Iowa State University Capstones, Theses and Retrospective Theses and Dissertations Dissertations
1974 Eutrophication of some northwestern Iowa lakes John Richard Jones Iowa State University
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JŒŒS, John Richard, 1947- HJTROPinCATICN OF SCME NORTHWESTERN lOWA. LAKES.
Iowa State University, Ph.D., 1974 Limnology
Xerox University Microfilms, Ann Arbor, Michigan 48io6
THIS DISSERTATION HAS BEEN wiCROFiLMED EXACTLY AS RECEIVED. Eutrophication of some northwestern Iowa lakes
by
John Richard Jones
A Dissertation Submitted to the
Graduate Faculty in Partial Fulfillment of
The Requirements for the Degree of
DOCTOR OF PHILOSOPHY
Department: Zoology and Entomology
Major: Zoology (Limnology)
Approved:
Signature was redacted for privacy. ti Charge of Ma^jor Work
Signature was redacted for privacy. For the Major Department
Signature was redacted for privacy.
Iowa State University Ames, Iowa
1974 ii
TABLE OF CONTENTS
Page
INTRODUCTION 1
MATERIALS AND METHODS 5
PART I. COMPARATIVE LIMNOLOGY OF THE IOWA GREAT 13 LAKES
PART II. NUTRIENT BUDGETS AND WATERSHED LAND USE 32 PRACTICES
PART III. RELATIONSHIP BETWEEN ANNUAL NUTRIENT 59 INPUTS AND THE MAGNITUDE OF THE SUMMER ALGAL BLOOMS
LITERATURE CITED 77
ACKNOWLEDGMENTS 85 1
INTRODUCTION
The Iowa Great Lakes watershed is located in three town ships of north-central Dickinson County, Iowa and extends into four townships of Jackson County, Minnesota (Figure 1). The lake system lies in the Cary drift of the Des Moines lobe and is enclosed by morainal topography (Thomas, 1913; Tilton, 1916;
Carman, 1917). Radiocarbon dating of lake sediments indicates a late Cary or a postglacial age for the lake basin (Dodd et
, 1968).
Seven major lakes lie within the watershed, they are:
West Okoboji, Spirit, East Okoboji, Upper Gar, Minnewashta,
Lower Gar, and Loon (Minn.). Each of these lakes is eutrophic, with some of the lakes having more recognizable eutrophication
problems than others. The magnitude of this trophic state is
indicated by the severity of the summer blue-green algal bloom
occurring m each lake. Nuisance ishytoplankton conditions
develop each summer in lakes East Okoboji, Minnewashta, Upper
and Lower Gar. Conditions in Spirit Lake are less severe
depending upon the year, while Lake West Okoboji only occasion
ally has algal problems.
The differences in the degree of eutrophication in the
Iowa Great Lakes are surprising within a lake region with a
common watershed having relatively uniform land-use practices.
Most of the land within the region is devoted to row crop
agriculture or animal husbandry; nearly 20% of the watershed 2
Figure 1. The Iowa Great Lakes watershed, located in Jackson County, Minnesota and Dickinson County, Iowa 3 is covered by ponds, lakes or marshes.
A group of local citizens interested in preserving and protecting the water quality of the Iowa Great Lakes was aware of the deleterious effects of cultural eutrophication in other lakes. They were concerned that serious problems might de velop in their lakes and wanted a scientific basis for deter mining the limnological conditions in the Iowa Great Lakes.
This group funded an intensive limnological investigation of this lake system through the Iowa Agriculture and Home Econom ics Experiment Station, Iowa State University, Ames, Iowa.
The field portion of this study extended from March 1971, through August 1973. The data collected and conclusions drawn from this study are given in Bachmann and Jones (1974).
My study was a portion of this limnological investiga tion. I wanted to find out what factors influenced the ob served differences among these lakes. To accomplish this I looked at the nutrient concentrations and algal standing crops of the lakes in relation to the annual nutrient loads deliv ered to each lake. Since these loads originated in the sur rounding watersheds, an important factor was the ratio of
A • « V» + A «./ «A W ^V IOVA # V ^ • A. O A vvn ^ A& VA W e +3% Wa
turnover time of lake water and influences the concentration
of dissolved materials in each of the lakes. I also wanted
to identify specific activities within the watersheds that
might contribute to the nutrient load. Such information would 4 be important in a nutrient reduction program.
My specific objectives were to: (1) determine limnol- ogical conditions in the Iowa Great Lakes and identify factors * which influence them, (2) determine the amounts of plant nutrients entering the lakes and how various land-use prac tices influence the amounts of plant nutrients entering these lakes, and (3) determine how nutrients influence the limnol- ogical features of the lakes. 5
MATERIALS AND METHODS
Sampling Methods
Water samples were collected from 6 stations on Lake West
Okoboji, 5 stations on Lake East Okoboji, 5 stations on Spirit
Lake, and 1 station on each of the following lakes: Upper Gar,
Minnewashta, Lower Gar, and Loon (Figures 2 and 3). Lake sta tions were sampled approximately every two weeks during the summer months and at least monthly during the rest of the year.
Surface water samples were collected in acid-washed BOD bottles immersed 10 to 20 cm below the water surface and a
deeper sample was taken just above the bottom substrate by
using a three-liter opaque plastic Van Doran sampling bottle.
Samples for chlorophyll a extraction and qualitative algal
analyses were taken below the surface by immersing a one-
gallon plastic jug. At Station 49, the deepest area of Lake
nest Okoboji (42 m), a vertical series of samples was col
lected at 5 m intervals to the depth of 35 to 40 m.
Stream sampling stations were located on streams which
flowed into or from the lakes (Figures 2 and 3) (Bachmann and
Jones, 1974). Along several of the larger streams, stations
were located at more than one point to describe water quality
within the sub-watersheds. Stream samples were collected on
an approximate weekly sampling schedule throughout the study.
Collections were made close to where the streams enter the
lake. 6
BIG SPIRIT L.
I3J
CENTE L.
ol^ojl LAKE
LAKE
MINNEWASHTA 521 « L
LOWER AR
TLOWER GAR OUTLET Figure 2. Lake and stream sampling stations on and around Lakes West Okoboji, East Okoboji, Upper Gar, Minnewashta, and Lower Gar LOON LAKE 'LITTLE SPIRIT, LAKFT
BIG Spirit LAK
I/ (MARBLEi y ) LAKE I
Figure 3. Lake and stream sampling stations on and around Big Spirit Lake 8
Stream samples were collected by immersing BOD bottles below the water surface. At the time of sample collection, stream flow was estimated by measuring average stream depth, width and velocity of flow.
At Loon Lake outlet, Orleans Spillway, and Stream Gage outlet on Milford Creek, volume of flow was measured by con tinuous recording stream gages operated by the U.S. Geological
Survey (Iowa City, Iowa).
Storm sewers within the watershed were occasionally sampled to obtain estimates of nutrient inputs from these sources. Sampling occurred during the time of runoff from spring snowmelt and during rainstorms.
Rainfall was sampled to estimate nutrient concentrations.
Rainwater was collected on the roof of the Limnology Labora tory at Iowa Lakeside Laboratory in a vinyl sheet hung across a wooden frame.
Physical Measurements
At lake stations, surface and bottom temperatures were taken with a Whitney Underwater Resistance Thermometer (Monte-
doro Corp=; San Luis Obisbo, Calif.). Turbidity (JTU) was
measured on both stream and lake samples using a Hach DRA
colorimeter. At lake stations, water transparency was deter
mined with a 20-cm Secchi disc painted alternately black and
white. 9
Chemical Measurements
The following chemical analyses were made on unfiltered lake, stream, rain and storm sewer samples. Ammonia nitrogen concentration was determined by the direct Nesselerization method. Nitrate nitrogen concentration was determined by the cadmium reduction method. Orthophosphate concentration was determined by the stannous chloride method. On lake samples, additional analyses were conducted to determine silica by the silicomolybdate method. Nitrate nitrogen was determined by the diazotization method but values were seldom found above
0.10 mg/1 in streams and 0.01 mg/1 in lakes so the test was
discontinued in August, 1971. All nitrate nitrogen values
reported in this study, therefore, also include the small
amount of nitrite also present. Prepared reagents for the
above analyses were purchased from Hach Chemical Co., Ames,
Iowa (Hach, 1967).
Total phosphorus was determined according to the proce
dures of Murphy and Riley (1962) with a persulfate oxidation
described by Menzel and Corwin (1965).
Organic nitrogen analyses were made on a selected series
of lake samples in May and June, 1972, by the Engineering
Research Institute Analytical Laboratory, Iowa State Univer
sity, Ames, Iowa, using the phenate method (A.P.H.A., 1965)
and a Technicon Auto Analizer II (Technicon Inst. Co., Tarry-
town, N.Y.). 10
An Industrial Instruments Conductivity Bridge Model RC
16B1 was used to measure specific conductance in micromhos/cm at 25 C. Chemical oxygen demand was measured on lake samples by the dichromate oxidation method (A.P.H.A., 1965), using a
1 hour reflux time and 0.025N potassium dichromate and 0.01 N ferrous sulfate.
Dissolved oxygen samples were collected and processed following standard procedures (A.P.H.A., 1965). The samples were titrated with 0.025N Phenylarsine Oxide. During winter collection, powder reagents were used for fixation (Hach,
1967).
Seasonally, lake samples were analyzed for total and cal
cium hardness by the CDTA method, total alkalinity by use of
Brom Cresol Green-Methyl Red indicator and titrating with 0.02
N sulfuric acid, and chloride by use of the mercuric nitrate
method (Hach, 1967).
Biological Measurements
For chlorophyll a analysis, a measured sub-sample of lake
water was filtered through a Type A Gelman glass fiber filter.
The filter was stored up to 40 days frozen over desiccant.
Chlorophyll concentration was determined by use of the methods
of Richards with Thompson (1952) and Yentsch and Menzel (1963).
Values were calculated from the equations of Parsons and
Strickland (1963).
Slide preparations of algae concentrated by passing lake 11 water through a No. 25 plankton net were examined to determine dominant algal genera.
Land Use Inventory
A land use inventory of the Iowa Great Lakes watershed was conducted by Mr. William Higgins. Information was ob tained from the area Extension Office, Soil Conservation Ser vice (SCS), Agricultural Stabilization and Conservation Service
(ASCS), and from landowners in the Iowa and Minnesota portions of the watershed. Field work was also necessary to obtain this information. The watershed area, lake watersheds and separate sub-watersheds surrounding each major lake were de lineated from U.S.G.S. topographic maps (7.5 minute series).
Areal determinations (hectares) were made of row crops (corn, beans, oats and set aside), grasslands (pastured and non- pastured grassland as well as conserving base areas), wood
lands, marshland, permanent water (small lakes and ponds), and
urban areas in each sub-watershed. Soil type and slope were
identified from SCS and ASCS records. Livestock numbers were
determined from ASCS records, county tax records, and field
inspection. Livestock values were converted to numbers of
animal units per sub-watershed using the definition of the
Environmental Protection Agency where one animal unit is de
fined as the number of animals required to produce wastes with
a biochemical oxygen demand equivalent to that of one beef
steer. 12
Two categories of sub-watersheds are considered in the study. The first is a metered watershed which has a specific boundary with an assigned station number where surface or tile drainage has been monitored according to the sampling schedule.
The second type is an unmetered watershed, not monitored during the study. The detailed inventory for all metered and un metered watersheds is given in Bachmann and Jones (19 74). 13
PART I. COMPARATIVE LIMNOLOGY OF THE IOWA GREAT LAKES
Results
Watershed features
The Iowa Great Lakes watershed is located in northwestern
Iowa and southwestern Minnesota (Figure 4). The watershed can be subdivided into separate drainage areas for each major lake
(Table 1). The watershed lakes are interconnected and drain age is southerly from Minnesota to Spirit Lake and over a spillway to Lake East Okoboji. Lakes East Okoboji, West
Okoboji; Upper Gar, Minnewashta and Lower Gar have the same water level. The outflow for this drainage system is an un gated spillway on Lower Gar Lake through which all the lakes eventually drain to the Missouri River via the Little Sioux
River. Municipal wastes from most of the built-up areas around the Iowa lakes are diverted by a trunk-line sewer to a sewage treatment plant which empties below the lakes.
Morphological and hydrological features
The morphological and hydrological characteristics of the
Iowa Great Lakes are given in Table 1. Morphometric maps of
each of the lakes are in Bachmann and Jones (1974). Lake West
Okoboj X xs the deepest lake and the only one wxth thermal
stratification. Because of its large volume and small water
shed it has the lowest ratio of watershed area to lake volume 2 3 (m /m ) and longest turnover time. The Spirit Lake basin is
saucer-like with a large surface area and a moderate mean 14
LOON LAKE
Mlj^N TOWA'
BIG SPIRIT LAKE
a
LAKE WEST OKOBOJI
LAKE EAST OKOBOJI
UPPER GAR LAKE - LAKE MINNEWASHTA LOWER GAR LAKE
t
Figure 4. The Iowa Great Lakes watershed. Dashed lines indicate watershed boundaries Table 1, Total area of individual lake watersheds, morphometric characteristics and ratios of watershed areas to lake volumes for Lakes West Okoboji, Spirit, East Okoboji, Loon and Lower Gar
West Spirit East Loon Lower Okoboji Okoboji Gar
Watershed area (ha) 7698 9962 5903 7935 4720
Lake area (ha) 1540 2168 764 291 98
Lake volume 184.0 111,9 21.2 4.5 1.1 (1 X 106m3)
Mean depth (m) 11.9 5. 2 2.8 1.5 1.1
Ratio of watershed area 0.33 0.69 2. 42 16.9 42.0 to lake volume (m2/m3)
Turnover time (years) 20 5. 5 1. 2 0.5 0.3 16 depth. Spirit Lake has a volume smaller than Lake West
Okoboji and a turnover tine only 25% as long. Lake East
Okoboji is long and narrow, comprised of several connected
basins. It has a moderate watershed area and small volume.
This lake has half the surface area but only 12% of the volume
of Lake West Okoboji. Lakes Upper Gar and Minnewashta do not
have surface watershed drainages separate from East Okoboji so
I have considered them as a southern expansion of the larger
lake. The watershed area to lake volume ratio of the three
lakes is such that the turnover time is one year. Lower Gar
Lake is the shallowest lake, and receives drainage from a land
area 43 times the lake surface area. Because of the large
watershed area to lake volume ratio the waters of Lower Gar
Lake are more directly influenced by the watershed runoff than
any lake in the watershed.
Interchange between lakes East Okoboji and West Okoboji
The watershed areas and volumes of lakes East and West
Okoboji influence the interchange of water between them.
Because Milford Creek, on Lower Gar Lake, is the only surface
outlet for the watershed, it is natural to assume that water
flows from Lake West Okoboji into Lake East Okoboji. Field
observations, however, indicate that waters of Smith's Bay,
West Okoboji, had characteristics similar to waters of Lake
East Okoboji, indicating a possible mixing between these
lakes. In summers 1971-1973, water samples were collected 17 along a transect from the open waters of Lake West Okoboji to
Lake East Okoboji to determine water quality within this interchange (Figure 5].
The mixing pattern between these lakes can be inferred from the specific conductance values (Figure 5), a conserva tive characteristic of a given water mass. In general. Lake
East Okoboji has higher specific conductance values than Lake
West Okoboji. If the general outflow was from Lake West
Okoboji to Lake East Okoboji, lower conductance values should persist to the interchange (Station 5, Figure 5) and increase into Lake East Okoboji. This was not found. Rather, there was a gradient across the connection.
The ratio of watershed area to lake area is higher in
Lake East Okoboji (6:1) than Lake West Okoboji (3.8:1). Dur ing periods of rising water levels Lake East Okoboji would rise at a more rapid rate than Lake West Okoboji if runoff volumes per unit area are the same in the two watersheds.
Thus, water would tend to flow from Lake East Okoboji to Lake
West Okoboji at those times. During periods of falling water
levels due to outflows through the Lower Gar Lake outlet, the
flow would be in the other direction. During periods of
stable water levels, wind action and waves would cause an
interchange of water in the connection between these lakes.
Groundwater flows may also influence this flow pattern. 18
EAST OKOBOJI
Smith's Sey WEST OKOBOJI
470 1971 oUJ
»- 1973 o o 450
1972
W 430 CL STATION Figure 5. Map of stations along a transect extending from the deep hole of Lake West Okoboji to the open waters of Lake East Okoboji. Also, the distribu tion of mean specific conductance - uss across the transect in 1971, 1972 and \ill- ci-e plotted for their respective stations 19 Water quality and trophic conditions in the lakes All of the studied lakes are eutrophic or biologically- productive, but some lakes are more eutrophic than others. In Table 2, several water quality parameters of the respective lakes are summarized. The concentrations of phosphorus and nitrogen compounds are indicative of the potential growth of plant materials in these lakes, while chemical oxygen demand and chlorophyll a measurements indicate the amount of growth achieved. Secchi disk transparencies are inversely related to chlorophyll a concentrations. Using these data, the lakes can be ranked in order of increasing states of eutrophication. This order is; Lake West Okoboji, Spirit Lake, Lake East Okoboji (including Upper Gar Lake and Lake Minnewashta) and Lower Gar Lake. Each of these lakes has summer algal problems ranging from mild to nusiance conditions as indicated by the chloro phyll a values in Table 2. Algal problems are most serious in Lower Gar Lake and Lake East Okoboji where blue-green algal blooms occur throughout the summer. The problem is least ser ious in Lake West Okoboji and is usually localized by wind concentration of blue-green algal cells. Algal concentrations in Spirit Lake are somewhat intermediate between these ex tremes. Thomas (1953) used the difference between winter and sum mer alkalinities in epilimnion waters as an index to the state Table 2. Summary comparison of Lake West Okoboji, Spirit Lake, Lake East Okoboji (including Upper Gar Lake and Lake Minnewashta) and Lower Gar Lake of mean summer (1971, 1972, 1973) values for total phosphorus, nitrate nitrogen, ammonia nitrogen, chlorophyll a, chemical oxygen demand and Secchi disk transparency Lake West Spirit Lake East Lower Gar Okoboj i Lake Okoboj i Lake Total P mg/1 0.033 0.041 0.165 0.222 NOj-N mg/1 0.009 0.017 0.085 0.145 NHj-N mg/1 0.110 0.239 0.468 0.644 Chlorophyll a mg/m' 4.3 27.5 122.2 226.8 Chemical oxygen 20.5 24.9 46.5 56.5 demand mg/1 Secchi disk 3.2 1.7 0.9 0.4 transparency (m) 21 of eutrophication of a lake. The greater this difference, the more eutrophic the lake. From seasonal alkalinity differences. Lake West Okoboji is the least eutrophic lake with a differ ence (winter to summer) of less than 10 mg/1. Spirit Lake has a difference of about 50 mg/1 and lakes East Okoboji and Lower Gar have differences from 80-165 mg/1. Forney (1957) attri butes this cyclic tendency for high winter alkalinities and low summer values to the utilization of carbonate forms during periods of biological activity and subsequent return to solu tion during reduced activity. Past changes within the lake system One change within this system is a change in the hypolim- netic oxygen deficit in Lake West Okoboji during the past 50 years. In other lakes the extent and rate of oxygen loss from the hypolimnion is taken as a measure of the state of lake eutrophication. An increase indicates an increase in the state of eutrophication. It is assumed that the delivery rate of oxidizable organic materials to the hypolimnion is propor tional to the rate of epilimnetic production; hence the greater the productivity, the greater the oxygen deficit (Edmondson, 1966; Bazin and Saunders, 1971). Oxygen data from Lake West Okoboji were examined to determine possible changes. Available oxygen profiles fall into two separate time periods, 1919-1928 (past data) and 1950-1973 (recent data). Most of the early oxygen data was 22 taken from an unpublished notebook of Dr. F. Stromsten. The original data from various sources are given in Eachmann and Jones (1974). For comparative purposes, summer oxygen pro files were separated into six periods of 10 to 15 days begin ning June 15 and ending August 21. Mean oxygen profiles within these time periods are plotted in Figure 6. Because of insufficient data, oxygen concentrations below 30 m were not included in the analysis. Comparing recent to past oxygen profiles, less oxygen is currently present at various depths below the thermocline (10 m). A t-test analysis was used to determine significant differences between mean past and recent oxygen concentrations from the various profile depths. Corresponding means that differ significantly are indicated by standard error bars in Figure 6. In July recent oxygen concentrations below the thermocline are significantly less than past values at all depths but one (30 m, July 1-10). In August recent oxygen concentrations at the upper hypolimnetic depths of 15, 20 and 25 m are significantly less than past concentrations. By late summer, oxygen depletion is almost complete at 30 m in both past and recent profiles. To test the possibility that temperature differences in the early summer may have caused hypolimnetic oxygen differ ences, t-tests were run of the mean differences between past and recent temperature values for June 15-30. These were non- 23 OXYGEN MG/L OXYGEN MG/L JUNE 15-30 JULY l-IO (O CO sc W 10 bJ fh20 25 25 30 30 OXYGEN MG/L OXYGEN MG/L JULY 11-21 JULY 21-31 10 - 15 - &20 25 30 30 Figure 6. Average dissolved oxygen concentrations at 5 m depth intervals in Lake West Okoboji during June- August 1919-1928 (dashed line) and 1950-1973 (solid line). Standard error bars indicate means are significantly different at a given depth 24 OXYGEN MG/L OXYGEN MG/L AUG l-IO AUG 11-21 I- 10 IW 20 25 25 30 30 Figure 6. (Continued) 25 significant. It is concluded that increased biological activ ity in the hypolimnion is responsible for the oxygen differ ence found. The hypothesis that increased algal productivity in the epilimnion is responsible for this change is supported by the finding that epilimnetic oxygen concentrations are greater in 1950-1973 than they were in 1919-1928 (July 21 through August 10). Again water temperatures could not account for this dif ference since recent, average temperatures for this period are slightly higher (22.9 C) than those measured in 1919-1928 (21.2 C). This difference is statistically significant and would tend to make the recent oxygen concentrations lower rather than higher on the basis of solubility laws. Higher rates of photoçynthetic oxygen production in the epilmnion in recent years could account for these higher oxygen values. Oxygen deficits (mg/cm 2) were calculated for periods dur ing the summer by determining the oxygen saturation value between the thermocline (10 m) and 30 m from the mean tempera ture curves for June 15-30, 1923-1928 and 1950-1973. By using the saturation values for those temperatures and the volume- depth curve for the lake the calculated hypclimnetic oxygen content at the onset of saturation was 685,500 kg in 1919-1928 and 684,000 kg in 1950-1973. Kypolimnetic oxygen content was then calculated for past and recent mean oxygen profiles with in each of the six time blocks between June 15 and August 21. 26 These values were subtracted from their respective initial saturation value and divided by the surface area of the 10 m 2 contour (716 ha) to yield areal oxygen deficit values (mg/cm ) (Figure 7). Comparing summer oxygen deficits within the six time blocks, initial values are similar but by July the 1950- 1973 deficits are 50% greater than 1919-1928 values. The August oxygen deficit values converge as hypolimnetic oxygen is exhausted and no further oxygen consumption is possible. Hypolimnetic oxygen utilization results from decomposi- tional consumption of materials produced within and washed to the lake from its watershed. These materials settle into the hypolimnion resulting in an oxygen deficit. If recent deliv ery of organic material to Lake West Okoboji is unchanged from the 1919-1928 period, the increased oxygen deficit would re sult from an increased productivity of the surface waters during the past 50 years. The magnitude of this increased oxygen deficit could be as much as 50%. A second biological change in Lake West Okoboji was the decline of mollusk diversity and abundance. The rich mollus- can fauna described by Shimek (1913b,1915) decreased by the 1 O % N C RCVKTFNAV- L O % C ^ TT1 1II/I O/I ^ W ^ AX ^ ^ ^ W ^ W W y ^ A WW from snails collected between 1954 and 1959 that from 25 to 40 additional species were found in the lake during the first quarter of this century which are not present today. This decline may have been in response to human pollution (Shimek, 27 7 1950-1973 6 5 1919-1928 4 3 oX 15-30 l-IO 11-20 21-31 l-IO 11-21 JUNE JULY JULY JULY AUG AUG 2 Figure 7. Oxygen deficit values (mg/cm ) from Lake West Okoboji for periods between June and August 1919-1928 and 1950-1973 28 1935; Bovbjerg and Ulmer, I960]. The most obvious change within the lake system occurred in Lake East Okoboji and the Gar lakes. Shimek (1915) and Pammel (Iowa State Highway Commission, 1917) found emergent and submersed vegetation so abundant in these lakes that they were marsh-like at the beginning of this century. Recent studies (Volker and Smith, 1965; Crura and Bachmann, 1973) show emergent vegetation has almost disappeared and submersed plants are restricted to shallow water along the shores. The plants have subsequently been replaced by blue-green algae. Detailed limnological studies on these lakes during the period of change in the plant distribution are lacking, making it im possible to assign a cause to those changes. Many references are made to changes taking place within the Lake East Okoboji system (Wylie, 1920; Shimek 1913a; Wieters, 1928; Kelley, 1926; Francis, 1930) without delineating the nature of this change. It is estimated the blue-green algae problem developed between 1920-1930 (Gale et ^., 1972). Crum and Bachmann (1973) con cluded planktonic algal blooms developed concurrent with the installation of a water-control structure about 1920 on the Outlet of Lower Gar Lake. Discussion Cultural eutrophication has had an alarming effect on the limnological conditions of many water bodies in recent years. Many lakes have changed from oligotrophic to eutrophic in a 29 matter of decades, a process that occurs naturally over thou sands of years. There was concern that this accelerated process was taking place within the Iowa Great Lakes and was responsible for water quality differences among the lakes. Usually cultural eutrophication is associated with sewage effluents as was the case in Lake Zurich and Lake Washington. In the Iowa Great Lakes watershed, however, sewage has a mini mal influence on water quality because most areas are sewered and the effluent is transported outside the watershed. Although the Iowa Great Lakes are presently eutrophic there is reason to believe they have been eutrophic for several thousand years. There are no physical or floristic changes in the sediments of Lake West Okoboji indicative of severe changes in the sedimentation rate or trophic level of the lake, even in recent deposits, which would reflect changes due to the activities of man (Stoermer, 1963; Collins, 1968; Dodd, 1971). The diatom flora of the sediment of Lake West Okoboji is characterized by taxa normally associated with eutrophic waters, indicating a long-term eutrophic condition. Because Lake West Okoboji is the deepest lake, it likely was the last lake within the watershed to undergo a trophic advance ; thus, it is reasonable that the other watershed lakes were eutrophic before Lake West Okoboji. Limnological changes have taken place within the Iowa Great Lakes since the turn of this century. The increased 30 hypolimnetic oxygen deficit in Lake West Okoboji during the past 50 years likely reflects a greater productivity in the surface waters, indicating increased eutrophication. The decreased molluscan fauna of this lake could have been in response to an environmental change, possibly from human activity (Shimek, 1935; Bovbjerg and Ulmer, 1960). The re placement of aquatic macrophytes in Lake East Okoboji by blue- green algae could be a sign of eutrophication or could be re lated to the stabilized water levels after the outflow struc ture was constructed (Crum and Bachmann, 1973). Without docu mentation it is impossible to determine what brought about these changes. Whatever the cause the rate of change is not comparable to lakes Washington, Erie and Zurich. An obvious correlation exists between the algal standing crops in each of the Iowa Great Lakes and the ratio of water shed area to lake volume. This relationship can also be ex tended to include mean depth (Tables 1 and 2). The lakes can be ranked by decreasing mean depth, increasing ratio of water shed area to lake volume and an increasing algal biomass. This order is: Lake West Okoboji, Spirit Lake, Lake East Okoboji, and Lower Gar Lake. The ratio of watershed area to lake volume can influence the nutrient load and the ultimate concentration of these nutrients achieved in lake water. Lakes act as collecting basins for water and dissolved materials delivered to them from their watershed. Lakes with small volumes will be influenced 31 more by watershed runoff than lakes with the same drainage area and a larger lake volume because a larger lake has more capacity for dilution. Nutrient budgets, estimating the annual load of nitrogen and phosphorus compounds delivered to each of the Iowa Great Lakes are presented in Part II. The influence these nutrient loads have on the algal conditions found in each lake are analyzed in Part III. 32 PART II. NUTRIENT BUDGETS AND WATERSHED LAND USE PRACTICES Results Nutrient budgets The ultimate effect of plant nutrients upon the water quality of the Iowa Great Lakes depends upon the annual input of these nutrients to each lake. Nutrient budgets were cal culated to determine the magnitude of the annual input of nitrogen and phosphorus to each of the studied lakes during 1971, 1972, and 1973. The major sources of nutrients con sidered in these budgets are the amounts of nitrogen and phosphorus carried in surface runoff from metered and un- metered watersheds and the amounts of these elements in rain fall on the lake surface. The nutrient inputs are broken down into three periods : March 1, 1971, to December 31, 1971; January 1, 1972, to December 31, 1972; and January 1, 1973, to July 1, 1973. Most of the annual runoff occurs each spring, and, because in 1971 many streams were frozen until after March 1, the input in the period from March to December, 1971, is considered as a good approximation of the annual nutrient input during calen dar year 19 71 in lakes West Okoboji, East Okoboji and Spirit. Determinations of total phosphorus were not started until September, 1971. To express the 1971 phosphorus input as total phosphorus, the relationship was examined between ortho- phosphate phosphorus concentrations and total phosphorus con 33 centrations. A regression of total phosphorus on orthophos phate phosphorus was calculated by using data from 750 stream samples on which both measurements had been made. The coeffi cient of correlation between the two variables was 0.83. The regression equation was: = 0.035 + 1.68 Pq where P^ is the concentration of total phosphorus in mg/1 and PQ is the concentration of orthophosphate phosphorus in mg/1. All of the March-September, 1971, measurements of orthophos phate phosphorus were converted to total phosphorus by using this equation. The total amount of each of the nutrients delivered by the separate streams was calculated as follows, using phos phorus as an example. For each station on each sampling date, the concentration of phosphorus was multiplied by the flow. The same was done for the next sampling date, and the mean value of the concentration times flow for the two dates was multiplied by the number of days between samples. The re sult was then multiplied by the number of seconds in a day because flows were in cubic meters per second. This was done for each of the three time periods to get annual phosphorus inputs for 1971, 1972, and January-July, 1973. This same integration procedure was used for nitrate and ammonia nitro gen. The areas of the metered and unmetered watersheds for 34 each lake are given in Table 3. The metered streams covered only a portion of the total watershed area. To estimate the inputs from the unmetered area, the input from the metered area was multiplied by the area of the unmetered portion, divided by the area of the metered portion. The sum of the metered and unmetered watershed inputs represented the total annual terrestial input to the respective lakes. The contribution of nitrogen and phosphorus from rainfall was estimated by calculating the total volume of rainfall on each lake, based on lake surface area and total precipitation. This was multiplied by the mean nitrate nitrogen, ammonia nitrogen, and total phosphorus concentrations in rainwater (Table 4). These mean nutrient concentrations are within the range of values found across the United States (Junge, 19 58; Carroll, 1962; Weibel, 1969). Concentrations of inorganic nitrogen and phosphorus in rainwater are expectedly high over areas of intensive farming (Allan e^ al., 1968), such as the Okoboji area. Precipitation on the lake surface contributed 2 2 0.032 gm/m phosphorus and 0.83 gm/m nitrogen annually during 1971-1973. This is within the range of 0.015-0.060 gm/m^ P and 0.18-0.98 gm/m 2 N delivered to lakes by rainfall in other studies (Vollenweider, 1968). The estimated nutrient inputs during the three periods are given for Lake West Okoboji (Table 5), Spirit Lake (Table 6), Lakes East Okoboji, Upper Gar, and Minnewashta (Table 7), 35 Table 3. Breakdown of metered and unmetered watershed areas (ha) of Lake West Okoboji, Lake East Okoboji. Spirit Lake, Lower Gar Lake, and Loon Lake West East Spirit Lower Loon Okoboj i Okoboj i Gar Total area 6158 5078 7794 4622 7935 Metered 4196 3303 2538 3996 - - Unmetered 1962 1775 5256 626 mm — Table 4. Means and standard errors of the mean for phos phorus, nitrogen, turbidity and specific conduc tance measurements made on rainwater collected at Iowa Lakeside Laboratory between June 24, 1871, and August 7, 1973 PO^-P Total P NHg-N NO^-N JTU Spec. Cond. N 36 29 36 36 32 10 00 X .04 .05 cn .47 3.3 29.1 0 o Std. .01 .01 0 .12 .8 5.7 error Table 5. Estimated total phosphorus, nitrate nitrogen, and ammonia nitrogen inputs (kg) to Lake West Okoboji from metered watershed, unmetered watersheds and rainfall in 1971, 1972 and the first 6 months of 1973 Lake West Okoboji Total P kg Nitrate nitrogen kg Ammonia nitrogen kg 1971 1972 1973 1971 1972 1975 1971 1972 1975 Metered 1667 558 1415 14412 15609 55495 4142 1565 5919 watersheds Unmetered 922 267 661 7970 6505 15642 2290 652 1850 watersheds Rainfall 551 608 523 4994 5718 5040 9032 10341 5498 Total 3120 1433 2399 27376 25852 52177 15464 12558 11247 Table 6. Estimated total phosphorus, nitrate nitrogen, and ammonia nitrogen inputs (kg) to Spirit Lake from metered watersheds, unmetered water sheds, rainfall, and the Loon Lake outlet in 1971, 113 72 and the first 6 months of 1973 Big Spirit Lake Total P kg Nitrate nitrogen kg Ammonia nitrogen kg 1971 1972 1973 1971 1972 1973 1971 1972 1973 Metered 1627 977 891 29784 24303 39965 3259 1962 2236 watersheds Unmetered 3173 1905 1737 58079 47391 77932 6355 3826 4360 watersheds Rainfall 748 856 455 7031 8050 4280 12715 14558 7740 Loon Lake 1685 601 530 14907 1048 2242 13030 2065 2250 outlet Total 7233 4339 3613 109801 80792 124419 35359 22411 16586 Table 7. Estimated total phosphorus, nitrate nitrogen, and ammonia nitrogen inputs (kg) to Lake East Okoboji from metered watersheds, unmetered watersheds, rainfall and the Spirit Lake Outlet in 1971, 1972 and 1973 Lake East Okoboji Upper Gar, Minnewashta) Total P kg Nitrate nitrogen kg Ammonia nitrogen kg 1971 1972 1973 1971 1972 1973 1971 1972 1973 Metered 2815 1087 1745 31575 29518 51471 5375 2642 4043 watersheds Unmetered 1621 587 937 18187 15940 27640 3096 1427 2171 watersheds Rainfall 285 330 173 2676 3102 1629 4841 5610 2947 Spirit Lake 402 71 234 350 63 1056 2900 278 2058 Outlet Total 5123 2075 3089 52788 48623 81796 16212 9957 11219 Table 8. Estimated total phosphorus, nitrate nitrogen, and ammonia nitrogen inputs (kg) to Lower Gar Lake from metered watersheds, unmetered watersheds, and rainfall in 1971, 1972, and the first 6 months of 1973 Lower Gar Lake Total P kg Nitrate nitrogen kg Ammonia nitrogen kg 1971 1972 1973 1971 1972 1973 1971 1972 1973 Metered 624 697 687 6089 9488 15234 2064 1994 2900 watershed Unmetered 98 109 108 956 1490 2392 324 313 455 watershed Rainfall 338 387 21 318 364 194 575 658 350 Total 1060 1193 816 7363 11342 17820 2963 2965 3705 39 and Lower Gar Lake (Table 8). Upper Gar Lake and Lake Minne- washta are combined with Lake East Okoboji because they have no tributary streams flowing into them. There are differences in the annual nutrient budgets for the respective lakes from year to year. This, in part, is explained by differences in annual surface runoff from the watersheds. The output of plant nutrients and water from the watersheds are summarized in Figure 8. For each year separate consideration is given to the interval preceding July 31 (Period I) and after July 31 (Period II). In general, the runoff and nutrient losses by the watersheds during Period I of 1972, were half the 1971 and 1973 values, whereas about twice the amount of nutrients and water were delivered from the watersheds during Period II of 1972 as during Period II of 1971. The spring runoff period in the first half of the year seems to make the major contribution of plant nutrients to the lake system. An extensive sampling program would be required to meas ure nutrient contributions from storm sewers. In the esti mated nutrient budgets, the urban areas were considered to contribute the same amount of phosphorus and nitrogen per unit area as did the agricultural watersheds. This probably was an underestimate, because storm waters were rich in plant nutri ents. Total phosphorus averaged 0.56 mg/1 P, ammonia nitrogen averaged 1.21 mg/1, and nitrate nitrogen averaged 1.83 mg/1. 40 6 TOTAL P 4 I03 KG 2 0 tznzj 1———J 160 120 NO3-N se 10^ KG 40 12 NH3-N 8 iô- KG 4 0 fc==d 24 18 WATER 12 10® 6 0 l=d 171 1171 172 31l72 173 Figure 8. Output o£ plant nutrients and water from the Iowa Great Lakes metered watersheds in 1971, 1972, and 41 Approximately 4% of the watershed area is urban and served by- storm sewers draining to lakes West Okoboji, East Okoboji and Minnewashta. Using the average nutrient concentration of stormwater and assuming 25-50% of the precipitation on urban areas flowed through the storm-water system, an estimate of their contribution to the nutrient budget of these lakes would be 3-6% of the phosphorus input and 1-3% of the inorgan ic nitrogen input. On this basis storm water was not a major source of plant nutrients. Factors associated with differences among tributaries There were differences in the concentrations of phos phorus and inorganic nitrogen among the various tributaries to the Iowa Great Lakes. These differences were noted early in the study and seemed to persist throughout the sampling period. Some tributaries were noteworthy for high phosphorus concen trations, others had high nitrogen concentrations, and other drainages had low or intermediate concentrations of these ele ments. The mean concentrations of total phosphorus, nitrate nitrogen and ammonia nitrogen for 35 sampling stations are given in Table 9 for the three years of study. A statistical procedure was used to determine if differ ences in nitrogen and phosphorus among streams could be re lated to land-use practices within the respective watersheds. A general summary of the land-use within the Iowa Great Lakes watershed is given in Figure 9. The detailed breakdown for Average concentrations (mg/l) of total P, NO3-N, and NH3-N during 1971, 1972 and 1973 for 35 stream sampling stations within the Iowa Great Lakes Watershed Total P NO3-N NH3-N 1971 1972 1973 1971 1972 1973 1971 1972 1973 1 1.04 0.47 0.35 3.80 6.32 7.10 1.63 1.09 0.64 2 0.11 0.01 0.05 0.21 0.53 10.19 0.02 0.01 0.14 3 0.38 0.25 0.35 1.44 4.19 2.30 0.69 0.25 0.57 5 0.11 0.25 0.09 3.43 2.92 3.51 0.67 0.56 0.73 6 0.15 0.09 0.11 0.15 0.11 0.10 0.84 0.64 0.91 8 0.43 0.45 0.33 7.45 10.52 12.81 0.91 1.52 0.83 9 0.21 0.21 0.16 7.96 12.85 12.38 0.20 0.21 0.41 10 0.22 0.25 0.16 5.14 5.53 9.59 0.44 0.44 0.28 11 0.18 0.50 0.13 4.97 6.54 9.17 0.40 0.77 0.25 12 0.27 0.22 0.28 1.52 0.62 0.93 0.41 0.29 0.69 13 0.20 0.17 0.14 5.12 6.24 7.35 0.24 0.11 0.17 ^ 15 0.57 0.18 0.47 3.13 2.82 5.58 0.95 0.24 0.74 w 16 0.28 0.17 0.14 3.89 3.33 7.93 0.28 0.17 0.21 17 0.62 0.61 0.59 1.04 1.77 0.94 1.09 1.08 1.04 18 0.31 0.22 0.25 2.26 4.88 5.60 0.65 0.21 0.65 IV 0.30 0.17 0.14 3.17 4.04 8.00 0.51 0.37 0.26 22 0.17 0.14 0.25 4.49 5.90 7.27 0.52 0.44 0.59 23 0.17 0.10 0.09 .276 1.95 4.20 0.42 0.21 0.18 24 0.25 0.18 0.16 3.71 5.15 5.69 0.14 0.07 0.15 28 0.92 0.71 0.78 4.54 6.65 4.74 1.46 0.53 2.44 29 0.28 0.13 0.13 0.23 0.14 0.29 0.93 0.51 0.61 30 0.08 0.11 0.27 1.67 1.22 1.00 0.17 0.11 0.53 31 0.24 0.12 0.13 5.46 7.16 4.48 0.32 0.08 0.17 32 0.28 0.32 0.21 0.05 0.04 0.07 0.39 0.24 0.37 33 0.17 0.07 0.11 2.76 3.14 5.11 0.28 0.12 0.26 34 0.17 0.10 0.04 5.46 9.10 10.32 0.31 0.10 0.10 38 0.55 0.37 0.36 2.74 4.80 7.06 0.77 0.49 0.48 39 2.76 8.18 3.52 3.74 8.00 3.85 2.72 0.73 8.00 Table 9. (Continued) Total P NO3-N NH3-N Station 1971 1972 1973 1971 1972 1973 1971 1972 1973 40 0.39 0.16 0.19 3.37 4.95 7.49 1.01 0.93 0.55 41 0.34 0.08 0.23 H. 24 9.49 9.40 0.75 0.21 0.77 42 2.96 1.33 2.40 2.52 1.90 4.18 4.65 0.89 6.32 44 0.13 0.10 0.07 5.37 7.92 9.97 0.29 0.37 0.26 46 0.23 0.13 0.21 5.11 10.03 10.97 0.30 0.15 0.25 47 0.21 0.12 0.15 5.94 7.91 8.40 0.28 0.06 0.23 48 0.20 0.19 0.14 1.69 2.37 2.78 0.67 0.56 0.60 43 GRASSLANDS LAKES a PONDS URBAN MARSH Figure 9. Distribution of land use practices in the Iowa Great Lakes watershed 44 each of the watersheds is given in Bachmann and Jones (1974). The number of hectares of row crops, grasslands, and marsh lands were divided by the watershed areas and multiplied by 100. This yielded percentage values that could be used to compare different watersheds. The number of animal units within different watersheds were divided by the areas to yield livestock densities in animals per hectare. In a multiple regression analysis, the concentration of phosphorus (mg/1) of the watersheds in Table 9 were used as dependent variables. The independent variables were animal units per hectare, and percentages of each watershed in row crops, pastures, and marshland. The independent variables were used separately and in all possible combinations in a series of multiple linear regression calculations against phosphorus concentration for the three years of study. Each calculated regression was tested using t-tests of the hypothe sis that the slopes were not different from zero. The 1% confidence limit was the criterion for significant difference. The number of animal units per hectare was the only inde pendent variable significantly related to phosphorus concen tration differences among streams. The coefficients of corre lation (r) were 0.78, 0.65, and 0.75 for 1971, 1972, and 1973. The calculated regression equations are; P7I = 0.158 + 0.498A P72 = -0.040 + 0.878A P73 = 0.072 + 0.511A 45 where P is the mean phosphorus concentration (mg/1) and A is the number of animal units per hectare. A second multiple regression analysis to test the phos phorus and animal unit relationship used the phosphorus output in kilograms per hectare for the 17 watersheds greater than 100 hectares (Table 10). The dependent variable, phosphorus (kg/ha) was determined by integrating the flow and phosphorus concentration measurements over time to yield annual phos phorus outputs from each watershed which were divided by the respective watershed area to yield annual outputs in kilograms per hectare. Percentages in each watershed of row crops, pasture, marshland and the animal units per hectare were used as independent variables. Phosphorus (kg/ha) differences between watersheds were significantly related to the number of animal units in each watershed, none of the other variables was found significant. Coefficients of correlation between animal units and phos phorus load (kg/ha) for 1971, 1972, and 1973, were 0.79, 0.64 and 0.71. The calculated regression equations are: P7I = 0.175 + 1.043A P72 = 0.136 + 0.269A P73 = 0.189 + 0.344A where P is the phosphorus load in kilograms per hectare, and A is the number of animal units per hectare. A multiple regression analysis was used to test the rela tionship between phosphorus losses (kg/ha) in these 17 water- Nutrient inputs for the 17 watersheds over 100 hectares used in the regression analysis. Values of total P, NO3-N and NH3-N for 1971, 1972, and 1973 are expressed in kilograms per hectare per year Total P NO3-N NH3-N 1971 1972 1973 1971 1972 1973 1971 1972 1973 1 2.86 0.68 0.89 10.40 9.20 17.96 4.45 1.58 1.61 5 0.47 0.24 0.09 14.31 2.78 3.38 2.81 a. 53 0.71 6 0.49 0.04 0.17 0.50 0.05 0.16 2.74 0.29 1.41 8 0.96 0.45 0.64 16.62 10.56 25.31 2.03 1.53 1.64 10 0.46 0.41 0.21 10.91 9.03 12.34 0.93 0.72 0.37 11 0.23 0.53 0.18 6.65 6.91 12.32 0.54 0.81 0.34 18 0.50 0.10 0.43 3.65 2.11 9.51 1.04 0.10U.IU 1.10i.iu ^ 19 0.72 0.21 0.34 7.68 4.88 19.89 1.24 0.45 0.66 22 0.32 0.23 0.48 8.32 9.68 14.09 0.96 0.73 1.14 23 0.38 0.24 0.18 6.33 4.68 8.67 0.95 0.50 0.37 29 0.36 0.06 0.18 0.29 0.07 0.42 1.17 0.24 0.86 33 0.38 0.10 0.39 5.99 5.83 18.12 0.61 0.17 0.94 34 0.06 0.01 0.02 1.85 0.54 5.77 0.11 0.01 0.05 38 1.29 0.60 0.67 6.42 7.84 13.08 1.80 0.80 0.89 40 0.68 0.23 0.33 5.91 6.98 13.15 1.77 1.32 0.96 41 0.90 0.14 0.55 21.55 16.09 21.81 1.97 0.36 1.78 48 0.15 0.17 0.17 1.30 2.09 3.37 0.51 0.49 0.73 47 sheds and the number of animal units 1) in feedlots with drainage to streams or tiles, 2) in pastures with drainage to streams or tiles, 3) in feedlots with no drainage to streams or tiles and 4) in pastures with no drainage to streams or tiles. Each independent variable in the four categories (Table 11) was divided by the watershed area to yield pastured or feedlot animal units per hectare. All combinations of independent variables were tested. The only significant correlation was found with animals in feedlots with drainage to streams or tiles. Coefficients of correlation (r) between phosphorus loss (kg/ha) and feedlot animal units per hectare with drainage were 0.89, 0.56, and 0.75 (Figures 10 and 11). This strong relationship between animal units held in feedlots where drainage enters a stream or tile and watershed phosphorus output is not unique. Others have found surface runoff from livestock feedlots high in phosphorus concentra tion (Miner et al. , 1966; McCalla e^ al. , 1969; Gilbertson e;t al., 1970; Taylor et aJ., 1971; U.S. EPA, 1971; Edwards et al., 1972). The phosphorus load is reduced by the amount of lake area within the watershed. Evidence for this relationship comes from the annual phosphorus output of 0.07 kg/ha in 1972 from the Loon Lake watershed, and 0.06 kg/ha was lost from the watersheds of lakes West Okoboji, East Okoboji, Spirit and the Gars in 1972. The annual phosphorus output from the metered Animal units per hectare in seventeen watersheds separated into pasture animal units with drainage to a stream or tile, pasture animal units without drainage, feedlot animal units with drainage to a stream or tile and feedlot animal units without drainage Pasture animal Pasture animal Feedlot animal Feedlot animal units without units with units with units without drainage drainage drainage drainage 0 0.161 1.75 0 5 0 0 0 0 6 0 0 0 0 8 0.038 0 0.713 0.040 10 0 0.241 0 0.050 11 0.003 0.008 0.140 0.809 18 0.122 0.066 0.089 0.209 19 0 0.004 0 0.025 22 0.102 0.052 0 0.215 23 0.072 0.096 0 0 29 0.027 0.108 0.065 0.087 33 0.027 0.021 0 0.007 34 0.030 0 0 0 38 0.044 0.058 0.092 0.194 40 0 0.154 0.270 0.246 41 0 0.044 0.680 0.203 48 0.031 0.121 0.015 0.095 49 1971 r« 0.89 CO 0 2 FEEDLOT ANIMAL UNITS/HECTARE Figure 10. The regression of phosphorus output (kg/ha) on feedlot animal units/ha for 17 watersheds in the Iowa Great Lakes area in 1971 50 0.8 1972 ' r • 0.56 • 0.6 -• • • ». w oc < t- o W 0.2 jT • >. • o h: (r# ' » H 3 a. 1973 H 3 " r»0.75 O 0.8 - (O 3 oc • • X 0.6 a. tn o 0.4 0.2 & 0 0 I 2 FEEDLOT ANIMAL UNITS/HECTARE Figure 11. The regression of phosphorus output (kg/ha) on feedlot animal units/ha for 17 watersheds in the Iowa Great Lakes area in 1971 and 1972 51 watersheds surrounding the lakes was 0.24 kg/ha in 1972, 0.46 kg/ha in March-Jan., 1971, and 0.34 kg/ha in Jan.-July, 1973. This terrestrial phosphorus loss is several times the phos phorus loss from the entire watershed, providing further evi dence that lakes retain phosphorus (Vollenweider, 1968). The retention of nitrogen by the lake system cannot be estimated inasmuch as total nitrogen was not measured, and the contribu tion to the nitrogen budget from nitrification by blue-green algae is not known, nor is loss by denitrification known. Statistical tests were used to determine if nitrate and ammonia nitrogen differences among stations also were related to land-use practices. Land-use categories used in the phos phorus analyses also were used as independent variables in nitrogen analyses. A multiple-regression analysis was conducted using ni trate nitrogen concentrations (mg/1) from 35 stream stations as the dependent variable (Table 9). For 1971. 1972 and 1973 the two variable model containing percentage in marshes and in pastures controlled a significant amount of the variation in 2 nitrate nitrogen in each year. The R values were 0.38, 0.30 and 0.56 respectively. À multiple linear regression was tested of nitrate load (kg/ha) for 17 metered watersheds larger than 100 hectares (Table 10). For 1971, 1972, and 1973 a significant negative correlation was found with percentage of watersheds in marsh lands. The correlation coefficients were -0.54, -0.63, and 52 -0.73. None of the multiple variable models were significant. No significant relationship was found between nitrate nitrogen and animal units held in pastures or feedlots. In a multiple regression of ammonia concentrations (Table 9) as the dependent variable upon the percentage of watershed in row crops, pasture and marshland and the number of animal units per hectare, a significant positive correlation was found with animal units per hectare in 1971, 1972, and 1973. The respective coefficients of correlation were 0.73, 0.45, and 0.79. With ammonia nitrogen values (kg/ha) from the 17 largest watersheds (Table 10) as the dependent variable and animal units/ha and land-use categories as independent variables, a significant relationship with animal units was found (the 1973 value was significant at the 2% level). The coefficients of correlation in 1971, 1972, and 1973 were 0.58, 0.68, and 0.55. An analysis of animal units broken down into pastures and feedlots with or without drainage (Table 11) compared with ammonia nitrogen (kg/ha) yielded a positive correlation with feedlot animal units per hectare with drainage to a stream or tile inlet. The coefficients of correlation for 1971. 1972, and 1973 were 0.73, 0.67, and 0.63. The calculated regression equations are: NH37I = 1.11 + 1.74A NH372 = 0.47 + 0.69A NH373 = 0.74 + 0.70A 53 where NH^ is the ammonia nitrogen load in kilograms per hec tare, and A is the number of animal units per hectare in feed- lots with surface drainage. Statistically, livestock held in feedlots with surface drainage to a stream or tile intake have been identified as a source of phosphorus and ammonia nitrogen in the tributaries of the Okoboji lakes. It is, therefore, proposed that a live stock waste-control program aimed at preventing feedlot drain age from entering the lakes would reduce the input of these nutrients. Such a reduction would likely have the beneficial effect of reducing the algal standing crop (Edmondson, 1961, 1969, 1970, 1972; Vollenweider, 1968). An estimate of the effectiveness of such an abatement program, by subtracting the nutrient contributions of feedlots in the watershed from the nutrient budgets during 1971, 1972 and 1973 is worthwhile. The slope of the regression equations between phosphorus and feedlot animal units per hectare [Fig ures 26 and 27) indicates 1.27 kg P, 0.25 kg P, and 0.39 kg P per feedlot animal unit were lost from the watersheds in 1971, 1972 and 1973. The phosphorus contribution from feedlot ani mal units was calculated by multiplying the total number of feedlot animal units having surface drainage in each lake watershed by the slope of the regression line (Table 12). In Table 12 the phosphorus attributed to feedlot animals as a percentage of phosphorus from all sources and as a percentage of phosphorus from terrestial sources is given. An abatement Table 12. Amount of phosphorus attributed to feedlot animals, and total phos phorus from feedlot animals as a percentage of phosphorus from all sources and as a percentage of phosphorus from the terrestrial watersheds Amount of Phosphorus attributed Phosphorus attributed phosphorus to feedlot animals as to feedlot animals as attributed a percentage of phos a percentage of phos to feedlot phorus from all phorus from terrestrial Lake animals sources watersheds West Okoboji 1971 643 kg 21% 25% 1972 127 kg 9% 15% 1973 197 kg 8% 9% West Okoboji 1971 1459 kg 29% 33% 1972 287 kg 14% 17% 1973 448 kg 15% 17% Spirit Lake 1971 1144 kg 16% 24% 1972 225 kg 5% 8% 1973 351 kg 10% 13% Lower Gar Lake 1971 94 kg 9% 15% 1972 19 kg 2% 3% 1973 29 kg 4% 4% 55 program would concentrate on reducing terrestrial phosphorus sources because little can be done to control phosphorus in rainfall. Had an abatement program been conducted that prevented feedlot runoff from entering the lakes before 1971, phos phorus output from the terrestrial watersheds of lakes West Okoboji, East Okoboji and Spirit would have been reduced by approximately 27% in 1971, 13% in 1972 and 13% in 1973. Of the total nutrient budget for each lake (including rainfall and flow from other lakes) this represents a 22%, 9% and 11% reduction for the respective periods. An abatement program would have been most effective on Lake East Okoboji. In 1971, the phosphorus budget to this lake would have been reduced by 29%, and in 1972 and 1973, a 15% reduction would have resulted. In Lakes West Okoboji and Spirit, such a program would have reduced the phosphorus load by about 20% in 1971, and 8% in 1972 and 1973. Little effect would be derived from an abatement program in the Lower Gar Lake watershed because only 2-9% of the incoming phosphorus during 1971-1973 is attributed to feedlot animals. During the study, a control structure designed to entrap feedlot runoff in an earth lagoon was built on a feedlot con taining 211 animal units with drainage to a stream (Station 1). Runoff is either pumped to a nearby grassland or allowed to evaporate. Construction began in September, 1972, and was completed in December, 1972. The lagoon seems to have had a 56 measurable effect on phosphorus and ammonia nitrogen outputs from this watershed (136 ha). Total phosphorus concentration in the stream dropped from a mean of 1.64 mg/1 P preceding September, 1972, to 0.42 mg/1 P from December, 1972, to August, 1973. Mean ammonia nitrogen concentration dropped from 1.85 mg/1 to 0.62 mg/1 after diversion of the feedlot runoff. Discussion The nutrient budgets are not complete, but are estimates of the amounts of nitrogen and phosphorus entering the lake system over a 29-month period. One contributing factor omit ted from the budget was the addition of nutrients to the sys tem by groundwater. This is a difficult source to quantify and, by necessity, has been left out of this analysis. Cot tages on lakes East Okoboji and Spirit not served by the sani tary sewer system may contribute nutrients through leaching of septic tank effluents, but this source could not be measured. Also no consideration was given to nitrogen fixation by blue- green algae or bacterial denitrification. Other unmeasured losses would be fish removal, insect emergence, and the with drawal of municipal water supplies from lakes West Okoboji and Spirit. The exchange of water between lakes East and West Okoboji could not be measured, nor could the contribution of water from Lake East Okoboji complex to Lower Gar Lake. A more comprehensive program would be required to measure exact ly the nutrient contributions of the storm sewers in the 57 region. Despite these omissions, the nutrient budgets are likely good estimates of the magnitude of nitrogen and phosphorus entering the respective lakes. An average of 0.35 kg/ha/yr was lost from the metered areas within the watershed. This is within the range of 0.18-1.0 kg/ha/yr found for runoff from pastures and cropland by other researchers (Vollenweider, 1968; Johnson e^ , 1965; Biggar and Corey, 1969). This annual phosphorus loss also compares with phosphorus outputs from the Des Moines River basin in Iowa. From July, 1971, to August, 1973, the average total phosphorus loss from this basin was 0.38 kg/ha/yr (Baumann, Oulman, and Naylor, 1973). From the analyses of watershed factors associated with nutrient loads, it seems that phosphorus and ammonia nitrogen are statistically related to animals in feedlots within the watershed. Phosphorus and ammonia nitrogen are present in high concentrations in feedlot surface drainages (Taiganides and Hazen, 1966; Pomeroy and Orlob, 1967; Vollenweider, 1968; Gilbertson e^ ^., 1970; Edwards e^ al., 1972; Martin and Goff, 1972). These nutrients are carried by runoff from feedlots to the lakes in stream flow or tile drainage. There are strong positive relationships between the concentration (mg/l) (r = 0.91) and losses (kg/ha) (r « 0.82) of phosphorus and ammonia from the metered watersheds. Phosphorus losses were greatest in 1971 and 1973, years of highest runoff and correlations between phosphorus outputs and animal units were greatest 58 these years. Feedlot animal units are identified with 3-33% of the terrestrial input of phosphorus to the respective lakes. Storm water drainage from urban areas within the watershed constituted approximately 5% of the phosphorus reaching the lakes. The remaining nutrient input from the terrestrial watershed, which accounts for 80% of phosphorus in the nutri ent budgets of the respective lakes, has not been identified with a specific source. Feedlot drainage without surface access to a stream or tile had little influence on the phosphorus or ammonia nitro gen load of a given watershed inasmuch as feedlots without surface drainage did not significantly describe any of the nutrient load in a multiple-regression analysis. This is likely because of the extreme insolubility of inorganic phos phate forms in soil solution and binding of ammonia nitrogen to cation exchange sites in soil (Biggar and Corey, 1969). For this reason, a nutrient abatement program within the water shed could be achieved by preventing feedlot surface drainage from reaching a stream or drainage tile intake. This would reduce the phosphorus and ammonia nitrogen inputs to the lakes. Such a nutrient reduction would expectedly have a bene ficial effect on water quality by reducing the standing crops of plankton algae (Edmondson, 1961, 1969, 1970, 1972; Vollen- weider, 1968). 59 PART III. RELATIONSHIP BETWEEN ANNUAL NUTRIENT INPUTS AND THE MAGNITUDE OF THE SUMMER ALGAL BLOOMS Results One factor controlling the algal standing crop in lakes is the concentration of inorganic nutrients, usually either nitrogen or phosphorus (Chu, 1943; Sawyer, 1947; Sakamoto, 1966a, 1966b; Schindler, 1971; Powers eit al., 1972). Recent research on reversal of eutrophication in Lake Washington indicated the annual input of plant nutrients is a major fac tor determining the summer standing crop of plankton algae (Edmondson, 1961, 1969, 1970, 1972). Vollenweider (1968) has set upper limits on annual inputs of nitrogen and phosphorus 2 per unit surface area (gm/m ) as a function of mean depth. He established dangerous surface loading values (gm/m ) above which an oligotrophic lake would expectedly degrade to eu- trcphy. Limnclogical vrcrk on ether lakes also indicated the importance of annual nutrient inputs to the growth of plankton algae (Megard, 1970; Schindler e^ al_. , 1971, Schindler et al., 1973; Shannon and Brezonik, 1972a, 1972b). For each of the Iowa Great Lakes the annual inputs of nitrogen and phosphorus have been estimated over a 3 year period. These annual nutrient inputs, taken as the total amount of phosphorus and inorganic nitrogen to enter a given lake were normalized by dividing by the respective lake volume to yield potential concentrations (Table 13), as suggested by Table 13. Maximum and mean July-August values of chlorophyll a for the Iowa Great Lakes. Potential concentrations of total phosphorus and inorganic nitrogen for Lake West Okoboji, Lake East Okoboji and Spirit Lake are calculated from total inputs between January 1 and July 31 divided by the volume of the respective lakes. The potential concentrations for Lower Gar Lake are based on the mean nitrogen and total phosphorus con- - centration of inflowing streams (Station 47 and 48). Values for Lake East Okoboji include Upper Gar Lake and Lake Minnewashta Mean Max imum July-August Potential Potential Chlorophyll a Chlorophyll a total P inorganic N mg/m3 mg/m3 mg/1 mg/1 1971 Lake West Okoboji 9.28 5.11 0.015 0.197 Spirit Lake 130.34 63.06 0.051 1.103 Lake East Okoboji 434.50 175.83 0.207 2.864 Lower Gar Lake 545.08 329.52 0.204 2.742 1972 Lake West Okoboji 4.92 3.64 0.006 0.147 Spirit Lake 20.35 9.16 0.029 0.579 Lake East Okoboji 496.96 88.69 0.072 1.663 Lower Gar Lake 309.03 133.16 0.224 3.468 1973 Lake West Okoboji 8.03 4.09 0.013 0.345 Spirit Lake 26.70 10.33 0.030 1.178 Lake East Okoboji 392.56 102.06 0.137 4.117 Lower Gar Lake 470.52 217.84 0.144 3.810 61 Edmondson (1961). This potential concentration can then be compared between lakes. Lake West Okoboji, with the smallest standing crop of plankton algae o£ the watershed lakes, had the lowest potential phosphorus and nitrogen concentrations. Lakes East Okoboji and Lower Gar have a higher algal biomass and had potential nutrient concentrations an order of magni tude higher than found in Lake West Okoboji. Algal conditions and potential nutrient concentrations in Spirit Lake are inter mediate between these extremes. The hypothesis was tested that annual nutrient inputs to the Iowa Great Lakes determine the differences in the magni tude of summer algal blooms. This was done by relating the potential concentrations of nitrogen and phosphorus calculated for each studied lake to the summer algal crop as estimated by chlorophyll a pigment. Potential nitrogen and phosphorus concentrations were cal culated for each of the Iowa Great Lakes in 1971, 1972 and 1973. The time period for 1972 and 1973, extended from Jan uary 1, to July 31; nutrients entering after that date would not measurably contribute to the magnitude of the summer algal bloom. In 1971. the nutrient income was calculated from March 1 to July 31, but, because there was little flow between Jan uary 1 and March 1, the nutrient incomes for the three years are comparable. Nutrient incomes for each lake during these periods were estimated by the procedures employed to calculate the annual nutrient budgets. Inputs from metered watersheds. 62 unmetered watersheds, and rainfall were included. The total nutrient loads for Lake West Okoboji, Lake East Okoboji, and Spirit Lake were divided by their lake volumes to yield poten tial concentrations (Table 13). To calculate potential con centrations for Lake East Okoboji, Upper Gar Lake, and Lake Minnewashta, the lake volumes were combined because these lakes do not have separate watersheds. In Lower Gar Lake the annual increment of water is over three times the lake volume so that the potential nutrient con centration based on annual input is not achieved. For this reason, the mean nutrient concentration of the watershed drainage is used as the potential concentration in the follow ing analyses (Table 13). This approach was used by Edmondson (1961) in such situations. The nutrient concentration of this stream is the potential concentration available to algal growth within the lake. The annual phosphorus income to the Iowa Great Lakes seems to determine the total phosphorus concentration of sum mer lake water and, thus, the phosphorus available for algal growth. A significant positive relationship (r = 0.91, P = 0=01) exists between potential and actual phosphorus concen trations within the lakes studied (Figure 12). A paired t- test shows the difference between actual and potential phos phorus means to be nonsignificant (P = 0.01). Vollenweider (1968) found a similar relationship between phosphorus loading 63 0.1 û. 0 0.1 0.2 ACTUAL CONCENTRATION PHOSPHORUS MG/L Figure 12. Potential phosphorus concentration (mg/1) plotted against the actual summer phosphorus concentration (mg/1) in Lakes West Okoboji, East Okoboji, Big Spirit and Lower Gar for 1971, 1972 and 1973 Not a line of best fit 64 (gm/m^/yr) and springtime phosphorus concentrations within different lakes. Phosphorus can be considered the limiting element in the lakes studied because many blue-green algae composing the plankton flora fix molecular nitrogen. Further evidence that phosphorus limits the standing crop in these lakes comes from the nitrogen-to-phosphorus ratio of the inputs. The ratio of nitrogen to phosphorus loading rate ranged from 13.2:1 to 38.6:1, which is similar to the N/P ratio of 15:1 found in algal cells (Vollenweider, 1968). The best relationship between potential phosphorus concen tration and algal chlorophyll would be with the greatest sum mer value from each lake because this would represent the max imum standing crop from a given phosphorus load. At the time of maximum standing crop, one would expect stored algal phos phorus to be minimal and algal biomass at its peak. Such conditions are critical determinants of lake water quality, but extreme values are difficult to reproduce because their magnitude depends on sampling frequency and climatic circum stance (Shannon and Brezonik, 1972a,1972b). To circumvent this problem, the mean July-August chloro phyll a value (as used by Edmondson, 1972) from each lake during the three years was regressed on the potential phos phorus concentration (r = 0.85, P = 0.01) (Figure 13). The regression equation was calculated by dividing the sum of the maximum chlorophyll concentrations by the sum of the potential 65 s 300 200 (O 100 0 C.î 0.2 POTENTIAL CONCENTRATION PHOSPHORUS MG/L Figure 13. The regression of mean July-August chlorophyll a (mg/m^) on the potential phosphorus concentration (mg/1) in the Iowa Great Lakes during 1971, 1972, and 1973 66 phosphorus concentrations (Snedecor and Cochran, 1967). This model was used because the variance is believed to progressive ly increase as potential nutrient and chlorophyll concentra tions increase. The zero intercept provided by the model is a result of the simplified assumption that summer algal growth depends upon annual phosphorus inputs. This model describes the levels of summer algal blooms and the annual phosphorus inputs to each of the lakes studied. With this model, algal bloom reductions are predicted when phosphorus loads are re duced as was seen in 1972 and 1973, when phosphorus inputs to each lake were less than in 1971 and algal levels were also less (Table 13). Phosphorus and nitrogen losses from the watersheds are highly correlated with one another (r = 0.86), and a regres sion of chlorophyll concentration on potential inorganic nitro gen (Figure 14) for each of the lakes during the period of study was significant (r = 0.74, P = 0.01). The strength of this relationship is likely from the strong correlation be tween phosphorus and nitrogen inputs and the dependence of chlorophyll upon the potential phosphorus concentration. To test further the relationship between potential phos phorus concentration and summer algal densities, I have com bined the Iowa data with comparable information for other lakes having published data on phosphorus inputs and summer chlorophyll a levels (Figure 15) (Mackenthun, Keup and Stewart, 1968; Ahlgren, 1967; Ahlgren, 1970; Edmondson, 1969, 67 9 200 100 0 12 3 4 5 PCT£NT!AL CONCENTRATION NITROGEN MG/L Figure 14. The regression of mean July-August chlorophyll a (mg/m3) on the potential nitrogen concentration" (mg/l) in the Iowa Great Lakes during 1971, 1972, and 1973 68 1000 L. Norrviken.Switzeriond # L. Lower Gar L.,IA (# L. East Okoboji.lA O Spirit L.,IA - V L. 227, Canada • L. Washington,WA •% V Shagawa L.,MN o> • L. Sammomish, WA E W L. Sebasticook, ME 100 O L. West Okoboji.lA A Clear L, Canada V®9-7I Q. 57-66 Ow o ''70-72 f o • 65 ^ '0 en 70 < I Log Y « 2.99 + 1.23 Log X ! J I I I : I I ' I I I 1 • 0.001 0.01 0.1 1.0 Potential Concentration Phosphorus (mg/l) Figure 15. Mean summer chlorophyll a concentrations (mg/m ) as a function of potential phosphorus concentra tions (mg/l) for several lakes. Numbers after symbols indicate year of data collection. For some lakes an average for several years is used. With the exception of Clear Lake, where only data on soluble reactive phosphorus was available, the phosphorus concentrations refer to total phos phorus 69 1970; Schindler and Nighswander, 1970; Schindler et al., 1971; Schindler e^ a^., 1973; Emery, Moon and Welch, 1973; Malueg, personal communication). A double logarithmic trans formation was used to linearize the relationship. The corre lation between the transformed variables is high (r = 0.94, P = 0.01) in view of the wide range of lakes examined and the problems involved in obtaining accurate nutrient budgets and representative chlorophyll data. In this comparison the nutrient values for Iowa lakes were based on annual rather than spring inputs to agree with published data on other lakes. For lakes East Okoboji, West Okoboji and Spirit, the 1972 and 1973 annual inputs were cal culated from July 1971, to July 1972, for 1972 and July 1972, to July 1973, for 1973. Annual input was, in part, estimated because data were not available for the entire time period. The annual phosphorus input for each lake in 1971 extended from July 1970, to July 1971. The phosphorus input for the period between July 1970, and March 1971, was estimated from runoff and rainfall records and the mean phosphorus concentra tion in each of these from March to July, 1971. In Lower Gar Lake the mean phosphorus concentration for each year was used as the potential concentration. With more data points from a wider sampling of lakes, the phosphorus-chlorphyll a relationship (Figure 15) should be use ful as a basis for predicting the benefits of a nutrient reduc tion program for a particular lake. An exception would be 70 those lakes where light transparency is markedly reduced by inorganic turbidities or high concentrations of humic mate rials. It would also be inapplicable in streams or in lakes with high flushing rates where the phytoplankton population is lost before the maximum potential densities can be attained. Because there is no discontinuity in the phosphorus- chlorophyll a relationship, there is no simple basis for establishing a critical value for nutrient loading in a nutri ent reduction program. A useful relationship to arrive at an acceptable nutrient loading value is the relationship between chlorophyll a concentration and transparency. Water clarity is readily evaluated by the general public and the impetus for many nutrient reduction programs is based on improvements in water clarity even though other limnological benefits are ex pected. Edmondson (1972) found that water transparency as measured by the Secchi disk depth is hyperbolically related to chlorophyll a concentration in Lake Washington. I have ex tended this relationship to include points for several other lakes (Figure 16) (Saunders, Trama and Bachmann, 1962; McGauhey et , 1963; Ahlgren, 1967; Ahlgren, 1970; Schindler , 1971; Larson» 1972; Powers et , 1972; Willen, 1972; Schindler et , 1973). This is an inexact relationship be cause factors such as size and shape of the algal cells, inorganic turbidities, and dissolved organic materials also determine the optical properties of lakes, but, generaliza tions can be made. Transparencies of lakes with chlorophyll a 71 40 35 30 V) oc »-w X È20 o 2 ° 15 oX o w « 10 5 0 0 50 100 150 200 250 300 350 CHLOROPHYLL 4 MG/Np Figure 16. Relacicnship between mean Secchi disk trans parencies for July-August and the mean July- August chlorophyll a concentrations for 16 lakes of various trophic states 72 values less than 10 mg/m^ are extremely sensitive to changes in algal abundance while there is little difference in trans parencies of lakes with chlorophyll a concentrations above this value. There is little difference between the Secchi disk depth in a lake with a chlorophyll value of 100 mg/m and a lake with 300 mg/m^ (Figure 16). A nutrient reduction program would have to reduce algal densities below 10 mg/m^ before improvements in water transparency would be achieved. This would correspond to an annual potential phosphorus con centration of 0.02 mg/1. Further reductions below this level should lead to increasing water transparencies. This value is comparable to the values arrived at by Vollenweider (1968). For a lake with an average depth of 10 meters, his maximum permissible loading value of 0.2 gm/m 2 corresponds to a potential concentration of 0.02 mg/1. Discussion The relationship between chlorophyll a concentration and phosphorus inputs is simplified because it is based on several assumptions. The first is that phosphorus is the element limiting algal growth. This is a reasonable conclusion be cause many of the planktonic genera present in these lakes can fix elemental nitrogen and the inflowing water contains ade quate nitrogen when compared with the amount of phosphorus. Another important assumption is that the entire phosphorus input is exclusively available to planktonic algal growth. 73 giving no consideration to the phosphorus, which could be taken up by sediments, bacteria, attached algae, aquatic macrophytes and other phosphorus sinks. Despite these assumptions, a highly significant positive relationship has been found between potential phosphorus and planktonic algae as measured by extracted chlorophyll pigments for lakes covering a wide trophic range. The relationship in Figure 15 supports the hypothesis that the trophic status of lakes is determined to a large extent by the annual inputs of nutrients, in this case phosphorus. In the Iowa lakes the magnitude of the summer algal standing crops was dependent upon annual phosphorus inputs. When natural changes in the annual runoff lowered the phosphorus input for a given year, the lakes responded with a smaller algal bloom. In a like manner, algal crops in Lake Washington decreased as the sewage effluents were diverted from that lake (Edmondson, 1969,1970, 1972). The rapid response of individual lakes to changes in the phosphorus inputs probably results from the strong tendency for phosphorus to become bound in the sediments so that there is little carryover from year to year fVollenweider, 1968). For the Iowa lakes, we found no significant difference between the potential concentrations of phosphorus as calculated from annual inputs and the actual summer concentrations of total phosphorus measured in the summer months. 0+her studies have shown that in the warm months the phosphorus in the epilimnion 74 is recycled many times and zooplankton are important in this process (Schindler, 1973). In this way the summer phosphorus supply remains available for phytoplankton growth during the growing season and can thus determine the ultimate size of the summer standing crop. This relationship is such that it might be practical to reduce the input of phosphorus to a lake and subsequently re duce the algal standing crop as was done in Lake Washington. A reduction in phosphorus input to a given lake might be expected to reduce the algal populations correspondingly. There is, of course, a lower limit to this relationship, for, if all inputs were removed, there would still be some phos phorus recycled within the lake and no controls could be placed on the phosphorus input from extraneous sources such as rainfall and particulate fallout. Experience has shown that reduction programs are not always successful. Little benefit has resulted from nutrient diversions in Lake Mendota (Lee, 1966; Sonzongni and Lee, 1974), Lake Sammamish (Emery e^ al., 1973) and Snake Lake (Born et al^. , 1973). In Lake Sammamish the annual phosphorus input was reduced by approximately 38% which resulted in a 28% reduction in the peak algal biomass. Neither of these reduc tions were statistically significant, but were similar to what would be expected from the phosphorus-chlorophyll a relation ship in Figure 15. 75 Using the chlorophyll a-Secchi disk relationship (Figure 16) as a criterion for a nutrient reduction program, phos phorus inputs to a given lake would have to be reduced below 0.02 mg/1 before significant increases in water transparency would be realized. Phosphorus reductions not attaining the 0.02 mg/1 point will have little tangible effect on water clarity because algal biomass will not be reduced sufficiently, however, other limnological benefits might be obtained from such a reduction. In the Iowa lakes, watershed feedlot animal units are a statistically identifiable source of phosphorus and ammonia nitrogen to the lakes. This source accounts for 2 to 29% of the annual phosphorus input to the various lakes. A nutrient reduction program has been proposed which would divert feedlot surface runoff from entering the lakes and thus reduce the phosphorus and nitrogen inputs with expectedly beneficial re sults. This diversion should annually reduce phosphorus inputs by approximately 13% in Lake West Okoboji, 20% in Lake East Okoboji, 10% in Spirit Lake and 5% in Lower Gar Lake. Should this feedlot diversion program take place, benefi cial effects would be most apparent in lakes West Okoboji and Spirit. Little visible change would occur in the water qual ity of lakes East Okoboji and Lower Gar. In Lake West Okoboji summer chlorophyll a concentrations are approximately 5 mg/m^, and in Spirit Lake this average is between 10 and 60 mg/m^. 76 Given the strong relationships between potential phosphorus concentration - chlorophyll a and chlorophyll a - Secchi depth transparency, a phosphorus reduction in these lakes would re duce the chlorophyll a concentration and subsequently increase the water clarity. In lakes East Okoboji and Lower Gar, the phosphorus reduction achieved from feedlot diversion would likely reduce the magnitude of the summer algal bloom but little improvement in water clarity would be noted. These lakes have mean summer chlorophyll a concentrations between 90 and 300 mg/m^. Phosphorus reductions resulting from feedlot diversion would not be sufficient to reduce these summer chlorophyll a values below 10 mg/m^, the point where water clarity is expected to improve. 77 LITERATURE CITED Ahlgren, G. 1970. 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Carlander, and Dr. John A. Mutchmore for their help and interest. I am grateful to Dr. David Cox of the ISU Statistics Laboratory for help with statistical analyses. This study was accomplished through the cooperative efforts of many local, state, and federal organizations and agencies, as well as of private individuals to whom I am indebted. Mr. John W. Cory of Spirit Lake was instrumental in these cooperative efforts, his help was most valuable. I want to thank Dr. Richard Bovbjerg, Director of Iowa Lakeside Laboratory, for providing laboratory facilities and the research notebook of Dr. F. Stromsten which contained un published oxygen profiles of Lake West Okoboji; Mr. Robert Benson, manager of the Laboratory, for help with sample col lection and providing other support services; Dr. John Dodd and Dr. Charles Reimer, for help with algal identifications; Mr. Jim Yungclas of the Iowa Cooperative Extension Service 86 for assistance in establishing the study; Mr. Sulo Wiitala for stream flow information; Mr. Earl Rose and Mr. Richard McVilliams of the Iowa Conservation Commission for information on past biological conditions in the lakes and help with sample collection; Mr. William Higgins for mapping the water shed boundaries and conducting the land-use inventory; and Messrs. Brian Borofka, Stephen Kilkus, Keith Schardein, Keith Govro, Terry Schwartzenbach and Randall Maas for collecting field data. I sincerely thank my parents for their encouragement and confidence. I am most grateful to my wife, Susan, for her love and unselfish enthusiasm in my work.