|Table of Contents|
The Florida Lakes data base: Resources, literature, contents
Development of a trophic index scheme to rank Florida lakes
Land use and nutrient loadings to Florida lakes
Priorities for restoration
The Oklawaha Lakes: A case study
Summary and conclusions
Appendix A: References
Appendix B: Florida lake references (by lake)
Appendix C: Data base description
Appendix D: Laboratory techniques of various lake studies
Appendix E: Calculation of total nitrogen concentrations from varying reported forms of nitrogen
Appendix F: Subgroupings of lakes used in TSI analysis
Appendix G: Hydrologic unit numbers associated with Florida lakes
Report ENV-05-82-1 December 1982
A CLASSIFICATION OF FLORIDA LAKES
Wayne C. Huber, Patrick L. Brezonik* and James P. Heaney Faculty Investigators
Robert E. Dickinson Research Associate
Stephen D. Preston, David S. Dwornik and Mark A. DeMaio Student Investigators
Department of Environmental Engineering Sciences University of Florida Gainesville, Florida 32611
Final Report to the
Florida Department of Environmental Regulation Twin Towers Building 2600 Blair Stone Road Tallahassee, Florida 32301
*Presently at Department of Civil and Mineral Engineering University of Minnesota, Minneapolis, Minnesota 55455
A classification of Florida lakes was undertaken in response to the mandate of the Clean Lakes Program of the US EPA. The study involved five aspects, the first of which received the most effort: development of a water quality and limnological data base for 788 of Florida's 7,712 fresh water lakes, trophic state index (TSI), nutrient loadings, prioritization, and a case study of the five upper Oklawaha Lakes. In addition a revised gazetteer of Florida lakes was prepared.
Water quality data were available to evaluate an average TSI for 573 lakes based on nitrogen, phosphorus, Secchi disk and chlorophyll _a. Similarly, land use data were available to evaluate N and P loadings to 325 lakes. No correlation was found between TSI and loadings. Macrophyte coverage for 299 lakes was considered as an independent trophic indicator.
Tables and data within the report were identified for aid in assessment of lake use, including information on annual user occasions and recreational facilities. Water quality and controllability may also be assessed on the basis of information in the report. No prioritization scheme was presented since that is the responsibility of the Florida Department of Environmental Regulation. That establishment of restoration priorities is complex and site specific is shown to be evident from the case study of the Oklawaha Lakes.
TABLE OF CONTENTS
Chapter 1. INTRODUCTION ................... 1-1
The Clean Lakes Program ................. 1-2
Overall Project Objectives ............... 1-3
Theory and Purposes of Classification .......... 1-3
Classification of Lakes ................. 1-4
Outline of this Study..................1-8
CHAPTER 2. THE FLORIDA LAKES DATA BASE: RESOURCES, LITERATURE, CONTENTS
General Information .............. ..... 2-1
Objectives and Methods for Data Search......... 2-2
Criteria for Data Selection............... 2-3
Data Resources of this Study............... 2-4
The Florida Lake Data Base................ 2-42
Location Maps for Florida Lakes............. 2-53
CHAPTER 3. DEVELOPMENT OF A TROPHIC INDEX SCHEME TO RANK FLORIDA LAKES
Introduction ...................... 3-1
-?Trophic Index Schemes Reported in the Literature..... 3-2
Basis for a Trophic State Index for Florida Lakes .... 3-9
Development of Subindices ................ 3-10
Integration of Subindices into an Overall TSI...... 3-35
CHAPTER 4. LAND USE AND NUTRIENT LOADINGS TO FLORIDA LAKES .
Use of Loading Coefficients............... 4-2
Land Characteristics Data Base............. 4-5
Nutrient Export Coefficients: Literature Review..... 4-18
.-Point Source Discharge................. 4-21
Mass Loading Equations and Land Use Categories ..... 4-21
impact of Municipal Sewage................ 4-30
Calculated Loadings ................... 4-30
Predicted Phosphorus and Nitrogen Concentrations .... 4-49
v�ake Physical Characteristics .............. 4-64
CHAPTER 5. PRIORITIES FOR RESTORATION
Introduction ...................... 5-1
Cultural Interactions with Lakes ............ 5-1
Lake Prioritization Schemes for Other States ...... 5-4
Restoration and Management Techniques , ......... 5-4
Possible Prioritization Criteria ............ 5-7
Recreation and Public Use................5-7
Professional Interests ................. 5-35
Water Quality Indicators.................5-43
Controllability ..................... 5-66
CHAPTER 6. THE OKLAWAHA LAKES: CASE STUDY
Introduction ...................... 6-1
Water Quality Decline in Oklawaha Lakes ......... 6-2
Characterization of the Oklawaha Lakes ......... 6-5
Comparison of Water Quality Measurements Made by
Different Agencies ................... 6-6
Temporal Variability as a Source of Error in Trophic
State Estimation.................... 6-12
Accuracy of Trophic State Estimation .......... 6-26
Comparison of Florida and Carlson Trophic State Indices . 6-27
Restoration Case Study: Lake Apopka........... 6-31
Prioritization of the Oklawaha Lakes .......... 6-35
CHAPTER 7. SUMMARY AND CONCLUSIONS
Florida Lakes Data Base................. 7-1
Trophic Status of Florida Lakes ............. 7-1
Land Use and Nutrient Loadings............. 7-3
Prioritization ..................... 7-3
Oklawaha Lake Case Study................. 7-5
REFERENCES TO REPORT TEXT - �
FLORIDA LAKE REFERENCES DATA BASE DESCRIPTION
LABORATORY TECHNIQUES OF VARIOUS LAKE STUDIES CALCULATION OF TOTAL NITROGEN CONCENTRATIONS FROM VARYING REPORTED FORMS OF NITROGEN SUBGROUPINGS OF LAKES USED IN TSI ANALYSIS HYDROLOGIC UNIT NUMBERS ASSOCIATED WITH FLORIDA LAKES
APPENDIX A. APPENDIX B. APPENDIX C. APPENDIX D. APPENDIX E.
APPENDIX F. APPENDIX G.
LIST OF TABLES
Table No. Page No.
Table 2-1. Lakes of the 55 Lake Study...............2-5
Table 2-2. Lakes of the Acid Rain Study..............2-8
Table 2-3. Lakes of the National Eutrophication Survey Study . . . 2-10
Table 2-4. Lakes of the Florida Game and Freshwater Fish
Table 2-5. Lakes of the USGS-DER Study..............2-16
Table 2-6. Lakes of the Aquatic Weeds Study............2-20
Table 2-7. Urban Lakes Sampled During Project...........2-25
Table 2-8. Lakes Sampled by the Southwest Florida Water
Management District .................. 2-27
Table 2-9. Lakes Sampled as Part of the Lake Conway Study.....2-30
Table 2-10. Lakes Sampled by the Department of Environmental
Table 2-11. Lakes for Which Data Were Obtained from STORET.' .... 2-32
Table 2-12. Lakes Studied by Kautz (1981) ............. 2-40
Table 2-13. Lakes with Macrophyte Data............... 2-43
Table 2-14. Frequency of Samples in Florida Lakes ......... 2-48
Table 2-15. Most Frequently Sampled Florida Lakes ......... 2-49
Table 3-1. Trophic Indicator Values Associated with TSI
Subindex Values .................... 3-14
Table 3-2. Trophic State Indices - 573 Florida Lakes ....... 3-39
Table 3-3. Trophic State Frequencies ............... 3-50
Table 3-4. Trophic State Indices - Potential Problem Lakes .... 3-53
Table 3-5. County Average TSl's.................. 3-55
Table 3-6. TSI by Lake Type.................... 3-56
Table No. Page No.
Table 3-7. TSI by Lake Area (Acres)...............3-56
Table 3-8. Statistics of 573 Florida Lakes - Mean and
Standard Deviation .................. 3-57
Table 3-9. Statistics of 573 Lakes - Minima and Maxima......3-66
Table 4-1. Land Use/Land Cover Classification .......... 4-5
Table 4-2. Florida Land Use Data, Acres.............4-7
Table 4-3. Water Areas in Drainage Basins............4-12
Table 4-4. Number of Studies Cited in Reckhow et al. (1980)
for Various Nutrient/Land Use Combinations ...... 4-19
Table 4-5. Municipal Discharges into Florida Lakes........4-22
Table 4-6. Industrial Discharges into Florida Lakes ....... 4-23
Table 4-7. Land Use Designations Included in Shahane (1982) . . . 4-24
Table 4-8. Nutrient Loading Coefficients for Florida.......4-31
Table 4-9. Phosphorus Lake Loadings...............4-37
Table 4-10. Nitrogen Lake Loadings................ 4-43
-.Table 4-11. Lake Depths, Volumes and Detention Times ....... 4-50
Table 4-12. Average Annual Land Surface Runoff from
Florida Counties ................... 4-54
Table 4-13. Regression Results (log-log) for Predicted vs.
Measured Nitrogen and Phosphorus Concentrations. . . . 4-62
Table 4-14. Predictive Models for Total Phosphorus and Total
�Table 5-1. Lakes Subject to Prior Restoration Efforts ...... 5-2
Table 5-2. Parameters Used by Other States in Management/
Table 5-3. Lake Restoration Techniques..............5-6
Table 5-4. Possible Prioritization Criteria ........... 5-8
Table No. Page No.
Table 5-5. Annual Statewide Demand in Selected Outdoor
Recreation Activities - 1979 ............. .5-9
Table 5-6. Lakes Ranked by Number of User Occasions....... 5-13
Table 5-7. Parks Associated with Lakes.............. 5-22
Table 5-8. Six Inland Counties with Most Boats Registered,
1977 - 1978...................... 5-28
Table 5-9. Resident-Per-Boat Ratio, Florida Coastal and
Inland Counties.................... 5-28
Table 5-10. Boat Ramps and Accessibility in Florida Lakes..... 5-30
Table 5-11. Lakes Used as Potable Water Supplies ......... 5-33
Table 5-12. Beneficial Uses and Water Quality of 75 Florida Lakes. 5-36
Table 5-13. Lakes as Objects of Scientific Reports ........ 5-40
Table 5-14. Fish Kill Incidents in Florida Lakes......... 5-41 �'-
Table 5-15. Lakes Ranked by TSI Deviations from County Mean. . . . 5-45
Table 5-16. Lakes Ranked by Fraction Macrophyte Cover....... 5-56
Table 5-17. Summary of Major Report Tables Relating to
Prioritization .................... 5-65
Table 6-1. Summary of 20th Century History of Lake Apopka .... 6-3^>
Table 6-2. Mean Secchi Disk Levels from Various Agencies
During the Years 1977-1980 .............. 6-7
Table 6-3. Mean Conductivity Levels from Various Agencies
During the Years 1977-1980 .............. 6-8
Table 6-4. Mean Total Phosphorus Levels from Various Agencies
During the Years 1977-1980 .............. 6-9
Table 6-5. Mean Total Organic Nitrogen Levels from Various
Agencies During the Years 1977-1980.......... 6-10
Table 6-6. Florida Trophic State Index Values, by Agency,
for Oklawaha Lakes..................6-13 /
Table No. Page No.
Table 6-7. Distribution of Monthly Trophic State Estimations
(UF data for Oklawaha Lakes).............6-16
Table 6-8. Frequency Analysis of Monthly Values of the Florida
Average Trophic State Index for Lake Apopka......6-18
Table 6-9. Frequency Analysis of Monthly Values of the Florida
Average Trophic State Index for Lake Beauclair .... 6-19
Table 6-10. Frequency Analysis of Monthly Values of the Florida
Average Trophic State Index for Lake Dora.......6-20
Table 6-11. Frequency Analysis of Monthly Values of the Florida
Average Trophic State Index for Lake Eustis......6-21
Table 6-12. Frequency Analysis of Monthly Values of the Florida
Average Trophic State Index for Lake Griffin ..... 6-22
Table 6-13. Frequency Analysis of Monthly Values of the Florida
Average Trophic State Index for Lake Weir.......6-23
Table 6-14. Frequency Ana
Table 6-14. Frequency Analysis of Monthly Values of the Florida
Average Trophic State Index for Lake McCloud ..... 6-24
Table 6-15. Distribution of TSIs for the Oklawaha Lakes ..... 6-25
Table 6-16. Comparative Values of Carlson and Florida TSIs .... 6-29
Table C-1. Florida Euteophication Date Base Variables ...... C-4
Table C-2. Lakes in the Data Base Containing Data of Any Kind . . C-7
Table C-3. Lakes in the Data Base with No Nutrient of
Table C-4. Lakes in the Data Base with all Three Parameters:
Nutrients, Macrophytes, Land Use ........... C-17
Table C-5. Program to Access STORET Data Stored on UF Computer. . C-28
Table D-1. Sampling and Laboratory Techniques for the 55
Table D-2. Sampling and Laboratory Techniques for the Acid
Table D-3. Sampling and Laboratory Techniques for the NES Lakes . D-6
Table D-4. Sampling and Laboratory Techniques for the Florida
Game and Freshwater Fish Commission Study.......D-8
Table No. Page No.
Table D-5. Sampling and Laboratory Techniques for the Aquatic
Table D-6. Sampling and Laboratory Techniques used to Study
the Urban Lakes....................D-ll
Table F-1. Trophic State Index for 326 Phosphorus Limited
Lakes in Florida, TN/TP :> 30.............F-2
Table F-2. Trophic State Index for 91 Nitrogen Limited Lakes in
Florida, TN/TP < 10..................F-5
Table F-3. Trophic State Index for 156 Nutrient Balanced Lakes
in Florida, 10 < TN/TP < 30..............F-7
Table F-4. Florida Lakes Used in Regression Analysis of
Table G-1. Page Numbers for Each Hydrologic Unit.........G-4
Table G-2. Lakes Indicated by Name on the Hydrologic Unit Maps. . G-5
Table G-3. Hydrologic Unit Numbers used in this Study and
Associated Land Use, Acres . .............G-42
Table G-4. Hydrologic Unit Numbers by Lake and Associated
Land Use, Acres.................; . . G-52
Table G-5. Hydrologic Master List................G-85
LIST OF FIGURES
Figure 2-1. Lacation Map of Florida Counties and Water
Management Districts................. 2-54
Figure 2-2. Map of the Oklawaha Lakes.............. 2-56
Figure 3-1. Secchi Disk vs. Chlorophyll a............ 3-12
Figure 3-2. Ln Secchi Disk vs. Ln Chlorophyll a_,
Least Square Fit................... 3-16
Figure 3-3. Ln Secchi Disk Depth vs. Ln Chlorophyll a_
Concentration, Least Absolute Value Fit ....... 3-17
Figure 3-4. Chlorophyll a vs. Total Phosphorus, Least
Absolute Value Fit.................. 3-19
Figure 3-5. Chlorophyll a vs. Phosphorus, Least Squares Fit . . . 3-21
Figure 3-6. Chlorophyll a vs. Total Nitrogen, Least
Absolute Value Fitl................. 3-22
Figure 3-7. Chlorophyll a vs. Total Nitrogen, Least Squares Fit . 3-24
Figure 3-8. Ln Chlorophyll a vs. Total Phosphorus, Nutrient
Balanced Lakes.................... 3-26
Figure 3-9. Ln Chlorophyll a. vs. Ln Total Nitrogen, Nutrient
Balanced Lakes.................... 3-27
Figure 3-10. Ln Chlorophyll a vs. Ln Total Nitrogen, Larger
Data Set, Least Squares Fit............. 3-29
Figure 3-11. Ln Chlorophyll ja vs. Total Phosphorus, Larger
Data Set, Least Squares Fit............. 3-30
Figure 3-12. Ln Phosphorus vs. Ln Nitrogen, Larger Data Set,
Least Absolute Value Fit............... 3-31
Figure 3-13. Ln Percent Macrophyte Coverage vs. Ln Chlorophyll
a Concentration ................... 3-32
Figure 3-14. Comparison of Carlson TSI and Florida TSI ...... 3-38
Figure 4-1. National and Florida Nitrogen Export Loadings
From Three Different Land Uses............4-32
Figure No. Page No.
Figure 4-2. National and Florida Phosphorus Export Loadings
From Three Different Land Uses............ 4-33
Figure 4-3. Predicted vs. Measured Phosphorus Concentrations.
Nitrogen Limited Lakes................ 4-56
Figure 4-4. Predicted vs. Measured Phosphorus Concentrations.
Phosphorus Limited Lakes............... 4-57
Figure 4-5. Predicted vs. Measured Phosphorus Concentrations.
Nutrient Balanced Lakes ............... 4-58
Figure 4-6. Predicted vs. Measured Nitrogen Concentrations.
Nitrogen Limited Lakes................ 4-59
Figure 4-7. Predicted vs. Measured Nitrogen Concentrations.
Phosphorus Limited Lakes............... 4-60
Figure 4-8. Predicted vs. Measured Nitrogen Concentrations.
Nutrient Balanced Lakes ............... 4-61
Figure 5-1. Interactions of Lakes with Cultural Factors ..... 5-3
Figure 5-2. Planning Regions Used in Florida Department of
Natural Resources Survey of User Occassions ..... 5-10
Figure 5-3. Top Freshwater Fishing Locations in Florida ..... 5-24
Figure 5-4. Fish Management Areas ................ 5-25
Figure 5-5a. Resident Fishing Licenses in Florida (by County). . . 5-27
Figure 5-5b. Nonresident Fishing Licenses in Florida (by County) . 5-27
Figure 5-6. Typical Cost Curve for Pollution Control....... 5-63
Figure 5-7. Conceptual Prioritization Scheme........... 5-67
The Florida Department of Environmental Regulation project officers contributed actively to the project. The authors express their gratitude to Lee Edmiston and Vernon Myers for their suggestions, data, reviews and editing.
Several students at the University of Florida contributed to data collection and analysis, data assembly and various aspects of the report: E. Edgerton, F. Dierberg, J. Goldman, C. Merkel, R. Gibney, M. Blosser, and S. Nix. Typing and drafting were accomplished by W. Stafford, V. Maxfield, K. Karr, A. Crawford, and J. Wilson. Computations were performed at the Northeast Regional Data Center on the University of Florida campus.
In addition to the Florida Department of Environmental Regulation, this project was supported by the Water Research Program, Engineering and Industrial Experiment Station, University of Florida. The cooperation and support of the Department of Civil and Mineral Engineering, University of Minnesota, which enabled one of the principal investigators (P.L. Brezonik) to maintain an active involvement in the project, is gratefully acknowledged.
THE CLEAN LAKES PROGRAM
The Water Pollution Control Act Amendments (P.L. 92-500) passed by Congress in 1972 established a policy and program for restoration of polluted and degraded lakes of the United States. The program has become known as the Clean Lakes Program of the US EPA. Section 314 of the act, which established the program, required that states classify their lakes (according to trophic state), as part of the overall strategy for development of lake restoration programs. The EPA provided funds to the states to undertake this classification program. This project for the Florida Department of Environmental Regulation is in response to the need for the State of Florida to develop such a classification system for its lakes.
The EPA guidelines (EPA, 1980) for development of lake classification request that states (1) identify and classify their publicly owned freshwater lakes according to trophic condition and (2) establish a priority ranking for lakes determined to be in need of restoration. Guidelines also were provided for the kinds of information to be provided in any lake inventory, but specific approaches for development of classification systems were left to the discretion of each state. In succeeding sections of this report, approaches for developing an inventory of Florida lakes, a trophic classification scheme applicable to Florida lakes, and procedures for prioritizing restoration/preservation activities on degraded or potentially degraded lakes are described.
OVERALL PROJECT OBJECTIVES
(1) Develop a computerized inventory of significant Florida lakes.
(2) Develop a trophic classification and trophic ranking scheme for Florida lakes.
(3) Classify and rank Florida lakes for which information on trophic conditions is available.
(4) Gather additional trophic information on selected lakes deemed to be of interest because of potential problems and/or desirability for restoration.
(5) Develop a general scheme to rank Florida lakes according to priority for restoration or preservation programs.
(6) Rank Florida lakes for which adequate information exists, according to priority for restoration or preservation programs.
THEORY AND PURPOSES OF CLASSIFICATION
Classification has been an important aspect of limnology since the early part of this century, and indeed, classification is a fundamental part of all science. According to Sokal (1974), the primary purpose of classification is to describe the structure of constituent objects to each other and to other similar objects and to simplify these relationships in a way such that general statements can be made about classes of objects. Much of the rationale of the scientific method is contained in the last sentence, but it should be emphasized that classification is of great practical importance, as well as of academic or theoretical significance.
At least four benefits and applications are derived from classification efforts; these can be summarized in four words.
(1) Identification. Grouped objects (classes) often are identified by
a common name that calls to mind certain distinctive properties of the class.
(2) Organization. Classification leads to a systematic organization of knowledge about the classified objects, resulting in better information retrieval and data handling.
(3) Generalization� Classification leads to development of hypotheses or theories of the behavior of objects in a given class. What do objects in a class have in common to cause similar behavior? How do objects in one class differ from objects in another class? Such questions arise naturally from the process of classification, and their answers form the basis of generalized understanding of the nature of systems.
(4) Management. Different classes of objects (e.g. lakes) may be suited for different uses and may require different types of regulation.
The specific benefits and applications of classifications in limnology reflect the above general discussion. Given the great number of features that characterize lakes and the great diversity of lakes, it is convenient to identify and describe lakes by class names, as a shorthand means to imply an array of attributes. From a scientific viewpoint, the ability to develop generalizations is the most important benefit of lake classification. The practical implications of classification as a tool in lake management have only recently become recognized.
Several words of cau jn are in order. Although classification of lakes is an important and useful exercise, it is not an end in itself, but simply a means to other ends. The purposes and ultimate uses of a classification system must be kept clearly in mind in developing such systems.
Moreover, a good classification system (whether for lakes or other objects) ideally should fulfill several criteria. Classes should be unambiguous, i.e. a lake should fit into only one class in a given scheme. Classes should be developed based on parallel features that divide the set of lakes in a logical manner. Classification schemes should be based on identifying parameters that are readily available or are easily obtained for the objects (lakes) being classified. For example, a classification scheme for Florida lakes based on primary production would not be useful to management agencies such as the Department of Environmental Regulation or the Game and Fish Commission. Primary production data are available for only a few lakes in Florida, and reliable data are difficult, time-consuming, and costly to obtain. On the other hand, it also is obvious that parameters must be used for classification schemes that relate to the purposes of the scheme. If the objective is to develop a trophic classification scheme, the accepted indicators of trophic state must be used in the scheme.
CLASSIFICATION OF LAKES
Lake classification schemes have been developed based on a wide variety of lake characteristics, including geomorphic, physical, chemical, and biological attributes. For example, lakes are classified according to mode of origin, shape, thermal structure, chemical content (hardness, pH, color), and the dominant types of organisms in the major food chain levels. A major feature of the non-biological classification schemes is that usually they are based on a sin^ -e parameter (e.g. temperature, color), and thus they can be referred to as univariate classification.
Biological classification systems usually are based on several parameters (e.g. indicator organisms), and thus are multivariate in nature. In general, it is easier to avoid problems of ambiguity and overlapping classes with univariate schemes.
By far the most important biological classification scheme for lakes is based on the concept of trophic state. This term is defined loosely as the nutritional status of a lake. Historical development of trophic state concepts was described by Hutchinson (1973). Brezonik (1976) described the characteristics of various trophic classes in detail. Much controversy has existed over terminology; precise delineation of trophic state classes, and a single, widely accepted scheme with well-defined boundaries for the various classes is not available.
Limnologists agree on two major trophic classes, oligotrophic lakes and eutrophic lakes, but the boundary between the two classes is rather vague. Oligotrophy is defined as the condition of low nutrient concentrations, low phytoplankton biomass, and consequently low primary productivity. Oligotrophic lakes characteristically have high clarity and good water quality. Eutrophy is defined as the condition of high nutrient concentrations, with consequently high phytoplankton (and perhaps macrophyte) biomass and high productivity. Eutrophic lakes have low water clarity because of the higher concentrations of phytoplankton, and generally speaking, they are presumed to have lower water quality.
A number of specific water quality problems are associated with eutrophic conditions, and these problems worsen as a lake becomes more eutrophic (nutrient enriched). Dissolved oxygen is lost from bottom waters as a result of organic matter decomposition; taste and odor problems develop from noxious growths of algae; aquatic weed growths become excessive and interfere with boating and swimming; game fish populations are replaced by rough fisn as a consequence of loss of spawning areas and foodstocks preferred by game fish. Of course, the degree of water quality problems depends on the intended use of the water, as well as on the degree of eutrophy. As warm-water fisheries, moderately eutrophic lakes may be preferable to oligotrophic lakes, and in this sense
it is simplistic to state that eutrophication is inherently detrimental. On the other hand, use of lake water for swimming or drinking purposes places a premium on water clarity, and the least degree of eutrophy (i.e. the most oligotrophic condition) is preferred for such uses.
Several other trophic classes have been recognized by limnologists to divide the spectrum of trophic conditions into smaller (more homogeneous) ranges. Ultraoligotrophy represents the extreme case of low nutrient, low productivity conditions, whereas hypereutrophy represents the opposite, i.e. very high nutrient levels and high algal density. Hypereutrophy has definite negative water quality connotations, and is usually associated with cultural (i.e. human-induced) conditions. Mesotrophy is a state between oligotrophy and eutrophy, and it is characterized by moderate levels of nutrients and algae, moderate productivity, and for the most part good (or at least acceptable) water quality.
As mentioned above, limnologists disagree on the precise boundaries between the classes listed above. Moreover, there is an inherent problem in classifying lakes according to trophic state in that more than one parameter is required to define trophic conditions. Depending on where one places boundary conditions, one trophic indicator may place a lake in one class, whereas another indicator may place it in another class.
Even if trophic class can be established unequivocally, the problem of differentiating between degrees of trophic state within a given class still remains. Obviously, a range of conditions exists within any single class; dividing the broad range of possible trophic conditions into two or three or even five classes still leaves much room for variability with classes. The problem is especially severe for the eutrophic class (or if used, the hyper-eutrophic class), which is essentially unbounded on the upper end.
Aquatic scientists have confronted the problems described in the two preceding paragraphs for the past ten years and have developed or applied several approaches to circumvent these difficulties. Multivariate statistical methods such as cluster analysis have been used by several workers to develop objective classification schemes based on multiple indicators (see Brezonik 1976). Discriminant function analysis was proposed by Brezonik and Shannon (1971) as a means of identifying the pre-established class to which a lake belongs, and the technique has been applied in eutrophication studies by Reckhow (1979) and Yeasted and Morel (1978).
One approach to quantifying the concept of trophic state is the development of a numerical index. A variety of such indices have been developed by aquatic scientists, using a range of mathematical techniques from simple numerical rankings to multivariate approaches such as principal component analysis (see review by Brezonik ). A widely discussed, general approach to trophic indices is that of Carlson (1977) , who developed separate indices based on three fundamental indicators of trophic conditions: Secchi disk transparency, total phosphorus concentration, and chlorophyll a_ concentration.
Trophic indices suffer from a variety of deficiencies and are subject to abuse, especially if applied to lakes outside of the data base on which they were developed. However, an index does not need to be universal in order to be useful. Indices should be considered as ad hoc tools that are useful in a defined set of circumstances and only for certain purposes. With these limitations in mind, however, indices can be a useful tool for eutrophication assessment and management. The index schemes used for this project are described in detail in Chapter 3.
OUTLINE OF THIS STUDY
The foremost activity of this study has been the development of a Florida Lakes Data Base (FLADAB) for application of the classification schemes developed herein. The sources of data are described in Chapter 2. Enough data were accumulated from various sources to provide some information for 788 lakes and to evaluate trophic state indices for 573 Florida lakes, far more than for lake classification schemes developed for any other state.
Following the development and application of the trophic state indices in Chapter 3, nutrient loadings are developed and applied to 286 lakes in Chapter 4. Lake use, water quality and controllability are considered in the context of prioritization for restoration in Chapter 5.
Over the past 15 years, the Department of Environmental Engineering Sciences at the University of Florida has engaged in many detailed studies of individual and groups of Florida lakes. One such group is the Upper Oklawaha chain (i.e., Apopka, Beauclair, Dora, Eustis, Griffin) for which a large amount of detailed recent (i.e., monthly for 1977-81) data is available. These lakes are considered as a case study in Chapter 6, in which the generalized conclusions reached earlier on the basis of relatively few data for most lakes are compared with conclusions based upon numerous data for these lakes.
The final summary and conclusions are given in Chapter 7. The full data set used for this study and many of the print-outs of results too voluminous for this main report are available as addenda.
THE FLORIDA LAKES DATA BASE: RESOURCES, LITERATURE, CONTENTS
Florida has approximately 7,712 fresh water lakes and reservoirs and approximately 3500 named lakes. These lakes cover 2,290,000 acres, about six percent of the state's surface area. A total of 236 Florida lakes have been meandered (surveyed shortly after statehood) and determined navigable, thus imparting title to the lake bed as 'sovereignty lands' of the state (Heath and Conover, 1981).
Florida's relatively flat, low-lying topography contributes to the generally shallow morphology of its lakes (with the exception of sinkhole lakes). Lake level fluctuation is significantly influenced by predominant weather patterns, degree of interaction with aquifers, runoff, and streamflow inputs and outputs (Heath and Conover, 1981).
Although a large variation in lake types is encountered in Florida, attempts have been made to correlate the regional characteristics of lakes, namely mineral composition, surface geology, potentiometric surface of underlying aquifers, etc. with reasonable success. Oligotrophic sandhill lakes of the Trail Ridge region of north central Florida, eutrophic lakes of the phosphatic Hawthorne formation in the lower-lying areas of north central,7 Florida, sinkhole lakes of central Florida, large marsh-like expanses and hard-water man-made real estate lakes in south Florida are typical, though not all inclusive, examples regionally predominant lake types in Florida (Canfield, 1981).
Influences of man on lake systems are also important features in Florida lakes. Point source discharges, modification of non-point sources through land use, drainage and other water management practices, pesticides, introduction of exotic species and other perturbations also have important impacts on lake characteristics. OBJECTIVES AND METHODS FOR DATA SEARCH
The major objectives for this literature review of Florida lakes are as follows:
1) Identify major water quality data sources for Florida lakes.
2) Describe the various methodologies used in these major lake studies and data sources. Particular attention is directed toward determining the compatibility of different data bases in the formulation of a trophic index, especially with regards to nitrogen, phosphorus, Secchi disk and chlorophyll a parameters.
3) Develop an extensive bibliography of Florida lakes, focusing on organizing these data by lake, and examining the possibility of applying information retrieval systems to guide in future literature searches of aspects regarding Florida lakes.
In accomplishing the above tasks the following steps were taken:
1) Computerized data sets were acquired when possible.
2) Other studies and sources deemed applicable and of high quality were added to form a broader data set (see below).
3) A one-time sampling of 30 urban lakes was performed by staff members during the summer of 1981. These data were also merged into the above data set.
4) A computer search of Florida lakes was obtained from the Office of Water Research and Technology and merged with "A Bibliography of Florida Lakes" by Robertson and Boody (1981) into a "by lake" bibliography. During the course of the project, additional references were added
to the bibliography. Water Management Districts, the Florida Game and Freshwater Fish Commission, universities, and others also were contacted to determine other studies applicable to such a bibilio-graphy. The resultant bibliography is presented in Appendix B.
5) A review of nitrogen, phosphorus, Secchi disk and chlorophyll a_ literature was undertaken to ascertain the comparability of measurements from various sources. This review focused primarily on nitrogen parameters. The results are given in Appendix E.
CRITERIA FOR DATA SELECTION
A large computerized data set was amassed that included many chemical, biological and physical parameters for numerous lakes. The Florida Lakes Data Base (FLADAB), described later, contains such parameters for 573 lakes with additional lakes covered only by macrophyte data. In addition, the Florida Lakes Gazetteer (Florida Board of Conservation, 1969, described later) has been expanded and updated with some new lake names and new lake entries (Dickinson et al., 1982).
Establishment of such a large volume of data (for use in calculating trophic state indices and other parameters) calls for access to computerized data sources, wherever possible. Hence, although no useful data resources were rejected because they were not computerized (i.e., available on punched cards or magnetic tape), some large sources such as EPA STORET could not have been used without this attribute.
Documentation is a second criterion. Ideally, all data included in the data base should have an associated report to describe the project and sampling methods. Unfortunately, some recent studies are undocumented, and others have only sketchy documentation. Still other sources, such as STORET, are a result of continuous monitoring by various agencies for which no documentation is available. However, in all cases, some knowledge of the source and quality of the data was available prior to inclusion in FLADAB.
The relative importance of individual lakes is a more subjective criterion since the status of any of several thousand lakes is important to local residents. Nonetheless, it is inconceivable that Florida's best known and most studied lakes would not be included in the study, and they have been to the extent of knowledge of the project staff and DER colleagues. The overall result of these liberal criteria has been to include almost all available data on Florida lakes that were accessible to the project.
DATA RESOURCES OF THIS STUDY Introduction
The final Florida Lakes Data Base (FLADAB) includes data from the following sources:
1. The "55 Lake Study" of north central Florida lakes by the UF Department of Environmental Engineering Sciences (UF-EES).
2. The UF-EES "Acid Precipitation" lake study.
3. The EPA National Eutrophication Survey.
4. Florida Game and Fresh Water Fish Commission water quality studies.
5. US Geological Survey - Department of Environmental Regulation water quality data.
6. The UF-Center for Aquatic Weeds study.
7. Selected Florida urban lakes, sampled as part of this project.
8. Water management district studies.
9. Studies by State Universities.
10. EPA STORET data.
11. Department of Environmental Regulation Study of lake nutrient conditions.
12. Other Studies.
13. Florida Aquatic Flora Survey-Macrophyte Data.
Data from these various sources and studies are described below.
55 Lake Study
Water quality is an important aspect of Florida's economy, and the state's freshwater lakes are used intensively for fishing, boating and other water sports. Despite this fact, water quality data prior to 1970 were very sparse. For this reason' Brezonik et al. (1969) began a survey of physical, chemical and biological attributes of lakes in north central Florida that resulted in the 55 lakes data set. The lakes are listed in Table 2-1.
Table 2-1. Lakes of the 55 Lake Study.
GfS COUNTY LAKE SOURCE
v'l ALACHUA � ALICE BREZONIK
2 ALACHUA ALTHO BREZONIK
3 ALACHUA BEVILLES POND BREZONIK
�i ALACHUA � BIVENS ARfl BREZONIK
5 ALACHUA BURNT PDND BREZONIK
6 ALACHUA CALF PDND BREZONIK
7 ALACHUA CLEAR BREZONIK
C \j ALACHUA CLEARHATER BREZONIK
�5 ALACHUA COflTER PDND? BREZONIK
10 ALACHUA ELIZABETH BREZONIK
ii ALACHUA HAHTHDRNE BREZDNIK
12 ALACHUA HICKORY POND BREZONIK
13 ALACHUA JEGGDRD BREZONIK
Vh ALACHUA KAHAPAHA BREZONIK
15 ALACHUA LITTLE ORANGE BREZDNIK
U ALACHUA LITTLE SANTA FE BREZDNIK
1? ALACHUA LOCHLOOSA BREZDNIK
1? ALACHUA HETA BREZONIK
H ALACHUA HIZE BREZONIK
20 ALACHUA HOSSvLEE BREZONIK
21 ALACHUA - � NEHNANS BREZONIK
22 ALACHUA ORANGE BREZDNIK
23 ALACHUA PALATKA PDND BREZONIK
2k ALACHUA SANTA FE BREZONIK
25 ALACHUA STILL PDND BREZDNIK
26 ALACHUA TUSCAHILLA BREZDNIK
27 ALACHUA UNNAHED 10 BREZDNIK
2?, ALACHUA UNNAHED 20 BREZONIK
21 ALACHUA UNNAHED 25 BREZONIK
30 ALACHUA UNNAHED 27 BREZDNIK
31 ALACHUA HATERHELDN PDND BREZDNIK
32 ALACHUA � HAUBERG BREZDNIK
33 CLAY BROOKLYN BREZONIK
3h CLAY GENEVA BREZDNIK
35 CLAY KINGSLEY BREZDNIK
26 CLAY HAGNOLIA BREZONIK
2? CLAY SAND HILL BREZDNIK
76 HIGHLANDS ANNIE BREZDNIK
11 HIGHLANDS CLAY BREZDNIK
L0 HIGHLANDS FRANCIS BREZDNIK
LAKE EUSTIS BREZDNIK
LAKE HARRIS BREZDNIK
^3 LEUY LONG PDND BREZONIK
RARION HEIR BREZDNIK
PUTNAH ADAHO . BREZDNIK
i / PUTNAH ANDERSON CUE BREZDNIK
-7 PUTNAH CDHPEN BREZONIK
PUTNAH GALLILEE BREZDNIK
PUTNAH LONG BREZDNIK
50 PUTNAH HCCLOUD BREZDNIK
51 FUTHAH SANTA ROSA BREZDNIK
52 PUTNAH SUGGS BREZDNIK
51 PUTNAH SHAN BREZDNIK
54 PUTNAH HALL BREZONIK
55 PUTNAH HINNOT BREZONIK
This study began with a number of goals. Since water quality had not been monitored continuously the data would assess present water quality conditions. With further monitoring these data would then serve as historical data in order to detect future trends in water quality. The data also would be used to investigate trophic dynamics specific to Florida and to develop a classification scheme for trophic conditions in Florida lakes. Present trophic conditions were assessed in relation to the factors controlling water quality degradation.
In order to have data representing the entire range of trophic states, specific groups of lakes were chosen. Sixteen oligotrophic lakes from the Trail Ridge area of north central Florida were selected to represent low productivity systems. Thirty three lakes of various trophic states were chosen from Alachua County, in part due to their proximity to the University of Florida. Six lakes from the eutrophic Oklawaha lakes also were included to represent the upper end of eutrophic conditions.
Most lakes were sampled four times per year (seasonally) but 19 lakes were sampled bimonthly to detect short term trends and periodicities. Samples were collected with a Van Dorn sampler and stored in refrigerated polypropylene bottles, Samples for nutrient analyses were preserved with 1 mL saturated mercuric chloride solution per liter water sample. Methods of analysis generally followed Standard Methods (A.P.H.A., 1965) ; however, some modifications were necessary. Exact methods are detailed in Table 1 of Appendix D.
Acid Rain Lakes
As part of a University of Florida study to characterize chemical aspects of Florida rainfall, a number of lakes were chosen to monitor effects of precipitation inputs, primarily with regard to pH (Brezonik et al., 1982). Twenty
lakes were chosen on the criteria of susceptibility to acid rain and the availability of historical data. These lakes were sampled seasonally during 1978 and 1979 and analyzed for a variety of physical, chemical and biological parameters. These data were then used to note trends in pH over time and to delineate determinative factors of pH in the lakes.
The studied lakes, listed in Table 2-2, were all softwater lakes located in two areas of Florida. Twelve lakes were chosen from the Trail Ridge area east of Gainesville, and eight lakes were chosen from the Highlands Ridge area located northwest of Lake Okeechobee. These two groups of lakes represent areas with differing amounts of acid deposition; the northern group showed a trend of decreasing pH over time, while the southern group did not show such a trend.
Sampling was done to determine the overall chemical and biological characteristics of the lakes. A station was set up at the deepest part of the largest pool. Samples were collected from three depths in the water column and composited for later analyses. Samples for nutrient analyses were preserved with 1 mL HgC^/L, placed on ice in the field and stored at 4�C. Chemical analyses were performed according to Standard Methods (A.P.H.A., 1976) and/or the EPA analytical manual (US EPA, 1974). Details of analyses are outlined in Table 2 of Appendix D.
National Eutrophication Survey
The National Eutrophication Survey (NES) was initiated in 1972 in response to a fede -\1 commitment to investigate increasing degradation of water quality in lakes caused by eutrophication. The survey was coordinated by the US EPA and
Table 2-2. Lakes of the Acid Rain Study.
GES COUNTY LAKE SOURCE
1 ALACHUA ALTHO HENDRY
2 CLAY BROOKLYN HENDRY
3 CLAY GENEVA HENDRY
k CLAY JOHNSDN HENDRY
5 CLAY KINGSLEY HENDRY
6 CLAY fJAGNDLIA HENDRY
? CLAY SAND HILL HENDRY
8 CLAY SHEELER HENDRY
�? HIGHLANDS ANNIE HENDRY
10 HIGHLANDS CLAY HENDRY
11 HIGHLANDS FRANCIS HENDRY
12 HIGHLANDS JOSEPHINE HENDRY
13 HIGHLANDS JIME-IK-HIHTER HENDRY
l�i HIGHLANDS LETTA HENDRY
15 HIGHLANDS PLACID HENDRY
16 PUTNAH ANDERSON CUE HENDRY
17 PUTNAH CDUPEN HENDRY
18 PUTNAH GALLILEE HENDRY
1H PUTNAH HCCLDUD HENDRY
20 PUTNAH SANTA ROSA HENDRY
used state agencies to gather information on nutrient sources and concentrations and impacts of nutrient loads on various state water bodies. This information was then compiled from all states in order to form a coordinated effort of eutrophication control. During the initial year of the survey Congress enacted the Federal Water Pollution Control Act Amendments of 1972, which reprioritized federal water quality research goals and charged the US EPA with the responsibility for leadership toward their achievement.
Lakes were selected for sampling according to susceptibility as defined by federal and state agencies. A number of factors were instrumental in this decision, including the number of municipal sewage treatment plants within 25 miles, whether the lake was 100 acres or larger and whether the mean hydraulic retention time was 30 days or more. Forty Florida lakes, (Table 2-3) were chosen on the basis of these factors.
Generally, sampling was done at discrete depths at the deepest part of the lake. Samples at each depth were analyzed for nutrients, alkalinity, pH, conductivity and dissolved oxygen. Nutrient samples were preserved with 0.25 mL of mercuric chloride solution. Samples for pH and conductivity analyses were collected in polyethylene bottles and' refrigerated in the dark until the end of the sampling day. Details of analytical methods are listed in Table 3 of Appendix D. Results of the survey were presented in the form of a separate report on each lake and a series of summary working papers, e.g., (NES, 1977).
Florida Game and Fresh Water Fish Coi '.ssion Water Quality Study
Florida's Game and Fresh Water Fish Commission (1967, 1968, 1969, 1970, 1971, 1972, 1973) conducted a comprehensive study of water quality in Florida lakes between the years 1966 and 1973. Through these years, 49 to 52 lakes
Table 2-3. Lakes of the National Eutrophication Survey Study.
DBS county lake source
1 breuard poinsett nes lakes
2 bseuard south nes lakes
3 clay doctors nes lakes
4 columbia alligator nes lakes
5 flagler crescent nes lakes
6 gadsden tal8uin nes lakes
7 highlands glenada nes lakes
6 highlands istokpoga nes lakes
n hillsborough thonotqsassa nes lakes
j* lake dora nes lakes
11 lake griffin nes lakes
11 LAKE hinneola nes lakes
13 lake TROUT nes lakes
14 LAk'E yale nes lakes
15 leon huhson nes lakes
li okeechobee okeechobee nes lakes
17 orange APOPKA nes lakes
li orange LAiiNE nes lakes
11 orange hinnehaha nes lakes
20 osceola east tghopekaliga nes lakes
21 osceola kissihhee nes lakes
22 osceola tghopekaliga nes lakes
2J pikellas sehinole nes lakes
24 pinellas tarpon nes lakes
25 polk banana nes lakes
U polk effie nes lakes
21 polk eloise nes lakes
23 polk gibson nes lakes
23 polk haines nes lakes
30 POLK hancock nes lakes
31 polk JESSIE nes lakes
T) polk LULU nes lakes
33 FOLK ha8idn nes lakes
34 FOLK reedy nes lakes
31 polk hedhyakapka nes lakes
li putnah george nes lakes
37 sehmjle horseshoe nes lakes
li sehmjle hqj1ell nes lakes
3i sehmjle JESSUP nes lakes
1(0 volusia honrde nes lakes
were examined in one year and 49 to 52 different lakes were examined the next year. This "alternating year" plan was repeated throughout the course of the investigation so that a total of 103 lakes were included in the report, with data covering a period of seven years. The lakes are listed in Table 2-4. Samples were collected semi-annually for various physical, chemical, and biological factors, with one sampling in spring (February-April) and one in fall (August-October). Collections were made at one mid-lake station, and 23 parameters typically were measured, although the number varied slightly from year to year. Also included in the analysis were lake surface area, elevation, drainage area, and a brief description of the lake itself. These descriptions included geographic location, all inflow and outflow points, local geology, and any major structures that were present in, or around the lake.
Additional, in-depth studies were also made periodically on a selected lake, or a group of lakes. For example, in 1968-69, Lakes Dora, Weir, and Yale were sampled on a weekly basis for 35 different parameters, including diversity and concentration of invertebrates. These three lakes were selected because they were thought to represent increasingly progressive stages of eutrophication.
Rodman Reservoir in Putnam County (also called Lake Oklawaha) was the subject of an intensive study in 1970-71. Monthly samples at ten different lake stations included 37 physical-chemical parameters, as well as phytoplankton, benthos, fish, and aquatic plant determinations. At that time the reservoir was only 2.5 - 3.5 years old, and it was considered a high quality lake. Hoover, predictions of rapid eutrophication were being made by environmentalists (Florida Defenders of the Environment, 1970) based on high nutrient inflow from the Oklawaha River. The GFWFC hoped to document the process of eutrophication from its beginning.
Table 2-4. Lakes of the Florida Game and Fresh Water Fish Commission Study.
fl�S COUNTY LAKE SOURCE
1 ALACHUA ALTHD FISHSGAflE
2 ALACHUA LOCHLODSA FISHSGAflE
/3 ALACHUA HEHNANS FISHSGAflE
ALACHUA ORANGE FISHSGAflE
5 ALACHUA SANTA FE FISHSGAflE
6 baker ocean POND FISHSGAflE
7 PAY DEER POINT FISHSGAflE
5 BRADFORD ROHELL FISHSGAflE
BRADFORD SAflPSON FISHSGAflE
10 BREVARD SOUTH FISHSGAflE
11 CHARLOTTE ilEBB AREA FISH*GABE
12 CITRUS TSALA APOPKA(F) FISHSGAflE
13 CITRUS TSALA apdpka(H) FISHSGAflE
14 CITRUS TSALA apdpka(I) FISHSGAflE
1-5 CLAY BROOKLYN FISHSGAflE
16 CLAY GENEVA FISHSGAflE
17 CLAY KINGSLEY FISHSGAflE
16 CLAY LOHERY FISHSGAflE
11 COLLIER TRAFFDRD FISHSGAflE
20 COLWBIA ALLIGATOR FISHSGAflE
21 COLUHBIA UATERTOHH FISHSGAflE
22 DIKE GOVERNOR HILL FISHSGAflE
23 GADSDEN TALOUIN FISHSGAflE
24 gulf DEAD FISHSGAflE
25 HERHANDO LINDLEY FISHIGAHE
24 HIGHLANDS FRANCIS FISHSGAflE
27 HIGHLANDS ISTOKPOGA FISHSGAflE
23 HIGHLANDS JACKSON FISHSGAflE
21 HIGHLANDS JUNE-IN-HINTER FISHSGAflE
30 HIGHLANDS LETTA FISHSGAflE
31 HIGHLANDS RED BEACH FISHSGAflE
n HILLSBOROUGH THONOTOSASSA FISHSGAflE
33 indian RIMER BLUE CYPRESS FISHSGAflE
34 JEFFERSON fllCCOSUKEE FISHSGAflE
31 LAFAYETTE KQON FISHSGAflE
3i lake BEAUCLAIR FISHSGAflE
V lake CATHERINE FISHSGAflE
31 lake CHERRY FISHSGAflE
33 lake DORA FISHSGAflE
40 lake DORR FISHSGAflE
41 lake EUSTIS FISHSGAflE
-4,7 lake GRIFFIN FISHSGAflE
43 lake HARRIS FISHSGAflE
44 lake LOUISA FISHSGAflE
4i lakh MINNEHAHA FISHSGAflE
44 lake (1INNEDLA FISHSGAflE
4/ lake YALE FISHSGAflE
43 LEON JACKSON FISHSGAflE
V? leon flUHSQN FISHSGAflE
55 ilAMSON FRANCIS FISHSGAflE
51 flARUJN kerr FISHSGAflE
52 HARIDN OCKLAHAHA FISHSGAflE
53 ilARTJJH heir FISHSGAflE
54 CKftLOOSA KARICK FISHSGAflE
55 OKEECHOBEE OKEECHOBEE FISHSGAflE
Table 2-4. (Continued)
GE'S COUNTY LAKE SOURCE
54 OSfifiGE AP8FKA fXSHSGftnt
5/ ORANGE BUTLER FISHSGAflE
53 ORANGE CARLTON FISHSGAflE
5=1 GRANGE JOHNS FISHSGAflE
ORANGE KILLARNEY FISHSGAflE
ORANGE LAHNE FISHSGAflE
a ORANGE BAITLAND FISHSGAflE
a ORANGE OLA FISHSGAflE
4'4 ORANGE TIBET BUTLER FISHSGAflE
i'5 ORANGE UNDERBILL FISHSGAflE
ORANGE VIRGINIA FISHSGAflE
a OSCEOLA ALLIGATOR FISHSGAflE
OSCEOLA FAST TGHOPEKALIGA FISHSGAflE
OSCEOLA KISSItttlEE FISHSGAflE
?o OSCEOLA flftRlAN FISHSGAflE
71 OSCEOLA flARIQN FISHSGAflE
72 OSCEOLA TGHOPEKALIGA FISHSGAflE
73 PASCO CLEAR FISHSGAflE
74 PASCQ BOON FISHSGAflE
75 PINELLAS ALLIGATOR FISHSGAflE
Fc PINELLAS HAGGIORE FISHSGAflE
?7 PINELLAS SEHINDLE FISHSGAflE
7S PINELLAS TARPON FISHSGAflE
7=1 FOLK CROOKED FISHSGAflE
GO POLK EFFIE FISHSGAflE
51. FOLK ELDISE FISHSGAflE
62 POLK GIBSON FISHSGAflE
33 POLK HANCOCK FISHSGAflE
04 POLK HDLLINGSHORTH FISHSGAflE
65 POLK JESSIE FISHSGAflE
8<$ FOLK JULIANA FISHSGAflE
8,? POLK LULU FISHSGAflE
ee FOLK RATTIE � FISHSGAflE
CI FOLK PARKER FISHSGAflE
50 POLK PIERCE FISHSGAflE
ft FOLK REEDY FISHSGAflE
�ft POLK ROSALIE FISHSGAflE
=i3 POLK SCOTT FISHSGAflE
�ft POLK STAR FISHSGAflE
15 POLK TRACY FISHSGAflE
POLK HALES FISHSGAflE
FOLK UEOHYAKAPKA FISHSGAflE
SANTA ROSA BEAR FISHSGAflE
SUflTER PANASCFFKEE FISHSGAflE
ICO UNION BUTLER FISHSGAflE
101 UNION PALESTINE FISHSGAflE
102 VOLUSIA HINONA FISHSGAflE
103 WASHINGTON PORTER POND FISHSGAflE
The overall GFWFC project (initiated in 1966) included the following long-term objectives:
1) document changes of water quality in selected Florida lakes,
2) gather background data to further aid scientific understanding of rates of water quality changes in Florida lakes,
3) establish a guide for appropriate water quality criteria to evaluate Florida's fishery resources,
4) provide information that could be used in evaluating the effects of pollution in Florida lakes.
Starting with the 1969-70 sampling and continuing through the rest of the project, the Commission attempted to classify the survey lakes. The classification involved three parameters that were thought to reflect biological conditions present in the lakes:
1) turbidity difference (from filtered and unfiltered measurements),
2) chlorophyll ji, and
3) particulate organic nitrogen content.
The lakes were arranged in order of the highest values for each parameter. Lowest values were assigned a rank of one, next lowest a rank of two, and so forth. The ranks for the three parameters were added up for each lake, and a final rank was established (the lowest possible final rank number being 3.0). It is quite obvious that this is strictly a relative classification system. The rankings do not necessarily reflect absolute values of turbidity, chlorophyll a, and organic nitrogen but only the relative values.
The GFWFC (1972) compared its trophic ranking system with the trophic index ranking scheme of Brezonik and Shannon (1971). Of 55 lakes sampled by the latter authors, 14 were included in the 51 lakes sampled by the GFWFC
in 1971. The Commission concluded that there was a strong similarity in trophic rankings computed by the two schemes. It should be emphasized, however, that the GFWFC scheme was merely a relative ranking procedure (based on three parameters), whereas the Brezonik-Shannon scheme assigned index values based on actual values for seven trophic indicators.
The parameters investigated and the laboratory methods for each are included in Table 4 of Appendix D.
U.S.G.S. - PER Lake Survey
The U.S. Geological Survey, in conjunction with the State of Florida Department of Environmental Regulation recently concluded a broad survey of Florida lakes. Sampling was conducted between February 1979 and May 1981 on 96 lakes in the state (Table 2-5). The study was designed primarily to initiate a statewide effort to classify Florida lakes in response to section 314 of the Clean Water Act (1977). Lakes were sampled based on suggestions from county and state officials. These lakes were either possible candidates for restoration studies or were the subject of numerous citizen complaints concerning water quality problems. Site-specific reports were written for each lake and a final statistical analysis of the data from all 96 lakes was prepared (personal communication, L. Edmiston, 1982).
The format for reporting results is almost identical for each of the lakes. The lake is identified by name, county, and location (center of lake given in terms of latitude and longitude). Physical parameters such as surface ar , drainage area, maximum depth, mean depth, and lake volume are listed. The lakes were sampled at a varying number of points (three to eight) depending on the size of the lake. Secchi disk transparency was measured at
Table 2-5. Lakes of the USGS
- DER Study.
COUNTY LAKE SOURCE
i ALACHUA LOCHLOOSA USGS-DER
2 ALACHUA NEUNANS usgs-DER
3 ALACHUA ORANGE USGS-DER
4 ALACHUA SANTA fe usgs-DER
5 BAKER OCEAN POND usgs-DER
/. BAY DEER POINT USGS-DER
7 BAY FIERI al USGS-DER
5 BRADFORD ROHELL USGS-der
1 BRADFORD SAI1PS0N USGS-DER
10 BREVARD HELEN BLAZES USGS-DER
11 BREVARD POINSETT USGS-DER
12 BSEVARD SOUTH USGS-der
13 CITRUS TSALA APOPKA
15 CLAY GENEVA USGS-der
16 COLLIER TRAFFORD USGS-DER
17 C0LUI1BIA ALLIGATOR USGS-DER
IS GADSDEN TALfiUIN USGS-DER
11 GULF DEAD USGS-DER
20 HERNANDO FOUNTAIN USGS-DER
21 HIGHLANDS DAilON USGS-DER
22 highlands DINNER USGS-DER
23 HIGHLANDS ISTOKPOGA usgs-DER
24 HIGHLANDS ' JACKSON USGS-DER
25 HIGHLANDS PLACID usgs-DER
26 HILLSBOROUGH BROOKES usgs-DER
27 HILLSBOROUGH KEYSTONE usgs-DER
23 HILLSBOROUGH THDNOTDSASSA USGS-DER
21 INDIAN RIVER BLUE CYPRESS usgs-DER
30 JACKSON CDfiPASS usgs-DER
31 JACKSON OCHEESEE POND usgs-DER
32 JEFFERSON fllCCOSUKEE usgs-DER
33 LAKE DEHHAH usgs-DER
34 LAKE DORR
35 LAKE ENOLA usgs-DER
36 LAKE KATHRYN usgs-DER
37 LAKE LOUISA USGS-DER
33 LAKE HINNEOLA USGS-DER
31 LAKE TUTUOLA USGS-DER
40 LEON IAHONIA usgs-DER
41 LEVY ROUSSEAU usgs-DER
42 LIBERTY flYSTIC usgs-DER
43 flARION BRYANT USGS-DER
44 karion KERR USGS-DER
45 ORANGE BASS USGS-DER
45 CSAHGE BUTLER USGS-DER
4? ORANGE CLEAR USGS-DER
45 GRANGE DGKN USGS-DER
41 ORANGE FAIflVIEH usgs-DER
50 ORANGE HOLDen USGS-DER
51 ORANGE HOURGLASS USGS-DER
52 OSAHGE JOHNS usgs-DER
53 ORANGE H AIT LAND USGS-DER
54 GRANGE HANN USGS-DER
55 ORANGE PEARL usgs-DER
CSAHCE SHEEN USGS-DER
5? ORANGE STARKE usgs-DER
5* OSAHGE SUSANNAH USGS-DER
si OSAHGE TIBET BUTLER USGS-DER
($0 ORANGE jjhderhill usgs-DER
61 OSCEOLA ALLIGATOR USGS-DER
62 OSCEOLA CYPRESS USGS-DER
*1 V -1 OSCEOLA GENTRY usgs-DER
�5 4 OSCEOLA HATCHIKEHA USGS-DER
6:5 OSCEOLA J1ARIAK usgs-der
PALH BEACH OSBORNE usgs-der
/? pasco THOilAS usgs-der
PINELLAS flAGGIDRE usgs-der
61 FDLK ALFRED usgs-der
7A J V PDtf ARBJJCKLE usgs-der
71 t 4. FCLK ARETTA usgs-der
70 1 L. FOLK BUFFUft usgs-der
73 FOLK CLINCH usgs-DER
Table 2-5. (Continued)
� FLORIDA LAKES K � USGS - FDER LAKE STUDY �
COUNTY LAKE SDURCE
74 POLK CROOKED USGS-DER
75 POLK ECHO USGS-DER
7^ POLK GIBSON USGS-DER
7? POLK HANCOCK USGS-DER
78 POLK HOLLINGSHORTH USGS-DER
71 POLK HOUARD USGS-DER
30 POLK HATTIE USGS-DER
81 POLK PARKER USGS-DER
82 POLK PIERCE USGS-DER
53 PUTNAM COHPEN USGS-DER
84 PUTNAH GEORGE USGS-DER
55 PUTNAH GEORGES USGS-DER
8* SEHINOLE JESSUP USGS-DER
87 SEHINOLE LOTUS USGS-DER
88 SEHINOLE HILLS USGS-DER
81 SEHINOLE PEARL USGS-DER
10 SEHINOLE TRIPLET USGS-DER
11 SUHTER DEATON USGS-DER
12 SUHTER OKAHUHPKA USGS-DER
13 SUHTER PANASOFFKEE USGS-DER
14 UNION BUTLER USGS-DER
15 VOLUSIA ASHBY USGS-DER
�W VOLUSIA HOLLY USGS-DER
all stations, and depth profiles of dissolved oxygen concentration and temperature were usually included for at least three stations.
Other physical and chemical meaurements were made on a depth-integrated water sample from a single station (usually mid-lake). Measured parameters included: ammonium, nitrate, nitrite, total organic nitrogen, total nitrogen, orthophosphate (soluble reactive phosphate, SRP), total phosphorus, turbidity, dissolved solids, specific conductance, pH, chlorophyll a^ and phaeophytin. Also in each report was a section devoted to a qualitative analysis and description of the lake. The outline of this segment typically included:
1) lake setting - general topography of surrounding area;
2) major inflows, outflows, and control structures;
3) land use surrounding the lake and percentage of each use;
4) point 'sources of pollution;
5) non-point pollution sources and any controls on these;
6) recreational facilities, access roads, and ramps;
7) occurrence of algae, aquatic plants, sediments, and other such deterrents to recreational use;
8) historical information from local residents;
9) aerial photographs of lake.
Each lake report included two or three maps of the lake and surrounding areas that show station and aerial photo locations. Aquatic Weeds Study
This study by the University of Florida Center for Aquatic Weeds sampled 165 Florida lakes (Table 2-6) bet <>.en September 1979 and August 1980 (Canfield,
1981). The lakes ranged from ultra-oligotrophic to hyper-eutrophic and dis-played vastly differing limnological conditions. Parameters and methods are listed in Table 5 of Appendix D. The study was designed to determine the chemical and trophic state characteristics of Florida lakes in different physiographic regions of the state and to determine relationships between mineral composition of lakes and the surface geology and physiography. Assessments were made of regional differences in chemical composition that may be of biological importance.
The State was divided into three major physiographic zones:
1) Northern zone - Region of continuous high ground which forms a broad upland in northern Florida. Most of the region is above the piezometric surface; thus it is characterized by features of dry highland or dead zone karst with large lake level fluctuations.
2) Central zone - Region of discontinuous highlands. Ridges are generally above the piezometric surface and valleys are generally below the piezometric surface.
3) Southern zone - Characterized by large expanses of wetlands. Large majority of region is below the piezometric surface. Other than Lake Okeechobee, there are few lakes in this region.
The report included 15 figures (isograms) showing statewide areal variation for the limnological parameters measured. Since only 165 out of the total 7700 lakes were examined, and because the measurements were infrequent all of the isograms must be considered as approximate. However, several noteworthy trends were distinguished from the data analysis.
For example, the physiographic region with the greatest variability in water quality is the central zone. The geology and physiography of this region are more diverse than is the case in the northern and southern zones. Additionally, except for total iron and color, there is a general increase in chemical concentrations (and in pH) from northwest to southeast
Table 2-6. Lakes of the Aquatic Weeds Study.
CBS county LAKE SOURCE
1 ALACHUA LOCHLDDSA Afl.HED
2 ALACHUA NEHNANS Afl.HEED
3 ALACHUA ORANGE Afl.HED
4 ALACHUA HAUBERG Afl.HED
5 BAKER OCEAN PDND Afl.HED
6 BAY DEER POINT Afl.HED
7 BAY MERIAL Afl.HED
BRADFORD CROSBY Afl.HED
BRADFORD HAMPTON Afl.HED
10 BRADFORD ROHELL Afl.HED
11 BRADFORD SAMPSON Afl.HED
12 BREVARD POINSETT Afl.HED
13 BREVARD WASHINGTON Afl.HED
14 BROWARD TIGER TAIL AOEED
15 CALHOUN DEAD Afl.HED
14 CALHOUN MCKENZIE Afl.HED
17 CALHOUN MIRROU Afl.HED
15 CALHOUN TURKEY PEN PDND Afl.HED
11 CITRUS TSALA APOPKA Afl.UED
20 CLAY GENEVA Afl.HED
21 CLAY KINGSLEY Afl.UED
22 CLAY LDHERY Afl.HED
23 CLAY MAGNOLIA Afl.HED
24 COLLIER TRAFFORD Afl.HED
25 COLUMBIA ALLIGATOR Afl.HED
24 COLUMBIA HATERTDHH AOEED
27 FLAGLER CRESCENT Afl.UED
28 FLAGLER DISSTON Afl.UED
21 FRANKLIN CORN LANDING Afl.HED
30 GADSDEN SUWANNEE Afl.HED
31 GADSDEN TALflUIN Afl.UED
32 GULF UIBICD Afl.HEED
33 HERNANDO LINDLEY Afl.UED
34 HERNANDO MOUNTAIN Afl.HEED
35 HIGHLANDS DINNER Afl.HED
34 HIGHLANDS HUNTLEY Afl.HED,
37 HIGHLANDS ISTDKPDGA Afl.HED
33 HIGHLANDS JACKSON Afl.HEED'
31 HIGHLANDS JOSEPHINE Afl.HED
40 HIGHLANDS LITTLE RED HATER Afl.HEED
41 HIGHLANDS LOTELA Afl.HED
*2 HIGHLANDS PLACID Afl.HEED
43 HIGHLANDS RED BEACH Afl.HEED
44 HIGHLANDS SEBRING Afl.UED
45 HILLSBOROUGH THONOTDSASSA Afl.UED
44 HQLBES SUN ' Afl.HED
4? HOLMES VICTOR Afl.UED
48 INDIAN RIVER BLUE CYPRESS Afl.HEED
41 JACKSON COMPASS Afl.UEED
50 JACKSON BERRITTS BILL POND Afl.HEED
51 JACKSON OCHEESEE POND Afl.HED
52 JACKSON ROUND Afl.HED
53 LAFAYETTE TOHHSEND PDND Afl.UED
54 LAKE CRESCENT Afl.UED
55 LAKE DORA Afl.UED
54 LAKE DORR Afl.UEED
57 LAKE EUSTIS Afl.HED
-58 LAKE GRIFFIN Afl.HED
51 LAKE HARRIS Afl.UED
�0 LAKE LOUISA Afl.UEED
41 LAKE- I1IXXEHAHA Afl.HEED
42 LAKE BINNEOLA Afl.HED
43 LAKE WILDCAT Afl.HEED
44 LAKE YALE Afl.HED
45 LEON CARR Afl.HED
44 LEiJi IABDNIA Afl.HEED
47 LEGN JACKSON Afl.HEED
Iv, LECH BliHSON Afl.HEED
41 LEW ROUSSEAU Afl.HEED
MADISON CHERRY Afl.HEED
71 HYSTIC Afl.UEED
72 HAHATEE MANATEE RESERVOIR Afl.HEED
73 Mfi&OH EATON Afl.HED
K BB BSB KBBBK KBBBH KBKS8 SB
Table 2-6. (Continued) � FLORIDA LAKES k
b CENTER FOR ASUATIC WEEDS �
� KB BBBBBBBBSSBSB Bfe'Bfifi BBBBB KB
ESS COUNTY LAKE SOURCE
74 MARION KERR AO.WEED
75 MARION SELLERS AOEED
74 MARION SMITH AOEED
l t PARION WEIR AOEED
73 OKALOOSA HURRICANE AS.WEED
74 OKALOOSA KARICK AOEED
3? OKEECHOBEE OKEECHOBEE AOEED
81 ORANGE APOPKA AOEED
82 ORANGE BALDWIN AOEED
83 ORANGE BUTLER AOEED
84 ORANGE CONWAY AOEED
85 ORANGE DOWN AOEED
fl4 GRANGE FAIRVIEW AS.WEED
87 GRANGE HART AOEED
58 GRANGE JESSAMINE AOEED
SI GRANGE JOHNS AOEED
10 GRANGE LAWNE AOEED
�il CSANGE MAITLAND AOEED
12 GSANGE MARY JANE AOEED
13 GRANGE UNDERHILL AOEED
14 GRANGE VIRGINIA AOEED
15 OSCEOLA ALLIGATOR AOEED
14 OSCEOLA CYPRESS AOEED
17 OSCEOLA EAST TGHOPEKALIGA AOEED
13 OSCEOLA GENTRY AOEED
11 OSCEOLA HATCHINEHA AOEED
100 GSCEQLA KISSIMMEE AOEED
101 OSCEOLA MARIAN AOEED
102 OSCEOLA TGHOPEKALIGA AOEED
103 FALM BEACH OSBORNE AOEED
104 PASCO CREWS AOEED
105 PASCO IDLA AOEED
104 PASCO MOON AOEED
107 PASCO PADGETT AOEED
103 PASCO PASADENA AOEED
1C1 PINELLAS MAGGIORE AOEED
110 PINELLAS SEMINOLE AOEED
111 PINELLAS TARPON AS.WEED
112 FOLK AGNES AS.WEED
in FOLK ARBUCKLE AS.WEED
114 FOLK ARETTA AS.WEED
115 FOLK ARIANA AS.WEED
114 PflLK BUFFUH AS.WEED
117 FOLK CLINCH AS.WEED
118 FOLK EAGLE AS.WEED
111 FOLK GIBSON AS.WEED
120 FOLK HOWARD AS.WEED
121 FOLK LITTLE CROOKED AS.WEED
122 FOLK LOWER Y AS.WEED
123 POLK MARION AS.WEED
124 FOLK PARKER AS.WEED
125 FOLK PIERCE AS.WEED
124 FOLK REEDY AS.WEED
127 POLK ROSALIE AS.WEED
123 FOLK TIGER AS.WEED
121 FOLK WALES AS.WEED
130 FOLK WEOHYAKAPKA AS.WEED
131 PUTNAM BROWARD AS.WEED
132 PUTNAM GEORGE AS.WEED
133 PUTNAM MARGARET AS.WEED
134 FUTNAM STELLA AS.WEED
135 SANTA ROSA BEAR A3.WEED
135 SARASOTA UPPER MYAKKA AS.WEED
137 SEMINOLE JESSUP AS.WEED
133 SEMINOLE SEMINOLE AS.WEED
131 SUITES 0EATON A3.WEED
�ft. \ SUITER HIDNA AS.WEED
141 SUMTER OKAHUMFKA A3.WEED
14? SUITER PANASGFFKEE AS.WEED
143 SUWANNEE LOUISE AS.WEED
144 SUWANNEE SUSAH AS. WEED
145 UNION BUTLER AS.WEED
144 UKCOH PALESTINE AS.WEED
Table 2-6. (Continued)
� FLORIDA LAKES *
� CENTER FOR ASUATIC HEEDS �
DBS COUNTY LAKE SOURCE
147 VOLUSIA ASHBY Afl.HEED
148 VOLUSIA DEXTER Afl.HEED
143 VOLUSIA DIAS Afl.HEED
150 VOLUSIA HARNEY Afl.UEED
151 VOLUSIA tiONROE Afl.HEED
152 VOLUSIA HINNEfflSETT Afl.HEED
153 UAKULLA ELLEN Afl.UEED
154 UAKULLA OTTER Afl.HEED
155 UAKULLA SANTA FE Afl.HEED
154 UALTON JACKSON Afl.HEED
157 HALTDN JUNIPER BAY Afl.HEED
158 UALTON OYSTER Afl.HEED
151 HALTDN STANLEY Afl.UEED
140 HALTON HESTERN Afl.HEED
141 HASHINSTON CRYSTAL Afl.UEED
142 HASHINGTON DUNFDRD POND Afl.UEED
143 HASHINGTON GAP PDND Afl.UEED
144 HASHINGTON PATE POND Afl.UEED
145 HASHING TON SfllTH Afl.HEED
and from highlands to lowlands. As a result, eutrophic conditions exist primarily in peninsular Florida. Relatively low alkalinity and hardness values and relatively high total nitrogen, total phosphorus, and chlorophyll a. values in the lakes lead to the conclusion that Florida lakes can be generally characterized as soft-water, productive bodies of water. In agreement with findings of other regional limnology studies, the author concluded that a strong relationship exists between the mineral composition of Florida's freshwater lakes and surface geology and physiography. / For example, lakes in the northern Central Valley of Florida, where there are major deposits of the phosphatic Hawthorn Formation, are naturally eutrophic, e.g., Lochloosa, Orange and Newnan's Lakes in Alachua County. In contrast, lakes located in nutrient-poor sandy soils, as occur in Washington and Jackson counties in the Panhandle, are naturally oligotrophic. A similar statement can be made about the Trail Ridge Lakes in Clay and Putnam Counties.
The use of empirical phosphorus loading models developed specifically for Florida was also stressed in the report.
Selected Florida Urban Lakes
This survey was done in summer of 1981 as part of the present (DER-sponsored) lake classification project. The purpose of the survey was to obtain water quality data on selected "urban" lakes deemed of interest due to potential problems and/or the desirability for restoration. Urban lakes generally have large amounts of stress from sewage effluent and/or other point source discharges, storm water runoff, and fertilizer losses from
residential lawns. An attempt was made to enlarge the small data base on urban Florida lakes by sampling a cross section of 30 urban lakes with varying morphology, proximity to urban centers, population density and impervious land in the watershed.
Lakes were sampled in four urban areas: Miami, Tampa, Orlando-Winter Park, and Lakeland (Table 2-7). The lakes were chosen by recommendation from various sources on the criteria of restoration need or lack of previous data. Locations, sizes, and land use features on topographic maps also were considered in making selections. Substitutes were identified and sampled when the primary lakes were found unacceptable for sampling (e.g., no access).
Temperature and dissolved oxygen profiles were obtained at meter intervals at mid-lake stations. A mid-lake water sample (depth-integrated at meter intervals) was utilized for chemical analysis and identification of dominant algae. Notes were taken regarding access, recreation, presence of filamentous algae, submerged or emergent macrophytes, and surrounding land use and point sources for each lake sampled. The parameters analyzed and evaluative methods are listed in Table 6 of Appendix D.
Water Management District Studies
Data for several lakes have been gathered by some of the state's five water management districts. Some of the sampling is routine and other sampling is conducted as part of special studies. A brief review of these data is given below.
A total of 53 lakes in the Southwest Florida Water Management District (SWFWMD) were sampled at least once during 1980-81 in an effort to provide background information on the water quality of the District's lakes. Data on lakes listed in Table 2-8 are given by Attardi (1981).
Table 2-7. Urban Lakes Sampled During Project.
DBS COUNTY LAKE SOURCE
I DADE BAHSI LAKE aAS
2 DADE BLUE LAGOON LAKE CLAS
3 DADE CATAUHA LAKE CLAS
4 DADE HENRY LAKE CLAS
5 DADE KATHARINE LAKE CLAS
6 DADE LAURENCE EAST LAKE CLAS
7 DADE LOUISE LAKE CLAS
8 DADE MYRTLE LAKE CLAS
R DADE SKY LAKE CLAS
10 DADE SOUTH BASS LAKE CLAS
11 HILLSBOROUGH CARROLL LAKE CLAS
12 HILLSBOROUGH EGYPT LAKE CLAS
11 HILLSBOROUGH ELLEN LAKE CLAS
14 HILLSBOROUGH MAGDALENE LAKE CLAS
15 08AHCE CHEROKEE LAKE CLAS
16 ORANGE DAVIS LAKE CLAS
17 ORANGE DRUID LAKE CLAS
18 ORANGE HIGHLAND LAKE CLAS
m ORANGE IJ81A LAKE CLAS
20 ORANGE IVAHHOE LAKE CLAS
21 ORANGE IVAHHOE LAKE CLAS
22 ORANGE KILLARNEY LAKE CLAS
23 ORANGE LUCERNE LAKE CLAS
24 ORANGE KAN LAKE CLAS
25 ORANGE RUCK LAKE CLAS
26 ORANGE SILVER LAKE CLAS
27 ORANGE UHDERHILL LAKE CLAS
28 POLK BEULAH LAKE CLAS
m POLK BEiiLAH LAKE CLAS
30 POLK ' HUNTER LAKE CLAS
31 PDLK MAUDE LAKE CLAS
32 POLK MEE LAKE CLAS
A more detailed study of Sawgrass Lake in Pinellas County was undertaken from July 1977 to July 1979 by the SWFWMD in cooperation with the City of St. Petersburg and the USGS (Dooris, 1980). Samples were taken at approximately monthly intervals, and results are included in the data base.
A large quantity of data has been gathered on Lake Okeechobee over the past decade by the South Florida Water Management District (SFWMD). Data for April 1973 through March 1980 were summarized and analyzed in detail by Federico et al. (1981), and the data are included in the data base.
Other lake data gathered by the SFWMD and by the St. Johns River Water Management District were unavailable in computerized form and could not be included in the data base in a timely manner. Such data may be included in the future. (Some SFWMD data are included in the STORET system.) No data were available from the Suwannee River or Northwest Florida Water Management Districts.
In addition to the three University of Florida studies described earlier, other studies on selected lakes have been conducted at the University of Florida and several other universities in the state.
A study on nonpoint source runoff by the University of Central Florida included detailed monitoring of Lake Eola in Orlando (Orange County), a classic example of a small lake surrounded by a large urbanized watershed (Wanielista, 1 ^6, Wanielista et al., 1982). Data from this study and subsequent data through June 1981 are included in the data base. Another Orlando lake, Lake Ivanhoe, was studied from
Table 2-8. Lakes Sampled by the Southwest Florida Water Management District.
sts COUNTY LAKE SOURCE
1 HERNANDO HUNTERS SWFWHD
2 HIGHLANDS ANGELA SWFWHD
3 HIGHLANDS ANOKA SWFWHD
4 HIGHLANDS FRANCIS SWFWHD
5 HIGHLANDS GLENADA SWFWHD
6 HIGHLANDS JUNE-IN-WINTER SWFWHD
7 HIGHLANDS LELIA SWFWHD
� HIGHLANDS LETTA SWFWHD
HIGHLANDS LITTLE BONNET SWFWHD
1? HIGHLANDS LITTLE RED WATER SWFWHD
11 HIGHLANDS LOTELA SWFWHD
12 HIGHLANDS RED WATER SWFUHD
13 HIGHLANDS MANE SWFWHD
14 HILLSBOROUGH GRADY SWFWHD
15 HILLSBOROUGH WIHAUHA SWFWHD
U PASCO BLUE SWFWHD
17 PASCO CREWS SWFWHD
13 PASCO I0LA SWFWHD
11 PASCO JESSAHINE SWFWHD
25 PASCO HIDDLE SWFWHD
21 PASCO HOQDY SWFWHD
22 PINELLAS ALLIGATOR SWFWHD
23 PINELLAS SALT SWFWHD
24 FOLK AGNES SWFWHD
21 P&K ANN SWFWHD
26 FOLK ARETTA SWFWHD
27 POLK ARIANA SWFWHD
23 POLK BONNETT SWFWHD
21 FOLK BONNY SWFWHD
35 FOLK BUFFUH SWFWHD
31 FOLK CLEARWATER SWFWHD
32 FOLK CONNIE SWFWHD
33 FOLK FANNIE SWFWHD
34 FOLK GARFIELD SWFWHD
35 FOLK GIBSON SWFWHD
36 FOLK GUH SWFWHD
37 POLK HAINES SWFWHD
33 FOLK HANCOCK SWFWHD
31 FOLK HELENE SWFWHD
45 FOLK HENRY SWFWHD
41 FOLK HUNTER SWFWHD
4? FOLK LENA SWFWHD
43 FOLK MATTE SWFWHD
44 FOLK HUD SWFWHD
45 FOLK ROCHELLE SWFWHD
4 s' FOLK SANITARY SWFWHD
47 FOLK SCOTT SWFWHD
43 FOLK SHART SWFWHD
41 POLK SWDDFE SWFWHD
55 FOLK TENNESSEE SWFWHD
51 FOLK THOHAS SWFWHD
52 POLK WHISTLER SWFWHD
53 SEHINOLE BANANA SWFWHD
February through April 1979 as part of a highway runoff study for the Florida Department of Transportation (Wanielista et al., 1980), and these data are also included.
Lake Jackson, near Tallahassee in Leon County, was monitored from June 1971 through June 1981 by workers at Florida State University and the Florida Institute of Technology. Data from reports by Harris and Turner (1974), Mason and Belanger (1978) and Burnett and Donahue (1982) are included in the data base. Also included in the data base are data from a 1977-78 study of Lake Washington (Brevard County) by Mason and Belanger (1979).
The Lake Conway data set was developed as part of an investigation of the ability of the white amur (grass carp) to control aquatic weeds. The University of Florida, sponsored by the U.S. Army Corps of Engineers Waterways Experiment Station, conducted a number of studies to investigate the effect of the white amur (Crisman and Kooijman, 1981). As part of these studies water quality was monitored throughout the period of inquiry. Sampling was performed at meter intervals from the center of each pool in the lake system. Samples were analyzed for four nitrogen and two phosphorus forms and for routine limnological parameters (Sompongse, 1978). Nutrient data were used in various input-output and simulation eutrophication models (Blancher, 1979).
In addition to Lake Conway, 16 other lakes (Table 2-9) were sampled by the University of Florida in related studies (T.L. Crisman, personal communication, 1982). These data are also included in the data base.
As part of a large scale nutrient abatement and lake restoration program on Lake Apopka, a water quality monitoring study of the Oklawaha chain of lakes was undertaken by the University of Florida, Department of Environmental Engineering Sciences under contract to the Florida Department of Environmental
Regulation. Bimonthly and monthly samples were taken from the lakes over four years (1977-1980) to monitor changes in water quality (Brezonik et.al., 1981). Lakes Apopka, Beauclair, Dora, Eustis and Griffin each were sampled at several stations and analyzed for numerous chemical and physical parameters. These data were later condensed to mean monthly values by lake for the four year period. Analytical methods were similar to those for the other University of Florida studies.
FDER Lake Study
The Florida Department of Environmental Regulation (L. Edmiston, personal communication, 1982) conducted a survey of 42 lakes around the state (Table 2-10) to evaluate limiting water quality and nutrients (by algal assays). The lakes, which ranged in area from 72 to 18,630 ha and had average depths between 2.0 and 3.0 m were sampled three times in summer and fall (of 1977). Trophic states of the lakes ranged from oligotrophic to hypereutrophic.
The primary purpose of the survey was to define nutrient"concentrations and limiting nutrient conditions in the lakes. Nutrient limitation was assessed from N/P ratios and the EPA algal assay procedure (AAP), using the test alga Selenastrum capricornutum (Printz). Actual limiting nutrients were compared to nitrogen/phosphorus ratios to determine their relationships. Physical and chemical measurements analyzed on the lake samples included: Secchi disk transparency, pH, conductivity, dissolved oxygen, turbidity, chlorophyll a_, ammonium, nitrate-nitrite, total Kjeldahl nitrogen, ortho-phosphate (SRP), and total phosphorus.
EPA STORET Data
As part of the project all Florida lake data contained in the massive EPA STORET data bank were retrieved and sent to UF on a magnetic tape.
Table 2-9. Lakes Sampled as Part of the Lake Conway Study.
Observation County Lake Source
1 Alachua Newnans Crisman
2 Alachua Santa Fe Crisman
3 Baker Ocean Pond Crisman
4 Bradford Sampson Crisman
5 Clay Kingsley Crisman
6 Highlands Annie Crisman
7 Highlands Francis Crisman
8 Highlands Jackson Crisman
9 Highlands Placid Crisman
10 Hillsborough Thonotosassa Crisman
11 Indian River Blue Cypress Crisman
12 Lake Eustis Crisman
13 Marion Kerr Crisman
14 Osceola East Tohopeka- Crisman
15 Polk Scott Crisman
16 Sumter Miona Crisman
Table 2-10. Lakes Sampled by the Department of Environmental Regulation.
CBS CDIKTY LAKE SOURCE
1 ALACHUA LOCHLOOSA FDER
2 ALACHUA NEWNANS FDER
s 3 ALACHUA ORANGE FDER
4 BAKER OCEAN PDND FDER
5 BAY WHITE WESTERN FDER
6 BRADFORD CROSBY FDER
7 BEEVARD FOINSETT FDER
i CALHDUK DEAD FDER
R CLAY KINGSLEY FDER
10 COLLIER TRAFFORD FDER
11 HIGHLANDS ISTDKFOGA FDER
�f -"J HIGHLANDS JACKSON FDER
13 HIGHLANDS JUNE-IN-WINTER FDER
14 HIGHLANDS LOTELA FDER
15 HILLSBOROUGH THONOTDSASSA FDER
li JACKSON flERRITTS MILL POND FDER
17 JACKSON OCHEESEE PDND FDER
IS LAKE DORA FDER
11 LAKE EUSTIS FDER
20 LAKE GRIFFIN FDER
21 LAKE HARRIS FDER
22 LAKE MINNEDLA FDER
23 LEDN BRADFORD FDER
24 LEON JACKSON FDER
25 MARION WEIR FDER
26 ORANGE BAY FDER
27 OSANGE BUTLER FDER
2i OSCEOLA EAST TDHOPEKALIGA FDER
21 OSCEOLA HATCHINEHA FDER
30 OSCEOLA TDHOPEKALIGA FDER
31 PINELLAS TARPON FDER
32 FOLK BANANA FDER
33 POLK HOLLINGSWDRTH FDEi?
34 POLK LULU FDER
35 POLK REEDY FDER
26 POLK WEDHYAKAPKA FDER
37 PUTNAM GEORGE FDER
33 SARASOTA UPPER HYAKKA FDER
31 SEMINOLE JESSUP FDER
40 SUMTER PANASOFFKEE FDER
41 VOLUSIA MONROE FDER
I n WALTON JACKSON FDER
Table 2-11. Lakes for Which Data Were Obtained from STORET.
1 ftl.AC.HUfl f-LTHO
2 ALACHUA BIVtKS arm
3 ALACHUA LITTLE SANTA FE
4 ALACHUA LOCHLDOSA
5 ALACHUA NEWNANS
4 ALACHUA ORANGE
7 ALACHUA FAYKES PRAIRIE
S ALACHUA SANTA FE
i BAKER CCEftN FOND
10 BAY [�ER FEUNT
11 BAY SERIAL
12 BAY FCUELL
13 BRADFORD CROSBY
14 BRADFORD JAMPTDN
15 BRADFORD FOHELL
14 BRADFORD SAMPSON
17 BREVARD CLEAR
18 BREVARD HELEN EiAZES
11 BREVARD LGUGKMAN
20 BREVARD PCIHSETT
21 BREVARD SALT
22 BREVARD SSHSRASS
23 BREVARD SOUTH
24 BREVARD WSHIKSTDK
25 BREVARD iilKOER CCDRGE
21 BROWARD FROSPECT
28 mum SVLVIA
21 CALHOUN LEAD
30 CHARLOTTE 40 ACRE POND
31 CITRUS rORRISDN POND
32 CITRUS TSALA APOPKA
33 CITRUS TSALA APOPKA(F)
34 CITRUS TSALA APOPKA(H)
35 CITRUS TSALA APOPKA(I)
34 CLAY �18 LAKE JOHNSON
37 CLAY ELUE FOND
38 CLAY BROOKLYN
31 CLAY CRYSTAL
40 CLAY [GCTORS
41 CLAY G-LHEVA
42 CLAY KALL
43 CLAY JGHNSGH
44 CLAY KINGSLEY
45 CLAY LGCH LOMMDND
44 CLAY rAGMLIA
47 CLAY FEBtLE
45 CLAY SAND HILL
41 CLAY SSIJH
50 COLLIER CYPRESS POND
51 COLLIER LANTERN
52 COLLIER TPAFF
53 COLUMBIA rLLIGATOR
54 COLUMBIA JiATESTGWN
55 DADE ELUE
54 DADE CAROLINE
57 DADE CATALIHE
DADE LAKE KO MIAMI BEACH
40 DIXIE GiiVtfiNOR HILL
41 DUVAL IHESDN POND
42 FLAGLER CCESCEKT
43 FLAGLER S-ISSTDH
44 GADSDEN TALSUIN
45 64 GLADES GULF HICFOCHEE im
67 GULF kimcn
45 HAMILTON EEfc HftVEK BAY
41 HERHAHDO f.YSIRE
70 HERNANDO HIGHLAND
71 HERNANDO HORSE
72 HERNANDO mKfERS
73 HERNANDO LIK9LEY
74 HERNANDO HEFF
STDRET 01J LAKE ALT HO AT WALDO FLA
STDRET BIVANS ARM NR GAINESVILLE FLA
STDRET 01J LITTLE SANTA FE LAKE NR HALD
STDRET LOCHLDOSA LAKE AT LOCHLDOSA FLA
STORET NEWHANS LAKE NR GAINESVILLE FLA
STDRET ORANGE LAKE AT ORANGE LAKE, FLA.
STDRET PAYNE'S PRAIRIE LAKE (NO NAME)
STORET SANTA FE LAKE NR KEYSTONE HTS, F
STORET OCEAN POHD AT DLUSTEE, FLA
STORET DEER POINT LAKE NEAR PANAMA CITY
STORET MERIAL LAKE NR CREENHEAD FL
STORET POWELL LAKE 3/4 DISTANCE UP WEST
STORET LAKE CROSBY II NORTH SHORE
STORET LAKE HAMPTON II HEAR NORTH SHORE
STORET 01J LAKE ROWELL NR STARKE FLA
STORET 01J LAKE SAMPSON NR STARKE FLA
STORET 01E CLEAR L NR CDCDA FLA
STDRET 01E LAKE HELEN BLAZES NEAR DEER
STDRET 01E LDUGHMANS L NR HIHS FLA
STDRET LAKE POINSETT NR. COCOA, FLA.
STDRET 01E SALT L AT HWY 44 NR HIHS FLA
STORET 01E SAUGRASS LAKE NEAR MELBOURNE
STDRET 01E SO LAKE NR TITUSVILLE FLA
STORET LAKE WASHINGTON NEAR EAU GALLIE,
STORET 01E LAKE WINDER NEAR BOHAVENTURE
STORET 10B LAKE GEORGE NR DANIA. FLA.
STORET 10B FT LAUDERDALE PROSPECT LK NR
STDRET LAKE SYLVIA - CENTER
STDRET DEAD LKS ST REC AR 100YD DFFSHOR
STDRET FORTY ACRE PDND NR PLACIDA, FLA
STDRET HARRISON PDND AT LECANTO*FLA.
STORET TSALA APOPKA L AT HUY 31A BRIDGE
STORET TSALA APOPKA LAKE AT FLORAL CITY
STORET TSALA APOPKA LAKE AT HERNANDO, F
STORET TSALA APOPKA LK AT INVERNESS, FL
STDRET BIG LAKE JOHNSON,NR KEYSTONE HTS
STORET 01E BLUE POND NR KEYSTONE HGTS F
STORET BROOKLYN LAKE NR KEYSTONE HGTS F
STORET CRYSTAL LK NR KEYSTONE HGTS FLA
STDRET 01E DOCTORS LAKE AT ORANGE PARK
STDRET LAKE GENEVA AT KEYSTONE HEIGHTS
STDRET HALL LAK NR KEYSTONE HGTS FLA
STDRET LT LAKE JOHNSDN NR KEYSTONE HGTS
STORET KINGSLEY LAKE AT CAMP BLANDIKG F
STORET 01E LOCH LOHHDND NR KEYSTONE HGT
STORET MAGNOLIA LAKE NEAR KEYSTONE HEIG
STORET PEBBLE LAKE NR KEYSTONE HEIGHTS STORET SAND HILL LAKE HR KEYSTONE HEIGH STDRET SMITH LK NR KEYSTONE HGTS FLA STDRET 10B CYPRESS PDND NM DF JETPDRT N STORET 10B LATERN LAKE AT NAPLES FLA STORET LK TRAFF S BOAT RAMP STORET ALLIGATOR LAKE AT LAKE CITY FLA STDRET WATERTOWN LAKE AT WATERTDWN FLA STORET 10B BLUE LAKE NR SW 40 ST AND 74 STDRET 10B L CAROLINE NR SW 54 ST AND 8 STORET 10B L CATALINE NR SW 54 ST AND 8 STDRET 106 LAKE IN NO MIAMI BEACH STDRET 10B HAULE LK NR SW 54 ST AND 74 STDRET GQVENOR HILL LAKE NR OLD TOWN FL
STORET ?OND, IHESDH STDRET CRESCENT L 2 E TIP BEAR ISL STDRET LAKE DISSTDN SE 8UADRAKT STDRET LAKE TALSUIN NEAR BLDXHAH FLA STORET LAKE HICFOCHEE VM RCORE HAVEN, F STOSSET DEAD LAKE NR HEUAHITCHKA FLA STORET LAKE WIMCO MOUTH STORET BEE HAVEN BAY SR 54 STOREf 01G LAKE BYSTRE NEAR BRQOKSVILLE STORET HIGHLAND LAKE NR BRDDKSVILLE, FL STDRET HORSE LAKE NR BRQOKSVILLE, FLA. STORET HUNTERS LAKE NR ARIPEKA, FLA. STDRET 01G L LINDSEY NR BRCOKSVILLE FLA STDRET NEFF LAKE NR BRODKSVILLE, FLA.
Table 2-11. (Continued)
10 4 HILLSBOROUGH
KB SftSfcSKBSBBBBBSR' KKKKKk'KKKKfc'K
� FLORIDA LAKES FROH STORET �
LAKE SOURCE DESCRIPT
SAND POINT POND STORET SAND FOINT POND NEAR BROOKSVILLE
SIMONS PRAIRIE LAKE STORET ORG SIHHQHS PRAIRIE L NR BRBDKSV
SPfiRKflAH STORET SPARKHAN LAKE NEAR SPRING LAKE..
SFSTKS STORET 01G SPRING LAKE NR BRODKSVILLE F
SfiUIRSl PRAIRIE LAK STDRET SQUIRREL PRAIRIE LAKE
liHITFELDS PRAIRIE L STDRET WHITFIELD'S PRAIRIE LAKE
ZEBRA STDRET 01G LAKE ZEBRA NEAR SPRING LAKE,
ZULU STDRET 01G LAKE ZULU NEAR LAKE LINDSEY,
AKHIE STORET LAKE ANNIE NR LAKE PLACID, FLA.
CHARLOTTE STDRET LAKE CHARLOTTE CENTER SECTION
CLAY STORET LAKE CLAY-200 YDS OFF H. END
mm STDRET LAKE DAflON-QFF 200 YDS, OF U.S.2
DINNER STORET DINNER L S SEBRING HIGHLANDS CO
FRANCIS STDRET LAKE FRANCIS NR LAKE PLACID, FLA
GLENA5A STDRET GLENADA LAKE
GRASSY STDRET 10B GRASSY LAKE NR L PLACID FLA
HUNTLEY STORET LAKE HUNTLEY 1/4 HI GUT FROH B.B
ISTOKPDGA STDRET LAKE ISTDKPDGA NR DE SOTO CITY,
JACKSON STDRET LAKE JACKSGN AT SEBRING, FLA.
JAX STDRET LK JAX CENTER HU ALC
JOSEPHINE STDRET LAKE JOSEPHINE NEAR DE SOTQ CITY
JUNE-IN-WINTER STDRET LAKE JUNE-IN-WINTER NR LAKE PLAC
LEffA STORET LAKE LETTA NR AVON PARK FLA
LITTLE LAKE JACKSON STORET LITTLE LAKE JACKSON-CENTER
LGfELA STDRET LAKE LOTELA NR AVON PARK FLA
HCCDY STDRET 10B LAKE MCCOY NR LAKE PLACID FL
PEARL STDRET 10B LAKE PEARL AT L PLACID FLA
FLACID STDRET LAKE PLACID NS LAKE PLACID, FLA.
RED BEACH STDRET 10B RED BEACH L AT DE SOTD CITY
SEBRING STORET LAKE SEBRING-CENTER-HIGHLANDS CO
SIRENA STDRET LAKE SIRENA AT LAKE PLACID, FLA.
BAY STDRET BAY LAKE NR SULPHUR SPRINGS, FLA
6U3REU. STDRET BURRELL LAKE TRIB LAKE (HWQ) NR
CALfi STDRET CALH LAKE NR ODESSA, FLA.
CAHP DOROTHY THOMAS STORET CAItP DOROTHY THOMAS LAKE
CASRDLL STORET LAKE CARROLL NR SULPHUR SPRINGS,
CHAPMAN STDRET CHAPMAN LAKE NR LUTZ, FLA.
CHARLES STORET LAKE CHARLES NR LUTZ, FLA.
CHURCH STORET CHURCH LAKE NR CITRUS PARK, FLA.
CITRUS PARK STDRET CITRUS PARK LAKE NEAR CITRUS PAR
CRENSHAW STORET LAKE CRENSHAW NR LUTZ, FLA.
CSB.1 STDRET CRUH LAKE NEAR LUTZ, FLA
CAN STORET LAKE DAN NR ODESSA, FLA.
DEES STDRET DEER LAKE NEAR LUTZ, FLA
C-EUSELL STORET LAKE DEUBELL NEAR LUTZ, FLA
DDSSCM STDRET DOSSEN LAKE NR LUTZ, FLA.
FAIRY STDRET FAIRY LAKE AT CITRUS PARK, FLA
GRADY STORET LAKE GRADY 1.5 HI. SO. OF ALAFIA
HASVEY STDRET LAKE HARVEY HR LUTZ, FLA.
HCBBS STDRET LAKE HDBBS NR LUTZ, FLA.
HORSE STQRET HORSE LAKE NR CITRUS PARK, FLA
ISLAND FORD STDRET ISLAND FORD LAKE NR ODESSA, FLA.
JACKSON STDRET 10J LAKE JACKSON NR LUTZ
SELL STDRET LAKE KELL NR LUTZ, FLA.
KEYSTONE STORET KEYSTONE LAKE NR ODESSA, FLA.
LIPSEY STDRET LAKE LIPSEY NR SULPHUR SPRINGS,
LDHG STDRET LONG LAKE NEAR HQWATHEY, FLA
MAGDALENE STDRET LAKE HAGDALENE NR LUTZ, FLA.
mxidh STDRET 10B LAKE HARION SITE 2 NEAR HAIN
HIHE PDND STDRET MINE PON!) AT CHRISTINA PARK, FLA
FIERCE STORET 10B LK PIERCE SI 2 NR WAVERLY FL
FRETTY STORET PRETTY LAKE KR CITRUS PARK, FLA.
SOUERTA STDRET LAKE ROBERTA AT TAHPA, FLA
RUBLES STDRET RUBLES LAKE AT TAHPA, FLA
ROGERS STCRET LAKE ROGERS NR CITRUS PARK,FLA.
ROSALIE STDRET 10B LAKE ROSALIE SITE 1 NEAR LAK
RGUM STDRET ROUND LAKE KR LUTZ, FLA.
SADDLEBACK STORET SADDLEBACK LAKE NR LUTZ, FLA.
STARVATION STQRET STARVATION LAKE HR LUTZ,FLA.
STEHFER STORET LAKE STEMPER NR LUTZ* FLA.
SUHSHEHE STORET LAKE SUNSHINE HEAR LUTZ, FLA
THaKOrOSASSA STORET L THDNOTOSASSA 400' FR JW SHORE
TURKEY FDRD STQRET TURKEY FORD LAKE HR LUTZ, FLA.
liHHAHED LAKE STDRET UNNAHED LAKE AT LAKE PARK NR LIJT
Table' 2-11. (Continued)
152 INDIAN RIVER
15 4 LAKE
an rKSHK kr-feHRHfe'sa'8 HKBHS r'Kr'BKrr'
h florida lakes froh stdret r an mma krhhs kkshk rhr-kkkr-rSr- m
LAKE SOURCE DESCRIPT
VALRICD STDRET VALRICD LAKE AT VALRICD, FLA
VAN DYKE STORET VAX DYKE LAKE HR LUTZ, FLA.
WHITE TROUT STORET WHITE TROUT LAKE NR SULPHUR SPRI
BLUE CYPRESS STORET BLUE CYPRESS LAKE NR. FELLSRERE,
HICCGSUKEE STORET LAKE fllCCDSUKEE NR MCCOSUKEE FL
TOWN SEND PDHO STORET TDWNSEND POND NR HAYQ FLA
ALEXArSER SPRINGS STORET ALEXANDER SPRINGS NEAR ASTOR
APSHAWA STORET LAKE APSHAWA NR HINNEOLA, FLA.
BAY STDRET 01G BAY LAKE AT BAY LAKE, FLA.
BEAUCLAIR STDRET 01E LAKE BEAUCLAIR HR ASTATULA F
BRIGHT STDRET 01E LAKE BRIGHT NR DKAHUHPKA, FL
EUGG SPRING STDRET 01E BUGG SPRING AT GKAHLUPLA FLA
CATHERINE . STORET CNTR L CATHERINE
CHERRY STORET CHERRY LAKE NEAR GRGVELAND, FLA.
CHURCH STORET CHURCH LAKE NR GROVELAND, FLA.
DEMHftl STDRET 01E LAKE DENHAH NR DKAHUHPKA, FL
DIME STORET LAKE DIME AT EUSTIS, FLA.
CORA STDRET LAKE DDRA AT HOUXT DORA, FLA.
DCSR STORET LAKE DORR NEAR ALTOGNA FLA
EHflA STORET L EHHA HIDDLE
EUSTIS STCRET LAKE EUSTIS AT EUSTIS, FLA.
FISH STORET 01E FISH LAKE HR PINE LAKES FLA
FLAT STORET 01E FLAT LAKE NR OAKLAND, FLA.
FLORENCE STQRET LAKE FLORENCE AT RONTVERDE, FLA.
GRASSY STORET 01E GRASSY LAKE NR HINNEOLA, FLA
GRIFFIN STDRET LAKE GRIFFIN AT LEESBURG, FLA.
HANCOCK STCRET 10B HANCOCK LAKE NR CLERHDNT FLA
HARRIS STORET LAKE HARRIS AT LEESBURG, FLA.
HIAWATHA STORET L HIAWATHA 150 FT OFF W SHORE
HDLLY STORET 01E HOLLY LAKE NR UHATILLA FLA
HORSESHOE STORET HORSESHOE LAKE NR TANGERINE FLA
&ATHRYN STORET 01E LAKE KATHRYN AT KATHRYN HEIG
LAOY STGRET LADY LAKE NR LADY LAKE, FLA.
LITTLE LAKE HARRIS STCRET ME LITTLE LAKE HARRIS AT HDWEY
LOUISA STDRET LAKE LOUISA NR CLERHDNT, FLA.
LUCY STDRET L LUCY HIDDLE
RASY STORET 01E LAKE HARY AT UHATILLA, FLA.
HELTON STORET 01E LAKE HELTON NR ASTATULA, FLA
HESSfihT SPRING STDRET RESSANT SPRING NR-SORRENTO, FLA.
HIHNEHAHA STDRET LAKE HINNEHAHA AT CLERHDNT, FLA.
HIKHEQLA STDRET 01E LAKE HINNEOLA NR CLERHDNT FL
KCRRIS STORET 01E LAKE NORRIS NR PAISLEY, FLA.
FINE STDRET PINE LAKE NR. CASSIA, FLA.
FITTS PDND STORET 01E PITTS PDND NR DKAHUHPKA, FLA
SCHIHHERH08N STDRET 01E LAKE SCHIHHERHORN AT ASTOR P
SELLERS STCRET L SELLERS CENTER OF EASTERN LOBE
SEtitHQLE SPRINGS STORET SEHINOLE SPRINGS NR SORRENTO, FLA.
SILVER STORET 01E SILVER LAKE NR LEESBURG, FLA
SOUTH STDRET LAKE SOUTH
SHATASA STDRET 01E LAKE SWATARA NEAR EUSTIS, FL
TROUT STORET TROUT LAKE NR CLERHDNT, FLA.
UHATILLA STORET LAKE UHATILLA AT UHATILLA, FLA.
WEST CROOKED STORET WEST CROOKED LAKE NR EUSTIS, FLA
YALE STGRET LAKE YALE AT GRAND ISLAND, FLA.
CHATEAU SUR-HER STCRET 10B LAKE AT CHATEAU SUR-HER
LEELfifB STDRET 10B LEELAND LAKE AT LEHIGH ACRES
BRADFORD STORET LK BRADFORD NR TALLAHASSEE FLA
ELLA STDRET LAKE ELLA II SOUTH SHORE
IAHDNIA STDRET LAKE IARONIA NR BRADFORDVILLE, F
JACKSON STDRET LAKE JACKSON II 100 YDS F8 SHORE
LAFAYETTE STDRET LK LAFAYETTE E SIDE SR 241
HEGGIHHISS ARH STGRET S END L N HAGGINNISS ASH
HUHSCN STCRET LK HUNSDN NR TALLAHASSEE FLA
UKKARED STDRET UNNAHED LAKE NEAR TALLAHASSEE FL
CHUNKY PDHO STORET CHUNKY POND NR BRONSON, FLA.
ROUSSEAU STDRET LAKE RDUSSEAU NEAR DUHKELLDH, FL
FRANCIS STDRET LAKE FRANCIS 11 SW
BANATEE RESERVOIR STORET WHR-1 MANATEE R RESERVOIR
WARD STDRET WARD LAKE NR BRADE.HTON, FLA.
BIS bass STORET 01E BIG BASS LAKE NR STARKEs FER
CHILES STDRET LAKE CHARLES HEAR SILVER SPRIKSS
EATGH STORET LAKE EATDN NEAR SILVER SFRIHCS.
.KERR STORET LAKE KERR NEAR EUREKA, FLA.
LITTLE LAKE WEIR STDRET LITTLE LK WEIR CENTER
Table 2-J.l. (Continued) � FLORIDA LAKES FROH STORET fi
DBS COUNTY LAKE SOURCE DESCsIPT
223 MARION ML'D STORET 01E MUD LAKE NR SALT SPRINGS FLA
224 MARION GCKLAWAHA STDRET LAKE OCKLAWAHA NEAR GRANGE SPRIN
MARION SELLERS STORET SELLERS LAKE-SOUTH END
224 MARION TDHSHflHK STORET 01E TOMAHAWK LAKE HR OCALA FLA
22? MARION STDRET UNNAMED LAKE IH RDSS PRARIE HR S
225 MARION weir STORET LAKE WEIR AT OKLAWAHA, FLA.
221 MONROE CYPRESS POND STDRET 10B CYPRESS PDND SOUTH OF JETFDR
230 MONROE GUM SLOUGH POND STDRET 10B PDND IN WESTERN PART GUM SLD
231 MONROE U MIAMI POND STORET 10B UNIVER DF MIAMI PDND AT SR 1
232 OKALOOSA KASICK STDRET KARRICK LAKE NR BLACKMAN FLA
233 OKEECHOBEE OKEECHOBEE STORET 10B LAKE OKEECHOBEE AT POINT 4 F
234 ORANGE ADAIR STORET LAKE ADAIR AT ORLANDO, FLA.
235 ORANGE APOPKA STORET LAKE APOPKA AT WINTER GARDEN, FLA
234 ORANGE BASS STDRET BASS LK NR ORLANDO FLA
237 ORANGE BAY STDRET BAY LAKE NR VINELAND, FLA.
238 ORANGE BEAUTY STDRET 10B LAKE BEAUTY AT ORLANDO FLA
231 ORANGE BIG SAND STORET 10B BIG SAND LK CENTER AT DOCTOR
240 QKAHGE BLACK STORET L BLACK SW OF WINTER GARDEN
241 ORANGE BRYAN STORET LAKE BRYAN, NR VINELAND, FLA.
242 ORANGE BUENA VISTA STDRET L BUENA VISTA CTR OF LAKE
243 ORANGE BUTLER STDRET LAKE BUTLER AT WINDERMERE, FLA.
244 ORANGE CARLTBH STDRET 01E LAKE CARLTON NR TANGERINE FL
245 ORANGE CHARITY STDRET LAKE CHARITY NR MAITLAND, FLA.
244 ORANGE CLEAR STDRET 10B CLEAR LAKE AT ORLANDO FLA
247 ORANGE CGKWAY STDRET LAKE CONWAY AT PINE CASTLE, FLA.
245 ORANGE CROOKED STORET CROOKED LK NR CLARCGNA FLA
241 ORANGE DGiiN STDRET L DOWN SW DRNG CTY GEO MID OF LK
250 ORANGE DOWNEY STDRET LK DOWNEY - HIWAY 50 i DEAN RD U
251 GRANGE EDLA STORET LK EDLA DOWNTOWN ORLANDO
252 ORANGE FAITH STDRET LAKE FAITH AT MAITLAND, FLA.
253 ORANGE FAHNY STORET 01E LAKE FANNY NR ZELLWDDD FLA
254 ORANGE FRANCIS STORET LAKE FRANCIS NR PLYMDUTH, FLA.
255 GRANGE GEORGIA STORET L GEORGIA N OF HW 50 W OF DEAN R
254 ORANGE HA3T STDRET 10B HART LAKE NR NARCDDSSEE, FLA
25? GRANGE HEffiKK STDRET 01E L HERRICK NR ORLANDO FLA
258 ORANGE HICKGRYNUT STDRET 106 HICKDRYNUT LAKE NR OAKLAND F
251 GRANGE K0?� STDRET LAKE HOPE AT MAITLAND, FLA.
240 GRANGE HGRSESHOE STORET HORSESHOE LAKE NR CLARCGNA FLA
241 ORANGE HOURGLASS STDRET 10B HOURGLASS LAKE AT ORLANDD FL
242 ORANGE INGRAM STORET 10B LAKE INGRAM NR OAKLAND FLA
243 GRANGE IRMA STDRET L IRMA CTR DF HE LOBE
244 GRANGE IVANHCE STORET LAKE IVANHDE-MIDDLE
245 ORANGE JGHIO STDRET 01E LAKE JDHID NR OCOEE FLA
244 ORANGE JDHKS STDRET JOHNS LAKE AT OAKLAND, FLA.
247 ORANGE kehoe STDRET 01E LAKE KEHQE NR UNION PARK FLA
245 ORANGE KILLASNEY STDRET 01E L KILLARNEY AT WINTER PARK F
241 GRANGE LAGQGN STDRET LAGOON AT S-405C
270 GRANGE LAWNE STDRET 01E LAWNE LAKE NR ORLANDO FLA
271 GRANGE LITTLE LAKE BRYAN STDRET LIT LK BRYAN CTR OF LAKE
272 ORANGE LITTLE SAND LAKE STDRET 10B LITTLE SAND LAKE NR VINELAND
273 ORANGE LCSG STORET L LONG W DF US 441 IN LDCHART
274 ORANGE LOVELY STDRET LK LOVELY N.W. ORLANDO
275 GRANGE LUCERNE STDRET 10B LAKE LUCERNE AT ORLANDO FLA
274 ORANGE LUCIEN STDRET LAKE LUCIEH AT MAITLAND,FLA.
277 ORANGE MABEL STORET L MABEL AT USGS GAGING STAT
275 ORANGE MAITLAND STDRET LAKE MAITLAND AT WINTER PARK FLA
271 GRANGE MANN STDRET L MANN SW ORLANDO SE LAKE
280 ORANGE MARY JANE STDRET LAKE MARY JANE NR NARCDDSSEE, FL
281 ORANGE MINNEHAHA STDRET LAKE MINNEHAHA
282 ORANGE NEEDHAM STDRET 10B LAKE NEEDHAM NR OAKLAND FLA
283 ORANGE GLA STORET 01E LAKE OLA AT TANGERINE F
284 OSAHGE CSCEOLA STORET L. OSCEOLA - WINTER FK
285 GRANGE FGCKET STDRET L POCKET SW ORHG CO GEO MID DF L
284 ORANGE FOSTER STDRET LK PORTER EAST DF CDKWAY GDS RD
28? ORANGE SHADOW STDRET LAKE SHADOW, DRNG CULVERT INTO L
288 ORANGE SHEEN STDRET L SHEEN sw ORHG CO ��G mid OF LK
231 ORANGE SHERliiDD STORET 01E L SHERWOOD HR ORLANDO FLA
210 OSAHSE SILVER STORET LK SILVER AT ORLANDO FLA
211 OSAHSE SFSIHS STORET SPRING LK AT ORLANDO FLA
212 &Mh� sue STDRET LK sue N.E. ORLANDO
213 GRANGE SYLVnN STORET LAKE SYLVAN CENTER
214 QttKGt TI8ET BUTLER STORET 10B LAKE TIBET HR WINDERMERE FLA
215 ORANGE TURKEY STDRET TURKEY LK SW ORLANDO VIC GEO-MID
214 OSAHGE UNDEFHILL STORET 10B LAKE UNDERHILL AT ORLANDO FL
Table- 2-11. (Continued) � FLORIDA LAKES FROH STORET �
HS SHH KttKlt K KSKHSt HSRHH KHSSH HH
QBS COUNTY LAKE SOURCE DESCRIPT
217 ORANGE L^rHEO-WINDERflERE STORET 10B UNNARED L NR WIHDERRERE FLA
218 ORANGE lE^US STDRET 10B LAKE VENUS NEAR ORLANDO FLA
211 OSAHGE VIRGINIA STDRET 01e LAKE VIRGINIA AT WINTER PARK
300 GRANGE tEKIVft STORET L WEKIVA N DF AH 50 HH ORLANDO
301 GRANGE l-ESTGN STDRET L WESTON NW ORLANDO VICINITY
302 DSCEGLA *JAY STORET 10B AJAY LAKE NR NARCDDSSEE, FLA
303 DSCEGLA fLLIGATOR STDRET ALLIGATOR LAKE NR ASHTON, FLA.
304 OSCEOLA WICK STORET 10B BRICK LAKE NR ASHTON, FLA.
305 DSCEGLA CEHIIR STORET 10B LAKE CENTER NR NARCDOSEE FLA
304 OSCEOLA CilriilN STORET 10B LAKE CONLIN NEAR ASHTDN FLA
307 DSCEGLA CGG* STDRET 10B COON LAKE NR ASHTDN FLA
308 DSCEGLA CYPRESS STORET CYPRESS LAKE NR ST. CLOUD, FLA.
301 OSCEOLA EAST TDHOPEKALIGA STORET EAST LAKE TDHOPEKALIGA AT ST. CLOUD,
310 OSCEOLA FKH STDRET FISH LAKE, NW LOBE
311 OSCEOLA FISH J COLLEEN STDRET LAKE COLLEEN/FISH LAKE
312 DSCEGLA FISH i HARK STORET LAKE RARK/FISH LAKE
313 OSCEOLA GLAIRY STORET 10B LAKE GENTRY NR ST CLOUD FLA
314 OSCEOLA f ATCHKEKA STDRET LAKE HATCHINEHA NR LAKE WALES, FLA.
315 OSCEOLA JV.fcSCtf STDRET 10B LAKE JACKSON CENTER NR KENAN
314 DSCEGLA j:5EL STORET 10B LAKE JDEL NR NARCDOSEE FLA
317 OSCEOLA SKSIHHEE STORET LAKE KISSIRREE NR LAKE WALES, FL
318 CiCEOLA LICE DAK STORET 10B LIVE OAK LAKE AT ASHTDN, FLA
311 OSCEOLA lizzie STORET 10B LAKE LIZZIE NR ASHTDN FLA
320 OSCEOLA fcKTAH STORET LAKE RARIAN NR KENANSVILLE, FLA.
321 DSCEGLA fcYRTLE STORET 10B LAKE MYRTLE CENTER NEAR NARC
322 DSCEGLA FfESlGN STORET 10B LAKE PRESTON NEAR NARCDDSSEE
323 OSCEOLA FG.'filE STORET 10B LAKE ROSALIE SITE 2 NR LK WA
324 DSCEGLA EisSSLL STORET 10B LK RUSSELL NR CARPBELL FLA
325 OSCEOLA TIGER STDRET 10B TIGER LAKE NR LK WALES FLA
324 OSCEOLA TSt'UFEKALIGA STORET LAKE TDHOPEKALIGA AT KISSIRREE,
327 GSCEDLA m-u STORET 10B TROUT LAKE CENTER NR ASHTON
328 PALR BEACH CLAW STORET LAKE CLARKE AT PINE TREE LANE NR
321 FALfl BEACH CLEr.R STDRET 10B CLEAR LAKE AT WEST PALfl BEAC
330 PALf! BEACH GSsSRKE STDRET LAKE OSBDRNE AT LAKE WORTH, FLA
331 PALf) BEACH W5TH STDRET 10B LAKE WORTH NR BDYTON BEACH F
332 FASCD EELL STDRET BELL LAKE NEAR DREXEL, FLA
333 PASCO STORET BIRD LAKE AT LAND 0"LAKES, FLA
334 PASCD EL^TGK STORET 01g LAKE BLANTON AT BLANTDN, FLA
335 PASCO CASF STDRET CARP LAKE NR DENHAH,, FLA.
334 PASCO �Lt� STORET CLEAR LAKE AT SAN ANTONIO, FLA.
337 PA SCC CREW STORET CREWS LAKE (NORTH) NR LDYCE,FLA.
338 FASCD E&LIHC STDRET 01g LAKE DOWLING NEAR BLANTDN, F
331 PASCO FEkGUSGH STORET 01g FERGUSON LAKE NEAR DADE CITY
340 FASCD STDRET GOOSE LAKE NEAR LDYCE, FLA
341 PASCO r#:CGCK STGRET HANCOCK LAKE NEAR DIXIE, FLA
342 FASCD ICIA STDRET LAKE I OLA NR SAN ANTONIO, FLA.
343 PASCO *IKS STDRET KING LAKE NR SAN ANTONID, FLA
344 FASCD LAKE Y STORET LAKE Y NR EHREN, FLA
345 PASCO �r-oy/r STDRET RDDDY LAKE NEAR SAN AHTGNID, FLA
344 PASCD KM STORET RDON LAKE NR NEW PORT RICHEY, FL
347 PASCO DIKES STDRET DAKES POND
348 PASCO FAOi7F.Tr STORET LAKE PADGETT NEAR LUTZ, FLA.
341 PASCO FASTER STORET PARKER LAKE NR ODESSA, FLA.
350 PASCD PASADENA STDRET LAKE PASADENA NEAR dade CITY, FL
351 PASCO FC�ifi:E STGRET LAKE PIERCE AT FIVAY JUNCTION, F
352 PASCG FCS-j - BIG FISH STDRET POND NEAR BIG FISH LAKE
353 FASCD FAY FOND STDRET RAY POND NEAR SAN ANTONIO, FLA
354 PASCD iAyi-N STDRET 10H SAXON LAKE NR DREXEL, FLA.
355 FASCD THLVAS STDRET LAKE TBORAS AT DREXEL, FLA.
354 PASCO THIN STDRET TWIN LAKES NR LAND 0'LAKES, FLA
357 PASCG W[r� TUS
351 Plh'ELLAS FASGlDRE STDRET LAKE HAGGIORE AT ST PETERSBURG,
340 PIKELLAS SAKKASS STORET SAWGRASS LAKE SITE t 2
341 FIKELLAS 5E1TKDLE STORET SERINDLE LAKE NR LARGO, FLA
342 FIFELLAS TPkFDN STORET LAKE TARPON NR TARPON SPRIKGS, F
343 FOLK H.FFED STORET LAKE ALFRED AT LAKE ALFRED, FLA.
344 FOLK mt� STORET LAKE ANNIE AT WAVERLY, FLA.
345 FOLK rFBirlklE STGRET LAKE ARBUCKLE hr AVON PARK, FLA.
344 FOLK fFETTA STDRET LAKE ARIETTA NR AUBURNDAIE, FLA.
347 FOLK ?-ri�iHA STORET ASIANNA LAKE POLK CD
343 FOLK ifKr'HA STDRET BANAXNA LAKE NS HIGHLAND CITY, F
341 FOLK ELLE JORDAN SHARP STORET 10B BLUE JORDAN SHARP NR FROSTPR
370 FOLK tCk^Y STDRET LAKE BONNY POLK COUNTY
m an ma umaa ss��� khsbk ��
( fonti nu e>A "i h FLORIDA LAKES FROM STORET a
OBS COUNTY LAKE SOURCE DESCRIPT
371 POLK BL'FFUH STORET LAKE BUFFUM SITE 3
372 POLK CANNON STDRET LAKE CANNON PGLK COUNTY
373 PGLK CLINCH STORET LAKE CLINCH AT FROSTPROOF, FLA.
374 FOLK CONNIE STORET LAKE CONINE PGLK COUNTY
375 POLK CROOKED STDRET CROOKED LAKE NR BABSON PARK, FLA
374 POLK DARSEY STORET LAKE DAISEY POLK CO
37? POLK DEES STGRET DEER LAKE NR WINTER HAVEN, FLA
378 POLK DEESON STGRET LAKE DEESDN NR LAKELAND, FLA.
3?i POLK DEXTER STORET LAKE DEXTER POLK CD
330 PDLK EAGLE STDRET EAGLE LAKE AT EAGLE LAKE, FLA.
331 POLK EFFIE STDRET LAKE EFFIE AT LAKE WALES, FLA.
332 POLK ELBERT STDRET FOLK COUNTY LAKE ELBERT
333 POLK ELDISE STORET LAKE ELDISE NR ELDISE, FLA
334 POLK FAKNIE STORET LAKE FANNIE NR FLORENCE VILLA, F
335 POLK GARFIELD STORET LK GARFIELD NR ALTURAS, FLA.
334 POLK GIBSON STDRET LAKE GIBSON NR LAKELAND, FLA.
33? POLK HAINES STORET LAKE HAINES AT LAKE ALFRED, FLA
338 POLK HAMILTON STQRET LAKE HAMILTON POLK CD
331 POLK HANCOCK STORET LAKE HANCOCK NR HIGHLAND CITY, F
310 POLK HARTRIDGE STORET LAKE HARTRIDGE AT WINTER HAVEN,
311 POLK KELENE STDRET LAKE HELENE NR POLK CITY, FLA.
312 POLK K3LUNGSWDRTH STDRET LAKE HDLLINGSWDRTH AT LAKELAND,
313 POLK KGWARD STORET LAKE HOWARD AT WINTER HAVEN, FLA
314 POLK HUNTER STQRET LAKE HUNTER AT LAKELAND, FLA
315 POLK IDYLWILD STORET IDYLWILD LAKE POLK CD
314 POLK JESSIE STDRET LAKE JESSIE NR AUBURNDALE, FLA
317 POLK JULIANA STORET LAKE JULIANA NR POLK CITY, FLA.
318 POLK LEE STDRET LAKE LEE AT WAVERLY, FLA
311 POLK LENA STDRET LAKE LENA AT AUBURNDALE, FLA.
400 POLK LINK STDRET LAKE MARIAM POLK CO
401 POLK LOWERY STGRET LAKE LOWERY HR HAINES CITY, FLA,
402 POLK LULU STDRET LAKE LULU NR ELDISE, FLA
403 POLK MARIANA STDRET LfiKE MARIANA NR AUBURNDALE, FLA.
404 POLK MARION STDRET LAKE MARION, NR HAINES CITY, FLA
405 POLK MATTIE STORET 01G LAKE MATTIE NR POLK CITY FLA
404 POLK MAY STDRET LAKE MAY MIDLAKE AT WINTER HAVEN
40? POLK MAYO STORET LfiKE MAYD PGLK COUNTY
408 POLK HCLEDD STORET LAKE MCLEOD POLK CO
401 POLK MIRROR STORET LAKE MIRROR POLK CD
410 POLK MORTON STDRET 25.2DA LAKE MDRTDN, POLK COUNTY
411 POLK MOUNTAIN STDRET MOUNTAIN LAKE NR LAKE WALES, FLA
412 POLK MYRTLE STORET LAKE MYRTLE NR LAKE WALES, FLA
413 POLK OTIS STDRET LAKE OTIS AT WINTER HAVEN, FLA
414 POLK PARKER STDRET LAKE PARKER AT LAKELAND, FLA.
415 POLK PIERCE STDRET LAKE PIERCE NR WAVERLY, FLA.
414 POLK REEDY STDRET REEDY LAKE NR FROSTPROOF, FLA.
41? POLK ROCKELLE STDRET LAKE ROCKELLE NR LAKE ALFRED, FL
418 POLK ROSALIE STDRET LfiKE ROSALIE NR LAKE WALES, FLA.
411 POLK RDY STORET LAKE ROY PDLK CO
420 POLK SARDEN STDRET SARDEN LAKE PDLK CD
421 POLK SCOTT STORET SCOTT LAKE NR LAKELAND, FLA
422 POLK SEA3S STORET SEARS LAKE POLK CO
423 POLK SHIFP STDRET LAKE SHIPP AT ELDISE FLA MID-LAK
424 PQLK SILVER STORET LAKE SILVER PDLK CD
425 POLK SMART STORET LAKE SMART NR FLORENCE VILLA, FL
424 POLK SPIRIT STDRET SPIRIT LAKE PQLK CO
42? POLK SPRING STORET SPRING LAKE POLK CD
428 POLK STAN STORET LAKE STARR AT WAVERLY, FLA
421 POLK SUMMIT STQRET LAKE SUMMIT PDLK CD
430 POLK SHODPE STORET LAKE SWDOPE E OF IRRIG CANAL
431 POLK THOMAS STORET LAKE THOMAS PDLK CD
432 POLK TRACY STORET LAKE TRACY PDLK CD
433 POLK KALES STORET LAKE WALES AT LAKE WALES, FLA.
434 POLK WEGHYAKAPKA STORE T LAKE WEDHYAKAPKA AT INDIAN LAKE
433 POLK WHISTLER STGRET LAKE WHISTLER NR AUBURNDALE, FLA
434 FOLK HINTERSET STORET LAKE WINTERSET
43? PUTNAH CRESCENT STORET CRESCENT LK BY MARKER tQ.2
41S PUTNAM GEORGE STGRET LAKE GEORGE NEAR SALT SPRINGS, F
431 PUTNAM CEGRGES STDRET GEORGES LAKE 200 YDS FROM H BANK
440 PUTNAM GRAHHK STORET LfiKE GRANDIN NR INTERLACHFN, FLA
441 PUTNAM LITTLE GEORGE STDRET LITTLE L GEORGE CHAN MARK 53A
442 SANTA 80S* STORET BEAR LK NR BAKER FLA
443 SARASOTA LOWER MYAKKA STORET LOWER MYAKKA LAKE HR SARASOTA, F
444 SARASOTA UPPER MYAKKA STORET UPPER MYAKKA LAKE-.? MILES KE Of
Table '2-11. (Continued) � FLORIDA LAKES FROH STDRET k
DBS COL'KTY LAKE SOURCE DESCRIPT
445 SE WHOLE ADA STDRET L ADA S END 50 YDS OFFSHORE
444 SE WHOLE BEAR STDRET BEAR LAKE CENTER OF NE END
447 SEMINOLE BRANTLEY STDRET L BRANTLEY NW DFFSHR HORSESHOE C
445 SEHINOLE CATHERINE STDRET L CATHERINE AT CHULUDTA CENTER
441 SEMINOLE CRYSTAL STQRET CRYSTAL L E END 200YD W OF PUB B
450 SEMINOLE ELEVENTH HOLE STDRET ELEVENTH HOLE POND AT ALTAHONTE
451 SEMINOLE FAIRY STORET FAIRY L SOFT OFFSHORE ARNOLD LDR
452 SEHINOLE FLORIDA STORET L FLORIDA AT 1000 FLA BLVD
453 SEHINOLE FRANCIS STORET L FRANCIS CENTER
454' SEHINOLE GOLDEN STDRET L GOLDEN CENTER
455 SEMINOLE HORSESHOE STDRET LAKE HORSESHOE
454 SEHINOLE HOWELL STDRET L HOWELL OFFSHORE JANES PROPERTY
457 SEHINOLE JEN HE STDRET L JENNIE S END APPROX 50YDS OFFS
453 SEHINOLE JESSUP STDRET LAKE JESSUP NEAR SANFORD FLA
451 SEHINOLE KATHRYN STORET L KATHRYN CENTER
440 SEHINOLE HARKHAH STDRET L HARKHAR CTR DF S LOBE S DF SR4
441 SEMINOLE MARY STDRET S LAKE HARY CENTER
442 SEMINOLE HILLS STORET HILLS L CTR DF E END 300Y0S DFFS
443 SEHINOLE HINHIE STDRET L HINNIE CENTER
444 SEHINOLE HIRRDR STORET HIRRDR L AT SR 434 20YDS DFFSHDH
445 SEHINOLE PEARL STDRET PEARL LAKE CENTER DF NW CDVE
444 SEHINOLE PSAIRIE STDRET PRAIRIE L SOFT DFFSHR DNG DITCH
447 SEHINOLE SILVER STDRET SILVER LAKE CENTER
448 SEHINOLE SPRING STORET SPRING LAKE C OF LAKE
441 SEMINOLE SYLVAN STORET SYLVAN L CTR OF SOUTH END DF LAK
470 SEHINDLE TRIPLET STORET L TRIPLET CENTER
471 SORTER DEATGN STDRET LAKE DEATDH NEAR HILBWOGD, FLA.
472 SUHTER DKAH'JHPKA STDRET LAKE DKAHUHPKA NR WILDWOOD, FLA.
473 SUMTER PAKASOFFKEE STDRET LAKE PANASOFFKEE NR LAKE PAHASDF
474 UNION BUfLER STDRET 01J LAKE BUTLER AT LAKE BUTLER F
475 UNION PALESTINE STORET PALESTINE LAKE NR GLUSTEE,FL
474 UNION SWIFT CREEK POND STDRET SHIFT CR POND NR RAIFGRD FLA
477 VOLUSIA ANGELA STORET LAKE ANGELA CENTER DF LAKE
473 VOLUSIA ASHBY STDRET LAKE ASHBY CENTER - VOLUSIA CO.
471 VOLUSIA BATCH STDRET L BATON CTR N LOBE NR DELTOHA
480 VOLUSIA BERESFDRD STDRET L BERESFDRD CENTER OFF W SHR RAR
481 VOLUSIA BUTLER STORET LAKE BUTLER CENTER OF N W SECTOR
482 VOLUSIA DEXTER STDRET LAKE DEXTER, CENTER DF LAKE
483 VOLUSIA DL'rONT STORET LAKE DUPDNT NR LAKE HELEN FLA
4S4 VOLUSIA HASKEY STORET LAKE HARNEY, CENTER OF LAKE
455 VOLUSIA HIRES STORET LAKE HIRES NEAR DE LAND FLA
484 VOLUSIA HUTCHINSON STQRET LAKE HUTCHINSON CENTER OF LAKE
457 VOLUSIA LINDLEY STORET 01E LINDSEY L NR DELAND FLA
488 VOLUSIA LOUISE STORET 01E LAKE LGUISE NR DELAND FLA
481 VOLUSIA HOLLY STDRET LAKE HOLLY CENTER OF LAKE
410 VDLUSIA MONROE STDRET L RONRQE NR SANFORD STP EFF
411 VOLUSIA PUZZLE STDRET L PUZZLE, ST JOHNS R INF TO
412 VDLUSIA TATUH STDRET 01E TATUM L NR DEL AND FLA
413 VOLUSIA THERESA STORET LAKE THERESA CENTER DF LAKE
414 VDLUSIA THREE ISLAND STDRET THREE ISLAND LAKE CENTER OF HORT
415 VOLUSIA H.INNEHISETT STDRET LAKE WINNEMISSETT NEAR DELAND, F
414 VOLUSIA WINOHA STDRET LAKE WINONA NR DE LAND, FLA.
41? UALTON DEFUNEAK STDRET DEFUNIAK LAKE AT DEFUNIAK SPRING
413 UALTON JACKSON STORET LAKE JACKSDN NR PAXTGN FLA
411 WASHINGTDK CLARKS STDRET CLARKS HOLE NR GREEHBEAD FLA
SCO HASHINSTDK GAP POND STORET GAP POND NR GRENHEAD FLA
50.1 HASHINSTDK GULLY STDRET GULLY LAKE NR GREENHEAD FLA
502 HA SHINS TDK HAMMOCK STDRET HAHHOCK LAKE NR GREENHEAD FLA
503 HASHINGTDK POSTER STORET PCRTER LK NR GREENHEAD FLA
5C4 WASHINGTON STILL PDND STDRET STILL PDND NR GREENHEAD FLA
505 WASHINGTON WAGES POND STORET WAGES POND NR GREENHEAD FLA
These data were gathered by the USGS and by the DER and its predecessor agencies and cover the period 1950-1980. The 505 lakes included in the STORET data are listed in Table 2-11.
Lake Tohopekaliga Drawdown Data
An extreme drawdown of Lake Tohopekaliga in Osceola County was undertaken in 1969 as an experimental management effort to reduce nutrient contribution from organic sediment. The results were presented by Wegener and Williams (1974), and their post-drawdown data from January 1972 to April 1974 are included in the data base.
South Lake 314 Study
As part of a grant from the EPA Clean Lakes Program (Section 314), Brevard County monitored South Lake west of Titusville. Data from June to December 1981 were available for inclusion in the data base.
Effects of Eutrophication on Fish Communities in Florida Lakes
Correlations between trophic state and fish abundance for 20 Florida lakes (Table 2-12) were made by Kautz (1981). Three parameters (chlorophyll a., particulate organic nitrogen, and the difference between filtered and unfiltered turbidity) were used to develop a trophic state index. Data on fish populations were obtained through a block net and rotenone-poisoning program, and fish were grouped into sport, commercial, rough, and forage categories.
Based on the above data base, Kautz concluded that commercial and rough\
fish displace sport and forage fishes with increasing eutrophication. The / displacement appears to be fairly rapid at a point in the trophic range just past maximum sport fish biomass, indicating a fine line between management of fisheries resources and nutrient and algae excess. Fish diversity also reaches a maximum in the middle trophic range. Kautz claimed that much
Table 2-12. Lakes Studied by Kautz (1981).
Lochloosa Newnans Orange Santa Fe Ocean Pond South
past the "optimal" concentration of 1.2 mg/L total N and a chlorophyll a of
greater than 10 mg/m , adverse effects due to enrichment may occur.
Some smoothing was done on the fish population data, so that inferences made on the trends must take this into account. Only nitrogen data were used in the trophic index used by Kautz. Although the majority of the lakes were thought to be nitrogen-limited (based on N:P ratios less than 10:1) a more thorough analysis should take into account the possibility of phosphorus limitation as part of the trophic index.
Florida Aquatic Flora Survey � Macrophyte Data
A 1979 study by the Florida Department of Natural Resources (Tarver et al., 1979) presents data on macrophytes in rivers, canals, and public lakes of over 100 acres in the State of Florida. A total of 1.16 million surface acres were surveyed, including 371 lakes and 60 rivers. This represented 41.4 percent of the total water acreage (2.8 million) in the state. The primary purpose of the aquatic vegetation report was to describe the distribution and abundance of aquatic plant species in Florida's public waters. A total of 70 genera (in 29 families) of aquatic plants were found in the rivers, lakes and canals included in the survey. The 70 genera include over 40 exotic plants that have been introduced to Florida; many of these plants are noxious weeds, but others are highly desirable components of the aquatic environment.
Tarver et al. (1979) did not list the specific water bodies surveyed, nor the extent and diversity of aquatic flora for site-specific lakes. Instead, the report is a summary of the actual survey, designed to present the results in relation to the state as a whole, not to individual rivers, canals, and lakes. Through the survey, it was concluded that the greatest aquatic problems lie with the three exotic aquatic plants hydrilla (Hydrilla verticillata royle),
waterhyacinth (Eichnornia crassipes (Mart.) solms.), and Eurasian watermilfoil (Myriophyllum spicatum L.).
A copy of the DNR comprehensive macrophyte data was obtained through the aid of DER personnel. These data included name and type of water body, surface area, county, problem aquatic plants, and acreage of each plant. From these, all lakes with aquatic flora were reviewed and keypunched with respect to the extent of coverage of major problem plants. A listing of these 299 lakes is given in Table 2-13.
The data used in this study are the coverage of twelve common plants, in acres for each lake. These twelve were chosen because of indications by the DER that they were primarily responsible for macrophyte problems in Florida lakes. Overlapping coverage was not distinguished by the observers, hence, the "total" area covered by the twelve plant types (TOTWDS in Table 2-13) can be greater than the total lake area, and the fraction covered ("COVER" in Table 2-13) can be greater then 1.0. Hence, the reader should not be misled by macrophyte coverages of greater than 100 percent for a few lakes.
THE FLORIDA LAKE DATA BASE
From all the previously described sources, the Florida Lakes Data Base (FLADAB) was constructed, with chemical data for 573 lakes. As shown in Table 2-14, 435 lakes are represented with more than one sample, and 138 lakes have more than 10 samples. Table 2-15 lists the 65 Florida lakes for which the largest number of water quality samples have been gathered. As expected, Lake ' Iteechobee heads the list with 621 samples. Macrophyte data are additionally available for 299 lakes. To reiterate, the sources are listed as follows:
Table 2-13. Lakes With Macrophyte Data.
DBS LAKE COUNTY
3 BIVEKS m ALACHUA
4 HflLFEM ALACHUA
5 LITTLE LOCHLDOSA ALACHUA
LITTLE GRANGE ALACHUA
7 LITTLE SANTA FE ALACHUA
8 LDCUGGSA ALACHUA
1 fiOSS LEE ALACHUA
10 NEW-fiNS ALACHUA
11 DRAKE ALACHUA
12 SANTA FE ALACHUA
13 TUSC*�ILLA ALACHUA
14 WATEFfELCN PDND ALACHUA
15 OCEAN FOND BAKER
14 BRIT BAY
17 DEER POINT BAY
18 RIVES FCND BAY
11 WHITE WESTERN BAY
20 BEDFORD BRADFORD
21 CRDSUy BRADFORD
22 HAHFTSN BRADFORD
23 RDHELL BRADFORD
24 SAHFSJN BRADFORD
25 CLAFK BREVARD
26 HELEH BLAZES BREVARD
27 LDUGHMAN BREVARD
28 PDXKETT BREVARD
21 RUTC BREVARD
30 SALT BREVARD
31 SAHGRASS BREVARD
32 SOUTH BREVARD
33 WASHINGTON BREVARD
34 UIKCER BREVARD
35 FORT CGOFER CITRUS
36 TSALA FPOPKA CITRUS
37 BLUE FEND CLAY
38 BRDCKLYN CLAY
31 CRYSTAL CLAY
40 SATO? BONE CLAY
41 GENEVA CLAY
42 HALL CLAY
43 jwmw CLAY
44 LDWERY CLAY
45 HAGKGLIA CLAY
44 OLDFIELD POND CLAY
47 SMITH CLAY
48 SPRING CLAY
41 STEIENS CLAY
50 WHITE SAND CLAY
51 ALLIGATOR COLUMBIA
52 JEFFERY C0LUI1BIA
53 CRESCENT FLAGLER
54 DEAD FLAGLER
55 DISSTSN FLAGLER
54 60RE FLAGLER
5? TAL9UIN GADSDEN
58 DEAD GULF
51 UIHIC3 GULF
40 QCTMATCHEE HAMILTON
41 LINE LEY HERNANDO
42 APTHGRFE HIGHLANDS
43 BOHJEfr HIGHLANDS
44 CLAY HIGHLANDS
45 DIHrES HIGHLANDS
44 FRAKCIS HIGHLANDS
47 GLEhADA HIGHLANDS
48 GRASSY HIGHLANDS
41 ISTCKFGGA HIGHLANDS
70 JAtttfiN HIGHLANDS
71 JOSEPHINE HIGHLANDS
72 JUNE-IK-WINTER HIGHLANDS
73 LELIA HIGHLANDS
74 LETTA HIGHLANDS
LAKEAREA TflTWDS COVER
73 1.0 0.013411
540 50.0 0.012513
181 1.0 0.005271
80 2.0 0.025000
2442 1112.0 0.420813
818 8.0 0.001780
1135 24.0 0.022707
5705 2801.0 0.410173
45 7.0 0.107412
7427 35.0 0.004713
12704 2487.0 0.211475
4721 51.0 0.010803
480 544.0 0.800000
531 158.0 0.217552
1774 25.0 0.014012
18 1.0 0.055554
5000 1475.0 0.335000
175 1.0 0.005714
177? 3.0 0.001488
114 2.0 0.010204
534 131.0 0.251328
823 31.0 0.037447
344 7.0 0.011231
2042 14.0 0.047013
182 10.0 0.414505
381 37.0 0.017113
557 35.0 0.042837
4334 210.0 0.044113
210 105.0 0.500000
344 40.0 0.101210
40? 41.0 0.100737
1101 221.0 0.200727
4342 47.0 0.010775
1414 287.0 0.111845
150 10.5 0.070000
14000 11055.0 0.410137
202 3.0 0.011*851
445 8.0 0.012403
408 4.0 0.014704
280 4.0 0.021421
1430 425.0 0.240734
430 3.0 0.004177
480 4.0 0.008333
1243 43.0 0.034044
205 3.0 0.014434
244 22.0 0.08270?
815 7.0 0.007821
144 1.0 0.W4841
230 3.0 0.013043
320 4.0 0.018750
338 50.0 0.147721
114 24.0 0.210524
15140 70.0 0.004384
500 21.0 0.058000
1844 144.0 0.078071
85 3.0 0.0352*
8850 115.0 0.0127*
4055 ..0 0.010111
115 20.0 0.102544
137 1.5 0.010141
211 32.0 0.144111
240 17.5 0.047308
347 154.0 0.425048
371 30.0 0.071154
531 353.0 0.454117
17? 3.0 0.014141
51? 243.5 0.501471
22000 2355.0 0.107045
3412 30.5 0.008131
1234 575.0 0.445210
3504 2715.0 0.774827
145 3.0 0.018182
478 8.0 0.014734
Table 2-13. (Continued) � FLORIDA HACROPHYTE DATA �
DBS LAKE COUNTY LAKEAREA TDTUDS COVER
75 LITTLE RED WATER HIGHLANDS 321 10.0 0.03040
74 LDTELA HIGHLANDS 802 15.0 0.01870
77 PLACID HIGHLANDS 3320 345.0 0.10312
78 RED BEACH HIGHLANDS 335 5.5 0.01442
71 SEBRIiW HIGHLANDS 448 1.0 0.01123
80 THDNDTflSiiSSA HILLSBOROUGH 811 10.0 0.01221
81 BLUE CYPRESS INDIAN RIVER 4555 108.0 0.01448
82 BATEAT FOND JACKSON 115 120.0 1.04348
83 COU PEH FDKD JACKSOK 230 240.0 1.13043
34 DCHEESEE PDND JACKSON 2225 251.0 0.11281
85 SEfllNCLE JACKSOK 12000 174.0 0.01447
96 fllCCOSHKEE JEFFERSDK 4224 3001.0 0.48201
87 BEAUCLAIS LAKE 1111 30.4 0.02740
88 CHERRY LAKE 374 1.0 0.02273
81 COOK LAKE 20 4.0 0.20000
10 CRESCENT LAKE 74 13.0 0.17548
11 DENHAP LAKE 241 5.0 0.01851
12 DORA LAKE 4475 112.0 0.02503
73 DORR LAKE 1533 33.0 0.02153
14 ELLA LAKE 447 18.0 0.03854
15 ehha LAKE 175 28.1 0.14514
14 EUSTIS LAKE 7804 72.0 0.00122
-17 GRIFFIN LAKE 14505 40.0 0.00344
18 HARRIS LAKE 13788 145.0 0.01177
11 HIAWATHA LAKE 48 1.0 0.18750
100 HULLY LAKE 18 55.0 0.54122
101 JUNIPER SPRINGS LAKE 40 20.0 0.50000
102 LITTLE LAKE HARRIS LAKE 2731 137.0 0.05002
103 LOUISA LAKE 3434 21.0 0.00578
104 LUCY LAKE 335 40.0 0.17110
105 RINNEHtHA LAKE 2241 43.0 0.01702
104 HINNEOLA LAKE 1888 23.0 0.01218
107 PALATLAKftKA LAKE 101 4.0 0.05741
108 SILVER GLEN SPRINGS LAKE 30 14.0 0.4444?
101 SUSAN LAKE 81 8.0 0.01877
110 UHATILLA LAKE 141 15.0 0.0731?
111 WILDCAT LAKE 232 43.0 0.13534
112 WILSON- LAKE 25 14.5 0.58000
113 YALE LAKE 4042 530.0 0.13112
114 BRADFCRD LEOH 113 10.0 0.05181
115 CARR LEON 412 150.0 0.21474
114 HALL LEOH 172 42.0 0.24411
117 IAHDNIA LEON 5757 14D.0 0.28018
118 JACKSGN LEOH 4004 1310.0 0.3271?
111 HUNSDH LEDN 255 40.0 0.15484
120 LONG LEVY 254 125.0 0.41213
121 ROUSSEAU LEVY 3457 3010.0 0.82308
122 CHERRY HADISDN 477 10.0 0.02088
123 DOBSOH POHD HADISON 7 5.0 0.71421
124 ELBOU HADISDN 44 7.0 0.10138
125 GINHDL'SE PDND HADISON 3 1.0 0.33333
124 HADISON POND HADISDN 5 1.0 0.20000
127 HYSTIC HADISDN 47 1.0 0.11141
128 flAHATEE RESERVOIR HANATEE 1200 30.0 0.02500
121 BRYANT HARIDN 747 35.0 0.04543
130 DELANCY HARION 382 40.0 0.10471
131 EATOH HARIDN 307 110.0 0.35831
132 HALFHCQN HARION mo 51.0 0.15000
133 HAHHOCK FCKD HARIDN 171 30.0 0.14740
134 JUHPER HARION 305 7.0 0.02215
135 LITTLE LAKE WEIR HARION 320 87.0 0.2718?
134 HILL BAH HARIDN 210 175.0 0.83333
137 HUD HARION 470 1.5 0.02021
138 DCKLAhfcHA HARION 5280 7071.0 1.33720
131 SELLERS HARION 1050 447.0 0.43524
140 WARNER HARIDN 415 45.0 0.01353
141 WEIR HARIDN 5485 45.0 0.00712
142 DKEECH&EE OKEECHOBEE 404042 40582.0 0.01115
143 APOPKA ORANGE 30471 1200.0 0.03112
144 AVALOH ORANGE 142 12.0 0.07407
145 BALDWIN ORANGE 114 120.0 0.41224
144 BARTDH ORANGE 233 40.0 0.24414
147 BIG SfHD ORANGE 1110 5.0 0.00450
148 BLACK ORANGE 244 13.0 0.05328
Table 2-13. (Continued)
� FLORIDA HACROPHYTE DATA K
CBS LAKE COUNTY LAKEAREA TABIDS COVER
141 BUTLER ORANGE 1445 70.00 0.04204
150 CAFLTCK ORANGE 382 7.81 0.02045
151 CATHERINE ORANGE 43 30.00 0.47411
152 CLEAR ORANGE � 331 325.00 0.15870
153 CTM ORANGE 255 1.00 0.00312
154 CDMiAY ORANGE 1833 185.00 0.10013
153 CROOKED ORANGE 84 10.00 0.11428
154 D01H ORANGE 872 20.00 0.02214
157 DDI-KEY ORANGE 100 20.00 0.20000
158 FAIRVIEM ORANGE 401 200.00 0.41875
151 FREDRICA ORANGE 71 12.00 0.14101
140 GEORGIA ORANGE 82 5.00 0.04018
141 HART ORANGE 1850 45.00 0.03514
142 HAWSSA ORANGE 200 13.00 0.04500
143 HEKQSYKIJT ORANGE 550 17.00 0.03011
144 HOLDEN ORANGE 252 11.00 0.04345
145 IRfcA ORANGE 123 20.00 0.14240
144 IVfHHOE ORANGE 125 15.00 0.12000
147 JESSAMINE ORANGE 304 120.00 0.31214
148 JflfcHS ORANGE 2417 45.00 0.02481
141 LOUISE ORANGE 145 5.00 0.03448
170 LUCIEN ORANGE 57 5.00 0.08772
171 HAITLfiHD ORANGE 451 200.00 0.44344
172 HARK ORANGE 244 240.00 0.18341
173 MARTHA ORANGE 30 25.00 0.83333
174 MARY JAKE ORANGE 1158 41.00 0.03541
175 HCKY ORANGE 133 25.00 0.18717
174 fllZELL ORANGE 42 30.00 0.48387
177 OLA ORANGE 442 20.00 0.04525
178 OSCEOLA ORANGE 15? 75.00 0.47771
171 PALflEi? ORANGE 54 5.00 0.08121
180 PEtfL ORANGE 58 50.00 0.84207
181 PICKETT ORANGE 742 25.00 0.03341
182 RATTLESNAKE ORANGE 111 100.00 0.10010
183 SMDOil ORANGE 77 2.00 0.02517
184 SHEEN ORANGE 545 25.00 0.04425
185 SHERhCDD ORANGE 111 7.00 0.05882
184 STARKE ORANGE 203 20.00 0.01852
187 SUE ORANGE 140 50.00 0.35714
188 SUSANiVAH ORANGE 74 10.00 0.13158
181 SYEELIA ORANGE 84 80.00 0.15238
110 TIEET ORANGE 1118 40.00 0.05008
111 TUSKEY ORANGE 323 15.00 0.04444
112 MIFGINIA ORANGE 223 100.00 0.44843
113 HAF.BEH ORANGE 121 30.00 0.23254
114 UALNATTA ORANGE 48 40.00 0.88235
115 ALLKATDR OSCEOLA 3404 714.50 0.21034
114 CEHTER OSCEOLA 410 10.00 0.02431
117 COCN OSCEOLA 1448 7.00 0.00483
118 CYFRESS OSCEOLA 4017 100.00 0.02441
111 EAST TOHOPEKALIGA OSCEOLA 11148 252.00 0.02104
200 GEHTRY OSCEOLA 1711 38.50 0.02150
201 HATCHINEHA OSCEOLA 4445 135.00 0.02024
202 JOEL OSCEOLA 217 133.00 0.41210
203 KISSIMMEE OSCEOLA 34148 1485.00 0.04821
204 LIZZIE OSCEOLA 712 428.00 0.54040
205 MARIAN OSCEOLA 5731 151.00 0.02771
204 MYRTLE OSCEOLA 543 347.00 0.47587
20? PRESTCH OSCEOLA 410 470.00 0.48114
208 NMPEKALIGA OSCEOLA 18310 2700.00 0.14354
201 TROUT OSCEOLA 273 183.00 0.47033
210 BELL PASCO 80 1.00 0.01250
211 BUEDY PASCO 10 5.00 0.05554
212 CLEAR PASCO 158 4.00 0.02532
213 IOLA PASCD 107 42.00 0.31252
214 PAtGETT PASCD 200 370.00 1.85000
215 PASADENA PASCD 373 45.00 0.12044
214 MASSKRE PINELLAS 380 13.00 0.03421
217 SALT PINELLAS 113 175.00 0.10474
218 SEWFGLE PINELLAS 714 58.00 0.08101
211 TAFPON PINELLAS 2534 755.00 0.21715
220 AGfES PDLK 384 11.00 0.02850
221 ALFRED POLK 734 8.00 0.01087
222 AREUCKLE PDLK 3828 117.00 0.03054
hS� k�tttt XXXHX HXXKK KBKH� H�HHtt KKKKB KBittiKgKgii Table* 2-13. (Continued) x FLORIDA HACRDPHYTE DATA �
DBS LAKE COUNTY LAKEAREA tothds COVER
223 ARETTA POLK 758 11.0 0.014512
224 ARIfKA PDLK 1024 8.0 0.00771?
225 BfiKfXA POLK 342 10.5 0.030702
224 BUFFliS POLK 1543 70.0 0.045344
227 CAHHQH POLK 334 15.0 0.044443
228 cl3kk POLK 120? 44.0 0.034454
221 CRDCKE5 POLK 5538 220.0 0.031724
230 EASY POLK 411 27.0 0.044431
231 ELDISE PDLK 1140 5.5 0.004741
232 FANNIE POLK 821 37.0 0.044432
233 GARFIELD POLK 455 287.0 0.438148
234 GIBSON POLK 474 11.0 0.023207
235 MOTES POLK 714 1.0 0.012570
234 HAfllLTCN POLK 2142 50.0 0.023127
237 HANCilOK POLK 4511 35.0 0.007745
238 HENRY POLK 857 25.0 0.021172
231 HOLLIHGSWDRTH POLK 354 13.0 0.034517
240 HUNTER PDLK 100 1.5 0.015000
241 JULIANA PDLK 124 11.0 0.011871
242 LIVINGSTON PDLK 1203 12.0 0.074475
243 LOHEFY POLK 720 4.5 0.004250
244 LULL1 POLK 301 20.0 0.044445
245 flARIOH PDLK 2110 148.0 0.041418
244 HATTIE POLK 1078 11.0 0.010204
247 hirs3r PDLK 123 10.0 0.081301
248 HOOC'7 PDLK 311 22.0 0.054244
241 nuD PDLK 140 50.0 0.312500
250 ons POLK 143 44.0 0.321478
251 PARKER POLK 2272 37.0 0.014285
252 PIEFCE POLK 3721 3245.0 0.875570
253 REEDY POLK 3484 250.0 0.071715
254 ROSfLIE POLK 4517 220.0 0.047857
255 SANITARY POLK 503 110.0 0.218488
254 SHIFP PDLK 283 5.0 0.017448
257 SURVEYORS PDLK 273 4.0 0.020478
258 TIGER POLK 2200 50.0 0.022727
251 HALES POLK 324 220.0 0.474847
240 HEDHYAKfiPKA POLK 7532 255.0 0.033854
241 HINTERSET PDLK 548 8.5 ' 0.015511
242 HIRE POLK 25 11.0 0.440000
243 brow) PUTNAH 480 12.0 0.025000
244 CDLuFEH PUTNAH 584 5.0 0.008542
245 GEDFGE PUTNAH 44000 550.0 0.011157
244 GEORGES PUTNAH 814 15.0 0.018382
247 LITTLE GEORGE PUTNAH 1414 22.0 0.015537
248 HARG^RET PUTNAH 380 15.0 0.031474
241 HCCARTHY PUTNAH 110 2.0 0.018182
270 STELLA PUTNAH 308 302.0 0.180511
271 JESiUP SEHINOLE 10011 320.0 0.031145
272 HILLS SEHINOLE 232 35.0 0.150842
273 HULLET SEHINOLE 431 72.0 0.114105
274 ORIEHTA SEHINOLE 121 70.0 0.542434
275 DEATON SUHTER 778 45.0 0.057841
274 hioka SUHTER 418 5.5 0.013158
277 DKAHUHPKA SUHTER 470 234.0 0.352231
278 PANfSOFFKEE SUHTER 4440 700.0 0.154151
271 BUTLER UNION 420 24.0 0.057143
280 PALESTINE UNION 111 35.0 0.038411
281 SHIFT CREEK pond UNION 548 7.0 0.012324
282 ASHEY VOLUSIA 1030 24.0 0.023301
283 beresfurd VOLUSIA 800 44.0 0.082500
284 BETfCL VDLUSIA 213 3.0 0.014085
285 HARrEY VOLUSIA 4058 15.0 0.015482
284 LOUISE VOLUSIA 25? 25.0 0.017274
287 HONFOE VOLUSIA 1404 11.0 0.002020
288 NORTH TALHADGE VOLUSIA 121 4.0 0.033058
281 puzzle VOLUSIA 1300 325.0 0.250000
210 SOUTH TALHADGE VDLUSIA 40 2.0 0.033333
211 OTTER WAKULLA 133 2.0 0.015038
212 bear mmm pond WASHINGTON 40 3.0 0.075000
213 GAP FD sc- WASHINGTON 52? 212.0 0.40227?
214 HICK fokd WASHINGTON 482 122.0 0.253112
215 LUCAv fond WASHINGTON 455 107.0 0.235145
214 hcdmiel LAKES WASHINGTON 50 12.0 0.240000
��� mmamasKmim uaam HH�K�HK�K�KKj8i� man Table 2-13. (Continued) * FLORIDA HACROPHYTE DATA �
BBS Lft*t COUNTY LAKEAREA TOTHDS COVER
SI K/W WASHINGTON 30 3 0.10000
218 PORTER WASHINGTON 143 412 0 44811
211 THE DEADLY LAKES WASHINGTON 253 213 l'15810
Table 2-14. Frequency of Samples in Florida Lakes.
Number of Lakes With Number of Samples_Indicated Number of Samples
Table 2-15. Most Frequently Sampled Florida Lakes.
c?s LAKE CGUNTY NUHB
1 OKEECHOBEE DKEECHDBEE 421
2 GRIFFIN LAKE 275
3 APOPKA DRANGE 245
4 EUSTIS LAKE 250
5 JACKSOK LEON 147
4 TOHOPEKALIGA OSCEOLA 145
7 dora LAKE 151
6 tarpdk PINELLAS 127
1 TH0X0T0SASSA HILLSBOROUGH 111
10 JESSUP SEMINOLE 110
It BLUE CYPRESS INDIAN RIVER 104
12 IST0KP0GA HIGHLANDS 100
13 BUTLER ORANGE 17
14 KISSIHHEE OSCEOLA 11
15 TSALA APOPKA CITRUS 85
14 REEDY PDLK 84
17 MARION PDLK 70
18 HEOHYAKAPKA PDLK 41
11 MONROE VOLUSIA 41
20 june-IN-HINTER HIGHLANDS 47
21 BEAUCLAIR LAKE 44
22 MARY JANE ORANGE 44
23 CYPRESS OSCEOLA 44
24 MARIAN OSCEOLA 44
25 OCKLAHAHA HARIDN 43
24 ALLIGATOR OSCEOLA 43
27 ANNIE HIGHLANDS 41
23 EDLA ORANGE 58
21 ROUSSEAU LEVY 54
30 ROSALIE POLK 54
31 FRANCIS 55
32 YALE LAKE 54
33 HEIR HARIDN 54
34 PANASOFFKEE SUHTER 54
35 ORANGE ALACHUA 51
34 ARBUCKLE POLK 51
CHARITY ORANGE 50
33 FAITH ORANGE 50
31 HOPE ORANGE 50
40 KERR HARION 41
41 KINGSLEY CLAY 44
42 PORTER ORANGE 44
43 HASHIHGTDN BREVARD 44
44 POINSETT BREVARD 43
45 HINNEOLA LAKE 43
44 SANTA FE ALACHUA 41
u? TALfiUIN GADSDEN 41
48 EAST TOHOPEKALIGA OSCEOLA 41
41 lulu PDLK 41
50 DEER POINT , BAY 31
51 JACKSON HIGHLANDS 31
52 PLACID HIGHLANDS 31
53 UNDERHILL DRANGE 38
54 HATCHINEHA DSCEOLA 38
55 eldise POLK 38
54 NEUNANS ALACHUA 37
57 HARRIS LAKE 37
z-i IUNNEHAHA LAKE 34
51 LDHERY POLK 35
<<0 MAITLAND ORANGE 33
41 LOUISA LAKE 31
42 LUCIEN ORANGE 31
43 CANNON PQLK 30
cl4 JESSIE PQLK 30
45 HOHELL SEHINOLE 30
55 55 Lake Study
20 Acid Rain Study
40 National Eutrophication Survey
103 Florida Game and Fish
165 Aquatic Weeds Survey
30 Urban Lakes
4 UCF, FSU, FIT
1 Florida Game and Fish
1 Brevard County
299 Macrophyte Data
Original data from the Aquatic Weeds Survey and from STORET frequently represented multiple samples of a lake on the same day and/or at different stations. Such data values were averaged to provide one mean value per lake per day. Hence, "raw" data in the data base from those two sources do not necessarily represent individual lake samples.
Lake areas are available for all lakes, using either recent measurements or a value from the Gazetteer (Florida Board of Conservation, 1969) as a default value. Limited additional physical data (e.g., elevation, mean depth) are available for about 100 lakes. Latitude and longitude are given for all lakes, although in practice it has been found that the county (included for all lakes) is the most useful location parameter.
The lake data are organized as a Statistical Analysis System (SAS, 1979) data set on the Northeast Regional Data Center (NERDC) computer network at the University of Florida, which operates two computer mainframes (an Amdahl 470 and an IBM 3033). The data set comprises 9914 entries as of June 1982.
A description of parameters and information in the data set is presented in Appendix C. The data set has been placed on a magnetic tape for storage and transferral to other users.
A large amount of project time and effort was spent in combining the several data sources into the one overall data base. A considerable number of discrepancies were found for spellings of names among different sources for the same lake. These discrepancies were caused both by misspellings and by differences in local practice. (For instance, Lake Hell'N Blazes and Lake He lien Blazes are both used on maps and in the literature, but the former is the name originally given the lake.) Different sources also frequently used confusing or incorrect identification numbers, (e.g., as arbitrarily assigned in STORET or by various agencies), and there was not always unanimity on whether the word "lake" should precede or follow the name. (In FLADAB, the word "lake" is omitted.) These conflicts had to be resolved, usually on a painstaking, individual lake basis, before data from different sources for one lake could be combined. The most difficult source was the STORET data base, in which it is common to have the same lake given with different spellings and in different counties.
A further quality control procedure involved a visual check of data entries. In this manner obvious errors could be found. All data keypunched as part of the project were checked visually against the source; however, only a few of the data that were already computerized were so checked.
The Florida Lakes Gazetteer (Florida Board of Conservation, 1969) contains a listing of about 7,500 Florida lakes, man-made and natural, named and unnamed, including reservoirs and some ponds. The surface area, elevation and map number are given for almost all lakes along with location (county, river basin, section, township and range). Four hydrologic types of lakes are listed (surface inflow, surface outflow, both, neither [i.e. seepage]), and drainage area is listed for a few lakes. Finally, remark codes are given regarding access, meandering, gaging and miscellaneous. The Gazetteer remains * useful document even though some of the information may have changed since its publication.
During this project, punched Gards containing some of the Gazetteer information for 6562 lakes with surface areas greater than or equal to 10 acres were obtained from the DER. (Cards for Highlands County were missing and subsequently punched during the project.) These cards were placed on a computer file at UF and used for needed information when required. Unfortunately, not all Gazetteer information was on the cards; for instance, remark codes were listed only as a letter "R". Hence, it is not possible to sort or search the file using the remark codes. The 1969 Gazetteer contained 160 italicized names from local usage for unnamed lakes on the USGS topographic maps used to compile the inventory. These names for 120 lakes were inserted into the computerized Gazetteer data. (An additional 40 italicized names in the NE and NW Florida quadrants were not represented among the 6562 punched cards.) Also approximately 80� named lakes smaller than 10 acres were subsequently added to the Gazetteer.
The result of these modifications is a revised Gazetteer, published separately (Dickinson et al., 1982) that includes computer listings of 7,320 lakes, containing: name, indication of a remark (R or blank), Florida Board of Conservation topographic map number, location, surface area, elevation, type, latitude-longitude and county. (Latitude and longitude may not agree exactly with more accurate values in the FLADAB.) The difference between (approximately) 7,712 total lakes in Florida and the 7,320 listed is that about 210 names refer to two or more multiple lakes. Including all multiple lakes gives the value 7,712. Approximately 200 fewer lakes are listed in the revised Gazetteer than in the 1969 edition because it was not possible to identify and include all unnamed lakes that were missing from computer cards. The revised Gazetteer does not replace the 1969 Gazetteer since it does not contain all the information contained in that publication. However, since it is computerized, the available data are more accessible in the revised than in the original form.
LOCATION MAPS FOR FLORIDA LAKES
It is not possible to place all of the nearly 3189 named Florida lakes or even the 573 lakes with nutrient data onto one report-sized map. The best single large scale map appears to be the 1:500,000 scale "State of Florida" map published by the USGS in Reston, Virginia (1967 edition). This 60 inch by 45 inch map contains most of the lakes discussed in this report and provides a base for section, township and range for the State. Almost all lakes can be located on 1:24,000 USGS quadrangle maps although .here can be ambiguities if the lakes are unnamed. Lakes typically are identified by county within this report, and a map of counties is shown in Figure 2-1.
A L A B
NORTHWEST FLORIDA WATER MANAGEMENT DISTRICT, HAVANA
SUWANNEE RIVER WATER MANAGEMENT DISTRICT, LIVE OAK
ST. JOHNS "J Y RIVER WATER-| -VM MANAGEMENT i�x DISTRICT, fiSy-^A M^X PALATKA
SOUTHWEST FLORIDA WATER MANAGEMENT DISTRICT, BROOKSVILLE
SOUTH FLORIDA WATER MANAGEMENT DISTRICT, WEST PALM BEACH -
0 O 20 30 �0 SO MILES
Figure 2-1. Location Map of Florida Counties and Water Management
Districts. (after Heath and Conover, 1981, p. 5)
Boundaries of the State's five water management districts are also shown. Lakes may also be located by their latitude and longitude, which are presented in the new Gazetteer.
Special attention is given in Chapter 6 to the Oklawaha Lakes of Central Florida. These are shown in Figure 2-2.
r^-J~Mfif ION COUNTY
M/o Ration alX^I
) Radio tower^
AaAe ICustis A
C Z ^ f'V
yt- ^>iLj^^^ JF?^Lri/f
0 ViH^^/P" ^^-'^^^
_/ V, <-
T*a -f Of) Clermont!
(y-TK- 7W.i>k/ v/f � V
� nil o
Figure 2-2. Map of the Oklawaha Lakes. Source: USGS 1:250,000 map, "Orlando-1962."
DEVELOPMENT OF A TROPHIC INDEX SCHEME TO RANK FLORIDA LAKES INTRODUCTION
Trophic state is the integrated expression of the nutritional status of a water body. As such, it is widely accepted that no single trophic indicator or parameter is adequate to completely describe and/or quantify the concept. Limnologists and water quality scientists have used a multiplicity of physical, chemical, and biological indicators to describe trophic state. The problem with this multivariable approach, of course, is that quantification of trophic state becomes difficult and often ambiguous. In the past, limnologists reviewed data on a variety of trophic state indicators and then assigned a lake to a certain trophic class in a simple nomenclatural system (e.g. most commonly based on oligotrophic, mesotrophic, eutrophic categories). This approach is now generally regarded as too subjective and too imprecise.
One approach to circumvent the above dilemma is to avoid nomenclatural classes altogether and to quantify the concept of trophic state by means of an index (or in some cases, by several indices). A large number of trophic indices have been proposed over the past 10-12 years. These indices vary widely in selection of indicator variables, method of development, mathematical complexity, precision and quantitativeness, and finally in acceptance by the limnological community. A review of indices developed through 1976 was prepared for the FDER by Brezonik (1976). Reckhow (1981) has described some more recent indices in a report for the United St<_,es Environmental Protection Agency Clean Lakes Program. The most important examples of these previously developed indices are described briefly in the following section.
TROPHIC INDEX SCHEMES REPORTED IN THE LITERATURE
Indices have long been used to simplify complicated phenomena. In essence an index reduces the dimensionality of a phenomenon to a single dimension or variable, which usually is a function of several measured variables. Perhaps the most commonly-cited index in our daily life is the gross national product (GNP). This single figure represents the entire economic activity of the country. Many other economic indices are also in common use; for example the Dow-Jones stock average is an index of conditions in the stock market.
Indices recently have become popular in the field of environmental quality. According to Brezonik (1976) , at least four reasons can be given for developing trophic state indices:
1) a numerical index is helpful in conveying lake quality information to the non- and semi-technical public;
2) an index is useful in comparing overall trophic conditions between lakes;
3) in the dynamic process of lake trophic change, an index provides a means to evaluate the direction and rate of change; and
4) an index can be used to develop empirical models of trophic conditions as functions of watershed "enrichment" factors (e.g. Shannon and Brezonik 1972).
As Reckhow (1981) has pointed out, an index is a summary statistic;
indices are used because the convenience of summarizing information in a
single number outweighs the disadvantage of information lost in the act of
summarization. Of course, it should be noted that the original data are not
really lost; they can be retrieved and examined if the summary statistic
(index) provides insufficient detail for the purpose of analysis.
Aside from semi-quantitative indices based on indicator organisms, which have been used in limnology for many years, the first indices used to compare lakes according to trophic state were simple ranking schemes for closed sets of lakes. For example, Lueschow et al. (1970) ranked 12 Wisconsin lakes based on five trophic indicators. The rankings of each lake according to each of the parameters were summed to yield a composite trophic ranking for * each lake.
A somewhat more sophisticated approach involves the use of proportional rankings for individual parameters. These rankings can be obtained as the difference between the parameter value for a lake and the minimum (or maximum) value for all lakes in the data set, divided by the range for the parameter among all lakes. Michalski and Conroy (1972) developed such a proportional ranking scheme using six parameters for ten lakes in Ontario. The National Eutrophication Survey of the US EPA used a percentile ranking system to rank the survey lakes in each state based on six trophic indicators. The NES also developed a similar percentile ranking scheme for a composite of several hundred survey lakes in the eastern United States.
Although relative ranking schemes can be useful in comparing lakes within a closed data set, such relative rankings have obvious limitations for open data sets (where lakes may be added to the data set after the original rankings are made) and even for very large, closed sets. Consequently, most recent trophic ranking schemes involve indices based on an absolute scale. Some of these indices involve well-defined and easily quantified variables (like chlorophyll a. and Secchi disk transparency), whereas others involve ill-defined variables like aesthetics (Wisconsin DNR, 1975) and use impairment (Uttormark and Wall, 1975).
Parameters like use impairment are defined on an arbitrary dimensionless scale, and determination of the scale value for a given lake involves subjective considerations. For example, Uttormark and Wall (1975) developed a "Lake Condition Index" (LCI) based on numerical ratings of lakes in four categories: dissolved oxygen (0-6 points), transparency (0-4 points), fish kills (0-4 points), and use-Impairment (0-9 points). In each category, zero represents the most desirable condition; penalty points are assigned based on a somewhat subjective evaluation of the severity of problems. The LCI is the sum of the penalty points for the four categories. A more complicated recreational index was devised by the Wisconsin DNR (1975) based on eleven criteria associated with four recreational categories (see Brezonik  for further details).
The first quantitative TSI involving conventional indicators like transparency, chlorophyll and nutrient levels was developed by Shannon and Brezonik (1972). The authors used a data base of 55 lakes in north-central Florida with a range from very oligotrophic to hypereutrophic conditions. Trophic state was defined in terms of seven indicators: chlorophyll _a, N, and P concentrations, transparency, primary productivity, conductivity, and a major cation ratio (divalent/monovalent ions). Shannon and Brezonik's index was developed by the multivariate statistical technique of principal component analysis, which reduces the dimensionality of a data set by deriving new (principal component) variables (PCV's) that are linear functions of the observed variables. The new variables are obtained from the characteristic roots and corresponding eigenvector of a correlation or covariance matrix of the original variables; the first PCV is the linear combination of the observed variables that explains the maximum variance in the original data. In Shannon and Brezonik's case, the first PCV accounted for about 70 percent of the variance, and this derived variable
thus was considered to best represent the single underlying concept (i.e. trophic state) described in part by each of the indicators. The Shannon-Brezonik TSI was a simple transformation of the first PCV, scaled to eliminate negative values. Further details on the index and a critique of its value and limitations are given by Brezonik (1976) and VanBelle and Meeter (1975).
This index has been used by various groups in the State of Florida over the past 10 years, but it suffers from several practical and theoretical problems, including the limited geographic extent of the data base, the difficulty in measuring some of the indicators (e.g. primary production), and the lack of an intrinsic relationship between some indicators (conductivity and the cation ratio) and the basic phenomenon of eutrophication, i.e. nutrient enrichment. Thus, use of this index is no longer recommended.
Of the recent attempts to develop trophic indices, the most widely used and best known is that of Carlson (1977). His approach was fundamental, and it is attractive because it has a good theoretical basis and relies on the three trophic indicators that are best understood and quantified. Separate indices were derived for each parameter from a data base of north temperate lakes. Because Carlson's approach was used to derive similar indices in the present study, his indices are described below in -some detail.
Carlson's goal was to have each index related to algal biomass such that a 10 unit change in the index would represent a doubling or halving of algal biomass. Each of the three indices was derived for a single indicator; i.e. the indices are univariate. Carlson developed indices based on Secchi disk transparency (SD), chlorophyll a concentration (Chi a), and total phosphorus concentration (TP), as the three best-quantified indicators of trophic state.
The three variables are highly inter-correlated, and as such each can be considered as an estimator or metric of the same underlying phenomenon (trophic state, or more narrowly, algal biomass).
Obviously, the most direct measure of algal biomass is obtained from chlorophyll a.; nonetheless Carlson chose Secchi disk transparency as the primary indicator, and he derived an index [TSI(SD)] such that a doubling of transparency caused the index to increase 10 units. The index was scaled such that TSI=0 represents a transparency of 64 m, which is greater than any lake transparency reported in literature, and TSI=50 represents a transparency of 2 m, which is commonly accepted as the approximate demarcation between oligotrophic and eutrophic lakes.
Carlson then developed indices for Chi a. and Chi a vs. TP into TSI(SD). The relationship between SD and Chi a was found to be nonlinear (In SD=2.04-0.68 In Chi a), and as a result the derived index for Chi a_ differs from those for SD and TP in that a 10 unit change in the former does not represent a factor-of-two change in Chi a concentration. Instead, Chi a doubles for each -1 unit increase in TSI(Chl a) (Carlson 1980).
Carlson (1977) recommended that his indices be used separately and argued that their use in combination (e.g. use of the average of the three indices) resulted in an undesirable loss of information. For a "well-behaved" lake (i.e. one in which the relationships among the three variables follow the regression relationships), the three indices should yield the same value. Carlson argued that in cases where the index values are different, the differences provide useful information on the lake. For example, if TSI(TP) > TSI(Chl a.), phosphorus probably is not the limiting nutrient for the lake; TS(SD) > TSI(Chl a) indicates the presence of non-algal turbidity in the lake. On the other hand, these inferences could be made from the untransformed data without recourse to
use of indices. As mentioned previously, indices are usually integrative measures, and loss of detail is perhaps an inevitable trade-off for advantage of integration. The desire to express trophic state on a single numerical scale has led some water quality scientists to combine Carlson's three indices and to report their simple arithmetic average.
Several trophic state indices have been developed recently that rely on Carlson's approach. For example, Kratzer and Brezonik (1981) developed a TSI based on total nitrogen concentration to complement Carlson's TSI(TP). The TSI(TN) was developed from a data base of primarily nitrogen-limited Florida lakes. Kratzer and Brezonik proposed that the lesser value of TSI(TN) and TSI(TP) indicated which of the two nutrients was limiting in a lake, and they combined the lower of these values with TSI(SD) and TSI(Chi a) to produce an average TSI that integrates the major physical, chemical, and biological features of trophic state.
Porcella et al. (1980) outlined a "Lake Evaluation Index", LEI, based partially on Carlson's indices. This index, the development of which is incomplete, was described by Reckhow (1981). The index is composed of 5-6 variables that are transformed into subindices called X-values. The latter are combined to produce the LEI as follows:
LEI = 0.25 [0.5(XCHA + XMAC) + XDO + XSD + XTP] (3-1) where XCHA, XSD, and XTP are obtained from Carlson's TSI equations for chlorophyll, Secchi disk, and total phosphorus, XMAC is a macrophyte subindex determined from percent coverage information, and XDO is a dissolved oxygen subindex based on the volume-wexghted deficit of O2 in the lake. A subindex for nitrogen was proposed but not included in the LEI. The index of Porcella et al. has certain desirable features, but its usefulness and acceptance by limnologists remain to be determined. Direct application of the LEI to
Florida lakes probably would not be appropriate. For example, thermal stratification is uncommon, and thus dissolved oxygen deficits typically are not a problem in Florida lakes.
Walker (1979) developed a series of indices that are analogous to those of Carlson (1977) but offer some advantages over Carlson's TSl's. Walker's index is based on chlorophyll a, which probably is the best measure of the central problem resulting from eutrophication (i.e. an increase in algal biomass resulting from increased nutrient concentrations). The components of Walker's index are:
I,,. . = 20 + 14.4 In Chi a Chi a �
ITp - 15.6 + 20 in TP (3-2)
ISD = 75.3 + 19.5 In (1/SD - a) The term a represents non-algal influences (e.g. clay, organic color) on transparency and has units of m \ Walker's index is the simple arithmetic average of the components (Reckhow 1981):
Tw= (lChl a+ *TP + hT?/3 <3"3> This index was developed from a data base on north temperate lakes, and thus it
should not be applied directly to Florida lakes.
In summary, a large variety of trophic state indices and "lake condition"
indices are available in the literature. Many have similar features; most
have been derived from data on temperate lakes. For this reason, none of the
recent indices (except perhaps for Kratzer and Brezonik's subindex for TN)
should be applied directly to Florida lakes. The approaches and positive
features of these indices are useful, nontheless, in developing a trophic
state index suitable for Florida lakes.
BASIS FOR A TROPHIC STATE INDEX FOR FLORIDA LAKES
The approach used by Carlson in deriving his indices has many advantages, but direct application of his indices to Florida lakes has some potential and real disadvantages. The most important of these disadvantages are summarized below.
1. The indices were based on interrelationships among SD, TP, and Chi a_ derived from a data base of north temperate lakes. Previous studies on subtropical and warm-temperate Florida Lakes, e.g. Baker et al. (1981), indicate that these lakes have somewhat different relationships among these variables. Thus indices for Florida lakes should be based on regression relationships developed from data on Florida lakes.
2. Carlson's index system assumes phosphorus is the limiting nutrient, but many Florida lakes are known to be nitrogen-limited. As mentioned previously, Kratzer and Brezonik (1981) developed a TSI(TN) for nitrogen-limited Florida lakes, and they proposed that the limiting nutrient for
a lake could be determined from the lower of TSI(TN) and TSI(TP). The lower of these values is used with TSI(SD) and TSI(Chl a.) to produce an average TSI. This general approach seems appropriate for Florida lakes.
3. Carlson's indices were derived based on SD; i.e. a factor of two change in SD produced a 10 unit change in the index. Carlson and others have reported nonlinear relationshps between SD and Chi a^, and a ten unit change in his TSI(Chi a) is not equivalent to a factor-of-two change
in Chi si (hence presumably in algal biomass). An increase in plant biomass is the central phenomenon of eutrophication (i.e. the primary consequence of nutrient enrichment). Thus it seems more appropriate to base the index on a more direct measure of plant biomass (e.g. Chi a).
4. Carlson's indices do not account for macrophyte problems that may occur as a consequence of nutrient enrichment. Such problems are common
in Florida lakes, and it would be desirable to be able to quantify macrophy problems and relate them to nutrient loading.
Based on the above considerations, a series of indices has been developed herein to rank and classify Florida lakes according to trophic state. In each case, the index is multivariate and represents the average of the main physical, chemical and biological expressions of the trophic state concept. Secchi disk transparency is the physical measure of trophic state; chlorophyll a_ and macrophyte abundance (MAC) are the biological measures, and concentrations
of total phosphorus and total nitrogen are the chemical measures. Accordingly, four subindices TSI(i), where i=SD, Chi a, TP, or TN were developed. Macro-phytes were considered separately and not as a subindex. Different average TSl's (and different nutrient subindices) were developed depending on whether the lake is primarily phosphorus-limited, primarily nitrogen-limited, or has a relatively well-balanced nutrient ratio.
DEVELOPMENT OF SUBINDICES General Approach
An increase in plant biomass is the central phenomenon of eutrophication, and consequently plant biomass indicators were selected as the basis for the indices. For algal biomass an index was developed based on chlorophyll, which is the most easily and widely quantified measures of algal abundance. An index [TSI(Chi a)] was developed such that a doubling of chlorophyll a concentration (hence a doubling of biomass) produces a 10 unit increase in the index. Subindices for Secchi disk transparency and TP and TN concentrations were derived by substituting regression-derived relationships between these variables and chlorophyll a^ concentration into TSI(Chi a).
For macrophyte biomass a different approach was used; instead of developing a somewhat conjectoral TSI(MAC), percent macrophyte coverage was used directly to form this index. Quantitative relationships are not well-defined between macrophyte abundance and the other trophic indicators, and macrophyte coverage tends to be independent of the other subindices, as shown subsequently.
Relationships Between Chi a and SD, TP and TN
Relationships between chlorophyll a concentration and the above variables (taken one at a time) were determined by regression analysis using two procedures
in the Statistical Analysis System (SAS): Proc GLM and Proc LAV. Proc GLM estimates the linear parameters of a model by using least squares regression. In least squares regression the sum of the squares of the deviations between the predicted line and the data points is minimized. Proc LAV estimates the linear parameters of a linear model by using least absolute value regression. This method minimizes the sum of the absolute deviations between the predicted line and the data points.
Least absolute value regression is preferred in cases where the data are widely scattered, since it is less influenced by outlier data points. The least absolute value regression line is the median line of best fit, since half the data points are on either side of the line. In contrast, the least-squares regression line may not be even close to the median line, since the regression line will be skewed to the side with the greatest magnitude outliers. For this reason the least absolute value regression parameters were used in development of trophic state indices for Florida lakes.
In the regressions that follow, data from 313 lakes from the non-STORET data base were used. The lakes are tabulated in Appendix F (Table F-4), and they represent the best and most complete data set at the time of the analysis. Subsequent regression trials were made using all data from the 573 lakes in FLADAB. Results differed insignificantly from the earlier runs with the 313 lakes, primarily because most studies with multiple lake samples are contained among the 313 lakes.
Figure 3-1 is a plot of Secchi disk depth versus chlorophyll a concentration for the 313 lakes from the non-STORET Florida Lake Data Base. The plot is nonlinear and hints at a power function relationship between Secchi disk and chlorophyll _a.
SECCHI DISK VERSUS CHLOROPHYLL A
M E fl
S E C C H I
M E T
c R 5
313 Florida Lakes
"i�i�r"i i i l i t�i i i i
100 150 200
HERN CHLOROPHYLL fl - t1G/KL3
u 'J 1
Figure 3-1. Secchi Disk vs. Chlorophyll a.
To linearize the model the natural log of both variables is taken. Because of the large range (several orders of magnitude) of values for each trophic indicator and the possibility of non-linear (power function) relationships between variables the (base e) log-log form was used for all regressions developed here.
TSI (Chi a)
As previously mentioned, the subindex for chlorophyll formed the basis
for the subindices for SD, TP, and TN. TSl(Chl a) was developed based on two
criteria: (1) a doubling of chlorophyll a concentration would produce a 10
unit increase in the index, and (2) the midpoint of the index scale [TSI(Chl
a) = 50] would be equivalent to Chi a = 10 mg/m . The latter value generally
is accepted as the approximate dividing line between eutrophic and non-eutrophic
lakes. A TSI (Chi a.) = 60 is equivalent to a chlorophyll a of 20 mg/m , which
corresponds to the "ad hoc" desirable upper limit used by the Florida DER to
define problem lakes (J. Hand, personal communication, 1980). The equation
for TSI(Chi a) is:
TSI(Chi a) = 10(1.68 +ln Chi a),
or TSI(Chi a) = 16.8 + 14.4 In Chi a (3-4)
where Chi a is in mg/m . The factor 1.68 is simply a scaling term so that Chi 3
a = 10 mg/m yields a TSI of 50; the In 2 term converts the equation from base 2 logarithms and scales the equation so that a doubling of Chi .a. results in a 10 unit change in the index. Table 3-1 lists chlorophyll a concentrations corresponding to TSI values from 0 to 100 in units of 10.
The subindex for SD was obtained from a regression between SD and Chi a for data from the 313 selected lakes from the. non-STORET Florida Lake Data
Table 3-1. Trophic Indicator Values Associated with
TSI Sub-index Values.
P-limited* N-limited** Nutrient-balanced***
lakes lakes lakes
TSI(i) Chi a SD TP TN TP TN
(mg/m3) (m) (yg/L) (mg/L) (yg/L) (mg/L)
0 0.3 7.4 2.7 .06 2.7 .060
10 0.6 5.3 4.1 .10 4.6 .1
20 1.3 3.8 6.3 .16 7.9 .16
30 2.5 2.7 9.6 .25 13.5 .27
40 5.0 2.0 15 .40 23 .45
50 10.0 1.4 23 .64 39.5 .74
60 20.0 1.0 34 1.02 67.7 1.23
70 40 0.72 52 1.62 116 2.04
80 80 0.51 80 2.58 198 3.4
90 160 0.37 122 4.11 340 5.6
100 320 0.26 185 6.54 581 9.3
* TN/TP > 30 (wt/wt) ** TN/TP < 10 *** 10 < TN/TP < 30
Base. Secchi transparency data were .in meters, and Chi a_ data were 3
in mg/m . Uncorrected (total) chlorophyll a values were used since only about half of the studies comprising the data base reported corrected values (i.e. total chlorophyll & minus phaeophytin a).
Figure 3-2 depicts the Proc GLM output along with the confidence limits on the regression line. Figure 3-3 shows the data points and the Proc LAV line of best fit. The Proc GLM output is:
In SD = 1.28 - 0.434 In Chi a (3-5a)
or SD - 3.6 Chi a"0,434 (r2 = 0.61) (3-5b).
The Proc LAV output is:
In SD = 1.46 - 0.484 In Chi a (3-6a)
or SD = 4.33 Chi a H (Pr < 0.0001) (3-6b).
Unfortunately, there is no widely accepted measure of goodness of fit for LAV regression. Instead, reliance must be placed on visual inspection and comparison of sums of absolute values of the residuals. In the case of the GLM and LAV regressions for SD vs. Chi a_, visual comparison of Figures 3-2 and 3-3 clearly favors the Proc LAV regression line. The median line is less sensitive to the large outliers, and overall it yields a better description of the relationship between the two variables. The scatter of the data is due to many factors. First, there is the multiplicity of data sources. Second, some lakes are high in color and low in chlorophyll a_ and Secchi disk depth. The lake data points at the lower left of the figures fall into this category. Thirdly, there is the normal variation present in any random process.
Substitution of the LAV expression for SD vs. Chi a_ into eq. 3-4, rearranging and simplifying leads to the following TSI(SD):
TSI(SD) = 10[6.0 - 3.0 In SD] (3-7)
SECCHI DISK VERSUS CHLOROPHYLL A
* LOG SD = B + ti x LOG CHLfl *
* STRRS RRc ACTUAL DRTR P0INT5 * x PROC GLM REGRESSION LIME *
* SS7. CONFIDENCE LIMITS fiRE ON *
* MEAN PREDICTED VRLUE5 *
-1-r�.� -i l- - i- �l i i �1 | : l-1-1-1-.--,-1-1-,-1--1--,---t-1� ,-t--,-,-j-j--,-,-.-,--,---,--,_
0 2 i] g
LOG Cttlfl CONCEKTRflTtOM
Figure 3-2. Ln Secchi Disk vs. Ln Chlorophyll a, Least Squares Fit.
SECCHI DISK VERSUS CHLOROPH
x LOG SD = B + M x LOG CHLfl * k STARS ARE ACTUAL DATA POINTS * * BULL5ETE ARE PREDICTED POINTS-x PROC LAV REGRESSION LINE x
- 2 0 2 ll
LOG CHLfl CONCENTRATION
Figure 3-3. Ln Secchi Disk Depth vs. Ln Chlorophyll a_ Concentration, Least Absolute Value Fit.
Based on this equation, a transparency of 1.0 m corresponds to a TSI of 60, and a transparency of 2.0 m yields a TSI of 39. SD values associated with TSI values from 0 to 100 (in units of 10) are listed in Table 3-1.
TSI(TP). Based on a review of the literature (Smith, 1982), it was concluded that lakes with ratios of TN/TP > 30 (wt/wt basis) may be considered phosphorus-limited. Lakes with TN/TP < 10 (wt/wt basis) may be considered to be potentially nitrogen-limited, and lakes with intermediate TN/TP ratios (10 <_ TN/TP <_ 30), may be considered to have a relatively balanced nutritional status. Separate chlorophyll-nutrient regressions were developed for these three subsets of nutrient-limiting conditions in order to best express the relationship between algal biomass and concentration of the limiting nutrient.
A subset of 95 lakes with TN/TP ratios > 30 (i.e. phosphorus-limited lakes) was obtained from the 313 listed in Table F-4 (see Table F-l for a listing of all P-limited lakes). A regression of uncorrected chlorophyll a vs. TP was obtained by the SAS LAV procedure (see Figure 3-4):
ln Chi a = 1.64 In TP - 2.12 (3-8a)
or Chi a_ = 0.06 TP (3-8b)
where both Chi a and TP are expressed in yg/L (mg/m ). Substitution of this regression relationship into eq. 3-4, rearranging and simplifying leads to the expression:
TSI(TP) = 10(2.36 In TP - 2.38) (TP in yg/L) (3-9)
A TP of 20 yg/L corresponds to a TSI of 47; i ralue of 50 yg/L (generally accepted as in the eutrophic range [Vollenweider, 1968, Dillon and Rigler, 1975, Baker et al., 1981]) yields a TSI of 69. Table 3-1 tabulates values of TP corresponding to TSI values from 0 to 100 in units of 10. Because lakes with ratios of TN/TP > 30 reasonably can be assumed to be phosphorus-
CHLOROPHYLL A VERSUS TOTAL PHOSPHORUS
* LOG CHLfl = 5 + M x LOG TP *
* STARS RRE RCTURL DATA POINTS * k BULLSEYE ARE PREDICTED POINTS* x PROC LRV REGRESSION LINE * x TN/TP RATIO ;> 30.0 *
?.0 2.5 3.0
LCu TO I AL PHOSPHORUS
Figure 3-4. Chlorophyll a_ vs. Total Phosphorus, Least Absolute Value Fit.
limited, with little or no limitation by nitrogen, the regression in eq. 3-8 should be the best predictive relationship between chlorophyll a^ (or algal biomass) and in-lake limiting nutrient concentrations for such lakes. The corresponding TSI(TP) thus is the best nutrient-related estimator of trophic state for P-limited lakes (lakes with TN/TP > 30).
For informational purposes, a least-squares (Proc GLM) regression also was run for the subset of P-limited lakes (see Figure 3-5) , and the resulting equation of best fit is:
ln Chi a = 1.52 In TP - 2.48 (3-10a)
or Chi a - 0.084 TP1,52 (r2= 0.69) (3-10b)
Because of the impact of outliers on the slope and intercept of this regression
line (as discussed earlier), it was not used to develop TSI(TP), but the r value indicates that variations in TP concentration explain about 70 percent of the variance in Chi & concentration.
TSI(TN). For lakes that are potentially nitrogen-limited (TN/TP < 10), algal biomass should relate more closely to the concentration of TN than to TP. In general, the relationship between Chi a_ and TP will change and become less exact as the ratio of TN/TP decreases. Consequently, an index based on TP would be a poor predictor of algal biomass (and hence of trophic state) in N-limited lakes. Thus TN is the appropriate chemical measure of trophic state in N-limited lakes.
A subset of 50 lakes with TN/TP < 10 (wt/wt) was obtained from those listed in Table F-4 (see Table F-2 for a list of all N-limited lakes). A regressi of uncorrected chlorophyll^ vs. TN was obtained by the SAS LAV procedure (see Figure 3-6) :
CHLOROPHYLL A VERSUS TOTAL PHOSPHORUS
* LOG CHLfl = B + M x LOG TP x x STARS ARE ACTUAL OATH POINTS * x BULL5EYE ARE PREDICTED POINTS* x PRCC GLM REGRESSION LINE x x TN/TP RATIO =>� 30.0 *
LOG TOTAL PKiJSPri�3RU5
Figure 3-5. Chlorophyll a vs. Phosphorus, Least Squares Fit.
CHLOROPHYLL A VERSUS TOTAL NITROGEN
x LOG CHLfl = 6 > H * LOG TN * x STARS HRE ACTUAL DATA POINTS * x BULL5EYE ARE PREDICTED POINTS* x PROC LRV REGRESSION LINE x x TN/TP < 10.0 x
-3.0 -1,0 -O.f; 0.6 l.fl
LOG TOTAL NTTftOSEN
Figure 3-6. Chlorophyll a vs. Total Nitrogen, Least Absolute Value Fit.
ln Chi a = 2.97 + 1.49 ln TN (Pr > 0.0001) (3-11)
where TN is in mg/L and Chi a. in mg/m . TN usually was determined as the sum of TKN plus N0~-N plus N0~-N or TON plus NH^-N plus oxidized N forms, but in those studies where only TKN was measured, it was assumed that TKN was the total N. Since N0� << NO^, and NO^ concentrations were much lower than TKN levels in all lakes having such data, this assumption is reasonable and did not introduce significant error into the Chi a - TN relationship.. Substitution of the above regression relationship into eq. 3-4, rearranging, and simplifying results in the following TSI:
TSI(TN) = 10(5.96 + 2.15 ln TN) (3-12) A TSI of 50 corresponds to TN = 0.64 mg/L, and TSI of 60 implies TN = 1.02 mg/L. These values seem reasonable for slightly eutrophic Florida lakes. Table 3-1 lists values of TN corresponding to the range of TSI values from 0 to 100 (in units of 10).
For informational purposes, least-squares regression also was performed on this data set (see Figure 3-7), yielding the equation
ln Chi a == 3.06 + 1.215 In TN (3-13a) or Chi a = 21.3 TN1,215 (r2 = 0.66) (3-13b).
Thus variations in TN concentration explain 66 percent of the variance in Chi a. concentrations in N-limited lakes.
TSI(Nutrient Balanced Lakes). Lakes having a TN/TP ratio between 10 and 30 exhibit relatively well-balanced nutrition, and it is not possible to assign a single limiting nutrient _o such lakes. Recent evidence (Smith 1982) suggests that lakes with N/P ratios in this approximate range respond to changes in loadings and concentrations of either N or P. Thus it is appropriate to relate chlorophyll a_ levels to concentrations of both nutrients and to use