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A" ., . “1]"; l-J l V; r’; .r~- '95? ’(c A . ‘ < ’ fi “013-. .‘D-m. “q.- - '_ ah; m o uni-nix? SIAM (}\Q~9‘%(’bUb mem HIGAN STATE UNIVERSlTY Ll RARIE HUI “HIE. .H «was ‘ 3 1293 00563 0649 LIBRARY Michigan State University h..— This is to certify that the dissertation entitled Ecology of the Cryptophyceae in a North Temperate Hardwater Lake presented by William D. Taylor has been accepted towards fulfillment of the requirements for Ph.D. degreein Botany and Plant Pathology Mabrpfofefi' Mflflmxfifimw/ Co-chairperson, Guldadge— Committee MS U i: an Affirmative Action/Equal Opportunity Institution 0-12771 MSU RETURNING MATERIALS: Place in book drop to LIBRARIES remove this checkout from .—:,—. your record. FINES will ' be charged if book is returned after the date stamped below. 30.2198 @909 ECOLOGY OF THE CRYPTOPHYCEAE IN A NORTH TEMPERATE HARDWATER LAKE BY William D. Taylor A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Botany and Plant Pathology 1988 ABSTRACT ECOLOGY OF THE CRYPTOPHYCEAE IN A NORTH TEMPERATE HARDWATER LAKE BY William D. Taylor The Cryptophyceae is a poorly understood small class of single celled flagellate algae with a ubiquitous distribution, often cited for large contributions to phytoplankton biomass. Interest in cryptophyte ecology has recently increased as information on their nutritional quality, short turnover times and intermittent dominance has accumulated. The objectives of this research were to (1) characterize short-interval cryptophyte dynamics within the framework of the annual phytoplankton community structure, (2) measure in gitg cryptophyte productivity for comparison with total phytoplankton community productivity, and (3) evaluate the impact of grazing losses to the cryptophytes. Routine limnological sampling was conducted biweekly while cryptophyte samples were collected daily over an annual period (1982-83) from phosphorus limited Lawrence Lake, Michigan. Only 20 of 121 species of algae contributed greater than 5% of the total biovolume at any particular time. Algal biovolume was often dominated by large unicellular species. Microflagellates (<10 um) constituted ca. 80 percent of the total algal units annually but their contributions to algal volume were <10%. Cryptophytes dominated the phytoplankton community during autumn (50% maximum by volume). Two cryptophyte species dominated within the group; Bhgdgmgnas mingtg (~70 um3) was abundant and unusually stable (100-300 cells-mL'1 80% of the time), Cryptomonas grggg (#1600 um3) was less abundant (rarely >100 cells-mL'l). An analysis of observed growth rates based on 2-day sampling showed that growth and loss was negligible (i.e. :6 >7 days), 52% and 34% of the time for Bhodomonas and gryptgmgnag, respectively. Few periods of sustained growth occurred by either species. 14C productivity and zooplankton grazing studies were conducted during the summer and autumn, 1984. Cryptophyte species productivity was determined using track micro- autoradiography. Unexpectedly, cryptophyte contributions to productivity were relatively less than their contributions to phytoplankton biovolume and cryptophyte carbon-based growth rates were lower than the phytoplankton community growth rates. Mixotrophic cryptophyte nutrition and temporary spatial patches of refuge from predation resulting from simultaneous differential migration by zooplankton and cryptophytes were discussed to explain the persistance of cryptophytes under high cladoceran grazing pressure, minimal 14C productivity and low growth rates. To Karen and Kristen iv Acknowledgments It was a privilege to work with Dr. Robert G. Wetzel at the MSU Kellogg Biological Station (KBS), a unique limnological institute. I am most grateful for Dr. Wetzel's support and guidance throughout my tenure. At KBS extensive technical and field assistance was provided by JoAnn Burkholder, Sandra Marsh Ford, Anita Johnson, Rich Losee, Jay Sonnad, Karen Taylor, Kristen Taylor, Paul Wetzel and Pam Wetzel. Support services were provided by Char Adams, Alice Gillespie, John Gorentz, Carolyn Hammarskjold, Dolores Teller, Steve Weiss and Art Wiest. Assistance on campus from Phyllis Robertson and especially Jan McNitt was invaluable. I thank committee members Drs. Donna King and Clarence McNabb for guidance early in my program, and Dr. Alan Tessier for graciously stepping in to help me complete my program. Dr. Mike Klug gave me his sage advice, the run of his laboratory, and his friendship. Dr. George Lauff's services on my behalf go well beyond normal expectations and require a special thanks. Dr. Peter Murphy agreed to chair my committee in the 11th hour for the dissertation defense. His long distance advice and support have been outstanding and indispensible. For technical advice and discussion I frequently sought and received the willing counsel of Drs. Mike Coveney, Robert Moeller and Phil Robertson. Autoradiography skills arrived at the lab via the Burkholder conduit from Dr. Gordon Robinson; to both I offer my appreciation. Taxonomic assistance with scaled chrysophytes was provided by Dr. Jim Wee, and with centric diatoms, by Hannelore Hakansson. Collaborative research with Drs. Mike Coveney and Mathew Leibold, and extended crewing with Dr. Rick Carlton resulted in long fruitful discussions in the confines of a row boat. A special comradery developed during those times. For two years I have been counseled and encouraged by Mississippi colleagues to complete this work. I greatly appreciate the support provided by Ms. Barb Kleiss, Mrs. Dwilette McFarland, Drs. Rex Chen and Mike Smart; special thanks to Dr. John Barko for his many efforts and patience on my behalf, and for support from the USACE, Waterways Experiment Station. I cannot begin to express the importance of the support and sacrifices given by Karen, my wife, and Kristen, my daughter over the past seven years in this degree program. To them I give thanks and my love. Financial support came from grants to Dr. R. G. Wetzel by the U. S. Department of Energy (DE-AC02-EV01599 and DE- FGOZ-87ER-60515, COO-1599-310) and the National Science Foundation. vi TABLE OF CONTENTS Page LIST OF TABLES . C O C C O O O C O O O O O O 0 LIST OF FIGURES O I O O O O O O O O O O O O I O CHAPTER 1: PHYTOPLANKTON COMMUNITY DYNAMICS IN LAWRENCE LAKE OF SOUTHWESTERN MICHIGAN Introduction . . . . . . . Site Description . . . . Materials and Methods . Results and Discussion Temperature . . . Light . . . pH, conductivity, Silica . . . . . Nitrogen . . . . Phosphorus . . . Chlorophyll a . . . Primary productivity . . . . Phytoplankton community dynami 5 Total cell concentration . Total algal units . . . . . Total cell volume . . . . . Phytoplankton divisional dynamics Euglenophyta . . . Pyrrhophyta . Cryptophytes Diatoms . . Cyanophyta . Chrysophyta Chlorophyta Microflagell oooflooooo o o o o ff. 0 o o o h< ini o o o 0 Ho 0 o o o lka C summary 0 O O O O O 0 References . . . . . . ate CHAPTER 2: SHORT-INTERVAL CRYPTOPHYTE DYNAMICS AND GROWTH RATES OVER AN ANNUAL PERIOD . Introduction . . . . . . . . . . . . . . . . Materials and Methods . . . . . . . . . . . Results and Discussion . . . . . . . . . . General cryptophyte dynamics . . . . Short interval cryptophyte dynamics . vii 102 102 103 104 104 107 Depth variations . . . . . . . . . . . . Effects of sampling interval on observed seasonal dynamics . . . . . . . . . . Effects of sampling interval on growth rate Summary . . References . CHAPTER 3: PRODUCTIVITY OF THE CRYPTOPHYCEAE VERSUS GRAZING IMPACTS DURING EPILIMNETIC DEEPENING IN AUTUMN . . . . Introduction . . . . . . Materials and Methods . . . Site description . . Sampling schedule . . Physical and chemical Phytoplankton . . . . Zooplankton Sampling Zooplankton grazing . Nuclear track microautoradiography (NTM) Results and Phytoplankton dynamics . . . . Zooplankton dynamics and grazing Cryptophyte productivity . . . . Summary . . References . NTM laboratory procedure . Labeling procedure Field methods . . Sample processing . . . . Quantification of zooplankton grazi g rates . . . . . . . . . . . . . . n Field methods . . . . . . . The leakage problem . . . Discussion . . . . . . . . Appendix A. Phytoplankton Species List . . . . . . . Appendix B. Abundance of Bhgggmgnag minute and Czyptomogas 'ezosa' in Lawrence Lake from August 1982 until August 1983. . . . . . viii 116 121 124 145 147 151 151 153 153 154 154 155 159 160 161 163 164 165 166 166 167 168 173 182 195 204 227 230 238 242 LIST OF TABLES Table page 1.1 Morphometric and limnological parameters for Lawrence Lake, Michigan. . . . . . . . . . . . 4 1.2 Number of phytoplankton species by major group, and dominant species during the annual cycle from August 1982 through August 1983. . . . . . . . . . . . . . . . . . . . 33 2.1 Specific growth rates (k) in 1n units and doubling times (G) reported in the literature for field and laboratory studies of Erxntemenae and Bhodemgnae. - - - - . . ~ - - . 134 3.1 Results of one-way ANOVA to examine horizontal patchiness of phytoplankton in Lawrence Lake, Michigan, using Bhgdgmgngs miggta as a test organism. (means as cells-mL' ) . . . . . . . . . 157 3.2 Dominant phytoplankton species (2 5% of total biovolume) listed from most to least abundant (left to right as biovolume) in Lawrence Lake, Michigan. . . . . . . . . . . . . . 183 3.3 Specific growth rate (R) and doubling time (G) for Gruesomenas 'eresa' (Ce). Bhodemenas mingta (Rm) and the phytoplankton community (pc) based on the ratio of carbon fixed per day to cell carbon . . . . . . . . . . . . . . 207 ix LIST OF FIGURES Figure 1.1 Daily solar radiation (Photosynthetically Active Radiation, g cal-cm"2-day"1 400-700 nm) (upper) and depth-time isotherms ('C) (lower) over an annual cycle in Lawrence Lake, Michigan. Water temperature at 2 m and total heat content (upper) and Schmidt stability (lower) over an annual cycle in Lawrence Lake, Michigan. . . . . Light characteristics over an annual cycle in Lawrence Lake, Michigan; (a) Monthly mean photosynthetically active radiation (PAR), (b) Secchi water transparency depth, (c) PAR and the percent of surface light at 8 m, (d) Light extinction coefficients (n) in two depth-strata . . . . . . . . . . . . . . . . . . pH (upper), conductivity (center), and alkalinity (lower) at 2 m and 6 m over an annual period in Lawrence Lake, Michigan . . . . Total alkaline phosphatase activity (unfiltered lake water) (upper) and the ratio of alkaline phosphatase activity to chlorophyll a concentration (lower) over an annual cycle in Lawrence Lake. . . . . . . . . . Chlorophyll a concentration (corrected for phaeophytin) over an annual cycle in Lawrence Lake. . . . . . . . . . . . . . . . . Primary productivity of phytoplankton over an annual cycle in Lawrence Lake, Michigan; integrated areal productivity in the 0-8-m stratum (upper), integrated volumetric productivity in the 0-4 m and 4-8-m strata (center), and percent of total 0-8 m carbon fixed in the 0-4 m and 4-8-m strata (lower). All points were corrected for depth-volume variations . . . . . . . . . . . . . . . . . . page 13 15 18 23 27 29 Percentage of algal cells within major phytoplankton groups in the 0-4-m stratum (upper) and 4-8-m stratum (center), and total cell concentrations (lower) in those strata over an annual cycle in Lawrence Lake, Michigan. Percentage algal units within major phyto- plankton groups in the 0-4-m stratum (upper) and 4-8-m stratum (center), and total algal unit concentrations (lower) in those strata over an annual cycle in Lawrence_Lake, Michigan. Annual mean percentage of algal units by phytoplankton groups: Euglenophyta (EUG), Pyrrhophyta (PYR), Cryptophyta (CRYP), diatoms (DIA), blue-green algae (B-G), Chrysophyta (CHRY), Chlorophyta (CHL), microflagellates, <6.0 pm diameter (MF). . . . . Percentage biovolume within major phyto- plankton groups in the 0-4-m stratum (upper) and 4-8-m stratum (center), and total phytoplankton volume (lower) in those strata over an annual cycle in Lawrence Lake, Michigan. . . . . . . . . . . . . Total dinoflagellate cell volume in two depth-strata over an annual cycle in Lawrence Lake, Michigan. . . . . . . . . . . . . Annual mean percentage cell volume by phytoplankton groups in two depth-strata over an annual cycle: Euglenophyta (EUG), Pyrrhophyta (PYR), Cryptophyta (CRYP), diatoms (DIA), blue-green algae (B-G), Chrysophyta (CHRY), Chlorophyta (CHL), microflagellates, <6.0 um diameter (MF). . . . . Total dinoflagellate cell concentration in two depth-strata over an annual cycle in Lawrence Lake, Michigan . . . . . . . . . . . Cell concentration of selected Pyrrhophyta species in two depth-strata over an annual cycle in Lawrence Lake, Michigan. The species are Gymnodinigm helvet um, geratigm Wan-Wm Len—diam. gatugensis, 2. pglgniggm and 2. willgi . . . . Cell concentration of selected Chrysophyta and diatom species in two depth-strata over an annual cycle in Lawrence Lake, Michigan. xi 37 40 43 46 52 54 56 59 1.17 The species of chrysophytes are Q1ngbrygn divergens, Mallomonas spp., Chrysosphaergl1a 10ng1s p1n a ands St1chogloea doederleinii, and the species of diatoms are Cyclotella miehieeniene.-Aeterienelleferme.§ Wandzmflerieereteneneieo-..... 61 Total cryptophyte cell volume in two depth- strata over an annual cycle in Lawrence Lake, MiChigan O O O O O O O O O O O O ‘ O O O I O 0 O O O 64 Cell concentration of selected Chlorophyta and Cryptophyta species, and microflagellates (<6 um dia) in two depth-strata over an annual cycle in Lawrence Lake, Michigan. The species of chlorophytes are Botryococcus braun11, Sphaerocyst1s schroeteri, Planktgnema lanterborni, Cruc1genia ecta laris, and of cryptophytes are Cryptomonas 'erosa-ovata', BELL—QHOHIOD minute V- neeneeieneLse and thablepharis ovg1is . . . . . . . . . . 67 Total diatom cell volume in two depth-strata over an annual cycle in Lawrence Lake, MiChj-gan O O O I I O I O O O O O I I O O O O O 0 O 7 o Total diatom algal units in two depth-strata over an annual cycle in Lawrence Lake, Michigan . . . . . . . . . . . . . . . . . . . . . 73 Total diatom cell concentration in two depth-strata over an annual cycle in Lawrence Lake, Michigan. . . . .‘. . . . . . . . . 75 Total Cyanophyta cell volume in two depth-strata over an annual cycle in Lawrence Lake, Michigan. . . . . . . . . . . . . . 79 Cell concentration of selected Cyanophyta species in two depth-strata over an annual cycle in Lawrence Lake, Michigan. The species are Chrgocgcggs 11mget1gug, ggelosphaer1um pa1idum, Gomphosphagr1a amine. 'Ap___2§ehanoca -Apbene_tb_e£e' and An__agna f1gs;aguae. . . . . . . . . . . . . 82 Total Chrysophyta cell volume in two depth-strata over an annual cycle in Lawrence Lake, Michigan. . . . . . . . . . . . . . 85 xii Total Chrysophyta algal units in two depth-strata over an annual cycle in Lawrence Lake, Michigan. . . . . . . . . . . Total Chlorophyta cell volume in two depth-strata over an annual cycle in Lawrence Lake, Michigan. . . . . . . . . . . Total microflagellate (<6 um dia) cell volume in two depth-strata over an annual cycle in Lawrence Lake, Michigan . . . . . . Contribution of cryptophyte cell.volume to total phytoplankton cell volume in 0-4-m (upper) and 4-8-m (center) strata, and total phytoplankton cell volume (lower) in Lawrence Lake, Michigan, at two-week sampling intervals. . . . . . . . . Bhedemenes.minete abundance by depth- strata in Lawrence Lake, Michigan. . . . . . crxntemenee 'ereee' abundance by depth- strata in Lawrence Lake, Michigan. . . . . . Cryptgmgnag phaseolus abundance by depth- strata in Lawrence Lake, Michigan. . . . . . minute and eretemenee 'ereee' cell abundance curves smoothed through the calculation of three-point running means. . . . . . . . . . . . . . . . . . . . Seasonal dynamics of Bhgdgmgnas in the 0-4-m stratum at sampling intervals ranging from 2 to 32 days. See text for discussion of different lines in each panel. Seasonal Ehgggmgnas cell abundance (upper) and observed growth rate constants (kn) calculated at sampling intervals from 2 to 30 days in the 0-4-m stratum (remaining panels) . . . . . . . . . . . . . Seasonal Cryptgmgnas cell abundance (upper) and observed growth rate constants (kn) calculated at sampling intervals from 2 to 30 days in the 0-4-m stratum (remaining panels) . . . . . . . . . . . . . Annual mean kn Of BhQQQanefi and QIXDLQaneé calculated at sampling intervals of 2 to 30 xiii 88 92 95 106 109 111 113 119 123 128 130 days in the 0-4-m stratum. Values for positive growth (kn) and negative growth (-kn) were meaned separately . . . . . . . . Frequency distribution of observed kn for Bhgggmgngs in the 0-4-m stratum. . . . . . . Frequency distribution of observed kn for Cryptgmgnas in the 0-4-m stratum . . . . . . Switching frequency as the percentage of pairs of adjacent kn values with opposite signs at sampling intervals of 2 to 30 days in the 0-4-m stratum. . . . . . . . . . Daily solar radiation (photosynthetically active radiation, 400-700 nm) (upper) and Secchi disk transparency, temperature at the two-meter depth and depth of the mixed layer (lower) in Lawrence Lake, Michigan during 1984 . . . . . . . . . . . . Percentage biovolume of major phytoplankton groups in the 0-4-m stratum (upper) and phytoplankton volume (lower) in that stratum in Lawrence Lake, Michigan in 1984. The large spike in late October (lower) was near all Qhryggphaerella biomass . . . Alkaline phosphatase activity (APA)(upper), chlorophyll a (Chla)(center) and the ratio of APA to Chla (lower) in the 0-4-m and 4-8-m strata in Lawrence Lake, Michigan in 1984. . . . . . . . . . . . . . . . . . . Seasonal variations in the total volume of the Cryptophyceae during 1982 and 1984 in Lawrence Lake, Michigan. . . . . . . . . . Percent algal units and algal volume by size classes (upper) and total algal units and total phytoplankton volume (lower) . . . grxntemenee and Bhedemenee cell abundance (upper), volume (center) and the percent species volume of the total volume (lower) . The seasonal variation in cell volume of Bhedemenee (upper) and erntemenee (lower) in Lawrence Lake, Michigan in 1984. (tSoEo, 11:25-30) 0 o e e o e e o e o o o o xiv 133 136 138 144 175 178 180 186 189 191 194 Abundance of Daphn1; and D1aptgmu§ in the light period presented as the percent of dark period abundance in various depth-strata. (data provided by M. Leibold). . . . . . . . . . . 197 Day-night Depnnie geleete nendetee abundance by depth-strata from July through October, 1984. Eight samples from four stations were combined to form one 84-L composite sample for abundance estimates at each depth stratum. (data provided by M. Leibold.) . . . . . . . . . . . . . 200 Distribution of grazing by Dapnn1a, Q1ap§_mu§ and cyclopoids during dark (upper) and light (middle) periods and by particle size class (<10 um, left and 10-30 um, right) as a percentage of the total 0-4-m stratum grazing rate for the dark and light periods. Zooplankton grazing rates during dark and light periods in the 0-4-m stratum for <10 um and 10—30 pm size classes (lower). . . . . . . . . . . . . . . . . . 203 In eitn productivity of cryptenenee and Bhodomonas populations determined by nuclear track microautoradiography in Lawrence Lake, Michigan, 1984 (tS.E., n=3-8) . . . 206 Ratio of grxntenenes and Bnedenenee cell volume to total phytoplankton volume and the ratio of Crypggmgnag and Bhodomonas primary productivity to total phytoplankton productivity . . . . . . . . . . . . . . . . . . . 210 Growth rate constant (k) of Bhgggmgnag, Cryptgmgnas and the total phytoplankton community based on the ratio of carbon fixed per day to total cell carbon. Carbon was derived from cell volumes according to the equations of Strathmann (1967). There were no corrections for dark respiration . . . . . 212 Bhgggmgnas specific growth rate as the ratio of carbon fixed per day (NTM) to cell carbon (volume conversion), total phytoplankton community specific growth rate as the ratio of carbon fixed per day (14C productivity) to total phytoplankton carbon (cell volume conversion), and the daily loss rate constant by zooplankton grazing on the <10 um size class (as the fraction of the water filtered per day) (upper). Seasonal XV dynamics of Bhodgmgnas and particles in the <10 um size class as total volume (lower). . . . . 217 Cryptgmgnas specific growth rate_as the ratio of carbon fixed per day (NTM) to cell carbon (volume conversion), total phyto- plankton community specific growth rate as the ratio of carbon fixed per day (14C productivity) to total phytoplankton carbon (cell volume conversion), and the daily loss rate constant by zooplankton grazing on the 10-30 pm particle size class (as the fraction of the water filtered per day) (upper). Seasonal dynamics of Czyptgmgnag and particles in the 10-30 um size class as total volume (lower) . . . . . . . . . . . . . . . 219 CHAPTER 1 PHYTOPLANKTON COMMUNITY DYNAMICS IN LAWRENCE LAKE OF SOUTHWESTERN’MICHIGAN Introduction An intensive and continuous limnological investigation of Lawrence Lake and its wetland areas was begun in 1967 and extended through 1986. During that period, extensive information was gathered, summarized, and synthesized, particularly regarding the interaction and functional role of wetlands and aquatic macrophytes in the productivity and carbon cycling of lakes. Wetzel (1975, 1983) used many of the data from Lawrence Lake during this extended period to illustrate functional processes within lakes. In so doing he also summarized and referenced many of the numerous publications resulting from research on the lake. The later volume (Wetzel 1983) contains a comprehensive summary of the limnology of Lawrence Lake. A detailed study of the phytoplankton community and its seasonal dynamics over an annual period was undertaken in 1968 but remains unpublished in detail. Graffius (1963), in a comparative study of Lawrence Lake and a nearby acid bog, provided the first qualitative summary of algal species occurring in this water. In his treatment, species 1 2 distributions within a variety of sampling sites in and around the lake were noted and subjective references were made to seasonality and abundance. Where_the phytoplankton are discussed in later studies, emphasis was placed on a few selected species of special interest (Wetzel et al. 1972, Manny 1972, McKinley and Wetzel 1979, Ward and Wetzel 1980a, Crumpton and Wetzel 1982, Stewart and Wetzel 1982) or detailed data were presented with minimal discussion (Stewart and Wetzel 1986). The phytoplankton data presented by Stewart and Wetzel (1986) were from studies conducted in 1967 and 1968 which makes them historically invaluable but not necessarily representative of current patterns. Taylor and Wetzel (1984) gave a more detailed discussion of phytoplankton community dynamics in Lawrence Lake but it covered only the period August through February and was restricted to the upper 4 m of the lake. The present study was undertaken (1) to characterize the community structure and seasonal dynamics of phytoplankton in Lawrence Lake relative to the physical and chemical constraints of the habitat and (2) to establish the background with which to compare the results of high frequency sampling for selected cryptophyte taxa. A detailed discussion of the high frequency sampling has been relegated to Chapter II of the dissertation. 3 Site Description Lawrence Lake is a small, dimictic, hardwater lake with low pelagic productivity in southwestern Michigan, U.S.A. The lake has been described with morphometric, chemical and biological data given in numerous sources (e.g. Rich et al. 1971, Wetzel et a1. 1972, Wetzel 1983). A brief summary of these characteristics is presented in Table 1.1. Materials and.Methods Phytoplankton samples were routinely collected and analyzed from one station over the central depression of the lake basin. Crumpton and Wetzel (1982) evaluated phytoplankton patchiness in Lawrence Lake and consistently found no greater variance among five stations than between replicates at a single station. Further periodic testing in this study at four stations supported their findings. Vertically integrated phytoplankton samples were collected biweekly between 10:00 and 14:00 with a 4-m long Van Darn-type sampler from 0-4, 4-8, and 8-12 m depths. These depths closely approximated the epi-, meta-, and hypolimnion during summer stratification. The sampler had an inside diameter of 5 cm with a total capacity of about 5 L. A water sample was poured into a bucket for mixing and a 130—mL subsample was immediately preserved with 1 mL of acid Lugol's solution (Vollenweider 1974). Table 1.1. Morphometric1 and limnological parameters for Lawrence Lake, Michigan. Parameter Value or Range Surface Area (h) Volume (m3) Maximum Depth (m) Mean Depth (m) Relative Depth (%) No3 + N02 nitrogen2 (mg-L'l) NH4 nitrogen2 (mg-L'l) Total Dissolved Phosphorus3 (mg-L'l) Soluble Reactive Phosphorus3 (mg-L'l) pH Alkalinity (meq-L‘l) Conductivity (umhos-cm'l, 25 °C) SiOz2 (mg-L'l) Secchi Disk Transparency (m) Annual Mean Productivityzr4 (mgc-M'Z-day‘l) Chlorophyll-a5 (corrected) (ug-L'l) 4.96 292,350 12.6 5.89 5.01 1.5 - 5.0 0.25 - 0.30 0.001 - 0.010 < 0.005 7.6 - 8.4 3.7 - 4.7 400 - 571 6 - 11 1.8 - 10.9 79.5 - 119.1 (93.3) 0.32 - 3.19 1Morphometric values are from Wetzel et a1. (1972). 2Wetzel 1983. 3Wetzel 1972. 4Fourteen-year range and (mean). 5Range of biweekly concentrations in the 0 to 8-m stratum (1982-1984). 5 UtermOhl's (1958) sedimentation method was used to prepare the samples for identification and enumeration. The recommendations of Lund et a1. (1958) were followed for counting precision. In all cases, between 600 and 2000 total algal units were counted giving a counting error of less than ten percent for each sample. Complete transects of the chamber diameter were counted at several magnifications (360x, 180x, 90x); the magnification was dependent upon the size and abundance of the cells being evaluated. The entire chamber was used to enumerate large forms such as Qera§1gm. Species identification under oil immersion (900x) was routine. Counting and cell measurements were made with a Wild M40 inverted microscope. Twenty-five mL samples were settled for at least 15 h within a styrofoam insulated box to minimize convective currents caused by temperature fluctuations throughout the day. Biovolumes were calculated for each species using formulae for solid geometric shapes most closely matching the cell shape. Mean cell volumes were based on individual cell volume calculations (Appendix A). Biovolumes were determined seasonally when changes in cell size were apparent (8-9- W m V- M)- Light and temperature measurements were made at 1-m intervals with a LiCOR model L1-185 quantum photometer and a YSI 43JD thermistor, respectively. Samples for determination of conductivity, alkalinity, pH, alkaline 6 phosphatase activity (APA), and chlorophyll a (Chla) were collected with an opaque 3-L Van Dorn bottle at 0,1,2,3,4,5,6,7,10 and 12-m depths. Primary productivity incubations were made at 0,1,2,3,5,7,10 and 12-m depths. Biweekly sampling was standard throughout the study but Secchi disk transparency, light (as uEinst-m“'2os'l PAR) and particularly temperature were often measured at more frequent intervals. Temperature, for example, was measured daily from mid-October to mid-November 1982 during epilimnetic destratification and every other day from March through June 1983 during restratification. Because phytoplankton samples were integrated over 4-m intervals, equivalent integrated values were determined for some of the parameters that were measured at discrete depths. Integral mean values, i.e. adjusted for differences in volume with depth, were calculated for primary productivity, APA and Chla for 0-4 and 4-8-m strata. APA of whole lake water samples was measured by the enzymatic hydrolysis of non-fluorescent 3-0-methyl fluorescein phosphate mono-cyclohexylammonium to the fluorescent product, 3-0-,ethyl fluorescein as slightly modified from Hill et a1. (1968) and Perry (1972) by Wetzel (1981). The 14C uptake method of Steemann Nielsen (1951, 1952) was used to measure primary productivity. Specific details of our methods are given in Wetzel and Likens (1979). One 7 mL of 14C as Nafil4CO3 with known specific activity ranging from 5-8 uci-mL’l (18.5-29.6 x 104 Bq) was injected into replicate 125-mL glass stoppered light bottles and non-replicated dark bottles. Samples were incubated 1n §1§g from about 10:00 to 14:00 at the depths from which the samples were collected. Fifty-mL aliquots were filtered onto HA Millipore filters (0.45-um pore size) and analyzed by Geiger-Mfiller radioassay (Nuclear-Chicago D-47 of known counting efficiency). Chlorophyll was measured using the trichromatic method of Strickland and Parsons (1968) as presented by Wetzel and Likens (1979). Samples of 500 to 750 mL were filtered onto AA Millipore filters (0.8-um pore size) at a vacuum differential of less than 0.5 atm. Alkalinity was determined by titration with H2804 using a mixed indicator. Conductivity was measured at 25°C with a Yellow Springs Model 31 conductivity bridge. A Coleman 38A pH meter was used to measure pH in the lab with samples at room temperature. Results and Discussion IEEDQIQEEIQ Temperature patterns in Lawrence Lake were typical for north temperate dimictic lakes of moderate depth and surface area (Figure 1.1). The lake was highly stratified in August 1982 with epilimnetic deepening commencing in September. Figure 1.1. Daily solar radiation (Photosynthetically Active Radiation, g cal-cm'z-day'l 400-700 nm)(upper) and depth-time isotherms (‘C) (lower) over an annual cycle in Lawrence Lake, Michigan. 03< 1.2. mwmw Nmmp 23—. >52 mm< m5). mm“. 25. Own >OZ FOO mum GD< 11111 11,11.11,11111,,11,111 1111,, ,, 11 ,,111111,111,11 111111 11111111,,11 .111 11 111 1. 1 1 , 11 (w) HidECl (u-Kep-z-wo-Ieofi) uva Figure 1.1 10 The lake continued cooling until autumn turnover during the first week of November. Autumnal circulation of Lawrence Lake has occurred within :1 week of 31 October since 1968 (Wetzel, unpublished). During this study southwestern Michigan had the mildest winter in 50 years. Permanent ice cover did not form until mid-January and it was gone again by 3 March. A warming trend during the week before and after ice-out led to an increase in surface water temperatures to about 7’C with ‘weak stratification. This thermal discontinuity was followed by a cooling period that resulted in a spring circulation towards the end of March. A persistent stratified water column followed an intense heating period mo.uueo._aomv E5 E0 .a 703.15% A15 5d 500% TI. c 1983 1982 F.igUre 1.3 16 changes in light at l-m intervals through each of the strata. Extinction coefficients varied from 0.279 to 0.711 m‘1 which was well within the range for Lawrence Lake (Wetzel 1983). n was always greater in the surface waters than in the 4-8-m stratum except in July and August when greater Chla concentrations developed in the metalimnion. Historically, and in this study, increased phytoplankton productivity and to a lesser degree increased surface temperatures in June and part of July lead to massive precipitation of calcium carbonate (otsuki and Wetzel 1974) which contributed to the observed increase in n. From these data it is clear that light limitation was rare and that in Lawrence Lake as much as 90 percent of the lake volume was in a light regime adequate to support most photoautotrophs during much of the year. During the stable stratified period adaptation to lower metalimnetic light levels is likely common. Accumulation of phytoplankton in the metalimnion is largely dependent upon growth rates being greater than losses by sedimentation. Wetzel (1983 and unpublished) found oxygen, photosynthetic productivity and biomass (as chlorophyll) maxima in the metalimnion of Lawrence Lake for 18 years during July and August. MW The hardwater character of Lawrence Lake is reflected in the pH, conductivity and alkalinity of its waters (Figure 1.4). 17 Figure 1.4. pH (upper), conductivity (center), and alkalinity (lower) at 2 m and 6 m over an annual period in Lawrence Lake, Michigan. 18 pH CONDUCTIVITY ()1th cm") ALKALINITY (meal-'1) 2 lAlslolNIDIJIFIMIAIMIJIJIA 1982 1983 Figure 1.4 19 A detailed analysis of calcium and total alkalinity budgets and calcium carbonate precipitation in Lawrence Lake is given in Otsuki and Wetzel (1974) . During this study pH varied less than one unit throughout the year at 6 m and only about 0.3 pH units at 2 11:. Usually pH was between 8.0 and 8.4 in water less than 8 m deep. Although annual conductivity values were high (>400 umho-cm'l) , significant variations occurred during the year and among depths. Conductivity was greatest in mid-winter (about 550 umho-cm‘l) and began decreasing steadily at ice-out with the onset of the spring phytoplankton bloom. The surface water decrease in conductivity during June was largely due to the massive precipitation of calcium Carbonate. Alkalinity was predominately bicarbonate alkalinity and f<>llowed a pattern similar to conductivity (Figure 1.4) . Small differences were observed between 2 m and 6 m until the onset of epilimnetic decalcification in June. Alkalinity ranged from 3.7-4.9 meq-L’1 at 2 m throughout the Year while staying nearly constant at 4.5 meg-L'l at 6 m. $4.112: Silica concentrations are high in Lawrence Lake and are never limiting to the growth of diatoms and other silica- dependent organisms. However, a significant biological 20 reduction of silica occurred, particularly in the epilimnion (Wetzel 1983) . Silica is transported by sedimenting diatoms out of the epilimnion to deeper water and ultimately to the sediments. Typical winter concentrations of 10-11 mg Sioz-L'l were reduced to about 6 mg Sioz-L'1 by June in the surface waters . 131mg: Nitrogen is a nutrient required in relatively large amounts by all living organisms. In Lawrence Lake inorganic nitrogen, mostly in the form of nitrate, is in great excess Of that needed to support the normal phytoplankton biomass found in the lake (Wetzel 1983) . The nitrogen inputs to I-awrence Lake occur largely as nitrates which leach from the calcareous till of the drainage basin. Annual Concentrations of N03-N02 range from about 1.5 to 5 mg-L“:L in the upper water (0-8-m stratum). Ward and Wetzel (1980a) detected no Nz-fixation over the growing season between April and September. Their work showed that certainly N03 and possibly 1111;, (via diffusion from the hypolimnion) was adcequate to supply all the nitrogen needs of the algae. W Direct measurements of pelagic phosphorus were made infrequently during this study. In calcareous lakes such as I'Elwrence, much of the soluble phosphate and other essential 21 micronutrients (i.e. iron and manganese) form highly insoluble compounds (Otsuki and Wetzel 1972, Wetzel 1972, 1983) . During the period of relatively high productivity (June) these precipitates and seston settle rapidly from the trophogenic zone. The absolute concentrations of phosphorus compounds in Lawrence lake are relatively constant and exhibited little correlation with changes in algal growth (Wetzel 1972) . More relevant are turnover rates and availability. Alkaline phosphatase activity (APA) was routinely measured to determine biological phosphorus stress and phosphorus availability in the system. APA was about 30x higher at its maximum in August than it was in February at its annual low point (Figure 1.5) . APA was uniform within the lake until thermal stratification stabilized the water Column in May (Figure 1.2) . Thereafter, APA was greater in the 4-8-m stratum than in the 0-4-m stratum indicating either a higher demand for phosphorus or reduced availability from organic compounds in the metalimnion. These findings were consistent with higher productivity I”Lites and Chla concentrations found inthe metalimnion during the same period. Further insight into phytoplankton phosphorus stress during the year is apparent with an examination of the ratio Of APA to chlorophyll (Figure 1.5) . During periods of gIl‘eatest vertical stability to mixing, phosphorus stress per 22 Flg‘Jre 1.5. Total alkaline phosphatase activity (unfiltered lake water) (upper) and the ratio of alkaline phosphatase activity to chlorophyll a concentration (lower) over an annual cycle in Lawrence Lake. 23 A'S'O'N'D'J'F'M'A'M' J'J'A 1982 1983 Figure 1.5 24 unit Chla was greater in the epilimnion than in the metalimnion. From the mixed winter period until epilimnetic decalcification in June the APA/Chla ratio was similar in both strata. The phosphorus stripping action of the annual decalcification event (precipitated by increased productivity) functioned to reduce available phosphorus to the epilimnetic phytoplankton during a period when replacement was least likely from internal and external loadings (Wetzel, in preparation). The bacterioplankton can also be direct or indirect sources of phosphatase. Cembella et a1. (1984) emphasized that APA may be derived in part directly from bacterial secretion or indirectly from bacterial degradation which would lead subsequently to high organic phosphorus production and induction of APA by bacteria and algae. 0f the total dissolved and particulate APA, non-algal particulate APA can comprise a major component (15 to 73%) of the particulate pool (Wetzel 1981; Stewart and Wetzel 1982). During thermal stratification APA was always lowest in hypolimnetic water below 8 m where inorganic phosphorus was more readily available in the more reducing environment. During February APA was minimal, as was algal biomass, productivity, temperature, and available light. 25 91112292111113 The oligotrophic status of Lawrence Lake was characterized by the low Chla concentrations (Figure 1.6). Mean Chla never exceeded 2 ug-L’1 in the 0-4-m stratum and did so only during July and August in the 4-8-m stratum. On most sampling dates concentrations were between 1 and 2 u.g-L"1 in the upper 8 m of the lake. Chla concentrations declined during the period of ice-cover on the lake. Minimal Chla concentrations of about 0.75 pg-L’1 were found in the upper 8 m just prior to ice-loss on 3 March. In general, Chla concentrations were slightly higher in the 0-4-m stratum during winter, but they were highest in the 4-8-m stratum during spring and summer. The elevated Chla concentrations in October and November were due to algal growth rather than upward mixing of metalimnetic algae during destratification, as has been noted elsewhere (Fee 1976). The excellent light conditions during October were conducive to the observed growth. W! Throughout the study period primary productivity (Figure 1.7) followed the pattern of annual solar radiation (Figure 1.1). The lowest rates occurred between November and ice-loss in early March when values were always less than 50 mg C-m’z-day'l. Primary productivity began to increase just prior to ice-loss, and continued until it 26 Figure 1.6. Chlorophyll a concentration (corrected for phaeophytin) over an annual cycle in Lawrence Lake. CHLOROPHYLL a (119-L") 27 4 I I I W] I I I I 0—00-4m 3 Hit-8m 2- OIAISIOINIITfJIFIMIAIMIJIJIAj 1982 1933 Figure 1.6 Figure 1.7. 28 Primary productivity of phytoplankton over an annual cycle in Lawrence Lake, Michigan; integrated areal productivity in the 0-8-m stratum (upper), integrated volumetric productivity in the 0-4 m and 4-8-m strata (center), and percent of total 0-8 m carbon fixed in the 0-4 m and 4-8-m strata (lower). All points were corrected for depth-volume variations. 29 I O—8m ' V v 3.6!.“ v'v". .‘lat¢¢ ’65" O 23.9. V '. :o‘ “o‘ e ‘1 3‘... ‘o ‘2. 'o' m — m m 2 .33 . NL... . can. 0 723 . PE .09: aux—u 20mm mmdqmumm madmumdlfiu .mwlaHmH dddlquMIMId . mm momumnmowumaafiomm HHQduduluumu nuldeQMHMW ..mnm mmmmmmddma wdlmuflflflu quHmIQHd udflmlflmqmd maamuwmammmluudu hm nuannommunu wmmflwmqadd mmumdmdmuqu .mmuadmm_amflummmmmmdwmw .mmmmnmqmqmdlmwmmmaqumd .mmmumummdw mammmmqa mm muhcmoseao mmflmeMAmmmmmd .> mumdfla mandamuqdm ..mmmNmImmew. mmamammmfluu w unannoumhuo qualms...“ ammflqmdmm Hmflmfluduum HmmdMIHdmm mmddmumqmuu .flmmmdumlmm .nu «danAummufld amdMIHMu NH ouhnaocuumm Amanao>oea Hana» ”m AV 6x69 ucocwaoc mowuonm mo Monasz coxca .nwma unavad avsoucu mama umsmz< aouu 0H0>0 finance ecu mcfiuso mowoumm usmcflaoo use .mcouo momma ha moaoomm couxcoamouanm mo Honaaz .~.H manna 34 diameter. Most of the cells counted in these size classes were microflagellates but other nondescript cells were placed here as well. With the exception of the small cryptophyte, Engggmgngs, the remaining dominant species were colonial. Cell volumes of the colonial species ranged from 4.2 um3 (Wm—W) to 890 um3 (W111). Phytoplankton data are commonly presented as either cells, biovolume or occasionally as algal units (particles) per unit lake volume. Each approach emphasizes a different aspect of the data and should be used accordingly. Each approach will be addressed in the following discussion to more fully characterize phytoplankton dynamics in Lawrence Lake. Algal cell sizes varied over four orders of magnitude (4.2 um3 to 84600 um3). Cells at either end of the range can certainly not be considered physiological and/or ecological equivalents. It can therefore be misleading to compare seasonal dynamics of species using cell number. Cell volume has been coupled to rates of metabolic activity (Banse 1976) and when combined with cell numbers provides a more acceptable basis for comparing phytoplankton dynamics of mixed taxonomic units. The algal unit incorporates colonial morphology into the analysis giving each algal particle, single cell, or colony, equivalent weight. The algal unit is particularly useful for grazing studies since 35 it is the unit encountered by grazers. The size, shape and abundance of particles may have profound effects on grazing rates and the structure of zooplankton populations (Gliwicz 1980). The arrangement of cell aggregation also effects light availability, e.g. it is well known that aggregates of cells such as those found in Aphgnizgmgngg flakes intercept less light than the equivalent biomass of cells distributed more evenly and in smaller aggregates throughout the same water volume. a c c n t 0 Annual patterns of cell concentration show that Cyanophyta (blue-greens) completely dominated the community from August through turnover at the end of October (Figure 1.8). Most of these cells were very small, non- heterocystis, and organized in high cell density colonies (e.g. Aphangthggg). As is often the case with this morphological type, the relative importance of the blue- green algae may be exaggerated. This group accounted for as much as 90 percent of the cells in August and September. Blue-green cell numbers dominated until permanent ice formation in mid-January when they still accounted for nearly 20 percent of the total cells in the upper 8 m of the water column. From autumnal turnover through winter, and until the lake stratified in mid-June, microflagellates and for a Figure 1.8. 36 Percentage of algal cells within major phytoplankton groups in the 0-4-m stratum (upper) and 4-8-m stratum (center), and total cell concentrations (lower) in those strata over an annual cycle in Lawrence Lake, Michigan. ALGAL CELLS 37 E E CRYPTOPHYTA l l I I l I I I I If 60000 — 0—4m — H 4-8m _ 1 E 40000 — _ (D .I .1 Lu 0 V 20000 — _ cA's'olN'DIJIFIM'AIMIJIJIA 1982 1983 Figure 1.8 38 shorter period cryptophytes, were the overwhelming contributors of phytoplankton cells to the lake. Very few colonial forms were present during the winter months. W The importance of colonial organization becomes apparent when algal units are compared to cell concentrations (Figures 1.9 and 1.8, respectively). The largely colonial forms of blue-greens and chrysophytes decreased considerably in their relative importance as algal units than as cells and were most abundant during the stratified period June through August. Total algal units ranged from about 600 to 4000 mL'1 during the study. The seasonal trends were similar in both strata. In general algal units declined steadily throughout autumn and winter from around 2300 mL’1 in August to the lowest point of 600 algal units-mL‘1 on 1 March, immediately preceding ice-loss. With the exception of a slight depression in mid-June, algal units then increased continuously in the 0-4-m stratum until early July to a maximum of 4500 mL‘l. Thereafter epilimnetic values declined sharply. The rapid increase after ice-loss was of shorter duration in the 4-8-m stratum where concentrations leveled out after reaching 2000 mL'1 in early April. The June depression was more apparent in the metalimnion. The Figure 1.9. 39 Percentage algal units within major phytoplankton groups in the 0-4-m stratum (upper) and 4-8-m stratum (center), and total algal unit concentrations (lower) in those strata over an annual cycle in Lawrence Lake, Michigan. ALGAL UNITS (%) (%) (ALGAL UNITS-ml ") oooooooo ........ 00000000 oooooooo 40 PYRRHOPHYTA CHRYSOPHYTA 3 CYANOPHYTA 0-4m 100 50 III/ll], o:o:o?.t.’”1/ Q MICROFLAGELLATES 0 I I I I I I I I I I I 6000‘ fi o—oO-4m 4000 “4"8"‘ - 2000 ._ 0A'S‘O'N'D'J'F'M'A'M'J'J'A 1982 1983 Figure 1.9 41 metalimnetic maximum (2900 algal units mL'l) occurred in the first week of July. Microflagellates and cryptophytes, being single-celled and in great abundance, produced an overwhelming majority of the algal units present in the lake. On an annual basis the average daily contribution by microflagellates was near 60 percent in both strata (Figure 1.10). Cryptophytes were of lesser importance but still they accounted for most of the remaining algal particles in the lake (about 20% annually). Seasonal cryptophyte contributions were greatest during the winter months under ice (>40%), but they also contributed more than 20 percent throughout and beyond the period of destratification in October and November (Figure 1.9). Important changes from the microflagellate-cryptophyte pattern of dominance occurred at the end of October in the 0-4-m stratum, when chrysophytes increased to 20 percent and in late August 1983 when cryptophytes, blue-greens, chrysophytes and greens accounted, about equally, for 50 percent of the total algal units (Figure 1.9). Seasonal patterns in the 4-8-m stratum differed. Blue-greens contributed about 25 percent in August 1982 and in late August 1983. Diatoms contributed 10-15 percent over an extended period from late February (ice-out) through July. Chrysophytes provided about 20 percent of the algal units during two periods, at turnover in early November and again in late June. Green algae made notable contributions in July and August of both years in the metalimnion. 42 Figure 1.10. Annual mean percentage of algal units by phytoplankton groups: Euglenophyta (EUG), Pyrrhophyta (PYR), Cryptophyta (CRYP), diatoms (DIA), blue-green algae (B-G), Chrysophyta (CHRY), Chlorophyta (CHL), microflagellates, <6.0 um diameter (MF). 43 _ _ _ _ TIIIIIHA/vaA/VUA/Von/MVUA/VU/ I/ 100 Ill am Hm IM rIIII/A/UA/V/ / a __ a _ _ _ _ _ _ _ _ m m w m o 9:23 ._<0._< kaUmmd Z "E .J . _ a", n o E .1 2 < 400 '- p. O .— 200 - Figure 1.24 I I I I I I A 4' 1 1 A la J J A 1983 86 algal units occurred during a four-week period between 7 June and 5 July (Figure 1.25). Greater numbers of microflagellates in the epilimnion than in the metalimnion (Figure 1.18) decreaSed the relative value of the chrysophyte algal unit contribution in the epilimnion at that time. Chrysophyte population dynamics were characterized by infrequent intense periods of growth followed by quick declines. Usually numerous species were present in very low numbers. Of four species of Qingbzygg identified in Lawrence Lake, only Q. dixerggns was notable (Figure 1.16). This species developed during the latter stages of destratification, reached a maximum in the same week as turnover, and then rapidly declined. Temperatures were less than 14‘C during this period. The species was undetected once lake temperatures reached 4°C and ice first formed on the lake. anygggpnagrgllg lgngigping followed a pattern similar to Diggbrygn in the autumn of 1982 but was less abundant, particularly at 4-8 m (Figure 1.16). A very large population developed in both strata, however, during August of 1983. Water temperature and stratification had little affect on the development of this species. During its occurrence nearly uniform epilimnetic temperatures ranged from 23 to 25'C, while the metalimnion was strongly stratified with temperatures ranging from 9 to 23°C (Figure 1.1). 87 Figure 1.25. Total Chrysophyta algal units in two depth-strata over an annual cycle in Lawrence Lake, Michigan. ALGAL UNITS ImL-‘i 88 firm—— I I l 500 I I I CHRYSOPHYTES H 0-4m 300 - 200 - 100 P- 2.-.: Figure 1.25 0 89 The Qnrygggphagrglla maximum in August 1983 closely followed the rapid decline of fitighgglgga, another colonial chrysophyte (Figure 1.16). fitighgglgga gggggzlginii was present throughout much of the study in very low concentrations, but unlike other chrysophytes it bloomed during late June and early July (Figure 1.16). This species accounted for about 45 percent of the total biovolume between 0-8 m during the first week in July. The bloom occurred during an extended period of high solar input and rapidly increasing epilimnetic temperatures. The temperature structure in the highly stratified metalimnion was stable during this period (Figure 1.1). During the Stichggloeg maximum, light penetration was reduced to the annual minimum by turbidity from epilimnetic decalcification and to a lesser degree high algal biovolume (Figure 1.3). Development of Mallgmgngg spp. was concurrent with the decline of other chrysophytes, i.e. 212923222 and anygggpnggrglla (Figure 1.16). Maximum cell concentrations of Mallomonas occurred under the sporadic ice-cover of early winter. Uniform vertical temperatures of 3-4°C were prevalent at that time. Solar radiation was then at its annual minumum (Figure 1.1). 90 9111222221122 Seasonal biovolume trends of the green algae closely followed those of the blue-green algae, i.e. peak development in June and August. The green algae never contributed more than about 16 percent of the total biovolume. Notable differences in biovolume between 0-4-m and 4-8-m strata occurred only in August 1982 where metalimnetic concentrations were four times the biovolume of the epilimnion (Figure 1.26). The green algae added few particles to the community during the study. Again, as with the blue-green algae, their greatest contributions (between 4 and 23 percent) were in late July and August. Four species of green algae were conspicuous components of the summer plankton community (Figure 1.18). glam—11224182 ode .2122122212w2221221222d glgnktgngmg lgutgrborni were restricted to July and August. figtryggggggg 2323311 maintained a relatively stable population through December 1982 until permanent ice formed. Elgnktgngmg grew very quickly in July, doubling almost daily over a two-week period in the epilimnion. Overall, green algae were of minor importance in Lawrence Lake during this study. 91 Figure 1.26. Total Chlorophyta cell volume in two depth-strata over an annual cycle in Lawrence Lake, Michigan. TOTAL CELL VOLUME (mm3 - m‘3) 92 30° I I. I I M I I I I I _ CHLOROPHYTES H O—4m p- H 4-8m 200 100 Figure 1.26 93 11122211122211.2222 Microflagellates were always present and often provided the greatest number of cells, and therefore particles per unit volume, of any group encountered. This group was composed largely of small Qghrgmgnag-like cells but always contained Qhrysgghrgmulina parga as well. The latter species could not always be positively identified during routine counting and was therefore placed in the general category. Annual cell concentrations of microflagellates (<6 pm in diameter) are given in Figure 1.18. The microflagellates rarely contributed more than 10 percent to the total biovolume and then only during the late autumn near the annual minimum (Figure 1.11). Their biovolume fluctuated frequently (Figure 1.27) with regular oscillations between about 15 and 40 mm3-m'3 from August through December 1982. A period of decline then followed through the end of February to the observed minimum for the group (6 mm3-m'3). During the August through February period there was no consistent pattern of microflagellate dominance in either the 0-4-m or 4-8-m strata. After ice-loss and the beginning of stratification in March, microflagellate biovolume increased faster and remained higher in the surface stratum. This pattern continued throughout the remainder of the study year. The microflagellate biovolume maximum was 78 mm3om‘3 in the 0-4-m on 5 July (Figure 1.27), but this accounted for less than 2 percent of the total algal biovolume at that time. 94 Figure 1.27. Total microflagellate (<6 um dia) cell volume in two depth-strata over an annual cycle in Lawrence Lake, Michigan. 95 '00 I I I W " MICROFLAGELLATES H 0-4m 80 — H 4-8m "J 2 3 2‘?" 6° .. F a» - o E .4 2 :5 4o - o i- ‘ \4 t 2. - V \ 0 I I I I I I I A s o J F M Figure 1.27 96 Summary 1. One hundred twenty-one algal species of phytoplankton were identified from hardwater Lawrence Lake of southern Michigan during this study. Only 20 species contributed more than 5 percent of the total biovolume at any particular time. Biovolume was often dominated by relatively large single celled forms, i.e. nglgtglla hgdaniga var. afjiggg (January through July), Qgratigm 212222122112 and 2221212122 2222222212 (summer). 2. 211121 (winter and spring) and erptgmgnas (autumn). Populations of the motile colonial forms thygggpnggrgllg (late summer) and Qingbrygn (autumn) developed and declined rapidly. Non- motile colonial forms varied in their occurrence, i.e. the short-lived development of Stighgglgga (summer), the irregular fluctuations of Fragilaria throughout the year and the blue-green algae during summer (22222222222-22222222222. 22222222222212. 22222222222. 22212222222122)- Small microflagellates (<6 um) and 3222222222 and 2222212222212 accounted for about 80 percent of the algal units in the lake throughout the year; their contributions to algal biovolume, however, was almost always less than 10 percent. 2. During this study a major phytoplankton biovolume maximum occurred in late June (about 2000 mm3-m'3). This maximum biovolume was largely the result of a bloom of 97 thygggphagrgllg. At other times biovolume ranged from about 250 mm3-m"3 to about 1000 mm3'm’3, only a fourfold factor. The oligotrophic status of the phytoplankton of Lawrence Lake was indicated by the low Chla concentrations (maximum = 3.2 ug-L‘l), productivity rates (maximum <300 mg C-m‘Z-day'l), and biovolume. 3. Several potentially nuisance species of blue-green algae were present in low numbers (i.e. nigzggygtig 2222212222. 2M bae 2192221122 and 2222212222222 2122; ggugg). Changes in community structure to where these species dominate could occur rapidly with nutrient enrichment and/or shifts in nutrient availability. 4. Only minor vertical stratification of species occurred during much of the study, which in part resulted from integration of portions of the water column by the sampling technique. However, even during the stratified period motile forms known to actively seek optimal strata or migrate vertically on a diel basis, e.g. erptgmgngg (Salonen et al. 1984) and Bhgdomonas (Sommer 1982), did not appear to congregate in one stratum more than another. Other forms were clearly located in discrete strata, e.g. Qymngdinium helveticum was almost always found in the metalimnion and the microflagellates were usually twice as abundant in the surface water as they were in the metalimnion during the stratified period. References Banse, K. 1976. Rates of growth, respiration and photosynthesis of unicellular algae as related to cell size - a review. J. Phycol. 12:135-140. Cembella, A. D., N. J. Antia and P. J. Harrison. 1984. The utilization of inorganic and organic phosphorous compounds as nutrients by eukaryotic microalgae: a multidisciplinary perspective: Part 1. CRC Crit. Rev. Microbiol. 10:317-391. Crumpton, W. G. and R. G. Wetzel. 1982. Effects of differential growth and mortality in the seasonal succession of phytoplankton populations in Lawrence Lake, Michigan. Ecology 63:1729-1739. Fee, E. J. 1976. The vertical and seasonal distribution of chlorophyll in lakes of the Experimental Lakes Area, northwestern Ontario: Implications for primary production estimates. Limnol. Oceanogr. 21:767-783. Gliwicz, 2. M. 1980. Filtering rates, food size selection, and feeding rates in Cladocerans - another aspect of interspecific competition in filter-feeding zooplankton. pp. 282-291. In: Evolution and Ecology of Zooplankton Communities. W. C. Kerfoot, (ed.). Special Symposium Vol. 3, Amer. Soc. Limnol. Oceanogr. University Press of New England, Hanover, New Hampshire. Graffius, J. H. 1963. A comparison of algal floras in two lake types, Barry County, Michigan. Ph.D. Dissertation, Department of Botany and Plant Pathology, Michigan State University. Hill, H. D., G. K. Summer and M. D. Waters. 1968. An automated fluorometric assay for alkaline phosphatase using 3-0-methylfluorescein phosphate. Anal. Biochem. 24:9-17. Hobro, R., and E. Willén. 1977. Phytoplankton countings. Intercalibration results and recommendations for routine work. Int. Revue ges. Hydrobiol. 62:805-811. Irish, A. E. 1979. Gymngdinium helvgticum Penard fa. achroum Skuja, a case of phagotrophy. Br. Phycol. J. 14:11-15. 98 99 Johnson, N. M., J. S. Eaton and J. E. Richey. 1978. Analysis of five North American lake ecosystems: II. Thermal energy and mechanical stability. Verh. Internat. Verein. Limnol. 20:562-567. Lund, J. W. G., C. Kipling and E. D. Le Cren. 1958. The inverted microscope method of estimating algal numbers and the statistical basis of estimations by counting. Hydrobiologia 11:143-170. Manny, B. A. 1972. Seasonal changes in organic nitrogen content of net- and nannophytoplankton in two hardwater lakes. Arch. Hydrobiol. 71:103-123. McKinley, K. R., and R. G. Wetzel. 1979. Photolithotrophy, photoheterotrophy, and chemoheterotrophy: Patterns of resource utilization on an annual and a diurnal basis within a pelagic microbial community. Microbial Ecol. 5:1-15. Niemi, A., T. Melvasalo, and P. Heinonen. 1985. Phytoplankton counting techniques and primary production measurements -- comments on the results of intercalibration. Aqua Fennica 15:89-103. Otsuki, A. and R. G. Wetzel. 1972. Coprecipitation of phosphate with carbonates in a marl lake. Limnol. Oceanogr. 17:763-767. Otsuki, A. and R. G. Wetzel. 1974. Calcium and total alkalinity budgets and calcium carbonate precipitation of a small hard-water lake. Arch. Hydrobiol. 73:14-30. Perry, M. J. 1972. Alkaline phosphatase activity in subtropical Central North Pacific waters using a sensitive fluorometric method. Mar. Biol. 15:113-119. Popovsky, J. 1982. Another case of phagotrophy by 92222212122 hglygtigum Penard fa. aghrgum Skuja. Arch. Protistenk. 125:73-78. Rich, P. H., R. G. Wetzel, and N. V. Thuy. 1971. Distribution, production and role of aquatic macrophytes in a southern Michigan marl lake. Freshwat. Biol. 1:3- 21. 100 Salonen, K., R. I. Jones, and L. Arvola. 1984. Hypolimnetic phosphorus retrieval by diel vertical migrations of lake phytoplankton. Freshwat. Biol. 14:431-438. Sommer, U. 1982. Vertical niche separation between two closely related planktonic flagellate species, (3222222222 1222 and 3222222222 212222 v. nanngplangtiga). J. Plankton Res. 4:137-142. Steemann Nielsen, E. 1951. Measurement of the production of organic matter in the sea by means of carbon-14. Nature. 167:684-685. Steemann Nielsen, E. 1952. The use of radioactive carbon (14C) for measuring organic production in the sea. J. Cons. Int. Expl. Mer. 18:117-140. Stewart, A. J. and R. G. Wetzel. 1982. Influence of dissolved humic materials on carbon assimilation and alkaline phosphatase activity in natural algal-bacterial assemblages. Freshwat. Biol. 12:369-380. Stewart, A. J. and R. G. Wetzel. 1986. Cryptophytes and other microflagellates as couplers in planktonic community dynamics. Arch. Hydrobiol. 106:1-19. Strickland, J. D. H. and T. R. Parsons. 1968. A Practical Handbook of Seawater Analysis. Bull. Fish. Res. Bd. Canada 167. 311 pp. Taylor, W. D. and R. G. Wetzel. 1984. Population dynamics of 3222222222 212222 V. 22222212222122 Skuja (Cryptophyceae) in a hardwater lake. Verh. Internat. Verein. Limnol. 22:536-541. Uterméhl, H. 1958. Eur Vervollkommnung der quantitativen Phytoplankton-Methodik. Mitt. Internat. Verein. Limnol. 9:1-38. Vollenweider, R. A., ed. 1974. A Manual on Methods for Measuring Primary Production in Aquatic Environments. 2nd Ed. Int. Biol. Program Handbook 12. Oxford, Blackwell Scientific Publications. 213 pp. Ward, A. K. and R. G. Wetzel. 1980a. Interactions of light and nitrogen source among planktonic blue-green algae. Arch. Hydrobiol. 90:1-25. 101 Ward, A. K. and R. G. Wetzel. 1980b. Photosynthetic responses of blue-green algal populations to variable light intensities. Arch. Hydrobiol. 90:129-138. Wetzel, R. G. 1972. The role of carbon in hard-water marl lakes. In: Nutrients and Eutrophication: The Limiting- Nutrient Controversy. G. E. Likens, (ed.). Special Symposium, Amer. Soc. Limnol. Oceanogr. 1:84-91. Wetzel, R. G. 1975. Limnology. W. B. Saunders Co., Philadelphia. 743 pp. Wetzel, R. G. 1981. Longterm dissolved and particulate alkaline phosphatase activity in a hardwater lake in relation to lake stability and phosphorus enrichments. Verh. Internat. Verein. Limnol. 21:369-381. Wetzel, R. G. 1983. Limnology. 2nd ed. W. B. Saunders Co., Philadelphia. 767 pp. Wetzel, R. G. and G. E. Likens. 1979. Limnological Analyses. W. B. Saunders Company, Philadelphia. 357 pp. Wetzel, R. G. and B. A. Manny. 1978. Postglacial rates of sedimentation, nutrient and fossil pigment deposition in a hardwater marl lake of Michigan. Polskie Arch. Hydrobiol. 25:453-469. Wetzel, R. G., P. H. Rich, M. C. Miller and H. L. Allen. 1972. Metabolism of dissolved and particulate detrital carbon in a temperate hard-water lake. Mem. Ist. Ital. Idrobio1., 29 Suppl.:185-243. CHAPTER 2 SHORT-INTERVAL CRYPTOPHYTE DYNAMICS AND GROWTH RATES OVER.AN ANNUAL PERIOD Introduction In Chapter 1 of this work a description of the limnology and phytoplankton population dynamics in Lawrence Lake was presented for an annual period, August 1982 to August 1983. Those data were collected at two-week intervals. Important changes in populations of small algae (<30 um) may be missed when seasonal phytoplankton studies employ sampling intervals much greater than the doubling times of the fastest growing forms. Under ideal conditions for growth, large species may have doubling times greater than three days (e.g., nggtigm), while smaller forms have the potential for dividing several times each day (e.g., Chlamyggmgnag) (Reynolds 1984). The purpose of this study was to determine short-interval population dynamics of selected cryptophyte species. The effects of sampling interval on seasonal population dynamics and estimates of daily net growth rate constants were evaluated for those species. The collections were made during 1982-1983, thus adding detail to the general discussion in Chapter 1. 103 Materials and Methods Sample collection, preservation and counting methods were as described in Chapter 1. Integrated phytoplankton samples were collected at two-day intervals (one-day intervals during October) from three depth-strata (0-4, 4-8 and 8-12 m) at the central depression. The cryptophytes were dominated by two taxa, 3299999999 (3299999999 919999, as discussed by Willén et a1. 1982) and 99199999999 '99999', a composite of mostly 9. 91999 but also 9. 9x999, two species often difficult to differentiate during cell enumeration. Between 100 and 450 3999999999 cells were counted per sample. Counting error (11 std) varied between 9 and 20 percent (Lund et a1. 1958). er99999999 '93999' abundance estimates were based on counts of 30 to 120 cells per sample, and counting error ranged from 18 to 30 percent. 9. 999999199 was very seasonal in its distribution and abundance in Lawrence Lake. In most samples during its growing-season at least 100 cells were counted. Observed (net) growth rate constants (kn) were calculated assuming exponential growth or decline between sampling intervals, a widely used practice by phytoplankton ecologists (Horn 1984, Braunwarth and Sommer 1985, Elser et a1. 1987): kn = 1n(N1/No)/ 90 t) of the total cryptophyte cell volume throughout the year in the 0-8-m stratum. Cryptophyte contributions to total phytoplankton biovolume were greatest between September and December, reaching a maximum of 50 percent in the 0-4-m stratum (Figure 2.1). 99y99999999 '99999' cell volumes were typically 20-fold greater than those of 3999999999 cells, and usually resulted in a much larger contribution to total cell volume by 99199999999 even though 3999999999 was always more abundant. Figure 2.1. 105 Contribution of cryptophyte cell volume to total phytoplankton cell volume in 0-4-m (upper) and 4-8-m (center) strata, and total phytoplankton cell volume (lower) in Lawrence Lake, Michigan, at two-week sampling intervals. PERCENT OF TOTAL GEL VOLLME .3 3 mm-m TOTAL CELL VOLLME. . 106 —- Total Cryptophytes - - - - Cryptomonas ------- Rhodomonas .......... .... ?.J.. -..d‘00'-. ‘--.—..‘.v"&-P,.' ..... Q J. I I I I l I I I I I I I 2000- 1000- Figure 2.1 107 22222_1222222l_22!22222!22_21222122 Population dynamics of 3999999999, 99199999999 '99999' and 9. 999999199 are presented by stratum at two-day intervals (one-day intervals during October) in Figures 2.2, 2.3 and 2.4, respectively. A complete list of cell abundances for 3999999999 and 99199999999 '99059' is given in Appendix 8. 2222222222 and 22222222222 '22222' were observed continuously throughout the annual cycle. 9. 999999199 was most frequently observed in summer and early autumn. 3999999999 abundance ranged from 33 cells'mL"1 in the hypolimnion in August to 544 cells-mL’1 in the epilimnion in October, representing only a 16-fold maximum difference within the lake during the year. Cell abundances between 100 and 300 cells-mL‘1 occurred in 80 percent of all samples examined from all depths, illustrating the highly stable nature of this population. These results are in marked contrast to the population dynamics of 39odomon9s in other north temperate lakes. Lund (1962) found 39od99on9s populations frequently reaching 1500-3000 cells-mL’1 in several lakes and in one case in Blelham Tarn, 6000 cells-mL‘l. Cell densities reached about 9000 cells-mL“1 in a eutrophic bay of Lake Malaren (Willén et a1. 1982). Larger seasonal fluctuations, as illustrated in these examples, are more typically encountered in the literature 108 Figure 2.2. 3999999999 919999 abundance by depth-strata in Lawrence Lake, Michigan. 109 mwm F CON 00v CON com 00v 000 ljw «sues . Figure 2.2 110 Figure 2.3. 99199999999 '99999' abundance by depth- strata in Lawrence Lake, Michigan. 111 “a mwmw 3 <4 xx _2 m w Nmmr n. 94 Au w < Dow 09 GOP 8N LJul-sues Figure 2.3 112 Figure 2-4- 22222222222 222222122 abundance by depth- strata in Lawrence Lake, Michigan. 113 4°° I I I TWP—FT I I I I .4 200‘ O—4m ° IMI‘MJT‘L‘I I I I I I I I I“ P 2001 4-8m :1 ‘ 4 E. ° I“ I‘MI I‘I I F I I I I“ 1’ 7 '55 O 800' .4 600.. .l M— 200' 8—12m o- - 4- - I. I I I I I I I I A s o N D J F M A M J J A 1982 1983 Figure 2.4 114 for a wide variety of phytoplankton species. The total autotrophic biovolume of Lawrence Lake varied by only eight- fold during this study (Figure 2.1). This level of community stability is similar to that described for total autotrophic biomass in tropical Lake Lanao (Lewis 1978). 3999999999 was the only species observed with such a consistently stable population in Lawrence Lake. The most abrupt population change occurred early in October with a five-fold increase during a ten-day period (Figure 2.2). A relatively large population was maintained under ice which, after ice-loss on 2 March, declined steadily over a six-week period to less than 100 cells-mL’l. The population increased again to about 300 cells°mL"1 during a two-week period in May and then fluctuated between 100-200 cells-mL‘1 during the rest of spring and summer. In contrast to 3999999999, 99199999999 '99999' abundance maxima occurred as broad peaks in the autumn and in the early summer (Figure 2.3). Both peaks developed and declined slowly over extended periods. The population remained low (<20 cells-mL‘l) throughout winter and spring. Cell abundances were rarely greater than 100 cells-mL"1 during the annual cycle. Unlike 3999999999, the 99199999999 population frequently occurred at very low cell abundances. 115 The third species, 99199999999 999999199, formed a dense population in the hypolimnion during September and October (Figure 2.4). Hypolimnetic samples integrated over 8-12 m had abundances exceeding 600 cells-mL’l, while abundances in occasional grab samples from 11 m exceeded 6000 cells-mL"1 indicating development of this species in thin strata. 9. 999999199 has been noted for its association with nutrient-rich environments (Anton and Duthie 1981). Very large nearly unialgal populations of 9. 999999199 were reported in a layer at the metalimnion where oxygen and sulfide were both at low concentrations (Pedros- Alio et a1. 1987). In Lawrence Lake the highest concentration of nutrients can be expected near the sediment-water interface during brief periods of anoxia. The development of this species coincided with the onset of anoxia at the sediment surface (early August). Although its decline was concurrent with the reintroduction of oxygen to the hypolimnion during autumnal turnover (early November), other factors such as decreasing light and lower temperatures may have been more important in its decline. Complete mixing of the lake can be seen in these data with the sudden introduction of 9. 999999199 into the upper eight meters on 5 November. Large day to day fluctuations in cell abundances of 9. 999999199 were common in the hypolimnion. This phenomenon was thought to result from repeated minor vertical 116 migrations by the population across the 12-m depth plane in response to changing light and nutrient regimes. Migration of the population below a depth of 12 m placed it beyond the 8-12-m sampling interval resulting in an apparent reduction in cell abundance in the hypolimnion. The maximum depth of the lake was 12.5 m, allowing the population a 0.5 refuge from the sampler. 13222122321222 Pronounced differences in cell abundance were found between depth-strata on numerous days (Appendix B) even though seasonal patterns in abundance appeared to be quite similar (Figures 2.2 and 2.3). Studies conducted under conditions of minimal turbulence demonstrated cell stratification by 3999999999 and 99199999999 along light gradients (Ruttner 1963, Wright 1964, Sommer 1982, 1986). In the present study, interpretation of daily differences in cell abundances among strata is difficult because of the potential variability associated with each datum. Variability may arise from vertical and horizontal patchiness, and cell enumeration. Variability resulting from vertical patchiness was reduced through the collection of 4-m-long integrated samples that masked stratification within the stratum when it was present. This sampling method restricted details to differences between major vertical strata. Crumpton and Wetzel (1982) tested for 117 horizontal phytoplankton patchiness in Lawrence Lake and consistently found no greater variance among five stations than between replicates at a single station. Similar periodic testing during this study using 3999999999 and 99199999999 '99999' as the test organisms support their findings. In order to identify differences in abundance between strata, three-point running means were calculated for the 3999999999 and 99199999999 data sets (Figure 2.5). These calculations integrated information over six-day periods during the year except in October when integration covered three days. This treatment of the data reduced much of the day to day variability and thus smoothed the curves and clarified comparisons among strata. Only minor variations in 3999999999 abundance occurred with depth (Figure 2.5). Departures from vertical homogeneity in the 3999999999 population were greatest during the period of thermal stratification. The largest depth differences were in August and September 1982 when 3999999999 abundance below 8 m was about half that in the upper strata. From May through June 3999999999 abundance was slightly stratified, high to low, from the surface downward. Just after photosynthetically induced epilimnetic decalcification in June, epilimnetic cell numbers declined relative to other strata, perhaps as a result of reduced nutrient (phosphorus) availability (Figure 1.5, Wetzel 1981). 118 Figure 2-5- 3222222222 212222 and 22222222222 '_m2_e a' cell abundance curves smoothed through the calculation of three-point running means. 119 cccccccc .... . 3a. .3 ‘C I ... ... .0 o...‘... ....‘I . h '- h u 0.:- . a v . 3 ~. ...... .. ... '0 x .11 u . . . I 8 . on.“ .. . o . «3...— .u . . ... fl. “0.. a u a. O Q n U 0‘ . . . . o . 9 .. an; I 09 --------- .. ......220210‘ '. cg.‘q."'°-u.. ---. .. ..- .o.... 1.. ...-.0 1 ea." m. .... ~ 2 ...... w. .. ... .. o .a .n a. I. . .. N . ...... a... . . . . a .u . .2 ...: . . .. .— u. .... ..u .... . .u .. cl. "w" E “PI“ ......... . .. Eolv ..... I 8.? EToI Law "60 Figure 2.5 120 By August, surface abundances of 3999999999 were lower than in deeper strata. The slight surface depression during March may have been a response by low-light adapted cells to intense light following ice-loss. Similarly, the 99199999999 population varied little with depth especially during winter and spring (Figure 2.5). Metalimnetic maxima occurred during July and August, the period of greatest density discontinuity from thermal stratification. Hypolimnetic 99199999999 and 3999999999 abundances were notably low in June and early July, possibly from reduced light during epilimnetic decalcification and its associated turbidity ("whiting") (Figure 1.3). The remarkable constancy in temporal and vertical abundance of 3999999999 and 99199999999 in Lawrence Lake is difficult to explain given the dynamic physical, chemical and biological conditions normally associated with a dimictic temperate lake. This stability suggests that these populations may be tightly controlled. Control by environmental factors seems unlikely in view of the extremes in temperature and thermal stability (Figures 1.1 & 1.2), seasonally and vertically variable light (Figure 1.3) and nutrient regimes (Figure 1.5). Light, among these variables, appears to have been adequate for growth throughout much of the water column during the study. Lund (1962) suggested that 3999999999 populations normally may be nutrient limited. Phosphorus limitation to phytoplankton 121 productivity prevails in the pelagial zone of Lawrence Lake throughout the year (Wetzel 1981, 1983) and may contribute to the apparent threshold levels of 3999999999 and 99199999999 population development. Lawrence Lake supports an active grazer community (Haney and Hall 1975, Crumpton and Wetzel 1982) that may exert seasonal control in some depth strata. 3999999999 and 99199999999 are an optimal size for many zooplankton grazers (Porter 1973) and 3999999999 is a preferred food item for rotifers (Pejler 1977). The grazers may be largely responsible for the maximal biomass levels of these species. Most likely, different factors are operating with depth to maintain population stability. The ubiquitous occurrence of these species in virtually all lake types and degrees of eutrophy underlie their ability to adapt to a wide range of conditions. ‘9.: . :22! - . 1 -‘ a ., .,:-,_9. :71,.,1 .4 Life: Sampling interval can greatly modify the apparent seasonal dynamics of a phytoplankton community (Horn 1984). The close-interval data for the 3999999999 population were used to examine this phenomenon by systematically increasing the sampling interval. Data were rejected to create subsets at 4-, 8-, 14- and 32-day intervals (Figure 2.6). The upper panel shows the complete data set at two-day sampling intervals. Randomly selected examples of curves for each 122 Figure 2.6. Seasonal dynamics of 3999999999 in the 0-4-m stratum at sampling intervals ranging from 2 to 32 days. See text for discussion of different lines in each panel. 123 600 y y ..... y m m ... w . L. ... 2 2 .. ....... 3 ”u. 1............ 4r ............. s} ..... \ \ .................. I‘ ......... I I ...? nu‘ q q a _ _ fl _ _ 400- 200— A.uE.m__mov 90:62:91 2 _ _ .... . J O O 400 300 200 100 Day Figure 2.6 124 interval are shown in the remaining panels to illustrate the effect of starting date, an element of pure chance, on the patterns. There were 16 possible patterns at 32-day intervals, seven patterns at 14-day, fOur at eight-day and two at four-day intervals. Details of population dynamics rapidly decreased with increasing sampling interval, e.g., at four days there was a 50 percent chance (depending upon starting day) of missing the annual maximum (near day 70). The importance of the day 70 population pulse could easily have been missed at eight-day sampling intervals. The extended population depression near day 250 was apparent at all sampling intervals illustrated in the figure except for one at 32 days where nearly all seasonal events were reduced to a flattened line. The risk of missing important population fluctuations greatly increased in 3999999999 as sampling intervals extended beyond seven days. Greater sampling flexibility existed with 99199999999. A similar analysis showed that two-week intervals were adequate to characterize important 99199999999 fluctuations because of the more extended growth periods in the species (Figure Phytoplankton species have been characterized as fast (r-selected) or slow (K-selected) growing forms (Kilham and Kilham 1980, Sommer 1981). Calculation of the exponential 125 growth constant for a species is one method of quantifying this variable. Under optimal laboratory conditions maximum growth rates can be determined. Reynolds (1984) compiled a table of growth rates for a wide variety of algal species from the literature. Growth at these maximal rates is rarely measured 19,9199 where cells are constantly lost by cell lysis, sedimentation, grazing, vertical and horizontal transport and through wash-out, and where optimal conditions are rare or ephemeral. The true growth rate constant is controlled by ambient conditions prevalent at any given time. Observed or net growth rate will usually be less than the true growth rate for a given species. Estimates of true growth rate constants during specified periods have been made by variously accounting for loss factors (e.g. Crumpton and Wetzel 1982, Lund and Reynolds 1982) or by using special techniques that are not affected by losses (Braunwarth and Sommer 1985, Campbell and Carpenter 1986). Growth rate is affected by temporal and spatial processes. Grazing impacts, for example, vary seasonally within lakes, and vertically within the water column on a diel basis. Growth rate has been inversely correlated with cell size (Fogg 1975, Banse 1976, Reynolds 1984) so that sampling intervals suitable to characterize large cells may be too broad for smaller cells. Sommer (1981), however, refutes the inverse relationship for all but the largest microflagellates. Errors in growth rate estimates will 126 result when wind mixing or lateral transport of cells within water masses occurs at time scales close to or less than the sampling interval. Harris (1986) places environmental fluctuations at scales of 50 to 200 h, a range of time intervals leading to interaction with growth rates and therefore population dynamics. In this study 187 paired data points, at two-day intervals, were used for calculating the net growth rate constant (kn). In order to examine the apparent affects of sampling interval on observed 3999999999 growth rates, kn was calculated for all combinations of'2-, 4-, 8-, 14- and 30-day intervals (Figure 2.7). The greatest range of kn values occurred at 2-day intervals and it progressively decreased with increasing sampling intervals. The assumption of exponential growth necessarily becomes invalid as sampling interval increases, i.e. the longer the interval between observations the more likely there will be a shift in the trend of population change (Tilzer 1984). This does not imply that exponential growth was always occurring at 2-day intervals. Similar results are presented for 99199999999 '99999' in Figure 2.8. The maximal kn values for 99199999999 occurred in winter and-spring during the annual population minimum and are misleading because, at that time, relatively small counting errors greatly affected the calculation of kn. 127 Figure 2.7. Seasonal 3999999999 cell abundance (upper) and observed growth rate constants (kn) calculated at sampling intervals from 2 to 30 days in the 0-4-m stratum (remaining panels). Cels m.“ kn (day' 1) 0.5 0.4 0.3 0.2 0.1 -0.1 -0.2 -0.3 0.2 0.1 -0.1 -0.2 0.1 -0.1 0.1 -0.1 0.1 -0.1 -0.2 128 I III III IIIIII III III III III II I III III I I I T I Rhodomonas. 0-4 m 2-DAY 4-DAY 8-DAY l 1 982 Figure 2.7 129 Figure 2.8. Seasonal 99199999999 cell abundance (upper) and observed growth rate constants (kn) calculated at sampling intervals from 2 to 30 days in the 0-4-m stratum (remaining panels). Cells ~mL'1 kh(d2f5 130 o ..I -o.2 - -o.4 - —o.e - -o.a - -1 _ III III III II III] H II] III ”I ,. III I 2—DAY 0.4 - 0.2 - o ... -o.2 J -o.4 - 4-DAY 0.2 ‘ s-oAY O .— -o.2 - 0.2 - 0 ‘W -0.2 - 14-DAY 0 ————— Ww' _ "F'T '71.... __‘._I..' _ "tum—w— A S 0 N D .J F M A M J J 1982 1983 Figure 2.8 131 Decreases in kn with increasing sampling interval were presented as annual means in Figure 2.9 for both taxa. Apparent in this figure is the possibility that optimal sampling interval for maximizing kn may be less than two days. The smallest usable sampling interval for the calculation of kn is dependent upon the growth estimator, in this case numerical abundance. If, as was shown for 3999999999 in culture (this study, Table 2.1), cell division occurs once each day, the optimal sampling interval would be one day. Light-synchronized 3999999999 populations, both in culture and at times 19 9199 (Lawrence Lake, June 1984), undergo cell division during the dark period (W. D. Taylor, unpublished data). In this case, calculation of kn based on multiple daylight samplings during one daylight period would be meaningless. Frequency distributions of kn for 3999999999 and 99199999999 '99999', are presented in Figures 2.10 & 2.11, respectively. Values of kn near zero resulted from small changes in population abundance between sampling intervals. The significance of these low values is difficult to interpret because at one extreme they derive from the lack of growth and losses through a time period, while at the other extreme they derive from a realistic balance between growth and loss rates. The latter is a dynamic and active situation while the former is static. Positive kn values less than 0.1 represent doubling times greater than seven Figure 2.9. 132 Annual mean kn of 3999999999 and 99199999999 calculated at sampling intervals of 2 to 30 days in the 0-4-m stratum. Values for positive growth (kn) and negative growth (-kn) were meaned separately. 133 0.3 H Cryptomonas H Rhodomonas 0.2 '- PA I >. .. (U 0.1 'C v j o C a (U (l) E 7:“ .01 c ' ‘- C (U -0.2 - '0-3 I I I I I 0 2 4 8 14 30 calculation interval (days) Figure 2.9 134 Table 2.1. Specific growth rates (k) in 1n units and doubling times (G) reported in the literature for field and laboratory studies of 99199999999 and BDQQQEQDQE- Species kn (day‘l) G (days) Location Source 3. 919999 0.16 4.4 in situ 1 3. 919999 0.46-0.62 1.5-1.1 in situ 2 3. minuta 0.11 6.3 enclosure 3 3. 1acus9919 0.27 2.6 in situ 4 3. 919999 0.23 3.0 in situ 5 3. 919999 0.20-0.34 2.0-3.5 in situ 6 3. 9inut9 0.17 4.1 enclosure (spring) 7 3. 919999 0.71 1.0 enclosure (ES) 7 3. 919999 0.29 2.3 enclosure 8 3. minut9 0.24 2.9 in situ 9 3. minut9 0.44 1.6 in situ 13 3. 919999 0.69 1.0 batch culture 10 3. 199999919 1.13 0.6 batch culture 4 9. 91999 0.5 1.4 batch culture 11 9. 99999 0.85 0.8 batch culture 12 9. (4 spp.) 0.19 3.4 in situ 1 9. sp. 0.6 1.2 enclosure 8 9. sp. 0.15 4.6 Enclosure (spring) 7 9. sp. 0.49 1.4 enclosure (ES, MS) 7 9. 91999 0.48-0.89 0.8-1.4 in situ 2 9. 91999 0.24-0.25 2.8-2.9 in situ 6 r 1Wright 1964; under snow-free ice and low grazing pressure. 2Sommer 1981: 3. 919999 in spring, 9. 91999 in spring and summer. 3Reynolds et al. 1983: high grazing pressure. 4Gayrieli 1984: 12 2122 at Greifensee, 1978, in culture at 22 c and 214.5 uEinst-m’Z-s’l 5Taylor & Wetzel 1984: seven days of log growth in autumn. 6Braunwarth & Sommer 1985; mitotic index used to calculate potential growth rate. 7Reynolds et a1. 1982; ES and MS are early and mid- stratification, respectively. 8Reynolds et al. 1985; depressed zooplankton biomass (July). 9Elser et a1. 1987. 1°This study: 12L/12D cycle, 150 uEinst-m'z-s’l, 20°C. 11Cloern 1977: ISL/9D cycle, 150 uEinst-m’Z-s'l, 20°C. 2Morgan and Kalff 1979: 138 IIEinst-m'z-s'1 continuous light, 23.5'C. 3Calculated from data given in Willén et al. 1982. 135 Figure 2.10. Frequency distribution of observed kn for 3999999999 in the 0-4-m stratum. Frequency 60 30 20 10 136 l 2'3. :;:;:-:-:-., .‘o‘véfi <0.0 >0.0 >0.2 >0.4 <-0.3 <-0.‘l >0.1 >0.3 >0.5 Observed k (day'1) Figure 2.10 137 Figure 2.11. Frequency distribution of observed kn for 99199999999 in the 0-4-m stratum. Frequency 138 .p. O 0) 0| 1 00 O I M 01 1 N O 1 <-O.6 <-0.4 <—0.2 ‘0.0 >0.0 >0.2 >0.4 <-0.5 <-O.3 <—0.1 >0.1 >0.3 ’0.5 Observed k (day 1) Figure 2.11 139 days while negative kn values larger than -0.1 represent halving times greater than seven days. A large number of cases fell within this narrow range (open bars in Figures 2.10 and 2.11), 52 and 34 percent for 3999999999 and 99199999999, respectively, indicating that during much of the year observable growth or loss was negligible. When kn approaches the laboratory-derived potential maximum growth rate ambient conditions are optimal and losses of any kind can be assumed to be minimal. Larger kn values contain more directly interpretable information. When losses can be measured or estimated the adjusted growth rate should be close to the true growth rate of the population. Use of the mitotic index to directly estimate 19 9199 growth rates, thus avoiding the problems associated with determining all loss factors, has recently been applied to the cryptophytes (Braunwarth and Sommer 1985). Very low negative values of kn represent observed cell losses in great excess of gains. Culture studies provide the means to determine growth characteristics of algal isolates under optimal nutrient, light and temperature conditions without the confounding factors of species interactions and environmental variability. There has been much critical discussion, however, on the transfer of laboratory7derived growth parameters to field situations where growth controlling factors (light, temperature, nutrients) are variable and, in the case of nutrients, with 19 9199 concentrations often 140 orders of magnitude lower than in the culture situation. Still, laboratory estimates of growth rate constants establishes potential maxima for various species and provide standards against which 19 9199 estimates can be compared. Maximum growth rates observed for 3999999999 and 99199999999 from culture and 19 9199 studies are summarized in Table 2.1. Laboratory-derived doubling times of less than one day were reported for both taxa in cultures grown in continuous light (Gavrieli 1984, for 3999999999, and Morgan and Kalff 1979, for 99199999999 99999). We found light-synchronized 3999999999 cultures to double at daily intervals under a 12L/12D cycle with cell division occurring in the dark phase. The minimum doubling time was greater for 9. 91999 (G = 1.4 days) within a 15L/9D cycle (Cloern 1977). Minimum doubling times reported in studies of natural populations of cryptophytes varied widely from 0.8 days for 9. 91999 (Sommer 1981) to 6.3 days for 3999999999 (Reynolds et a1. 1983); this range encompassed extremes in grazing pressure and growth conditions found in a variety of lake types. In Lawrence Lake, near maximal growth rates (i.e. G S 1 day) were not observed for 3999999999 and only rarely and in winter for 99199999999 (occurring less than two percent of the time). Observed doubling times were nearly always greater than three days for both species. Distributions of kn values occurring during an annual period are useful for evaluating population dynamics 141 relative to known maximum growth rates. However, an evaluation of the frequency of switching between positive and negative growth provides insight into how well growth or loss was sustained during consecutive sampling intervals. Switching frequencies (the percentage of pairs of adjacent kn values with opposite signs) at several sampling intervals are presented in Figure 2.12. At two-day sampling intervals more than 60 percent of the pairs of adjacent values (for both taxa) switched signs, indicating apparent frequent reversals during growth and loss phases. High frequency switching at the closest intervals resulted largely from minor variability in cell abundances. Increasing sampling interval reduced switching frequency by spanning relatively minor close-interval variations in cell abundance, thereby focusing on longer-term population phenomena. However, rapid changes in the magnitude of kn may be associated with the ability of these species to respond quickly to changing conditions (Stewart and Wetzel 1986). On the contrary, reductions in kn may indicate high mortality associated with intense zooplankton grazing or cell lysis. The reduction in switching frequency with increasing sampling interval is also apparent in the lower panels of Figures 2.7 and 2.8. There were few periods of sustained exponential growth by 3999999999 or C9199o9on9s during this study. The assumption of exponential growth in the calculation of kn was frequently invalidated when intervals exceeded several 142 _ days. With these data, minimizing day to day variations in kn by increasing sampling interval automatically resulted in a reduction in calculated kn. This change was so because the denominator in the equation for calculating kn increased with longer sampling intervals while the difference between the population maximum and minimum remained constant for any given data base. 143 Figure 2.12. Switching frequency as the percentage of pairs of adjacent kn values with opposite signs at sampling intervals of 2 to 30 days in the 0-4-m stratum. Percent Switching Frequency 144 II 024 " Figure 2.12 I T 8 14 Calculation Intervals (days) 30 145 Summary 1. The crYPtOPhYtBS. Wanna minus; and W '99999', dominated the phytoplankton community during autumn, and accounted for a maximum of 50 percent of the total cell volume. 2. Annual seasonal cryptophyte dynamics varied between species. 3999999999 had unusually stable population dynamics throughout the study while 9. '99999' developed broad maxima in summer and autumn with a much reduced population during winter and spring. 3. Differences in abundance with depth of 3999999999 and 99199999999 were generally small and restricted to periods of thermal stratification. Metalimnetic maxima occurred during parts of March, April, July and August with 39o909ona9 and during July and August with 99199999999. 4. The risk of missing important population fluctuations substantially increased as sampling intervals extended beyond one week for 3999999999 and two weeks for W- 5. The greatest observed growth rates occurred at the closest sampling intervals and often when cell abundance was lowest. Calculations of kn at these times were most susceptible to small variations in abundance estimates. Dynamic population trends were better reflected in larger sampling intervals but exponential growth, an assumption for 146 calculating kn, was frequently invalidated at intervals exceeding three or four days. 6. During much of the year observable growth and loss was negligible (:6 > 7 days), for 52 and 34 percent of the time for 3999999999 and 99199999999, respectively. 7. 3999999999 was never observed to change 19 9199 at maximum laboratory measured growth rates while 99199999999 was observed at maximum rates in less than two percent of the cases. 8. High frequency switching, between positive and negative kn, at the closest intervals was thought to be largely due to minor variability in cell abundances. Increasing sampling interval reduced switching frequency by spanning relatively minor close-interval variations in cell abundance, thereby focusing on longer-term population phenomena. 9. Few periods of sustained growth occurred by either species during this study even though both were present continuously. 39o9omon99 was always present in great enough abundance to take advantage of periodic optimal growth conditions. That such rapid responses did not occur is an indication of either continuous limitation by an essential nutrient (e.g. phosphorus), strong competition by other phytoplankton for limited nutrients, or finely adjusted population control by grazers. References Anton, A., and H. C. Duthie. 1981. Use of cluster analysis in the systematics of the algal genus 99199999999. Can. J. Bot. 59:992-1002. Banse, K. 1976. Rates of growth, respiration and photosynthesis of unicellular algae as related to cell size - a review. J. Phycol. 12:135-140. Braunwarth, C. and U. Sommer. 1985. Analyses of the 19 9199 growth rates of Cryptophyceae by use of the mitotic index technique. Limnol. Oceanogr. 30:893—897. Campbell, L. and E. J. Carpenter. 1986. Diel patterns of cell division in marine 9199999999999 spp. (Cyanobacteria): use of the frequency of dividing cells technique to measure growth rate. Mar. Ecol. Prog. Ser. 32:139-148. Cloern, J. E. 1977. Effects of light intensity and temperature on 99199999999 91999 var. 991us99i9 (Cryptophyceae) growth and nutrient uptake rates. J. Phycol. 13:389-395. Crumpton, W. G. and R. G. Wetzel. 1982. Effects of differential growth and mortality in the seasonal succession of phytoplankton populations in Lawrence Lake, Michigan. Ecology 63:1729-1739. Elser, J. J., N. C. Goff, N. A. MacKay, A. L. St. Amand, M. M. Elser and S. R. Carpenter. 1987. Species-specific algal responses to zooplankton: Experimental and field observations in three nutrient-limited lakes. J. Plankton Res. 9:699-717. Fogg, G. E. 1975. Algal Cultures and Phytoplankton Ecology. Second edition. The University of Wisconsin Press, Madison, 175 pp. 147 148 Gavrieli, J. 1984. Studies on the autoecology of the freshwater algae flagellate 3999999999 199999919 Pascher et Ruttner. Diss. at Swiss Federal Institute of Technology of Zurich, Switzerland. 77 pp. Haney, J. F. and D. J. Hall. 1975. Diel vertical migration and filter-feeding activities of 9999919. Arch. Hydrobiol. 75:413-441. Harris, G. P. 1986. Phytoplankton Ecology: Structure, Function and Fluctuation. Chapman and Hall Ltd., London, 384 pp. Horn, H. 1984. The effects of sampling intervals on phytoplankton growth and loss values derived from seasonal phytoplankton biomass variations in an artificial lake. Int. Revue ges. Hydrobiol. 69:111-119. Kilham, P. and S. S. Kilham. 1980. The evolutionary ecology of phytoplankton. 19: The Physiological Ecology of Phytoplankton, I. Morris (ed.), pp. 571-597, University of California Press, Berkeley. Lewis, Jr., W. M. 1978. Dynamics and succession of the phytoplankton in a tropical lake: Lake Lanao, Philippines. J. Ecology 66:849-880. Lund, J. W. G. 1962. A rarely recorded but very common British alga, 3999999999 919999 Skuja. British Phycol. Bull. 2:133-139. Lund, J. W. G., C. Kipling and E. D. Le Cren. 1958. The inverted microscope method of estimating algal numbers and the statistical basis of estimations by counting. Hydrobiologia 11:143-170. Lund, J. W. G. and C. S. Reynolds. 1982. The development and operation of large limnetic enclosures in Blelham Tarn, English Lake District, and their contribution to phytoplankton ecology. Prog. Phycolog. Res. 1:1-65. Morgan, K. C. and J. Kalff. 1979. Effect of light and temperature interactions on the growth of 99199999999 99999 (Cryptophyceae). J. Phycol. 15:127-134. Pedrés-Alio, C., J. M. Gasol and R. Guerrero. 1987. On the ecology of a 99199999999 99ase91u9 population forming a metalimnetic bloom in Lake Ciso, Spain: Annual distribution and loss factors. Limnol. Oceanogr. 32:285-298. 149 Pejler, B. 1977. Experience with rotifer cultures based on . Arch. Hydrobiol., Beih. Ergebn. Limnol. 8:264-266. Porter, K. G. 1973. Selective grazing and differential digestion of algae by zooplankton. Nature 244:179-180. Reynolds, C. S. 1984. The Ecology of Freshwater Phytoplankton. Cambridge University Press, New York, 384 pp. Reynolds, C. S., G. P. Harris and D. N. Gouldney. 1985. Comparison of carbon-specific growth rates and rates of cellular increase of phytoplankton in large limnetic enclosures. J. Plankton Res. 7:791-820. Reynolds, C. S., J. M. Thompson, A. J. D. Ferguson and S. W. Wiseman. 1982. Loss processes in the population dynamics of phytoplankton maintained in closed systems. J. Plankton Res. 4:561-600. Reynolds, C. S., S. W. Wiseman, B. M. Godfrey and C. Butterwick. 1983. Some effects of artificial mixing on the dynamics of phytoplankton populations in large limnetic enclosures. J. Plankton Res. 5:203-234. Ruttner, F. 1963. Fundamentals of Limnology (Translation by D. G. Frey and F. E. D. Fry). University of Toronto press, Toronto, 295 pp. Sommer, U. 1981. The role of r- and K-selection in the succession of phytoplankton in Lake Constance. Acta 0ecolog. 2:327-342. Sommer, U. 1982. Vertical niche separation between two closely related planktonic flagellate species (Bheggmeneg lgng and Bhgdgmgngg minute v. 99999919999199). J. Plankton Res. 4:137-142. Sommer, U. 1986. Differential migration of Cryptophyceae in Lake Constance. 19: Migration: Mechanisms and Adaptive Significance. M. A. Rankin (ed.). Mar. Sci. Supp. 27:166-175. Stewart, A. J. and R. G. Wetzel. 1986. Cryptophytes and other microflagellates as couplers in planktonic community dynamics. Arch. Hydrobiol. 106:1-19. Taylor, W. D. and R. G. Wetzel. 1984.- Population dynamics of Bhggemengg minus; V. nannenlangsise Skuja (Cryptophyceae) in a hardwater lake. Verh. Internat. Verein. Limnol. 22:536-541. 150 Tilzer, M. M. 1984. Estimation of phytoplankton loss rates from daily photosynthetic rates and observed biomass changes in Lake Constance. J. Plankton Res. 6:309-324. Willén, E., M. Oké and F. Gonzalez. 1982. 39odomon9s 21.2222 and 1311222221122 1222 (Cryptophyceae) - impacts on form-variation and ecology in Lakes Malaren and Vittern, Central Sweden. Acta Phytogeogr. Suec. 68:163-172. Wetzel, R. G. 1981. Longterm dissolved and particulate alkaline phosphatase activity in a hardwater lake in relation to lake stability and phosphorus enrichments. Verh. Internat. Verein. Limnol. 21:369-381. Wetzel, R. G. 1983. Limnology. 2nd ed. W. B. Saunders Co., Philadelphia. 767 pp. Wright, R. T. 1964. Dynamics of a phytoplankton community in an ice-covered lake. Limnol. Oceanogr. 9:163-178. CHAPTER 3 PRODUCTIVITY OF THE CRYPTOPHYCEAE VERSUS GRAZING IMPACTS DURING EPILIMNETIC DEEPENING IN AUTUMN Introduction Periods occur during the year when increasing rates of change in weather cause rapid alterations in the physical and chemical structure of most north temperate lakes. After several months of relatively high thermal stability and maximal algal biomass, decreasing solar radiation in autumn causes rapid cooling of the surface waters. With cooling, thermal stability is eroded, mixed depth is increased and available light is reduced. These events lead to the decline of the summer phytoplankton community and its replacement by species better adapted to a less stable environment. Stewart and Wetzel (1986) proposed a modified model of phytoplankton community dynamics in which microflagellates and the Cryptophyceae can function as couplers to maintain productivity between the waxing and waning of major algal community components. Characteristics of these organisms cited in support of their model included intermittent numerical dominance, high nutritional quality, short turnover times, ability to grow and reproduce at low light intensities, and pulse timing (i.e., growth coinciding 152 with periods of decomposition of dominant populations. Many of these factors are operating in Lawrence Lake, Michigan, where dominance by cryptophytes during the autumnal epilimnetic deepening period has been consistently observed (Taylor and Wetzel 1984, Stewart and Wetzel 1986). Worldwide, cryptophytes have been reported as dominants in the phytoplankton community in all seasons (reviewed by Stewart and Wetzel 1986). Cryptophytes dominate in large lakes (Munawar and Munawar 1975) and in small ponds (Kalff 1967), and under a wide range of lake trophic states, e.g., oligotrophic (Findenegg 1971), mesotrophic (Moss 1972), eutrophic (Willén 1976) and dystrophic (Ramberg 1979). Distribution is cosmopolitan, ranging from the tropics (Lewis 1978) to tundra ponds in the high northern latitudes (Kalff 1967). Their widespread occurrence in freshwater plankton communities is unquestioned and yet very little is known about their ecology (Oakley and Santore 1982). Taxonomically the Cryptophyceae, at the light microscope level, are an exceptionally difficult group with less than 100 described freshwater species (Huber-Pestalozzi 1968). Taxonomic difficulties arise from the simplicity of their external morphology and the reliance of classical taxonomists on characteristics such as color, cell shape and orientation of trichocysts. Cells of cryptophytes are unsymmetrical and the shape of even slightly rotated cells may vary considerably from published illustrations and 153 descriptions. Taxonomic problems have hindered study of cryptophyte ecology. Ultrastructural investigations are revealing distinctive features unavailable to the light microscopist that should allow a more natural separation of species and genera (Oakley and Santore 1982). Recently, expanded interest in the Cryptophyceae has extended our knowledge of their ecology (Morgan and Kalff 1975, Cloern 1977, 1978, Sommer 1982, Gavrieli 1984, Pedros-Alio 1987). The purpose of this study was to verify the timing of transitional population shifts, make direct measurements of cryptophyte productivity for comparison with the rest of the autotrophic community, and evaluate the potential impact of the grazer community on cryptophyte populations in Lawrence Lake. Materials and Methods 51.122222211221211 Lawrence Lake is a small, dimictic, hardwater lake with low pelagic productivity in southwestern Michigan, U.S.A. The lake has been well described morphometrically, chemically, and biologically (e.g. Rich et a1. 1971, Wetzel et al. 1972, Wetzel 1983). Details of annual phytoplankton dynamics and community structure are presented in Chapter 1 of this dissertation. 154 W Studies for general limnology, zooplankton grazing, zooplankton density and cryptophyte productivity were staggered because the work load precluded their simultaneous execution. General limnology and zooplankton grazing studies were conducted biweekly. Samples for zooplankton densities were collected at 3 to 5-day intervals: those nearest to the sampling dates for zooplankton grazing were used in this analysis. Cryptophyte productivity studies were conducted at intervals varying from 5 to 16 days between August 7 and November 30. However, intervals were from 5 to 9 days during the very active period of cryptophyte growth, September 18 to November 16. Phytoplankton samples were collected at 1 to 7-day intervals. MW Light and temperature measurements were made at l-m intervals with a LiCOR model LI-185 quantum photometer and a YSI 43JD thermistor, respectively. Samples for determination of conductivity, alkalinity, pH, alkaline phosphatase activity (APA), and chlorophyll 9 (Chla) were collected with an opaque 3-L Van Dorn bottle at 0, 1, 2, 3, 4, 5, 6, 7, and 10-m depths. APA of whole lake water samples was measured by the enzymatic hydrolysis of non-fluorescent 3-0-methyl 155 fluorescein phosphate mono-cyclohexylammonium to the fluorescent product, 3-0-,ethyl fluorescein as slightly modified from Hill et a1. (1968) and Perry (1972) by Wetzel (1981). Chla was measured using the trichromatic method of Strickland and Parsons (1968) as presented by Wetzel and Likens (1979). Samples of 500 to 750 mL were filtered onto AA Millipore filters (0.8-um pore size) at a vacuum differential of less than 0.5 atm. Alkalinity was determined by titration with H2804 using a mixed indicator. A Coleman 38A pH meter was used to measure pH in the laboratory with samples at room temperature. Total available inorganic carbon was calculated from pH, temperature, and alkalinity measurements (Wetzel and Likens 1979). Because phytoplankton samples were integrated over 4-m intervals (see below), equivalent integrated values were determined for some of the parameters that were measured at discrete depths. Integral mean values, i.e. adjusted for differences in volume with depth, were calculated for APA and Chla for the 0-4-m and 4-8-m strata. £21222122322n Crumpton and Wetzel (1982) evaluated phytoplankton patchiness in Lawrence Lake and consistently found no greater variance among five stations than between replicates 156 at a single station. Further periodic testing in this study at four stations supported their findings (Table 3.1). Vertically integrated phytoplankton samples (130 mL) were collected over the central basin with a 4-m long 5-L capacity Van Dorn type sampler and immediately preserved with 1 mL of acid Lugol's solution (Vollenweider 1974). Uterméhl's (1958) sedimentation method was used to prepare the samples for identification and enumeration. The recommendations of Lund et a1. (1958) were followed for counting precision. In all cases, between 600 and 2000 total algal units were counted giving a counting error of less than ten percent for each sample. Complete transects of the chamber diameter were counted at several magnifications (360x, 180x, 90x); the magnification was dependent upon the size and abundance of the cells being evaluated. The entire chamber was used to enumerate large forms such as C9r9t1um. Species identification under oil immersion (900x) was routine. Counting and cell measurements were made with a Wild M40 inverted microscope. Twenty-five mL samples were settled for at least 15 h within a styrofoam insulated box to minimize convective currents caused by temperature fluctuations throughout the day. Cell volumes were calculated for each species using formulae for solid geometric shapes most closely matching the cell shape. Mean cell volumes were based on individual 157 Table 3.1. Results of one-way ANOVA to examine horizontal patchiness of phytoplankton in Lawrence Lake, Michigan, using 3999999999 919999 as a test organisml. (means as cells-mL' ) Date Range of Means Grand F Significance from 4 Stations Mean (n=12) Level 30-0ct-82 210-224 215.1 0.5249 0.677 02-May-83 156-169 163.2 0.2133 0.884 21-Jun-83 157-173 167.6 0.5843 0.642 23-Ju1-83 130-159 138.8 1.2212 0.363 1Three replicate integrated 0-4 meter samples were collected from each of four stations 50 to 100 meters apart in the open water. Cells were counted according to the methods described in the text. 158 cell volume calculations. Cell volumes were determined seasonally when changes in cell size were apparent. Given the difficulty of directly measuring cell carbon for individual algal species in a mixed population, workers generally rely on conversions from measurable attributes such as cell volume (Nauwerk 1963, Beers et al. 1975, Banse 1976, Smayda 1978, Reynolds 1984). Cell volumes are commonly calculated from measurements of cell dimensions. Significant differences occur between conversion factors in accordance with whether or not the cells are preserved prior to measurement. For example, Borsheim and Bratbak (1987), using three measuring techniques, reported a 55-percent mean reduction in microflagellate cell volume after fixation with acid Lugol's solution. The latter authors determined a cell volume to cell carbon conversion of 0.10 pg C-nm'3 for living flagellates and 0.22 pg C-um’3 for preserved flagellates. The latter conversion factor is very close to that calculated from Strathmann's (1967) empirically derived formula for non-diatom species when applied to fixed cryptophytes of similar cell volume (this study). A conversion factor for 3999999999 of 0.28, based on direct measurements of cultured cells, was provided by Yngvar Olsen (personal communication). He stressed the importance of using this factor only with fixed cells. The formulae of Strathmann were used throughout this study because they accounted for differences between diatom and non-diatom 159 species, reflected changes in relative carbon content with increasing cell size and they provided a consistent method for estimating cell carbon in a mixed community. Cell volumes varied by a factor of 5 x 104 during this study. The phytoplankton community was subdivided into particle size classes (<10 um, 10-30 pm, 30-50 um, >50 um) based on microscopic determination of their greatest linear dimension. 3999999999 and 99199999999 were in the <10 and 10-30 pm size classes, respectively. The grazing studies directly measured loss rates for the 3999999999 and 99199999999 size classes of particles. Calculation of specific growth rates (k) for the phytoplankton community and for selected cryptophyte species was as follows: k = P/C (1) where P is 14C productivity per day and C is algal carbon (Redalje and Laws 1981). Methods for 14C productivity estimates are given below. WW Zooplankton population estimates were based on aggregate samples collected from four stations in the main basin (data provided by M. Leibold). The stations were at least 20 m apart. Samples were collected with a 10.5 L 160 Schindler trap, equipped with a 75-um mesh net, at one meter intervals at each station, beginning at 0.5 m. The trap was 0.5 m high. The samples were combined across stations and by depths, i.e., depths 0.5 plus 1.5 m and 2.5 plus 3.5 m. Final aggregate samples were thus the result of eight Schindler trap samples with a total sample volume of 84 L. Samples were collected at night and during the day on each sampling date. Nighttime samples were collected at least one hour after sunset (total darkness) although some were collected later, up to three hours after sunset. Although zooplankton samples were collected twice weekly throughout much of the study period, only the samples closest to grazing rate study dates were used in this analysis. Zooplankton were preserved in 4% sucrose formalin solution (Haney and Hall 1973). Samples were counted under a dissecting microscope at 250x using an ocular micrometer for measurements. Subsamples for counting were taken with a calibrated 'dipper' from a well-stirred sample. Enough subsamples were counted to ensure that.at least 100 individuals (9999919 species) were counted for each vertical profile. Individuals were sorted by size class on the basis of length between the eye and origin of the tail spine. W The grazing rate studies were conducted to estimate the impact of zooplankton on cryptophytes in the epilimnion of 161 Lawrence Lake. The general approach was to measure 19 9199 grazing rates for species and size classes of zooplankton on a per individual basis. Independent zooplankton population estimates were used in conjunction with measured grazing rates to calculate total grazing impact. All grazing rate estimates were made 19 9199 using a 5.9-L Haney chamber (Haney 1971). Grazing rates for two algal size classes were obtained with a dual label. 99199999999 9999199999999 was used for the <10 um size class. It varied in cell volume from 40-70 um3 with a greatest linear dimension of about 9 pm. 9919919999999 sp. was used to represent the 10 to 30 um size class. The cell volume of 9919919999999 varied from 700 to 1800 um3 with a greatest linear dimension of about 16 um. Cell concentrations amended in feeding experiments were kept as low as possible to minimize the direct effect of particle number on grazing rate. Addition of the final labeled algal suspension to the incubation chamber increased cell abundances by less than 20 percent for each size class. MW Stock algal cultures were maintained in freshwater medium (Guillard and Lorentzen 1972) with phosphorus and nitrogen at half strength on a 12:12 L:D cycle at 140 uEinst-m"'2-s'1 and 20°C. 99199999999 was kept axenic to eliminate the possibility of bacterial uptake of 32F during 162 the labeling period. Pre-labeling cultures were prepared about one week prior to each grazing analysis. A 1-2-mL inoculation was made into 25 mL of fresh media producing rapidly growing populations of cells for labeling. The process of labeling cultures was started 48 to 72 h prior to each grazing determination. The entire pre- labeling culture of 9919929999999 was concentrated by centrifugation to about 5 mL. The cells were added to 35 mL of standard media with about 200 ucil4C (7.4 x 106 Bg). About 4 to 6 mL of the pre-labeling 99199999999 culture was added to 35 mL fresh media at 1/4-strength phosphorus. Sufficient stock 32F, as NaPO4, was added to the 99199999999 inoculum to insure an activity of about 1 mCi (3.7 x 104 Bg) one week after the run. The labeling cultures were buffered to pH 7.5 with tricine/HCO3 and were kept at 20°C in constant light. Final preparation included concentration and washing by centrifugation and resuspension to final density for the experiments. The stocks of labeled algae were kept on ice in the dark after the field experiments began. Calibration samples were taken immediately before and after laboratory preparations for the first and last field experiments. This calibration activity was interpolated for each experimental run during the 24-h day. The inoculation cylinders were kept on ice in a cooler until used in the field. A one-mL 163 sample from each culture was preserved with acid Lugol's solution for microscopic cell counts. W Large diel variations in zooplankton grazing rates have been well documented in several lakes (e.g. Haney and Hall 1975, Crumpton and Wetzel 1982). Lakes dominated by daphnids have greater nighttime grazing rates; experiments were therefore conducted three times during the day on each sampling date over the central depression of the lake. Two experiments, predawn and 1-2 h after dusk, were made in total darkness and the third was made at noon. Two replicate incubations of less than ten minutes each were made at two depths, 2 and 9 m. Grazing rate estimates from the 2-m depth were assumed to be representative for the epilimnion (0-4 m). After the incubations the grazing chamber was evacuated into a pair of nested Nitex screens mounted on Plexiglas cylinders. The inner screen (140-um mesh) trapped the larger zooplankton while the outer screen (70-um mesh) trapped the smaller rotifers and nauplii. Separation of the two groups in the field greatly enhanced the efficiency of sorting in the laboratory which was done between field trips. The screens with zooplankton were immediately placed in wide mouth glass jars half full of ice-chilled filtered lake water. The water was filtered through a 30-um mesh size screen and a 0.5 mgP-L'1 inoculum was added to exchange 164 with any 32F adsorbed to the zooplankton. An equal volume of chilled carbonated soda water was added to the container before it was sealed. No further preservation was used other than to keep the samples chilled with ice until they were processed. These measures were taken to lessen leakage of label resulting from chemical or heat killing of the animals (cf. Holtby and Knoechel 1981). W Between field experiments the samples were processed in the laboratory. The large zooplankton'were separated and counted by species and size class directly into scintillation vials. When available at least twenty individuals from each category were sorted. In most cases rotifers and nauplii were segregated into groups of 100 individuals each. Rotifer and nauplii grazing activity was always inconsequential relative to total grazing activity. Therefore their contributions were not considered further in the analysis. The samples were dried in a forced air oven at 80°C for 3-6 h and then digested for liquid scintillation radioassay in 0.75 mL per vial of Packard Soluene~350 at 55°C. After a 20-h digestion 10 mL of a compatible liquid scintillation cocktail was added to each vial. The samples were mixed twice, one hour apart, and then were undisturbed for 8 h at room temperature to reduce chemiluminescence. Radioassay 165 was done in two channels to separate 14C and 32F activities in a Beckman 8000 liquid scintillation counter. Samples with either 14C or 32F internal standards were used to determine counting efficiency for each isotope. Blanks (filtered lake water) and calibration samples were processed with the zooplankton samples. WWW Zooplankton grazing rates were determined for individual species and size classes during one light and two dark periods on each date. Zooplankton population estimates were made for each species and size class at noon and 1 to 2 hours after sunset within 2 days of the grazing rate determinations. This information was reduced, using the following formula, to provide an estimate of daily grazing rate: G = hd[8((Fid1 + Fid2)/2)*Aid] + h1[Z(Fil*Ail)] (2) where G is the integrated 24-h grazing rate (mL-L’l-day'l), hd and hl are the length of the dark and light periods (hours), respectively, Fidl and Fidz are replicate means of the first and second dark period instantaneous grazing rates for the ith species (mL-animal'l-h'l), respectively, F11 is the replicate mean light period instantaneous grazing rate for the ith species, and Aid and Ail are the abundance 166 estimates for the ith species in the dark and light periods (animals-L'l), respectively. En9l2az_srn2K9gigrgausgrggiggzannx_flflznl 21219.1929995 19 9199 14C incubations were used to estimate community primary productivity (Steemann Nielsen 1951, 1952) and for estimating the productivity of selected cryptophyte species using nuclear track microautoradiography (Knoechel and Kalff 1976). Replicate 500-mL glass-stoppered reagent bottles and a 130-mL bottle for phytoplankton enumeration were filled with vertically integrated lake water (0-4 m) collected over the central basin with a 4-m long Van Dorn type sampler. The sampler, made of opaque PVC, had an inside diameter of 5 cm with a total volume of about 5 L. Possible algal toxicity from PVC was minimized since the sampler had been used daily for more than a year prior to this study. Optimal recommended radioactivity for NTM prepared material should be 0.1-1.0 disintegrations-cell'l-day"l with a usable range of 0.01-10 disintegrations-cell"':'--day"1 (Knoechel and Kalff 1976). Preliminary testing indicated that this criterion could be met in Lawrence Lake with 3-mL injections of 20-26 uCi 14c (7.4-9.6 x 105 Bq). This activity was also suitable for total productivity determinations. Three replicate light bottles and one dark bottle were incubated at a depth of two meters for about two hours. All 167 incubations were made between 10:00 and 14:00, with most occurring between 10:30 and 12:30. After incubation with 14C the bottles were placed in the dark, chilled with ice and returned immediately to the laboratory (usually within 30 minutes) for processing. Th§_l§akags_nrghlgl There has been considerable recent discussion about the problem of label leakage from cells after chemical fixation in microautoradiography studies. Silver and Davoll (1978) and Paerl (1984) used unacidified Lugol's solution in their experiments and found losses near 50% within minutes of adding the fixative. Their reason for using unacidified Lugol's in their experiments was not stated, but acidified Lugol's solution has been a preferred general algal fixative for many years. Davenport and Maguire (1984) used acidified Lugol's and found the samples to be within <5% of the control. Carney and Fahnenstiel (1987) reported 14C losses on preservation with acid Lugol's solution lower and more consistent than previously reported (0-21%). Watt (1971) and later Paerl (1984) used a combination of filtration, quick freezing, and lyophilization to minimize leakage problems. Both workers mounted and cleared the filters for grain density autoradiography. Smith and Kalff (1983) used a combination of very brief fixation with acid Lugol's solution followed within seconds by filtration to minimize 168 33P losses. The filters were air dried and mounted on slides for clearing. Cryptophytes are especially susceptible to cell lysis during mechanical manipulations (e.g. filtration, centrifugation) and must be fixed prior to processing to ensure cell integrity. The methods mentioned above were modified to minimize the time that cells were suspended in water after fixation thereby reducing their susceptibility to leakage. Hewes and Holm-Hansen's (1983) filter-transfer-freeze (FTF) method was combined with the basic approach of Watt (1971) and Paerl (1984). The FTP technique was developed to concentrate and recover intact nanoplankton cells for light microscopy and eliminate the filter from the final slide mount thus improving resolution of the microflagellates. The general procedure was as follows: after filtration the filter was frozen face down on a microscope slide and then peeled off leaving the cells transferred in a frozen state to the slide. Hewes et al. (1984) found the FTP technique equal or superior to other methods for estimating nanoplankton populations. HIE.1§DQI§§QI¥.EIQ§§QQE§ Two replicate 50-mL aliquots from each of the four incubation bottles (three light, one dark), one replicate fixed with acid Lugol's solution (at a ratio of 0.1:50) and the other untreated, were filtered onto HA Millipore filters 169 (0.45-um pore size) and analyzed by Geiger-Muller radioassay (Nuclear-Chicago D-47 of known counting efficiency) for total primary productivity estimates. The acid Lugol fixed samples were used to estimate loss of label due to fixation for the total autotrophic community. Six 50-mL replicate aliquots from each incubation bottle were processed as follows for NTA: each aliquot was fixed with acid Lugol's (at a ratio of 0.1:50) and immediately filtered onto a polycarbonate filter (1.0-um pore size) at a vacuum less than 0.3 atm. Vacuum was released just as the meniscus reached the surface of the filter leaving a thin film of water on the filter. The filter was removed while the surface was still wet, placed face down on a drop of filtered (0.22-um pore size) lake water on a glass slide and frozen on a liquid-N2 cooled aluminum plate (Paerl 1984). The glass slides had previously been cleaned and coated with a five percent gelatin-chrom-alum solution (5 g gelatin plus 0.5 g chromium aluminum sulfate-L'l: Rogers 1979). These procedures reduced the critical processing time (i.e., from the addition of fixative through freezing) to less than one minute. Slides with frozen filters were temporarily stored at -70°C in an ultrafreezer until all filtrations were completed. The filters were peeled off, transferring the frozen cells to the slide as described by Hewes and Holm-Hansen (1983), the sample remaining frozen at all 170 times. The complete slide-set was placed directly into a lyophilizer with a shelf temperature pre-cooled to -30°C. After lyophilization, all slides were fumed over HCl for four minutes to drive off inorganic 14C (Davenport and Maguire, 1984). Slides were stored at room temperature under desiccation until prepared for autoradiography. Loss of label from lyophilized cell preparations was assumed to be negligible. Slide preparations for the dark bottle incubations served as controls for dark fixation, chemography, and background. The NTM procedure was modified from Knoechel and Kalff (1976). Lyophilized slides were dipped in liquid (33 - 34°C) Kodak NTB3 nuclear track emulsion (Eastman Kodak Company, Rochester, New York), chilled on inverted ice- cooled pans and dried at room temperature in a desiccator for at least 1 h. Coated slides were stored in light-tight boxes at 4°C with desiccant for 1-3 d. These procedures were carried out in total darkness except for filling the dipping jar with emulsion which was done at least 1 m from a Kodak No. 2 safe light with a 15-Watt bulb. Slides were developed in complete darkness using Kodak D-l9 developer (7 min), followed by a 1% acetic acid stop bath (5 min), rinses in 30% and then 10% Kodak Fixer (30 min each), and two final rinses in deionized water (15 min each). Gentle mixing was maintained for each step during 171 development. The slides were dried in a laminar flow hood and stored at room temperature in a desiccator. The emulsion was rehydrated with 1-2 drops of 30% glycerin solution. A cover slip sealed with clear nail enamel reduced desiccation and produced a semipermanent mount for viewing with a light microscope. Emulsion on the bottom of the slide was removed with a razor blade. Slides with emulsion >25 um thick were used for counting tracks on an Olympus BH microscope with dark field phase contrast optics at 800x magnification. A strict track counting protocol was used. 99299999999 '99999' and 3999999999 919999 cells selected for track evaluation had cell membranes intact and were isolated from neighbors to avoid interference from track overlap. Otherwise the cells were evaluated as they were encountered in random transects of the preparation. A track consisted of a trace with at least 4 grains in a definite sequence, arising within 5 pm of the cell (Knoechel and Kalff 1976). A range of 30 to 150 cells per species were evaluated for tracks on each slide. A factor of 1.14x was used to correct track counts for losses from sample fixation with acid Lugol's solution. The factor was derived from a time series batch culture experiment using 3999999999 as the test organism. A unialgal culture in late exponential growth (20°C, 140 uEinst-m'z's'l, 12L/1ZD light cycle, defined medium of 172 Guillard and Lorentzen 1972) was split between the three 500-mL glass-stoppered light bottles used during the routine 19 9199 productivity studies. After a two-hour incubation with 14C at an activity similar to that used in field studies, 25-mL samples were filtered onto polycarbonate filters (1.0-um pore size) at a vacuum less than 0.3 atm. Samples were taken just prior to fixation, immediately after fixation, and thereafter at 1, 2, 4, 8, 20 and 45-minute intervals. Activity dropped immediately to 93.8% (std = t 5.2%) after addition of fixative and to 85.9% (std i3.3%) after 1 min. Activity was reduced to about 30 percent of initial activity after 45 minutes. Additional less rigorous batch culture experiments showed similar results with immediate post-fixation losses of label ranging from 9.6 to 12.7 percent of non-fixed sample. Finally, pre- and post- fixed samples from all 19 9199 productivity studies were filtered and counted to evaluate label loss for the entire phytoplankton community. Results of these tests showed mean losses of 13.7 percent (std = t11.4%, n=18) 13 to 29 minutes after fixation. Since elapsed time from fixation to stabilization (freezing) of microautoradiography samples took slightly less than one minute, the correction was based on one minute using results from the time series experiment. Comparison of phytoplankton community productivity with microautoradiography derived productivity for selected cryptophyte species required common units. The 14C 173 productivity equations given by Wetzel and Likens (1979) were used in both cases. No adaptations were required for calculation of phytoplankton community productivity. It was necessary to convert track counts to dps-species-l-mL"1 of lake water before they could be used in the equations. Mean track counts per cell were corrected for cell size, cell- emulsion geometry, length of exposure to the emulsion, beta particle energy and latent image erasure according to Pip and Robinson (1982). Independent estimates were made of species cell abundances which were multiplied by the corrected track count to give the required units. Results and Discussion This study was conducted during the annual cooling period from August, a time of maximum surface water temperatures, until December, with minimum water temperatures (Figure 3.1). Maximum cryptophyte development occurred during this period of epilimnetic deepening as the mixed zone approached a depth of eight meters (Chapters 1 and 2). Wide fluctuations in solar radiation from frequent passage of weather fronts characterized the light climate at the lake surface during much of this period (September through December). The declining surface water temperature closely followed the seasonal decline in solar radiation. The lake mixed during the first week in November at a water column temperature of about 11.5'C. Figure 3.1. 174 Daily solar radiation (photosynthetically active radiation, 400-700 nm) (upper) and Secchi disk transparency, temperature at the two-meter depth and depth of the mixed layer (lower) in Lawrence Lake, Michigan during 1984. 175 '7; 350 1‘3 300 “.‘E 250 !i if: 20° 1 1111 11>. 01m111 1W 1 . MW H 1 1111 1. 1| I"! _ E 581111111111111111 1 11 111(111111111111111111‘“ 11‘ 11111111111111 U 1 :3" m 6‘ ‘1 - 5 ‘2 B E - 6 8- Secchi g -7 l— 1 temperature at 2 m 8 ‘ I— ‘. i t —9 depth of mixed layer 1 . 6 - t — 1o 0 O 4 5 -11 2 ‘ '. ‘. - 12 0 1 1 984 Figure 3.1 Depth, (m) 176 The summer phytoplankton volume was in decline in late July and August prior to the start of epilimnetic deepening (Figure 3.2). In September, as mixing increased below the normal summer mixed depth of about 4-meters (Figure 3.1) biomass (as chlorophyll) in the O-4-m stratum increased, probably because of upward mixing from the more densely populated metalimnion (Figure 3.3). Water clarity (as Secchi depth transparency, Figure 3.1) increased throughout the deepening period until the development of an exceptionally large ghzysggphggxgllg lgngispiga population in late October (Figure 3.2). Several sources of independent evidence indicate that the epilimnetic gnxyggsphggrgllg population represented new biomass rather than a mixing of a deeper population into the surface water: chlorophyll (Chla) concentrations increased simultaneously throughout the O-8-m stratum in October (Figure 3.3), total water-column particulate organic carbon increased (carbon data from a concurrent study by M. F. Coveney and R. G. Wetzel, in preparation), and microscopic examination of the water column showed clearly the absence of a large gnzygggphggzgllg population prior to late October. Alkaline phosphatase activity (APA), used as a relative indicator of phosphorus stress (see Chapter 1 for more details), was greatest in the metalimnion (4-8 m) until September (Figure 3.3). A precipitous decline occurred in August followed by increased activity in September. Figure 3.2. 177 Percentage volume of major phytoplankton groups in the 0-4-m stratum (upper) and phytoplankton volume (lower) in that stratum in Lawrence Lake, Michigan in 1984. The large increase in late October (lower) was nearly entirely from gnrxsgsnnaerslla- 178 - BACILLARIOPHYTA W m - CRYPTOPHYT A @ PYRRHOPHYTA m a W W - m v. C _ 2 5 1 5 o o. wowx wEwEE m23._0> ZO._.¥Z<._n_O._.>In_ 1984 Figure 3.2 179 Figure 3.3. Alkaline phosphatase activity (APA)(upper), chlorophyll a (Chla)(center) and the ratio of APA to Chla (lower) in the O-4-m and 4-8-m strata in Lawrence Lake, Michigan in 1984. 180 6 Es .m. .9 see .30 um) accounted for a variable but large portion of the phytoplankton volume (20-80%), particularly in October- November during the Chrygggpnggrglla bloom. Bhgggmgggg and Cryptgmgnag were important components of the <10 um and 10-30 pm particle size classes, respectively. The relative magnitude of their abundances and volume differed, giving each a unique role in trophic interactions of the upper stratum (Figure 3.6). Both populations developed during the autumn cooling period as they did in 1982, and together accounted for more than 90 percent of the cryptophyte volume. Bhodomonas developed a 188 Figure 3.5. Percent algal units and algal volume by size classes (upper) and total algal units and total phytoplankton volume (lower). 189 10t030um ll ...... - 30to50um <10 um ALGAL UNITS ALGAL VOLUME 100— ,, PERCENT —l 0| l0 IlllLliLlLlLllllll lllllllllLJJlL 3a -3 .m.x10 —L AUmL". x10'3 .0 0| O J'A's'o'N J'A'STO'N Figure 3.5 190 Figure 3.6. Cryptgmgnas and Bhgdgmgnag cell abundance (upper), volume (center) and the percent species volume of the total volume (lower). 191 -------. Cryptomonas A '0‘.-"-%.’ ‘\..'.s Rhodomonas ‘0' ~ I A 600 500- 400- 300- zoo... 100- O m!.qao m 100‘ 50 A WE. m5: msS.._O> ._<._.O._. ___.__________ m m m o m_2340> 4.50 45.0... "—0 FZMOmmm 1984 Figure 3.6 192 relatively large population with a maximum in the third week of October, and the Cryptgmgnag maximum occurred two weeks earlier. The larger Cryptgmgnag cells, nearly 20 times the volume of Bhgdgmgnag, were sufficient to offset the numerical advantage of Rngggmggag. As a result, Crypggmgggg made a much larger contribution to total phytoplankton volume (Figure 3.6). The October gnrygggphggzgllg bloom markedly altered the relative importance of both Cryptgmgnag and Bhgdgmgnas (Figure 3.6, bottom) to total phytoplankton volume. Cryptgmgggs was reduced from 26 to about 6 percent of the total biovolume during the bloom. Bhgggmgggg, with a maximum contribution of nine percent during the study period, was reduced to about two percent during the bloom period. Competitive interactions between Chrysgsphaerellg and cryptophytes for resources are unknown, but the pattern and magnitude of cryptophyte development was similar to that in 1982, suggesting a minor influence by Chrysosphaerella. Both cryptophyte species showed a significant seasonal variation in mean cell volume during the study (Figure 3.7). Cells were smallest during the summer, they increased in volume during autumn, and were reduced in cell volume during December and January. These seasonal variations had a direct affect on estimates of cell carbon. Culture studies with Bagggmgggg showed diel variations in cell volume on the same scale as those found in the lake 193 Figure 3.7. The seasonal variation in cell volume of Bhgdgmenee (upper) and Cryptgmgnee (lower) in Lawrence Lake, Michigan in 1984. (iS.E., n=25-30) 3 .um CELL VOLUME 3 -3 CELL VOLUME. um x 10 194 Rhodomonas 100 e 50 _. O J ' A ' s ' o a Cryptomonas 2 _. 1 _ o J ' A ' s ' o 1984 Figure 3.7 195 seasonally (W. D. Taylor, unpublished data). The diel changes resulted from synchronized cell division during the dark period which halved pre-dark period cell volume. The same phenomenon was observed in Lawrence Lake during late September, 1983. Interruptions in synchronized cell division should be expected if conditions during the daylight period are not suitable for cell growth leading to a critical size necessary for cell division during the dark period. Under these conditions larger cells would be expected in samples collected before noon, and the average cell volume of the population would increase. If this were the case, a critical overestimate of the fixed particulate carbon required for cell division was used in calculations of specific growth rates (see below). The consistent times of sampling, however, would result in consistency in the daily estimates. WWW Diel vertical migration occurred in Qaphnia and (niaptgmgg. Day-night differences in abundance are presented as light period abundance of animals expressed as a percentage of dark period abundance in various depth-strata (Figure 3.8). Migration was strongest in Qaphnia. Surface water (0-4 m) abundances of Daphnig were reduced 30 to 80 percent during the light period, while the reductions ranged from 3 to 60 percent for Diaptgmgg. When the surface water 196 Figure 3.8. Abundance of Qgpnnig spp. and Diaptomgs spp. in the light period presented as the percent of dark period abundance in various depth-strata. (data provided by M. Leibold) LIGHT PERIOD : DARK PERIOD ABUNDANCE (percent) 197 100 C] Diaptomus 0.4 m 80 — I Daphnia T r so _ F 40 _. O .. I 0-2 m Daphnia [3 2—4 m T 100 - 0 — I I I 0—2 m Diaptomus C] 2-4 m 100 - T F J 1 I JUL AUG SEP OCT 1984 Figure 3.8 198 was similarly examined as two strata (0-2 and 2-4 m) different patterns appeared (Figure 3.8). There was a greater relative decrease in abundance in the o-z-m stratum for both genera, much less so for pigptgmgg in the later part of the study. In the 2-4-m stratum, however, a small relative increase in animal abundance was observed on several dates. This increase was a one-time event for Dapnnia but it occurred on several dates with Qiaptgmgg. It seems clear that near-surface populations descended but on some occasions only small 1 net changes in abundance were observed in the 2-4-m stratum. Details of day-night paphnia gglggta mgnggtag abundance by depth-strata are presented in Figure 3.9. This species was responsible for most of the grazing pressure during this study (details below). With one exception in September, D. galggta abundance was always greater at night in the upper four meters of the water column than it was during the daylight period. At night when grazing rates were highest there was a variable and inconsistent distribution of p. gglggtg with depth. These data show that Q. gglgatg was not always uniformly dispersed within the upper water column during the dark or the light periods. As a result, the assumption that grazing was uniform throughout the mixed layer must be used with caution. Important differences in surface water (0—4 m) grazing rates existed between the dark and light periods of the day Figure 3.9. 199 Day-night 12:21:11.1: 9:12:12: mendgfae abundance by depth-strata from July through October, 1984. Eight samples from four stations were combined to form one 84-L composite sample for abundance estimates at each depth stratum. (data provided by M. Leibold.) 6-Jul 20-Jul 3—Aug 20—Aug 4-Sep 20-Sep 1 1-Oct 24-Oct DAY l I l | l l l l I 010203040010 203040 Abundance, animals per mL Figure 3.9 201 (Figure 3.10, lower). Daytime grazing rates ranged from 6 to 31 percent of those found at night. Differences like these have been attributed to vertical migration by zooplankton to greater depths and a reduction in filtration rate per individual during daylight hours (Haney and Hall 1975, Crumpton and Wetzel 1982). The light-period abundance of zooplankton in the surface water (074-m) was reduced to between 22 and 80 percent of dark period levels. Grazing was dominated throughout the 24-h day by paphnia galeata mgnggtag for both size classes of labeled algal cells (Figure 3.10). pgphgig puligaria accounted for only 3 to 4 percent of the total grazing rate. However, important day-night differences in grazing impact emerged. piaptgmus grazing became progressively more important at night for the larger particle size class (10-30 um) than it did for the smaller particle size class (<10 um) (Figure 3.10, upper). The relative importance of cyclopoids increased at night late in October after Qaphnia abundance declined. The total grazing pressure progressively decreased to very low levels towards the end of October. During daylight hours (Figure 3.10, middle) Qiaptomug and cyclopoids (on larger cells), contributed considerably more to the grazing impact than they did at night. 202 Figure 3.10. Distribution of grazing by Qgpnnia, Qiaptgmgg and cyclopoids during dark (upper) and light (middle) periods and by particle size class (<10 um, left and 10-30 pm, right) as a percentage of the total 0-4-m stratum grazing rate for the dark and light periods. Zooplankton grazing rates during dark and light periods in the 0-4-m stratum for <10 um and 10-30 pm size classes (lower). 203 SIZE CLASS < 10 um 10-30 um darkperlod 100 darkperlod JLL'AUGjSEP'OCT ightperiod liht riod uuuuuuuuuuuuuuu ooooooooooooooooooooo -------------------------- oooooooooooooooooooooooooooo nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn Percentage of Grazing Rate nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn oooooooooooooooooooooooooooooooooooo -1) Grazing Rate (period 0.7 0.. __ — daukperiod 0.5 _ ...... WM 0.4 1 0.3 - 0.2 - 0.1 - o.o Figure 3.10 204 Willi! The productivity rates of both Cryptgmgggg and Rhgggmgnag populations were low and variable, ranging from about 0.3 to 2.8 m.gC~m"3-day"'1 in the 0-4-m stratum (Figure 3.11), as compared to the entire phytoplankton community which varied from 12.7 to 58.4 mgc-m’3-day'“1 in the same period. Populations of both species fixed carbon at the highest rates in early October followed by rapid declines by turnover in early November. The Cryptgmgnas population also had higher rates in September than at other times. Such similar productivity between the two species was not expected because of the great disparity between their cell volumes and abundance (Figure 3.6). The similarity in productivity resulted partly from the combination of small cells-high abundance for Engggmggag and large cells-low abundance for Cryptgmgnag, but it resulted also from the low productivity per unit cell carbon (equivalent to specific growth rate, k) for Cryptomgnas (Table 3.3). A number of studies have demonstrated an inverse relationship between cell size and growth rate (e.g. Banse 1976, Schlesinger et al. 1981, Munawar and Munawar 1982, Rai 1982, Reynolds 1984). This relationship suggests that smaller algae can be expected to have productivity rates that are proportionally greater than their contribution to the total phytoplankton volume. In this study the opposite was observed, i.e., productivity rates for Bngggmgggg and 205 Figure 3.11. In gitg productivity of Cryptgmgngg and Rngggmgngg populations determined by nuclear track microautoradiography in Lawrence Lake, Michigan, 1984 (iS.E., n=3-8). 206 : Cryptomonas l l l I A S O N D : Rhodomonas l l l l A S O N D Figure 3.1 1 207 Table 3.3. Specific growth rate (k) and doubling time (G) for Cryptgmgggg 'grosa' (Ce), Rhodomonas miggta (Rm) and the phytoplankton community (pc) based on the ratio of carbon fixed per day to cell carbon. k (day'l) G (days) DATE Ce Rm pc Ce Rm pc 07-AUG-84 0.07 0.16 0.46 9.4 4.3 1.5 l8-AUG-84 0.08 0.13 0.58 8.4 5.1 1.2 03-SEP-84 0.13 0.21 0.44 5.4 3.3 1.6 18-SEP-84 0.12 0.14 0.44 5.8 4.9 1.6 26-SEP-84 0.09 0.08 0.35 8.0 8.4 2.0 03-0CT-84 0.05 0.16 0.55 13.1 4.2 1.3 lO-OCT-84 0.13 0.38 0.73 .5.4 1.8 0.9 l7-0CT-84 0.08 0.26 0.60 8.8 2.7 1.2 26-0CT-84 0.05 0.14 0.36 14.2 4.8 2.0 3l-OCT-84 0.03 0.09 0.18 20.9 8.0 3.8 07-Nov-84 0.02 0.08 0.29 29.6 9.2 2.4 l6-NOV-84 0.05 0.10 0.52 13.7 6.9 1.3 30-NOV-84 0.03 0.08 0.28 24.1 8.9 2.5 208 Cryptgmgnas were proportionally smaller than their contributions to total phytoplankton volume (Figure 3.12). The discrepancy was generally larger with Cryptgmgnas. The differences between the two species, as reflected in these ratios, are apparent in the specific growth rate constants which were nearly always lower for Cryptgmgnag (Figure 3.13). The range of doubling times based on these growth rates was 2-9 days for Bhgggmgngg and about 5 to 30 days for erntemenae (Table 3-3)- One method of evaluating the productivity of Cryptgmgnas and Bhgfigmgngg is to compare their carbon based specific growth rates (k) with those of the autotrophic community (Figure 3.13). Carbon was derived from cell volumes according to the equations of Strathmann (1967). Most evidence from comparative studies indicates that the 14C method measures photosynthetic rates closer to net than to gross photosynthesis (Wetzel and Likens 1979). It was assumed that net 14C fixation reflects algal particulate carbon formation (Ryther and Menzel 1965). Great differences were found between the specific growth rates of the three taxonomic entities examined. Without exception, total autotrophic community growth rates were greater than growth rates for either of the cryptophyte species alone. Growth rates generally tended to decline from August to November but in all three cases maxima developed during October. The sharp decline in growth rates 209 Figure 3.12. Ratio of Cryptomonas and Bhgdgmgnas cell volume to total phytoplankton volume and the ratio of Cryptemenae and Bhedemenae primary productivity to total phytoplankton productivity. RATIO 0.3 0.2 0.1 0.0 2 10 Cryptomonas llll llllllllljl CRYP VOL: TOTAL VOL ---- CRYPPPITOTALPP Rhodomonas 0.10 0.09 - 0.08 - 0.07 '- 0.06 - 0.05 - 0.04 - 0.03 - 0.02 - 0.01 - —— RHODVOLITOTAL VG. ---- RHODPP:TOTALPP ’O’ -.‘s.’ .-o.’ 0.00 AUG ' SEP ' oer ‘ NOV ' DEC 1 984 Figure 3.12 211 Figure 3.13. Growth rate constants (k) of Bhgggmgngg, Cryptgmgnas and the total phytoplankton community based on the ratio of carbon fixed per day to total cell carbon. Carbon was derived from cell volumes according to the equations of Strathmann (1967). There were no corrections for dark respiration. k (day") 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 212 ------- Cryptomonas community Figure 3.13 213 after mid-October coincided with the rapid deepening of the mixed zone leading to turnover in early November. Community and Bhgdgmgngg growth rates fluctuated broadly, reaching a maximum two weeks prior to the ghzygggphggrglla maximum. Cryptgmggag growth rates were quite low, averaging only 16 percent of the community growth rates, and they were less variable through time. Rhgdgmgnas growth rates were more similar to those of the community growth rates, but still averaged only 34 percent of those values. Theoretically, the specific growth rate of a species must equal or exceed the sum of all loss rates (e.g., grazing, flushing, sedimentation, cell lysis) if the population is to be maintained or to expand (Crumpton and Wetzel 1982). Loss processes have recently been emphasized for their importance in influencing algal species succession (Jassby and Goldman 1974, Kalff and Knoechel 1978, Smayda 1980, Reynolds 1984). In this study only losses resulting -from grazing activities were critically investigated. The importance of sedimentation as a loss factor varies depending largely on thermal stratification, turbulence, the physiological state of the population and the species under consideration (Livingston and Reynolds 1981, Sommer 1984). In several studies, using non-poisoned sedimentation traps, cells of cryptophytes were seldom found even though they were abundant in the water column (Reynolds 1976, Livingston and Reynolds 1981, Reynolds and Wiseman 1982, Sommer 1984). 214 Sommer (1984) concluded that cryptomonads were unaffected by sedimentary losses. As pointed out by Reynolds (1976), however, the lack of cryptophytes in traps may result from avoidance (motility), consumption by zooplankton, or death and decomposition in the immediate water column. That Bhgggmgnag and Cryptgmgngs migrate diurnally in response to light and that their direct contribution to sedimenting particulate carbon was small, was clearly demonstrated by Burns and Rosa (1980). Pedrés-Alio et al. (1987), however, successfully collected Cryptgmgnag with non-poisoned traps set in anoxic water below extremely dense metalimnetic populations. Cryptophytes lack structures resistant to decay and should not be expected to persist in an unpreserved state. In this study, living Bhgggmggag cells were observed bursting upon lysis to form nondescript bubbles which would certainly be unidentifiable if present in traps. It appears that cryptophyte motility and their demonstrated tendency for vertical migration minimizes their losses due to sedimentation except in unusual situations (e.g. Pedros-Alio et al. 1987). Flushing losses were not measured in this study but a calculation of epilimnetic flushing losses by Crumpton and Wetzel (1982), assuming that all precipitation impinging on the drainage basin went through the epilimnion, at no time indicated that losses were greater than a few percent. 215 Potential loss of cells from zooplankton grazing was evaluated for two size classes; <10 um, representative of Bhgdgmgnas and comprised almost exclusively of microflagellates (Figure 3.14) and 10-30 pm, representative of Cryptgmgnag (Figure 3.15). In each figure, carbon based growth rates (k) for Rhgggmgnag or Cryptgmonas and the entire autotrophic community are plotted along with loss rates from all grazing activity. In the lower panel of each figure are total cell volumes of the size class and the cryptophyte species of interest. Biovolume in the <10-um particle size class fluctuated with the grazing rate (Figure 3.14) until the end of October when zooplankton abundance and grazing were minimal, then the <10 um algae rapidly increased in abundance. Rhgggmggag biovolume followed the same pattern but was reduced in magnitude. It accounted for most of the biovolume in its size class only during the declining period of zooplankton grazing. By November the non-Bhgggmgngg microflagellates had recovered while Bhgggmgnag was in decline. The continuous decline in the total volume of Rhodomonas during November and December coincided with decreased growth rates. The autumnal transition period of rapid environmental changes provided conditions for opportunistic species to flourish. With decreasing surface water temperatures and increasing mixed depth, summer phytoplankton were in decline. Nutrient (phosphorus) availability improved, Figure 3.14. 216 Rhgdgmgnas specific growth rate as the ratio of carbon fixed per day (NTM) to cell carbon (volume conversion), total phytoplankton community specific growth rate as the ratio of carbon fixed per day (14C productivity) to total phytoplankton carbon (cell volume conversion), and the daily loss rate constant by zooplankton grazing on the <10um size class (as the fraction of the water filtered per day) (upper). Seasonal dynamics of Bhogomongg and particles in the <10 um size class as total volume (lower). Growth and Loss Rate Constant Total Volume 217 1.0 0.9 '— 0.8 '- 0.7 -‘ 0.6 -' 0.5 ‘- (day‘) 0.4 — 0.3 — 0.2 -' 0.1 '- 0.0 I 100 88 11 ‘10 an m a 88888 I mm- ( 10— Rhodomonas Figure 3.14 N l D Figure 3.15. 218 Cryptgmgngg specific growth rate as the ratio of carbon fixed per day (NTM) to cell carbon (volume conversion), total phytoplankton community specific growth rate as the ratio of carbon fixed per day (14C productivity) to total phytoplankton carbon (cell volume conversion), and the daily loss rate constant by zooplankton grazing on the 10-30 pm particle size class (as the fraction of the water filtered per day) (upper). Seasonal dynamics of Cryptgmgngg and particles in the 10-30 pm size class as total volume (lower). Growth and Loss Rate Constant Total Volume 219 1.0 0 9 _ """ Cryptomonas ' ''''''''' phytoplarkton community 0.8 - -- loss rate.10-30 um particles D , 665 4m— 10—30umsizeclass 3m— “2‘ m. E 3200- Cryptomonas 100- \ 0 ' A ' s ' o ' N ' D Figure 3.15 220 probably from phytoplankton cell decomposition and increased mixing of deeper hypolimnetic water. Microflagellate growth was obviously stimulated during this period. The increased zooplankton abundance and grazing may have been in response to more than the microflagellates. Non-algal particulates (bacterial and non-living organic particles) may also have been in concentrations sufficiently large to stimulate zooplankton growth and subsequently add to increased autumnal grazing rates. Preliminary estimates indicated that total pelagic bacterial cell volume was nearly constant and at levels equal to maximal cryptophyte contributions throughout the study period (M. F. Coveney, personal communication). The rapid decline in the <10 um size class during late September appears to be more directly related to grazing pressure as it coincides with maximal grazing rates (Figure 3.14). Competitive interactions between microflagellates and Chrygggpnggrgllg in late October were obscured since both developed rapidly together as grazing pressure and phosphorus limitation decreased. Grazing rates were generally higher on particles in the 10-30 pm size class than they were on <10 um size class particles. Reduction of particles in the 10-30 pm size class appears to have followed increased grazing pressure during August and September (Figure 3.15). But Cryptgmgngg, after growth in August, maintained a nearly constant volume 221 during September which suggests some kind of refuge from the grazing pressure. Specific growth rates were much lower than apparent grazing loss rates for Bhgdgmgnas until mid-October and for Cryptgmgngg until the zooplankton population was reduced to very low levels in November (Figures 3.14 & 3.15). In the most extreme case for Cryptgmgnag in September, assuming uniform distribution and no algal growth, zooplankton would reduce the 10-30 pm size-class population by one half in 1.3 days, while it would take eight days for the Cryptgmgggg population to double assuming no losses (Figure 3.15). The phytoplankton community as a whole had specific growth rates at levels greater than or equal to grazing losses for all dates except two in September (Figure 3.15). The obvious discrepancy between the high grazing loss rates and low cryptophyte growth rates requires some explanation since cryptophytes annually form a significant portion of the phytoplankton community during the autumn. Their continued presence and growth requires growth rates sufficiently high to overcome losses of all kinds or a mechanism to avoid cell death. Potential methodological errors which may contribute to the discrepancy are discussed below. Calculation of a specific growth rate is dependent upon accurate estimates of cell carbon and 14C productivity for the species. Strathmann's (1967) equations for estimating cell carbon from cell volume account for decreasing relative 222 cell carbon with increasing cell size and for differences between diatoms and other algae. Strathmann's formula has not been specifically tested for cryptophytes but it results in carbon estimates similar to independent determinations for the class (discussed in methods section). These equations are probably most applicable to cells in exponential growth phase (Smayda 1978), an event of questionable frequency in Lawrence Lake because of continual phosphorus limitation. Strathmann's equations may overestimate cryptophyte cell carbon which would lead to underestimated specific growth rates. Cryptophyte productivity was determined via nuclear track microautoradiography where several sources of potential error were possible. Microscopic observations showed more cell damage associated with sample preparation to cryptgmgnag than to Bhgdomonas. The larger cells may have been more susceptible to lysis if the acid Lugol's solution did not fix them quickly enough. Cryptophytes lack a rigid cell wall but the smaller more compact geometry of Bhgggmggag may give it a mechanical advantage over the larger Cryptgmgnag and therefore make it less susceptible to lysis under the same physical stresses. Optimally, preparations for track counting should provide cells with no more than ten tracks per cell (Knoechel and Kalff 1976). Cryptgmgngs cells with 10-20 tracks were encountered in some preparations. The 223 difficulties associated with accurately sorting overlying tracks from one another could lead to a significant underestimate of track abundance and therefore an underestimate of 14C productivity for that species. Track number per cell can be controlled, within limits, by varying any of numerous factors during field and laboratory stages of sample preparation that would effectively alter the activity associated with the cells. A common method for controlling track number is to adjust the length of time the photographic emulsion is exposed to decay events prior to development. In order to ensure proper track to cell ratios for cells of all sizes, many replicate slide preparations are required. In this study only six slides per incubation bottle could be prepared, reducing the opportunity for multiple exposure periods. The methods were optimized for Bhgdgmgnas cells which may have resulted in underestimates for Cryptomonas productivity. A recent comparison between light microscopy and scanning electron microscopy indicated that the latter enabled resolution of tracks formed by grains sufficiently small to be overlooked under light microscopy (Burkholder 1986). This comparison showed a mean of 2.8-fold more tracks per unit algal volume were counted with SEM- than with LM-autoradiography, a potential source for significant underestimates of algal productivity. Corrections for the 224 difference were not applied in this study since Burkholder (1986) was testing material labeled with 32F. The zooplankton grazing rates given here were within ranges reported in the literature, but they were frequently greater than rates reported by Crumpton and Wetzel (1982) for Lawrence Lake. They found a maximum grazing rate of about 0.41~day"1 while in this study rates were generally higher and greater than 0.5-day'1 on several occasions (Figure 3.15). The grazing rates of Crumpton and Wetzel (1982) were based on direct counts of the combined zooplankton community while in this study grazing rates were determined separately for individual species and size classes of zooplankton and then combined with independent abundance estimates to arrive at a zooplankton community grazing rate. The former approach provides a more direct estimate of total grazing impact without the uncertainty associated with numerous independent estimates of subcomponents. The advantage of the latter approach is in providing information on the distribution of grazing pressure within the zooplankton community. The trade-off is precision (Crumpton and Wetzel 1982) for detail (this study). Therefore, it is possible that grazing rates reported here are overestimates, thereby exaggerating the discrepancy between grazing rates and growth rates. Rates of algal mortality inflicted by zooplankton have been demonstrated to be species-specific (Lehman and 225 Sandgren 1985). Therefore, extrapolation of grazing rates based on labeled non-cryptophyte species to ggyptgmggag and Bhgdgmgnag may be erroneous. That cryptophytes were grazed at a lower rate than the labeled cells seems implausible given much evidence to the contrary, i.e., high nutritional value (Pejler 1977, Stemberger 1981), readily digested and assimilated (Porter 1973, Schindler 1971), apparent selective removal by Daphnia of cryptomonads from the water column (Lehman and Sandgren 1985, Vaga 1985) and the decided preference for Cryptgmgnas over Chlamyggmgnas in laboratory studies by the rotifer Eglyarthza (Gilbert and Bogdan 1984). Productivity rates for the cryptophytes were probably underestimated but they indicate that these algae were not major contributors to total phytoplankton productivity as their continual presence and contributions to the phytoplankton volume would suggest. The timing of their growth and maximal biovolume with rapid transition periods in the lake is still consistent with their suggested role as couplers (Stewart and Wetzel 1986) maintaining productivity during those times. It appears that cryptophyte populations are tightly coupled to zooplankton grazing activities in Lawrence Lake. Even so, the cryptophytes, especially Engggmgnag, maintained a significant numerical presence at all times in the lake. The continuous gngggmgngg population suggests a lower limit to cell abundance below which the 226 grazers are not efficient at harvesting the cells regardless of their measured grazing rate. There are other possible explanations for the discrepancies between grazing loss rates and cryptophyte growth rates. Cryptophytes have been shown to be auxotrophic as a result of requirements for certain vitamins. Problems associated with growing them in defined culture media were overcome only after this discovery. In addition, recent conceptual developments and expansion of theory which recognizes the importance of the microbial food loop has led to a renewal of interest in mixotrophy in pigmented flagellates (reviewed by Sanders and Porter 1988). Phagotrophy by pigmented cryptophytes has been demonstrated in several studies using a variety of particles: bacteria (Porter et al. 1985), small flagellates (Pratt and Cairns 1985) and polystyrene beads (Porter 1988). That cryptophytes are capable of using particles as a source of organic carbon has been established but its importance in the nutrition of the group is uncertain. Sanders and Porter (1988) suggest that extreme environmental conditions may be necessary to induce feeding by autotrophic cryptomonads. During this study a large bacterial biomass (equal to that of the cryptophytes) was observed (M. F. Coveney, personal communication) providing a large pool of particulate organic carbon. The relatively large autumnal cryptophyte community in Lawrence Lake had the potential for satisfying its 227 nutritional requirements phagotrophically. If this were the case, underestimates of total cryptophyte productivity using the 14C method offers a partial explanation for the results reported here. Another possible explanation for the discrepancy between grazing loss rates and cryptophyte growth rates emerges from a closer examination of the primary operational assumption of this study, i.e., uniform processes within the mixed layer of the lake. It was shown that the vertical distribution of Daphnia galeata, the primary grazer, varied inconsistently with depth at any given time as well as on a diel basis (Figure 3.9). The implication is that epilimnetic grazing impacts varied with depth at intervals of less than four meters during the day. Additionally, diel vertical migration by cryptophytes has been well documented (Sommer 1982, Salonen et al. 1984). Simultaneous differential diel migration by zooplankton and cryptophytes may result in dynamic vertical patchiness forming refuges within the epilimnion that were not apparent with the integrated sampling approach used in this study. Summary The cryptophytes increased in numbers and volume during the autumn transition period in Lawrence Lake. Their contribution to total algal volume was masked by the exceptional bloom of ghzygggphggrglla even though 228 cryptophyte volume was similar to that observed in other years. The ability of ghzyggspnggrgllg to attain maximum summer biovolume levels during the autumn indicated adequate nutrient availability at that time. Daphnia galgata mgnggtag was responsible for most of the grazing pressure in the lake. Summer grazing rates remained large until the zooplankton populations declined in October. Grazing had a negative effect on the 10-30-um size class but was positively correlated with density of the <10-um particle size class. The latter was suggestive of nutrient recycling by the grazers. The productivity rates of Cryptgmgnas and Rhodgmgnas populations were low compared to the entire phytoplankton community, but similar to each other even though great differences occurred between their cell volumes and abundances. The productivity of cryptophytes relative to total phytoplankton productivity was proportionally smaller than their contribution to total phytoplankton volume. In addition, the specific carbon based growth rates of the cryptophytes were lower than the total phytoplankton community growth rates. These findings likely reflect an underestimate of cryptophyte productivity resulting from methodological problems, but, the conclusion to be drawn from these data is that cryptophyte contributions to total phytoplankton productivity during the autumn are not as 229 great as expected from their volume contributions to the total phytoplankton community. The continued presence of cryptophytes in the lake under high grazing pressure and with low primary productivity and growth rates may have resulted from a combination of processes. Simultaneous differential diel migration by zooplankton and the cryptophytes may have created spatial patches of refuge from predation thus reducing apparent grazing losses. 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Iineatum Lindemann Peridinium sp. 1 9 2600 Peridinium sp. 2 1 37000 CRYPTOPHYTA firyptomgnas gaudata Schiller 14 470 Cryptomgnas (erosa-ovata size class) 720 1666 gnyptomonas erosa Ehrenberg gryptomonas marssonii Skuja 29 700 Cryptomonas ovata Ehrenberg Cryptomonas phaseolus Skuja 22 340 Cryptomonas rostratiformis Skuja 6 5300 getablepharis ovalis Skuja 22 66 W m__inuta var. nannopIanctica Skuja 938 67.4 CYANOPHYTA Angbgenn planktonic; Brunnthaler 19 340 Anabaena flgs-agnae (Lyngb.) De Brébisson 30 150 Anabaena inaeggalig (Kuetz.) Bornet & Flahault Anabaena sp. 8 67 Anabaenopsis gIgnkinii Miller 1 220 Apngnizomenon flos-aqnag (L.) Ralfs 1 85 'Aphanocansa-Aphanothece' 47 4.2 Aphanocapsa glachista West & West Aphanothece nigulans P. Richter CogIosphaerium paligum Lemm. 25 4.9 239 Appendix A, cont'd, Mean cell Volume TAXON N (um'3) 92212521122111 naegelianum Unger 1 31 Cnrgesossus limnetisss Lemmermann 71 69 Chroococcus preseettii Drouet & Daily Chroococsna ep- 4 261 Dastxlesessepsis smithii Chodat & Chodat 1 43 Gemshesphaeria seeping Kuetzinq 25 41 Lynsbya bergei G. M- Smith Lyngbya l1mne11_a Lemmermann Mer1smeped1a tenuissima Lemmermann 4 1.8 M19r_sy_11s.a_ruginosa Kuetzinq 50 63 912111112111 limnetiga Lemmermann 12 15 Qeeillat_ria 8p p- Radigcystis gemIngtn Skuja §p1rulina 8p- canysopnyma .B1tri_h11 _ngdntII (Reverdin) Chodat 10 155 strangling means? Doflein 3 1255 Chryseghre_ulina 21:21 Lackey 10 24 Chrxsgso_sus ep- 1 1440 Chrysesphaerella brex1§pina Korshikov gnrygggpnggrgllg s Lauterborn 36 890 gngy§_IkQ_ sknja aI (Nauwerck) Willen 3 58 D1n2bryon assuminatum Ruttner 3 121 nIngnrygn bavaricnm Imhof 5 121 Dinobryon srenulatnm W- 8 G. S West 2 83 D1nebryen 91_ergen§ Imhof 53 221 Dinobrxen sos1al var. angzi_§nnn (Brun. ) Bachmann l 84 MQIIQnQngs spp. (combined mean volume) 38 1570 Mallemonas asareides Perty em- Iwanoff MgIIgngnns Qandatg Iwanoff em. Krieger uglIgngnas grassisgnama (Asmund) Fott Mallemenas heterospina Lund Mallomenas mansefera Harris & Bradley Mallemonas tensurata Teiling em- Krieger Hallemenas tensurata var. ngIng (Pascher 8 Ruttner) Krieger Hallemonas psegdeserenata Prescott 5 1600 anromonas sp. 2 65 Benedekephyrian attenuatnm Hilliard 2 390 fininifgggngngs trioraIIs Takahashi fit1§nogleea doederleinii (Schmidle) wille 25 210 240 Appendix A, cont'd, Mean cell Volume TAXON N (um’3) Synnrn gnztIgpInn (Petersen & Hansen) Asmund fiynpra petersenii Korebikov nreglenepsis amerigana (CalkinS) Lemmermann BACILLARIOPHYCEAE Aetnanthes minutissima Kuetzing 4 94 Amp_1prera sp- AERQQIQ SP- Asterienella fermesa Hassall 50 645 stletella bedanisa var. affines Grunow 405 4986 chIoteIla cgnt a (Ehren. ) Kuetzing chIgteIIa ngneghInIang Kuetzing chIoteIla mI_nIggnIann Skvortzow 86 1546 Eyel_tell_ semen_1§ Grunow 92822112 SP- 5 7000 Eunetia Sp- Fragilaria erotenensis Kitton . 50 750 Eelssira 8p- l 690 Meridian girsplare (Grey-) 0. A- Agardh Nazisula Spp- - Nitzsshia Sp- Pinnularia sp- Stephanod1s§u§ sp- 1 13700 Sgepnanodiscus Iggrgn (Ehren.) Grunow 6 33300 Synggra acns Kuetzing Syneggn deligagIssIna W. Smith Synggra nIng (Nitzsch) Ehrenberg fiynedrn (large) 8 18300 Syngggn (medium) ‘ 24 4760 Synggzn (small) 4 1240 §y_gg;n (very small) 26 360 Tabellar1a fen_strata (Lyng- ) Kuetzing CHLOROPHYTA Ankistredesmus falsatus (Corda) ralfs 9 112 Anki_tredesmss f_lee_us var. QQIQQI§L1_ (A. Braun) G. S. West Betryosossus .111111 Kuetzinq 10 56 QQIEQIIQ SP- 1 394 QhIamygomongs sp 3 154 QIQ§_gIInn grngIIg De Brébisson 2 9380 Cesmarium Sp- 5 9530 241 Appendix A, cont'd, Mean cell Volume TAXON N (um-3) grueigenia rectangularis (A. Braun) Gay 30 226 Desmidium 8p- 1 16689 Elakatetnrir gelatinesa Wille n_phr_sytium _sardhiannn Naegeli 10 212 Nephr_sytiem limneti_um G. H. Smith Heugeetia 8p- 7 2103 Qegystis submarine Lagerheim 6 120 QggyggIg sp. 1 12 600 Q_Qy§§I§ sp. 2 5 3820 Easiestrum b_ryannm (Turp- ) Meneqhini 1 493 Eediastrum duplex Meyen EIgn_thgma IautgrbornI Schmidle 25 33 Quadrigula lassstris (Chod ) G- M- Smith 10 56 So nro ogdnga sgtIgera (Schroeder) Lemmermann 6 76 Sggngdggmng abnndgns (Kirch.) Chodat 1 38 Sphaeresystis sehreeteri Chodat 26 69 Staurastrum Sp- Tetraédron minimum (A- Braun) Hansqirg 1 44 Tetraédron pentaedrieum West 6 West 1 109 EUGLENPHYTA EngIgnn sp. 14 34200 Enngng pyznn (Ehrenberg) Stein Trashelemonaa 8p- 12 600 MISCELLANEOUS microflagellates size class no. 1 size class no. 2 size class no. 3 (<3 um dia) (3-6 pm dia) (6-10 pm dia) 242 Appendix B. Abundance of Engggngnng nInngg and 'gzggn' in Lawrence Lake from August 1982 cryptomonas until August 1983. cam-1W ____Bhedemonas___ ...erptemonas___ Date 0-4 4-3 3-12 0-4 4-3 3-12 08/06/82 102 139 63 17 74 51 03/07/32 173 204 52 30 51 34 03/09/32 134 234 141 23 62 49 03/11/32 209 186 33 21 54 31 03/13/32 112 196 53 35 63 35 03/15/32 186 149 53 24 31 34 03/17/32 133 117 13 59 03/19/32 193 145 71 - 25 47 37 03/21/32 150 249 37 23 63 26 03/23/32 170 221 43 27 33 29 03/25/32 166 162 124 20 43 29 03/27/32 171 146 55 16 36 36 03/29/32 165 146 109 20 23 19 03/31/32 130 36 33 43 09/02/32 143 142 104 23 34 50 09/04/32 36 37 40 22 43 30 09/06/82 257 146 93 65 34 46 09/03/32 125 173 70 45 49 20 09/10/32 135 123 132 47 63 51 09/12/32 120 124 33 43 43 46 09/14/32 295 161 35 73 09/16/32 260 170 76 77 75 55 09/13/32 130 137 134 75 71 47 09/20/32 154 145 145 52 65 54 09/22/32 225 143 121 51 60 33 09/24/32 130 122 103 34 39 31 09/26/32 159 102 144 54 47 51 09/23/32 110 115 43 33 09/30/32 95 140 105 34 27 41 10/01/32 103 155 154 . 39 66 42 10/02/32 127 151 157 33 63 53 10/03/32 153 196 145 40 59 33 10/04/32 219 222 200 54 53 55 10/05/32 232 265 226 50 60 23 10/06/82 337 326 236 90 63 63 10/07/32 373 377 379 45 91 45 10/03/32 363 377 359 70 64 62 10/09/32 436 357 350 73 79 99 10/10/82 328 490 322 75 47 53 Appendix B, cont'd, 243 99113131'1.92.31:3§03.130______ ____Bh2d9mgna§___. ___Q;xntgmgue§__ Date 0-4 4-3 3-12 0-4 4-3 3-12 10/11/32 439 344 462 63 63 63 10/12/32 544 343 345 120 100 10/13/32 331 424 290 31 55 39 10/14/32 373 433 279 33 33 51 10/15/32 341 392 322 73 77 39 10/16/32 273 317 377 74 72 33 10/17/32 236 233 206 64 53 53 10/13/32 263 255 233 62 63 66 10/19/32 253 301 293 30 72 33 10/20/32 254 307 213 30 71 61 10/21/32 319 300 273 73 65 69 10/22/32 242 332 234 91 56 74 10/23/32 255 231 334 72 50 63 10/24/32 256 273 261 53 75 55 10/25/32 259 223 229 33 121 55 10/26/32 215 247 57 56 10/27/32 273 222 230 53 32 26 10/23/32 233 213 210 79 77 63 10/29/32 239 203 252 69 30 53 10/30/32 219 239 210 67 53 32 10/31/32 235 234 230 93 53 59 11/01/32 275 214 253 109 47 42 11/03/32 243 271 257 95 55 42 11/05/32 191 230 137 56 66 56 11/06/32 207 223 193 50 53 67 11/07/32 134 242 203 53 41 57 11/09/32 176 175 49 39 11/11/32 240 273 232 67 65 11/12/32 222 223 231 63 52 50 11/13/32 179 215 207 45 55 44 11/15/32 131 132 157 30 33 43 11/17/32 191 194 137 31 46 46 11/19/32 134 131 209 46 47 39 11/21/32 249 265 205 34 31 19 11/22/32 222 239 210 35 33 26 11/23/32 227 230 34 24 11/25/32 219 200 207 43 35 21 11/27/32 173 173 137 31 21 36 11/29/32 155 211 204 34 30 36 12/01/32 130 152 174 32 20 23 12/03/32 211 131 154 23 27 26 244 Appendix B, cont'd, ____Bh9d9m2na§__. __Q:12§2mgna§___ Date 0-4 4-3 3-12 0—4 4-3 3-12 12/05/32 217 131 136 30 27 34 12/07/32 172 160 ‘ 35 43 12/09/32 174 133 140 32 24 30 12/11/32 131 232 176 27 23 27 12/13/32 151 135 170 25 24 26 12/15/32 132 261 223 23 31 31 12/16/32 214 23 12/17/32 143 172 203 31 13 31 12/13/32 241 30 12/19/32 223 136 169 13 19 15 12/21/32 267 239 20 22 12/22/32 317 20 12/23/32 324 135 272 31 19 23 12/24/32 225 20 12/25/32 273 273 230 33 13 15 12/27/32 253 220 234 20 24 16 12/29/32 214 199 243 14 14 26 12/31/32 233 236 251 14 19 27 01/02/33 205 193 134 13 20 15 01/04/33 242 213 17 11 01/06/33 305 273 234 17 12 23 01/03/33 196 165 171 10 15 17 01/10/33 175 145 111 14 15 16 01/12/33 234 237 160 - 6 7 12 01/14/33 271 254 223 16 11 9 01/16/33 193 214 145 4 12 10 01/13/33 252 202 10 20 01/20/33 199 240 199 6 11 6 01/22/33 173 204 222 9 12 10 01/24/33 276 197 155 14 13 7 01/26/33 334 234 267 4 15 15 01/23/33 133 231 273 6 3 10 01/30/33 233 227 263 13 5 4 02/01/33 417 437 9 20 02/03/33 329 303 303 20 17 9 02/05/33 340 456 339 6 11 4 02/07/33 339 232 273 11 11 11 02/09/33 430 332 305 16 11 6 02/11/33 316 241 192 6 7 4 02/13/33 267 253 215 3 12 13 02/15/33 244 221 3 7 245 Appendix B, cont'd, C91151mL'¥_px_§tratum_imi_______ ____Bhgdgm2na§__. Cryptomgna§__. Date 0-4 4-3 3-12 0-4 4-3 3-12 02/17/33 147 136 171 2 9 5 02/19/33 237 216 213 4 5 6 02/21/33 219 191 131 3 2 11 02/23/33 302 291 303 7 0 3 02/25/33 371 233 333 15 7 12 02/27/33 324 223 261 2 12 13 03/01/33 150 233 5 10 03/03/33 216 233 275 5 3 4 03/04/33 332 265 239 9 13 6 03/06/33 263 261 235 4 3 13 03/07/33 253 339 273 6 14 10 03/09/33 336 456 395 15 16 24 03/11/33 424 433 473 11 17 6 03/13/33 333 336 364 5 5 9 03/15/33 309 370 3 17 03/17/33 307 375 395 6 7 12 03/19/33 333 455 360 4 7 3 03/21/33 333 340 431 17 13 15 03/23/33 273 322 305 13 17 9 03/25/33 291 290 195 11 13 6 03/27/33 273 317 333 3 2 6 03/29/33 279 195 14 6 03/31/33 207 223 261 9 10 7 04/02/33 237 232 205 4 7 6 04/04/33 196 223 137 7 6 4 04/06/33 169 213 224 10 6 5 04/03/33 130 34 149 1 5 4 04/10/33 125 149 174 11 7 6 04/12/33 127 131 5 7 04/14/33 33 103 102 5 3 04/16/33 39 126 131 6 3 4 04/13/33 125 39 120 4 7 04/20/33 39 91 33 5 1 4 04/22/33 74 115 122 6 2 5 04/24/33 37 142 113 4 6 10 04/26/33 52 97 9 2 04/23/33 96 147 171 4 3 9 04/30/33 145 151 173 15 7 11 05/02/33 155 122 120 10 4 13 05/04/33 136 175 113 21 13 11 05/06/33 262 134 157 7 6 7 246 Appendix B, cont'd, Cell§;mL'1_hx_§t:atum_imi_______ ____Bh2d9m2na§___ ___§£22tgmgna§___ Date 0-4 4-3 3-12 0-4 4-3 3-12 05/03/33 212 243 134 13 13 14 05/10/33 129 220 19 10 05/12/33 292 272 219 23 16 9 05/14/33 279 223 163 22 5 6 05/16/33 277 250 139 26 20 12 05/13/33 216 133 216 23 17 21 05/20/33 250 176 219 19 12 17 05/22/33 327 222 155 20 9 13 05/24/33 226 245 12 23 05/26/33 275 246 179 14 27 13 05/23/33 164 153 152 13 20 13 05/30/33 316 152 131 - 31 17 13 06/01/33 213 169 112 41 13 17 06/03/33 195 71 49 41 13 11 06/05/33 135 176 170 42 37 41 06/07/33 231 151 55 62 06/09/33 220 157 140 51 45 63 06/11/33 192 154 142 100 53 50 06/13/33 133 76 93 32 53 57 06/15/33 144 123 115 99 116 53 06/17/33 152 144 123 30 75 79 06/19/33 164 136 107 36 33 71 06/21/33 165 121 54 67 06/23/33 122 116 72 92 74 33 06/25/33 133 141 112 59 64 39 06/27/33 173 167 136 30 93 60 06/29/33 233 173 33 123 35 44 07/01/33 167 171 91 33 97 41 07/03/33 161 195 113 67 92 50 07/05/33 213 213 123 119 07/07/33 207 231 31 93 141 43 07/09/33 164 171 112 112 113 54 07/11/33 123 232 156 66 125 73 07/13/33 102 157 121 . 57 149 63 07/14/33 97 179 96 53 109 67 07/15/33 214 203 170 63 93 73 07/17/33 99 161 129 56 102 64 07/19/33 105 137 42 54 07/21/33 156 150 37 32 53 39 07/23/33 125 105 77 19 40 24 07/25/33 105 143 39 26 26 22 07/27/33 143 115 119 23 19 23 247 Appendix B, cont'd, CellgemL'1_Qx_§§;atum_imi______ ____Bn9d2mgna§___ ' __szp£2mgne§____ Date 0-4 4-3 3-12 0—4 4-3 3-12 07/29/33 37 91 77 23 33 23 07/31/33 115 124 74 23 37 19 03/02/33 123 140 29 33 03/04/33 224 213 155 43 53 30 03/06/33 237 322 236 33 74 34 03/03/33 194 310 133 32 75 30 03/10/33 133 356 293 23 30 59 03/12/33 124 264 337 39 51 23 03/14/33 149 210 154 35 53 22 03/16/33 231 263 37 51 “Wilifli'ifll'jflfiflflfii'fl'fliflwflfliflfiflr