111mm" whitever conclul not apylicable c ityreach to bio 13; if the 8.15:). firediction abor ticts correctl; T-lllueg et a1. adrmced Waste Thagawe. Lake 3"“vilymzxent21 ‘* Wet 1976 0311 be assess treat-.318“ Off Th e obJeCtin th- e rest-01.11:1 critical @0’ treatment 00 ‘teq e95 1O algae will grow at an increasing rate. Then growth, although increasing, will increase at a decreasing rate. The point at which the growth changes from an increasing to a decreas-‘ ing rate is termed the Maximum Specific Growth Rate (Amax)‘ Although the experiments in this study were not designed specifically to show the correctness of the "Law of the Kinimum" as it applies to static bioassays, some experiments provide such evidence. Some may say if the "Law of the Minimum" does not hold for natural situations, then whatever conclusions are reached in a static bioassay are not applicable outside the laboratory. A more pragmatic approach to bioassay is used for this study. This approach is; if the algal bioassay is used to make an assessment or prediction about a natural situation and it assesses or pre- dicts correctly, then continue using the assay. For instance, Malueg et al. (1973) used the AAP to make predictions about advanced wastewater treatment for phosphorus removal in the fihagawa Lake Restoration Project, Ely, Minnesota. This U.S. Environmental Protection Agency project will continue until at least 1976, at which time the value of the algal bioassay ‘can be assessed. Preliminary investigations with pilot plant treatment efficiencies determined by bioassay are promising. The objective of the Shagawa Lake Project is to demonstrate the restoration of a manemade eutrophic lake by removing the critical growth.promoting nutrient, phosphorus, by advanced treatment of municipal wastewater while permitting such treated effluent to continue to flow into the lake. If the project is access solved a technoli methods and tech. the technologica‘ Ilgal bioassay s‘. 11 project is successful, the algal bioassay will have helped solved a technological problem. Biology is much in need of methods and techniques that can more easily be applied to the technological problems in water pollution control. Algal bioassay shows promise as such a tool. The LA? was iications were ne Table 1. Synthe' given liter. ================ (impound C02 ¥ 3 r 5210.5 V r: 1‘?“ 4 tug-63:01:. F, r natiCF. L\. r'gclz'BECF at”: 80] bale $103 was 1 We: 8 made. tion req‘e‘tire in .. accuracy ALGAL BIOASSAY PROCEDURE The AAP was followed closely for this study. Some modi- fications were necessary and are noted here. Table 1. Synthetic algal nutrient medium macronutrients given as final concentrations in milligrams per liter. M Compound Concentration Element Concentration (Qéli) imgll) NaNO3 25.500 N 4.200 K HPO4 1.044 P 0.186 Mg012°6H0H 12.143a lg 2.904 MgSO4°7H0H 14.143 S 1.911 CaClZ-ZHOH 4.410 C 2.143 NaHCO3, 15.000 Ca 1.202 Na 11.001 K 0.469 amg012-6H0H is substituted for AAP's 5.700 mg MgClz/l. Stock solutions of individual macronutrient salts were made up in 1000 times the final concentration. A six-place balance was used for weighing and appropriate dilutions were made. A four-place balance used for a stock prepara- tion required more dilutions, but was not judged as a loss in accuracy of the final nutrient concentrations. Micronutrient trace metals and EDTA (ethylenediamine- tetraacetic acid) were combined into a single stock mix at 12 1000 times the i was necessary to tain trace elem Table 2. Synth given liter *— ‘- Conpound C1 “1303 1'21le 4308 sz2 120012 011012 " 11a (004.2}:‘(11‘ ———l Fe013. SHOE iagz‘ 211m ailing-secs 9013-6110:: The :11: a miliecLubes hereafter b one my distilled ‘ medium. I: nutrients nutrient ' Since 1:1. .19 13 1000 times the final concentrations. The EDTA chelator was necessary to insure the biological availability of cer- tain trace elements, primarily the Fe-EDTA complex. Table 2. Synthetic algal nutrient medium micronutrients given as final concentrations in micrograms per liter. Compound Concentration Element Concentration Qggll) bugziy H3BO3 185.520 B 32.460 Mn012-4How 415.379a ms 115.374 ZnCl2 32.709 Zn 15.691 00012 0.780 Co 0.354 CuCl2 0.009 Cu 0.004 Na2M004°2HOH 7.260b Mo 2.878 EeCl3°6HOH 159.881 Fe 33.051 NazEDTA°2HOH 300.000 aMnCIZ4H0H was substituted for AAP's 264.264 g MnClZ/l. bFeClB'GHOH was substituted for AAP's 96.000 g FeClB/l. The dilution water was distilled water passed through a mixed-bed resin ionpexchange column. This water will hereafter be referred to as just distilled water. One milliliter of each stock solution was added to distilled water to give a final volume of one liter of AAP medium. Hurray et al. (1971) found the order in which the nutrients were added and the freshness of the medium changed nutrient concentrations. I did not initially realize this since the AAP does not stress the importance of medium pre- paration and freshness. ‘It was initially noted the nutri- ents formed a precipitate when directly combined and then w Lu II .225" diluted. Therefc flask half fillec volume. It was 1 precipitation 1e: :etal-EUI‘A stool-z mt a 0.47/4 nem‘ The nutrien rial contaninati in an axenic con necessary, .211 e phate was lost c‘ detected. The 1 304. and E03 £02 and Centrifugat for these nutri in soluble 8111 containers. If Should be nOted 14 diluted. Therefore, the stocks were added to a volumetric flask half filled with distilled water and brought up to volume. It was believed this made the kinetic chances for precipitation less favorable. The AA? recommends the trace metal-EDTA stock be added after filtration. This was done with a 0.41M.membrane filter. The nutrient stocks were autoclaved to minimize bacte- rial contamination. Since the algae used were not obtained in an axenic condition, sterilizing culture medium is not necessary. in experiment was conducted to determine if phos- phate was lost due to autoclaving. No significant loss was detected. The AAP tested for losses in Ca, Na, K, Mg, 01, 804, and N03 following autoclaving, membrane filtration, and centrifugation. No significant decreases were noted for these nutrients. However, autoclaving caused an increase in soluble silica concentrations, possibly from the glass containers. If diatoms are used as a test organism, this should be noted. Reilly (1972) compared growth obtained by autoclaving and membrane filtering the medium and found no difference. He also found Microcystis aeruginosa grew better with its "symbiotic" bacteria than in an axenic state. There is a need for more studies comparing axenic with nonpaxenio bio- assays, however, the AAP as developed is intended for nonp axenic bioassays. Selenastrum capricornutum Printz, the test organism, was obtained fro tel, Pacific Nor detection lgenc . ‘1 received, 9 tr;“ nique we used 1 continuation. soon became 010‘; transfer schedu] trif’le’iflg and v 11 glassware u elated. 51923ng ‘3 ‘Imlytical EtcTies (U.S. 805.1115 Carbon 101d, 34110 1‘1: gents were u The cm The masts ‘ plug-3. Cm flash for dioxide 6&1 (1972) £01; All 30am 1 11161 all i 15 was obtained from the National Eutrophication Research Cen- ter, Pacific Northwest Water Laboratory, U.S. Environmental Protection Agency, Corvallis, Oregon. When the algae were received, a transfer was made into AA? medium. Aseptic tech- nique was used in handling the stocks to avoid unnecessary contamination. It was found if this was not done the stocks soon became cloudy with bacteria. A weekly routine stock transfer schedule was followed. Transfers were made by cen- trifuging and washing the cells twice with 15 mg NaH003/l. All glassware used for stock cultures and transfers was auto- slaved. Cleaning of glassware was done according to the Handbook for Analytical Quality Control in Water and Wastewater Labor- atories (U.S. Government, 1972). Glassware was washed with sodium carbonate, soaked in ten percent reagent hydrochloric acid, and rinsed several times with distilled water. Deter- . gents were not used to avoid phosphorus contamination. The culture flasks were 125-ml Pyrex Erlenmeyer flasks. The flasks were washed, autoclaved, and stoppered with foam plugs. Only fifty ml of sample or medium was placed in the flasks for optimum surface to volume ratios to aid in carbon dioxide diffusion into the culture solutions. Justice at al., (1972) found certain foam plugs were toxic to Selenastrum. All foam plugs were compared to foil coverings and none were significantly different. Inoculum was prepared so nutrient carryover was minimized and all flasks got as closely as possible the same number of a152,], cells. T de‘cel‘mJ-Ile h" 1: cell concentra’c found deliverih be in excessive centrifuge a PC to a solution in the Mambo: e long-stem ca; to judge the n: concentration c counted media 16 algal cells. The AAP suggests counting the inoculum to determine how much to deliver to the flasks. The starting cell concentration should be about 103 cells per ml. I found delivering the inoculum with a calibrated pipet to be in excessive error. The final method I adopted was to centrifuge a portion of the stock culture, wash it twice with a solution of 15 mg NaHCO3/l, and resuspend the cells in the bicarbonate solution. Inoculum was delivered with a long-stem capillary dropper. With experience, I was able to judge the number of drops needed to give an initial cell concentration of about 103 cells per ml. One flask was counted immediately after inoculation and this was recorded as the initial cell concentration. Inoculated flasks were stoppered with the foam plugs and incubated at 24°C under cool-white fluorescent illumi- nation. Squares were drawn on a white assay platform, each to accommodate one culture flask. The light intensity reaching each square was determined with a light meter and varied according to Figure 1. 260 305 330 350 350 330 305 260 330 390 420 450 450 420 390 330 350 420 450 475 475 450 420 350 330 390 420 450 450 420 390 330 260 305 330 350 350 330 305 260 Figure 1. Light intensity in foot-candles reaching each square on the assay platform. cm. Figure 1 to 475 ft-c. r3 astrum is al.-’30 Ii- of its forty sq alloted to thee {1.971) found 11 rates when 0021} not exceeded '11 The [if n within the ran. “3': I'Zethods Studied in 31p in this study stated in a re "It doe is if :h. to nefisures we than Using 0p‘ and daily ham shaker tables 311', and bubb: The resuts 0 Fr mrling Wag dismissal or . hop Era 17 Figure 1 depicts the light intensity ranges from 260 ft-c to 475 ft-c. The AAP states the optimum intensity for §2$22f astrum is 400': 50 ft-c. The assay platform had twenty-two of its forty squares in this optimum range. Flasks were alloted to these squares whenever possible. Murray et al. (1971) found light intensities of 500 ft-c reduced growth rates when compared to 350 ft-c. Therefore, 500 ft-c was not exceeded in this study. The AAP recommends the pH in a culture should be kept within the range of 8.0 to 8.5 to insure carbon availabil- ity. Methods suggested by the AAF for controlling pH were studied in Experiment 7. The approach I took to pH rises in this study followed that of Fitzgerald (1972b), who stated in a recorded discussion, "It doesn't make any difference what pH it is if the algae grow. I don't care if my algae grow in pH 10 or 11. If they grow, that's a successful culture". No measures were taken in this study to control pH other than using optimum surface to volume ratios for the medium and daily hand swirling of the flasks. The AAP also suggests shaker tables, ventilation of air or carbon dioxide enriched air, and bubbling of air or carbon dioxide enriched air. The results of Experiment 7 plus the findings of the £333;- Laboratorz Precision Test (Maloney, 1971) that daily hand swirling was equivalent to shaker table results led to the dismissal of venting or bubbling measures. Two parameters are used by the AA? to describe algal .. ' ace—v4! “- M growth: (1) the l4 Maximum Standing on the bioassay < Detailed in: given by Myers ( (1951). Alg’l g liiited material Because all envi (Calm, 1971), tl pattern in natu tree for static a pomatlcn is Where i 18 some and ,u. is the s A" has been su “Myer, 1962) file gives an 18 growth: (1) the Maximum Specific Growth Rate and (2) the Maximum Standing Crops. The use of these parameters depends on the bioassay objectives. Detailed information on the kinetics of algal growth is given by Myers (1962), Pearson et al. (1969), and Tamiya (1951). Algal growth under theoretical conditions of un- limited materials would result in a J-shaped growth curve. Because all environments have a definite carrying capacity (Odum, 1971), the S-shaped or sigmoid curve is the growth pattern in nature for most living populations. The same is true for static bioassays. The equation for the growth of a population is: dX/dt = ,«x, where 2.18 some measurable reflection of growth, 3.13 time, and,u.is the specific growth rate coefficient. The symbol, 55 has been substituted by the symbols 3 (Odum, 1971) and ‘E (Myer, 1962) in other literature. The specific growth rate gives an intrinsic measure of the rate of total meta- bolism leading to cell synthesis (Myers, 1962). Calculus manipulation of the above equation gives the following formula from which growth rate calculations are easily made: = ln(X2/X1) ’ (ta-t1) where E'is measured directly in cell numbers or biomass. E can also be measured indirectly by calibrating optical density, in vivo chlorophyll fluorescence, chlorophyll i r»' by“. flaw . a concentration The Maxi when the cult for growth. of the adequz also a funct: or temperatu Jim other t should be he The grc the 31le a bioassay, l-Eanm Sta] cell number This Value Standing C: the 89m ir. :15th 18 e] 21' By de< 19 concentration, or ATP concentration to a direct measurement. The Maximum Specific Growth Rate (”max) is reached when the culture conditions, changing with time, are optimum for growth. For algal bioassay,/A:max provides a criterion of the adequacy of inorganic nutrition (Myers, 1962). It is also a function of other factors such as light intensity or temperature. For this reason, all factors affecting Aha: other than the factor of concern in the bioassay should be held constant and frequently checked. The growth parameter of Maximum Standing Crop represents the maximum quantity of cells or cell biomass achievable in a bioassay. According to the AAP, it may be assumed the Maximum Standing Crop has been reached when the increase in cell numbers or biomass is less than five percent per day. This value is often not the absolute maximum. The Maximum Standing Crops are denoted as cell numbers or biomass by the same indirect methods discussed previously. The para- meter is expressed as cell numbers per ml or dry weight per m1. By determining both expressions for the parameter and reporting the two as a quotient, one comes up with dry weight per cell. This is often expressed as dry weight per million cells and is descriptive of not only the nutrients assayed, but also the physiological condition ("cell health") of the cells at the time of measurement. Devices commonly used to determine cell numbers are Sedgwick-Rafter chambers, hemacytometers, Palmer chambers, and electronic particle counters such as the Coulter counter. I found large (1000 ed after set dense for or gave accept: usually occr Crops betweo on a daily 1 For tr: ‘13? Weights useful for ; Species (ed it is often found gram- :2me Sta; flax Perez‘s is achieve d weight dete be able to liter or m weighing. I used A portion 0 0 t1, “bed tori.2 Sr: ferrEd to t 20 I found the Sedgwick-Rafter chamber had a volume too large (1000 mm3) to give accurate cell counts. Cells count- ed after settling to the bottom of the chamber were too dense for counting. The Palmer chamber's volume (100 mm3) gave acceptable counts according to EXperiment 1. The Amax ‘usually occurred between days 0-3 and the Maximum Standing Crops between days 5-10. Therefore, cell counts were made on a daily basis. For this study, gravimetric determinations were always dry weights of the algal cells. This method is especially 'useful for assessing the growth of joined or filamentous species (e.g., Anabaena, Cladgphora, or Scenedesmus) since it is often difficult to obtain accurate cell counts. I found gravimetric determinations to be very precise for the Maximum Standing Crop parameter, but not suitable for the fihax parameter. This is because the maximum growth rate is achieved during cell densities too low for precise dry weight determinations. Gravimetric determinations might be able to monitor daily growth for large cultures of a liter or more where large subsamples can.be taken for weighing. I used the aluminum pan method to determine dry weight. A portion of algal suspension was centrifuged, cells washed twice with distilled water, cells resuspended to the same volume as the original portion, cell suspension trans- ferred to tared aluminum pans, cells dried overnight in a hot air oven olace balanc method which on pan math Indirec mine than th as defined b entration of only measuri caused by re ing depends the technica Iiephelometry of a Photome function 0.: mum-t? is {‘3‘ ‘ 21 hot air oven at 105°C, and dried cells weighed on a six- place balance. The AAP describes a membrane filtration method which it states to be less sensitive than the alumi- num.pan method. Indirect measurements are easier and faster to deter- mine than the direct methods. Optical density or absorbance as defined by Beer's Law, can be used to determine the conc- entration of cells in suspension.(Myers, 1962). One is not only measuring light absorption, but also light scattering caused by reflection and refraction. The amount of scatter- ing depends upon the instrument quality. Turbidimetry is the technical name for light scattering measurements. Nephelometry is the term when a fluorometer is used instead of a photometer (Skoog and West, 1971). Absorbance is a function of cellular pigmentation.and extracellular products. Turbidity is afunction of cell shape, size, and volume. I found absorbance to be useful for determining Maximum Stand- ing Crops but not ”hax for the same reasons as gravimetric measurements. This was investigated in Experiment 2. Indirect measurements of extracted chlorophyll concen- trations determined by spectrophotometry are reported to be sensitive enough to monitor daily growth (Strickland and Parsons, 1968 and Yentsch and Menzel, 1963). However, the method is time consuming for routine determinations. L13 1119 chlorophyll fluorescence of unextracted algal suspensions is a relatively new technique which is rapid and very sensitive. It can be used to determine growth rates. with a red BeI ‘ris procedure equipped with one is direct! {1965), Stri« :ethod statin. seasuements, Galorophyll c extraction for] tive than the ATE (ads: tions has not becoming used Since bacteri making direct Sorokin and I the PrinCiple “T3 molecule ; 885MB can be light eZlissio: “Wants and enzyme, 11mm traCtg. Th:- ofldt it megsm of — m aléa‘Ill b1 22 Lorenzen (1966) used the in 1112 method on a fluorometer with a red sensitive photomultiplier which he reported to increase the sensitivity by a factor of ten. I investigated his procedure in Experiment 2, but with a fluorometer unp equipped with a red sensitive photomultiplier. For details one is directed to the AAP, Lorenzen (1966), and Strickland (1968). Strickland adds a precautionary note to Lorenzen's method stating light scattering, as in optical density measurements, can add to the recorded fluorescence values. Chlorophyll can be determined using fluorometry with the xtraction procedure discussed previously and is more sensi- tive than the spectrophotometric method. ATP (adenosine triphosphate) concentration determina- tions has not seen use in algal bioassays. It is rapidly becoming used for aquatic bacterial biomass determinations since bacteria are so closely associated with detritus, making direct biomass determination almost impossible. See Sorokin and Kodota (1972) for details. Briefly, it involves the principle that one photon of light is emitted for each iTP molecule hydrolysed. The concentration of ATP in any sample can be obtained by measuring the intensity of the light emission when the sample is mixed with the proper reactants and enzyme. The reactant, luciferin, and the enzyme, luciferase, are obtained from firefly lantern ex- tracts. The advantage of the ATP-bioluminescent method is that it measures only living material. In advanced stages of an algal bioassay one is unsure if all cells are viable. The ATP method : micrograms of A' or biomass. '1'}: growth and woul where viable a: 13%. Algae 1m (Sweeney, 1970 Total earl have not found most laborator Goldman ( 5°: a18311 bioa Since 11; is a the algae, Re bioassays 1t 1 tie activity . Kins (19‘ f°llow daily cult111-es. By carbonate m a. ..os this, a 23 The ATP method is sensitive. for a work range of 10"3 to 10"7 micrograms of ATP and can be calibrated to total cell carbon or biomass. This method could be used to measure daily growth and would be especially useful for toxicity bioassays where viable and nonliving cell ratios may be rapidly chang- ing. Algae have been used to bioassay various pesticides (Sweeney, 1970). Total carbon determinations, although very sensitive, have not found extensive applications for algal bioassay since most laboratories are not equipped with a carbon analyzer. Goldman (1963 and 1968) uses radiocarbon procedures for algal bioassay. This method deserves more extensive use since it is a direct measure of the metabolic activity of the algae. Recently,Kerr (1972) suggested for nonpaxenic bioassays it is open to great error due to dilution of speci- fic activity by carbon dioxide produced by bacteria. ‘King (1972) uses perhaps the simplest technique to follow daily growth. He monitors daily pH changes in closed cultures. By knowing the initial alkalinity, he can determine carbonate alkalinity decreases from the pH measurements. From.this, growth rates can be calculated. 313333115 1"} The exper The data and g concise fashic treatment rep: the treatment would depict . one figure, 0f replicatio; C'ilI'Ves fol. ea The numb rm. To Comp em t0 1 tes Heed tests, 5 Hemamxeuls might haVe be 0f QXperimEnt (CV) and is E the 339811 “Sue below has bee for bioaSSay l EXPERIMENTS INVESTIGATING SOME SOURCES OF ERROR IN THE ALGAL BIOASSAY PROCEDURES The eXperiments are presented in the order performed. The data and growth curves are not presented in the most concise fashion. For instance, a growth curve for each treatment replication is depicted in the figures. Normally, the treatment replication data would be averaged and figures would depict one mean growth curve for each treatment all in one figure. For this study, it was hoped a visual comparison of replication precision would be achieved by giving growth curves for each treatment replication. I The number of statistical tests has been kept to a mini- mum. To compare means the Student's t test (hereafter short- ened to‘t test) was used exclusively. Other less commonly used tests, such as Duncan's Multiple Range test, Student- NewmanéKeuls test, and Least Significant Difference testing might have been used. The statistic used as the indicator of experimental precision was the Coefficient of Variation (CV) and is simply one standard deviation (SD) divided by the mean usually expressed in percent. Cv of 15 percent and below has been suggested as the acceptable level of precision for bioassay (Toerien et al., 1971). When testing for significant differences between means, 24 f j the difference the confidence confidence leve is to decide or The first systematic var: ments are appl: 25 the difference is reported as not significant (ns) only when the confidence level is below 50%. Otherwise, the difference confidence level will be reported if above 50% and the reader is to decide on the significance. The first eight experiments are attempts to minimize systematic variances in the procedure. The last six experi- ments are applications of the procedure. ‘3' ‘itzis‘r ‘.'—Ir This exp-e: hate sources 0 later chamber aPPTOXinate di nation factor Sis Of Varianc -esig A Nested noMum's are Variance comp: Y . “here Y. 135 u Experiment 1 Cell Counting Error Purpose This exPeriment attempted to locate, study, and elimi- nate sources of variability in counting algal cells. Five Palmer chambers were compared. The manufacturer gives only approximate dimensions of chamber volumes with no error esti- mation factor (volume given as 0.1 ml or 100 mm3). An analy- sis of variance is called for. Desigg A Nested Analysis of Variance is used. The statistical notations are those used by Sokal and Rohlf (1969). The variance components tested were Yijk = u + C1 + Rij + Mijk where Yijk = sample mean (observed mean), u = population mean (true mean), C1 = effects of counting chambers, Rij = effects of samples within chambers, and Mijk = effects of counts within samples. Five chambers were used for the analysis. Counting consisted of two samples per chamber from a single Selenastrum' culture with five countings per sample. A "count" is a cell number determination under a Whipple micrometer grid at 100x 26 magnification. cells per ml 8 So the mean is The nesting of Table 3. Cell how Rune witl Chamber Chan \F‘ i.) / \J‘l -P- \)J {\J —‘ ' I 27 magnification. The cells per grid were not transformed to cells per ml since transformations do not affect variances. So the mean is: Yijk \£:counts (measurement) m = 5 as k = 1,2,3.4,5 sampling -(run) r = 2 as j = 1,2 chamber 0 = 5 as i = 1.2.3.4,5 The nesting of the data is shown in Table 3. Table 3. Cell counts for a Nested Analysis of Variance show- how the data is nested. Runs Measurements within within Run Chamber Chamber (cells/grid) Yii. Yi.. Y.L. 1 1 96, 97,110,121,104 528 2 136,116,112,118,119 601 1129 2 1 123,174,15091399159 745 2 103. 95.110,116,128 552 1297 1 93,116,122,127.135 593 3 2 108,130,140,128,121 627 1220 1 ' 143.143.137.134,143 700 4 2 93,120,121,112,126 572 1272 1 132.122.125.153.131 663 5 2 107. 99.139.105.104 554 1217 6135 2 bid /m = 3808161/5= 761632. 2 Yijk = 768473. 0 Rfi = 7544323/1o= 754432. 3 correction term (CT) = Y. /mrc= 37638225/50: 752764.5 Mtotal ngk - CT = 76847300 - 75276405 = 15708.5 530 = Y2 /mr - CT = 754432.3 - 752764.5 = 1667.8 es? = Y2; o/m -lom - ss = 761632.2 - 752764.5 (C) 2 C - 1667.8 = 719909 FSM(R0)= rijk - CT - ssC - 533(0) = 76e473.0 - 75276405 - 1667f8 - 719909 = 6840.8 ‘k'_“WWx. an Table 4a. 81;!“ r SOURCE SS D1m “'3 “ 0L2“ 2' . M items. Chamber SS, 28 Table 4a. Symbolic Nested Analysis of Variance to study the variance in cell counting by defining the effects due to counting chambers, samples with- in chambers, and grid cell counts within samples. SOURCE SS df MS EMS Chamber SSC (c-1) SSC/(c-1) <1; + mag + erE a 2 Run ”SR c(r-1) SSE/C(r-1) 6M + mag Meas. SSM cr(m-1) SSM/cr(m-1) Ufi TOtal SSTOtal (N-1) Table 4b. Numerical Nested Analysis of Variance to study the variance in cell counting by defining the effects due to counting chambers, samples with- in chambers, and grid cell counts within samples. Chamber 1667.8 4 416.95 0.289 ns Run 7199.9 5 1439.98 8.420 *** Meas. 6840.8 {39 171.02 FTotal 15708.5 49 ** ***F .001(4.5) = 31" .001(5.40)= 5'13 F.O1(4,5) = 11.4 **F.o1(5.40) = 3'51 *F.05(4.5) = 5'19 R _ F.05(5’4O) — 2045 Variance Components - 0% due to Chambers - 60% due to Runs within Chambers - 40% due to Measurements within Runs ***F Results The analysis in Table 4a,b indicates no significant difference exists between counting chambers difference exists between runs within a chamber at a 99.9% confidence level. Variance 0 :pc mariance ue i to measuremen‘ Either t' m (maple) ed counting. aelysis 0i 1 freedom in b1 given in ”22‘s Table 5. lie I] CC CE NE 8.] 29 Variance component calculations indicate there is more variance due to runs (sample taken from one bottle) than to measurements (cell counts) within a run. Either the technique of withdrawing and preparing a run (sample) needed improving or more runs per chamber need- ed counting. To check on the latter possibility a second analysis of variance was conducted with more degrees of freedom in both Runs and Measurements. The results are given in Table 5. Table 5. Nested Analysis of Variance studying the variance in cell counting by defining the effects due to counting chambers, samples within chambers, grid cells within samples. The degrees of freedom were 4, 20, and 225 respectively compared to 4, 5, and 40 from Table 4b. "OURCE 6‘8 df MS F D u § Chamber 1092.42 4 273.11 1.55 ns Run 3516.48 20 175.82 4.34 *** Meas. 9112.10 ‘222 40.50 Total 13721.60 249 ***F F.05(4.20) = 2'87 **F.01(4.2o) = 4'43 .001(4,20)= 7'10 The analysis in Table 5 indicates no significant diff- erence exists between chambers and a difference exists bet- ween runs within a chamber at a 99.9% confidence level. This suggests the technique rather than the degrees of freedom was responsible for the unwanted variance due to withdrawing and prepar'ng a m: technique was < The metho: to (1) swirl t"; cell suspensioz capillary drop in the Chi‘filber let the C8118 . the bottom Of . then the . occured in the suspension was COVGI‘ slips WC about the time was BusPeczted SiIICe "floater In); r028 °f Cell 2933 cell Suso on the chamber and (4) 1 tion of t n3601; he Ce r: able 5 is an m. Able 6 1 teen Chambers 011 ‘ Dre E: h P I‘i“g W 3O preparing a run sample for counting. A closer look at the technique was called for. The method used to prepare a chamber for counting was to (1) swirl the flask about fifty times to insure an even cell suspension, (2) withdraw a sample with a long stem capillary dropper, (3) place a few drops of cell suspension in the chamber, (4) place a cover slip over the chamber, and (5) let the cells settle for a few minutes so they are all on the bottom of the chamber. When the cells were allowed time to settle, evaporation occured in the chamber. Therefore, a slight excess of cell suspension was placed in the chamber so that the cover slips floated. Upon cell settling and subsequent evaporation the cover slips would come in contact with the chamber walls about the time the cells had completely settled. This method was suspected (after the results in Table 5) to cause error since "floaters" produce unequal chamber volumes. A modification in the method involved (1) placing a few drops of cell suspension on the chamber, (2) withdrawing ex- cess cell suspension from the port so the cover slip was snug on the chamber wall surface, (3) allowing cells to settle, and (4) injecting distilled water into the port upon evapora- tion of the cell suspension, but not overfilling the chamber. Table 6 is an Analysis of Variance that used the modification. Table 6 indicates no significant differences exist bet- ween chambers or runs within chambers. The modified method of preparing chambers eliminated the variance due to runs 31 within chambers. This puts all the variance in counting, which is desirable since one can control the error by simply counting more grids per run. (However, when the cells per grid is very low, such as less than ten cells per grid, one has very little control over variance. The cells are distri- buted in a Poisson distribution according to Appendix A.) With a significant portion of the variance due to poor techni- que, as was the case for Table 4b and 5, one has very little control over error. Table 6. Nested Analysis of Variance studying the variance in cell counting by defining the effects due to counting chambers, samples within chambers, and cells within samples. The degrees of freedom were 4, 20, and 100 respectively. fiaaaaaEEaaaaaaaaaEaaaaEaaaaaaaaaEEaaaaaEaaaaaaaaaaaaaaaaaaaaaaa SOURCE SS df MS FS Chamber 251.41 4 62.85 1.52 ns Run 898.08 20 44.90 0.104 ns 21% 4556.80 L92 433.68 Total 5486.29 124 * F.05(4’20) = 2.85 **F.O1(4,20) = 4043 ***F.OO1(4,20) = 7010 *F.05(20.120)= 1'66 **F.o1(20.120)= 2'03 ***F.001(20.120)=2‘52 Variance Components - 0% due to Chamber - 0% due to Runs within Chambers - 100% due to Measurements with Runs Conclusion By using a Nested Analysis of Variance an unwanted source of error in cell counting was located, identified, and eliminated by modification of procedures, J' ‘k4‘i9w- ! Correl: Chlorophyll “Spensions ing daily 2 Procedure A 3911 § an initial 2.20z10'5 c fluoregcen concentrat Cell dilution 2 counts We] (Tables 7 0kilo: Experiment 2 Correlations between cell counting, iggzng chlorophyll fluorescence. and optical density measured 0W cell suspensions Purpose Correlations were made between cell counts, ipwzizg chlorophyll fluorescence, and optical density of cell suspensions to determine if a indirect method of monitor- ing daily Selenastrum growth could be used. Procedure A Selenastrum stock culture was diluted nine times from an initial concentration of 3.64x106 cells per ml down to 2.20x105 cells per ml. Cell counts, optical density, and fluorescence were measured on each of the ten different cell concentrations. Cell counting consisted of counting two samples per dilution and twenty micrometer grids per sample. Expected counts were calculated and compared with the observed counts (Tables 7 and 8). Chlorophyll fluorescence was measured using an in;zizg method with a Turnex’, Model 111 fluorometer. Lorenzen (1966) used the method on the same fluorometer, Specially equipped with a red sensitive photomultiplier tube and blue lamp light source, to measure the chlorophyll within phytoplankton 32 ' Y 4 l 1. - _ wry-I“ ['3‘ 1W- 6. .w; cells from lak increases the Lorenzen and a* recently in t'r. For this studyI without the re tion. Since L (natural smpl the ten fold l The cell suspe filters (red a I‘escence was 1» the fluoresce ‘ thirty Since 1 sensitivity 86 Optical c suspenSions 11: length of 680 lists the flu Cflcufflted fl" (*1 ion °°effici 33 cells from lake samples. The modification to the fluorometer increases the sensitivity by a factor of ten according to Lorenzen and also Turner (1975). Many have used the method recently in the field due to its sensitivity and simplicity. For this study attempts were made to use the Ephzizg_method without the red sensitive photomultiplier or blue lamp adap- tion. Since Lorenzen was working with very dilute samples (natural samples) relative to bottle cultures, it was hoped the ten fold loss in sensitivity would not be realized. The cell suspensions were placed in sample holders, matched filters (red and blue) were placed in the fluorometer, fluo- rescence was measured, and readings were recorded. To obtain the fluorescence units, the readings are multiplied times thirty since the fluorometer was operated at the maximum sensitivity setting of 30x. Optical density was measured directly on the cell suspensions with a Baush & Lomb, Spectronic 20, at a wave- length of 680 nm and a sample cell width of 1 cm. Table 7 lists the fluorescence and optical density readings. Results The correlation coefficients listed in Table 8 were calculated from the data in Table 7. A statistical table (Bailey, 1959) gives the probability of observing a correla- tion coefficient greater than 0.872 for eight degrees of free- dom as 0.001 or 0.1%. The smallest of the five calculated here was 0.988, showing the high degree of correlation for Table 7. I c c Eilution I . 8 c ratio stock 4:1 3:1 2:1 1:1 1:2 1:3 1:4 1:8 a ExpeCted peCted a Gee Fig; 34 Table 7. Data from cell counts, optical density, and in vivo chlorophyll fluorescence measured on ten dilations of a Selenastrum cell suspension. —- --.~....._. .._-—-—.- .._ - n- . - _..._- __ —-..—__.._ wilution Percent Expected Observed Fluorescence Optical ratios of stock cells/ml cells/ml readings density stock 100 3.64x106 3.64x106 100.00 0.139 4:1 80 2.91x106 2.79x106 84.93 0.102 3:1 75 2.73::106 2.63x106 78.25 0.096 2:1 67 2.40x106 2.19x106 78.88 0.089 1:1 50 1.82x106 1.57x106 55.13 0.067 1:2 33 1.20x106 1.28x106 40.75 0.044 1:3 25 9.10x105 8.40x10S 27.85 0.020 1:4 20 7.30x105 7.50x105 19.88 0.009 1:8 12% 4.40x105 2.60x105 5.50 0.009 1:10 4 2.20::105 2.40x105 2.60 0.011 Table 8. Correlations between expected cell counts, observed cell count, in vivo chlorophyll fluorescence, and Optical density measured on ten dilutions of a Selenastrum cell suspension. t W Variables Compared Coefficient ———-1 Observed - Expected Cell Counts 0.995 aObserved Cell Counts - Fluorescence 0.991 aObserved Cell Counts - Optical Density 0.988 Expected Cell Counts - Fluorescence 0.991 Expected Cell Counts - Optical Density 0.992 aSee Figures 2 and 3. 110 . 100 , 98 n. no AU AU ORAN/05 43 Uflfipdoh MOZMOWWMODRM 0 2 o 11 O FLUORESCENCE reading 110 100 90 80 70 60 50 40 50 20 10' 35 Figure 2. fl Y = 32.99X - 2.25 . IJAAIAAILIIAALAALA4L 1.0x106 2.01106 3.0x10 CELLS per ml. 6 The straight-line relationship between observed cell counts and in vivo chlorophyll fluorescence with regres- sion equation. OPTICAL DENSITY reading OPTICAL DENSITY reading 36 .110 . .100 , .090 . .080 . .070 b .060 l .050 . .040 . .030 , .020 .. .010 . . Y = 39.96 - 6.19 1 .000 ........ l i .-.n’lnn-.lln- 0 no??? 232x10 3.02706 CELLS per ml. Figure 3. The straight-line relationship between observed cell counts and optical density with regression equation. .___.—.p- ! -..-- . . the conpariso: Fig-“ares cell counts 2 against fluor the lower det 1:1 132 cells Conclusions It was calibrated t of daily Spe be indirect] using M 104 and 105 occurrinb a could be us haVe used ‘ Optical de: assays. E liar with Optical d e 37 the comparisons made. Figures 2 and 3 depict the relationships between observed cell counts against optical density and observed cell counts against fluorescence. It is apparent from the figures that the lower detection limit for both instruments is approximate- ly 105 cells per ml with the methods tested here. Conclusions It was hoped fluorescence or optical density could be calibrated to cell counts thus allowing the growth parameters of daily Specific Growth Rates and Maximum Standing Crops to be indirectly determined. The AAP found most algal bioassays using Selenastrum have the‘flmax occurring between counts of 104 and 105 cells per ml and the Maximum Standing Crops occurring above counts of 105 cells per ml. Both methods here could be used to determine standing crops. Many experimenters have used with success, Maximum Standing Crops measured by optical density as the only growth parameter for algal bio- assays. However, a purpose of this study was to become fami- liar with algal growth rates. Therefore, fluorescence and optical density were not used in subsequent experiments since they were not sensitive enough for the results desired. To increase the sensitivity of optical density others have used optimum cell widths (Myers, 1962; Yentsch and Men- zel, 1963; and Yentsch, 1957). To increase the sensitivity of fluorescence a red sensitive photomultiplier must be installed on Turner fluorometers. Another method involves concentrating the cells before making measurements. 4.!1 e; 4'! E.lects 1 * figowth Primer: Selenastrnz; K COllecting, eiPerizents 59118 itiVi‘tv Phosbhate. Desigg Ortho pf 38 Experiment 3 Effects of four levels of orthophosphate on Sglgnagirgm growth for familiarization with bioassay procedures BHIEOSG Primarily, this experiment was for familiarization with Selenastrum culturing, handling, growth measuring, and data collecting. Problems were noted and used to design subsequent experiments. Secondarily, the objective was to determine the sensitivity of the bioassay procedure to low levels of ortho- phosphate. Desigg Orthoph08phate was bioassayed at four levels of 0.00, 0.01, 0.02, and 0.03 mg P/l. Each treatment level was run in four replications. Cell counts were used as the growth indicator. Procedure The control treatment was the AAP nutrient medium minus potassium phosphate. Potassium chloride was added to give potassium to the medium at the concentration shown in Table 1. The other three treatments each had potassium phosphate added in amounts which gave the desired phosphorus concentrations. A six-day-old stock of Selenastrum.was used as inoculum. The cells were washed and resuspended in a weak bicarbonate solution ( are prep-'11“ Ill of 111001 about 1x10‘ calibrated treatments . squares whi Cell c This consis twenty micr: the desired 2187-385 treatment re 0‘3 Variation tables B1, 3 cell Counts counting tee: then the eel: alparent 13h 8 cells Der gr are 1212 (the 2‘ ‘ “he 4’°isson chm”. so calCUlat e S 't 39 solution (15 mg NaHCOB/l) to minimize nutrient carry-over. The prepared inoculum was counted and it was determined 0.55 ml of inoculum should give an initial cell concentration of about 11:104 cells per ml. Inoculum delivery was done with a calibrated 1-ml pipet into fifty ml of one-day-old media treatments. The flasks were randomly inoculated and allotted to the assay platform squares using sixteen of the forty squares which were closest to 400 ft-c. Cell counts were determined on day O,1,2,3,5,6, and 10. This consisted of taking two samples per flask and counting twenty micrometer grids per sample. From the cell counts the desired growth parameters were determined. Results Figures 4a,b,c,d depict the growth curves for each treatment replication. The cell counts and Coefficient of Variation for counting (CV) are given in Appendix B tables B1, B2, BB, and B4. The Cv values decrease as the cell counts per grid increase. This may be due to the counting technique rather than the state of the cultures. When the cells per grid are less than about ten, it is apparent the CV values are generally above 40%. When the cells per grid are greater than about thirty, the Cv values are 15% (the desired level) or lower. Appendix A discussed the Poisson nature of distribution for cells in a counting chamber. For cell counts above ten, the standard deviation calculates to be nearly equal for Poisson and normal distri- butions. standard d was calcul normal dis leading Cv grid range The c cation. I; since they numbers wa: suggested : Table Dent replic between (133 Table in three F at 955; com- differenceS increase as correlation differenCes are all 8:001 level of pm Table 1 Differences 0M 1” v70 find 95% 4O butions. However, when the means are below ten or so, the standard deviations differ more. For this study, the Cv was calculated from standard deviations calculated from the normal distribution formula. This may have resulted in mis- leading Cv values for cell counts in the less than ten per grid range. The cell count tables show the maximums for each repli- cation. In many instances they are not the absolute maximums since they are the last count for which an increase in cell numbers was above five percent per day. This is the procedure suggested in the AAP. Table 9 gives daily Specific Growth Rates for each treat- ment replication. The maximums are underlined and occurred between days 1 and 3 for all replications. Table 10 gives the‘flmax for each treatment replication. All three phosphorus treatments responded over the control at 95% confidence levels, however, there were no detectable differences between the levels of phosphorus. The'fihax values increase as the levels of phosphorus increase, suggesting a correlation. Experimental error may not have allowed the differences in treatment levels to be detected. The Cv values are all above 15% (15% to 38%) which is not an acceptable level of precision according to Bliss (1952) for bioassays. Table 11 gives the Maximum Standing Crops in cell numbers. Differences were detected between phosphorus treatments at 90% and 95% levels except for one comparison. Phosphorus 41 * L.w_._-! Figure 4. Growth curves for Selenastrum from a ten day bio- assay of the effects of four levels of phosphorus in the AAP medium. a. Page 42 - The 0.00 mg P/l treatment run in four replications. b. Page 43 - The 0.01 mg P/l treatment run in four replications. c. Page 44 - The 0.02 mg P/l treatment run in four replications. d. Page 45 — The 0.03 mg P/l treatment run in four replications. CELLS por ml. 10 111illrn 10 IIIII' fl, 10.. 10 IO CELLS per ml. 10 IO 1 2 42 3 4 5 6 TIME IN DAYS Figure 4a 7 0 1 l... .7: con wimU 104 10 IO CELLS per ml. 104 d 2 43 3 i... 4 3 4 5 6 7 8 910 TIMEINDAYS Figure 4b 10" 6m wig?» . it .35. Waqu 5m 10‘ IO CELLS per ml. 10 10 l 2 44 a ——-o 3 4 5 6 7 8 910 TIMEINDAYS Figure 4e fl.rbfp Flhll 107 —F.LlEl _ 0 I .7: Lou wqumU E «W 104 IO CELLS per ml. 5,. 10 l 2 45 3 4 5 6 TIME IN DAYS Figure 4d 7 9 IO - a" Table y. .1‘ C) (’3 46 Table 9. Effects of four levels of phosphorus (0.00, 0.01, 0.02, and 0.03 mg P/l) on Selenastrum daily Specific Growth Rates for a ten day static bioassay. SPECIFIC GROWTH RATES cu/day) Time Control (no P) Control + 0.01 mg P/l (Days) 1 2 3 4 1 2 3 4 O 0.25 b0.00 0.32 0.00 0.50 0.63 0.70 0.23 1 a0.65 0.00 0.41 gggg 0.53 0.37 1‘29 gggl 2 0.00 gggg ‘gggz 0.23 Qggg 9‘11 0.65 0.58 3 0.00 0.00 0.00 0.03 0.20 0.12 0.12 0.26 5 0.00 0.00 0.00 0.00 0.05 0.08 0.11 0.05 1: 0.00 0.00 0.00 0.00 0.03 0.00 0.00 0.00 Time Control + 0.02 mg P/l Control + 0.03 mg P/l (Dare) 1 2 3 4 1 2 3 4 O 0.23 0.92 0.59 0.84 0.62 0.64 0.54 0.68 ; 0.49 0. 8 9‘15 1.1 0.27 ygggg 0.7 0.57 9:14 0.71 0.69 0.67 1‘55 0.53 0.48 eggs 3 0.55 0.40 0.35 0.37 0.78 0.36 0.25 0.30 5 0.39 0.09 0.17 0.17 0.25 0.37 0.22 0.21 1: 0.09 0.00 0.03 0.00 0.01 0.07 0.07 0.07 aSpecific Growth Rates of 0.00 have been recorded for values of 0.00 or less. hUnderlined values are the maximums for each repli- cation. Table 10. Rep. Number 47 Table 10. Effects of four levels of phosphorus (0.00, 0.01, 0.02, and 0.03 mg P/l) 0n Selenastrum Maximum Specific Growth Rates with Cv and 1 testing. MAXIMUM SPECIFIC GROWTH RATE (flhax) gfigber Control Control + Control + Control + (no P) 0.01 mg P/l 0.02 mg_P[l 0.03 mgP/l 1 0.65 0.88 0.74 1.44 2 0.34 0.77 0.98 0.64 3 0.43 1.06 0.75 0.75 4 0.56 0.81 1.14 0.88 Mean i 130 0.50 i 0.14 0.88 i 0.13 0.90.: 0.19 0.93 i 0.36 Cv 27% 15% 21% 38% at test 14:2 at 95% level 2 vs 3 is ns (onELtailedl 1<:3 at 95% level 2 vs 4 is ns ° 1<:4 at 95% level 3 vs 4 is ns aOne-tailed test since growth stimulation was expected. Table 11. Effects of four levels of phosphorus (0.00. 0.01, 0.02, and 0.03 mg P/l) on Selenastrum Maximum Standing Crops in cells/ml w v and 3 testing. MAXIMUM STANDING CROPS in cells/ml Esgber Control Control + Control + Control + (no P) 0.01 mg P11 0.02 mg P/l 0.03 mg P/l 1 4.9x104 2.422105 5.6x105 2.0x106 2 6.3x104 4.4x105 9.8x105 7.2x105 3 1.9x104 3.9x105 6.2x105 4.7x105 4 2,6x104 5.0x10E 1.0;:106 7- x105 Meanl: 1SD 3.9x1044 3.9x1055 7.9x1055 9.8x1055 i2.0x10 i1.1x10 i2.3x10 i6.9x10 Cv 52% 28% 29% 69% t test 1<2 at 99% level 2<3 at 95% level (onE-t'liled) 1<3 at 99% level 2<4 at 90% level ‘ 1<4 at 95% level 3 vs 4 is ns aOne-tailed test since growth stimulation was expected. 48 treatments responded over the control at 99% levels. The Cv values are again all above 15% (28% to 69%) indicating poor precision for this growth parameter. Conclusion Miller and Maloney (1971) reported Selenastrum responded to phosphorus levels as low as 0.01 mg P/l using the AAP procedures. This eXperiment supports their finding. Maloney and Bartsch (1969), as well as others, reported algal bioassay was as sensitive in many cases as chemical determinations. Sensitivity, not to be confused with the detection limit, is the ability to detect a difference bet- ween two close levels of the same substance. The closer the levels are to being equal with differences detectable, the more sensitive is the measuring device (Skoog and West, 1971). This experiment showed the bioassay has the potential to be very sensitive. However, before I can place as much confi- dence in a bioassay (for phosphorus) as in a chemical deter- mination, I will have to further reduce experimental error. This was done in the following experiments by identifying and minimizing error sources. Experiment 4 Effects of light intensity ongfiglgnastgnm_gggwth Purpose This experiment attempts to determine the effects of HIGH vs LOW light intensity on Selenastrum growth rates and standing drops under bioassay test conditions. Design The treatments were HIGH intensity of 475 ft-c (5111 lux) and LOW intensity of 260 ft-c (2798 lux). The AAP gives 400 ft-c (4304 lux) as the optimum intensity for Selenastrum growth. Each treatment was run in five replications. Cell counts were used to assess growth. Procedure The inoculum was prepared in the manner discussed previ- ously from a six-day-old stock culture. The inoculum was counted and it was determined 0.13 ml of inoculum delivered to fifty ml of medium should give an initial cell concentra- tion of 103 cells per ml. Ten 125-ml Erlenmyer flasks were given fifty ml portions of sevenpday-old AAP medium that had been stored in the dark (as suggested by the AAP) to prevent any photochemical reac- tions to the medium. Each flask was randomly inoculated from a calibrated 1-ml pipet with 0.13 ml of inoculum. 49 50 Cell counts were made immediately after inoculation and on days 1,2,3,4, and 6. Cell enumeration involved counting two samples per flask and ten micrometer grids per sample. Results Appendix table BS lists the cell counts for each treat- ment replication. It was apparent the method used to deliver the inoculum was in error from the counts recorded immediately after inoculation. Initial cell concentrations ranged from 6.4x103 to 7.0x104 cells per ml. Figures 5a and 5b depict this initial error and how it subsequently resulted in poor growth curve precision between treatment replications. The figures also depict "abnormal" growth curves. Only replication 4 (see also Appendix table B5) of the HIGH inten- sity treatment gave a "normal" growth curve by going through a logarithmic phase, indicative of nutrients present initially in unlimiting amounts (Pringsheim, 1946). The other cultures do not go through a logarithmic growth phase, suggesting some factor or nutrient was initially limiting algal growth. To test if some nutrient was limiting growth, two dr0ps of the seven AAP stock solutions were added separately to seven aliquots of replication 2 of the HIGH intensity treat- ment on day 6. Counts were then made on days 7,8,9, and 10 for the seven aliquots. Table 12 lists the cell counts. A significant growth response at a 99.9% confidence level was obtained from the TRACES treatment. This is depicted in Figure 5b. The other six no-effect treatments have not been graphed separately since they gave no significant responses, Figure 5. a. b. 51 Growth curves for Selenastrum from a six day bio- assay of the effects of two levels of light inten- sity on growth. Differences were judged not detect- able due to methodological errors. Page 52 - HIGH intensity treatment of 475 ft-c (5111 lux) run in five replications, showing poor precision for initial cell concentrations and no cultures going through a logarithmic growth' phase except for one replication. The response to the TRACES stock added on day 6 is shown. The average response of the other stock nutrients is also shown. This suggests TRACES are limiting algal growth. Page 53 - LOW intensity treatment of 260 ft-c (2798 lux) run in five replications, showing poor precision for initial cell concentration and no cultures going through a logarithmic growth phase. CELLS per ml. 52 HResponse to one drop of TRACES stock. Average response to one drop of the o——-o six macronutrient stocks. 12345678910 TIMEINDAYS Figure 58 CELLS per ml. 5t. 10 y 103 l 2 53 3 4 5 6 TIME IN DAYS Figure 5b 7 9 10 54 Table 12. Cell counts of seven aliquot portions of a seven- day-old culture. Each portion was treated with one of the seven nutrient stock solutions used to prepare AAP medium to determine if a stock nutri- ent was limiting growth. Treatment solution nutrients (counts in cells/ml) a NaNO3 KZHPO4 Mg012 MgSO4 Ca012 NaHCO3 TRACES C>xo a1-o ox Q:mtd : 6.9x1016.9x104 6.9x104 6.9x1046.9x104 6.9x104_6.9x104 6.9x104 7.1x104 6.8x104 7.0x104 7.2x104 7.1x104 8.4x104 7.0x104 7.2x104 6.8x104 7.1x104 7.6x104 7.1x104 3.2x105 7.1x104 7.4x104 6.7x104 7.3x104 8.2x104 7.4x104 8.2x105 7.0x104 7.6x104 6.9x104 7.5x104 8.7x104 7.9x104 1.2x106 aTRACES is a stock solution containing a mixture of all the trace elements used to prepare AAP medium. TRACES was the only treatment giving a significant response according to t testing. Table 13. Cell counts of seven aliquot portions of a ten- day-old culture. Each portion was treated with a trace element solution to determine which element in the stock of TRACES was limiting growth. +_- - aTreatment solutions of trace elements (cells/ml) EEBO 2 Mn012 ZnCl2 00012 Cu012 FeClz Na2M004 1 .7x101 1 .7x104 1 .7x104‘1Jx104 1 .7x104 1 Jx104 1 .7x104 1.9x104 1.6x104 1.9x104 1.8x104 1.9x104 1.7x104 1.7x104 2.1x104 1.7x104 2.4x104 1.6x104 1.6x104 2.1x104 2.0x104 aNone of the trace treatments gave a significant response according t°.I testing. however they 5b for comps An atte trace elemen TRACES mixtu concentratio of each trac of replicati Counts were not ShOWn gr treatments g W | An atte light inteng to methOdolgl The prq gave high Vz expected C0! ranged from I1 The me, growth due ‘ upon pI‘Epar properly pl" treatmEnts .. 55 however they have been averaged and are presented in Figure 5b for comparison purposes. An attempt was made to determine which trace element was limiting by preparing a solution for each of the seven trace elements at concentrations found in the AAP stock of TRACES mixture. EDTA was added to each solution at the concentration found in the AAP stock of TRACES. Two drops of each trace element solution were added to seven aliquots of replication 5 of the HIGH intensity treatment on day 10. Counts were made and are listed in Table 13. The counts are not shown graphically since none of the seven trace element treatments gave significant responses. Conclusions An attempt to determine the effects of two levels of light intensity on Selenastrum growth was unsuccessful due to methodological errors. The procedure used to inoculate the culture medium gave high variance to initial cell concentrations. The expected concentration was 103 cells per ml and the observed ranged from 6.4x103 to 7.0x104 cells per ml. The medium was found to be initially limiting to algal growth due to lack of TRACES. This may have been omitted upon preparation of medium, may have been added from an im- properly prepared stock, or may have become unavailable after addition. An attempt to determine if one specific trace element was limiting growth showed no-effect for all trace treatments tested. Experiment 5 Effects of three levels of initial cell concentration Wowth during a bioassay ngpose Experiment 4 indicated that varying initial cell concen- trations possibly resulted in excessive growth curve variance between treatment replications. This experiment will investi- gate specifically the effects of three levels of initial cell concentration on Selenastrum growth rates and standing crops. Design The treatments were three levels of initial cell concen- tration each run in three replications. Cell counts consisted of counting one sample per flask and ten micrometer grids per sample. Procedure The inoculum was prepared from five-daybold stock in the previously mentioned manner. A new delivery method was tested in hopes of obtaining better precision than the pipet method gave. The delivery was done with a long stem capillary dropper. The inoculum treatments were four drops, fifteen drops, and fifty drops. The initial cell concentrations were counted to be 1.68x103, 6.00x103, and 2.1Ox104 cells per ml. This gave a ratio of 1:34:124 which was approximately 56 57 equal to the treatment ratio of 4:15:50. Therefore, it was apparent the drops were uniform in volume and that the dropper method was an improvement over the pipet method for delivering inoculum. Results Cell counts are listed in Appendix table B6 for the replication averages of each treatment. These counts were used to depict the growth curves in Figure 6. It shows the growth curves are shifted to the left on the graphs as the initial cell concentrations were increased. This caused the ‘Mmax to occur earlier in the assay. It is not desirable to have theMmax occur between days 0 and 1 since there is high counting error on day 0 as discussed previously in this study. Therefore, Figure 6 suggests the initial cell concentration for bioassays should be below 104 and close to 103 cells per ml if the test alga is Selenastrum. Table 14 shows the effect of increasing the initial cell concentration was to cause/4E]ax values to increase. If experiments are to be compared, it is apparent the inocula- tion size must be carefully controlled whenfiinax is the growth parameter. Table 15 shows the three levels of initial cell concentration had very little effect on Maximum Standing Crops. Conclusions The initial cell concentration in an algal bioassay can effect growth rates. This may be one reason why the eight- laboratory evaluation of the Provisional Algal Assay Procedure era 4 Figure 6. 58 Growth curves for Selenastrum from an eleven day bioassay of the ef cc 8 o ree leve s of initial cell concentration (1.68x10 , 6.00x10 , and 2.10x104 cells per ml) on growth. CELLS per ml. IO IO '5' U1 10 10 1 _ 2 3 4 TIME 59 5 6 7 IN DAYS Figure 6 8 9 10 6O Table 14. Effects of th ee levels3 of initial 08 l concentra- tion (1. 68x10 6. 00x103 , and 2.10x10 cells per ml) on Selenastrum daily Specific Growth Rates for an eleven'daybioassay with treatment replications averaged and t testing on theA values. are numbered as 1,2,3 respectivEI§. Time SPECIFIC GROWTH RATE cfl/day) (Days) Treatment 1 Treatment 2 Treatment 3 O a 0.24 0.77 2.2 1 a 1.13 1. 2 1.66 2 1.31 1.41 1.00 3 a 1.70 1.46 0.30 4 '“"' 1.15 0.49 0.15 5 0.64 0.00 0.00 7 0.00 0.00 0.00 11 aMaximums compared by‘t testing: Table 15. Treatment 1 <1Treatment 2 at the 95% level. Treatment 24<.Treatment 3 at the 95% level. Treatment 1 <.Treatment 3 at the 99% level. Effects of thgee levels of initial ce 1 concentra- tion (1. 68x10 6. 00x103, and 2.10x10 cells per ml) on Selenastrum.Maximum Standing crops in cells per ml wITH t testing. The treatments are numbered ,2 ,3 respecTively. 6 7.4x10g cells/ml 5.4x105 cells/ml 4.2x105 cells/ml Treatment 1 yielded 4.2x10 Treatment 2 yielded 4.8x106 Treatment 3 yielded 5.0x106 I-I- I+ I+ ‘3 testing showed no significant differences. 61 (Bueltman-Chairman, 1969) found high interlaboratory variance and low intralaboratory variance as noted in the Inter-labor- atory Precision Test (Maloney-Deputy Chief, 1971). The PAAP and the AAP give no standardized procedures for inoculating cultures. It is necessary to use the best available method to deliver a precise inoculum and to keep the initial cell concentration near 103 and not above 104 cells per ml for Selenastrum bioassays according to the results of this experi- ment. Experiment 6 Effects of light intensiW (repeat of Exp. 4) Purpose Experiment 6 bioassayed the effects of HIGH vs LOW light intensity on Selenastrum growth rates and standing crops utilizing information gained from Experiments 4 and 5. The variable results for Experiment 4 were attributed to AAP medium lacking stock mixture of trace elements and to Poorly controlled initial cell concentrations for the bioassay. Experiment 6 was an attempt to eliminate these sources of variance. Desigg The treatments of HIGH intensity at 475 ft-c (5111 lux) and LOW intensity at 260 ft-c (2798 lux) were run in duplicate replications with cell counts made on days 0,1,2,3.4,5.6,7, and 11, consisting of one sample per flask and twenty micro- meter grids per sample. On day 4 the LOW intensity treat- ments were divided with one half put in a clean culture flask and placed under HIGH intensity while the other half was re- placed under LOW intensity. Procedure Fresh AAP medium was prepared and randomly inoculated 62 63 with five-day-old stock inoculum cultured and prepared in the usual manner. The inoculum was delivered with a long stem capillary dropper and gave an initial cell concentration of 2-91103.i 1.4x103 cells per ml upon enumeration immediate- ly after inoculation. By day 4 the LOW intensity treatment was noticably growing less than the HIGH intensity treatment. For an internal control, half of the LOW intensity treatment was placed under HIGH intensity illumination on day 4Vto test I if growth could recover and reach the level of the treatment originally placed under HIGH intensity. Results The cell counts are listed in Appendix table B7 from which the growth curves,,qmax, and Maximum Standing Crops were determined. Figure 7 depicts the growth curves. It is evident the internal control fully recovered and underwent a logarithmic growth phase. Table 16 lists the daily Specific Growth Rates. The maximums occurred between days 1 and 3. Table 17 gives the ”max values with HIGH intensity greater than LOW intensity at the 80% level. Table 18 gives the Maximum Standing Crops with.HIGH intensity greater than LOW intensity at the 99% level. Conclusions Light intensity had a marked effect on Maximum Standing Crops and less so on ”max values. A reduction in light inten- Lawn: Figure 7. 64 Growth curves for Selenastrum from an eleven day bioassay showing tEe effects of HIGH and LOW light intensity (474 ft-c and 260 ft-c). Also shown is the response when on day 4 a portion of the LOW intensity treatments was placed under HIGH inten. sity. IO 10 U1 CELLS per ml. 10 IO 2 65 H HIGH intensity treatment - 475 ft-c H LOW intensity treatment - 260 ft-c. 0—-O LOW intensity treatment portion placed under HIGH intensity on day 4. 3 4 5 6 7 8 910 TIME IN DAYS Figure 7 66 Table 16. Effects of two levels of light intensity (475 ft-c and 260 ft-c) on Selenastrum daily Specific Growth Rates for an eleven Hay static bioassay. . . . Q . ' F,— ; SPECIFIC GROWTH RATES CA/day) T1m° LOWIntensitz HIGH intensify (Days) 1 2 1 2 0 0.51 0.65 0.69 0.15 1 0.69 0.55 1.53 2.11 2 ""' 3 81.92 1.9: 1.94 1.91 0.84 0.99 1.55 1.39 4 0.60 0.67 0.97 0.94 5 6 0.55 0.54 0.50 0.60 0.34 0.34 0.06 0.22 7 0.07 0.09 0.00 0.00 11 a'Ma.ximums are underlined. 67 Table 17. Effects of two levels of light intensity (475 ft-c and 260 ft-c) on Selenastrum Maximum Specific Growth Rates with Cv anal: testing. MAXIMUM SPECIFIC GROWTH RATE (#531) Rep. Number LOW intensity HIGH intensity 1 1.92 1.94 2 1.93 2.11 Mean 2.025 i 0.120 1'929.i 0.007 ‘1 1SD Cv 5.9% 0.4% HIGH intensity is greater than 11 teSt L0w intensity at a 90% level Table 18. Effects of two levels of light intensity (475 ft-c and 260 ft-c) on Selenastrum Maximum Standing Crops with Cv and i testffig. MAXIMUM STANDING CROPS in cells/ml Rep. Number LOW intensity HIGH intensit 1 1.1x106 4.4x106 2 1.2x106 4.7x106 Mean 1.15x10g 4.55x102 i,1SD 10.07110 i0.21x10 0v 6% 5% HIGH intensity is greater than ‘3 teSt LOW intensity at a 99% level 68 sity from 475 ft-c to 260 ft-c (about 50%) caused a 75% reduc- tion in the maximum number of Selenastrum cells that could be cultured in a eleven day static bioassay. A LOW intensity treatment placed under HIGH intensity on day 4 recovered by undergoing another logarithmic growth phase, suggesting light intensity was limiting growth. The limiting effect was reversible since the cultures fully re- covered when placed under higher intensity. Whether light should be considered a limiting factor or a tolerance factor is a matter of definition. This has been brought out on page £3 of this study. Liebig (1840) and Odum (1971) defined the "Law of the Minimum" to include only nutri- ents. Taylor (1934) and Ruttner (1963) define the "Law of the Minimum" to include light. If one sees the "Law of the Minimum" as the lower end of Shelford's "Law of Tolerance", then light could be included in both "Laws" since it has been shown excessive light can effect algal growth (Murray et al., 1971) The mechanism is believed to be photooxidation of plant pigments (Odum, 1958; Knutson, no date; and Forsythe, 1972). Because light effects algal growth, it should be carefully controlled in bioassays. When one can not completely control light, as in this study, experimental designs which block out light effects should be used (e.g., Randomized Block Design). Experiment 7 Effects of carbon availability ongfiglgnggtgum growth during a static bioassay Purpose The objective of this experiment was to compare the AAP's suggested methods of insuring carbon availability to static algal bioassays. These methods are continuous shaking, venting air, venting CO2-enriched air, bubbling air, bubbling COZ-enriched air, and using optimum surface to volume ratios for the medium. All but the continuous shaking methods were investigated. Design Six treatments were bioassayed in duplicate replications for eleven days and are shown in Table 19. Specific Growth Rates were determined from daily cell counts through day 7. From the cell counts and dry weights determined on day 11, the "Cell Health" parameter of weight per million cells was calculated. Procedure Fresh AAP medium was randomly inoculated with six-day- 010 stock inoculum cultured and prepared in the usual manner. The inoculum was delivered by a long stem capillary dropper and gave an initial cell concentration of 2.9x103 cells per ml upon enumeration immediately after inoculation. 69 70 Table 19. Treatments of six levels of carbon dioxide vented above or bubbled into Selenastrum cultures to assess the AAP's suggested methods of insuring carbon availability in static bioassays. Treatment Treatment gas and Percent C0 Flow rate of number method of delivery by volume in treatment gas to the cultures treatment gas in cc/min foampplug no gas I stoppered control delivered none II air vented 30.00396 25 III air bubbled 0.003% 5 5% COg-enriched IV air vented 5.003% 25 5% CO ~enriched ’17 air babbled slow 5-0039‘ ‘3 5% CO -enriched VI air babbled fast 5‘003% 50 afromfl'andbook of Chemistry and Physics, Chemical Rubber Co. The pH was measured before the treatments began. All treatments were begun on the day of inoculation and delivered through polyethylene tubing equipped at the end with capillary droppers bent to fit the culture flasks. Flow rates for the treatments were controlled with.small aquarium valves. Flow rates were determined by bubbling the treatment into a grad- uated cylinder filled with water and inverted in a large beaker partially filled with water. The bubbling was done at about one inch below the surface of the water in the beaker and in the cultures so that error due to pressure differences would be minimal. Gas flow displacing the water in the grad- uated cylinder was adjusted until the desired flow in milli- liters (cc) per minute was achieved. 71 Air treatments were delivered using a small aquarium pump. COZ-enriched air treatments were delivered using a 5% COZ-enriched air cylinder equipped with a pressure reduc- ing valve and gauge. Flasks were stoppered with foam plugs. Bubbling was done near the bottom of the cultures and ‘venting was done about two inches above the cultures. An error was noted on day 1 for the flow rate of replication 2 of the air venting treatment (number II in Table 19). The rate was about 50 cc/min and should have been 5 cc/min as replication 1 was. Instead of correcting the flow rate, it was allowed to remain at 50 cc/min. Cell counts and pH were determined on days O,1,2,3,4.5, 6,7, and 11 and are listed in Appendix table B8. Figures 88, b,c,d,e, and f depict the growth curves and Figure 9 summar- izes the pH data. On day 11 dry weights were determined except for three flasks which had undergone excessive media evaporation due to the venting treatments. Aluminum weighing pans were tared by drying overnight at 105°C in a hot air oven and then allow- ed to come to equilibrium overnight in a desiccator having fresh desiccant. The pans were then weighed on a six-place balance and replaced in the desiccator until samples were ready for drying. The cell suspensions were centrifuged and resuspended in distilled water. This was to eliminate error due to varying amounts of suspended and dissolved solids in the medium. From each suspension, two 20 ml samples were pipeted into two tared pans. The samples were then dried =1 w. Figure 8. a. be Co 72 Growth curves for Selenastrum from an eleven day bioassay showing the effects of six levels of carbon dioxide used to insure carbon availability during algal culturing. Page 73 - Page 73 - Page 73 - Page 73 - Page 74 - Page 74 No treatment gas delivered to the culture. Air vented above the culture at 25 cc/min. Air bubbled into the culture at 5 oc/min, with one replications flow rate in error and found to be 50 cc/min. COZ-enriched air vented above the culture at 25 cc/min. COz-enriched air bubbled into the culture at 5 cc/min. COz-enriched air bubbled into the culture at 50 cc/min. 73 i". d 1:... «1 _q:qq.- q _::.d- - 11.—.9 . 7 114.. q d 3:1..4 («Fae-u T Z Time3in Days (:1) 2 E-Fbp PL - —--p_ p n b -..hbb h b —-P- ~ 0 fibpr b b qua q .4 .qqqd1d4 q uu-‘ufidfij dead-«14 4 ,7 «dad a 1 .11111114 #111111 a 1 acrllllllhpunr1 an, .1H1 1H .hemmmoan capwpm on» you mosae> >0 ommaobs nomwmomHmoa one nsonm .aopem assess oamaooam haaee so moaspaso asavmsnoflom on» oped eoappsp no o>onw covso> ouaNoae sonnoo mo maeboa was no evoommm .om magma 79 Table 21. Effects of six levels of carbon dioxide on Selen- astrum Maximum Specific Growth Rates with Cv and _t testing. 3 Control Air Air 002 CO CO vented bubbled vented bu bled bu bled P I II III IV v VI 1 1.94 1.77 1.53 1.82 1.90 1.86 2 2.11 1.67 1.68 1.67 1.43 1.50 1 $10 2.025 1.720 1.605 1.745 1.670 1.680 :18 {i-120 ‘1.071 1.106 ¢.106 $.332 1.255 eV 5.9% 4.1% 6.6% 6.1% 20% 15% T-I > T-II 80% level T-I > T—IV 60% level ‘3 testing T-I > T-III 80% level T-I > T-V 60% level T-I > T-VI 60% level Table 22. Effects of six levels of carbon dioxide on Selen- astrum Maximum Standing Crops as cell numbers wIth C and 2 testing. v R 1 Air Air CO CO CO e Control vented bubbled vefited bu bled bu bled P I II III Iv v 1 4.38x106ano count 4.77x106— 4.441106 3.2ex105' 2 4.67x106 ano count 8.17x106 ano count 4.01x106 ean 4.52x10g 6.47:102 4.44x106 3.64:102 3.09::106 1SD ‘1.20x10 32.40x10 -- ‘1.52x10 ‘:.82x10 0V 4.49% - 37% ' - 14% 27% T-I vs T-III ns :1; testing T-I > T-V 70% level T-I > T-VI 70% level a"No cell count made because of excessive media evaporation due to gas venting. 80 Table 23. Effects of six levels of carbon dioxide on Selen- astrum Maximum Standing Crops as dry weight mIcrograms/ml with CV and 2 testing. 3 Control Air Air C02 CO CO vented bubbled vented bu bled bu bled P I II III IV V VI 1 193 anot weighed 221 369 233 225 2 206 8not weighed 420 anot weighed 441 326 Mean 200 -—- 320 369 362 276 318D 1 9 --- 1141 --- 3112 i 71 Cv 4'5% "‘ 44% -- 31% 26% T-I vs. T-III ns _t_ testing T-I < T-V 70% level T-I < T-VI 60% level a'Not weighed because of excessive media evaporation due to gas venting. Note: Weighing consisted of two 20 ml sample per rep on a six- place balance with the C between the two samples as a 9% average showing the inghing technique was precise. Table 24. Effects of six levels of carbon dioxide on Selen- astrum "Cell Health” a dry weight per millIon cells in micrograms/1O cells with Cv and 3 testing. 2 Control Air Air 002 00 00 vented bubbled vented bu bled bu bled P I II III IV V VI 1 44.1 a-- 46.3 83.1 86.3 89.6 2 44.1 a--- 51.4 39- 109.9 88.8 Jean 44.1 - 48.9 83.1 98.1 89.2 T-I < T-III 60% level T-III < T47 80% level t testing T-I < T-V 30% level T-III < T-VI 95% level " T-I < T-VI 99% level T-V v5. T-VI ns a"Not calculable because of excessive media evaporation. Note: Parameters calculated by taking a value from Table 23 and dividing it by the respective value from Table 22 then multiplying by one million. 81 Table 23 lists the Maximum Standing Crops in dry weights for each treatment not undergoing media evaporation. The control again gave the lowest Cv at 4.6%. The other treat- ments all gave Cv_higher than 15%. The‘t testing showed the bubbled COZ-enriohed air treatments yielded the highest dry weights and the control yielded the lowest dry weights. The trend appears to be that while dry weight increases with inp creasing carbon availability, cell numbers correspondingly decrease. This was visually noted when counting cells. The control's cells were small and irregularly shaped while as the carbon availability increased, the cellS'were more turgid appearing and much larger. No dimension measurements were made. King (1972) also noted this in cultures of Selenastrum and proposed algae respond to low carbon availability by de- creasing their size and increasing their numbers to increase surface area to volume ratios so that carbon dioxide can be more readily taken up by the cells. Table 24 lists the average dry weights per million cells which is an indication of "Cell Health". Again, the control gave the lowest CV. The Cv for the other treatments is lower in this table than all others suggesting the "Cell Health" parameter is a good measure for these assays. Table 26 lists the correlation and confidence levels for comparisons between pH maximums for each treatment and the various growth parameters. The table indicates a very high correlation between pH maximums and the "Cell Health" para- meter. 82 Table 26. Correlation and confidence levels for comparisons between pH maximums reached during the bioassay (this reflects carbon availability) and the growth parameters determined. Variables Compared Correlation aConfidence Coefficient level pH maximum vs Maximum 0.277 ns Specific Growth Rates pH maximum vs Maximum Standing Crops in 0.424 80% cell numbers pH maximum vs Maximum Standing Crops in 0.441 80% dry weights pH maximum vs "Cell Health" in dry weight per million 0.857 99% cells aTaken from tables of Bailey (1959),"confidence levels for correlation coefficients". Conclusions Table 25 summarizes all the Cv data. It is evident the control yielded lower variation than the other methods tested for insuring carbon availability. The parameter for "Cell Health" yielded the lowest variance of the four growth para- meters measured. This suggests the "Cell Health" parameter is good to use when bioassaying carbon availability. It may be good because it combines two parameters and cancels out variances in cell suspension volumes. In this case, the variance caused by excessive media evaporation was thought to be the major source of variance. Murray et al. (1971) the treatment gases through acidified water to humidify the 83 .msapsob mam op can scapegoawbo caves obnmmeoNo mo madness eondsnovoc Pozs .mmos escapees» or» new am.o as. 116 ae.e 116 ao.o eaaee neaaaae pea shade: awe ad :HPHNON HHOO: flflmgmfl O .maon assesses» o3» so“ Rom arm 11a aee 11 Rw.¢ as sea Pumas: has me maowo mdaeqepm aeaanez_neoreep o .maoh Passpconp cap arm Rev 116 arm 11 Rm.¢ new as you maaoo me maomo meaeqepm_aeaauez 6663969 o .mmeh sues am. ecu a..m ee.e ea.e am.m neeeee or» new needs sesame caufioomm seesaw: soozpop o .maea assesses» cap How movcm arm see as. Rom am. an. neeewe eamaeeam aaaee noes» top 0 sobmm on» yo owenoba H» e >H HHH HH H Aeov can an soap an covsob uoapnsp sovnob Hohpnoo soapcaasb mo 00 oo «00 Had 9H4 Psoaonmmooo Ho oaks .b acmaaaonxm pom mpnmonom mm soapmanc> mo mpaodofiywooo one mo hamsasm .mm magma 84 gas and minimize the effects of evaporation. This procedure would have helped in this experiment apparently. However, it is evident the "Cell Health" parameter corrects for media evaporation since the volume term is cancelled in calculation. Because of the loss in precision when attempting to control carbon availability, one may have to concede to no controls other than optimum surface to volume ratios for culture medium. Certainly for studies that look at carbon availability or carbon-nutrient interactions, one should attempt to control carbon. It is apparent Selenastrum is tolerant of fairly low pH levels (near pH 6). Selenastrum responds to low levels of carbon by increasing cellular surface area to volume ratios (King, 1972). This experiment supports King's finding since I found cell size decreased and cell numbers increased when available carbon (free COé) decreased. Finally, I suggest this carbon control problem may be another reason (see page 57 of this study) for the high interlaboratory variances and the low intralaboratory vari- ances noted in the InterbLaboratory_Precision Test (Maloney- Deputy Chief, 1971). It is likely that before the AAP becomes the "standard" needed, a precise method of controlling carbon availability will have to be developed. Experiment 8 Effects of culture medium freshness on Selenastrum.growth ose Fresh AAP medium was compared to media one and two weeks ‘ old to determine if aged media affected nutrient concentra- tions. Bioassay was used rather than chemical assessment of the media because bioassay assesses the biological avail- ability of nutrients. Design The three treatments were (1) fresh AAP medium, (2) seven. dayhold AAP medium, and (3) fourteenpday-old AAP medium all prepared from the same nutrient stock solutions. Each treat- ment was run.in.duplicate. Procedure The treatments were randomly inoculated with fourbday-old inoculum cultured and prepared in the usual manner. The initial cell concentration was about 2x103 cells per ml and all six flasks were placed under light intensity of 420 ft-c. On day 10 cell counts and dry weights were determined using procedures described previously. Results Table 27 lists averages for cell counts and dry weights, coefficients of variation, and percent reduction in cell counts 85 1 86 and dry weights causedby aged media. The fresh medium yielded significantly higher cell counts and dry weights at 99% confidence levels according to _t_ testing. Table 27. Com arison of fresh AAP medium to aged AAP medium by a) cell counts and (b) dry weights after ten days growth. Also shown are C and percent reductions in cell counts and dry xeights due to medium freshness. a Cell counts Percent Treatments cells/ml i: 1SD Cv reductio Fresh medium 4.5x106 It .2x106 4.5% -- Seven-day-old medium 7.6x105 i .1x105 1.3% 83% Fourteen-day-old medium 6.41:105 .1". .1x10‘3 1.6% 87% (b) Dry weights Percent Treatments ' [lg/ml i 1SD Cv reductio: Fresh medium 199.5 :1; 9.2 4.6% - Seven-day-old medium 92.1 :1; 3.0 3.3% 64% Fourteen-day-old medium 84.6 :1; 3.7 4.4% 68% A simple test was conducted to determine which nutrients were lost in aged media. Seven aliquot portions from the fourteenpday-old treatment were placed in.seven small vials on day 10. Each vial was treated with a few drops of one of the nutrient stock solutions used to prepare AAP medium. After five days only the vial that received the TRACES stock treatment (micronutrient mixture) responded significantly. Table 28 shows the results of this testing. Reductions of up to 87% and 68% for cell counts and dry weights respectively 87 were observed. It is not known if the nutrients were lost (e.g., adsorbed onto the glass of the flask in.which.the media treatments were aged) or if the nutrients became bio- logically unavailable (e.g., chemical precipitation). The media were aged in one-liter flask and poured into the culture flasks on the day of inoculation. By this procedure, the nutrients may have been adsorbed onto the one-liter flask and subsequently not transferred when the medium was poured into culture flasks. Another bioassay would have to be con! ducted to determine if medium aged in the culture flasks affected nutrient concentrations. Table 28. Cell counts of Selenastrum cultured in aged medium (fourteenpday-ola). On day 10 the culture was divided into seven portions and each treated with one of the AAP nutrient stocks. Cell counts were made after five days of culturing. *w— -.. _. ._ ._ Treatment solution nutrients (counts in cells/m1) s. y [ nano K23204 Mg012 113304 0111012 wenco amoss 1 6.4x105 6.4x105 6.4x10‘56.4x1o5 6.4x1o5 6.4x10E 6.4x105 . 15 7.1x105 6.ex105 7.51105 7.9x105 6.81105 6.9x105 2,9106 aTRACES is a stock solution containing a mixture of all trace elements (micronutrients) used to prepare AAP medium. TRACES was the only treatment giving a significant growth response according to'g testing. ‘ Conclusions This experiment demonstrates the importance of using freshly prepared AAP medium for bioassays. Many of the problems encountered in earlier experiments in this study may have resulted from using aged AAP medium. 88 The Algal Assay Procedure: Bottle Test (Bartsch-Director, 1971) does not specify that only fresh medium be used for bioassays. It states, "It is recommended that uninoculated sterile reference medium be stored in the dark to avoid any (unknown) photochemical changes." Murray et al. (1971) observed the order in which the nutrients were added in preparing the AAP medium effected T) Selenastrum growth. I suggest these problems need to be N studied and if proven, the AAP should be modified to eliminate discrepancies resulting from such unmodified procedures. APPLICATIONS OF ALGAL BIOASSAY The following six experiments are applications of the bioassay to limnological questions since it was felt the it techniques had been mastered sufficiently. Three Michigan lakes were assayed for (1) possible inhibitory substances reported to prevent algal growth in oligotrophic lakes and (2) the nutrient limiting Selenastrum production in a lake sample. Lake samples were collected in July of 1973 and bioassayed a day after sampling. 89 Experiment 9 Bioassay of Torch Lake for inhibitogy:substances ose An oligotrophic lake was assayed for unknown substances reported to inhibit algal growth. The lake assayed was Torch Lake, Michigan, near Traverse City along the western side of the state, a few miles inland from Lake Michigan. McDonald et al. (1970) reported an oligotrophic soft water lake, Lake George, in the Adirondack Mountains of New York, contained inhibitory substances that limited Selenastrum productions in static bioassays. McDonald used the PAAP medium which differs slightly in nutrient concentrations when compared to AAP medium. He put PAAP nutrient stock solutions in two, one-liter volumetric flasks, diluted one flask with distilled water (control), and diluted the other flask with Lake George water which had been membrane filtered to remove indigenous algae. The two treatments were inoculated with Selenastrum and growth was followed. It was found that the nutrients diluted with Lake George water gave significantly lower,umax compared to the control (e.g., 0.98 and 1.32 re- spectively). He also reported a 29% reduction in dry weight for the treatment where the diluent was Lake George water. He repeated the experiment with Gorham's medium and noted similar results. It was concluded Selenastrum could not use 90 91 the increased nutrients added when the lake water was used to dilute the AAP nutrients because some unknown inhibitory substance was apparently in the lake water. This experiment is designed to be similar to McDonald's study. Desigg The treatments were (1) AAP nutrients diluted with distilled water (control) and (2) AAP nutrients diluted with 0.45M.membrane filtered Torch Lake water. A third treatment was attempted using paper filtered lake sample as a diluent, but gave inconclusive results since the filtering passed through many protozoans. These were much larger than Sglggg astrum cells so it was likely spores or eggs passed through the filters. One species was very numerous (up to 103 per ml) and appeared full of Selenastrwm cells. When these protozoans (identified as Collodictzon sp.) were placed in a formalin solution, they burst open and released from ten to twenty algal cells. The membrane filtering passed some bacteria through, however, axenic samples are not strived for using the AAP bioassays. Each treatment was run in five replications. Cell counts were used to follow growth. A blocking technique was used to block out the effects of slight differences known to exist in light intensity over the assay platform. W Torch Lake water, known to be oligotrophic, was collected 92 and transported under ice in acid rinsed dark bottles to the laboratory where it was immediately membrane filtered. The filtrate was used to dilute a batch of AAP nutrients. The control was a batch of AAP nutrients diluted with distilled water. The treatments were inoculated shortly after preparation with four-day-old stock Selenastrum prepared and delivered in the usual manner. Cell counts were made on days O,1,2,3,5,7, and 10. Results Daily cell counts and pH are listed in Appendix table B9. The maximum pH reached was about 10.1 for the control and 9.8 for the lake water treatment. Figures 10a,b depict the growth curves and show the precision between treatment replications was high. Table 29 gives the daily Specific Growth Rates for each treatment replication. The underlined maximums always occurred between days 1 and 3. Table 30 gives the,umax values. The Cv between the treatments replications was low and acceptable for bioassays at 10% and 13%. The t test showed no signifi- cant difference between the ,44 max values. Table 31 gives the Maximum Standing Crops in cell numbers for each treatment replication. The Cv was 3.2% for the control and 17% for the lake water treatment. The t test showed the control yielded significantly higher standing .0 e0.0 00.0 00.0 00.0 00.0 0 00.. . .. mmam. 04.. Mada 00.. 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M e m N . nope: ones nonoa ea eeoaaan none: eoaa.eea0 ea enooaan Anson. @0030 was. 0.5000 058.50 050 .mwmmeomm capwpm has so» a new mopmm masons oawaooAm mason mssnpmesoaom so pops: coaaspmuo spas sovsaav mpseuapss m<¢ one on coasasoo upsofihpss mad now Psosaas m we noses oxen noses coaopafim escapees mo upcomwm rIIlIllllIIIIIIlllllIllIIIlIIIIIIIllIIIlIlIlIIIIIlllllllllllllmwmmmmmml. .mN manna Table 30. 97 Effects of membrane filtered Torch Lake water as diluent for the AAP nutrients compared to the AAP nutrients diluted with distilled water on Selen- astrum Maximum Specific Growth Rates. are CV and 5 testing data. m Also Iisted MAXIMUM SPECIFIC GROWTH RATES (*hax) Rep Number Diluent is Diluent is distilled water Torch Lake water 1 2.09 1.87 2 1.98 2.52 3 2.22 2.22 4 1.94 1.91 5 1.68 1.96 Mean i 182 1.98 1 0.20 2.09 i 0.27 Cv 10% 13% The treatment means do not differ t test 1- significantly above the 50% level Table 31. Effects of membrane filtered Torch Lake water as a diluent for the AAP nutrients compared to the AAP nutrients diluted with distilled water on Selen- astrum Maximum Standing Crops in cells numBers. Also Iisted are Cv and 3 testing data. Rep 1 MAXIMUM STANDING CROPS in CellZml uent is uent is Number 1' ll]] 3 a!; I 1 I J l 1 4.8x10 3.1x10 2 4.5x106 3.5x106 3 4.6x106 3.8x106 4 4.610106 3.5x106 5 4.4x106 4.8x106 Meanii 1SD 4.6x106‘i 0.2x10g 3.7x10 ‘1 0.6x106 Cv 3.2% 17% The treatment means differ at a 13 test 95% level 98 Conclusions McDonald found when the PAAP nutrients were diluted with an oligotrophic lake water and compared to a control of nutri- ents diluted with distilled water, that the latter gave sign- ificantly higher/4max and Maximum Standing Crops. I found when Torch Lake water was used as a diluent for the AAP nutrients and compared to a control, that the latter gave no detectable differences in/“max and significantly higher Maximum Standing Crops measured in cell numbers. McDonald suggested inhibitory substances caused this. I suggest from this experiment alone, there is insufficient evidence to conclude the decreases in cell production were caused by inhibitory substances. There are other plausible causes for this study's and McDonald's results. For instance, the added carbonate alkalinity from the lake water treatment may have effected algal growth. Experiment 7 indicated Selenastrum responds to decreased carbon availability by increasing cell numbers and decreasing cell size. King (1972) noted this response and suggested it was to increase the sur- face to volume ratios of the cells. It was noted during counting in this experiment that the control's cells were small and deformed while the lake water treatment's cells were larger and more turgid (similar to the finding in Experi- ment 7). This could have accounted for the observed and deter- mined results in this experiment. McDonald noted a 29% reduction in standing crops. Here a 19% reduction was noted (Table 31). Although these results 99 were statistically significant, Figures 10a and 10b show the reduction in cell numbers is hardly noticeable from growth curves. The visual observation of varying cell sizes for the treatments is not reflected in the data collected. When dry weights were determined, as in Experiment 11, this ob- servation is verified. Experiment 10 Bioassay of Deep Lake for inhibitory substances Purpose This experiment was similar to Experiment 9 except the lake bioassayed was Deep Lake, located in Barry County, Mich- igan, within the Yankee Springs State Recreation Area. The lake is free of cottages, Spring fed, and oligotrophic. A secchi disk reading of twelve meters was observed in July at the time of sampling. The lake is stocked with Lake and Brown Trout yearly. It gave a good sample to test McDonald's hypothesis that oligotrophic lakes contain unknown inhibitory substances effecting algal production.(McDonald et al., 1970). Desigg The setdup was the same as for Experiment 9 except that four treatment replications were used instead of five. Procedure The methods are the same as for Experiment 9. Some chemical determinations were made on the lake sample. Phenol- phthalein alkalinity was 8 mg/l and total alkalinity was 145 .mg/l as calcium carbonate. Total hardness was 166 mg/l as calcium carbonate. Orthophosphate was less than the lower detection limit of 0.01 mg P/l using a molybdate method on “the filtered samples. Cell counts were made on Days 0,1,2,3, 100 101 4, 6,10, and 18 (Experiment 9 was assayed for only ten days). Results Cell counts, pH, and Cv for each treatment replication are listed in Appendix B10. Figures 11a and 11b depict the growth curves. Table 32 gives the daily Specific Growth Rates with the maximums all occurring between days 1 and 2. Table 33 gives the ’umax values. The Cv between the treatment replications was 6% and 4% which indicates excell- ent precision. The mean ’“msx for the Deep Lake water diluent treatment was greater than the distilled water diluent treat- ment at a 95% confidence level. This is contrary to the findings of McDonald as explained in Experiment 9. Table 34 gives the Maximum Standing Crops in cell numbers. The Cv between the treatment replications was 9% and 6% which again indicates excellent precision. The mean Maximum Stand- ing Crop for the Deep Lake water diluent treatment was less than the distilled water diluent treatment at a 94% confidence level. This agrees with McDonald's finding. Bacterial growth was noted when counting the lake treat- ment, especially after day 6. No attempts were made to quantify or identify these microbes. Conclusions AAP nutrients diluted with membrane filtered Deep Lake Vsater compared to AAP nutrients diluted with distilled water gave higher '“max values (1.94 and 1.70 respectively) and lower Maximum Standing Crops (3.8x106 and 4.5x106 cells per ml re- apectively) . .129 5? ..~—.. Figure 11. a. b. 102 Growth curves for Selenastrum from.an eighteen day bioassay of the effects of membrane filtered Deep Lake water used to dilute the AAP stock nutrients. Page 103- The treatment was AAP nutrients diluted with distilled water (control). Page 104- The treatment was AAP nutrients diluted with membrane filtered Deep Lake water. 1 2 103 3 4 5 6 7 TIME IN DAYS Figure 11a 9 10 10 10 C ELLS per ml. 8 U1 10 1 2 104 3 4 5 6 TIME IN DAYS Figure 11b 7 8 9 10 105 Table 32. Effects of membrane filtered Deep Lake water as a diluent for the AAP nutrients compared to the AAP nutrients diluted with distilled water on Selenastrum daily Specific Growth Rates for an eighteen7day static bioassay. SPECIFIC GROWTH RATES (fl/day) D a Diluent is distilled water Diluent is Deep Lake waten _%1 7—74 1T‘IA 1.22 1.36 1.34 1.48 0.88 1.10 1.31 1.39 1 2 81.68 1.62 1,84 1.65 2.01 1.99 1.96 1.91 1.17 1.31 0.99 0.82 1.58 1.24 1.26 0.96 3 1.23 1.17 1.28 1.35 1.20 1.06 1.04 P...- 4 6 0.35 0.31 c0.00 0.40 0.22 °0.00 0.24 -- 0.03 0.01 0.00 0.00 0.02 0.00 0.04 0.07 10 0.00 0.01 0.00 0.00 0.00 0.01 0.00 0.00 18 aUnderlined growth rates are the maximums for each repli- cation. b Not determined because of "outlier" in Appendix table B10. 0Growth rates recorded as 0.00 may be less than zero. 106 Table 33. Effects of membrane filtered Deep Lake water as a diluent for the AAP nutrients compared to the AAP nutrients diluted with distilled water on Selenastrum Maximum Specific Growth Rates with C and t testing. v .— :— MAXIMUM SPECIFIC GROWTH RATE ( ) figgber Diluent is Diluent is _distilled water Degp Lake water 1 1.68 2.01 2 1.62 1.99 3 1.84 1.86 4 1.65 1.91 Mean 3 1SD 1.70 i 0.10 1.94 i 0.07 CV 6% 4% Distilled water diluent mean is sma114 ‘3 test or than Deep Lake water diluent mean at a 95% level. Table 34. Effects of membrane filtered Deep Lake water as a diluent for the AAP nutrients compared to the AAP nutrients diluted with distilled water on Selenastrum Maximum Standing Crops in cell numbers, wItE 0v andIg testing. MAXIMUM STANDING CROPS in Cells/ml Rep Diluent is Diluent is Number distilleg Egtg; 233p Lgkg wgtg; 1 4.1x10 3.9x10 2 4.5x106 3.51106 3 5.1x1o6 3.7x106 4 4.4x106 4.0x106 Mean 4.5x102 3.8x10g 313D I 04110 1: 0.2x10 CL 9% 6% t test Distilled water diluent eater than 1- lake water diluent at 95 level 107 These results were highly significant statistically. However, the biological significance is not apparent. A speculation was given in Experiment 9 on the cause of these _ results. Another plausible cause might be the effects of the bacteria in the lake sample. The only organic compound in the AAP nutrients is the chelator, EDTA. This chelator is believed to make certain nutrients biologically available. If the chelator was destroyed during the assay, the effects might be nutrients becoming unavailable. Tiedje (personal ‘ communication) is presently investigating EDTA decomposition by microbes. He reports that EDTA was not a carbon source for any of the microbes tested. In many inStances EDTA acts as an antibacterial agent. In a few instances it was metab- olized, but only at extremely slow rates. He doubted metab- olism of EDTA in algal bioassay would be significant for short duration tests. Experiment 11 Bioassay of Lake Lansing_for inhibitory:substances ose This experiment, like Experiments 9 and 10, assesses the effects on Selenastrum of a lake water used to dilute the AAP stock nutrients. The lake bioassayed was Lake Lansing, near Lansing, Michigan. Lake Lansing is relatively eutrophic when compared to Torch Lake and Deep Lake. Desigg Dry weights, as well as cell counts, were used to assess growth. A mistake in inoculation resulted in two rather than four replications for the distilled water diluent treatment. The lake sample diluent treatment was run in four replications. Procedure Phenolphthalein alkalinity was 13 mg/l and total alkalinity was 110 mg/l as calcium carbonate. Total hardness was 136 mg/l as calcium.carbonate. Orthophosphate measured with a molybdate method was 0.03 mg P/l. Total phosphate measured with a per- sulphate digestion method was 0.08 mg P/l. The two treatments were randomly inoculated with six-day- old stock inoculum prepared in the usual manner. Two flasks were apparently not inoCulated, since no growth was noted. Counts were made on days O,1,2,3,5,7, and 14. Dry weights 108 i.-. _ 109 were determined on day 14. Results Appendix table B11 lists the cell counts from which the growth curves in Figures 12a and 12b were determined. Table 35 gives the daily Specific Growth Rates which shows the maxi- mums all occurred between days 1 and 2. Table 36 gives the ,0 ”tax values and Table 37 gives the Maximum Standing Crops. The results are the same as for the Torch Lake and Deep Lake experiments. -The AAP nutrients diluted with membrane filtered Lake Lansing water gave higher/uhax values and lower Maximum Standing Crops when compared to the AAP nutrients diluted with distilled water. Table 38 gives the data used to calculate the growth parameter of Maximum Standing Crops in cellular dry weights. The lake water diluent treatment yielded about two and a half times as much dry weight as the distilled water diluent treatment. The difference is obviously highly significant and was not‘g tested. Table 39 was calculated from the cell counts on day 14 listed in Appendix table B11 and the dry weights of Table 38. The parameter of "Cell Health" showed the lake water diluent treatment yielded more than three and a half times as much dry weight per million cells as the other control treatment. The maximum pH reached was 9.8 for the distilled water diluent and 8.7 for the lake water diluent. This suggests both treatments were likely under carbon stress with the Figure 12. a. b. 110 Growth curves for Selenastrum from a fourteen day bioassay of the effects of membrane filtered Lake Lansing water used to dilute the AAP stock nutrients. Page 111 - The treatment was AAP nutrients diluted with distilled water (control). Because of an inoculation error, only two repli- cations were run. Page 112 - The treatment was MP nutrients diluted with membrane filtered Lake Lansing water. IO 10 CELLS per ml. cm 10 I 2 111 3 4 5 6 TIME IN DAYS Figure 12a 7 9 IO IO CELLS per ml. IO I /___ __ // 2 112 3 4 5 6 TIME IN DAYS Figure 12b 7 9 IO Tabl 113 [’77 e 35. Effects of membrane filtered Lake Lansing water as a diluent for the AAP nutrients compared to the AAP nutrients diluted with distilled water on Selenastrum daily Specific Growth Rates for a fOurteen day static bioassay. an. #NIU'IUIN SPECIFIC GROWTH RATES (Ad/day) Diluent is distilled water Diluent is Lake Lansing water 1.12 1.16 a a-- 0.59 1.13 0.79 1.00 I’m 1_._g_§ 1. s g_._gg _2_._2_6_ 2. o 1.07 1.40 1.33 1.36 1.32 1.33 1.01 0.97 0.83 0.61 0.63 0.66 0.21 0.05 0.12 0.00 0.00 0.00 0.00 0.02 0.00 0.00 0.00 0.00 aNo replications because of inoculation error. bUnderlined values are the replication maximums. Table 36. 114 Effects of membrane filtered Lake Lansing water as a diluent for the AAP nutrients compared to the AAP nutrients diluted with distilled water on Selenastrum Maximum Specific Growth Rates, with Mating. MAXIMUM SPECIFIC GROWTH RATE (”hax) Rep fi_______________, number Diluent 1s Diluent is distilled water Lake Lansing water 1 1.54 1.98 W1 2 1.48 2.00 ‘ 3 -- 2.26 4 """""' 2030 “" Mean i1SD 1.51 :1; 0.04 2.14 :1; 0.17 ' eV 3% 8% Lake Lansing treatment mean is great- ‘5 test er than the control mean at a 99% level. Table 37. Effects of membrane filtered Lake Lansing water as a diluent for the AAP nutrients compared to the AAP nutrients diluted with distilled water on Selenastrum Maximum Standing Crops in cell numbers, with UV and 3 testing. MAXIMUM STANDING CROPS in Cells/ml gnger DiluentIIs ’“fiIluent is distilled water Lake Lane water __'—_—__6—-___' 1 4.8110 3.3x10 2 4.4x106 3.11106 3 2.8x106 4 -- 3.7x106 Mean 1 1SD 4.6::106 i 2.8x10 3.2::106 i: 3.8x105 c‘7 6% 12% t test Lake Lansing treatment mean is less '- than the control mean at a 95% level. 115 Table 38. Dry weight data for the treatments (1) AAP nutri- ents diluted with distilled water and (2) AAP nutrients diluted with membrane filtered Lake Lansing water determined on day 14. 0 given for precision of samples within replicatioXs and repli- cations within treatments. Sample wt Replication wt Treatment wt (grams/ml from (micrograms/ml (micrograms/ a 20.0 ml i 1SD with i 1SD with portion) percent Cv percent Cv 22 1 211 O Table 39. "Cell Health" parameter of dry weight per million cells for treatments (1) AAP nutri- ents diluted with distilled water and (2) AAP nutrients diluted with membrane filtered Lake Lansing water. 0 given for precision of replications within treatments. 3: R DRY WEIGHT per MILLION CELLS 1 e e '__Replications Treatments | i p micrograms/106cells micrograms/106 calla 1 46.9 1 2 41.4 44.1; 3.9 :92 1 148.6 2 161.6 2 3 202.1 4 132.6 161 .LL29.7 L18) 116 Table 40. Summary of the determined growth parameters of l4 , Maximum Standing Crops in cell numbers, um Standing Crops in dry weights, and "Cell Health" in dry weight per million cells for The treatments were 1% Ex§eriments 9, 10, and 11. Torch Lake, Deep Lake, and Lake Lansing. AAP nutrients diluted with distilled water and AAP nutrients diluted with.membrane filtered lake water sample. The lakes bioassayed were Treat- Lake Bioassayed Parameter determined ment Number Torch Deep Lansing a Maximum Specific 1 1°93 1-70 1.51 °T°'th 331°” 2 82.09 1.94 2.14 6 6 °r°P° in °°118/m1 2 3.7x106 3.8x106 3.2x106. maximum Standing 1 "’ "‘ 2‘8 Crops in dry weights ___ .__ 521 (micrograms/ml) 2 "Cell Health" as 1 -- -- 44.1 dry weight per million cells 2 161.3 aNot significantly different. different at a 95% confidence levels. All other parameters are 117 distilled water treatment more so. It was noted while counting, the cells of the lake water treatment were larger and more turgid appearing than the other treatment's cells which were "scrawny" and small although in significantly larger numbers. This observation is similar to the two previous eXperiments. Bacteria were more numerous in the lake water diluent treatment. Conclusions Table 40 summarizes the finding for Experiments 9, 10, and 11, where the lakes bioassayed were Torch Lake, Deep Lake, and Lake Lansing respectively. For all three lakes the membrane filtered lake water treat- ments gave higher Amax values, higher Maximum Standing Crops measured as dry weight, and lower Maximum Standing Crops measured as cell numbers. The parameter of "Cell Health" indicated the distilled water diluent treatments gave unhealthy cultures compared to the other treatment. The results of the three experiments are similar to the findings for EXperiment 7, where it was suggested the algal response to carbon availability stress was an increasing cell- ular surface area to volume ratio accomplished by decreasing cell size and increasing cell numbers. Here it is suggested carbon stress may have caused the noted responses. Algae may respond similarly to other nutrient stresses. In terms of carbon stress, the lake water diluent treatment added avail— able carbon directly (carbonate alkalinity) and indirectly 118 (organic carbon) as carbon dioxide respired from the microbe heterotrophs. The growth curves do not depict the treatment responses at a glance. The high degree of experimental precision allowed slight differences to be detected. It was concluded success had been achieved in mastering the techniques used in static algal bioassay. Experiment 12 Bioassay of Torch Lake for limiting nutrient Purpose The limiting nutrient in a membrane filtered Torch Lake sample was determined by static algal bioassay. Design The treatments to a membrane filtered sample of Torch Lake water were (1) lake sample control, (2) lake sample plus 0.40 mg N/l, and (3) lake sample plus 0.05 mg P/l. Phosphorus and nitrogen were the only nutrients assayed for because they had been shown to be the nutrients most often limiting algal pro- duction in freshwater lakes (e.g., Maloney et al., 1972). Each treatment was run in three replications. Cell counts were used to follow culture growth. Procedure Torch Lake water was filtered through a 0.453M membrane filter to remove indigenous algae as soon as possible after collection (about eight hours). The treatments were prepared by placing an amount of sodium nitrate to give 0.40 mg N/l in a one-liter volumetric flask, by placing an amount of potassium phosphate to give 0.05 mg P/l in a one-liter volumetric flask, and by then bringing both flasks up to volume with the filtered lake sample. The control was the filtered lake sample with 119 120 no nutrients added. Any significant increases in growth were not attributed to the cations in the treatment salts since I am not aware of any reported lakes limited in algal produc- tion by sodium or potassium. (This is not to say that sodium and potassium are unimportant in lakes. Provasoli (1969) and Wetzel (1972) have stated these two elements are important components leading to the change in flora induced by eutrophi- cation. Blue-green algae have an absolute need for both ele- ments, but other freshwater algal groups apparently do not according to Provasoli.) Treatment replications were randomly inoculated with six- day-old Selenastrum.stock inoculum prepared in the usual manner. The flasks were randomly allocated to blocks of squares on the assay platform so the effects of light intensity would be blocked out. Cell counts and pH were determined on days 0,1, 2.3.4.5. and 7 and are listed in Appendix table B12. Results The pH ranged from 8.2 to 8.6 for all treatments suggest- ing the cultures were likely not under carbon stress. The Cv values for cell counting were high (averaged about 50% in Appendix table B12) for the control and nitrogen treatments because of variance encountered when cells per micrometer grid are sparse. The phosphorus treatment responded and gave cell counts up to 150 per grid while the other two treatments gave counts of from 2 to 7 per grid. Figures 13a, 13b, and 13c depict the growth curves. It Figure 13. a. 121 Growth curves for Selenastrum from a seven day bio- assay to determine the nutrient limiting algal pro- duction in a Torch Lake membrane filtered water sample. Page 122 - The treatment was membrane filtered Torch Lake)water with no nutrients added (con- trol . Page 123 - The treatment was control plus 0.40 mg N/l. Page 124 - The treatment was control plus 0.05 mg P/l. CELLS per ml. 10 a" d 10 ‘. } I 2 3 4 TIME 122 5 6 IN DAYS Figure 13a 7 9 IO IO 105 C ELLS per ml. 10‘ I. 10 I 2 3 123 45-6 TIME IN DAYS Figure 1 3b 7 9 IO IO 10 CELLS per ml. 10 10 I 2 124 3 4 5 6 TIME IN DAYS Figure 13c 7 9 IO 125 is evident the phosphorus treatment responded. The third replication of the nitrogen treatment gave a slight response for unknown reasons. The curves for the control and nitrogen treatments are discrepant and may reflect the problems mention- ed for counting cells at low concentrations. Table 41 gives the daily Specific Growth Rates for each treatment replication. The maximums occurred randomly for the control and nitrogen treatments. The maximums for the phosphorus treatment all occurred between days 1 and 2. Table 42 gives the Amax values. The 3 testing between "lnax means showed the phosphorus treatment gave higher values than either of the other treatments at a 95% confidence level. Table 43 gives the Maximum Standing Crops in cell numbers. ‘ The‘t testing between means showed the phosphorus treatment yielded higher standing crops at a 99% confidence level. For growth parameters the Cv was high for the control and nitro- gen treatments which again may reflect counting problems for low algal concentrations. Very little bacterial growth was noted throughout the assay when counting the control and the nitrogen treatments. However, the phosphorus treatment had increasing numbers of bacteria as the assay progressed. They were most numerous after about day 4. Whether the bacterial respond directly to the nutrients or indirectly to the algal assimulated or- ganic materials is not known. 126 Table 41. Effects of two nutrient treatments of 0.40 mg N/l and 0.05 mg P/l to membrane filtered Torch Lake water on Selenastrum daily Specific Growth Rates for a seven day static bioassay. SPECIFIC GROWTH RATES Wday) D Control plus Control plus a °°ntr°1 0.40 mg N/l 0.05 mg P/l y 1 2—3 1 T1 1 {—1— 0.08 0.10 0.00 30.22 0.00 0.00 0.68 1.09 0.50 1 -——— b0.00 0.41 0.53 0.03 0.00 0.66 1.51 1.61 2.08 2 0.00 0.20 0.00 0.00 0.21 0.00 1.09 0.79 1.06 3 0.00 0.22 0.74 0.20 0.22 0.82 0.53 0.39 0.56 4 ' '"' " 0.8 0.04 0.04 0.00 0.03 0.05 0.33 0.15 0.00 5 0.02 0.00 0.05 0.00 0.10 0.14 0.01 0.05 0.05 7 aUnderlined growth rates are the maximums for that repli- caticne Growth rates recorded as 0.00 may be less than zero. 127 Table 42. Effects of two nutrient treatments of 0.40 mg N/l and 0.05 mg P/l to membrane filtered Torch Lake water on Selenastrum Maximum Specific Growth Rates, with Cv and 5 testing. MAXIMUM SPECIFIC GROWTH RATE LA ) Rep max ._ Number Control Control + N Control + P 1 0.83 0.22 1.57 2 0.41 0.52 1.61 3 0.74 0.82 2.08 Mean 1 1SD 0.66 i 0.22 0.52 i 0.30 1.75 1 0.28 Cv 33% 58% 16% ControI vs. ControI + N is ns. ‘1 testing Control <:Control + P at a 95% level. Control + N < Control + P at a 95% level. Table 43. Effects of two nutrient treatments of 0.40 mg N/l and 0.05 mg P/l to membrane filtered Torch Lake water on Selenastrum Maximum Standing Crops in cell numbers, w and‘t testing. v MAXIMUM STANDING CROPS as Cells/m1 Rep Number Control Control + N Control + P 1 1.81110I 1.3x104 6.8x105 2 2.611104 1.sx104 6.2x105 3 2.011104 5.8x104 7.2x105 Mean 2.1x10§ 3.0110: 6.7x102 _+_ 131) 14.2x10 12.51110 35.01110 Cv 20% 83% 7% ControI vs. ControI + N is ns. .1; testing Control < Control + P at a 99% level. Control + N < Control + P at a 99% level. 128 Conclusions A membrane filtered Torch Lake sample treated with 0.05 mg P/l phosphorus gave higher/umax values and Maximum Standing Crops than a sample treated with 0.40 mg N/l and a sample not treated with a nutrient (control). The‘Hmax values for the control, nitrogen, and phosphorus treatments were 0.66, 0.52, and 1.75 respectively. The Maximum Stand- ing Crops were respectively 2.1x104, 3.0x104, and 6.8x105 cells per ml. This definite stimulation for the phosphorus treatment indicates the Torch Lake sample limited Selenastrum production under the bioassay test conditions. Kerr et al. (1972) found additions of inorganic nitrogen and phosphorus directly stimulated heterotrophic growth. She might suggest the responses noted here for Selenastrum were indirect. Regardless of whether the noted response for Selenastrum was direct or indirect, the results indicate that the addition of phosphorus to Torch Lake from some external source would increase algal production. Experiment 13 Bioassay of Deep Lake for limiting nutrient Purpose The limiting nutrient in a membrane filtered Deep Lake sample was determined by static algal bioassay. Desigg The design was the same as for EXperiment 12. Procedure The procedure was the same as for Experiment 12, except cell counts were made through day 10 instead of day 7. Results Cell counts were determined on days 0,1,2,3,4,6, and 10 and are listed with Cv in Appendix table B13. Figures 14a, 14b, and 14c depict the growth curves. Table 45 gives the ”max for each treatment replication and the means for values taken from Table 44 of daily Specific Growth Rates. The phosphorus treatment gave a higher mean ‘flmax than the other two treatments at 90% and 87%Iconfidence levels. Table 46 gives the Maximum Standing Crops in cell numbers. The phosphorus treatment gave a higher mean than the other two treatments at 95% confidence levels. Both growth parameters showed the lowest Cv for the phosphorus treatment. 129 r ,_-._—— ...wvw-v :17 N Figure 14. a. 130 Growth curves for Selenastrum from a ten day bio- assay to determine tEe nutrIent limiting algal production in a membrane filtered Deep Lake sample. Page 131 - The treatment was membrane filtered Deep Lake)water with no nutrients added (con- trol . Page 132 - The treatment was control plus 0.40 mg N/l. Page 133 - The treatment was control plus 0.05 mg P/l. 10 'c'i. CELLS per ml. 10 10 I 2 131 3 4 5. 6 TIME IN DAYS Figure 14a 7 8 9 10 10 I0 CELLS per ml. IO I0 I 2 132 3 4 5 6 TIME IN DAYS Figure 14b 7 9 I0 I0 105 CELLS per ml. 10 I0 I 2 133 3 4 5 6 TIME IN DAYS Figure 1 4c 7 8 9 I0 134 Table 44. Effects of two nutrient treatments of 0.40 mg N/l and 0.05 mg P/l to membrane filtered Deep Lake water on Selenastrum daily Specific Growth Rates for a ten day static bioassay. SPECIFIC GROWTH RATES cM/day) D Control plus Control plus a C°ntr°l 0.40 mg N/l 0.05 mg P/l _{‘1 2—1 12—1 1 fl—1 0.64 a0.26 0,2: 0.72 0.10 0.10 1.31 1.06 1.16 1 80.88 0.21 0.39 0.34 b0.00 0.00 0.23 1.42 1. 2 2 0.00 0.11 0.08 0.15 0.00 0,80 0.19 0.09 0.22 3 0.00 0.00 0.00 0.00 0.00 0.00 0.16 0.15 0.12 4 6 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.16 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 aUnderlined growth rates are the replication maximums. Growth rates of 0.00 may be less than zero. b 135 Table 45. Effects of two nutrient treatments of 0.40 mg N/l and 0.05 mg P/l to membrane filtered Deep Lake water on Selenastrum Maximum Specific Growth Rates, with Cv and 3 testing. MAXIMUM SPECIFIC GROWTH RATES Ulnar) Rep Number Control Control + N Control + P 1 0.88 0.79 1 .41 2 0.26 0.10 1.06 3 0.53 0.80 1.16 Mean i1SD 0.56 i 0.31 0.56 :1; 0.40 1.21 i. 0.18 Cv 55% 72% 15% Control vs. CBnEroI + N is ns. 3 testing Control < Control + P at a 90% level. Control + N < Control + P at a 87% level. Table 46. Effects of two nutrient treatments of 0.40 mg N/l and 0.05 mg P/l to membrane filtered Deep Lake water on Selenastrum Maximum Standing Crops in cell numbers, w v and 2 testing. MAXIMUM STANDING CROPS a8 Cells/ml Rep Number Control Control + N Control + P 1 6.4x104 3.6x104 3.1x105 2 1.91104 1.3x104 1.9x105 3 2.711104 1.921104 3.4x105 Mean 3.71101 2.3x1ofi 2.8x103 i1SD i 2.4x10 3; 1.2x10 i 7.9x10 av 65% 52% 28% ConfroI vs. ControI + I is ns. 2 testing Control < Control + P at a 95% level. Control + N < Control + P at a 95% level. 136 Conclusions The results indicate the nutrient limiting Selenastrum production in a membrane filtered sample of Deep Lake water was phosphorus when tested by a static bioassay. The ”max values for the control, nitrogen, and phosphorus treatments were 0.56, 0.36, and 1.21 respectively. The Maximum Standing Crops were respectively 3.7x104, 2.3x104, and 2.8x105 cells per ml. Experiment 14 Bioassay of Lake Lansingfor limiting nutrient Purpose The limiting nutrient in a membrane filtered Lake Lansing sample was determined by static algal bioassay. Desigp The design was the same as for Experiment 12. Procedure The procedures were the same as for Experiment 12. A fourth treatment was added to this experiment. The treat- ment is control plus 0.40 mg N/l and 0.05 mg P/l. Results Cell counts were determined on days 0.1.2.3.4.5.7. and 10 and are listed with C7 in Appendix table B14. Figures 15a, 15b, 15c, and 15d depict the growth curves. The phosphorus and the phosphorus plus nitrogen treatments showed increases in pro- duction. The phosphorus plus nitrogen treatment depicts a decrease in Cell numbers after day 7 while the phosphorus treatment shows no such decrease. Table 47 lists the daily Specific Growth Rates. Table 48 gives thefl'hax for each replication and the means. The 3 testing showed the phosphorus treatments had greater,AEax values than the control and the nitrogen treatments at 99% 137 ..j Figure 15. a. 138 Growth curves for Selenastrum from a ten day bioassay to determine the nuErIenE IIEiting algal production in a membrane filtered sample of Lake Lansing water. Page 139 - The treatment was membrane filtered Lake Lansing with no nutrients added (control). Page 140 - The treatment was control plus 0.40 mg N/l' Page 141 - The treatment was control plus 0.05 mg P/l. Page 142 - The treatment was control plus 0.40 mg N/l and 0.05 mg P/l. I0 an CELLS per ml. 10 10 I 139 .4 v +I :0. fl. 2 3 4 5 6 7 8 9 IO TIME IN DAYS Figure 15a 10 '51.. C ELLS per ml. 0‘. I0 ><::.':':: I 2 140 3 4 5 6 TIME IN DAYS Figure 1 5b % 7 9 I0 I0 105 C ELLS per ml. I0 10 I 2 141 3 4 5 6 TIME IN DAYS Figure 150 7 9 10 IO 23,, C ELLS per ml. 10 103 I 2 142 3 4 5 6 TIME IN DAYS Figure 15d 7 8 9 I0 Table 47. 143 Effects of three nutrient treatments of 0.40 mg N/l, 0.05 mg P/l, and 0.40 mg N/l plus 0.05 mg P/l to membrane filtered Lake Lansing water on Selenastrum daily Specific Growth Rates for a ten day oassay. D SPECIFIC GROWTH RATES Wday) 3 Control gffigTS; £§§B 0.00 0.00 0.00 0.00 0.00 0.00 1 0.11 0.00 0.0 0.07 0.00 0.00 2 0.10 0.00 0.00 9.9g 0.08 0.00 3 9L1_4_ 9.95 0.00 0.08 0.0 0.00 4 0.00 0.00 0.00 0.03 0.03 Qggg 5 0.00 0.00 0.02 0.00 0.00 0.00 1: 0.00 0.00 0.02 0.00 0.03 0.00 3 3331;: 1}? 353538131? 0.41 0.41 0.53 0.26 0.47 0.41 1 1. 0 iii} 1.42 1.5g 1px mg 2 0.58 0.41 0.62 0.66 0.48 0.72 3 0.35 0.17 0.17 0.31 0.41 0.40 4 0.22 0.21 0.20 0.29 0.24 0.00 5 0.15 0.00 0.12 0.04 0.09 0.13 1: 0.10 0.11 0.06 0.00 0.00 0.00 144 Table 48. Effects of three nutrient treatments of 0.40 mg N/l, 0.05 mg P/l, and 0.40 mg N/l plus 0.05 mg P/l to membrane filtered Lake Lansing on Selenastrum Maxi- mum Specific Growth Rates, with Cv anH i ’Ees‘Eing. Rep MAXIMUM SPECIFIC GROWTH RATE (Than) Number W on ro on r0 + Coniroi + 2 ConEroI + N+P 1 1 0.14 0.08 1.50 1.48- 2 0.04 0.09 1.58 1.36 3 0.05 0.20 1.42 1.12 Mean iISDi 0.08 :1; 0.05 0.12 1’. 0.07 1.50 i 0.08 1.32 1'. 0.18 cv 62% 58% 5% 14% ConTroI vs. on ro + is ns. Control < Control + P at a 99% level. t testi Control < Control + N+P at a 99% level. - ng Control + N < Control + P at a 99% level. Control + N < Control + N+P at a 99% level. ControlL+ P > Control + N+P at a 10% level. Table 49. Effects of three nutrient treatments of 0.40 mg N/l, 0.05 mg P/l, and 0.40 mg N/l plus 0.05 mg P/l to membrane filtered Lake Lansing water on Selenastrum Maximum Standing Crops as cell numbers, w v an 3 testing. '1: Rep MAXIMUM STANDING CROPS in Cells/ml Number ‘ ControI ConEroI + N ControI + P Control + N+P 1 1.1x104 7.4x1O 3.3x10 2.2x105 2 7.2x103 6.4x103 1.8x105 2.3x105 3 8.61103 1.011104 2.7x105 1.7x105 Mean 8.9x10‘;F 7.9x103F 2.6x10f 2.1x1045 :1 SD 13.6x10 31.8x10 37.5110 33.2x10 Cv 40% 23% 29% 15% Cont'roI vs. on ro + Is ns. Control 4 Control + P at a 95% level. t t e t Control < Control + N+P at a 99% level. - 3 ing Control + N < Control + P at a 95% level. Control + N <. Control + N+P at a 99% level. Control + P > Control + N+P at a 60% level. 145 confidence levels. Table 49 gives the Maximum Standing Crops in cell numbers and shows the phosphorus treatments yielded greater numbers than the control or the nitrogen treatments at 99% and 95% confidence levels. Conclusions The results indicate the nutrient limiting Selenastrum production in a membrane filtered sample of Lake Lansing water was phosphorus when tested by a static bioassay. The/“max values for the control, nitrogen, phosphorus, and phosphorus plus nitrogen treatments were 0.08, 0.12, 1.50, and 1.32 re- apectively. The Maximum Standing Crops were reapectively 8.9x103, 7.9x103, 2.6x105, and 2.1x105 cells per ml. The results suggest the nutrient limiting the decomposition of organic matter (nonliving Selenastrum cells) was nitrogen according to the growth curves depicted in Figure 15d. It is well known nitrogen is a key nutrient substance for microbial growth and hence for organic matter breakdown. Algal cells always contain some nitrogen, but its availability and amount vary greatly. According to Alexander (1961), if the nitrogen of the substrate is high and the element is readily utilized, the microbe satifies its needs from this source, and additional quantities are unnecessary. If the substrate is poor in the element, decomposition is slow, and carbon mineralization will be stimulated by supplemental nitrogen. The AAP medium was intended to culture cells that would be nutrient starved so nutrient carry over would be minimal during inoculation. It 146 appears the nonliving Selenastrum cells did not contain suffi- cient quantities of nitrogen for their breakdown to occur by heterotrophic activity. Lake Lansing evidently did not have the supplemental nitrogen needed for breakdown. Therefore, the phOSphorus plus nitrogen treatment furnished the necessary nutrient to allow decomposition. SUMMARY Following are sources of error encountered for bioassays while conducting this study. These errors affected bioassay precision noticeably: 1. The first tried method of cell counting resulted in unsuitable variance according to Nested Analyses of Variance caused by poor technique in preparing chambers for counting. A modified technique placed all the counting variance in the number of grids counted per sample, which allows control over precision. 2. The first attempt at culturing Selenastrum in a bioassay of four low levels of phosphorus showed much need for improvement since Coefficients of Variation were above 15% (the generally acceptable level for bioassays) for the growth parameters determined. 3. The initial cell concentration in a bioassay culture effected growth. As the initial cell concentration increased, the ’“max increased and also occurred earlier in the bioassay. Maximum Standing Crops were not appreciably effected. 4. Light intensity effected both growth rates and standing crops. A 50% reduction in light intensity resulted in a 75% reduction in the maximum number of cells that could be cultured and a significant (at a 90% confidence level) 147 148 lowering Of’flmax' Cultures grown.under an intensity of 260 ft-c and later placed under 475 ft-c (after undergoing a logarithmic growth phase) underwent a second logarithmic growth phase, suggesting light can limit growth in bioassays. 5. Culture medium freshness affected the concentrations of biologically available nutrients. Sevenpdaybold medium re- sulted in a 68% reduction in the maximum number of cells that could be cultured when compared to fresh medium. One of the trace elements in the micronutrient stock mixture was assessed as becoming unavailable as culture medium aged. .A specific trees could not be identified by bioassaying. 6. Suggested methods of insuring carbon availability (given in the AAP) were tested. Six levels of carbon dioxide were introduced to cultures of Selenastrum.and resulted in higher growth parameter discrepancies than no carbon dioxide introductions other than what occurred naturally through the foam plugs stoppering the culture flasks. However, cells under carbon stress were small and irregularly shaped compared to the large, turgid cells not under stress. Cultures under carbon stress yielded lower [Am values, lower Maximum Stand- ing Crops measured in dry weights, poorer "Cell Health" measured in dry weights per million cells, and higher Maximum Standing Crops when measured in cell numbers. The responses were attributed to a cellular surface area to volume ratio phenomenon since cell sizes decreased and cell numbers increased when cultured under carbon stress. 149 High bioassay precision was achieved after these sources of error were realized and controlled. Following are summaries of six applications of the bioassay: 1. Three Michigan lakes, Torch Lake, Deep Lake, and Lake Lansing (oligotrophic, oligotrophic, and eutrophic respectively) were used as a diluent for the nutrient stocks in culture medium preparation and compared to nutrient stocks diluted in the usual manner with distilled water. 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Effects of secondary and tertiary wastewater effluents on algal growth in a lake-river system. J. Water Poll. Cont. Fed. 43(12):2361-2365. MilliporeRCorp. 1973. Application Manual: Biological Analysis of Water and Wastewater. AM302 (3rd printing). Bedford, Mass. 83 pp. Murray, 8.. J. Scherfig, and P.S. Dixon. 1971. Evaluation of algal assay procedures-PAAP Batch Test. J. Water Poll. Cont. Fed. 43(10): 1991-2003. 155 Myers, J. 1962. Laboratory cultures. In: Physiology and Biochemistry of Algae. R.A. Lewin (ed.). Academic Press, New York. pp. 603-615. Naumann, E. 1917. UndersBkningar Over fytoplankton och.under den pelagiska regionen f6rsiggaende gyttJe-och dy- bildningar inom vissa syd-och mellansvenske urberg- vatten. K. Sv. Vetensk. Akad. Handl. 56(6):1-165. Odum, E.P. 1971. Fundamentals of Ecology. (3rd ed.). W.E. Saunders, Philadelphia, Pa. 574 pp. Odum, H.T. 1958. The chlorophyll a of communities. Pub. Texas Inst. Mar. Sci. 5:65-96. Pearson, E.A., E.J. Middlebrooks, M. Tunzi, A. Aleti, P.H. McGaughey, and G.A. Rohlich. 1969. Kinetic assessment of algal growth. In: Proceedings of the Eutrophication-Biostimulation.Assessment Workshop. E.J. Middlebrooks (ed.). Oregon State Univ.. Corvallis, Ore. pp. 56-79. Powers, G.F., D.W. Schultz, K.W. Malueg, R.M. Brice, and M.D. Schuldt. 1972. Algal responses to nutrient addi- tions in natural waters II: Field experiments. In: Nutrients and Eutrophication: The Limiting Nutrient Controversy. R.A. Likens (ed.). Special Symposia Vol. I. Limnol. and Oceanogr. Allen Press, Lawerence, Kane. pp. 141-155. Pringsheim, E.G. 1946. Pure Cultures of Algae. Cambridge Press, London. 118 pp. Provasoli, L. 1969. Algal nutrients and eutrophication. - In: Nutrients and Eutrophication: The Limiting Nutrient Controversy. R.A. Likens (ed.). Special Symposia Vol. I. Limnol. and Oceanogr. Allen Press, Lawerence, Kans. pp. 547-593. Reilly, P.J. 1972. Concurrent Growth of Bacteria and Algae in a Closed Vessel. 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State Univ. 0011. at Buffalo, New Yerk. 10 pp. Tamiya, H. 1951. Some theoretical notes on the kinetics of algal growth. Botan. Mag. (Tokyo). 64:167-173. Taylor, W.P. 1934. Significance of extreme or intermittent conditions in distribution of species and manage- ment of natural resources, with a restatement of Liebig's law of the minimum. Ecology. 15:274-279. Tiedje, J.M. 1973. (Personal communication). Dept. of Soil Science, Mich. State Univ.. E. Lansing, Mich. 157 Toerien, D.F., C.H. Huang, J. Radimsky, E.A. Pearson, and J. Scherfig. 1971. Final Report-Provisional Algal Assay Procedures. SERL No 71-6. Univ. of Calif. at Berkeley. 178 pp. Tunzi, M.G. 1971. The effects of agricultural wastewater treatment on algal bioassay response. Bioengineering Aspects of Agricultural Drainage, San Joaquin Valley, Calif. U.S. Environmental Protection Agency, Region IX, San Francisco. 57 pp. . 1972. Algal bioassay: examples, advantages, and limitations of current approaches. In: Proceedings of Seminar on Eutrophication and Biostimulation. Calif. Dept. of Water Resources, Sacramento. pp. 173-8. Turner-SID G.K. (Association). 1973. Determination of algae in natural waters by fluorometry. In: Fluorometry Reviews-Chlorophyll. Palo Alto, Calif. 4 PP. Yentsch, C.S. 1957. A non-extractive method for the quant- itative estimation of chlorophyll in algal cultures. Nature. 179:1302-1304. and D.W. Menzel. 1963. A method for the determina- tion of phytoplankton chlorophyll and phaeophytin by fluorescence. Deep-Sea Research. 10:221-231. Weber, C.A. 1907. Aufbau und Vegetation der Moore Norddeut- Wetzel, R.G. 1966. Variations in productivity of Goose and hypereutrophic Sylvan Lakes, Indiana. Invest. Ind. Streams and Lakes. 7:147-184. . 1972. The role of carbon in hard water marl lakes. In: Nutrients and Eutrophication: The Limiting Nutri- ent Controversy. R.A. Likens (ed.). Special Symposia Vol. I. Limnol. and Oceanogr. Allen Press, Lawer- ence, Kane. pp 84-97. U.S. Government. 1972. Handbook for Analytical Quality Con- trol in Water and Wastewater Laboratories. National Research Center, Analytical Quality Control Lab., U.S. Environmental Protection Agency, Cincinnati, Ohio. 180 pp. APPENDIX A APPENDIX A It is well known that cells enumerated with the aid of counting chambers are distributed in a Poisson fashion. (Sokal and Rohlf, 1969). Bailey (1959) emphasised that al- though there is an exceedingly small chance of any particular cell finding its way to a given small square of the Whipple micrometer, the total number of cells is so large that quite a lot of the squares are likely to be occupied by one or more cells. The Poisson distribution is very similar to Gaussian or normal distribution when the means are above 10 or so. However, since Poisson distribution is a function of only the observed mean, it becomes noticeably skewed as the means approach zero. Knowing the observed mean, one can simply look up the relative expected frequencies from statistical tables (Sokal and Rohlf, 1969). In figure A1, the observed frequencies closely fit the expected frequencies. Chi Square fitting showed for the three cases depicted in figure A1 there is less than a 0.5% chance that the observed values occurred by chance alone. Therefore, the distribution is Poisson. 158 0.5 0.4 Relative expected frequencies A1. 159 o——-o Observed distribution with a mean of 1.4. e—-e Expected Poisson distribution for a . mean of 1.4. s———e Observed distribution with a mean of 3.2. .— Expected Poisson distribution for a _ mean of 3.2. o——110bserved distribution with.a mean of 5.3. —- Expected Poisson distribution for a mean of 5.3. l ‘ L 6 8 10 Number of cells per micrometer grid Figure of the relationship between observed distri- butions for cell counts (from fifty grid counts per sample and three samples with mean counts of 1.4. 3.2, and 5.3 cells per grid) and expected Poisson distributions for the given means. APPENDIX B APPENDIX B B1. Cell counts as cells/grid and cells/ml for the treat- ment control of AAP nutrients minus phosphorus medium of EXperiment 3 with maximums marked as * and with Cv‘ E g Mean Mean Cv p y cells/grid i 1SD cells/ml i 1SD % O inoculum 8about 104 1 4.2 _+_ 1.6 2.0x104 2: 7.7::103 38 2 7.2 i 3.4 3.5xlo4 i 1.6xlO4 47 1 3 9.5 i 3.7 4.6x104 32 1.8x104 38 5 10.2 i 1.4 b44.9:{104 i 6.6::103 l3 6 8.9 i 3.8 4.3x104 i 1.8x104 43 10 6.4 _+_'3.0 3.1x104 _+_ 1.4x104 47 1 5.7 I 2.0 2.7x104 i 9.5::1045 33 2 8.5 g 3.2 4.1::104 i1.5xlO4 37 2 3 13.2 i 3.9 *6.3x104 :1.9x104 30 5 8.2 i 2.7 3.9x104 35. 1.3x104 33 6 7.4 1 3.3 3.6x104 i1.6x104 44 10 9.2 i 3.5 4.4x104 i1.7x104 38 1 3.0 i 1.7 1.5x104 38.2x103 56 2 2.8 2: 1.8 1.3x104 i 8.7x103 65 3 3 4.0 i 2.2 *1.9x104 i1.0x104 53 5 3.8 i 2.5 1.8x104 i1.2x104 67 6 3.0 i 1.2 1.4x104 1 5.9::103 42 10 2.4 i 1.5 1.2x104 i 7.2::103 60 1 2.8 i 1-8 1.3x104 i 8.7xI035 65 2 5.4 i 2.2 *2.6x104 11.0x104 38 4 3 5.3 i 2.0 2.5x104 2‘. 9.81:103 39 5 4.4 .t 1.3 2.1x104 i 6.3::103 30 6 3.4 i 1.4 1.6x104 i 6.81:103 42 10 1.8 351.4 8.6x103 33 6.9x103 79 aAbout 1O4 cells/ml for all treatment replication. bAccording to the AAP, the maximums are the last cell count at which an increase of 5% Per day took place. This maximum is often not the absolute maximum. 160 APPENDIX B B2. Cell counts as cells/grid and cells/ml for the control plus 0.01 mg P/l treatment of Experiment 3 with maxi- mums marked as * and with Cv‘ E 2 Mean Mean Cv p y cells/grid i ISD cells/ml,i 1SD % O inoculum aabout 1O!I 1 11.8 : 3.9 5.6x104,: 1.9x104 34 2 17.2 : 3.3 8.3x104,: 1.6x104 19 1 3 37.4,: 7.4 1.8x105,: 3.6x104 20 5 47.0,: 7.1 2.2x105,: 3.4x104 15 6 50.9 : 5.9 *2.4x105,: 2.8x104 12 10 48.5,: 4.9 2.3x105,: 2.4x104 10 1 13.8 : 4.0 6.6x104 : 1.9x104 29 2 30.6,: 5.4 1.5x105,: 2.6x104 17 2 3 54.4 : 7.0 2.6x105 :3.3x104 13 5 91.6 :11.0 *4.4x105,: 5.0x104 11 6 95.7,: 9.3 4.6x105,: 4.4x104 10 10 93.5 : 7.6 4.5x105,: 3.6x104 8 1 11.2 : 2.4 5.4x104,: 1.2x104 22 2 19.1,: 4.1 ' 9.2x104 : 2.0x104 22 3 3 46.0,: 7.9 2.2x105 : 4.4x104 17 5 68.7,: 9.1 3.3x105,: 4.4x104 13 6 72.0 :10.7 3.4x10 ,: 5.0x104 15 10 81.1,: 7.6 *3.9x105,: 3.6x104 9 ' 1 13.1,: 3.8 6.3x104,: 1.812104 29 2 37.7,: 4.9 1.8x105 i 2.4x104 13 4 3 72.6,:16.8 3.5x105,: 8.0x1O4 23 5 92.3 :11.9 4.4x105,: 5.7x104 13 6 104.1,: 9.0 *5.0x10 ,: 4.3x104 9 10 102.1,: 8.2 4.9x10 ,: 3.9x104 8 aAbout 104 cells/ml for all treatment 161 replications. APPENDIX B B3. Cell counts as cells/grid and cells/ml for the control plus 0.02 mg P/l treatment of Experiment 3 with maxi- mums marked as * and with Cv‘ E 2 Mean Mean Cv p y cells/grid : 1SD cells/ml : 1SD % O inoculum aabout 104 1 7.9 : 2.8 3.8x104 .t 1.3x104 35 2 12.9 i 2.8 6.2x104,: 1.3x104 47 1 3 27.2 : 7.1 1.3x105 : 3.4x104 26 5 54.6 i 5.5 2.6x105,: 2.6x104 1O 6 80.3,:12.4 3.8x105,: 6.0x104 15 10 116.6 : 9.1 *5.6x105 : 4.4x104 8 1 15.6 i 5.2 7.5x104 : 2.5x104 33 2 41.4 : 6.1 2.0x105 : 2.911104 15 2 3 84.4 : 8.8 4.0x105 : 4.2x104 10 5 188.3 :15.9 9.0x105 : 7.6x104 8 6 205.2 :17.0 *9.8x105 : 8.2x104 8 10 206.6 :18.9 9.9::105 : 9.1x104 9 1 11.2 : 3.3 5.4x102‘ :1.6x101 29 2 23.8 : 4.7 1.1x105 : 2.3x104 20 3 3 47.4 : 5.6 2.3x105 : 2.7x1o4 12 5 96.1 : 7.9 4.6x105 : 3.8x104 8 6 114.6 :15.0 5.5::105 : 7.2x104 13 10 129.2 :12.4 *6.2x105 : 5.9x104 10 1 14.5 : 4.4 7.0x104 : 2.1x104 31 2 45.2 : 7.2 2.2x105 : 3.5x104 16 4 3 88.6 : 8.8 4.2x105 : 4.2x104 10 5 185.6 :22.5 8.9x105 :1.1x10‘3 12 6 218.2 :24.2 *1.0x106 : 1.2::10l3 11 10 193.3 :15.9 9.3::10'5 : 4.4x104 8 8About 104 cells/ml for all treatment replications. 162 APPENDIX B B4. Cell counts as cells/grid and cells/ml for the control plus 0.03 mg P/l treatment of Experiment 3 with maxi- mums marked as * and with Cv' 1: 2 Mean Mean Cv p y cells/grid : 1SD cells/ml : 1SD 76 O inoculum aabout 1O4 1 11.6 : 4.4 5.6x104 : 2.1x104 38 2 15.2 : 3.3 7.3x104 :1.6x104 22 1 3 64.0 :14.1 3.1x105 i 6.7x104 22 5 303.6 :17.3 1.5x106 _+_ 8.3x104 6 6 393.2 :37.2 1.9x106 : 1.8::10l5 9 10 411.2 :12.7 *2.0x106 : 6.1x104 3 1 11.9 : 3.9 5.7x10‘I :1.9x104 ‘ 33 2 22.6 : 6.1 1.1::105 : 2.9x104 27 2 3 38.1 : 5.0 1.8x105 : 2.4x104 13 5 79.1 : 7.6 3.8x105 : 3.6x104 9 6 114.2 : 9.3 5.5x105 : 4.5x104 8 10 149.6,:13.6 *7.2x105 i 6.5x104 9 1 10.7 : 4.0 5.1x104 :1.9x10I 38 2 22.7 : 4.0 1.1x105 _+_1.9x104 18 3 3 36.8 _+_ 6.6 1.8x105 : 3.2x104 18 5 60.4 : 4.9 2.9::105 : 2.3x104 8 6 75.9 : 7.0 3.6x105 : 3.4x104 9 10 98.8 :11.9 *4.7x105 : 2.3x104 12 1 12.4 : 3.2 5.9x104 :1.5x10ZF 26 2 21.9 : 4.0 1.0::10l5 :1.9x104 18 4 3 53.0 : 8.7 2.5::10l3 : 4.2x104 16 5 97.2 : 9.5 4.7::10‘5 : 4.6x104 10 6 119.3 :10.5 5.7x105,: 5.0x104 9 10 157.1 :12.1 7.5x105 : 5.8x104 8 aAbout 1O4 cells/ml for all treatment replications. 163 APPENDIX B B5. Cell counts from Experiment 4 bioassaying two levels of light intensity (260 ft-c and 475 ft-c) with CV. WW 8 a Mean v Mean v p y cellsjmli 1SD j. cells/ml 4:1 SD % 0 2.0x104 : 1.0x104 50 3.5x104 : 1.8x104 51 1 3.024104 : 1.214104 40 4.6x104 : 2.0x104 44 2 7.024104 : 2.6x104 37 7.4x104 : 1.9x104 26 1 3 7.6x104 1". 2.8x104 37 9.2::104 : 2.0x104 22 4 no count made -- 1°3X105.i 2.4x104 19 6 1.6x105 : 3.2x104 21 2.1x105 :1.5x104 7 0 1.0x104 : 6.01:105 60 3.3x104 :1.6x104 48 1 1.0x104 : 5.1x103 51 4.3x104 :1.3x104 34 2 1.1x104 : 5.0x103 45 4.3::104 :1.3x104 34 2 3 1.4x104 : 6.5x103 40 5.3x104 : 7.511103 14 4 no count made - 6.6x104 i 1.7x104 26 6 1.2x104 :1.1x104 46 6.9x104 :1.6x104 23 0 4.1x104 .I 2.0x104 48 6.0x1OT: 2.0::102r 33 1 5.924104 : 2.3x104 39 8.4x104 : 2.1x104 25 2 1.1x105 : 2.2x104 20 1.4x105 : 3.1x104 22 3 3 1.7x105 : 2.9x104 17 1.2x105 :1.8x104 14 4 2.1x105 33.2x104 15 no count made -- 6 3.6x105 : 5.0x104 14 2.6x105 : 4.1x104 16 0 6.4x103 : 6.0241043 94 8.8::105 : 4.4::103 50 1 7.724103 : 7.0x103 95 1.3x104 : 5.0x103 38 2 1.2x104 : 6.5x103 54 6.4x104 : 2.1x104 33 4 3 1.6x104 : 7.024103 44 1.4::105 : 3.7x104 26 4 no count made -- 2:IXI05.i 3.0x104 14 6 4.5x104 : 2.1x104 47 4.5x105 : 7.5x104 16 O 7.0x104,: 3.4x104 49 1.2x104,: 8.0xI03 67 1 9.1x104 : 3.1x104 34 1.4x104 : 7.0x103 54 2 1.5x105 : 3.5x104 23 1.2x104 : 5.5::103 48 5 3 1.6x105 : 3.1x104 19 1.1x104 : 6.0::103 55 4 no count made - no count made -- 6 3.1x105 : 5.5x104 16 1.2x104 : 4.8x103 30 164 APPENDIX B Cell counts, average of three replication, from Experi- ment 5 bioassaying th 88 level of initial algal cell concentration (1.7x10 , 6.0x10 , and 2.1x104 cells/ml) with C between replications. Treatments are shown as I, II,vand III respectively. W r R C e 8 Rep Means v i P cells/ml : 1SD % 0 1.7x103,: 1.6xIOz—- 94 1 2.2x103 :1.8x103 82 2 6.7x103 i 2.4x103 36 3 2.5x104 : 8.7x103 34 4 1.4x105 : 6.0x104 42 5 4.3x105,: 2.4x104 5 7 3.1x106 : 8.0x105 26 11 4.2x106,: 9.0x105 21 0 6.0x103,: 2.5x10T 42 1 1.3x104,: 5.0x103 38 2 8.8x104 : 2.4x104 36 3 3.612105 : 3.0x105 83 4 1.6x106 i 8.8x105 54 5 2.5x106,: 1.0x106 40 7 4.8x105,: 1.5x106 31 11 4.8x106 :_1.4x106 29 O 2.1x104,: 1.112104 52 1 2.0x105 : 1.0x105 50 2 1.1x106,: 5.0x105 45 3 2.8x106 : 1.2x106 43 4 3.8x106,: 1.7x106 45 5 4.5x106 : 2.0x106 44 7 5.0x106 : 2.1x106 32 11 5.2x106,: 2.5x106 48 165 APPENDIX B B7. Cell counts from Experiment 6 bioassaying (a) two levels of light intensity (260 ft-c and 475 ft-c) and (b) cell counts for a portion of the 260 ft-c treatment placed under 475 ft-c on day 4 and cul- tured through day 11. Both (a) and (b) with Cv‘ (a TIT—TM e a Mean v Mean p y cellséml i 1SD % cells/ml i 1SD 0 2.9x10 .i 1.7x10 59 2.8x10 .i 1.7x10 59 1 4.8x103 i 2.2x103 46 5.8x103 i 2.4x103 42 2 2.2::104 _+_ 1.2x104 54 1.2::104 : 7.0::103 58 3 1.5::10‘3 .t 2.0x104 13 7.8x104 .1 2.9x104 37 1 4 7.4::105 : 5.1x104 7 1.8::10r5 : 3.4x104 19 5 1.9x1O6 :1.4x105 7 3.3x105 : 3.5x104 11 6 3.224106 : 5.0x105 16 5.7x105 : 5.7x104 10 7 4.1x106 : 3.4x105 8 8.0x105 :1: 7.0x104 2 O 2.9x10 ,1 1.7x10 59 2.7x10 .i 1.6x10 59 1 3.4::103 :1.8x103 54 5.5x103 i 2.3x103 42 2 2.8x104 : 1.2::104 43 9.6::103 : 5.5::103 57 3 1.924105 : 3.632104 19 6.6x104 -_1-_1.8x104 27 2 4 7.5x105 : 8.6x104 11 1.8x105 : 2.6x104 14 5 1.9::106 : 9.624104 5 3.51:105 : 3.6x1o4 10 6 3.5::106 : 3.4::105 10 6.0x105 : 6.0x104 10 7 4.4x106 : 5.6::105 12 8.4x105 : 8.2x104 9 11 *4.7x106 : 2.2x105 5 *1.2x106 : 1.0::10'5 8 311 *4.4x106 i_6.7x105 15 *1.1x106 £4.2x105 11 (b) R D ION intensity treatment portion from Rep 1 E 2 e a placed under HIGH intensity of day 4. p y cells/mil) 11SD cells/mil); 1SD 4 1.8x105 : 3.4x104 19 1.8x105 : 2.6x104 14 5 1.1x106 : 8.7x104 8 1.2::106 : 6.6x104 5 6 2.3::106 : 2.3::10‘3 10 2.5x106 3: 2.5::10t5 10 7 3.7::106 : 3.7x105 10 4.3x106 : 1.0::106 23 11 5.6x106 .1. 8.3x105 15 5.6x106 $3724105 7 aCounts are for rep 1. Maximums are marked with *. 166 APPENDIX B mesospmmap Ham sow Hs\maaoo moawm.m mas 0 has no moapmspsOosoo Ha .mpsospsosa Has sow >.> mm; mm was so HespHsHo .As«s\oo m as umensn m mom op wosmasoo mm oposv m mam 90% sas\oo 0m we coasnfip Add .msapsob op one soapmsoms>o Basses obfimmmoao Ho nuances mums peace Haoo 02M Tm moasmé m oofimn in censuses". oss Rm moasmm m octane I m.m moaxo.m ”.moaav.m P.m moaso.m H.moaam.m m.m mopsm.m ”.moaxe.e a m.m moaxo.¢ H.mo.Nm.m m.m moasw.m ”.moFNN.P m.m moFNe.n H_mo_xm.m m e.m m0.Me.m H.moaxm.. m.m eopso.m H.moaxm.m m.m torso.m H_moaxm.P m m.> eOFMNM H.moFNm.m o.m coaxe.a H.moaxa.m >.m eoaxm.m ”.mopae.> a m m.» scram.a ”_moaao.> m.> eoFNm.. H.eoasb.m m.m eo_am.n ”.moaxm.a m >.> moaxb.m H.vo_xs.F b.> moFNe.> H.eo—Mm._ m.> soFNm.F H.409Nw.m m >.> MOFNo.m + Mopxm.mp m.b Moasn.m + moaxm.m >.>moasm.m +mo—Me.m F m.m mots; .H. moasmze on measlessoo es en moaned m noun}. 2 m.m moaao.m H mopxe.n m.m moaxm.o H.moaxo.w m.m mOFNs.m H.movsa.e b m.m mopxm.e H mopam.m e.m moasv.m H_moaxm.e >.m moaso.m H.mopsm.m m 0.0 voPNe.m H moaao.w m.m moaam.a ”_moaxe.m m.m moaxe.a H_moFMm._ m m.> eoaxo.m ”.moaam.w m.m eoPN>.> H_moaxm.e m.m soaaa.m ”_moase.> e a m.u eoFMe._ H sopxa.m o.m soaam.a H_eoaxm.> m.m eoFHO.N H_moFNm.F m >.> moaxm.m H.802Nm.. m.> eoFMO.F H_voFNm.F m.> eoFNm.P ”.mowwm.m m v.6 oaxm.m + OFMm.m >.> oaxm.a + owxe.m >.> OFNN.N + oasm.¢ F mm m a? as mice as J44 SW38 maimmfloe T1 sas\oo mp sds\oo mm 86H pap so copsmb m o ooSPse p.34 seasons alum B so she oz 9 m1 .m<¢ as moemmmmSM ms pump mappon as mewHHpsaam>m mousse mashed op moms osflxoac consmo we mao>oa Nam mushcmmmOHn b psosahomsm 809% mm was menace Haoo .mm 167 .msapcob op was cospmsoam>m assess mpammooxo omvos was moms 9:500 HHOO oz .ma mammaa was negosm mo madness so Mose cocks» mswappsmw .mpaoaw Hemam on Ho mmsmoop wwo desks» msaapnsm .mpsospmosp Ham sow >.> mes ma cums madcapmoap Has now Hs\maaoomoaxm.m as: 0 has so soapmaPsoosoo Haoo HespusHs APPENDIX B as eczema m conga m8 mouse m sonata osssleqaoo one :. m.o moasm.m H_ooase.m m.m eoasm.m H moasm.eo m.o moaaa.a H.ooasa.o a m.o moasm.m H.oo.s_.. 8.8 eoasm.. ”_moasm.a m.m moasm.o ”_ooase.m o m.m soasa.a H moaam.e o.s moasa.m H_eoaso.m m.o eo_s_.m H_ooaai.i m a.m eoasm.e_H moasm.a 4.8 moaan.m H_mo.sa.m m.o eoaso.m H.moaso.m a m o.m moasm.a H_eoasa.e m.o moasa.. H.mo.Rm.mo m.o eoasm._ H.eo.sa.m n m.m moawo.o ”_moas..m 4.6 moasm.m ”_moaae.m 2.8 mo_so.m H eoasm.a N m.m moasa.m +mOasm.m n.ommasm.m +moasm.e m.mmoasm.m +moasm.m a ma moasmé H sonata 8.6 mounts. m 80:86 E. moasmm m oofieé Z w m.o moasa.m H_moaso.m m.a moase.e H_mo.aM.m a.» moaam.o H noise.m a .1 m.m eoaam.e ”_moasm.m m.o moas_.m ”_ooaao.m o.a moaum.a H_oo_am.m o n.m eoiso.o H moism.e m.o moasa.n ”_ooasm.m a.o moaso.am.moasm.a m m.o eoasm.n H eoasm.m m.m moaso.m ”_moasa.e m.o scans.“ ”_moasa.m e a 0.8 soasa.. H.eoaxa.n m.o eoaso.m ”.moaso.a o.o eoasm.a H_eo.so.e m m.m moasm.e ”.moasm.e e.o eoaum.a H eo_RN.N o.m moaao.m H.eo_sm.a m m.m oase.m + oawm.e m.o oasm.m + oase.m m.m oasa.a + oasm.m _s 3.2.. as is: as is: ale. sas\oo mm sas\oomm sas\oo mm s o .o ..5. e. .0 ..s. e. .o so> o . .Ao.paoov mm APPENDIX B B9. Cell counts and pH from Experiment 9 comparing by bio- assay the ;.P nutrients diluted with Torch Lake membrane filtered water to AAP nutrients diluted with distilled water. Maximums marked as *. uen 3 11911 B e a DISTILLED WATER TORCH LAKE WATER p p cells/ml 1SD PH cells/ml 1SD PH 0 8‘about 6x10 7. 7 aabout 6x10 7.7 1 L9x104 + 8. 8x105 8. 0 1.6x104,: 8.8x105 8.7 2 1. 0x105_ 2. 5x104 8. 3 1.1x105,: 2.7x104 9.1 1 3 8. 2x105+ 2. 1x104 10.1 6.9x105 : 7.6x104 9.8 5 3.6x106+1.4x105 9.5 2.6x106‘i 1. 6x105 9. 6 7 *4.8x106+ 7. 0x105 8.6 2. 9x106 : 5. 5x105 9. 2 10 4.7x106 : 1,0x106 8.5 *341x1064;_3 3x105 8_9_ 1 1. 6x10 : 8. 8x10 8.0 1. 8x104 : 1. 2x104 8. 7 2 1.1x105 + 2. 4x104 8. 3 2. 2x105: 1 .7x104 9. 2 3 7. 6x105 + 1.1x105 10.1 9.7x105+ 1. 2x105 9. 8 2 5 2. 9x106 + 3. 3x105 9.5 2. 6x106+ 3. 7x105 9. 7 7 4. 2x106 : 4. 0x105 8.6 *3. 5x106 : 4. 3x105 9. 0 10 *4. 5x106 1: 5. 4x105 8.5 1.4x106 6 .4x105 8. 8 1 2. 4x104 : 7. 3x105 8.0 1. 6x10 +9 4x105 8. 7 2 1. 0x105 : 1. 8x104 8. 3 9. 0x104 : 1 .7x104 9.1 3 9.5x105 : L 3x105 10. 3 8. 2x105 + 8. 7x104 9. 8 5 5 3.9x106,: 1.7x105 9.4 2.1x106 + 9. 0x104 9. 6 7 *4.6x106,: 3.2x105 8.3 *3. 8x106 : 5. 4x105 9. 2 10 4.7x106 : 6.§x105 8.4 3. 8x106g;L5. 6x105 8. 8 1 1.7x104,: 8.7x10 8.0 2. 3x106+ 8. 5x105 8. 7 2 1.2x105,: 2.0x104 8.3 1.2x105,: 1. 8x104 9. 2 3 6.7x105 : 4.9x104 10.2 8.0x105,: 8.0x104 9.7 4 5 3.3x106,: 9.7x104 9.8 2.9x106 i 7.1x104 9.6 7 *4.6x106,: 2.2x105 9.0 *3.5x106,: 5.7x105 8.9 10 4.8x106 : 3.4x105 8.5 3.2x106 : 1.7x105 8.7 1 2.0x104 : 9.0x10 8.0 1.5x10 ,: 6.7x10 8.7 2 1.1x105 :,3. 4x104 8. 3 1.0x105 i 2.0x104 9.3 3 4.0x105: 4. 42:104 10.0 6.9x105,: 7. 4x104 9. 7 4 5 2. 9x106 : 4. 2x104 9. 2 2. 7x106_ 1 .3x105 9. 7 7 3. 8x106 + 6.1x105 8. 6 3. 6x106 + 9. 6x105 9. 0 1O *4. 4x1053; 2. 7x105 8. 6 *4. 8x10 6;E2.Ox105 8. 8 aAbout the same for all repligstions. B10. APPENDIX B Cell counts,C , and pH from Experiment 10 comparing by bioassay the AAP nutrients diluted with Deep Lake membrane filtered water to AAP nutrients diluted with distilled water. Maximums marked as *. _— n I I uen s C I uen s C e a DISTILLED WATER ”v pH DEEP LAKE WATER v pH 9 y cells/ml 9; 1SD 7° cells/ml i1SD % o aabout 104 7.7 6about 104 8.2 1 3.4x1o4 41.114104 32 7.5 2.4x1o4 i1.4x104 58 8.5 2 1.8x105 .1 2.9x1o4 16 7.7 1.8x105 3: 2.124104 12 8.7 3 5.8x105‘i 2.6x104 5 9.1 6.9x105 12 3.6x104 5 9.3 1 4 2.0x1o6 .: 3.0x1o5 15 9.2 2.3x1o6 i1.6x105 7 9.4 6 *4.1x1o6 i 4.234105 10 9.0 *3.9x106 2: 5.014105 13 9.0 10 4. 7x106 + 4. 8x105 10 8.5 4. 32106 + 1. 0x106 23 8.5 18 5. 0x106 L5- 0x105 10 8.5 4. 2x10642510 2x105 10 8.5 1 3. 8x104 :1. 1x104 29 7.5 3. 0x104 +1 .3x106 43 8.5 2 2.0x105 i 2.524104 12 8.0 2. 2x105+ _ 3.0::104 14 8.8 3 7.3x1o5 i1.1x105 15 9.1 7.6x105 2‘. 9.034104 12 9.2 2 4 2.3x1o6 11.824105 8 9.2 2.2x106 2.“. 2.214105 10 9.4 6 *4.5x106 35 6.2x105 14 8.8 *3.5x106 2: 2.924105 8 8.9 10 4.724106 3: 3.3::105 7 8.8 3.6x106 3: 3.11:105 9 8.5 18 5.114106999654105 19: 8.5 4.0::106 564-03105 10 8.5 1 3.8x106 i 1.214106 32 7.4 3.0x1o4 i 1.3x106 43 8.5 2 2.4x105 3: 4.1::104 17 8.6 2.424105 i 3.2x1o4 13 8.9 3 6.5x105 i 8.3x103 13 9.3 8.5x105 1: 8.2x1o4 10 9.4 3 4 2.314106 : 3.4x1o4 15 9.3 2.4x106 41.614104 7 9.5 6 *5.1x106 i 4.3x105 8 8.9 *3.7x106 i 3.2x105 9 9.0 10 5.2x106 3: 6. 8x105 13 8.8 4. 4x106 _+_ 6. 4x105 15 9.0 18 5gx1o6 .4. L5. 8x105 11 8.6 4.1x10i7.0x105 17 8.7 1 4.424106; :2 L 2x104 27 7.4 4. 02:10Zr + 2. 0x104 50 8.2 2 2.3x105 : 2.6x1o411 8.9 2. 7x105 + 3.114104 12 8.5 3 5.224105 : 2.9x104 6 9.4 7. 0x105 + 7. 0x104 10 8.9 4 4 2.0x1o6 :t 5.524104 3 9.3 1’7. 6x10 i6 0x106 19 9.3 6 *4.4x1o6 i 2.924105 7 9.0 3. 3x106 + 3. 3x105 10 9.5 10 5.124106 i 4.924105 10 8.7 *4. 0x106 + '7. 2x105 16 9.0 18 5.1::106445;.9:c1o5 12 8.6 4.1x1o6 3.1.14.8:4105 12 8.6 b aAbout 104 for all replications. Tested to be an "outlier",1$%AP, Appendix 11, 1971). re <--~.—- i APPENDIX B B11. Cell counts and C from Experiment 11 comparing by bioassay the AAP Xutrients diluted with Lake Lansing membrane filtered water to AAP nutrients diluted with distilled water. Maximums marked as *. Inoculation error accounted for only two replications of the distilled water treatment. C LAKE LANSING WATER V e a DISTILLED WATER v p 4y cells/ml + 1SD % cells/ml + 1SD % o aAbout 106 aAbout 104 1 3.024104 i 1.014104 34 1.8x104 1 8.7x1o3 47 2 1.454105 i 2.3x1o4 16 1.3x105 38.2x1o4 63 1 3 4.134105 i 1.6x104 4 4.9x1o5 i 7.3x1o4 15 5 3.1x1o6 13.124105 10 2.6x106 i 4.014105 15 7 *4.8x106 i 4.1x105 9 *3.3x106 1 7.014105 21 14 4.8x106 32.814105 6 3.7x1o6 i 6.1x1o5 16 1 3.2x104 i 1.4x1O4 44 3.1x104 31.3x104 43 2 1.424105 i 1.414104 10 2.3x105‘i 2.8x1o4 12 3 5.7x1o5 33.2x1o4 6 9.0x105‘: 7.7x104 9 2 5 4.0x1o6 i 3.6x105 9 *3.1x1o6 i 2.9x105 9 7 *4.4x106 3; 4.214105 10 2.9x106 2: 5.4x1o5 19 14 5.1x106 i 5.0x1oS 10 3.2x106 i 6.2x1o5 19 1 2.2x104 1 1.2x1o6 54 2 2.1x1o5 32.814104 13 3 3 7.9x1ozi 7.3x1o: 9 5 *2.8x10 ‘1 2.8x10 1o 7 2.7x1o6 :4.7x1o5 17 14 2.8x106 33.5x1o5 12 1 2.61104 i 9.6x1o3 37 2 2.6x1o5 i 3.014104 12 3 9.8x1o5 i 6.5x104 7 4 5 *3.7x106 1 7.7x105 21 7 3.4x1o6 37.6x1o5 22 14 3.4x106 12.614105 8 3About 104 cells/ml initially for all replications. 171 APPENDIX B .msoaPNOHHmwh Had pom haawapfisfi Hs\maamo 404 psop.4 + moaxm.4 4.m om mo_s4.m + 40444.? 4.m m4 4oFNN.F + 4o_mm.N 4 9m 0 40:2.N m mound 46 4m moEmN m mozsd 46 8 42%; m 40:8.N m N 6m N 40:44. n + mofim; 46 8 moiN.4 H mosses. m6 Nm mofind H 4036; N n.m Q44o_xN. a + 4o_xo. m m.m s4 moamm.m + 0.x».s m.m mm noise. 4 +4o_na. F _ 4.m N 403R. anmofim. 4+ ta 3 moix4.m14oE; 4.m 4o moss. 0.94036. 4 N. 46 N, 403"». 4+1moEL 4 4.m mm moss. 4+1 1402a; 4.N 44 monN. m m 40:6. 3. m m6 : 40:44. m1 meta. 4 4.m 44 note .m H 4058.: MN Nm mo§4.N H notes 4 mam m 40:8. N +1.mo:£ N 9m N4 nous}. H 40:3; 9m mm Mensa H $38.4 m a 6m mm 4028. m11 4024. 4 Wm 04 moixNfi H 40:3; m6 am not”; H 40:8; N n.m om 4o_NN. a + 4oixo.N N.m as moaxm.m + 4o_NN.P N.m am monN.m + 4oaxa.. a N.m 404 456944 N.m 404 psopam N.m 404 456946 0 mm 44 mm? +w4<1638 mm 4% mm: ”4 waNmflmo mg a a? + H3628 alml o mMMM Hwammom >0 mmm%HwamWom >0 Hoapsoo M m .* mm vegans mpqdoo adafixsz .H\m ms mo. 0 mafia Hoppsoo Amv was .H\z ms 04.0 mdam Hoppsoo M3 .Hoapsoo exam >nomoe cmampaaM mcmhnama AFV mo mammapmmhp map Low m_ quaflhm mm aoaw mm was a mpqfioo HHmo .mFm 172 APPENDIX B .msoapsoaaamg Has N64 saasapasfi Ns\maamo 4oN 456948 .* ms vmxama mazaaNN.N mafia Hoapsoo Amv was :H\N ms 04. 0+Hoapsoo Amv msmppsms ANV mo mpsospmmav on» Now mN psmsaammxm Scam .Hohpnoo H\N ma mo. 0 mama 666m swampaam 0 was mpqsOo Hao0 4 4oan. mla1moNx4.n* Nm noNxo. mEu11oNsN. N ON moNsm. m «74ONNN.N oN a 4oNnn. N m.MoNxo.N mm moNsn. m H.4oNx4. N Nm 4oNNN. N m 4oNxN.N N NN 4oNNm.m H_moNNN.N mm 4oNNc. N H.4oNN>.N O4 4oNNo. N H.4oNNm.N 4 m 4N 4oNxo.m H.moNNm.N mm 4oan.N H 4oNNm.N* 44 4oNNN.N H.4oNH>.N+ m 4N 4oNNo.N H.moNxN.N mm noNNN.m + moNNm.N Nm moNNs.> H.4oNsm.N N Nm LNoNxo. N + NNoNsN. n om moss. m «Loss; Nm 2de + oNfiN N 9 4022.. mi moNxm. N.. R. moNxN. 0 40:2; NN Mona.“ a1 40:64.: 2 4N 4oNN4. N m_MoNxm. N Na moNxN. m 1.moNNN.m 4m M0:26 H.4oNNm.N m 4N 4oNxo.N H.moNN4.N Nn moNxm. m H.4oNxN.N 44 moNsm.> H.4oNxs.N 4 N mN 4oNNm.N H.moNNN.N Nm moNsm.m H 4oNNm.N* 0m moNNN.m H.4oNsm.N m NN 4oNNm.N H_moNxN.N N4 moNxo.m H.4oNxN.N 4N noNNs.m H.4oNNm.N N mN oNNm.> + oNxm. N Nm oNNN. m + oNNN.N mm oNxm.m + oNxm.N N 4 MONNQNWMONNN. N.. N MONNN.N.J11WOINN4N N. 3346* oN NN 4oNNN.N H moNxm. N 44 4oNN4.N H.4oNxN.m O4 4oNNN.N H.4oNNN.m w mN 4oNNo.m H moNon Nm 4oNxo.N H_4oNNN.m 4m 4oNNm.N.H 4oNN4.4 4 NN 4oNxN.N H.moNNs.N mm 4oNNN.N H.4oNNm.m+ mm 4oNx4.N H.4oNNN.4 m N 4N 4oNxN.N H.moNN4.N mm 4oNNN.N H.4oNNN.m NN 4oNNm.N H.4oNNm.4 N Nn 4oNxm.N + 4oNNN.4 m4 moNxm.m + 4oNEN.N on moNxm.m + 4oNxm.N N 4oN 456p44 4oN 456p14 4oN 456944 0 a mmN + HQNENHEO u mmN + Na\maamo u mmN + Ns\maamo N11m1 >0 H\a mwwammoo >0 H\z mr 04.0 >0 Hoapnoo a m .mNm 173 lPPENDIX B ‘R A. v. 1|- 1 Ith .41. 1 I. .maONNNONHamp Has NON HHNNHNHnN Ha\maaoo moNs0.N swaps m 0N 0NN0.N H. CNN .m . I. I. N.N N4”: N. 4444 N.. 44am N was... 0.. 4.44m N NNNNN NN MNNNN N .NNNNN N. 0N 0NM0.4 H. 0Ns4.N mN 40NN . 1.m .N 04 moNN0.4 H. 0N40.N* NH 0N40.m H_m0NN . mm VOUCHM H. mo N . An N m H mots _. Om OFNFJV + .vOPNN.m 00 m . I m O N.. m .v o .l .V w? m _NN Crumb-N + OwNMoF mm M o I M MOPNm m H OrNFoN. NV M mm OFNO —+ 03630 .v . I m OUR m H O—No.m mm 0 N . m . V o .l V o m? OFNF M H OFNOo M o m o _NN m H OwNO m M N4 moNNN 0 + 40Nsm N 04 moNNm.N + 40Nss.w mm moNMm.4 H.m0NxN.H mm moNso.m H.m0NH0.0* N . 1. 4 0 noN N 0 + noNsm 0 0m noNx0.4 + 0NHN.N N 0N 40NNN N H.m0Nxm.N mN 0Nsm.N H. 0NNN.N 4 . 1. n 0N 40NNN.N H. 0Nxm.N+ mN 40Nx4. .H m . + N moNxm N H.n0NNN.0 Nm 0NNN.n H. 0NxN.0 0N 0 0Nxm.N + m0E0; 4 .N 1.m0NN0 N mm moNxN.N + 0NN0.0 0m m0NH0.m H m . 0N W0N90.N_H moNxm.N mm 4wan.w m.mmwmmnw mm moNxN.m m m0N44.0+ m0 moNx4.4 H.mwwmw.w m mN 0Nxm.N H. 0N4 . 4 . 1.m 0NxN.m + 0NxN.0 04 N . 1. . m 1.m 0 N mN 0Nxm N + 0NNN.N m . 1.m moN 0 m H. 0NsN H4 4 N 04 0N90.m + 0NNN.0 0m 40 a . 1.m . 0m noNxN n H. 0NHH.m 0m 0NNN.4 + moNxm. mm moNxm.m H.4 . 4 N N.N H.40Nxm.H mm 0NN0.N H.00Nsm.m m . 1.m .0 m . . N. E... . ., . 4 . N. NE 4. NEW N .N. 0N 0NN0.N .H. 0:3; NN x2 1 . . 1 1 0N woNxN.N.H moNNN.N* mN 4mflxm.m m.mwwwm.m* 0m moNxm.N H.m0Nxm.m 00 m0NN4.H H. 0NN0.0 0N NN H 4 H N.N Ema .N. .NNNHN .N m . H H moNNm._ Hm owxm.m H. 03g.F m . I.n * m morwb.m H. ONHF.P m HN 0Nxm.N + 0NNN.N 4 . 1.m . N4 0Nx0 m H. 0NNN.H 4m 0NNH. + 4 . mN 40:8; H moNxN..m mm 40NH0.m H moNxN.N m4 M0386 H. mogum ms moNxN.m H 40NMN.N* 4 N . 1 0NEN+ 022.0 0m 0:25..m . m 1.4.200 4 $40 OHNO m + Organ;V N..—4 ovum—KN. H OFNm. m . I. OFNN 0 0m MOSSN.H. + 0:3.m N moNN0.0 psop4 moNN0.m NsonaN Nm moNmem0H 0Hm0.m 00 noNN0.4 H.W0NNN.H N >0 N\N ms m0.0 >. E mmN Hs\maamo a 0mN1n7Hs\mHHmo NNZ NE 04.0 0 NNN 48 m0.0 >0 N\z ma 04.0 N N .* ms umtha mass Hm. . . .44....NNNHNNN 2.4.44 4ka ”N.N. N.N..NNN HNONNNNNNN Ema _. m Gm fimgg A V P spmmap esp How #— pamsHHmmMm Sony 0 was quSoo Hamo .HNm MICHIGAN STATE UNIVERSITY LIBRARIES 0 3056 5992 III! 'I 3 1293