PRIMARY PHOTOSYNTHETIC PRODUCTIVITY OF TWO MICHIGAN PONDS Thesis for the Degree of M. S. MICHIGAN STATE UNIVERSITY IOHN R. GEHRING 1969 T [III/1W {WW L 5 8509 m LIBRA R Y Michigan @1- '3 UnivcmW PLACE IN RETURN BOX to remove this checkout from your record. TO AVOID FINES return on or before date due. DATE DUE DATE DUE DATE DUE U-‘ a—-— - R h mew—41113 Wm .45“: my 3-, ‘ MSU Is An Affirmative Action/Equal Opportunity Institution cMIMmHt ABSTRACT PRIMARY PHOTOSYNTHETIC PRODUCTIVITY OF TWO MICHIGAN PONDS BY John Rowland Gehring The primary photosynthetic productivity of two ponds was studied. Two methods of estimating the productivities of the ponds were employed. First the changes in the dis- solved oxygen content of the waters were monitored and the resulting data converted to productivity values in terms of gm. cal./m2/day. Secondly, the three groups of primary producers, plankton, macrophytes, and periphyton, were sampled periodically to determine their role in the total photosynthetic production of each pond. There existed a close relationship between the light intensity and the rate of primary production. Periods of cloudiness brought about a drop in the primary production while periods of higher light intensities resulted in an increase in the productivity of the ponds. The efficiency with which the photosynthetic organisms fixed solar energy was found to decrease with increasing light intensities up to a saturation level of light intensity. John Rowland Gehring In both ponds primary production slightly exceeded community respiration, thereby classifying them as auto- trophic communities. A probable relationship existed between macrophyte and periphyton growth with the former inhibiting the growth of the latter by means of nutrient limitations or direct inhibiting action. PRIMARY PHOTOSYNTHETIC PRODUCTIVITY OF TWO MICHIGAN PONDS By "\ John R1 Gehring A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE Department of Fisheries and Wildlife 1969 ewe/7 31/ x- 70 ACKNOWLEDGMENTS I wish to express my sincere appreciation to Dr. Robert C. Ball for the opportunity given me to pur- sue this advanced study and for the patience and guidance he has afforded throughout its duration. I also wish to express my thanks to fellow graduate student Jack Bails for his help in initiation of the study and to Danny Jackson for his help with taxanomic problems. ii TABLE OF CONTENTS INTRODUCTION . . . . . . . . . . . LITERATURE REVIEW . . . . . . . . Oxygen . . . . . . . . . . . Periphyton . . . . . . . . . Macrophytes . . . . . . . . . Plankton . . . . . . . . . . DESCRIPTION OF STUDY AREA . . . . TECHNIQUES AND EQUIPMENT . . . . . Physical Measurements . . . . Oxygen Monitoring System Solar Energy Measurement Water Temperature . . . Gravimetric Measurements Calorimetry . . . . . . Biological Measurements . . . Periphyton . . . . . . . Algae Identification . . Macrophytes . . . . . . Plankton . . . . . . . . PRIMARY PRODUCTION . . . . . . . . RESULTS AND DISCUSSION . . . . . . Diurnal Oxygen Curves . . . . Gross Primary Productivity . . Productivity The Role of Light, Primary Efficiency . . . . . . . P/R Ratios . . . . . . . PERIPHYTON PRODUCTIVITY . . . . . MACROPHYTE PRODUCTIVITY . . . . . iii Page (0030101 N |—‘ 11 15 15 15 16 16 16 17 17 17 20 20 21 22 25 25 23 SO 55 57 41 59 TABLE OF CONTENTS-—continued Page PHYTOPLANKTON PRODUCTIVITY . . . . . . . . . . . . . 65 SUMMARY . . . . . . . . . . . . . . . . . . . . . . 68 LITERATURE CITED . . . . . . . . . . . . . . . . . . 70 APPENDIX . . . . . . . . . . . . . . . . . . . . . . 76 iv LIST OF TABLES Table 1. Productivity estimates of ponds and other small aquatic habitats. . . . . . . . . . . . Paired t-test of the productivities of ponds B and D during the first thirty-one days of study. . . . . . . . . . . . . . . . . . . . Paired t-test of the productivities of ponds B and D during the second thirty-one days of study. . . . . . . . . . . . . . . . . . . . Efficiency of solar energy utilization for various aquatic habitats. . . . . . . . . . . The genera of algae found in the periphyton community of the Lake City ponds. . . . . . . Net primary periphyton productivity of ponds B and D. . . . . . . . . . . . . . . . . . . Percent efficiency of utilization of photosyn- thetically active solar energy by pond peri- phyton communities. . . . . . . . . . . . . . Net primary productivity and percent effici- ency of utilization of photosynthetically active solar energy of pond macrOphytes. . . Page 27 28 29 54 42 54 55 64 LIST OF FIGURES Figure 1. A map of the Lake City ExPerimental ponds. . . 2. The net photosynthetic productivity of the test ponds during the summer of 1965. . . . . 3. The changes in solar radiation and dissolved oxygen concentrations in pond D, August 8, 1965. O O O 0 O O O O O O O O O O O O O O O O 4. The efficiency values for ponds B and D during the summer of 1965. . . . . . . . . . . . . . 5. The relationship between efficiency and inci— dent solar radiation in pond B during the summer of 1965. . . . . . . . . . . . . . . . 6. The relationship between phytOpigment units and organic weight. Ninety-five percent con- fidence limits for Y (mean estimates) are BC and for individual estimates AD. . . . . . . . 7. The phytopigment-organic weight regression for the Lake City ponds, line AB, for the Red Cedar river (Grzenda, 1960), line CD. . . . . 8. A representative growth curve of periphyton accumulating on artificial substrates in a Lake City test pond during the summer of 1965. 9. The efficiency of periphyton communities B and D in transferring photosynthetically active solar energy into organic matter. . . . . . . 10. The rates of net production and biomass accumu- lation of the aquatic macrOphytes in ponds B and D O O O O O O O O O O O O O O O O O O I I 0 vi Page 14 25 52 56 45 48 52 57 62 INTRODUCTION The problem of determining the primary productivity of aquatic ecosystems has been foremost in the minds of many aquatic biologists. Although scientific investiga- tion into this field of aquatic biology has only relatively recently begun a considerable amount of data has been accumulated and new techniques have been developed. The study of primary productivity in ponds has not received the attention of investigators as have some of the other aquatic habitats such as the open seas. The primary objectives of this investigation were to measure the primary productivity of two ponds by imple- menting two techniques, one of which is relatively new and the other being somewhat older. The former method, that of measuring the dissolved oxygen content of the water over a period of time, will give an index of the total primary productivity of the ponds and the latter method, that of sampling the standing crOps of primary producers will identify which groups of primary producers are the dominant ones. Environmental factors were also investigated and their effect upon primary productivity determined. LITERATURE REVIEW Energy fixation and transfer in an aquatic ecosystem is complex and difficult to quantify. The study of the first step in the bio-energetic cycle involving fixation of solar energy by attached algae (periphyton), planktonic algae, and higher aquatic plants (macrophytes) is a some- what less formidable task. Saijo and Ichimura (1961) credit Thieneman as being the first modern author to attempt a critical assessment of the concept of primary biological productivity. He de- fined primary production as the total amount of organic matter produced in a given Space during a given period. According to Saijo and Ichimura (92, gig.) Lohmann made one of the first attempts to estimate primary produc- tion by noting changes in a standing cr0p, taking into account rates of reproduction and the effects of grazing. .This method was followed by many well—known limnologists in the 1940's such as Juday and Lindemann, who studied energy flow through producer and consumer levels of the aquatic ecosystem. The majority of research conducted with small ponds has been designed to measure various physical and chemical parameters. Changes in these parameters have been associ- ated with changes in biological activity; however, rela- tively few attempts were made until recent years to quantify the results. Birge and Juday (1914) observed that heavy concentra- tions of photosynthetic organisms produced a substantial increase in the pH of the water; however, no effort was made to calculate productivity on the basis of this change in alkalinity. Phillip (1927) observed pH fluctuations in a lake thought to be caused by vegetation in the water, but again no attempt was made to calculate photosynthetic productivity. Oxygen Calculation of photosynthetic rates from changes in the oxygen content of waters followed the use of changes in pH and carbon dioxide by several years. The original idea of estimating production from the photosynthetic rate of phytOplankton was first introduced by Gaarder and Gran (1927). The light and dark bottle method which they used, though usually giving overesti— mates of gross production, has been widely employed by researchers. Wiebe (1951) recorded data which showed a daily in- crease from 1.66 ppm. oxygen to 16.9 ppm. oxygen and believed that the increases were roughly prOportional to the amount of algae present. Whitney (1942) measured pH and oxygen changes in small ponds and a stream and prOposed that these fluctuations were dependent Upon photosynthetic and respiratory activity of the aquatic organisms. The use of diurnal oxygen pulses to determine the rates of primary or photosynthetic productivity became widespread after publication of work by Odum (1956). He outlined a method whereby diurnal oxygen curves could be analyzed and the component rates of production, respiration and diffusion, determined. Ryther (1956), Verduin (1956), Odum and Hoskin (1957), Odum and Hoskin (1958), Odum and Wilson (1962), and Duffer and Dorris (1966) are a few of those who have refined techniques and added to the data already accumulated. Saijo and Ichimura (1961) review various techniques for measuring primary production in both fresh and salt waters. Doty (1961) gives a bibliography of articles pertinent to primary production in both fresh and salt water. The majority of research dealing with productivity in ponds has been directed at estimating fish growth and re- lated t0pics of fish management. More recently, however, researchers have made an attempt to estimate the rates of primary production in ponds and other smaller bbdies of water. C0peland and Whitworth (1965) and Butler (1964) both used diurnal oxygen curves to measure the primary productiv- ity of two different sets of Oklahoma farm ponds. Knight, Ball and Hooper (1962) estimated the primary production of the three groups of primary producers--plankton, periphyton, and macrOphytes—-in four Michigan ponds. .Manual sampling and testing of various parameters such as oxygen concentrations are very time consuming and im- possible to maintain on an around the clock basis. What was needed was a robot-monitor device. One of the first robot monitors was the original conception of Edward J. Cleary (1967) of the Ohio River Valley Water Sanitation Commission. .His investigations were begun in.1956 and by 1960 a monitor designed to measure ten different water quality character- istics was placed in operation on the Ohio river. Avail- ability of such monitoring devices will undoubtedly be a tremendous aid to the production biologist of the future. Periphyton Periphyton is defined by Odum (1955) as: "organisms both plant and animal attached or clinging to stems and leaves of rooted plants or other surfaces projecting above the bottom.” In shallow ponds such as the ones used in this study the littoral zone extends to all depths. Aquatic habitats, within which the littoral zone is all encompassing frequently possess periphyton communities that play a very important role as primary producers (Wetzel, 1964). Cooke (1956) credits a 1915 Swedish publication as giv- ing the first description of a specific technique whereby artificial substrates could be introduced into the water for the collection of aquatic organisms. The majority of the papers written that incorporated the artificial substrate method were primarily concerned with taxonomy studies and surveys of various aquatic com- munities (Bissonnette, 1950). Ecological studies were also undertaken to determine the distribution of various algal and other life forms using the artificial substrate as a collection device (Miller, 1956). Extensive reviews of studies conducted that made use of artificial substrates as a collection device have been compiled by Cooke (1956) and Sladecokova (1962). One of the first researchers that used artificial sub- strates in estimating productivity was Newcomb (1949). He reported that the organic matter collected from vertically and horizontally placed substrates was in the ratio of 1 to 6.6 respectively. In view of these findings, Newcomb (1950) stated that horizontal placement of substrates ap- peared to be the most advantageous. .Newcomb (1949) noted that most of the evidence tended to indicate that the growth forms present on the glass artificial substrates were repre- sentative of those occurring on the natural substrates such as aquatic plants and detritus. The relationship between chlorophyll concentrations and photosynthetic productivity led early workers, especially marine researchers, to develop methods of phyto- pigment extraction. Kreps and Verjbinskaya (1950) were among the first to develOp a suitable technique. They were later followed by Harvey (1954) and Manning and Juday (1941) whose works further soPhisticated phytopigment extraction methods and, in the case of Manning and Juday (1941), applied these methods towards the estimation of primary pro- ductivity. The application of the artificial substrate method to determining periphyton productivity is dependent Upon the ability of the worker to quantitatively assess the amount of organic matter accumulated on the substrate. Numerous methods have been employed. Direct microscopic observations and counting of the material collected has been widely used in the past. When dense growths of periphyton make direct observations impossible, the growth has been scraped from the substrate and various volume and weight measurements have been made. More recently, however, the use of phytoPigment extracts have been employed to estimate the amounts of periphyton growing on artificial substrates. Grzenda and Brehmer (1960) credit HOOper, Ball, and Hayne with being the first to estimate periphyton production by combining the artificial substrate and phytopigment extraction methods. Grzenda and Brehmer (1960) found that a linear relationship existed be— tween a given number of phytopigment units and the organic weight of the periphyton from which the phytopigments were extracted. It was found that one regression was capable of making year-round predictions of organic periphyton weight from chlorophyll absorbency readings. This technique represents a significant advancement which enabled succeed- ing workers to more rapidly assess periphyton productivity. The problem of determining what portion of the periphy- ton growth curve on artificial substrates most precisely represents that growth which occurs on natural substrates is discussed in a paper by Kevern, Wilhm and Van Dyne (1966). They discuss a method whereby measurement of the standing cr0p of periphyton over a period of time provides an instantaneous growth rate which is comparable to the growth of periphyton actually taking place on the natural sub- strates. Macrophytes The initial research, dealing with higher aquatic plants in America, is credited by Pieters (1894) to Profes- sor Douglas Campbell who conducted a study of aquatic plant distribution in the Detroit river. Pieters (1894) also sampled aquatic plants in the Detroit River by pulling a drag with a sailboat which scooped plants from the river bottom. Denniston (1922) worked with higher aquatic plants in Lake Mendota but also confined his work, as did the majority of his contemporaries, to taxonomic surveys and distribution studies. Rickett (1920) was one of the first to make a quanti- tative survey of higher aquatic flora. Working on Lake Mendota he estimated the total standing crop of various higher aquatic species. Primary productivity estimates of higher aquatic plants have only been made during the recent past. Penfound (1956) measured the productivity of some larger aquatic plants and compared their productivities with those of other plant forms in other ecosystems. Odum (1957), Smally (1959), Knight, Ball, and Hooper (1962), and Vannote (1964) are a few of those who have contributed much needed data on the productivity of different species of aquatic plants in a wide variety of aquatic habitats. Plankton Planktonic organisms have long been studied from a taxonomic aspect. Birge and Juday (1922) credit Hensen's work of 1882 as being the first involving plankton to be of a quantitative nature. Birge and Juday (1922) conducted extensive research on the planktonic organisms of several Wisconsin lakes. Their work, being quantitative in substance, enabled them to assess the primary productivity of the planktonic community. Many other workers such as Riley (1959) contributed more data and refined techniques developed by Birge and Juday. 10 The majority of these early workers measured the stand- ing crop of planktonic organisms and then estimated the rate of p0pulation turnover before computing productivity indices. More recently attempts by such workers as Manning and Juday (1941) have been made to utilize the chlorophyll content of water as an index of phytoplankton productivity. -The most convenient and reliable method for the estimation of phytOplankton productivity has proven to be the carbon-14 method introduced by Steeman-Nielson (1952). DESCRIPTION OF STUDY AREA This project was conducted at the Lake City Experi- mental Station which is located in the west central area of Missaukee County two miles south of Lake City, Michigan. The station is owned by Michigan State University, and here research projects are conducted by the College of Agriculture. The area for study consisted of four experimental ponds which were constructed near the headwaters of Mosquito Creek. A dam, located west of the ponds on the stream,. forms a six and one-half acre reservoir which is used for filling the ponds. Each pond has a separate inlet and out- let and can be filled and drained independently into the creek which flows below and behind the ponds. The ponds were excavated in an area of sandy soil. However, since their formation (1945-1945), their bottoms have become covered with several inches of small twigs, mud, and detritus. The land surrounding the ponds is flat and covered with grass which holds surface runoff to a minimum. The ponds are designated alphabetically A, B, C, D from west to east. The ponds used in this study are B 11 12 and D. Both ponds have an average depth of one meter. Pond B has an area of 0.45 acres and pond D an area of 0.18 acres. Figure 1 shows the positioning of the ponds and labora- tory areas. 15 .mccom HmucmEfiHmmxw mufiu mxmq may no mmE m .a musmflm 14 a wusmflm mm_mOhfluooponm Uwumnucwmouonm mmoum one .N whomflm 25 POND D POND B 25' '1 o; I I I f I f I In 9 n N v- Q h Rep zD/Qo'wg uogsonpold 1d I I I 0 In Q ‘thgld I I M N 55019 15 20 25 30 10 15 AUG. SEPI 10 30 15 20 JULY 10 Figure 2 26 are shown in Table I. Reference to Table I shows that the val- ues of gross primary productivity for the Lake City ponds are in general agreement with values reported by other authors. InSpection of Figure 1 indicates that there is a marked difference in the productivity of the two ponds dur- ing the beginning of the study period. The data revealed that the productivity of pond B was significantly greater than that of pond D as determined by a paired t-test of the productivity estimates for the first thirty-one days of the investigation (Table II). It is most probable that this difference in productivity was partially due to the removal of the higher aquatic plants (macrophytes) from pond D prior to the initiation of the study. Draining of the test pond would severely deplete the periphyton p0pula- tion which would also in turn contribute to the low pro- ductivity values observed in pond D. The data also revealed that there was no significant difference between the productivity of the two ponds as determined by a paired t-test of the productivity estimates for the second thirty-one days of the study period (Table III). By the second month of study lush growths of higher aquatic plants, primarily thgg, had established themselves to an extensive extent over the bottom of pond D. The periphyton growth had also recovered from the initial drain— ing and was now clinging to most of the available substrates. 27 TABLE I PRODUCTIVITY ESTIMATES OF PONDS AND OTHER SMALL AQUATIC HABITATS Author Year . Habitat PrOductivity gm.02/m2/day Butler 1964 Pond 2.4 - 16.1 Copeland and Whitworth 1965 Pond 4.4 - 27.4 Odum and Hoskin 1958 Tank 1.16 Copeland and Dorris 1962 Polluted Pond 25.4 Copeland, Butler and 1961 Pond 1.1 - 7.5 Shelton Hepher 1962 Pond 4.4 - 22.6 Minter and Copeland 1962 Pond 0.0 - 5.9 28 TABLE II PAIRED t-TEST OF THE PRODUCTIVITIES OF PONDS B AND D DURING THE FIRST THIRTY-ONE DAYS OF STUDY N = 51 2d = 48.01 2d2 = 114.79 (2d)2 = 2504.96 52d = 1.54 32 = 0.045 3' s_ = 0.205 23' = 1.54 d t = 7.55* *Significantly different at the 0.05 level (d.f. = 50). 29 TABLE III PAIRED t-TEST OF THE PRODUCTIVITIES OF PONDS B AND D DURING THE SECOND THIRTY-ONE DAYS OF STUDY N = 51 2d = 5.07 252 = 67.59 (2d)2 = 56.84 92d = 2.21 92_ = 0.712 d s__= 0.845 E'= 0.19 d t = 0.22* * Not significantly different at the0.50 level (d.f. = 50). 50 The noticeable increase in the abundance of these two im- portant groups of primary producers most probably accounts for the increase in productivity of pond D during the second thirty-one days of measurement. The Role of Light, Primaryggroductivity A close correspondence between light intensities and variations in primary productivity has been noted by several authors. Odum and Hoskin (1958) present diurnal oxygen curves which indicate that decreasing light intensities caused by cloud cover cause a decrease in the photosynthe- tic rate of the aquatic primary producers. Odum and Wilson (1962) state that diurnal oxygen curves have the same general hump shape as that of the incident solar radiation. A diurnal oxygen curve is also presented which shows a sharp drop in the dissolved oxygen accompanying the passage of a cold frontal squall line. Observations similar to the above were made during the course Of this study. Figure 5 shows a diurnal oxygen curve for pond D and below it the corresponding graphic representation of the solar radiation levels occurring in the vicinity of the Lake City ExPeriment Station. Inspec- tion of Figure 5 shows that the rises and falls in solar radiation intensity are remarkably reflected in correspond* ing rises and falls in the dissolved oxygen concentration of pond D. 51 .mmma .m umoms¢ .n Ocom OH OOOHDMHDOOUGOU cwm%xo O0>Hommwp can cofiumfipmu HOHOm CH mmmcmnu 058 .m musmflh 52 m onsmwm 15o .o oar? m o n m m _ coozmfi "S o" .zdm P It’- - n h n p P b a o m m a _ .5522 Z 2 53 p b h n b b n F b P JElOS 00!"!938 h Jun/1m ueflxo panossga 55 Efficiency The efficiency of the primary producers in converting solar energy into chemical energy was calculated from gross oxygen production and solar radiation data. During the computation of efficiencies it was assumed that there was an approximate conversion of 4 kg. cal./gm. of oXygen metabolized (Odum and Wilson, 1962). It was also assumed that approximately fifty percent of the incident solar radiation was available at the surface for photosynthesis (Edmondson, 1955; Forsythe, 1954; and List, 1951). Table IV lists several efficiencies reported for a diverse range of aquatic habitats. The efficiency of solar energy utilization in pond B ranged between 0.5 and 2.1% with a mean efficiency of 0.7%. The efficiency of pond D ranged from 0.1 to 1.61% with a mean efficiency of 0.6%. The efficiencies observed in the test ponds generally corres- pond with those values reported by the more recent studies of similar habitats. Figure 4 illustrates the efficiencies observed in both ponds for the entire testing period. As one would expect, noting the method for calculation of efficiencies, pond B is clearly more efficient for the first nineteen days of study. From this time until the end of the test period the efficiencies of the two ponds come closer to approximating each other. The probable reason for the observed differ- ences in the efficiency levels would be similar to that EFFICIENCY OF SOLAR ENERGY UTILIZATION FOR VARIOUS AQUATIC HABITATS TABLE.IV Author Year 'Habitat Percent Efficiency Druffer and Dorris 1966 River 0.1 - 2.7 Odum 1957 Spring 4.0 Odum and Wilson 1962 Sewage Lagoon 6.0 Odum and Hoskin 1957 Microcosm 1.0 - 8.0 Butler 1964 Pond 0.2 — 1.8 Kohn 1956 Coral Reef 1.1 Clarke 1959 Lake 0.04 - 0.5 Juday 1940 Lake 0.40 Lindeman 1942 Bog Lake 0.10 Dineen 1955 Pond 0.04 Teal 1957 Cold Spring 0.20 55 .mmma mo HmEEsm mnu mGHHOU Q 0cm m mpcom How mwoam> >ocmfloemmm one .w musmflm 56 15 2O 25 30 10 AUG. SEPT. 15 JULY 1..- :3 1.7- it :Séfié ‘3“0l3l613 Figure 4 57 given for explaining the Observed differences in the gross primary productivities of the two ponds. The relationship between light intensity and effici- ency has been shown by Odum and Wilson (1962) and Druffer and Dorris (1966) to be an inverse one, with efficiency decreasing with increasing light intensities. Inhibition of photosynthesis at high light intensities has also been shown to exist. Rabinowitch (1951) states that there is a general trend in most cases towards a linear increase in photosynthesis with a corresponding increase in light intensity only to a saturation point. Beyond this satura- tion level higher light intensities do not increase photo- synthesis but eventually result in its inhibition. Steeman- Neilsen (1952) also states that in exceedingly bright light photo-oxidation of enzymes interfere with part of the photo- chemical mechanisms involved in photosynthesis. Examination of Figure 5 shows a situation similar to the one described by Rabinowitch (1951) existed in pond B. There appears to be a steady decrease in photosynthetic efficiency up to a saturation energy of approximately 475 gm./cal./cm2/day. Beyond this solar energy level decreases in efficiency, with increasing energy levels, become less pronounced. P/R Ratios The ratio of photosynthetic productivity to community respiration, P/R ratio, was used by Odum (1956) to classify 58 Figure 5. The relationship between efficiency and incident solar radiation in pond B during the summer of 1965. 2J~ 201 19- 18‘ 1J< 3- I-O .— o—o o—o n) c» p in m n 1 n 1 n Utilization Of EffiCIency P F3 P ,. H w a: (O o L- 1 1 1 1 1 Percent o m l P m 1 0.4-1 03‘ 02~ 0J- 59 I 100 Solar j 200 I 300 Radiation I 400 Figure 5 1 500 gncal4H2mg/day I 600 1 700 40 communities according to their total metabolism and the relative dominance of autotrophic and heterotrophic metab- olism. P/R ratios that are less than one occur when community metabolism exceeds photosynthetic production. P/R ratios greater than one are found where photosynthesis exceeds community reapiration. vExamination of the P/R ratio of a community makes it possible to classify it as either heterotrOphic or autotrophic. The P/R ratios varied between 0.59 and 2.64 in pond B and 0.50 to 5.00 in pond D. With mean P/R ratios for both ponds B and D being 1.01 and 1.04, respectively, we can classify them both as autogrophic communities producing approximately as much organic matter as they are using. PERIPHYTON PRODUCTIVITY The net photosynthetic productivity of the periphyton communities in the test ponds was measured by the employ- ment of artificial substrates as collecting agents. Periphyton shingles were examined at random during the summer to determine which genera of algae composed the periphyton community of the Lake City ponds. It has been noted by Castenholz (1960) that the artificial substrates are non-selective and do not favor the establishment of one particular type of algae. A list of the genera of algae found to be present in the periphyton of the test ponds is given in Table V. Although no quantitative measurements were made, there did not appear to be any one particular genus or genera of algae that dominated the peri- phyton community at any one particular part of the summer or during any specific part of the substrate eXposure period. The experiments of Grzenda (1960) showed that the number of phytopigment units in a given sample of peri- phyton extract could be used to quantitatively predict the organic weight of that particular sample. 41 42 TABLE V THE GENERA OF ALGAE FOUND IN THE PERIPHYTON COMMUNITY OF THE LAKE CITY PONDS Genera Genera Genera Actinotaenium tElakatothrix Oscillatoria Anabaena Euastrum Pandorina Ankistrodesmus Eudorina Pediastrum Aphanothece Fragilaria Penium Apiocystis Franceia Peridinium Botryococcus Geminella Pleurotaenium Bulbochaete . Gloeocapsa Quadrigula Calothrix Gloeocystis Radiofilum Ceratium GomphOSphaeria Rhabdoderma ChaetosPhaeridium Hormidium Scenedesmus Chroococcus Kirchneriella Sphaerocystis Closterium Lyngbya Spondylosium .Coelastrum Micrasterias .Staurastrum CoelOSphaerium Mougeotia Staurodesmus Coleochaete Nephrocytium .Stipitococcus Cosmarium .Nostoc Tetraedron Crucigenia Oedogonium Tolypothrix Cylindrocapsa Onychonema Trachelomonas Desmidium Oocystis Vaucheria 45 An attempt was made to establish a phytopigment- organic weight relationship for the periphyton growth in the experimental ponds using the method described by Grzenda (1960). The data in Figure 6 was derived from forty-four samples taken at random from periphyton collections made throughout the summer. The formula used for the regres- sion model was: Y = a + bx the mean organic weight estimate in milligrams, where Y a = the intercept of the Y axis, b = the point estimator of the population lepe, and X = the observed phytopigment reading in phytopigment units x 103. The predictive equation obtained by substituting the computed constants is: Y = -O.26 + O.47X Range of X = 7 to 114 n = 44 r = 0.98. The equations for computing the confidence regions on the linear regression (Figure 6) are given by Snedecor (1956). The 0.95 confidence limits for the Y (mean esti- mates) is denoted by CB (Figure 6). The 0.95 confidence 44 .Qd mmumEHumw Hmspfl>epcfl How com um mum Ammumfiflumm cmmev N How muHEHH wocwpemcou unwouwm m>amn>uwcflz .unmflm3 Uecmmuo can open: ucmEmem0u>£m cmm3umn manmcoflumamn one .m musmHm 45 OOH . om ow moH on - x mu_:D om . w musmwm acoE maelsd ow - om . om ON o~ .59 ram rmm -om 1mm agueflio IufiiaM (1W) 46 limits for the Y (individual estimates) is represented by .AD (Figure 6). The confidence limits for the mean and individual estimates appear as lines with slightly curved iborders. These curved borders illustrate the hazard of making predictions of Y at an X far removed from 32 (the Inean of the X's). .The minimum and maximum 95% confidence limits for individual estimates of Y are.i 8.45 mg. and .i 8.56 mg. respectively. The minimum and maximum 95% confidence limits for the mean estimates of Y are 1.1.24 :mg. and i.1.94 mg., reSpectively. Minimum values are located at R (mean of the X‘s), and maximum confidence limits occur at the maximum value for X which is 114 phyto- pigment units x 103. Figure 7, line CD, shows the linear regression as calculated by Grzenda (1960) for the phytopigment organic weight relationship of the periphyton occuring in the Red Cedar River. Phyt0pigment organic weight regressions calcu- lated by Kevern (1962) for an artificial stream also approxi- mate those reported by Grzenda (1960). Line AB (Figure 7) is the linear phytOpigment organic weight regression calcu- lated for the periphyton community of the Lake City ponds. Examination of the two regressions reveals that there is a greater quantity of organic matter per any given number of phytOpigment units in the test ponds as opposed to the Red Cedar River. This difference in the chlorophyll content of the two periphyton communities is most probably due to 47 .Q0 OCHH .Aomma .mocwuuov Hm>flu umooo pom map How .m¢ OOHH .mocom >uwo exam 0:» Mom coflmmwumwu unmww3 UHOMOHOIucmEmflmoumnm one .> ousmflm 48 co.“ co cm on meg x cm . w whomfim are: 0% EoEmEchm cc on to“ in" row ImN tom Imm 10v umv agueBJo tusiaM ('3‘“) 49 differing species compositiOn of the two algal communities and to the different conditions under which they are growing. These observed variations between the phytOpigment organic weight relationships of various habitats illustrates the necessity of workers who WiSh to use this method to construct regression equations for the particular habitat in which they are working. Only then will a regression equation have any predictive value. When attempting to measure the photosynthetic produc- tivity of a periphyton community by employing the use of artificial substrates as collecting agents, one must deter- mine which portion of the periphyton growth on these sub- strates is most representative of the growth taking place on the naturally occurring substrates. Kevern (1962) stated that periphyton productivity could be estimated by using artificial substrates as collecting devices only if the exposure period was long enough for the collected periphyton to approach a growth phase similar to that occurring on natural substrates. He also indicated that his investiga- tions showed that productivity estimates based on the growth accumulated during the last few days of the eXposure period yield the most reliable productivity estimates. The substrates used to make productivity estimates were exposed for a minimum of four days before removal from the pond and for a maximum of twenty-four days. A new series of periphyton shingles was placed in the ponds sixteen days after placement of the preceding rack. 50 The growth curve of the periphyton on the substrates exhibited a J-shaped form in all cases except one, which occurred at the end of the summer when periphyton production was greatly reduced. Figure 8 shows a growth curve typical of those found for the periphyton growth on the collecting shingles. The decline in total biomass of periphyton cling- ing to the substrate usually began on the 16th or 20th day of exposure. The decline in biomass was caused by the sloughing off of the periphyton coating. This sloughing Off may be caused by the accumulation of oxygen bubbles during the day time which would cause the loose periphyton growth to float away. During the latter part of the sub- strate exposure period the periphyton covering the Plexiglass plate became very fuzzy with growth extending out away from the substrate. Undoubtedly some of this very loose growth was lost when the substrate was removed from the supporting rack. This sampling error would also contribute to the J-shaped form of the growth curve. Periphyton production was estimated by subtracting the total amount of organic matter accumulated on a pair of substrates at the end of the fourth day of exposure from the total organic biomass present on another pair of sub- strates at the removal date immediately prior to the begin— ning of the sloughing Off period. ,This difference was then divided by the total time elapsed to give the periphyton production in terms of grams of organic matter accumulated 51 Figure 8. A representative growth curve of periphyton accumulating on artificial substrates in a Lake City test pond during the summer of 1965. Matter/m2 Organic Standing Crop Gm. 0f 2- 1:- 52 I 4 Time Of T I l 8 12 16 Substrate Exposure Figure 8 r 20 (days) 2'4 55 per sq. meter per day. Use of the time period described above for periphyton productivity estimates enables one to eliminate incorporation of the colonization period in the calculations thereby providing an estimate of peri- phyton production more closely approximating the production occurring on natural substrates in the ponds themselves. The periphyton production ranged from 0.12 to 0.50 gm. organic matter/mZ/day in pond B and from 0.04 to 0.20 gm. organic matter/ma/day in pond D. Mean productivity values for ponds B and D were 0.17 and 0.11 gm. organic matter/mZ/day respectively. The productivity values for the entire study period are given in Table VI. The efficiency of the periphyton community in convert- ing or transferring the photosynthetically active solar radiation (50% of incident solar radiation or éLi) into organic matter (Pn) was estimated for both test ponds (see Table VII). The equation used to convert the organic weightof the algae into caloric values was developed by Kevern (1962) who determined the energy content of peri- phyton, using bomb calorimetry. The conversion equation used is: gm. cal. = organic weight x 4500 Inspection of Figure 9 shows that the periphyton community of pond B was, with but one exception, more efficient in its utilization of solar energy. It is also evident that the efficiencies are more widely divergent during the latter part of the summer. 54 TABLE VI NET PRIMARY PERIPHYTON PRODUCTIVITY OF PONDS B AND D —4 Net Primary Productivity Date (ash-free dry wt. gm.(m2(dayt Pond B Pond D 7-1 thru 7-19 0.50 0.20 7-20 thru 7-51 0.22 0.16 8-1 thru 8-12 0.16 0.15 8-15 thru 8-24 0.15 0.05 8-25 thru 9-5 0.12 0.04 9-6 thru 9-16 0.14 0.08 Mean 0.17 0.11 55 TABLE VII PERCENT EFFICIENCY OF UTILIZATION OF PHOTOSYNTHETICALLY ACTIVE SOLAR ENERGY BY POND PERIPHYTON COMMUNITIES ii Date Pond B Pond D 7-1 thru 7-19 0.04% 0.05% 7-20 thru 7-51 0.05% 0.02% 8-1 thru 8—12 0.05% 0.05% 8-15 thru 8-24 0.02% 0.01% 8-25 thru 9-5 0.05% 0.01% 9-6 thru 9-16 0.04% 0.02% Mean 0.05% 0.02% 56 .uouume Uflcmmuo oucfl hmumcm HMHOO o>fluom maamoeumnucwnouozm mafinuommcmnu CA Q can m mmfluficofiaoo coumnmflnmm mo mocmHoflmmm one .m mnsmflm 57 a gunman mooted :oZmEme 3:20.102“. 513 we Em H mm; A? _. mew Nam .13 at .. 8e 2? HS IHQ \o/ INC. \ / \ \ \ / - /a .mo qu Kauaiama tuaOJad 58 Hasler and Jones (1949) found that large growths of aquatic plants had an inhibiting effect upon the growth of phytOplankton and rotifers. Moore (1952)suggested that low phytoplankton productivity was caused by the use of the nutritive materials by the higher aquatics. .From approximately August lst until the end of the test period there was a substantial die—off of higher aquatic plants in pond B. Pond D, on the other hand, was experiencing rapid growth of its late flourishing macro- phyte p0pulation. Although no positive relationship between a decreas- ing macrophyte population and an increasing periphyton pro- duction rate can be authoritatively established from these data, one could speculate as to the fact that periphyton growth in pond D was affected by nutrient limitations or availabilities placed upon it by the rapidly growing macro- phyte p0pulation. It should be noted that production rates occurring on artificial substrates are only indices of production rates occurring on the natural substrates. Pond D, in fact, may have possessed a greater total amount of periphyton produc- tion due to its greater surface area available for coloni- zation. MACROPHYTE PRODUCTIVITY The second source of primary productivity in the test ponds was that of the macrOSCOpic aquaticflplants. The net photosynthetic productivity of the macrophytes was measured by employment of the harvest method. Forty samples were removed from randomly selected loca- tions in pond B upon initiation of the productivity study. Pond D had previously been drained and ranked clear of all higher aquatic growth making an initial sampling unnecessary. The macrOphytes were again sampled in pond B on August 1, 1965 and finally on September 10, 1965. Macrophytes were sampled in pond D on August 5, 1965 and September 10, 1965. During the final sampling period the aquatic plants removed from pond D were separated according to genera and weighed to determine the composition of the plant population. The most abundant macrOphyte was th£§_sp. with 91.0% of the dry weight of the pOpulation being comprised of this particu- lar genera. The second most abundant macrophyte was Elodea Sp. which comprised 5.9% of the total dry weight. The re- mainder of the pOpulation was composed of gotamogeton sp. 2.9%. Very small amounts of Najas flexilig_were also noted in some of the samples. 59 60 Plans were originally made to conduct a similar survey of the macrophyte population of pond B, however, at the time the attempt was made the population was so severely depleted that any results would have proved highly unreliable. Inspection of dried samples from the first and second sam- plings of pond B did show thatthe three genera of macrophytes were present in approximately the same ratios as those found in pond D. The caloric content of the three genera of macrophytes was determined by analysis of five or more-samples of each type. The caloric content of ghg£g_3p., after corrections were made for endothermy was 1882.6.i 95 cal./gm. dry weight. The caloric content of Elodea Sp., and Potamogeton Sp., are 5470.5.i 68 cal./gm. dry weight and 5961.6.1 255 cal./gm. dry weight reapectively. InSpection of Figure 10 shows that the average biomass of macrOphytes decreased in pond B throughout the study period while the biomass of the macrophyte population in pond D steadily increased over the same time period. .This fact also reflects itself in the net productivity rates of the two ponds. .This difference was undoubtedly due to the fact that pond D was drained on June 21, 1965 prior to ini- tiation of the study. The macrOphyte population of pond B, which was not drained had passed its maximum growth phase by the time the study was begun. The rates of net primary productivity of the macrOphytes in pond D varied from 0.45 to 0.92 gm. dry weight/ma/day. - to 'm‘io'q. ‘5' "I "in. Figure 10. 61 The rates of net production and biomass accumulation of the aquatic macrOphytes in ponds B and D. 62 Biomass S [U A V. U m m. m m. m. J 5 4 3 2 1 550.2 .Ow cod mEmco-mmmEo_m L nip 8 n S O t C U . d 8 Tu m A P O N V. U a < q J q .J 0 8. 6 4. 2. . . O O xmo com cone—2 Ow com mESG Sept L 1” S B D s O S N a :M O m P 0 B V. Iu J q u u q a 0 0 0 0 0 . 5 4 3 2 l . Loam: om com mEmco- mmmEo_m L ID. 8 S n O B H C U e on w d u 0 A 0 r P P t e N .W U J A u q 4 u D B 5 4. 2 1 0 0 0 0 .25 can. .305. .Om can. mEmco POPQD [) POIUD D Figure 10 65 Knight, Ball, and Hooper (1962) reported the same pond to have a net productivity of 6.00 gm. dry weight/ma/day for the entire growing season of 1960. Vannote (1965) reported production rates of 0.41 and 1.57 gm. dry weight/ma/day for a Vallisneria community in the Red Cedar River. The dry weight estimates of the macrophyte pOpulations were converted to caloric content by the following rela- tionship: gm. cal. = dry weight x 2056 The net productivity rates in terms of gm. cal./m2/day are given in Table VIII for the macrophyte communities of the two ponds. The efficiency of the macrOphyte community in convert- ing the photosynthetically active solar radiation, éLi, into organic matter, Pn, was estimated for pond D, with results also being given in Table VIII. Efficiencies in pond D ranged from 0.05 to 0.1%‘with a mean efficiency of 0.08%. Vannote (1965) reported mean annual Pn/Li efficiencies from 0.05 to 0.07%. 64 TABLE VIII NET PRIMARY PRODUCTIVITY AND PERCENT EFFICIENCY OF UTILIZATION OF PHOTOSYNTHETICALLY ACTIVE SOLAR ENERGY OF POND MACROPHYTES ‘_—l —_ Pond Date Grams per Gram calories Percent sq. meter per sq. meter Efficiency _per day per day Pn/%Li D 7-1 thru 0.45 875.5 0.05% 8-2 8-5 thru 0.92 1875.2 0.10% 9-9 B 7-1 thru 0.00 0.0 0.00% 7-51 8-1 thru 0.00 0.0 0.00% 9-9 Pn = Net primary production. fiLi= Photosynthetically active solar radiation. PHYTOPLANKTON PRODUCTIVITY The phytoplankton are the third and final group of photosynthetic organisms fOund in the experimental ponds. The dominant group of phytoplankters appeared to be the desmids. The C14 method of measuring the productivity of the phytoplankters, although generally accepted, was not used in this study. An attempt was made to estimate the pro- ductivity of the phytoplankton by measuring the_standing crOp of organisms and estimating their rate of turnover. Standing crOps of plankton were sampled weekly from both ponds B and D throughout the study period. Plankton samples once collected were dried, weighed, ignited and the loss of weight upon ignition determined and recorded as the organic weight of the sample. The average standing crop of planktonic organisms in pond B was 1.44 gm. organic matter/m2. The standing crop of planktonic organisms in pond D averaged 1.14 gm. organic matter/m2. These values are similar to those average values reported by Birge and Juday (1922). Birge and Juday (1922) estimated that approximately 25 percent of all the planktonic material is composed of 65 66 ZOOplankton. Riley (1940) in a study of the plankton of a New England pond stated that the mean phytOplankton to zooplankton ratio, which he considered to be somewhat high, was 4.5 to one. For the purpose of estimating the standing croP of phytoplankton in the test ponds it was assumed that the phytoplankton to ZOOplankton ratio was 5:1. .The average estimated standing crOp of phytopoankton in pond B was 1.08 gm. organic matter/m2 and 0.85 gm. organic matter/m2/ in pond D. Birge and Juday (1922) indicate that the turnover rate of the plankton population falls somewhere between one and two weeks. Riley (1959) estimated that the phytoplankton production was 2.02 crops per week in surface waters. Since the entire area of both ponds are within the euphotic zone a turnover rate of two crOps per week was used to estimate the mean phytoplankton production of the two test ponds. The estimated average production of organic matter by the phytOplankton pOpulation of pond B is 0.50 gm. organic matter/ m2/day. The average rate of energy fixation by the phyto— plankton of pond D is somewhat less rapid with 0.24 gm. organic matter being fixed ma/day. .These values though some- what lower are in general agreement with those reported by Knight, Ball, and HOOPer (1962) for the same test ponds. If it is assumed that the caloric content of the phyto- plankton is 4500 cal./gm. organic weight, the average 67 efficiency of conversion of photosynthetically active solar energy, éLi, into organic material would be 0.05 percent for pond D and 0.06 percent for pond D. SUMMARY The primary productivity of two ponds was measured by monitoring the dissolved oxygen content of the water and by the collection of the three groups of primary producers. The mean net productivity rates of ponds B and D were 5.75 gm. Og/me/day and 5.05 gm. 02/m2/day respectively. A close correspondence was noted between the level of light intensity and the rate of primary production. Periods Of decreased light intensities even though quite short produced a decrease in primary production while increases in light intensity brought about an immediate increase in primary production. There was a relationship between the light intensity and the efficiency with which the photosynthetic organisms fixed the available solar energy. Efficiency of utilization of solar energy was found to decrease with increasing light intensities up to approximately 475 gm. cal./cm2/day. Above this light intensity increases in solar energy pro- duced little decreases in efficiency levels. This decrease in efficiency accompanying increases in light intensity is thought to be due to photo-oxidation of enzymes essential to photosynthesis. 68 69 The mean P/R ratios for ponds B and D were 1.01 and 1.04 reSpectively, thereby classifying them as autotrophic communities. A linear relationship between ethanol phytopigment extracts of periphyton and the organic weight of the sample was established. In pond B the phytoplankton was the leading primary producer (0.50 gm. organic matter/mZ/day) with periphyton being second (0.17 gm. organic matter/ma/day) and the macro- phytes fixing no solar energy during the study period. In pond D the macrophytes were the leading primary producers (0.67 gm. organic matter/ma/day) with the phytOplankton second (0.24 gm. organic matter/me/day) and periphyton last (0.11 gm. organic matter/mZ/day). A relationship appears to exist between macrOphyte, periphyton and phytoplankton growth. Increased levels of macrophyte growth coincide with decreased levels of periphyton and phytoplankton growth in pond D, while decreased macro- phyte growth concurs with increased production of phyto- ’plankton and periphyton in pond B. It is possible that nutrient limitations placed upon the periphyton and phyto- plankton populations by the flourishing macrophyte growth occurring in pond D resulted in the lower rate of productiv- ity of the periphyton and phytoplankton. The macrOphytes may also have had a direct inhibiting action upon the growth of the periphyton and phytoplankton. LITERATURE CITED Birge, E. A., and C. Juday. 1914. A limnological study of the Finger Lakes of New York. Bull. U. S. Bur. Fisheries, No. 52:525-609. . 1922. The inland lakes of Wisconsin. The plank- ton. Part I. Its quantity and chemical composition. Wis. Geol. Nat. Hist. Surv., 64:1-222. . 1954. Particulate and dissolved organic matter in inland lakes. Ecol. Monogr., 4:440-474. Bissonnette, T. H. 1950. A method of securing marine in- vertebrates. Science, 71:464—465. Butler, J. L. 1964. Interaction of effects by environmental factors on primary productivity in ponds and microeco- systems. Doctor's thesis, Oklahoma State University, 88 pp. Castenholz, R. W. 1960. Seasonal changes in the attached algae of freshwater and saline lakes in the lower Grand Coulee, Washington. Limnol. and Oceanogr., 5:1-28. Clarke, G. L. 1959. The utilization of solar energy by aquatic organisms. 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Wiebe, A. H. 1951. Diurnal variations in the amount of dissolved oxygen, alkalinity, and free ammonia in certain fish ponds at Fairport, Iowa. Ohio J. Sci., 51:120-126. APPENDIX 76 Solar energy measured at the Lake City Experiment Station during the summer of 1965. Values are expressed as gram calories per square centimeter per day. Date Gram cal. cm"2 Date Gram cal. cm-2 day'l day‘ 7-1 702.9 8-9 80.4 7-2 296.5 8-10 625.7 7-5 675.2 8-11 597.2 7-4 672.6 8-12 512.5 7-5 664.4 8-15 478.0 7-6 501.0 8-14 675.0 7-7 601.1 8-15 595.0 7-8 595.6 8-16 424.4 7-9 295.7 8-17 512.1 7-10 659.5 8-18 117.0 7-11 605.0 8719 589.0 7-12 687.6 8-20 476.1 7-15 507.7 8-21 521.0 7-14 685.2 8-22 575.1 7-15 699.8 8-25 574.0 7-16 285.0 8-24 488.1 7-17 291.1 8-25 142.6 7-18 460.6 8-26 221.1 7-19 628.8 8-27 297.5 7-20 572.7 8-28 440.4 7-21 596.0 8-29 475.8 7-22 456.0 8-50 140.5 7-25 567.9 8-51 110.8 7-24 628.2 9-1 594.0 7-25 655.7 9-2 470.9 7-26 580.0 9-5 470.4 7-27 620.0 9-4 518.9 7-28 600.0 9-5 485.6 7-29 560.0 9-6 185.5 7-50 590.0 9-7 85-8 7-51 110.0 9-8 471.0 8-1 170.0 9-9 120.8 8-2 586.6 9-10 210.9 8-5 285.7 9-11 475.7 8-4 468.0 9-12 485.6 8.5 495.0 9-15 455.5 8-6 542.2 9-14 202.9 8-7 594.2 9-15 87.8 8-8 168.7 9‘16 181.1 77 Gross primary productivity of the Lake City ponds expressed as grams of oxygen per meter squared per day--Summer, 1965. Date Pond B Pond D Date Pond B Pond D 7-1 4.58 1.57 8-9 1.66 0.64 7-2 2.42 1.20 8-10 5.95 7.18 7-5 5.95 1.80 8-11 4.09 4.05 7-4 5.12 5.10 8-12 4.89 5.70 7-5 6.19 2.40 8-15 5.47 4.75 7-6 5.51 1.85 8-14 4.27 6.29 7-7 5.12 1.66 8-15 5.28 5.51 7-8 5.40 2.54 8-16 5.05 5.90 7-9 2.82 0.56 8-17 5.98 5.60 7-10 5.45 2.72 8-18 2.91 1.55 7-11 5.05 1.65 8-19 5.58 5.14 7-12 5.55 2.80 8-20 5.28 5.14 7—15 5.50 1.58 8-21 5.80 5.50 7-14 4.26 5.27 8-22 5.55 4.65 7-15 6.71 2.75 8-25 5.58 4.65 7-16 5.06 1.20 8-24 2.79 6.84 7-17 2.50 1.67 8-25 2.21 1.60 7-18 4.10 2.65 8-26 5.05 2.41 7-19 5.95 5.25 8-27 4.45 4.70 7-20 4.19 4.58 8-28 4.45 5.08 7-21 5.20 5.52 8-29 2.95 1.91 7-22 2.75 2.57 8-50 1.42 1.56 7-25 4.65 4.40 8-51 1.44 0.84 7-24 4.55 4.50 9-1 5.19 1.59 7-25 4.88 5.55 9-2 2.41 1.68 7-26 4.06 5.11 9-5 5.55 5.55 7-27 4.71 5.51 9-4 4.08 2.26 7-28 5.92 4.26 9-5 5.77 4.75 7-29 5.76 5.56 9-6 2.57 2.17 7-50 5.50 4.12 9-7 1.89 1.15 7-51 2.55 2.15 9-8 2.60 2.55 8-1 2.54 1.62 9-9 1.92 1.21 8-2 5.56 5.84 9-10 2.52 2.27 8-5 2.57 1.55 9-11 5.08 5.82 8-4 5.15 4.28 9-12 2.76 2.58 8-5 2.05 4.98 9-15 2.64 4.20 8-6 5.56 4.51 9-14 2.45 5.25 8-7 5.02 4.22 9-15 1.89 1.77 8-8 4.49 2.92 9-16 2.45 1.84 78 Community reSpiration of the Lake City ponds eXpressed as grams of oxygen per meter squared per day--Summer, 1965. Date Pond B Pond D Date Pond B Pond D 7-1 4.05 0.60 8-9 2.55 2.15 7-2 5.45 1.95 8-10 4.66 6.55 7-5 2.70 0.60 8-11 4.15 5.55 7-4 5.40 5.60 8-12 5.60 4.00 7-5 6.75 2.40 8-15 4.55 5.75 7-6 5.70 1.55 8-14 4.15 7.55 7-7 5.12 1.95 8-15 5.55 5.46 7-8 4.52 2.55 8-16 5.20 4.00 7-9 2.40 1.65 8-17 5.46 5.60 7-10 6.96 2.70 8-18 4.40 2.00 7-11 1.80 1.05 8-19 5.86 5.75 7-12 6.26 2.40 8-20 5.55 4.15 7-15 5.46 1.86 8-21 4.40 5.60 7-14 4.26 2.40 8-22 5.20 5.46 7-15 2.55 2.26 8-25 5.46 2.66 7-16 5.86 1.86 8-24 2.80 6.40 7-17 2.55 2.00 8-25 4.00 5.60 7-18 2.80 2.26 8-26 5.46 2.55 7-19 5.20 2.55 8-27 4.55 5.46 7-20 2.95 5.06 8-28 5.86 2.80 7—21 5.20 5.06 8-29 2.66 1.46 7-22 4.40 5.06 8-50 2.40 1.52 7-25 4.40 4.26 8-51 1.92 1.52 7-24 5.46 5.75 9-1 2.88 1.08 7-25 6.40 5.06 9-2 2.64 1.44 7-26 5.75 5.15 9—5 4.52 2.52 7-27 4.65 5.50 9-4 4.52 5.56 7-28 5.90 5.50 9-5 5.48 7.52 7-29 4.65 5.45 9-6 5.00 5.12 7-50 4.50 5.00 9-7 2.16 1.56 7-51 5.60 5.90 9-8 1.52 1.20 8-1 2.80 2.15 9-9 2.85 5.05 8-2 5.75 2.80 9-10 2.07 5.05 8-5 2.95 1.20 9-11 5.16 2.29 8-4 2.80 5.86 9-12 5.27 1.85 8-5 2.95 4.15 9-15 5.58 4.14 8-6 4.55 5.75 9-14 2.04 6.10 8-7 4.95 4.80 9-15 1.96 2.94 8-8 5.86 5.75 9-16 1.65 0.76 79 P/R ratios found in ponds B and D during the summer of 1965. Date Pond B Pond D .Date Pond B Pond D 7-1 1.15 2.29 8-9 0.65 0.50 7-2 0.70 0.61 8-10 1.27 1.09 7-5 1.45 5.00 8-11 0.99 1.20 7-4 0.94 0.86 8-12 0.87 0.92 7-5 0.91 0.76 8-15 0.76 1.27 7-6 0.96 1.57 8-14 1.05 0.85 7-7 1.00 0.85 8-15 0.99 1.00 7-8 0.78 0.91 8-16 0.97 0.97 7-9 1.17 0.54 8-17 1.15 1.00 7-10 0.66 1.00 8-18 0.66 0.67 7-11 1.59 1.55 8-19 1.44 1.57 7-12 0.88 1.16 8-20 0.99 0.76 7-15 0.60 0.75 8-21 0.86 1.47 7-14 0.99 0.98 8-22 1.02 0.84 7-15 2.64 1.20 8-25 ,1.02 1.74 7-16 1.79 0.64 8-24 0.99 1.06 7-17 0.91 0.85 8-25 0.55 0.44 7-18 1.97 1.16 8-26 1.45 0.95 7-19 0.76 1.28 8-27 0.98 0.86 7-20 1.42 0.86 8-28 1.14 1.10 7-21 1.00 1.08 8-29 1.09 1.50 7-22 0.88 0.77 8-50 0.59 1.18 7-25 1.05 1.05 8-51 0.75 0.64 7-24 0.82 0.78 9-1 1.10 1.47 7-25 0.76 1.08 9-2 0.91 1.16 7-26 1.08 0.98 9-5 0.82 1.52 7-27 1.01 1.06 9-4 0.94 0.67 7-28 1.00 1.29 9-5 1.08 0.64 7-29 1.24 0.97 9-6 0.79 0.69 7-50 0.77 1.57 9-7 0.87 0.74 7-51 0.65 0.54 9-8 1.96 2.12 8-1 0.90 0.76 9-9 0.67 0.59 8-2 1.45 .1.57 9-10 1.12 0.74 8-5 0.87 1.12 9-11 0.97 1.66 8-4 1.12 1.10 9-12 0.84 1.59 8-5 0.69 1.20 9-15 0.78 1.01 8-6 0.78 0.78 9-14 0.85 0.55 8-7 1.01 0.88 9-15 0.96 0.60 8-8 0.76 0.78 9-16 1.49 2.41 MICHIGAN STATE UNIV. 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