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Canal-estuary nutrient exchange and metabolic levels in Florida residential canals

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Canal-estuary nutrient exchange and metabolic levels in Florida residential canals
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Canal-estuary nutrient exchange and metabolic levels in Florida residential canals
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Bailey, William Arthur
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William Arthur Bailey
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English

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Canals ( jstor )
Carbon ( jstor )
Datasets ( jstor )
Estuaries ( jstor )
Metabolism ( jstor )
Nutrients ( jstor )
Oxygen ( jstor )
Phosphorus ( jstor )
Plankton ( jstor )
Water quality ( jstor )
City of Marco Island ( local )

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University of Florida
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University of Florida
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Copyright [name of dissertation author]. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
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03334690 ( OCLC )

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CANAL-ESTUARY NUTRIENT EXCHANGE AND METABOLIC LEVELS
IN FLORIDA RESIDENTIAL CANALS








By

WILLIAM ARTHUR BAILEY


A DISSERTATION PRESENTED TO THE GRADUATE COUNCIL OF
THE UNIVERSITY OF FLORIDA
IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE
DEGREE OF DOCTOR OF PHILOSOPHY

















UNIVERSITY OF FLORIDA

1977















ACKNOWLEDGMENTS


Numerous individuals, to whom I am much indebted, helped me with

the field collections. During the 1975 collections, William Marsh,

Deborah Lupton, and Warren and Ann Hansen forfeited many hours that are

normally devoted to sleeping. Florinus Kooijman volunteered to accom-

pany me to Marco Island and Boca Ciega Bay; David Price to Hillsboro

Inlet and Panama City; and Richard Brightman to Apollo Beach.

The members of the department's chemistry laboratory, particularly

Hugh Prentice and Lloyd Chesney, were invaluable as troubleshooters

when I was having problems with water analyses. Without the Department

of Environmental Engineering Science's truck and boat, and without

Dr. Patrick Brezonik's ability to keep the chemistry laboratory stocked

with chemicals, I would have been unable to collect and analyze samples

during 1976.

I am grateful to Dr. B.A. Christensen and Fred Morris of the

Hydraulic Laboratory, Department of Civil Engineering, for providing me

with the 1975 hydrographic data and for loaning me a tide recorder

during 1976. I am also grateful to Dr. Emmett Bolch for providing me

an assistantship on his Florida Power Corporation Project during 1976.

I would like to thank my committee members for their comments and

guidance throughout this investigation. Dr. Jackson L. Fox, my chairman,

has spent many hours listening to my problems. His efforts are greatly

appreciated.









The person most responsible for my completion of this study is my

wife. Mary worked beside me during more than half of the sampling

trips and encouraged me when things seemed hopeless. She taught school,

under less than ideal circumstances, in order to support us and to pay

for unfunded sampling trips in 1976. I doubt that I would have com-

pleted this work without her.















TABLE OF CONTENTS


Page

ACKNOWLEDGMENTS . . . . . . . . . .. . ii

LIST OF TABLES . . . . . . . . .. . . . vi

LIST OF FIGURES. . . . . .. . . . . . . ix

ABSTRACT . . . . . . . . . . . . . xii

CHAPTER 1 INTRODUCTION . . . . . . . .. . 1

CHAPTER 2 LITERATURE REVIEW. . . . . . . . . 6

CHAPTER 3 SITE DESCRIPTIONS. . . . . . . . .. 16

CHAPTER 4 MATERIALS AND METHODS. . . . . . . ... 40

Metabolism . . . . . . . . . . 40
Nutrient Exchange and Water Quality. . . . ... 42
Canal/Sampling Day Characteristics . ... .. . 44
Statistical Analyses . . . . . . . .. 44

CHAPTER 5 RESULTS . . . . . . . . . . .. 45

Metabolism . . . . . . . . .. . 46
Combined Data . . . . . . . ... 46
1975 Data . ... . . . . . . ... 58
Daily Variability in One Canal. . . . ... 65
Nutrient Exchange. .. . . . . . .... .. 67
Combined Data . . . . . . . ... 67
Diurnal Cycle of Nutrient Concentrations. . 84
1975 Data . . . . . . . . ... 86
Daily Variability in One Canal. . . . ... 91
Water Quality. . . . . . . . . ... 93
Structure of the Data Principal Components . 100
Combined Data . . . . . . . ... 102
Metabolism. . . . . . . . . ... 104
Exchange. . . . . . . . . . 106
Water Quality ................ 107
Canal/Sampling Day Characteristics. . . ... 110
Summary . . . . . . . . .. 113
Canonical Correlations . . . . . . ... 114
Metabolism vs. Exchange . . . . ... .117
Metabolism vs. Water Quality. . . . ... 120









TABLE OF CONTENTS
(Continued)


Page


Metabolism vs. Canal/Sampling Day
Characteristics . . . . .
Exchange vs. Water Quality. . . .
Exchange vs. Canal/Sampling Day
Characteristics . . . . ..
Water Quality vs. Canal/Sampling Day
Characteristics . . . . .
Summary . . . . . . . .
Regression Equations . . . . . .


CHAPTER 6 DISCUSSION . . . . . . . .


Metabolism . . . . . . . .
Water Quality. . . . . . .
Nutrient Exchange. . . . . . .
General Observations . . . . . .
"Average" Canal . . . . . .
Design and Management Implications. .


CHAPTER 7 CONCLUSIONS. . . . . . . . .... .193

LIST OF REFERENCES . . . . . . . . ... . .196

APPENDIX A Oxygen metabolism data for all individual stations. 201


APPENDIX B


APPENDIX C


APPENDIX D


Oxygen profiles for all stations and sampling
times . . . . . . . . . . . .

Nutrient and water quality data for each canal
entrance and sampling interval. . . . . .

Descriptive statistics and correlation coefficients
for all parameters. . . . . . . . .


BIOGRAPHICAL SKETCH. . . . . . . . . . . .


. . . 123
. . . 126

. . 126

. . . 130
. . . 138
. . . 140


155

156
164
171
178
179
183


211


235


276

327














LIST OF TABLES


Table Page

1. Canal and sampling day physical characteristics ... .19

2. Nomenclature for variables. . . . .. .. . .. 47

3. Metabolism results averaged by canal for each sampling
day . . . . . . . .. . . . . . 51

4. Results of the analyses of variance for the total com-
munity and planktonic metabolism data (1975). . . .. .61

5. Community and plankton gross primary production mean
values for the 1975 data. .. . . . . . . 64

6. Metabolism results for three consecutive days of
sampling on one canal (North Miami site) . . . 66

7. Canal-estuary exchange results for the nutrient and
water quality parameters. .... . . . . . . .69

8. Regression coefficients for the change in nutrient con-
centrations versus time of day. . . . . . .. 85

9. Mean values for 1975 net-exchange data. . . . .. 88

10. Descriptive statistics and analyses of variance results
for 1975 net-exchange data. . . . . . . .. 90

11. Nutrient/water quality exchange results for three
consecutive days at the North Miami site. . .. . 92

12. Water quality characteristics for all canal observations. 95

13. Principal components of the combined data (44 variables). 103

14. Principal components and correlation matrix for the
metabolism data . . . . . . . . .. ... . 105

15. Principal components and correlation matrix for the
net nutrient exchange data. . . . . . . .. 108

16. Principal components and correlation matrix for the
water quality data. . . . . . . . . .. 109









LIST OF TABLES
(Continued)


Table Page

17. Principal components and correlation matrix for the
canal/sampling day characteristics . . . . ... 111

18. Data set variables used in correlation analyses. ... .118

19. Canonical correlation analysis of the metabolism and
nutrient exchange data sets. . . . . . . ... 119

20. Canonical correlation analysis of the metabolism and
water quality data sets.. . . . . . . . . 121

21. Canonical correlation analysis of the metabolism and
canal/sampling day data sets . . . . . ... 124

22. Canonical correlation analysis of the exchange and
water quality data sets. . . . . . . . ... 127

23. Canonical correlation analysis of the exchange and
canal/sampling day characteristics. . . . ... 128

24. Canonical correlation analysis of the water quality and
canal/sampling day characteristics day sets. . . . 131

25. Summary table for canonical correlation results. ... .139

26. Dependent and independent variables used in the stepwise
regression analyses. . . . . . . . . 142

27. Descriptive models for 20 dependent response parameters. 143

28. Significant-factor frequencies for the metabolism,
exchange, and water quality models . . . . ... .149

29. Appearance frequencies of the grouped factor-types in
the metabolism, exchange, and water quality models
(grouped) . . . . . . . . . . . 152

30. Gross primary production levels for different aquatic
systems. . . . .. . . . . . . . 157

31. Significant factor effects on canal metabolic parameters 161

32. Significant factor effects on canal water quality
parameters . . . . . . . . . . . . 169

33. Organic carbon net-exchanges for several coastal systems 174









LIST OF TABLES
(Continued)


Table Page

34. Significant factor effects on canal-estuary net
exchange parameters ................... 176

35. Physical characteristics, water quality, metabolic
levels, and net canal-estuary exchanges for an "average"
residential canal ..................... 180


viii















LIST OF FIGURES


Figure Page

1. Sampling sites within Florida. . . . . . . ... 17

2. Canal and sampling stations at Punta Gorda sites . .. 23

3. Canal and sampling stations at Port Charlotte
site . . . . . . . . . . . . .. 25

4. Canal and sampling stations at Pompano Beach
site . . . . . . . . . . . . . 26

5. Canal and sampling stations at Loxahatchee River
site . . . . . . . . . . . . . 27

6. Canal and sampling stations at Marco Island site . .. 29

7. Canal and sampling stations at Boca Ciega Bay
site . . . . . . . . . . . . . 30

8. Canal and sampling stations at Hillsboro Inlet
site . . . . .. . . . . . . . . 32

9. Canal and sampling stations at Flagler Beach
site . . . . . . . . . . . . . 33

10. Canal and sampling stations at Apollo Beach site . .. 34

11. Canal and sampling stations at Goose Bayou (Panama City)
site . . . . . . . . .. . . . 36

12. Canal and sampling stations at Key Colony site . . . 37

13. Canal and sampling stations at North Miami site. .. .... 38

14. Frequency distribution and descriptive statistics for
total community gross primary production (g 02/m2-day),
averaged by canal. . . . . . . . ... . 54

15. Frequency distribution and descriptive statistics for
planktonic gross primary production (g 02/m2-day),
averaged by canal. . . . . . . . . ... 54

16. Frequency distribution and descriptive statistics for
total community respiration (g 02/m2-day), averaged by
canal. . . . . . . . . . . . . . 56









LIST OF FIGURES
(Continued)


Figure Page

17. Frequency distribution and descriptive statistics for
planktonic respiration (g 02/m2-day), averaged by
canal. . . . . . . . . . . . . ... 56

18. Frequency distribution and descriptive statistics for
total community production:respiration ratio, averaged
by canal . . . . . . . . . . ... 57

19. Frequency distribution and descriptive statistics for
planktonic production:respiration ratio, averaged by
canal. . . . . . . . . ... ...... 57

20. Frequency distribution and descriptive statistics for
plankton domination of community production. . . ... 59

21. Frequency distribution and descriptive statistics for
(a) weighted-average ebb total carbon concentration
(mg/l), and (b) the net change from average flood
concentrations . . . . . . ... . . . . 74

22. Frequency distribution and descriptive statistics for
(a) weighted-average ebb inorganic carbon concentrations
(mg/1), and (b) the net changes from average flood
concentrations . . . . . . . ... . . 75

23. Frequency distribution and descriptive statistics for
(a) weighted-average ebb total organic carbon concen-
trations (mg/l), and (b) the net changes from average
flood concentrations . . . . . . . . ... .76

24. Frequency distribution and descriptive statistics for
(a) weighted-average total phosphorus concentrations
(mg/l), and (b) the net changes from average flood
concentrations . . . . . . . . . . . 78

25. Frequency distribution and descriptive statistics for
(a) weighted-average ebb ortho-phosphate concentrations
(mg/l), and (b) the net changes from average flood
concentrations . . . .... . . . . . . 79

26. Frequency distributions and descriptive statistics for
(a) weighted-average ebb total organic phosphorus con-
centrations (mg/l), and (b) the net changes from average
flood concentrations . . . . . . . .... .81

27. Frequency distribution and descriptive statistics for
(a) weighted-average ebb ammonia concentrations (mg/l),
and (b) the net changes from average flood concentrations. 82









LIST OF FIGURES
(Continued)


Figure Page

28. Frequency distribution and descriptive statistics for
(a) weighted-average ebb turbidity levels (NTU), and
(b) the net changes from average flood concentrations. .. 83

29. Frequency distribution and descriptive statistics for
(a) average dissolved oxygen concentrations (mg/1), and
(b) minimum dissolved oxygen values recorded in all
canals . . . . . ... . . . . .. . . 98

30. Frequency distribution and descriptive statistics for
the average Secchi depths (m) recorded in all canals 99












Abstract of Dissertation Presented to the Graduate Council
of the University of Florida in Partial Fulfillment of the Requirements
for the Degree of Doctor of Philosophy



CANAL-ESTUARY NUTRIENT EXCHANGE AND METABOLIC LEVELS IN
FLORIDA RESIDENTIAL CANALS

By

William Arthur Bailey

March 1977

Chairman: Jackson L. Fox
Major Department: Environmental Engineering Sciences

Sixty-one observations of oxygen metabolism, canal-estuary nutrient

exchange, and water quality in 35 residential canals at 12 locations in

the State of Florida were made over a 20 month period. The free-water

diurnal oxygen method and in situ light-dark bottle 24 hr oxygen in-

cubations were used to estimate the oxygen metabolism of the total canal

communities and the planktonic components. Total community gross

primary production varied from undetectable to 24.9 g 02/m2-day and

hadamean value of 8.59. Planktonic gross primary production varied

from 0.40 to 23.9 g 02/m2-day and had a mean value of 4.91. Community

gross primary production:community respiration ratios varied from 0.31

to 2.95 and had a mean value of 1.16. Regression equations for the

metabolic parameters explained more than 70 percent of the observed

variabilities using canal physical attributes, daylengths, solar in-

solation levels, and local estuarine water quality as independent

variables.

Net canal-estuary exchanges of carbon (total C mass and organic C),

phosphorus (total P mass, ortho-P, and total organic P), ammonia









turbidity, and color were determined from flow-weighted mean concen-

trations during flood and ebb tidal phases over complete tidal cycles

(24 hrs). Net exchanges varied from a substantial export to a sub-

stantial retention of these materials by canals. Most frequently, there

was little or no compositional change of the estuarine water than ex-

changed with the canal water. Canonical correlation analyses showed

that, in general, the net fluxes of materials across canal entrances

were independent of the metabolic levels within the canals and canal

water quality; the general correlation between material flux and canal/

sampling day characteristics seemed to be derived from an association

between turbidity and color exchanges and the current velocities within

the canals. Regression equations,however, explained more than 80 percent

of the observed exchange variabilities, except for that of ammonia and

ortho-P.

Daily and spatially averaged dissolved oxygen concentrations re-

corded in'the canals ranged from 1.78 to 9.07 mg/l and had a mean value

of 5.58. Most canals had average dissolved oxygen levels of 4 mg/l or

greater. Minimum oxygen values ranged from zero to 7.13 mg/l and had

a mean value of 2.05; 70 percent of the canals had minimum-oxygen values

below 4 mg/l. Regression equations for average and minimum dissolved

oxygen concentrations explained 91 and 88 percent, respectively, of the

observed variabilities.


xiii














CHAPTER 1
INTRODUCTION



Residential canals and canal construction in the coastal zone are

sensitive environmental and political issues in Florida and other

Atlantic and Gulf coast states. Land developers argue that they are

filling a need by providing the public with attractive waterfront

property. Environmentalists and regulatory agencies contend that the

loss of wetlands and shallow estuarine areas outweighs housing benefits.

Regional planners are in a dilemma because the principles governing the

behavior and conditions of canals in the coastal zone and the percentage

of the coastal wetlands that can be developed before the estuarine

systems suffer serious damage are unknown.

The conversion of wetlands (mangrove and salt marshes) and shallow

estuarine areas into waterfront developments via dredge and fill opera-

tions proceeded largely unchecked until the early 1970s. Following the

Earth Days of the late 1960s, the public became more environmentally

conscious and, therefore, more concerned about the destruction of

estuarine habitats. A widely circulated 1972 publication by Barada and

Partington, which portrayed residential canals as open sewers and as

sources of toxic materials to the adjoining estuaries, added impetus to

the movement against dredge and fill operations. In response to public

pressures, state legislators imposed a moratorium on dredge and fill

operations in Florida. The federal and state governments became

actively involved in attempts to curtail further dredging in the coastal









zone by strengthening the permitting requirements.

The development corporations were not prepared for the rather

sudden imposition of controls on their dredging plans. But, with their

businesses and livelihoods threatened, they resisted the controls by

litigation. In the courts, it became apparent that very little was

known about artificial canal systems and their impacts on the coastal

zone. The developers' lawyers were asking questions for which there

were no answers. Without facts to support their contentions, the

positions of state and federal agencies were weakened in the courts.

This study was initiated in response to the Florida Department of

Environmental Regulation's quest for more scientific facts. Data col-

lection occurred in two phases. The first phase was conducted as part

of a one year project (see Fox et al., 1976) funded by the Department

of Environmental Regulation. During the first phase, the metabolism

and canal-estuary nutrient exchange patterns of four pairs of similar

canals (Punta Gorda, Port Charlotte, Pompano Beach and Loxahatchee

River sites) were examined on four occasions in 1975. The second phase

of the study consisted of single sampling trips to eight additional

canal locations in 1976. The data from each phase and the combined

data provide different types of information.

The locations of the sampling sites covered most of Florida and

were approximately distributed in proportion to canal densities in

Florida. Most canal dredging has occurred in southern Florida, par-

ticularly along the southeast coast (Gold Coast). For example, the

City of Fort Lauderdale has over 150 miles of waterways. Extensive

dredging and filling has also taken place in the Tampa Bay area and,

more recently, along much of the southwest coast of Florida. The









varying densities of canal developments along Florida's coastline can

be seen in the sampling-site figures (Site Description).

A complete inventory of the number or acreage of Florida canal

developments has not been made. However, some reported figures will

illustrate the extent of this type of activity. Chesher (1974) estimated

that there were about 321 canals in the Florida Keys. Marshall (1968)

believes that 24000 ha or about 7 percent of Florida's estuarine habi-

tat less than 2 m deep has been filled by coastal developers. Castanza

and Brown (1975) found that 5,600 ha of mangroves (2.3 percent) in

south Florida (below Lake Okeechobee) have been developed since 1900.

Several classification schemes have been proposed to categorize or

distinguish the various types of dredged canals (or lagoons). Polis

(1974) distinguishes between dead-end canals and open-ended canals.

Within these two major categories, Polis classifies canals as "bay-fill"

or "upland" types; the former are created in shallow estuarine areas,

and the,latter, in upland areas. The presence of a sill at the canal

entrance is also thought by Polis to be a distinguishing feature.

Lindall and Trent (1975) classify canals as "bayfill, inland, and

intertidal"; the mean-low and mean-high tide marks separate the three

types of dredged areas. The Florida Department of Environmental

Regulation describes the extent of canal branching as first-order

canals, second-order canals, etc.

The canals examined during this study were mostly dead-ended

(exceptions are identified in Site Description section) and upland

(intertidal and inland).

This study was designed to increase the data base and the under-

standing of the role and behavior of Florida residential canals in the









coastal zone. The specific goals were to 1) evaluate the conditions

within canals, in terms of their metabolic levels and water qualities,

2) determine the magnitudes and direction of material exchanges across

canal entrances, 3) elucidate any recurring patterns or associations

between canals' behavioral and physical attributes, and 4) generate

and evaluate simple regression equations for the response variables

from relatively simple independent factors.

In order to achieve these objectives four types of data were col-

lected for each canal: 1) metabolism levels, 2) nutrient water quality

net-exchanges between the canals and adjacent estuaries, 3) several

basic water quality parameters, and 4) the canal and sampling day

physical characteristics. The metabolism and water quality data pro-

vide information on the conditions within the canals, whereas the

exchange data provide information on the nature of the canal-estuary

interactions.

Rather than intensively studying one or two canal systems over an

extended period, the strategy was to examine the short-term behavior of

a large number of canals around Florida. By sampling canals with wide

geographical distribution and varying physical attributes, the vari-

abilities of the response parameters were assessed for Florida resi-

dential canals. Once the variabilities of canal behavior and conditions

were known, then the degrees of interdependence among the response

parameters and the canal and sampling day characteristics, plus the

amounts of variability explained on the basis of canal physical attri-

butes, estuarine water quality, and local tidal dynamics, were evaluated

using standard statistical methods.

Multiple regression analysis was employed to determine quantitative


I









relationships among 20 response.parameters (metabolism, net-exchange,

and water quality) and their significant explanatory factors (canal

physical attributes, estuarine water quality, and local tidal dynamics).

The analysis did not provide the mechanistic relationships for the

response and explanatory variables but did, however, identify and

quantify the associations among the response parameters and the ex-

planatory factors. Since the regression equations have been derived

from data on existing canals, they constitute a foundation from which

future workers can develop canal design criteria, canal management

policies, and mechanistic theories for the controlling factors in

canals.

This study substantially increases the data base for the conditions

within Florida residential canals, provides heretofore lacking infor-

mation on the exchanges of materials between canals and estuaries, and

presents equations that can be cautiously used to estimate the condi-

tions and behavior of existing or future canal systems. It does not,

however, attempt a total evaluation of the ecological and socioeconomic

impacts of residential canals in the coastal zone.















CHAPTER 2
LITERATURE REVIEW



A review of the existing literature concerning dredged canals,

channels, and holes up to 1974 has been prepared by Polls (1974) under

a grant from the State of Maryland. His reviews that pertain to resi-

dential canals are described briefly below.

The work of Trent and associates (Moore and Trent, 1970; Corliss

and Trent, 1971; Trent et al., 1972) in West Bay, Texas includes

hydrographic, water quality, substrate, phytoplankton, benthic in-

vertebrate, oyster, fish, and crustacean data for canal, marsh, and

open bay stations. The canal stations were found to contain more silts

and clays than the marsh and bay stations. Turbidity was higher in the

bay than in the canals, but lower in the marsh than in the canal.

Benthic invertebrates, fish, and crustacean numbers were similar in the

marsh and canal, and tended to-be higher in the bay. Phytoplanktonic

primary production per unit surface area was greater in the canal than

in the marsh. A large standing crop of oysters was observed on the

bulkheads of the canal but growth and spatfall were reduced in the

canal relative to the marsh. Oyster mortality was greater in the canal

than in the marsh. Blue crabs and grass shrimp were more abundant in

the marsh than in the canal.

Taylor and Saloman (1968) examined the sediments, water quality,

and primary production of canals in Boca Ciega Bay, Florida. They found

dissolved oxygen levels of at least 3.5 ml/l (4.9 mg/l) at all times


I








and stations, lower turbidities in the canals than in the bay, and no

significant differences in phytoplankton primary production levels

between natural and dredged areas. Silts and clays predominated in

the canal sediments, as compared to sand and shell in the bay sediments.

Fewer species of fish were netted in the canals than in the bay (49

versus 80), but thirty percent more fish were caught in the canals.

Sykes and Hall (1970) sampled the mollusks of canals and natural

areas in Boca Ciega Bay, Florida, concomitantly with Taylor and Saloman.

Their results show a marked reduction in numbers of individuals and

species in the soft sediments of the canals as compared to those of

the bay.

Lindall, Hall and Saloman (1973) followed the fish populations of

a newly opened canal system off Tampa Bay, Florida. Only anchovies

(Anchoa mitchilli) were caught in the system three months after inunda-

tion, but during the following year 36 species were netted. Lindall

et al. thought that newer canals provide a more favorable habitat for

fishes than do older canals.

Barada and Partington's (1972) report on waterfront developments

in Florida, while supplying no new data on canals, was instrumental in

bringing the problem of canal dredging to the public's attention. Their

report, citing several of the above investigations, discusses the lack

of good circulation and flushing, excessive depths, stratification,

fish kills, odor, and bacterial problems of canals. An image of canals

as open sewers and as having detrimental effects on ground and surface

waters, was projected.

Godwin and Sholar (n.d.) found increased silt and clay fractions

and decreased benthic invertebrate diversities in dredged canal sediments,









relative to natural areas in North Carolina.

The work of Daiber et al. (1972, 1973) in Delaware provided at that

time the most comprehensive study of biological, chemical and physical

aspects of any canal system. Conditions were generally poorer in the

canals than in the adjacent natural salt marsh embayments, but the

uniqueness of each canal system was recognized. A dye flushing study

of one 800-meter canal showed that the initial surface concentration at

the dead-end was reduced by only 56 percent after five days, and that

the bottom water exchanged much more slowly.

Since Polis' review, several other studies have appeared. Chesher

(1974) reported biological and hydrological data on 50 canals in the

Florida Keys. Paulson et al. (1974, 1975) studied four canal systems

along the Gulf of Mexico. Nixon et al. (1973), in an ecological study,

compared a small boat marina with a natural marsh embayment in Rhode

Island. The Environmental Protection Agency (1973, 1975) has issued

preliminary reports on several canal systems in the Florida Keys,

Charlotte Harbor, Florida area, and North Carolina. Daiber et al.

(1974, 1975) have completed two more reports on Delaware canals. The

Marco Island, Florida project has been studied by a group from the

University of Miami (Van de Kreeke and Roessler, 1975a and b, and

Carpenter and Van de Kreeke, 1975) and by the Deltona Corporation

(1975). Adkins and Bowman (1976) have prepared an informative document

on the canals dredged for oil drilling rigs in Louisiana. Burk and

Associates, Inc. (1975) examined the condition of a residential canal

development in Louisiana, and evaluated several developments in Florida

in an attempt to forecast water quality in the Louisiana development.

Thurlow (1974) did research on the water quality and sediment





-9-


characteristics of four New Jersey canal developments. Substantial

data on four pairs of canals in Florida have been reported by Fox et al.

(1976) and by Piccolo et al. (1976).

Chesher (1974) discusses his physical, chemical, geological, and

biological work on 50 canals in the Florida Keys, and finds the canals

generally to be in good condition. Canal orientation to the wind and

the substrate type were found to be the most important factors affecting

canal water quality. Chesher feels that the advantages of such systems

outweigh the disadvantages to the productivity and economy of the Keys.

Paulson et al. (1974) report physical, hydrological, phytoplankton,

benthic fauna, and sediment composition data for single collections in

two canal systems in Florida and two in Texas. They believe that the

lower dissolved oxygen concentrations at the dead-end stations might be

alleviated by restricting the depths of the canals and eliminating

dead ends. Paulson's 1975 report includes physical, biological, and

chemical data for a canal system and a natural bayou in southern

Mississippi. They found essentially no differences in flushing rates

and biota between the two systems. However, dissolved oxygen values

tended to decrease and coliform levels tended in increase toward the

dead end of the canal. The canal was shallower than the adjacent water

body.

Nixon et al. (1973) evaluated the production, metabolism, suspended

material, dissolved organic, nutrients, phytoplankton,.bacteria, fish,

fouling communities, and sediments of a small boat marina and a natural

marsh embayment in Rhode Island. The two types of systems were similar

and were felt to be compatible coastal systems in Rhode Island. The

authors regarded the fouling communities of the bulkheads, pilings, and





-10-


boats as an important food source for juvenile fish populations and

which may serve the same detritus-producing role as do the marsh grass

in the natural marsh embayment. The fouling communities reached a

maximum biomass of 5,000 g/m2, about five times the standing crop of

marsh grass. The respiration rate of the fouling communities was quite

high (mean = 1.80 g 02/m2-hr) with no net production and was about 20

times the oxygen demand of the-sediments.

The preliminary E.P.A. (1973, 1975) reports represent the most

exhaustive sampling sessions on selected canals in Florida and North

Carolina. Impressive amounts of water quality, sediment, microbial,

hydrodynamic, mass transport, and biological data were collected twice

for two pairs of canals near Punta Gorda and Big Pine Key, Florida, and

once at sites in Marathon, Florida, Panama City, Florida, and Atlantic

Beach, North Carolina. Their preliminary but unofficial recommendations

were to restrict canal depths to 4-to 6 feet, to centralize the waste

treatment facilities of the development and discharge the effluent at

points remote from the canals, to have the developer provide sufficient

bonding to correct any water quality violations in the canals or to

isolate the canals from receiving waters, to design developments so

that stormwater runoff does not enter the waterways, to avoid sills at

the canal mouths, and to require an assessment of a proposed canal

development's impact on any local shallow freshwater aquifers.

Daiber et al. (1974) expanded on their earlier work and presented

seasonal data on seven canal systems in Delaware. Hydrological,

coliform, BOD, fish and benthic invertebrate results are reported along

with more flushing characteristics and a simple tidal excursion model

for transport within a canal. They concluded that the flushing rates






-11-


and general ecological condition of the canals are dependent on the

adjacent water body. It is difficult to obtain healthy canals on a

stressed bay.

Daiber et al. (1975) reported additional benthic invertebrate data

from the Little Bays area of Delaware, in addition to intertidal inver-

tebrates and vegetation, and ichthyoplankton results. The numbers of

individuals and species of benthic invertebrates were generally lower

in canal stations than in marsh and bay stations during the summer and

fall. However, the uniqueness of each canal system and its environ-

mental conditions was again emphasized. The three habitats were found

to have similar fauna during the winter and spring. Biomass comparisons

between different types of canal shorelines indicated that old bulkheads

have higher standing crops of plants and animals than do bare banks.

The old bulkheads had fewer macrophytic plants, but higher animal biomass

than did the salt marsh environment. The ichthyoplankton data, though

limited, suggested that canals are not as favorable a habitat for larval

fish as is the salt marsh.

The information reported by the University of Miami group

(Carpenter and Van de Kreeke, 1975 and Van de Kreeke and Roessler,

1975a and b) on the Marco Island, Florida development consists of

oxygen data, estimates of production and respiration, and a model to

predict oxygen levels. Their model was developed for the main flow-

through arterial channels fifteen feet in depth. The model revealed

that dissolved oxygen concentrations for Marco Island canals are sig-

nificantly dependent on the vertical mixing coefficient and the detritus-

supported respiration, and not sensitive to atmospheric transfer,

photosynthesis and respiration. For the dead-end tributary canals,





-12-


wind induced motion and diurnal density induced motion were thought to

be important factors affecting dissolved oxygen distribution.

Adkins and Bowman (1976) provide an informative review of the

impact of canal dredging in the coastal zone, as well as the results of

a two year study on canals dredged in Louisiana marshland for oil

drilling rigs. Fish, blue crab, shrimp, water chemistry, and sedi-

mentology data were presented for open, semi-open, and closed canals,

and for unaltered areas. The greatest number of animals were found in

the unaltered areas. Dissolved oxygen levels remained within tolerance

limits of marine organisms during most of the study, though fish kills

were observed in the semi-open and closed canals (one each).

Burk and Associates (1975) conducted a one day study of water

quality and biota at five stations within a 5,300 acre development off

Lake Pontchartrain, Louisiana. By evaluating the conditions of five

Florida canal developments and reviewing canal literature, Burk and

Associates made several recommendations for improving the future water

quality in the Louisiana development. Recommendations to improve flush-

ing and water circulation in the existing canals were to create flow-

through systems via culverts and saltwater wells, and to install bottom

aerators or air injection systems. Design criteria for new canals in

the area were to limit canal depths to 6 to 8 feet and canal lengths to

800 feet, to provide sloping sides and smooth bottoms in the canals, to

allow canals to be as wide as possible, and to align the canals with

the prevailing winds. Other recommendations included the construction

of grassy swales in the development, the establishment of natural

vegetation buffer zones between homes and canals,.and the spray-

irrigation of the sewage treatment plant effluent onto the local golf

course.





-13-


Thurlow (1974) examined the water quality and sediment character-

istics of four canal developments in New Jersey. He concluded that each

canal system was unique and that depth had a major influence on water

quality, particularly on the bottom water quality. Canals with sills

were "more polluted" at points remote from the entrances. Accumulations

of nutrients and heavy metals plus.anaerobic conditions were observed

in excessively deep areas. Water quality was similar in old and new

canals, even though the new canals were deeper. Canal developments

with homes utilizing septic tanks had better water quality than those

with a sewage treatment plant whose effluent was discharged into the

canals. The water quality was best in the canal system that had a

sewage treatment plant and a remote discharge point. Thurlow recommended

canal depths of 8 to 10 feet, maintenance dredging of sills, sewered

developments with remote discharge points, and the reductions of organic

inputs to the canals, in the use of lawn fertilizers, and in the sub-

stitution of stones for lawns.

Two groups of investigators at the University of Florida (Piccolo

et al., 1976 and Fox et al., 1976) jointly examined four pairs of

similar canals at different locations in Florida, on a seasonal basis.

Piccolo et al. provided the hydrography of the canals and a pollutant

dispersion model. Fox et al. reported the water and sediment chemistry,

the metabolism levels, the phytoplankton and benthic invertebrate

populations, the canal-estuary net nutrient exchanges, the benthic

oxygen demand, and the hydrocarbon levels of the canals. They concluded

that canals constitute complex and variable systems. The individual

canals within the essentially identical canal pairs (directly adjacent)

often had dissimilar attributes. Not all canals had poor water quality.





-14-


The factors responsible for the differences in water qualities were

not clear. Rankings of the canal water qualities did not simply reflect

differences in a single factor such as canal depth, age, flushing rates,

or local estuarine water quality.

No clear consensus exists in the literature for the most important

factor affecting water quality in residential canals. Excessive depths

and poor circulation and flushing are most frequently thought to lead

to poor conditions. The dead-end nature of the canals and sill forma-

tion at the canal entrances are not conducive to good mixing and flush-

ing. Local tidal dynamics and their influences on canal flushing rates

are considered important by several investigators. The water quality

of the adjoining water bodies, while not frequently mentioned by

investigators working in single locations, undoubtedly affects the

canals. In addition to canal depth, other canal characteristics such

as length, width, configuration, bottom topography, orientation to the

wind, and substrate type, are often identified as important factors.

Allochthonous sources of organic and inorganic materials and their

management, appear to be significant in some canal systems.

Many aspects of the impact of canal dredging on the coastal zone

have been discussed by the investigators cited above. Reviews of the

subject can be found in Lindall and Trent (1975), Adkins and Bowman

(1976), and Odum (1970). Possible impacts of canal dredging in the

coastal zone given by these authors and their referenced literature,

include:

1. Destruction and loss of nursery areas for coastal fisheries.

2. Biological productivity losses of dredged areas. Taylor and

Saloman (1968) estimate that $1.4 million of annual revenue is






-15-


lost from Boca Ciega Bay, Florida as a result of dredging and

filling. Douglas and Stroud (1971) concluded that 535 pounds

of fish products from the continental shelf are lost per acre

of estuary that is obliterated; Gosselink et al. (1974) value

the non-competing uses of marshland at $4,000 per acre per

year.

3. Changes in upland drainage patterns.

4. Changes in water depths and substrate types of dredged areas.

5. Harmful silt release during dredging operations and after

canal completion via resuspension.

6. Alteration of the local water currents and circulation patterns.

7. Estuarine detritus retained by canals.

8. Low dissolved oxygen concentrations and unfavorable conditions

in the canals and the resultant effects on estuarine organisms

entering the canals.

9. Possible spill-over of accumulated sludge and poisonous wastes

from canals to estuaries (Barada and Partington, 1972).

10. Saltwater intrusion into shallow freshwater aquifers and

former freshwater areas.

11. Deleterious effects of an active dredging operation on local

residents and wildlife.














CHAPTER 3
SITE DESCRIPTIONS



Thirty-three canals at twelve locations throughout the State of

Florida (Figure 1) were sampled over a twenty month period. The indi-

vidual canals and sampling stations are shown in Figures 2 through 13.

Several canals were sampled more than once, resulting in a total of

sixty-one canal observations. In addition, data for thirteen canals

were obtained from the Environmental Protection Agency and have been

included in some analyses.

Canal geometries (length, width, mean depth, water surface area,

water volume, sill height), canal age, percent of shoreline bulkheaded,

canal water minimum residence time, and some of the canal development's

attributes (presence or absence of curbed streets and sewer systems,

percent development) are shown in Table 1 for each canal observation.

The levels of solar insolation, tidal ranges, and cumulated tidal

amplitudes on the sampling days are also given in Table 1. Additional

information and distinguishing features of each canal site are given

below.

Punta Gorda (PG. Figure 2). The three canals at this location

are part of the Punta Gorda Isles development. The developer made an

effort to design this rather new canal system so that circulation and

flushing were maximized by dredging to uniform depths and leaving

sloping banks. Management of the canal system includes regulations

against the discharge of grass clippings and fish heads into the canals.


-16-






-17-


Figure 1. Sampling sites within Florida.
















Table 1. Canal and sampling day physical characteristics.

Units: LENGTH, WIDTH, MDEPTH, SILL, TIDE, CUMTIDE -- meters
AREA -- square meters
VOLUME -- cubic meters
DEVEL, AGE -- percent
AGE -- YEARS
CURBS, SEWERS -- 1 present, 0 absent
MINRES (Minimum residence time) -- days
SUN -- langleys/day
DAYL (Daylength) -- hours

See Table 2 for more complete identification of the parameters.









OBS CANAL MONTH DAY YEAR LENGTH WIDTH MDEPTH


PG6
PG3
PC3
PC6
P83
P86
LX3
LX6
PG6
PG3
PC3
PC6
PB3
PB6
LX6
L X3
PG3
PG6
PG9


747
652
b75
018
732
732
631
521
747
652
575
618
732
732
521
631
652
747
3650


2.8
2.2
3.2
2.7
3. C
3.2
1.8
1 6
2.8
2.2
3.2
2.7
3.0
3.2
1.6
1.8
2.2
2.8
3.0


22400
19000
19000
20400
16800
15400
13900
8860
22400
18300
19000
20400
16800
15400
8860
13900
18300
22400
480000


62700
60700
60700
55100
50500
49200
25000
14200
62700
40200
60700
55100
50500
49200
14200
25000
40200
62700
1440000


0.0
0.2
1.1
0.8
1.1
0.8
0.6
1.2
0.2
0.0
0.5
0.8
1.1
0.8
1.2
0.6
0.2
0.0
0.0


08S DEVEL AGE BULK CURbS SEWERS


30
50
100
100
100
98
0
0
30
50
100
100
100
98
0
0
50
30
50


100
100
100
100
100
100
80
0
100
100
100
100
100
100
0
80
100
100
100


MINRES TIDE CUMTIDE SUN DAYL


2.9
2.7
5.0
4.0
2.0
2.1
1.2
1.2
3.6
2.9
4,2
3.6
1.8
1.9
1.4
1.4
2.2
2.7
2.7


0.58
0 58
0.58
0.58
1. 10
1 10
0.70
0.70
0.55
0.55
0C73
0.73
1.01
1.01
0.52
0.52
0.64
0.64
0,64


0.83
0.83
0.77
0.77
2. 14
7. 14
1.15
1.15
0 74
0.74
0.83
0.83
1.77
1.77
1.24
1. 24
1.10
1.10
1. 10


602
602
642
642
488
488
434
434
650
650
676
676
342
342
378
378
426
426
*


12.0
12.0
12.0
12.0
12.0
12.0
12.0
12.0
13.5
13.5
13.5
13.5
13.5
13.5
13.5
13.5
12.3
12.3
12.3


AREA VOLUME SILL








OBS CANAL MONTH DAY YEAR LENGTH WIDTH MDEPTH AREA VOLUME SILL


Table 1. (Continued)


20 PC3 9
21 PC6 9
22 PC9 9
23 P83 9
24 PB6 9
25 LX3 9
26 LX6 9
27 PG6 11
28 PG3 11
29 PG9 11
30 PC3 11
31 PC6 11
32 PC9 11
33 P86 11
34 P9 11
35 P83 11
36 LX3 11
37 LX6 11
38 MIl 3

OBS DEVEL AGE

20 100 16
21 100 16
22 75 14
23 10C 23
24 98 23
25 0 16
26 0 16
27 30 9
28 5C 9
29 50 11
30 100 16
31 100 16
32 75 14
33 98 23
34 100 20
35 100 23
36 0 16
37 0 16
38 50 10


9 75
9 75
9 75
7 75
7 75
12 75
12 75
21 75
21 75
21 75
23 75
23 75
23 75
14 75
14 75
14 75
16 75
16 75
24 76


575 33
618 33
1350 30
732 23
732 21
631 22
521 17
747 30
652 28
3650 30
575 33
618 33
1350 30
732 21
738 23
732 23
631 22
521 17
2837 30


BULK CUR6S SEwERS

100 0 1
100 0 1
90 0 1
100 0 0
100 0 0
80 0 0
0 0 0
100 0 1
100 0 1
100 0 1
100 0 1
100 0 1
90 0 1
100 0 0
100 0 0
100 0 0
80 0 0
0 0 0
100 0 1


3.2
2.7
2.5
3.0
3.2
1.8
1.6
2.8
2.2
3.0
3.2
2.7
2.5
3.2
2.5
3.0
1.8
1.6
2.7


19000 60700 0.5
20400 55100 0.8
182000 455000 1.5
16800 50500 1.1
15400 492C0 0.8
13900 25000 0.6
8860 14200 1.2
22400 62700 0.0
18300 40200 0.2
480000 1440000 0.0
19000 60700 0.5
20400 55100 0.8
182000 455000 1.5
15400 49200 0.8
70000 175000 1.0
16800 505C0 1.1
13900 25000 0.6
8860 14200 1.2
312000 842000 0.0


MINRES TIDE CUMTIDE SUN DAYL


4.4 0.57
3.8 C.57
3.1 0.57
1.8 0.98
2.0 0.98
1.5 0.64
1.6 0.64
2.5 0.74
1.9 0.74
2.9 0.74
3.6 0.80
2.9 0.80
3.0 0.80
2.4 0.73
2.1 0.73
2.3 0.73
1.2 0.63
1.2 0.63
3.3 0.67


0.81
0.81
0.81
1.67
1.67
Is 14
1.02
1* 02
1.02
1.02
0.83
0.83
0.83
1.17
1.17
1.17
1.37
1.37
0.81


446 12.3
446 12.3
23 12.3
238 12.3
238 12.3
296 12.3
296 12.3
296 11.0
296 11.0
1.0
334 11.0
334 11.0
11.0
352 11.0
11.0
352 12.3
204 11.0
204 11.0
520 12.0









08S CANAL MONTH DAY YEAR LENGTH WIDTH MDEPTH AREA VOLUME SILL


Table 1. (Continued)


MI2
MI3
8C1
8C2
BC3
HI I
HI2
HI3
FL1
FL 2
FL3
API
AP2
AP3
G81
GB2
GB3
KC1
KC2


OBS DEVEL AGE BULK CURdS SEWERS


3 24
3 24
4 20
4 20
4 20
5 19
5 19
5 19
6 12
6 12
6 12
7 14
7 14
7 14
7 31
7 31
7 31
8 18
8 18


76 397 30
76 040 30
76 1320 53
76 984 48
76 1310 30
76 3370 30
76 3370 30
76 690 30
76 520 21
76 450 24
76 800 24
76 3910 46
76 1140 52
76 2710 38
76 264 25
76 173 25
76 427 20
76 730 29
76 730 29


MINRES TIDE CUMTIDE SUN DAYL


0.67 0.81
0.67 0.81
0.67 0.67
0.67 0.67
0.67 0.67
0.82 1. 50
0.82 1.50
0.82 1.50
0.31 0.47
0.31 0.47
0.31 0. 47
0.72 0.95
0.72 0.95
0.72 0.95
0.21 0.30
0.21 0.30
0.21 0.30
0.41 0.59
0.41 0.59


520 12 0
520 12.0
571 12.5
571 12.5
571 12.5
515 13.0
515 13.0
515 13.0
504 13.5
504 13.5
504 13.5
506 13.5
506 13.5
506 13.5
554 13.5
554 13.5
554 13.5
72 13.0
72 13.0


2.6
2.7
4.0
3.0
4.0
1.5
2.0
2.9
2.8
3.1
4.9
2.6
2.7
2.0
1.1
1.7
1.2
3.8
4.1


12700 33000 0.5
41100 111000 0.0
184000 736000 1.1
46800 140000 2.3
122000 488000 1.4
385000 577000 0.0
385000 770000 0.0
36000 1040CO 0.8
11000 30800 0.9
11000 34100 1.4
50000 145000 1.2
402000 1040000 2.7
56000 151000 1.5
238000 476000 0.
9200 10000 0.6
4300 7300 1.2
22000 26000 0.3
21200 80400 2.1
21200 86900 0.3


25
10
75
100
100
100
100
100
20
40
80
50
10
45
60
80
30
50
80


7 100
8 100
20 100
20 100
20 100
18 100
18 100
18 100
11 20
15 40
20 50
19 75
i9 10
19 50
7 10
15 100
5 5
16 50
16 80


3.2
3.3
6.0
4.5
6.0
1.0
1.3
1.9
9.0
10.0
9.4
2.7
2.8
2.1
3.7
5.7
4.0
6.4
6.9









OBS CANAL MONTH DAY YEAR LENGTH WIDTH DEPTH AREA VOLUME SILL


Table 1. (Continued)


KC3
NMI
NM2
NM3
PE1
PE2
BP3
8P4
SA8
A83
A65
MIH
MIJ
MIL
MIM
MIM
MIN


18 76
26 76
27 76
28 76
14 74
14 74
19 74
19 74
23 74
17 74
17 74
8 75
10 75
6 75
6 75
8 75
7 75


08S OEVEL AGE BULK CURBS SEWERS

58 20 16 40 0 1
59 50 20 50 0 1
60 50 20 50 0 1
61 50 20 50 0 1
62 0 19 0 0
63 30 19 0 0
64 0 15 0 0
65 30 15 0 0
66 0 0 0
67 75 0 0
68 40 0 0
69 80 10 100 0 1
70 10 100 0 1
71 10 100 0 1
72 50 10 100 0 1
73 50 10 100 0 1
74 8 80 0 1


730 29
624 31
624 31
624 31
762 30
610 25
457 12
163 9
873 26
671 43
488 30
1267 30
458 30
660 30
2837 30
2837 30
4463 30


3.9
6.2
6.2
6.2
2.1
2.1
2.7
2.4
5.4
3.3
3.6
3.1
2.0
3.4
2.7
2.7
2.2


MINRES TIDE CUMTIDE SUN DAYL


6.6
7.8
8.7
8.7
2.6
2.6
3.9
3.5
11.5
2.2
2.4
1.7
1.3
2.1
3.3
3.3
1.2


0.41 0.59
0.80 1.42
0.71 1.36
0.71 1.23
0. 70 0. 80
0.70 0.80
0.31 0.69
0.31 0.69
0.31 0.47
0.91 1.52
0.91 1.52
1 08 1.81
0.82 1.49
1.02 1.61
1.02 1.62
0.95 1.62
1.03 1.79


72 13.0
316 11.5
346 11.5
183 11.5
13.0
& 13.0
13.0
S 13.0
13.0
12.3
S 12.3
13.0
S 13.0
S13.0
13.0
S13.0
S 13.0


21200 82700 0.8
38500 238000 2.9
38500 238000 2.9
38500 238000 2.9
22900 48000 1.2
15200 32000 0.6
5480 15000 0.0
1650 3950 0.0
52400 263000 3.1
28900 95200 1.2
14600 52700 0.6
120000 373000
13800 27600
63000 214000
312000 842000 0.0
312000 842000 0.0
613000 1350000






-23-


Canals and sampling stations at the Punta Gorda site.


Figure 2.






-24-


Floating debris is regularly removed from the canals. Limited boating

activity was observed. Canals 3 and 6 were sampled four times during

1975, while Canal 9 was sampled twice. Local tidal dynamics are quite

irregular in amplitude and frequency. The adjoining Peace River has high

phosphorus levels as a result of phosphate mines in its drainage basin,

and experiences lowered salinities during the rainy summer season.

Port Charlotte (PC. Figure 3). The three canals in the Port

Charlotte development are across the Peace River estuary from the Punta

Gorda canals, but are older and more developed than Punta Gorda Isles.

A sand bar (exposed at low tides) separates the dredged channel along

the development from the river. Southerly winds in the spring and

summer tend to hold floating debris in the canals. A secondary sewage

treatment plant in Port Charlotte enters the end of a 4,000-foot canal

whose entrance to the Peace River is approximately 2,000 feet east of

the canals. Canals 3 and 6 were sampled four times during 1975. Canal

9 was sampled twice.

Pompano Beach (PB. Figure 4). The three canals sampled at the

Pompano Beach location are representative of many canals in that area.

Extending off the Intracoastal Waterway, the canals are old, narrow,

and completely developed with homes using septic tanks (until 1975).

Considerable boating activity exists along the Intracoastal Waterway

and within the canals. Tides in the area are uniform and semi-diurnal.

The nearest oceanic inlet (Hillsboro Inlet) is approximately six

kilometers north.

Loxahatchee River (LX. Figure 5). Dredged and abandoned about

1960, the two canals at this site are approximately seven kilometers

up the Loxahatchee River from Jupiter Inlet. One of the canals (LX3)





-25-


:-I .Ii ,: ^] -'"

j2 l . *:'.. .... ..

22 ../ 23

S )rt Charlot e .








2 26 _
I s *

SScal .e i


'c
Figure 3. Canals and sampling stations at the Port Charlotte site.
A . .







I Point'',
... ..






S- PC 9 PC --6 PC3









500 m









Figure 3. Canals and sampling stations at the Port Charlotte site.






-26-


Figure 4. Canals and sampling stations at the Pompano Beach site.






-27-


Canals and sampling stations at the Loxahatchee River site.


Figure 5.





-28-


has concrete bulkheading, while the other (LX6) has sloping sides up to

the dredge spoils on one side and to a mangrove community on theother

side. The unbulkheaded canal has a landfill site at the dead end. The

Loxahatchee River in this vicinity is about one meter deep, is lined

with mangrove trees, experiences uniform semi-diurnal tides, and'is

strongly influenced by freshwater inputs during the wet season.

Marco Island (MI. Figure 6). This large and complex development,

constructed by the Deltona Corporation, is an island separated from the

mainland by the Marco River. Canal MI1 is large, extensively branched,

and borders a golf course that is spray-irrigated with the development's

sewage treatment plant effluent. The MI3 canal had received maintenance

dredging the year prior to sampling, as part of a canal design experi-

ment by the Marco Island Applied Marine Ecology Station. At the time

,of sampling (March) the water in the area was more turbid than during

most of the year due to strong westerly winds that kept the Gulf .of

Mexico turbulent. Some of the Environmental Protection Agency's data

from Marco Island has been incorporated into this study (canals MIH,

MIJ, MIL, MIM, MIN).

Boca Ciega Bay (BC. Figure 7). Located in the southeast section

of Boca Ciega Bay, this site was the only one that had curbed streets

in the development. The stormwater enters directly into the canals via

drain pipes. A large boat marina operates at the end of BC3 canal

(station BC32). Westerly winds from the Gulf of Mexico during the

spring and summer afternoons keep Boca Ciega Bay and the canal entrances

turbulent. Tides in the area have irregular amplitudes and frequencies.

On the sampling day the tidal cycle was diurnal, i.e., one high slack

and one low slack tide in 24 hours.






-29-


Figure 6. Canals and sampling stations at the Marco Island site.




-30-


Pier


CANALS


BC1-

BC 2-

:BC 3-


IC '


I -


Scale
1:24000


500 m
t-. I


Figure 7. Canals and sampling stations at the Boca Ciega Bay site.


''





-31-


Hillsboro Inlet (HI. Figure 8). The three canals sampled near

Hillsboro Inlet are part of Lighthouse Point Township. Canals HI1 and

.HI2 form a single complex canal system with two entrances. Both the

HI2 and HI3 canal entrances are approximately 500 meters from the

Hillsboro Inlet. Yet, the influence of the oceanic inlet is quite dif-

ferent for each canal. More of the ocean water that passed through the

inlet during flood tide seemed to be flowing north, rather than south

along the Intracoastal Waterway, during the sampling period. As a

result the turbidity and color at the HI2 canal entrance was noticably

less than at the HI3 entrance. Different volumes of freshwater flow

into the respective Intracoastal Waterway sections from upland drainage

were assumed to be affecting the movement of the seawater entering the

inlet. Boat traffic along the Intracoastal Waterway results in much

wave activity at the canal entrances. The large homes in the develop-

ment tend to shelter the canal branches from the wind. A sewer system

was installed in the development during the year prior to sampling.

Flagler Beach (FL. Figure 9). The three canals sampled at Flagler

Beach extend off the Intracoastal Waterway about 15 kilometers south of

Matanzas Inlet. This section of Florida's coastline is not extensively

developed. Mangroves and marshland surround most of the Intracoastal

Waterway in the area. The water was quite colored (ca. 200 cpu) at the

time of sampling, and did not have much tidal activity.

Apollo Beach (AP. Figure 10). The Apollo Beach development,

located on the eastern shore of Tampa Bay, is approximately 10 kilo-

meters from a phosphate processing plant. One large canal was

sampled as three canal observations. Canal API was taken as the

entire canal. Canals AP2 and AP3 were the major branches of the system.






-32-


-Scale

1:24000

500 m
t- -


8


Figure 8. Canals and sampling stations at the Hillsboro Inlet site.





-33-


\ -,, .
-- -- - -- --._ .-- .- - -
'.VJV........ -.................. ........ .. :

ATL.
'2 ... . 5, ', i' x ,V', \\ O n





'" '219
,' . :"' : \ ., -.. \ 1 .\

I '," Iv ,, ' . :\ \

IFL
.. .. C.I A L 2"
7Z\IBM


S0 *, .* i
o.... :, "




S ..



I
1


Scale
1:24000


J ...' ,,o o, \ .
FL 3




1,8MI ,



S, Flagler Beach
I-




] "" 'V '"


' .I ' \ \ (
, ,, ,,-
.. .- .' I ', ..







^ 'B. -
S -- ----0

", ,K,. \ \ '13 K
14 \








'2


Figure 9. Canals and sampling stations at the Flagler Beach site.


ANTIC


SN\
1M


-N


tI


\BM
i'











**,
!\
.-.A
.. '*'>~



'' '
*...
\
.







)





,/'
/;-






i//.
/j


---


'Ei






-34-





-35-


A shallow culvert connects sections of AP2 and AP3, but the interaction

between the two canals is limited to the surface water. The canal

system was dredged in a former mangrove community, had several deep

holes, and had varying widths. Onshore winds were strong (ca. 20 mph)

throughout the sampling period.

Goose Bayou (GB. Figure 11). The three canals sampled on Upper

Goose Bayou, located off North Bay near Panama City, were the most

recently dredged of the canals examined. These canals were also

shallowest and experienced the least tidal fluctuations. Marshland

and sparsely populated shorelines predominate in this estuary.

Key Colony (KC. Figure 12). The three canals in Key Colony

Beach are located on Fat Deer Key, about midway down the Florida Keys.

The substrate is limestone and fossilized sand. A sewer system serves

the development. However, the outfall from the treatment plant enters

an embayment about 400 meters north of canal KC1. A tropical depres-

sion with high winds, heavy rains, and little solar insolation, was

over the area during the sampling period, making conditions rather

uncharacteristic of the Keys.

North Miami (NM. Figure 13).' One branched canal in North Miami

Beach was sampled for three consecutive days. Each 24 hour period was

considered a canal observation. This canal was the deepest (6 m) of the

canals examined. An anoxic water layer existed below the two meter

depth throughout the three days. A cold weather front came through the

area during the sampling period, bringing cloudiness, shifting winds,

and rain. The development and the adjacent Maule Lake were mangrove

communities before dredging and filling.





-36-


Little Oyster Bar Point .- '
/4 I I :
SI - .Light.
\. Light .. '0 '

', '' U S MILITARYm RESERVATION /-
r-. V -',-- ---i- -- 1J
7 "


GB 1
.* -i" :. ",,
CANALS GB 2
GB3


"*, +- - i f

-- -- -



City) site.
'.- 17 \ _
/7 / .i- % '--. -- '
, . - '-*. .- Ii


\ ^ --<, ---J-: '* '-- .--- --7 .,- --- ----- -
SGoose Island' -- '"-

Go Scale" "'... ,- - -"



1 : 24000 F'. rNNU' Nt J-, R po -- ... -.O
** ^ --^ ^^ 1" //-- -^


i ^ ,\"< .:' *r/h 9i / - 2 --, +



I 500 m I "> "-" "^ "




Figure 11. Canals and sampling stations at the Goose Bayou (Panama
City) site.






-37-


9


.1


I \
1\




Scale

1:24000


500 m


Figure 12. Canals and sampling stations at the Key Colony site.


(l~






-38-


I'"



It -...-r I uzzZZZIL



itli


-.-- '"'



\h I




Ala u~Lae drrey`
/ ..(- I


Light l


4,\


CANAL NM 1,2,3 ...

[ East" I,,
3reynolds. \ *--- \\\
Fark, .. .. ,;'* : -".




S NORTIP MIAMI BEACH

:. : i (part of) '
,,. -: ,. .


\ I ,'* :-- : i .




\ \ .- 1 .


Scale

1:24000


500 m I
I I 'j--


Figure 13. Canals'and sampling stations at the North Miami site.


[i..
* -.? *C*


__


II


s-:

"~~ "' "~"
::





-39-


Environmental Protection Agency Data. Observations 62-74 were

obtained from the Environmental Protection Agency. Descriptions of

their Punta Gorda (PG), Big Pine Key (BP), Marathon (SA), and Atlantic

Beach, North Carolina (AB) canal studies can be found in their report

(E.P.A., 1975). Their Marco Island data (MIH, MIJ, MIL, MIM, MIN) has

not been published.















CHAPTER 4
MATERIALS AND METHODS



Metabolism


The oxygen metabolism rates for the total canal communities and

the planktonic components were determined for each canal, except Punta

Gorda 9, Port Charlotte 9, and Pompano Beach 9.

Community metabolism was estimated by the free-water diurnal oxygen

method (Odum and Hoskins, 1958, see also Slack et al., 1973 for a

detailed outline). This technique assumes that the dissolved oxygen

change from sunrise to sunset in a volume of water can be attributed to

either net oxygen production of the biotic community in contact with the

water, or to oxygen diffusion across the air-water interface. Similar-

ly, any change in dissolved oxygen levels from sunset to sunrise is

assumed to be due to either community respiration or to diffusion. By

neglecting or adjusting for oxygen diffusion, estimates of daytime net

production and nighttime respiration are obtained. By further assuming

that the daytime respiration rate equals the nighttime respiration rate,

the total gross primary production and respiration levels for a 24 hour

period can be calculated.

For the first two sampling trips in 1975 (March and June), dis-

solved oxygen profiles were taken every three hours for 24 hours at

four stations along each canal (32 stations on 8 canals). Oxygen values

were determined by Winkler titrations. Mean values for the water column


-40-






-41-


at each sampling interval were used to compute the community metabolism.

Oxygen stratification generally was present. Oxygen diffusion across

the air-water interface was neglected, since the mean values for the

water column and not the surface values were used in the computations.

Ignoring diffusion leads to underestimates of metabolism, but was not

felt to be a serious source of error due to the generally quiescent

nature of the canal water.

After the first two sampling trips, oxygen profiles were taken at

every station for a sunrise-sunset-sunrise or a sunset-sunrise-sunset

sequence. The resulting three mean values for the water columns were

used to compute the daytime net production rates and the nighttime

respiration rates. The total community gross primary production and

total respiration were estimated on an areal (m 2) basis from the two

rates, allowing for daylength on the sampling day and for water depth.

The planktonic contribution to the total community oxygen metabolism

was determined by light-dark bottle 24 hour in situ incubations at one

or more stations per canal. Pairs of light and dark bottles were sus-

pended at one meter intervals throughout the water column. The changes

in dissolved oxygen levels were determined by Winkler titrations. To

obtain metabolism estimates on an areal (m 2) basis, the values at the

discrete depths were integrated over the depth of the water column.

The production:respiration ratios for the total community and

plankton component were calculated from the respective 24 hour gross

primary production and respiration values (m 2). The extent of plankton

dominance of the community primary production was calculated as the

ratio of the plankton GPP to the community gross primary production

values (canal means). The amount of solar insolation on the sampling





-42-


days was measured with a Belfort pyrheliometer.



Nutrient Exchange and Water Quality


The net exchanges of total carbon, inorganic carbon, total organic

carbon, total phosphorus, ortho-phosphorus, total organic phosphorus,

ammonia, turbidity, color, and conductivity across the canal entrances

were estimated by determining the total mass of each material entering

and leaving the canals during 24 hour periods. The concentrations/

values of these parameters were measured in surface water samples taken

periodically at the canal entrances. The volume and direction of water

flow across the canal mouths were determined from a recording tide

gauge and the canal water surface area. By summing the products of

the concentrations and volumes of flow for each sampling interval, the

total mass exchange for each material and each tidal phase was obtained.

Since the ebb and flood tidal phase volumes were not always equal, the

total mass exchange for each tidal phase was divided by the respective

total flow volume, to obtain weighted-average concentrations of each

material. The difference between the weighted-average concentrations

(flood-ebb) yield the net exchanges in concentration units. The mass

exchange values are not shown in the Results section but can be obtained

for each material by multiplying the weighted-average exchange concen-

trations (Table 7) by the canal surface area (AREA) and the cumulated

24 hr tidal range (CUMTIDE) in Table 1.

Several assumptions were included in this approach to estimating

net exchanges. The water samples collected and the concentrations

measured were assumed to represent the average concentrations of the

water transported during the sampling intervals. The water surface was





-43-


assumed to have zero slope and have constant area, so that changes in

water level were proportional to the flow volumes.

During the first two sampling periods at the Punta Gorda, Port

Charlotte, Pompano Beach, and Loxahatchee River canals, surface and two

meter depth water samples were taken from the center of the canal

entrance (ca. 50 meters inside). For the remaining exchange observa-

tions, hourly surface water samples were taken near the canal shoreline

by Serco Model NW3-8 Automatic Samplers. All water samples were

preserved with a solution of saturated mercuric chloride (1 ml/1) and

kept on ice until returned to the laboratory for analysis.

Total carbon and total inorganic carbon concentrations were deter-

mined with a Beckman Model 915 Total Carbon Analyser. Total organic

carbon concentrations were then determined by subtracting the inorganic

carbon concentrations from the total carbon concentrations. Total

phosphorus concentrations were determined by persulfate digestion and

the Murphy-Riley single reagent method (APHA, 1971). Ortho-phosphorus

concentrations were also determined by the Murphy-Riley technique. Total

organic phosphorus concentrations were obtained by subtracting the

ortho-phosphorus value from the total phosphorus value. Ammonia analyses

were performed with an AutoAnalyzer using the indophenol method (E.P.A.,

1974). Turbidity levels were determined with a Hach Model 2100A

Analytical Nephelometer. Apparent-color was measured at a 420 nm

wavelength on a Bausch and Lomb Spectronic 88 spectrophotometer.

Specific conductance (25 OC) values were obtained with a Beckman Model

RC 16B2 Conductivity Bridge.





-44-


Canal/Sampling Day Characteristics


The canal geometries and tidal exchange information for the Punta

Gorda, Port Charlotte, Pompano Beach, and Loxahatchee River sites, were

provided by B.A. Christensen, Hydraulics Laboratory, Department of Civil

Engineering, University of Florida. For the remaining canal sites, this

information was obtained from scaled maps, tide recordings and depth

profiles.

The recorded canal lengths were the distances along the canals from

the entrances to the most distant points. The mean centerline depths

and entrance-sill heights were determined from depth recordings. The

canal water surface areas were obtained from scaled maps. The canals

were assumed to be rectangular channels to that canal volumes were taken

as the product of the surface areas and mean depths. Canal ages were

obtained from local residents or estimated from comparisons of aerial

photographs and maps. The canal-water minimum residence times were

calculated as the ratios, mean depth:cumulated tidal amplitude, where

the cumulated tidal amplitude was the sum of the tidal ranges during

the 24 hour period.



Statistical Analyses


Descriptive statistics, principal components analyses, canonical

correlation analyses, and stepwise multiple regression analyses were

performed by an IBM 370 computer using the Statistical Analysis System

(Barr et al., 1976) package. Brief conceptual descriptions of the

multivariatemethods and references for each are given in Chapter 4.














CHAPTER 5
RESULTS



As stated in the introduction, the data for this study were

collected in two phases. The first phase (1975 data) was done in con-

junction with a more extensive team study (see Fox et al., 1976 and

Piccolo et al., 1976) wherein pairs of similar canals at four locations

(Punta Gorda, Port Charlotte, Pompano Beach, Loxahatchee River) were

examined four times. The second phase consisted of single sampling

trips to eight other locations. At seven of these locations, data were

collected for three canals over single 24 hour periods. At the eighth

location (North Miami), data were collected for one canal over three

consecutive 24 hour periods.

Four types of data were collected for each canal: 1) metabolism

levels, 2) nutrient/water quality net-exchanges between the canals and

adjacent estuaries, 3) several basic water quality parameters, and

4) canal and the sampling day physical characteristics (shown in Site

Description section).

Analysis of the data has been done in four steps. The first step

is a presentation of the raw data, frequency distributions, and descrip-

tive statistics for the metabolism, exchange, and water quality

responses. The second step is an attempt to evaluate the structure

of the data and to reduce the number of variables to a more manageable

figure without loss of information. The third step is an examination

of the association or correlations between the four data types, and the


-45-





-46-


final step is the generation of descriptive models that relate the

responses of the dependent variables to the levels of the independent

variables.

Sixty-four variables appear in the metabolism, exchange, water

quality, and physical characteristics data sets. The nomenclature for

the variables is shown in Table 2.



Metabolism


Combined Data


The metabolism results for the individual stations are included in

the Appendix. The mean values for the individual canals are presented

in Table 3. The frequency distributions and descriptive statistics

for the metabolic parameters are shown in Figures 14-20.

The mean value of total community gross primary production was
2
8.59 g 02/m -day for the 56 individual canal observations, with a

standard deviation of 5.87 g 02/m2-day. These two values lead to a

coefficient of variation (C.V.) of 66 percent. The frequency distri-

bution and range (0.0 to 24.9 g 02/m -day) of the 56 observations are

shown in Figure 14.

The planktonic component of the total community had a mean gross

primary production of 4.91 g 02/m2-day and a standard deviation of

3.91 g 02/m2-day. The range of values (0.40 to 23.9 g 02/m2-day) and

the frequency distribution are shown in Figure 15. The coefficient

of variation (80 percent) suggests that plankton production is

relatively more variable in the canals than is the total community

gross primary production (C.V. = 66 percent). The frequency distribution





-47-


Table 2. Nomenclature for the variables.


METABOLISM

TGPP Total community gross primary production (g 02/m2-day)


2
TR Total community respiration (g 02/m2-day)

PGPPM2 Plankton gross primary production (g 0 /m -day)

PRM2 Plankton respiration (g 02/m2-day)
3_
PGPPM3 Plankton surface gross primary production (g 02/m -day)

PPRM3 Plankton surface respiration (g 02/m3-day)

TPR Community production:respiration ratio (TGPP/TR)

PPR Plankton production:respiration ratio (PGPPM2/PRM2)

PDOMIN Plankton dominance of community production (PGPPM2/TGPP)

SUN Solar insolation (langleys/day)


EXCHANGE

TC Total carbon concentration (mg/l as C)

TIC Total inorganic carbon concentration (mg/l as C)

TOC Total organic carbon concentration (mg/l as C)

TP Total phosphorus concentration (mg/l as P)

OP Ortho-phosphorus concentration (mg/l as P)

TOP Total organic phosphorus concentration (mg/l, TP-OP)

NH3 Ammonia concentration (mg/l as N)

TURB Turbidity (NTU)

COLOR Apparent color (CPU)

COND Conductivity (micromhos/cm 100)

F-prefix Weighted-average flood tidal phase concentration

E-prefix Weighted-average ebb tidal phase concentration






-48-


Table 2. (Continued)


D-prefix Difference between flood and ebb concentrations (Flood Ebb)

Sign convention -- minus sign (-) indicates Flood value was less than

Ebb value

positive sign (+) indicates Ebb value was less than

Flood value


WATER QUALITY

AVGDO Average dissolved oxygen concentration (mg/l)

MAXDO Maximum dissolved oxygen concentration (mg/1)

MINDO Minimum dissolved oxygen concentration (mg/1)

SECCHI Secchi depth (meters)

TEMP Water temperature (OC)

E-prefix Nutrient and water quality parameters from Exchange data


CANAL/SAMPLING DAY CHARACTERISTICS

LENGTH Centerline length, entrance to most distant point (meters)

WIDTH Average canal width (meters)

MDEPTH Average canal depth (meters)

AREA Canal water-surface area, total (meters)

VOLUME Water volume in canal at mean water level (cubic meters,
MDEPTH AREA)

SILL Sill height (meters)

AGE Canal age (years)

BULK Percent bulkheaded, canal sides

CURBS Presence or absence of curbs and gutters in development
(1 or 0, respectively)

SEWERS Presence or absence of a sewer system in development
(1 or 0, respectively)


I





-49-



Table 2. (Continued)


MINRES Minimum residence time of canal water (days, MDEPTH/CUMTIDE)

CUMTIDE Cumulated tidal amplitude in 24 hr period (meters)

TIDE Maximum tidal amplitude in 24 hr period (meters)

DAYL Hours of daylight on sampling day

SUN Solar insolation (langleys/day)














Table 3. Metabolism results averaged by canal (1 to 5 stations
per canal) for each sampling day.

Nomenclature and units as in Table 2






-51-


OBS CANAL MONTH LDA YrtAk FPf' T PGPPM2

1 PG6 3 l1 75 b.1t 3.28 1.64
2 PG3 J 21 7s 1.15 .06 2.10
3 PC3 3 2 75 b.44 10.12 9.19
4 PCO 3 -1 75 5.57 6.03 5.79
5 Pu3 3 20 75 7.64 8.85 7.01
6 Pb6 3 jo 75 5.Ob 5.9 8 7.58
7 LX3 3 25 75 /.37 6.14 '2.89
8 LXo 3 2 75 t. 8t o.06 2. o
I Pub 6 1 75 6.5o 5.51 2.39
10 PG3 6 14 75 7.91 6.13 2.62
S1 PC3 O 1b 75 11.07 '9.61 3.90
12 PCo 6 1b 75 7.63 10.22 6.50
13 P63 6 19 75 10.25 13.01 7.51
14 POb 6 19 75 v. .2d 14.15 6.45
15 LXc 6 1l 75 6.88 9.46 2.07
16 LXJ 6 lo 75 4.d2 4.64 3.72
17 PG3 9 6 75 0.00 0.00 0.4d
18 PG6 9 o 75 0.00 0.00 0.61
19 PG9 9 b 75
20 PC3 9 9 75 20.73 18.15 3.29
21 PC6 9 9 75 7 3.95 23.51 5.93
L2 PC Y 9 9 75
23 P83 9 7 7z 17.o0 20.13 7.56
24 Pu6 9 7 75 *14.15 14.05 10.04
25 LXJ 9 1. .7b 8.8a 6.47 3.67
26 LX6 9 i7 75 11.47 8.87 7.12
27 PG6 11 1- 75 6.10 3.25 2.80
2d PG3 11 21 75 e.02 5.84 2.73

L S PRM2 POPPM 3 PPMt3 T PPk POOMIN SUN

1 2.03 2.47 O.ou 0.97 0.7o 0.52 602
2 2.05 2.2j 1.07 0.06 3.21 1.00 602
3 5.9c5 .91 2. O0.oj 3.61 i.09 642
4 3.20 3.57 L. : 0. 9 1 .e1l 1.04 642
5 2.32 1.J36 l.lo 0.b9 j.O0 0.89 488
6 2.63 1"2.ob 0.b 0.95 2 .6 1.00 488
7 0.66 ,.73 O0.u 1.20 4. r0 0.39 434
8 1.75 2.00 0.6/ 1.lo 1.7. 0.49 434
9 2.C5 2.13 0.71 1.19 1.18 0.36 650
1 01.6 3 0.o 1.29 1.56 0.3-; 650
11 4.57 4.34 2.00 1 .b O.0o 0.35 o76
.17 7.98 3.99 1.73 0.7 0.90 O.j3 75
13 6.46 9.55 J.Jb 0.7- 1.lu 0.7J 342
14 o.33 9.50 4.o O.oo0 1.08 0.69 342
15 2.87 4.55 1.44 0.73 0.72 0.30 370
16 1.95 4.52 0.96 1.04 1.90 0.77 378
17 0.75 0.77 0.51 1.20 426
18 0.49 1.06 0.O c 2.92 426
19
20 3.77 5.66 2.04 1.1:, 0.93 0.16 446
21 6.03 8.68 3.c0 1.02 0.96 0.25 446
22 .
23 2.74 11.69 2.0o 0.td 3.5v 0.43 238
24+ 3.17 13.72 1.9' 1.01 J.41 0. 71 23d
25 1.96 3. 76 1.0 1 7 1 7 0.41 296
20 4.72 6.02 2.b4 1.2y 1.49 0.62 290
27 0.79 3.7o 0.o2 1.8 4.24 0.46 296
28 1.37 4.41 2.10 ,.89 1.97 0.47 290






-52-


Table 3. (Continued)
OBS CANAL MONTH DAY YEAR TGPP TR PGPPM2

29 PG9 11 21 75 .
30 PC3 11 23 75 9.33 9.91 2.04
31 PC6 11 23 75 8.49 4.52 3.48
32 PC9 11 23 75
33 PB6 11 14 75 3.39 3.06 3.45
34 P89 11 14 75
35 P83 11 14 75 3.45 3.09 2.96
36 LX3 11 16 75 5.09 4.60 2.87
37 LX6 11 16 75 3.42 3.67 3.03
38 MI1 3 24 76 5.86 5.72 5.64
39 MI2 3 24 76 7.11 7.20 3.46
40 M13 3 24 76 9.79 11.19 3.94
41 bC1 4 20 76 24.89 18.65 8.04
42 BC2 4 20 76 16.30 14.30 8.61
43 BC3 4 20 76 15.40 14.19 13.50
44 HI1 5 19 76 7.65 2.66 6.46
45 HI2 5 19 76 7.53 2.55 7.43
46 HI3 5 19 76 14.79 5.65 23.90
47 FL1 6 1L 76 8.34 8.63 3.19
48 FL2 6 12 76 12.69 12.69 2.91
49 FL3 6 12 76 8.66 11.22 4.12
50 API 7 14 76 21.84 19.89 4.00
51 AP2 7 14 76 15.22 16.34 7.71
52 AP3 7 14 76 10.83 10.82 3.30
53 GB1 7 31 76 1.56 2.86 1.20
54 G82 7 31 76 2.27 3.57 0.77
55 GB3 7 31 76 1.95 2.15 0.96
56 KC1 8 18 76 5.53 9.39 1.39

OBS PRM2 PGPPM3 PPRM3 TPR PPR PDOMIN SUN

29 .
30 0.74 2.01 0.56 0. 4 1.98 0.22 334
31 0.53 2.93 0.06 1.88 5.02 0.41 334
32 .
33 1.92 1.39 1.51 1.11 1:79 1.02 352
34
35 1.96 2.71 1.57 0:90 1:76 0.47 352
36 0.92 2.96 0.70 1.11 3.45 0.56 204
37 1.49 3.10 0.93 1 13 2.04 0.78 204
38 3.67 6.38 1.49 1.02 1.54 0.96 520
39 2.91 2.99 1.27 0.99 1.19 0.49 520
40 4.91 3.40 1.56 0.87 0.80 0.40 520
41 4.35 4.81 1.54 1.33 1 84 0.32 571
42 3.20 4.41 1.37 1.14 2.69 0.53 571
43 5.24 6.02 1.88 1.08 2.58 0.88 571
44 2.47 5.55 1.76 2.87 3.76 0.84 515
45 2.99 5.15 1.93 2.95 2.48 0.99 515
46 6.16 18.00 3.10 2.62 3.81 1.00 515
47 3.92 3.26 2.17 0.97 0.81 0.38 504
48 4.98 1.77 1.75 1.00 0.58 0.23 504
49 3.48 3.25 1.01 0.77 1.18 0.48 504
50 3.94 3.96 2.40 1.10 1.02 0.18 506
51 3.75 10.64 2.86 0.93 2.05 0.51 506
52 2.95 4.22 2.04 1.00 1.12 0.30 506
53 1.45 1.67 1.62 0.55 0.83 0.77 554
54 0.74 1.18 1.12 0.64 1.04 0.34 554
55 0.46 1.34 0.21 0.91 2.09 0.49 554
56 2.01 0.87 0.86 0.59 0.69 0.25 72






-53-


Table 3. (Continued)
OBS CANAL MONTH DAY YEAR TGPP TR PGPPM2

57 KC2 8 18 76 5.51 6.37 1.53
58 KC3 8 .18 76 1.76 5.63 0.40
59 NM1 10 26 76 1.88 1.96 9.06
60 NM2 10 27 76 11.10 4.15 10 71
61 NM3 10 26 76 15.01 12.10 6.40
62 PE1 8 14 74
63 PE2 8 14 74
64 8P3 8 19 74
65 BP4 8 19 74
b6 SA8 8 23 74
67 AB3 9 17 74
68 AB5 9 17 74
69 MIH 8 6 75
70 MIJ 8 10 75
71 NIL 8 6 75
72 MIM 8 6 75
73 MIM 8 8 75
74 MIN 8 7 75

UBS PRM2 PGPPM3 PPRM3 TPR PPR PDOMIN SUN

57 2.09 0.43 0.56 0.86 0.73 0.28 72
58 1.36 0.38 0.60 0.31 0.29 0.23 72
59 5.02 3.81 3.10 0.96 .O0 1.00 316
60 6.06 6.26 1.45 2.68 1 77 0.96 346
61 2.62 4.37 175 1.24 1.64 0.43 183
62
63 .
64 .
65
66
67 .
68
69
70 .
71 .
72 .
73
74 .





-54-


u15
o
o.* ___



g 02/m-day
0 -H





0 - - -

0 2 4 6 8 10 12 14 16 18 20 22 24 26

g 0 2/m -day

N = 56 Mean = 8.59 Std. Dev. = 5.87 Range 0.00 to 24.9
C.V.% = 66


Figure 14.


m15
0

o
10

S5


Frequency distribution and descriptive statistics for
total community gross primary production (g 02/m2-day),
averaged by canal. Values are rounded to nearest integer.


Ii I I I I I I
1 2 3 4 5 6 7 8 9 10

g 02/m -day


N = 56 Mean = 4.91 Std.


13 24 r
13 24


Dev. = 3.91 Range 0.40 to 23.9


C.V.% = 80


Figure 15.


Frequency distribution and descriptive statistics for
planktonic gross primary production (g O2/m2-day), averaged
by canal. Values are rounded to nearest integer.


Ir I I~rl I





-55-


histogram suggests that a bimodal distribution was observed for

planktonic production. No canal actually exhibited the mean value of

5 g 02/m2-day (values were rounded to nearest integer to construct

the histograms). The plankton production for these canals tended to

occur in two levels; a low range of 1-4 g 02/m2-day, and a higher range

of 6-10 g 0 2/m2-day.

The distribution and descriptive statistics of the community and

plank-tonic respiration are shown in Figure 16 and 17, respectively.

Community respiration had a mean value of 8.20 g 0 /m2-day for the 56

canal observations, compared to 3.01 g 02/m2-day for the plankton. The

standard deviation and range of the community respiration responses

(5.45 and 0.0 to 23.5 g 02/m2-day) were greater than those of the

planktonic component (1.83 and 0.46 to 7.98 g 02/m -day). The relative

variabilities of respiration are comparable for the total community

and plankton (C.V. = 66 and C.V. = 61, respectively).

The frequency distributions and descriptive statistics for the

primary production:respiration ratios of the total community and

planktonic component, are presented in Figures 18 and 19. The mean

value (1.16) of the 56 community observations suggests that these

systems tend to be balanced or slightly autotrophic. However, the

range of values (0.31 to 2.95) indicate that canals can exhibit both

heterotrophic and autotrophic characteristics. The range of P:R ratios

(0.29 to 5.02) for the planktonic component of the total canal com-

munities also indicates that both heterotrophic and autotrophic behavior

exists for the plankton. The mean value for plankton P:R ratio (1.93)

indicates greater autotrophy in the water column than for the entire

canal. From a trophic standpoint the planktonic component is relatively






-56-


SJ15

J 10

c 5n 5


0
0 2 4 6 8 10 12 14 16 18 20 22 24

g 02/m2-day


N = 56 Mean = 8.20 Std. Dev, =
C.V.% = 66


Figure 16.















n 15
o 0
0 -H
4J 10

zao
P) 5
o0
0


5.45 Range 0 to 23.5


Frequency distribution and descriptive statistics for
total community respiration (g 02/m2-day), averaged
by canal.


0 1 2 3 4 5 6 7 8
02/m day
g 02/m -day


N = 56 Mean = 3.01


Std. Dev. =
C.V.% = 61


1.83


Range 0.46 to 7.98


Figure 17.


Frequency distribution and descriptive statistics for
planktonic respiration (g 02/m2-day), averaged by canal.






-57-


O i
)l



4) > 5


O I I I I I I I I
o1 0 P i-\ !F-----, -o--


0.3 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.9 2.6 2.9

TGPP/TR

N = 56 Mean = 1.16 Std. Dev. = 0.59 Range 0.31 to 2.95
C.V.% = 50


Figure 18.















Uo
44 o
LO
0 -r4




0
0


Frequency distribution and descriptive
total community production:respiration
by canal.


0 1-
0.0


N = 56 Mean = 1.93


statistics for
ratio, averaged


.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5

PGPPM2/PPM2


5.0


Std. Dev. = 1.14 Range 0.29 to 5.02
C.V.% = 59


Figure 19.


Frequency distribution and descriptive statistics for
planktonic production:respiration ratio, averaged by
canal.


I





-58-


more variable than the total canal community (C.V. = 59 and 50,

respectively).

Figure 20 shows the frequency distribution and descriptive

statistics for the degree of plankton dominance of the total community

gross primary production for the 56 canal observations. The distri-

bution seems to be somewhat bimodal with plankton production accounting

for 50 percent or less of the total community production in 31 of the

54 observations. In other words, some canals were plankton dominated

on the day sampled but others were not. The range of values (PGPPM2/

TGPP) was 0.16 to 1.0. The mean value (0.60) for all the observations

may be misleading since few of the responses were this value.



1975 Data


Thirty-two of the fifty-six metabolism observations were obtained

during 1975 in a study for the Florida Department of Environmental

Regulation (see Fox et al., 1976). The design of the project consisted

of four locations (Punta Gorda, Port Charlotte, Loxahatchee River, and

Pompano Beach) with two similar canals per location, four stations per

canal (bay, mouth, middle, and'back), and four sampling seasons (March,

June, September, and November).

This design allowed the factors of location, season, and distance

along the canals to be evaluated for significant effects on the

metabolic levels. In addition to making possible the assessment of

the seasonal and distance variabilities, the unexplained or inherent

variability between canals that appeared identical could be determined

using analysis of variance.

The canal mean metabolic levels from this 1975 work are included






-59-


o 10


5
zm
o0 *
z o ,

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

PGPPM2/TGPP

N = 54 Mean = 0.60 Std. Dev. = 0.28 Range 0.16 to 1.0
C.V.% = 101


Figure 20. Frequency distribution and descriptive statistics for
plankton domination of community production.






-60-


in Table 3 for the eight canals and four seasons. The individual

station results are presented in the Appendix. The results of the

analyses of variance on the data are shown in Table 4.

The analyses indicate that there are significant differences in

the levels of community production and respiration with the season of

the year, with the location of the canal, and with distance up a canal.

This three way interaction indicates that the spatial and temporal

distribution of metabolic levels in these residential canals is a

non-additive function of the distance, location and season factors.

The seasonal changes have different effects on community metabolism

depending on the canal location and on the distance up the canal. The

lack of simple trends for any of the three factors can be illustrated

by the fact that the highest community metabolism levels occurred

during September for all locations except Punta Gorda, where the level

was the lowest recorded for the year.

The sources of variation listed in Table 4 account for 88 and 87

percent (R2 value) of the community production and respiration vari-

ability, respectively. The remaining 12 percent of the variability

is composed of the error involved with the determinations of the

metabolic levels and with the difference in metabolism levels of the

individual canals within the pairs, which were treated as replicate

observations; the latter source of residual variance could be a result

of factors such as plankton patchiness, water circulation patterns, and

nutrient inputs. This small amount of unexplained variability indicates

that the individual canals within the pairs of canals do not differ

appreciably in the patterns and levels of metabolic activity, relative

to the total variability for all locations, seasons, and distances.





-61-


Table 4. Results of the analyses of variance for the total community
and planktonic metabolism data (1975).


Community Plankton
Source of
Variation Per Square Meter Per Square Meter Surface

GPP* R* P/R* GPP R P/R GPP R


Location NS NS

Distance NS NS NS NS

Month NS

Location x Distance NS NS NS NS ** NS

Location x Month NS ** ** NS ** **

Distance x Month NS NS NS ** NS NS

Location x Distance ** ** NS NS NS NS NS NS
x Month

Mean 7.80 7.49 1.36 4.01 2.56 2.30 4.71 1.47

S.D. (adjusted) 2.95 3.30 1.80 1.69 1.64 1.52 1.68 0.91

C.V. % 37 44 132 42 64 65 35 62

R2 0.88 0.87 0.50 0.83 0.77 0.77 0.92 0.77

Unadjusted S.D. 6.22 6.49 1.77 2.63 2.20 2.01


GPP gross primary production; R respiration;
P/R production : respiration ratio (GPP/R)

** Indicates the term is a significant source of variation

NS Indicates the term is not a significant source of variation

Blank indicates that an exact test for the term cannot be made

Units- g 02/m2-day or g 02/m3-day


I






-62-


The community production:respiration ratio analysis does not

yield the same.pattern as the production and respiration results. No

significant differences were found for the 64 combinations of location,

distance and month factors. The mean value for all observations was

1.36 with a coefficient of variation equal to 132 percent. This para-

meter was relatively more variable than production and respiration for

the replicate canals, resulting in the inability to detect differences

among the means.

Analysis of the planktonic metabolism data yields inferences some-

what different from those of the whole community metabolism. The level

of planktonic gross primary production and respiration on a square

meter basis depends on the season and the location. No significant

differences in the levels of planktonic production and respiration for

the entire water column could be detected along the lengths of the

canals.

There were significant differences among the means of the plank-

tonic P:R ratio. The changes in the P:R ratio with season varied

depending on the distance up the canals.. No significant differences in

the patterns of planktonic P:R ratios was detected for the four

locations.

The results of the analysis of variance for the surface values of

planktonic metabolism were similar to those for the entire water columns.

The effect of distance and season varied with canal location for the

surface plankton production, whereas only the effect of season varied

with location for the entire water column. In fact, no effect of

distance up the canal could be detected for the planktonic metabolic

levels on a square meter basis, for these canals.





-63-


The variability or standard deviation remaining after the re-

sponses were adjusted for the three factors and their interactions is

also shown in Table 4. These unexplained variances represent the

dissimilarity between canals that appear identical, for the individual

parameters. For example, the community gross primary production values

had a standard deviation of 6.22 g 02/m2-day before adjustment.for the

factor effects, and 2.95 g 02/m2-day after adjustment. The latter

value indicates the variability of community production estimates once

the canal location, the season of the year, and the distance along the

canal have been specified. The corresponding unexplained variability

for the plankton production data is 1.69 g 02/m2-day.

While the analyses of variance for the metabolic parameters in-

dicated that no consistent trends existed for all the locations and

sampling periods, the mean values (Table 5) computed by location, by

season, and by distance for all the data show the average pattern for

these different factors.

Community gross primary production was lowest in March (5.13
2
g 02/m -day), increased through June, peaked in September (11.2 g

02/m2-day), and then declined in November. The production:respiration

ratio for the total communities increased each sampling season to a

peak in November (mean P:R = 2.34), whereas the planktonic P:R ratio

was highest in the fall and lowest in June.

The mean values of the metabolic parameters with distance along

the canal (Table 5) suggest that the community and plankton production

tends to increase from the adjacent estuary (Bay) to the middle and

back of the canals. It would be tempting to conclude that these canals

were more productive than the adjacent estuaries. However, the





-64-


2
Table 5. Community and plankton gross primary production (g 0 /m -day)
means for the four locations sampled in 1975, averaged by
location, by season, and by distance along canal.


TGPP PGPPM2 TPR PPR


PG

PC

PB

LX

Std. Dev.


March

June

September

November

Std. Dev.


3.74

10.5

8.48

6.15


2.92


5.13

6.63

11.2

5.53

2.79


Means by Location

1.85

4.87

6.43

3.46


1.96


Means by Month

4.78

4.16

4.47

2.89

0.83


2.11


1.56

1.71

0.98

1.18


2.35

2.39

2.44


0.34


0.15


0.94

0.98

1.32

2.34

0.65


2.55

1.21

1.92

3.40

0.93


5.33

6.68

8.2.8

8.20

1.40


Means by Distance Along Canal

2.53 1.29

3.96 1.11


4.40

0.98


1.16

1.87

0.35


3.23

2.27


2.07

0.62


Grand Mean 7.18 3.98 1.36 2.31


Nomenclature as in Table 2
Units g 02/m2-day


Bay

Frong

Middle

Back

Std. Dev.





-65-


analysis of variance detected no significant differences for plankton

production between the bay and canal stations, and indicated that the

effect of distance on community metabolism depended on the location

and month. No significant differences for community production:

respiration ratio could be detected for distance, season, or location,

though the highest mean value was found at the backs of the canals.

For the planktonic P:R ratio the lowest mean value occurred at the

backs of the canals; the highest mean value occurred in the bay, but

again this cannot be considered a consistent pattern since the analysis

of variance found that the effect of distance depended on the month of

sampling.



Daily Variability in One Canal


One canal (North Miami site) was sampled for three consecutive

days to obtain an estimate of the day-to-day variability for one canal;

the metabolism results are shown in Table 6.

The estimates of planktonic primary production were quite repro-

ducible when the level of solar insolation is considered. The planktonic

production:respiration ratios were also consistent (mean = 1.74,

C.V. % = 5) for the three days. The community metabolism results,

however, were not as uniform (mean TGPP = 9.33 g 0 /m -day, C.V. % =

72). The changes of community primary production, community respiration

and the community production:respiration ratio estimates did not

parallel those of the plankton for the three day period.

The most likely explanation of the seemingly sporadic total com-

munity results for the three consecutive days at the North Miami site,

is the limitation of the estimation technique. The free-water diurnal





-66-


Table 6. Metabolism results for three consecutive
one canal (North Miami site).


days of sampling on


Date TGPP TR PGPPM2 PRM2 PGPPM3 PPRM3


26 Oct 76 1.88 1.96 9.06 5.02 3.81 3.10

27 Oct 76 11.10 4.15 10.7 6.06 6.26 1.45

28 Oct 76 15.0 12.1 6.40 2.62 4.37 1.75

Mean 9.33 6.07 8.72 4.57 4.81 2.10

Std. Dev. 6.73 5.33 2.17 1.76 1.28 0.88

C.V. % 72 88 25 39 27 42



Date TPR PPR PDOMIN SUN


26 Oct 76 0.96 1.80 4.82 316

27 Oct 76 2.68 1.72 0.96 346

28 Oct 76 1.24 1.64 0.43 183

Mean 1.63 1.74 2.07 281

Std. Dev. 0.92 0.08 2.40 87

C.V. % 57 5 1.16 31


Nomenclature as in Table 2

Units g 02/m2-day or g


02/m -day






-67-


method requires a homogeneous water column, to be reasonably accurate

and precise. The North Miami canals were approximately six meters deep

and were anaerobic below the two meter depth throughout the three days.

The chemical oxygen demand of the hydrogen sulfide (strong odor present)

in the large anoxic layer could remove varying amounts of oxygen from

the surface layer. The weather conditions during the three day study

in October were also not conducive to uniform conditions within the

canal (a cold front was passing through the area, producing colder air

and strong shifting winds). The deep stratified North Miami canal

during a period of water column overturn, was inappropriate for appli-

cation of this technique. The only other occasion when a canal with

anoxic bottom water was sampled during a period of overturn was Port

Charlotte (Canal PC1) in November 1975.



Nutrient Exchange


Combined Data


The weighted-average flood concentrations, the difference between

the flood and ebb concentrations for the nutrient/water quality para-

meters determined for each canal observation during this study, plus

those obtained from the Environmental Protection Agency, are shown in

Table 7. The frequency distributions and descriptive statistics for

the weighted-average ebb concentrations and net changes of the carbon

forms, phosphorus forms, ammonia, and turbidity are presented in

Figures 21-28. A positive (+) sign with the net exchange values in-

dicates a net retention or sink type of activity. Conversely a negative

(-) sign indicates a net export or source type of activity.














Table 7. Canal-estuary exchange results for the nutrient and water
quality parameters.

Nomenclature and units as in Table 2






-69-


C M
A 0 Y i
U N ND t F UE T1 T F G F
13 A T A A r T I I I U T T O
b L H Y C C L C C C P P P

1 PG6 3 21 75 20.6 -0.6 10.2 0.5 1o.3 -1.2 0.441 0.005 0.377
2 PG3 3 21 75 20.3 -1.4 9 -2.4 17.1 1.2 0.460 -0.068 0.369
3 PC3 3 22 75 27.5 0.ti .2 1.3 lo.3 -1.0 0.547 0.069 0.423
4 PC6 3 22 75 26.8 -0.1 0.7 0.9 10.1 -1.0 0.500 0.063 0.401
5 P83 3 26 73 31. 0 l .t [ 17.4 0.219 0.189
6 Pbb 3 26 75 32.2 1 l.7 0.222 '0.203
7 LX3 3 25 75 37.9 1.7 b.4 0.7 12.6 0.6 0.04 0.c005 0.027
8 LX6 3 25 75 37.7 1.0 2..7 -0.4 13.1 1.1 0.053 0.004 0.029
9 PG6 6 14 75 29.7 -2.4. 168. -0.3 10.6 -2.1 0.479 0.011 0.533
10 PG3 6 14 75 29.8 -0.o 19.2 0.6 10.6 0.3 0.500 0.043 0.547
11 PC3 6 15 75 28.3 0.0 lo.6 0.0 9.7 0.9 0.53d -0.007 0.583
12 PC6 6 15 75 30.5 -1.0o 1.9 1.4 11.4 -3.4 0.518 0.003 0.600
13 Pb3 6 19 75 41.4 -1.3 9.5b -0.j 11.9 -1.1 0.221 0.000 0.180
14 Pb6 6 19 75 41.7 -1.4,+ 9.o 0.3 11.9 -1.7 0.225 0.013 0.179
lb LX6 6 18 75 46.4 1.7 4.b 2.1 11.8 -0.4 0.067 -0.001 0.024
o1 LXJ 6 18 75 47.3 2. .t .2 2.1 11.1 0.4 0.086 0.002 0.028
17 PGJ 9 6 73 33.2 0.0 1t,.5 -0.4 16.7 2.1 0.511 0..028 0.405
18 PG.6 9 6 75 29.2 -3.7 14.3 -2.4 14.9 -1.3 0.449 -0.029 0.447
19 PG9 9 6 75 35.0 1.9 Ib..~ -1.0 19.o 3.c 0.550 0.067 0.503
20 PC3 9 9 75 34.1 0.7 it.5 -0.1 17.6 0.9 0.535 -0.017 0.4bb
e1 PC6 9 9 75 36.3 1.1 15.9 0.1 2.' 1.0 0.4 76 -0.066 0.470
22 PC9 9 9 75 34.5 -1.1 lo.1 0.1 lo.4 -1.2 0.bol 0.026 0.463
23 PU3 9 7 75 38.2 -0.9 -o .o -1.7 11.4 -0.5 0.243 -0.004 0.207

F D
F L C C F D
F L F U T T L U C C
O O T T N N U U L L 0 O
a O U 0 H -R R 0 U N N
S P- P P 3 J u u K P O O

1 0.039 0.OoO -0.03o 0.0- 0.00 4.6 0.1 .
2 O.OOC 0.099 -0.C69 0.0, 0.01 b.J -1. .
J 0.045 0.144 0.029 0.05 0.04 7.2 2.1 .
S 0.0 3 0.100 0.042 0.01 -0.02 7.c 3.3 .
5 0.030 C. 1 4.0 .
6 0.019 0.10 J. .
7 -0.001 0.022 0.006, 0.01 C.0 3. 0.3 .
8 -0.008 0.C24 0.012 0.01 0.00 3.j 0.2 .
9 0.055 -0.044 O.Cb 0.00 0.9 -0.0 53 -1J
10 0.037 -0.012 0.07 -0.02 0.1 -0.6 05 8
11 0.002 -0.009 0.0 -0.01 1.0 0.0 41 10
12 0.030 -0.027 0.04 -0.OJ 1.0 0.0 39 34 .
1J 0.010 0.041 -0.008 0.09 0.00 2.2 0.0 104 12
14 0.002 0.036 -0.002 0.07 -0.01 2.4, 0.2 113 12
15 0.004 0.044 -0.005 0.0 u.0 3.0 -0.3 140 16
16 0.001 0.0 8 0.010 0.0z 0.01 3.4 -0.9 1 38 1J .
17 0.030 0.046 -0.002 0.21 0.02 J.1 -1.3 239 -14
18 -0.006 002 -0.023 C.2 -6.04 3.0 0.b 232 -13
I1 0.009 C.O" -0.003 0.17 -0.01 2.9 0.1 20 39
20 -0.014 0.077 -0.004 0..4 0.06 4.2 -0.5 222 8 .
21 -0.017 0.CO -0.049 C.lo 0.04 10.0 5.0 233 13
22 0.005 0.090 0.021 0.11 0.01 0.b c.0. 223 d
23 0.007 0.CJo -0.011 0.00 -0.C4 3.1 0.9 j 17






-70-


Table 7. (Continued)

C M
A O Y F D
O N N D E F D F D T T F D F
SA T A A T T I I U 0 T T 0
SL H YR C C C C C C P P P

24 P86 9 7 75 41.3 -0.4 26 6 -1.9 15.0 1.5 0 254 -0.016 0.206
25 LX3 9 12 75 50.1 -0.3 32.7 0.8 17.4 -1.L 0.051 -0.002 0.063
26 LX6 9 12 75 49.1 -0.1 33.1 0.4 16.0 -0.4 0.048 -0.009 0.058
27 PG6 11 21 75 33.2 -0.9 18.5 -0.4 14.7 -0.5 0.296 -0.030 0.257
28 PG3 11 21 75 .
29 PG9 11 21 75 34.0 -0.4 15:6 -0.9 18.4 0.7 0.382 0.012 0.356
30 PC3 11 23 75 34.4 1.2 21.5 0.4 12.7 0.6 0.349 0.007 0.303
31 PC6 11 23 75 35.1 0.0 18.0 0.0 17.1 0.0 0.332 0.022 0.296
32 PC9 11 23 75 34.3 -1.1 19.9 0.5 14.4 -1.6 0.346 -0.011 0.283
33 P86 11 14 75 57.8 -0.1 41.5 1.J 10.2 -1.5 0.236 -0.014 0.203
34 PB9 11 14 75 57.0 0.7 42.1 -0.5 14.9 1.2 0.224 -0.012 0.196
35 P83 11 14 75
36 LX3 11 16 75 49.4 6.2 34.0 1.5 15.4 4.6 0.057 0.003 0.016
37 LX6 11 16 75 .
38 MI1 3 24 76 39.0 -5.4 23.3 05 15.6 -5.9 0.067 -0.016 0.043
39 M12 3 24 76 36.9 -1.6 22.1 -0.9 14.7 -0.7 0.064 0.004 0.043
40 MI3 3 24 76 39.8 -0.4 24.2 0.3 15.5 -0.7 0.082 0.029 0.044
41 BC1 4 20 76 36.4 0.9 13.7 1.2 22.7 -0.4 0.193 -0 004 0.158
42 bC2 4 20 75 38.1 0.9 12.7 -0.1 25.3 0.9 0.210 0.008 0.166
43 BC3 4 20 76 37.5 2.4 12.1 -2.2 25.4 4.8 0.184 -0.010 3.159
44 HI1 5 19 76 49.9 1.8 21.1 0.5 28.9 1.4 0.063 0.011 0.044
45 HI2 5 19 76 42.0 -0.6 1 .4 -1.0 2J.6 0.2 0.041 0.002 0.025
46 HI3 5 19 76 47.8 2.5 22.4 0.3 25.4 2.1 0.120 -0.003 0.104

F D
F D C C F D
F 0 F U T T U O C C
SD T T N N U U L L O O
6 0 0 U H H R R O 0 N N
S P P P 3 3 b 8 R R 0 D

24 -0.012 0.048 -0.004 0.08 -0.18 4.2 0.7 112 7 .
25 -0.01C 0.000 0.000 0.00 0.03 4.5 -0.3 124 3
26 -0.009 0.000 0.000 0.02 -0.03 4.1 0.2 115 18
27 -0.031 0.038 0.001 0.07 -0.02 .
28 .
29 C.014 0.026 -0.002 0.01 -0.07 .
30 0.003 0.045 0.003 0.21 0.01 .
31 0.019 0036 0004 00 -0.10
32 -0.029 0.064 C.019 0.04 0.04 .
33 -0.002 0.031 -0.014 0.23 0.00 .
34 -0 007 0.028 -0.005 0.23 0.02 .
35 .. : .
36 0.004 0.041 0.000 0.05 0.01
37 .
38 -0.013 0.025 -0.003 0.10 -0.01 5.7 09 35 2 345 -2
39 0.002 0.021 0.002 0.06 0.01 3.0 -0.1 14 -12 343 -8
40 0.011 0.037 0.017 0.05 0.02 4.1 0.4 26 -13 337 -14
41 -0.007 0.034 0.003 0.09 0.02 3.1 -2.1 21 -7 260 -20
42 -0.002 0.044 0.010 0.15 0.00 5.4 0.8 21 5 274 9
43 -0.009 0.C25 -0.005 0.10 -0.03 2.6 -0.5 12 -8 268 9
44 0.011 0.019 0.000 0.14 0.04 1.0 0.0 52 -2 307 -23
45 0.002 0.C16 0.000 0.12 0.03 0.5 -0.2 25 -18 376 21
46 -0.003 0.016 0.000 0.11 -0.02 1.2 0 1 69 4 294 -5





-71-


Table 7. (Continued)

C M
A O Y F D
O N N D E F F D T T F 0
B A T A A T T I I O O T T
S L H Y R C C C C C C P P

47 FL1 6 12 76 41.0 1.1 22.6 -0.3 18.4 1.4 0.090 0.004
48 FL2 6 12 76 40.3 1.1 2348 1.0 16.5 0.1 0.092 0.009
49 FL3 6 12 76 41.3 2.0 22.5 1.2 18.9 1.0 0.095 0.007
50 API 7 14 76 37.6 -1.i 13.1 0.5 22.9 -2.5 0.842 -0.025
51 AP2 7 14 76 44.6 7.5 16.8 -2.5 27.7 10.0 0.807 0.020
52 AP3 7 14 76 40.3 0.0 13.6 -1.5 26.7 1.7 0.842 0.006
53 GB1 7 31 76 32.7 1.6 14.4 -0.9 18.3 2.5 0.021 -0.001
54 G82 7 31 76 28.0 -0.1 15.9 0.2 12.1 -0.3 0.023 0.001
55 663 7 31 76 30.1 -2.5 16.2 0.0 13.9 -2.5 0.030 -0.007
56 KC1 8 18 76 34.9 1.7 25.4 0.0 9.5 1.7 0.021 0.002
57 KC2 8 18 76 32.4 0.5 25.0 0.4. 7.3 0.0 0.018 0.001
58 KC3 8 18 76 30.6 0.2 24.9 0.1 5.7 0.1 0.014 0.000
59 NM1 10 26 76 54.8 -0.4 12.6 0.6 42.2 -1.0 0.065 0.000
60 NM2 10 27 76 56.7 1.1 1J.6 -C04 42.0 0.4 0.066 0.004
61 NM3 10 28 76 53.0 0.3 12.6 -0.4 40.6 0.7 0.054 -0.001
62 PE1 8 14 74 15.6 -0.2 0.310 -0.020
63 PE2 8 14 74 e 15.3 0.6 0.200 -0.020
64 BP3 8 19 74 1.8 -0.1 0.040 0.000
65 BP4 8 19 74 1.9 0.0 0.030 -0.010
66 SA8 8 23 74 1.0 0.0 0.030 0.000
67 A83 9 17 74 a 3.3 -0.1 0.030
68 A85 9 17 74 2.6 0.2 C0040 -0.010
69 MIH 8 8 75 a 9 7.0 -1.2 0.179 0.029

F D
F D C CF D
F 0 F D T T O 0 C C
O F D T T N NU U L L 0 0
S0 0 0 H H R R O O N N
S P P P P 3 38 8 R D D

47 0.037 0.004 0.053 C.000 0.09 0.01 4.5 0.8 236 43 341 -2
48 0.035 0.002 0.059 0.008 0.05 0.01 4.7 0.6 219 43 337 -5
49 0.038 -0.001 0.057 0.009 0.08 0.02 4.8 1.3 170 44 335 -4
50 0.692 -0,028 0.151 0.003 0.04 0.01 J.9 -0.9 107 -6 274 3
51 0.747 0.025 0.076 0.001 0.06 0.00 5.0 -0.3 109 -6 275 1
52 0.731 0.027 0.111 0.004 0.06 0.02 6.0 0.4 126 1 268 1
53 0.015 0.001 0.003 -0.001 0.07 0.00 2.8 -0.4 112 0 266 -3
54 0.016 0.000 0.007 0.001 0.09 0,02 2.8 -0.3 93 -7 269 4
55 0.019 -0.005 0.011 -0.002 0.07 0.00 4.8 0.2 140 -12 285 0
56 0.003 -0.003 0.018 0.005 0.07 -0.04 1.8 -0.2 26 -3 448 0
57 0.004 0.001 0.014 0.001 0.03 -0.01 2.4 0.4 37 6 446 3
58 0.004 0.000 0.010 0.001 0.01 0.00 1.8 -0.1 20 -5 443 -4
59 0.034 -0.002 0.029 0.000 0.04 0.01 3.0 0.0 85 3 260 2
60 0.032 0.003 0.032 0.001 0.04 0.03 3.4 0.1 91 7 259 -4
61 0.025 0.000 0.028 -0001 0.02 -0.03 3.4 0.1 85 -3 265 -4
62 .* 0.12 -0.01 .
63 0.10 -0.04 .
64 .* 0.06 0.00 .
65 e. 0.08 -0'.02 .
66 .* 0.04 -0.01 .
67 0.09 0.00 .
68 * 0.08 -0.02 .
69 .* 0.02 0.00 .






-72-


Table 7. (Continued)


0
N D
T A
H Y


F U F D
T T I I
C C C C


70 MIJ 8 10 75 10*7 1.7 0.257
71 MIL 8 6 75 6.2 -0.1 0.072
72 MIM 8 6 75 6.6 0.3 0.090
73 MIM 8 8 75 6.2 0.1 0.095
74 MIN 8 7 75 8.4 -0.2 0.095


F 0
F D T T
0 0 0 0
P P P P


F 0
F 0 C C F D
D T T C C C C
N U U L L 0 0
H R R 0 0 N N
3 B B R R D D


70 0.093 *
71 0.004
72 0.006 .
73 0.010 *
74 0.003 .


S 0.03 0.01
* 0.01 -0.01 .
* 0.01 0.00 .
* 0.03 0.01 .
* 0.03 0.01 .


* .
* .
* .
* .
. .





-73-


The total mass exchange of each material is not shown in Table 7

but can be calculated for each canal observation from the net change in

concentrations (weighted-average flood concentration minus weighted-

average ebb concentration) in Table 7 and the information in Table 1.

The product of the cumulated 24 hr tidal amplitude (CUMTIDE, Table 1)

and canal surface area (AREA, Table 1) for a particular canal observa-

tion yields the tidal exchange volume (m ) for the sampling day. The

product of the exchange volume and the net changes in concentration from

flood to ebb tidal phases (D values in Table 7, mg/l or g/m 3) gives

the net mass transport (g/day) of each material.

The average total carbon concentrations (Figure 21) ranged from

24.1 mg/1 to 57.9 mg/l, with a mean of 38.0 mg/l. The estimates of

net exchange of total carbon ranged from a net export of 5.4 mg/l of

exchanged water, to a net retention of 7.5 mg/l of exchanged water.

The mean value for net exchange was a net retention of 0.2 mg/l, with

a standard deviation of 2.0 mg/l. The distribution of net exchange

responses indicates that all canals do not exhibit the same type of

behavior. About equal numbers of these canals were found to be sources

of carbon to the adjacent estuaries, as were found to be sinks for

carbon from the estuaries.

The average inorganic carbon concentration (Figure 22) was 20.6

mg/l, with a standard deviation of 7.6 mg/l and a range of 7.8 to 42.6

mg/l. The mean value for inorganic carbon exchange was a net export of

0.1 mg/l of exchanged water, with a standard deviation of 1.1 mg/1 and

a range of -3.4 to +2.1 mg/l.

The mean total organic carbon concentration (Figure 23) was 15.5

mg/1, with a standard deviation of 8.3 mg/l and a range of 1.0 to 43.2





-74-


a. Average ebb concentration of total C.


24 27 30 33 36 39 42 45 48 51 54


N = 58 Mean = 38.0


mg/1

Std. Dev. = 8.0


Range 24.1 to 57.9


b. Net change (flood-ebb) of total C.


'4- 0 10
0 *H




0




N = 56 Mean = +0.2 Std. Dev. 2.05 Range -5.4 to +7.5




Figure 21. Frequency distribution and descriptive statistics for
(a) weighted-average ebb total carbon concentration (mg/1),
and (b) the net changes from average flood concentrations.


o
0
4 10


M 5
0






-75-


a. Average ebb concentration of inorganic C.


8.0 11 14 17 20 23 26 29 32 35 38 41

mg/1


N = 58 Mean = 20.6 Std. Dev. = 7.6


Range 7.8 to 42.6


b. Net exchange (flood-ebb) of inorganic C.


15
0
' 10
nd


o-
0

-3.4


-2.7 -2.2-1.7 -1.2 -0.7-0.2 +0.2 +0.7+1.2 +1.7 +2.2


mg/1

N = 56 Mean = -0.1 Std. Dev. = 1.1 Range -3.4 to +2.1



Figure 22. Frequency distributions and descriptive statistics for
(a) weighted-average ebb inorganic carbon concentrations
(mg/1), and (b) the net changes from average flood con-
centrations.


15

o
10



0





-76-


a. Average ebb concentration of organic C.


o15
4J
S10

4 5
0
C


N = 71


1.0 4.0 7.0 10 13 16 19 22 25 28 31 40 43

mg/l

Mean = 15.5 Std. Dev. = 8.3 Range 1.0 to 43.2


b. Net change (flood-ebb) of organic C.


S15
0

10 10

0 5


-0 3. -7 +0'.2 +1.2-,
-5.9 -2.7 -1.7-1.2 -0.2 +0.7 +1.7+2.2+2.7 4.7 10.0
3.6
mg/1

N = 69 Mean = +0.2 Std. Dev. = 2.0 Range -5.9 to +10.0








Figure 23. Frequency distributions and descriptive statistics for
(a) weighted-average ebb total organic carbon concentrations
(mg/1), and (b) the net changes from average flood con-
centrations.





-77-


mg/l. The mean value for net organic carbon exchange was a net reten-

tion of 0.2 mg/l of exchanged water, with a standard deviation of 2.0

mg/1. The values ranged from a net export of 5.9 mg/l at Marco Island

canal Mil, to a net retention of 10 mg/l at Apollo Beach 2. The most

frequent response, however, was no significant change in the organic

carbon concentration between estuarine water entering and that leaving

the canals.

The range of total phosphorus concentrations (Figure 24) in these

canals was large, reflecting the presence of phosphate mining in the

vicinity of some of the canals. The highest values observed (ca. 0.8

mg/1) were at the Apollo Beach site. The higher values make the mean

value (0.231 mg/1) somewhat misleading, considering that nearly half

of the observations had values less than 0.1 mg/l. The net changes in

total phosphorus concentrations from flood to ebb tides had a mean

value of +0.003 mg/1, with a standard deviation of 0.020 mg/l and a

range of -0.067 to +0.093 mg/1. As in the case of total carbon, these

canals differ in the phosphorus mass transport activities, but most

frequently have little or no effect on the phosphorus loads of the

exchanged water.

The frequency distributions and descriptive statistics for the

ortho-phosphate levels and exchange responses of these canals are

presented in Figure 25. The ortho-phosphate distribution follows a

pattern similar to that of total phosphorus. The range of net exchange

responses (-0.031 to +0.069 mg/1) indicates that some canals can be

sources of ortho-phosphate to the estuaries, while other canals can be

sinks. The most frequent response was essentially no effect on the

ortho-phosphate concentrations, whereas the mean value (+0.005 mg/1)





-78-


a. Average ebb concentration (ppm) of total P.


15
0
-H
4-1



.. 5
o


.00 .05 .10 .15 .20 .25 .30 .35 .40 .45 .50 .55 .79 .84.87

mg/1

N = 71 Mean = 0.231 Std. Dev. = 0.226 Range 0.014 to 0.867












b. Net change (flood-ebb) of total P.


'15
O -H









-.032
mg/1
mg/1


.012 .022 .032 .063
.007 .017 .027 .043 .093


N = 68 Mean = +0.003 Std. Dev. = 0.030 Range -0.067 to +0.093



Figure 24. Frequency distributions and descriptive statistics for
(a) weighted-average total phosphorus concentrations (mg/1),
and (b) the net changes from average flood concentrations.





-79-


a. Average ebb concentration of ortho-P.


20 -

o 15
o
O *.r
P a 10-
3
ze 5
0

0


.00 .05 .1


I I I I I I I
0 .15 .20 .25 .30 .35 .40 .45 .50
mg/l


Unr


.55 .60 .71


N = 58 Mean = 0.221 Std. Dev. = 0.29 Range = 0.003 to 0.722











b. Net change (flood-ebb) of ortho-P.


20

S15
04-1
o

K 10
oJ>

zo 5
0

0


-.031-.017 -.007 .002 .012
-.028 -.012 -.002 .007

mg/l


.022 .032 .045 .069
.017 .027 .039 .055
.057


N = 56 Mean = +0.005 Std. Dev. = 0.024 Range -0.031 to +0.069


Figure 25.


Frequency distributions and descriptive statistics for
(a) weighted-average ebb ortho-phosphate concentrations
(mg/1), and (b) the net changes from average flood con-
centrations.





-80-


suggests a slight retention of inorganic phosphate by the canals.

Figure 26 shows the frequency distributions and descriptive

statistics for the total organic phosphorus (TP-OP) concentrations and

net exchanges. The organic phosphorus concentrations are.more normally

distributed around the mean value (0.043 mg/l) than are the total and

ortho-phosphorus concentrations. The net organic phosphorus exchange

estimates also exhibit a wide range of values (-0.069 to +0.042 mg/1),

and a mode of essentially zero effect on the organic phosphorus levels

of the estuarine water entering the canals. The mean value (-0.002

mg/l), though, suggests that a net export of organic phosphorus took

place.

The frequency distribution and descriptive statistics for the ebb

concentrations and net exchanges of ammonia for these canals are shown

in Figure 27. The ranges of concentration (0.00 to 0.26 mg N/l) and of

net exchange (-0.18 to +0.08 mg N/1) are wide. The mean value of ammonia

exchange (0.00 mg/l) indicates that the "average canal" has no effect

on the ammonia levels of the estuarine water. The distribution of the

exchange responses shows that some canals are sources of ammonia to

the estuary, whereas other canals are sinks.

The distributions of the average ebb turbidity levels and the net

changes in turbidity levels from ebb to flood tide for these.canals

(Figure 28), show the ranges of values and of effects on the flooding

waters. The mean net change value (+0.2 NTU) suggests that the "average

canal" lowers the turbidity level of the estuary. But the range of

values (-2.1 to +5.0 NTU) show that canals can either decrease or

increase the turbidity levels of the entering water.






-81-


a. Average ebb concentration of organic P.


0
4 10


u 5
o
0


.00 .01 .02 .03 .04 .05 .06 .07 .08 .09 .10

mg/l


N = 54 Mean = 0.043


.11 .15 .17


Std. Dev. = 0.033 Range 0.000 to 0.168


b. Net change (flood-ebb) of organic P.


020


Q)
cl5

010
144
0
o '-- ____
S5 -

| 0 T,. r- ,
-.069 -.044 -.023 -.012 -.002 .007
-.049 -.038 -.017 -.007 +.002 .012


.017
.022


.029


.042


-.027
mg/1

N = 56 Mean = 0.002 Std. Dev. = 0.017 Range -0.069 to +0.042

Figure 26. Frequency distributions and descriptive statistics for
(a) weighted-average ebb total organic phosphorus con-
centrations (mg/1) and (b) the net changes from average
flood concentrations.





-82-


a. Average ebb concentration.


.00 .02 .04 .06 .08 .10 .12 .14 .16 .18 .20 .22 .24

mg N/1


N = 71 Mean = 0.08 Std. Dev. = 0.06


Range 0.00 to 0.24


b. Net change (flood-ebb).


-.18 -.10-.07-.04 -.03-.02 -.01 .00 +.01 .02 .03 .04 .08

mg N/1

N = 69 Mean = 0.00 Std. Dev. = 0.03 Range -0.18 to +0.08


Figure 27. Frequency distributions and descriptive statistics for
(a) weighted-average ebb ammonia concentrations (mg/1) and
(b) the net changes from average flood concentrations.


0
t 10

S5
o
0


S15
0


0
" 5






-83-


a. Average ebb value of turbidity.


0 1.0 2.0 3.0 4.0 5.0 6.0 7.0

NTU


N = 50 Mean = 3.4 Std. Dev. = 1.4


Range 0.7 to 6.9


b. Net change (flood-ebb) of turbidity.


0

CO

5
o


-2.2 -1.7 -1.2 -0.7 -0.2+0.2 0.7 1.2 1.7 2.3

NTU

N = 48 Mean = +0.2 Std. Dev. = 1.1 Range -2.1 to +5.0


Figure 28.


Frequency distributions and descriptive statistics for
(a) weighted-average ebb turbidity levels (NTU) and (b) the
net changes from average flood concentrations.


14
0



z
-


0
' 10

5

0
,x9
o






-84-


Diurnal Cycle of Nutrient Concentrations


A diurnal cycle of nutrient concentrations in the canal and bay

waters could influence the estimates of the net direction and magnitude

of exchange. If a diurnal cycle were superimposed on the tidal cycle,

a bias in the estimate would result, particularly for those canals

where essentially only one ebb and one flood tidal phase occurred

during the 24 hour period. For example if planktonic primary production

during the daylight hours raises the levels of organic carbon in the bay

and canal waters, and if water continually floods into a canal during

the day, the rising levels of organic carbon would be recorded as

increasing flood phase concentrations. Then as photosynthesis stopped,

the tide reversed, and respiration continued, a decreasing organic

carbon concentration would be recorded for the ebb tidal phase. That

canal would be labelled a sink for organic carbon. Conversely a canal

could mistakenly be labelled a sink for organic carbon, when in fact

only a diurnal cycle was observed, superimposed on a tidal cycle having

predominantly ebb phase during daylight.

To determine whether diurnal cycles were occurring for the exchange

parameters that could bias the results, the mean concentrations of the

response parameters for all observations were regressed against the

hour of the day, transformed with a sine function. The transformation

(sin (0.2618 (Time 12))) was used so that a sunusoidal function with

a period of 24 hours, the minimum value at 0600 hours, and the maximum

value at 1800 hours, would result and would coincide with the diurnal

cycle. The results of these regressions are summarized in Table 8.

The only parameter observed to have a significant diurnal component





-85-


Table 8. Regression coefficients for the change in nutrient concen-
trations versus time of day (transformed). Model y =
Intercept + Slope (NTIME).

,t 2
Parameters Number of Intercent Slope Probability R
y Observations Slope # 0

Total carbon 1105 38.77 -0.035 0.92 0.00

Inorganic carbon 1103 20.80 -0.24 0.45 0.00

Total organic carbon 1101 17.97 0.19 0.60 0.00

Total phosphorus 1108 0..253 -0.0010 0.91 0.00

Ortho-phosphorus 1102 0.214 -0.0018 0.84 0.00

Total organic P 1065 0.043 0.0007 0.68 0.00

NH3 1107 0.086 -0.012 0.0005 0.01

Turbidity 951 3.61 0.16 0.16 0.00

Color 850 104. 3.1 0.36 0.00

Conductivity 532 31.7 0.69 0.86 0.00



aTransformation: NTIME = sin (0.2618 (Time 12)), Time 0-24 hours

Units: as in Table 2





-86-


to the mean concentrations was ammonia. The rate of change of ammonia

concentration per unit transformed time is -0.012 mg/l (non-linear on

an hourly basis). The transformed values of the hour of the day ranged

from -1.0 at 0600 hours to +1.0 at 1800 hours. Therefore by stustituting

these values into the linear equation (Table 8), it can be seen that

the mean ammonia concentration tends to be 0.012 mg/l greater at sun-

rise than at noon, and 0.012 less at sunset than at noon. This results

in an expected change in ammonia concentration of 0.024 mg/1 from

sunrise to sunset, attributable to a diurnal cycle.

The lack of a significant diurnal effect on nutrient concentra-

tions, except for ammonia, suggests that a serious bias is not intro-

duced by neglecting the time of day for tidal phases. The possible

bias associated with a diurnal ammonia cycle and the estimated net

movements of .ammonia across the canal mouths is limited to Gulf Coast

canal observations that met the conditions given above. The Atlantic

canal systems generally experience semi-diurnal tides.



1975 Data


The nutrient exchange results obtained during the first phase of

this study, wherein four pairs of canals (PG, PC, LX, and PB) were

sampled on four occasions, provide information on the seasonal changes

and on the variabilities between canals that appear identical. The

two-way design (4 locations x 4 seasons, with replication) of this phase

of the study allowed analyses of variance to be performed on the data

in order to test for significant location and season effects. The

nutrient exchange data from the 1975 work are included in Table 7.





-87-


The mean net changes of total organic carbon, total organic phosphorus,

and ammonia concentrations for the four locations (PG9, PC9, and PB9

not included) and four sampling periods are shown in Table 9. The

descriptive statistics and significant factor effects (as determined

by analyses of variance) for the 1975 data are presented in Table 10.

No significant location or season effect was detected for total

organic carbon and ammonia exchange levels for these four locations

(Table 9). It may actually be that there were organic carbon and

ammonia exchange differences between these locations and seasons, but

the large amount of variability within the pairs of canals and the small

sample size (2 canals per location) prevent the detection of small dif-

ferences in mean values.

For the total organic phosphorus (TP-OP) exchange data, there were

significant differences between the mean values. The significant month

x location interaction effect indicates that both location and season

did affect the organic phosphorus exchange activities, but that the

effect of season depended on location. The organic phosphorus exchanges

between canals and estuaries did change with season, but the magnitude

or direction change varied with canal location. For example, the

mean net export of organic phosphorus from the Pompano Beach canals

increased from 0.008 mg/l in September to 0.010 mg/l in November,

whereas a mean net export (0.011 mg/l) or organic phosphorus from the

Port Charlotte canals in September, had shifted to a net import of

0.009 mg/l in November.

Even though differences between the organic phosphorus exchange

activities among these canals were detected, the variability within

the pairs of similar canals was rather large. The mean value for these




Full Text
-92-
Table 11. Nutrient/water quality exchange results for three consecu
tive days at the North Miami site.
Date
DTC
DIC
DTOC
DTP
DOP
DTOP
26 Oct 76
-0.4
0.6
-1.0
0.000
-0.002
0.000
27 Oct 76
1.1
-0.4
0.4
0.004
0.003
0.001
28 Oct 77
0.3
-0.4
0.7
-0.001
0.000
-0.001
Mean
0.3
1
o
I*
0.0
0.001
0.000
0.000
Std. Dev.
0.7
0.6
0.9
0.003
0.003
0.001
Date
DNH3
DTURB
DCOLOR
DCOND
26 Oct 76
.01
0.0
3
2
27 Oct 76
.03
0.1
7
-4
28 Oct 76
-.03
0.1
-3
-4
Mean
0.00
0.1
2
-2
Std. Dev
0.03
0.1
5
-3
Nomenclature and units as in Table 2


Table 24. (Continued)
Correlation Coefficients Between Physical Characteristics Variables and Canonical Variables
SUN
LENGTH
WIDTH
MDEPTH
AREA
VOLUME
SILL
DEVEL
AGE
BULK
CURBS
SEWERS
TIDE
MINRES
CUMTIDE DAYL
1
0.26
0.58
0.80
0.30
0.53
0.57
0.06
0.28
0.27
0.43
0.34
0.75
0.57
-0.33
0.23
-0.24
2
0.67
-0.14
0.17
0.12
-0.05
-0.05
-0.35
0.30
-0.44
0.24
0.45
-0.06
-0.38
0.00
-0.54
0.12
3
0.11
0.03
-0.06
-0.28
0.11
0.12
0.21
0.32
0.00
0.29
0.00
0.34
0.17
0.28
0.27
-0.49
4
0.03
0.02
-0.37
-0.24
-0.04
-0.21
-0.34
0.12
0.08
0.31
-0.27
-0.38
0.50
-0.80
0.66
-0.02
5
0.06
-0.01
0.09
0.47
0.00
-0:12
0.48
0.47
0.67
-0.02
0.30
-0.28
0.26
0.23
0.18
-0.11
6
-0.50
-0.13
-0.06
-0.35
-0.10
-0.05
0.06
0.13
0.12
0.19
0.32
0.17
0.06
-0.03
0.01
-0.46
7
-0.35
-0.47
-0.08
0.26
-0.52
-0.48
-0.11
0.34
0.04
0.32
-0.25
0.12
0.08
0.06
0.06
-0.14
8
0.07
-0.42
0.08
-0.03
-0.40
-0.27
0.13
-0.58
-0.32
-0.25
-0.05
0.07
-0.07
0.09
-0.09
-0.58
9
0.10
-0.25
-0.16
-0.09
-0.23
-0.18
-0.18
0.03
0.17
0.15
0.26
-0.15
0.33
-0.01
0.24
0.00
-135-


-13-
Thurlow (1974) examined the water quality and sediment character
istics of four canal developments in New Jersey. He concluded that each
canal system was unique and that depth had a major influence on water
quality, particularly on the bottom water quality. Canals with sills
were "more polluted" at points remote from the entrances. Accumulations
of nutrients and heavy metals plus, anaerobic conditions were observed
in excessively deep areas. Water quality was similar in old and new
canals, even though the new canals were deeper. Canal developments
with homes utilizing septic tanks had better water quality than those
with a sewage treatment plant whose effluent was discharged into the
canals. The water quality was best in the canal system that had a
sewage treatment plant and a remote discharge point. Thurlow recommended
canal depths of 8 to 10 feet, maintenance dredging of sills, sewered
developments with remote discharge points, and the reductions of organic
inputs to the canals, in the use of lawn fertilizers, and in the sub
stitution of stones for lawns.
Two groups of investigators at the University of Florida (Piccolo
et al., 1976 and Fox ejt al., 1976) jointly examined four pairs of
similar canals at different locations in Florida, on a seasonal basis.
Piccolo e_t al. provided the hydrography of the canals and a pollutant
dispersion model. Fox ej: al. reported the water and sediment chemistry,
the metabolism levels, the phytoplankton and benthic invertebrate
populations, the canal-estuary net nutrient exchanges, the benthic
oxygen demand, and the hydrocarbon levels of the canals. They concluded
that canals constitute complex and variable systems. The individual
canals within the essentially identical canal pairs (directly adjacent)
often had dissimilar attributes. Not all canals had poor water quality.


-310-
CRRELATICN COEFFICIENTS / PRub > |R| UNDER H0:RH=0 / NU
Mb EK OF OBSERVATIONS
SUN
DEVEL
0.20 482
0.1300
56
SEWER S
0.2 0469
0.1302
56
SECLHI
-0. 19043
0.1 698
bo
VOLUME
0.18878
0.1635
56
DTP
0.18266
0. 1995
5 1
LENGTH
0 16064
0.2363
56
ETURB
0.15695
0.2867
48
MAX DO
0.151 06
0.2664
56
OTC
-0.15082
C.2908
5 1
PG PPM 2
0.14230
02955
56
DT P
- 0.1 31 62
0.3572
51
UA Y
0.12608
0.3545
56
FTURB
0. 12353
0.4 029
48
PPR M3
0.11321
0.4061
56
TGPP
0.10948
0.4219
56
TIDE
- 0 1056 6
0.4383
56
ETOC
0. 1 0 G 62
0.4735
53
DT U C
-0. 09277
0. 5173
51
CUMTIDE
-0.09207
0. 4997
56
F TOC
0 .06471
0.6452
53
ENHJ
0.0603 1
0.6680
53
FNH3
0.06031
0.6680
53
YEAR
0.04694
0.7202
56
PGPPM3
0.04376
0 74 88
5o
DCCJND
-0.040 75
0. 8500
24
TEMP
0.03792
0.7814
56
ECULOR
0.03316
0.8390
40
TR
0.0294 7
0.8293
5o
P PR
- 0 .0 2 8 62
0.8341
56
MINRES
-0.025 1 1
0.8543
56
PCULK
-0.0 l 92 8
0.9060
40
DT.Ukb
C 016 7o
0. 9120
46
T PR
0.01222
0.9301
54
DIG
-0.00754
0.9561
51
DCULUR
-0 .0 0046
0.9978
4 0
AYL
DAY L
1.00000
0.0000
74
T EMP
0.73721
0.000 l
73
PPR
-0.46267
0.00C3
5o
MUNTH
-0.36156
0. 00 06
74
SUN
0.34969
0. 0062
56
FTURB
-0.32472
0.0214
50
ETURb
-0 .28764
0.04 2 8
50
PR M2
0 .2 7 768
0.0383
56
true
-0 .2o79 9
0.0239
7 1
F IOC
0.2 5u5 3
0.0306
71
Ti DE
-0.25454
0.026o
74
T PR
-0.25338
0.0645
54
PDOMIN
- 0. 22864
0.0963
54
TR
0.22641
0.0934
56
DAY
- 0.22373
0 .0553
74
PPRM3
0.21969
0.1036
56
OCOLOK
0.21596
0 1 o 9 6
42
EN H3
-0.2 0982
0. 0791
71
FNH3
0.20962
0.0791
71
OTUKB
-0.20 343
0.1655
48
BULK
-0.1 93 79
0.1161
6 7
FTC
-0.19300
0.1466
58
DOP
0.1909 1
0.1587
56
El o
-0. 1 7054
0.2006
58
DCUND
0.15421
0.4719
24
MUEPTH
-0.15076
0.1997
74
Y EAR
0.15043
0.2006
74
MINRES
0.14243
0.2261
74
FOUND
0. 14 19 1
0.5083
24
CUM1IDE
-0.1 380 7
0.2408
74
TGPP
0.13491
0.3215
56
L CUNU
0.120oc
0. 5 7 65
24
SE W ok 5
-0.11193
0. 3 4 tL 4
74
FTUP
0.09551
0.4921
54
MINO
0.09540
0.4220
73
DNHJ
0.09018
C 4 6 l 2
6 9
AVoDU
0.08892
0.4544
73
D 1 OP
-0.08021
05u0 o
56
U TP
0.08013
0.5160
68
LENGTH
0. 0 78 J<+
0.5070
74
EUP
0. 0 7652
0.5661
58
DEVEL
-0.06680
0.5799
71
ET UP
0.06112
0 66C 6
54
FOP
0.05034
0.7074
56
AG E
-0.04b9o
0. 665 1
7 1
AR EA
C.04604
0.6969
74
SILL
-0.04 1 76
0. 7314
70
DTC
0 .04 171
0.7602
56
PGPPM3
0 .041 1 5
0.7633
56


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CHAPTER 1
INTRODUCTION
Residential canals and canal construction in the coastal zone are
sensitive environmental and political issues in Florida and other
Atlantic and Gulf coast states. Land developers argue that they are
filling a need by providing the public with attractive waterfront
property. Environmentalists and regulatory agencies contend that the
loss of wetlands and shallow estuarine areas outweighs housing benefits.
Regional planners are in a dilemma because the principles governing the
behavior and conditions of canals in the coastal zone and the percentage
of the coastal wetlands that can be developed before the estuarine
systems suffer serious damage are unknown.
The conversion of wetlands (mangrove and salt marshes) and shallow
estuarine areas into waterfront developments via dredge and fill opera
tions proceeded largely unchecked until the early 1970s. Following the
Earth Days of the late 1960s, the public became more environmentally
conscious and, therefore, more concerned about the destruction of
estuarine habitats. A widely circulated 1972 publication by Barada and
Partington, which portrayed residential canals as open sewers and as
sources of toxic materials to the adjoining estuaries, added impetus to
the movement against dredge and fill operations. In response to public
pressures, state legislators imposed a moratorium on dredge and fill
operations in Florida. The federal and state governments became
actively involved in attempts to curtail further dredging in the coastal
-1-


-113-
Summary
These principal component analyses indicate that recurring patterns
for the metabolism levels, nutrient exchange activities, water quality,
and physical characteristic for these canals, are not well defined.
The factors that lead to differences or that account for some of the
variability in the data sets, have been elucidated. The interpretation
of the various factors in terms of the importance or weightings of the
individual parameters, has been successful to varying degrees. Re
duction of the number of variables to a more manageable but still
meaningful number of artificial variables containing most of the
information of the original data sets was found to be unsatisfactory.
Only about 60 percent (80 percent for the metabolism data) of the
variability in the data sets could be incorporated into the best three
linear combinations of the parameters.
This type of analysis describes the structure of single data sets
and defines the important variables contributing to the variability
within the data set. It does not evaluate interrelationships between
the subsets. For example, the general level of metabolism was identi
fied as the most important factor distinguishing the canal metabolic
characteristics; similarly the net exchanges of carbon forms, for canal
nutrient exchange behavior. The dependence or correlation of the
nutrient exchange behavior on the metabolic characteristics of a canal
has not been established. Correlation and regression analyses are
required to evaluate such associations.


-289-
CURRELATIUN CU EFE 1CI ENTS / PRub > |R| UNDER H0:RHU=O / NU
MB ER UF OBSERVATIONS
E TP
DIC
0.291 78
0.029 1
56
FTURB
0.2 881 l
0.042 5
50
TOPP
0.28748
0. 0369
53
MAX D
0.27038
0. 0236
70
FNH3
0.2450 1
0.03 95
71
ENH3
0.24501
0.0395
71
TUP
-0 .24399
0. 0700
56
BULK
0.23303
0.0582
64
Dt VEL
C.22383
0.0665
68
AVLmJ
0.2 2 32 2
0Oo32
7 0
FT OC
0.2 04 06
0.0869
7 1
SEcem
-0.20001
0.1358
5 7
MINRES
-0.19578
0.1018
71
PPR M 3
0.19501
0.1617
53
LEO TH
0. 1 9479
0.1036
71
truc
0. 18472
0.1230
7 1
C CU NU
0.14561
0.4972
4
VOLUME
0. 1 34 0 1
0.2652
71
PRM2
0.13327
0.34 14
53
AREA
0.13107
0. 2759
7 1
TPR
-0.12583
0.3790
51
UT OC
0.12044
0.3242
69
PDUMI N
-0.11589
0.4 180
5 1
MDEPTH
-0.11360
0.3455
71
T 1UE.
0.11158
0.3542
71
PGPPM3
G 10539
0.4526
53
DTURD
0.09306
0.5293
46
S l LL
-0.07954
0.5223
67
YEAR
- 0.06620
0.5833
71
UT C
-0 C5879
C .6669
56
CUMT IDE
-0.05458
0.6512
7 1
AGE
0.04252
0. 73Gb
68
PGPPM2
-0.0 4 l 87
0. 7659
53
CURBS
-C.03179
0.7924
71
DNH3
0.02506
0.8381
6 9
TEMP
0 .02504
0.8370
70
PPR
-0.02 053
0. 884 0
53
MimTH
0.01941
0.8724
7 1
DC UL UR
-0 .0 1 4 1 J
C.9292
42
M I NU U
-0.00958
0.9373
70
DTP
-C.00371
0.9760
68
DA YL
-0.00221
0.9854
7 1
TP
DTP
1 .00000
0.0000
68
UP
0.7120 7
0.0001
5 6
DT UP
0.60 1 03
0.0001
56
DCND
-0.26738
C.2065
24
F T UP
0.2 32 73
0.0969
52
DI C
0.22928
0 .0892
56
ENH3
-0.20159
0.0993
68
F NH3
-0.201 59
0.0993
68
DT C
0.1 966 1
0.1464
5 6
3 E W E K S
C.19ol3
0.1089
68
LTURB
-0. 1 92 13
0.1908
4b
SUN
0.18266
0. 19 95
51
TGPP
-0.17322
0.2241
5 1
E IC
0.15635
0.24 98
56
DC UL OR
0.15360
0.3314
42
AGE
-0.15199
C.2231
6 6
ECUNU
0.139/4
0.514^
24
TR
-0.13912
G 3 3 0_
51
MUN lh
-0.1 368 7
0.2657
68
ETC
-0.13599
0.3176
56
ET P
-0.12966
0.3595
52
F I C
-0.12443
0.3609
56
OTUC
0.12311
0.3172
68
PDUMI N
0. 12037
C .4100
49
VULUME
0.11424
0. 3 5 36
oo
M AXDU
-0.1 1275
0.30 36
67
FT C
-0.11275
0.4080
56
AVGD
0.11248
0.3648
67
FTP
0.10999
C.3719
68
MINU
0.10459
0.3996
67
SECCUl
0.10409
0.4495
55
AREA
0.1 0326
0.4020
68
FCUND
C.10143
0.6372
24
AI DTH
0.09587
0.4368
68
FTURB
-0.09342
0.5277
4 8
CUMTIDE
0.08654
C .4828
68
DT UR B
0.0834 8
0.5/27
4 8
PGPPM3
-0.0 3 3 3
0.5657
5 l
UAYL
0.0 80 13
0.5160
68
L ENGTH
00 7424
0. 54 74
t>8
BULK
0.0734 7
0.5704
62
DE VEL
0.06695
0.5962
65


-64-
Table 5. Community and plankton gross primary production (g 0 /m -day)
means for the four locations sampled in 1975, averaged by
location, by season, and by distance along canal.
TGPP
PGPPM2
TPR
PPR
Means by Location
PG
3.74
1.85
1.56
2.11
PC
10.5
4.87
1.71
2.35
PB
8.48
6.43
0.98
2.39
LX
6.15
3.46
1.18
2.44
Std. Dev.
2.92
1.96
0.34
0.15
Means by Month
March
5.13
4.78
0.94
2.55
June
6.63
4.16
0.98
1.21
September
11.2
4.47
1.32
1.92
November
5.53
2.89
2.34
3.40
Std. Dev.
2.79
0.83
0.65
0.93
Means by Distance Along Canal
Bay
5.33
2.53
1.29
3.23
Frong
6.68
3.96
1.11
2.27
Middle
8.28

1.16

Back
8.20
4.40
1.87
2.07
Std. Dev.
1.40
0.98
0.35
0.62
Grand Mean
7.18
3.98
1.36
2.31
Nomenclature as in Table 2
2
Units g 0 /m -day


LIST OF FIGURES
(Continued)
Figure Page
17. Frequency distribution and descriptive statistics for
planktonic respiration (g C^/m^-day), averaged by
canal 56
18. Frequency distribution and descriptive statistics for
total community production:respiration ratio, averaged
by canal 57
19. Frequency distribution and descriptive statistics for
planktonic productionrrespiration ratio, averaged by
canal 57
20. Frequency distribution and descriptive statistics for
plankton domination of community production. ....... 59
21. Frequency distribution and dscriptive statistics for
(a) weighted-average ebb total carbon concentration
(mg/1), and (b) the net change from average flood
concentrations 74
22. Frequency distribution and descriptive statistics for
(a) weighted-average ebb inorganic carbon concentrations
(mg/1), and (b) the net changes from average flood
concentrations 75
23. Frequency distribution and descriptive statistics for
(a) weighted-average ebb total organic carbon concen
trations (mg/1), and (b) the net changes from average
flood concentrations 76
24. Frequency distribution and descriptive statistics for
(a) weighted-average total phosphorus concentrations
(mg/1), and (b) the net changes from average flood
concentrations 78
25. Frequency distribution and descriptive statistics for
(a) weighted-average ebb ortho-phosphate concentrations
(mg/1), and (b) the net changes from average flood
concentrations 79
26. Frequency distributions and descriptive statistics for
(a) weighted-average ebb total organic phosphorus con
centrations (mg/1), and (b) the net changes from average
flood concentrations 81
27. Frequency distribution and descriptive statistics for
(a) weighted-average ebb ammonia concentrations (mg/1),
and (b) the net changes from average flood concentrations. 82
x


CHAPTER 4
MATERIALS AND.METHODS
Metabolism
The oxygen metabolism rates for the total canal communities and
the planktonic components were determined for each canal, except Punta
Gorda 9, Port Charlotte 9, and Pompano Beach 9.
Community metabolism was estimated by the free-water diurnal oxygen
method (Odum and Hoskins, 1958, see also Slack et^ al., 1973 for a
detailed outline). This technique assumes that the dissolved oxygen
change from sunrise to sunset in a volume of water can be attributed to
either net oxygen production of the biotic community in contact with the
water, or to oxygen diffusion across the air-water interface. Similar
ly, any change in dissolved oxygen levels from sunset to sunrise is
assumed to be due to either community respiration or to diffusion. By
neglecting or adjusting for oxygen diffusion, estimates of daytime net
production and nighttime respiration are obtained. By further assuming
that the daytime respiration rate equals the nighttime respiration rate,
the total gross primary production and respiration levels for a 24 hour
period can be calculated.
For the .first two sampling trips in 1975 (March and June), dis
solved oxygen profiles were taken every three hours for 24 hours at
four stations along each canal (32 stations on 8 canals). Oxygen values
were determined by Winkler titrations. Mean values for the water column
-40-


TABLE OF CONTENTS
Page
ACKNOWLEDGMENTS. . -. ii
LIST OF TABLES vi
LIST OF FIGURES ix
ABSTRACT xii
CHAPTER 1 INTRODUCTION 1
CHAPTER 2 LITERATURE REVIEW. 6
CHAPTER 3 SITE DESCRIPTIONS 16
CHAPTER 4 MATERIALS AND METHODS 40
Metabolism 40
Nutrient Exchange and Water Quality 42
Canal/Sampling Day Characteristics . 44
Statistical Analyses 44
CHAPTER 5 RESULTS 45
Metabolism 46
Combined Data 46
1975 Data . 58
Daily Variability in One Canal 65
Nutrient Exchange. 67
Combined Data 67
Diurnal Cycle of Nutrient Concentrations. ... 84
1975 Data 86
Daily Variability in One Canal 91
Water Quality 93
Structure of the Data Principal Components .... 100
Combined Data 102
Metabolism 104
Exchange. . 106
Water Quality 107
Canal/Sampling Day Characteristics 110
Summary 113
Canonical Correlations 114
Metabolism vs. Exchange 117
Metabolism vs. Water Quality 120
iv


-12-
wind induced motion and diurnal density induced motion were thought to
be important factors affecting dissolved oxygen distribution.
Adkins and Bowman (1976) provide an informative review of the
impact of canal dredging in the coastal zone, as well as the results of
a two year study on canals dredged in Louisiana marshland for oil
drilling rigs. Fish, blue crab, shrimp, water chemistry, and sedi-
mentology data were presented for open, semi-open, and closed canals,
and for unaltered areas. The greatest number of animals were found in
the unaltered areas. Dissolved oxygen levels remained within tolerance
limits of marine organisms during most of the study, though fish kills
were observed in the semi-open and closed canals (one each).
Burk and Associates (1975) conducted a one day study of water
quality and biota at five stations within a 5,300 acre development off
Lake Pontchartrain, Louisiana. By evaluating the conditions of five
Florida canal developments and reviewing canal literature, Burk and
Associates made several recommendations for improving the future water
quality in the Louisiana development. Recommendations to improve flush
ing and water circulation in the existing canals were to create flow
through systems via culverts and saltwater wells, and to install bottom
aerators or air injection systems. Design criteria for new canals in
the area were to limit canal depths to 6 to 8 feet and canal lengths to
800 feet, to provide sloping sides and smooth bottoms in the canals, to
allow canals to be as wide as possible, and to align the canals with
the prevailing winds. Other recommendations included the construction
of grassy swales in the development, the establishment of natural
vegetation buffer zones between homes and canals, and the spray-
irrigation of the sewage treatment plant effluent onto the local golf
course.


-90-
Table 10. Descriptive statistics and analyses of variance results for
organic carbon, organic phosphorus, and ammonia data;
4 locations x 4 seasons x 2 canals per location.
TOC TOP NH3
Mean
+0.0 -0.005 -0.01
Standard Deviation
(unadj usted)
2.0 0.022 0.05
Range
-3.5 to +5.7 -0.069 to +.042 -0.18 to 0.08
Significant Factor
Effects (Anova, a < .05)
None Month x Location None
Within Paired-Observation
, Standard Deviation
(adjusted)
0.014
R2
39 81 62
N = 29


-165-
water temperature, Secchi depth, and oxygen values constituted the
water quality data set. Of these parameters, the dissolved oxygen
levels are most frequently used as an indication of water quality and,
therefore, will be discussed most fully.
The distributions of the average and minimum dissolved oxygen con
centrations are shown in Figure 29. To ascertain whether these canals
violated the E.P.A. water quality standard of 4 mg/1, one must decide
whether the dissolved oxygen standard applied to the average concentra
tion within the canals or to the minimum value recorded. If the
average oxygen level is used, then 12 percent of these canals were
observed to violate water quality standards. If the minimum values
are used, then 70 percent of the canals violated the standards.
The principal components analysis of the water quality data set
showed that a suitable water quality index for Florida residential
canals could not be generated using the parameters in Table 18. The
best linear combination of the water quality parameters could only
explain 29 percent of the total variability. This small amount of
explained variance can be contrasted to the results of Shannon and
Brezonik (1972), who proposed a Trophic State Index (TSI) for north
central Florida lakes. Shannon and Brezonik sampled the water quality
of 55 lakes and found that once the lakes were categorized as colored
or clear lakes, the first eigenvectors of their principal components
analyses explained 72 and 71 percent, respectively, of the observed
water quality variability among the lakes. The wide geographical dis
tribution of the canals most likely led to the lack of recurring water
quality patterns observed in this study.
Phosphorus concentrations and color values were the most


3 91 -FLUX -SAS -FT ILF 0 01
DBS
MONTH
DAY
YEAR
SI AT I UN
T 1 ME
Z1 D 01
Z2
DO 2
1
3
25
75
LX 1
l 02
C 5
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0.5
4.99
2
3
25
75
LXl
5 19
0 5
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1 .0
5. 73
3
3
25
75
LX 1
730
0 5
. 08
1.0
4. 21
4
3
2 5
75
LA l
10 15
0 4
.85
1.0
4.22
5
3
2 5
75
LXl
1310
0 6
. 1 7
0.5
5. 92
6
3
2b
75
LXl
13 40
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0.5
6. 08
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3
25
75
LXl
1616
C b
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1 .0
6.86
8 '
3
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LXl
1852 .
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6. 39
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3
25
75
LXl
22 0 0
C 6
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0.5
5. 64
10
3
26
75
LX2
1 1 1
0 5
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0.5
4.63
l 1
3
26
75
L X2
527
0 5
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1 0
5.15
l 2
3
26
75
LX 2
74 0
0 4
.95
1.0
4.83
13
3
26
75
LX2
1020
0 5
.35
0.5
4.90
1 4
3
25
7 5
L X 2
1 320
0 6
. 4 7
0.5
b. 26
1 b
3
2 o
75
LX 2
1 3=>0
0 o
.84
0.5
5.74
l 6
3
25
75
LX2
1 625
0 6
.59
1 .2
6.81
l 7
3
25
7 5
L X 2
1658
0 o
.35
0.5
6.4 1
1 8
3
25
75
LX2
22 05
0 6
.20
0 .5
5.81
1 9
3
2 o
75
LX3
1 1 7
0 5
.46
0.5
5.44
20
3
26
75
LX j
53 7
0 5
.04
1 .0
4. 98
2 1
3
26
7 5
Lx j
752
0 5
.23
1 .0
5.40
22
3
26
75
L X 3
10 30
C 5.46
G 5
5.50
23
3
25
75
LX 3
1325
0 5
.59
0.5
5.73
24
3
26
75
LX3
1400
0 b
. 1 7
0.5
6.37
25
3
25
75
LXj
1 630
0 6
.27
1.0
6. 79
26
3
25
75
LX 3
1902
0 6
.53
1 .0
6.28
27
3
25
75
L X5
221 5
C 6
. 1 9
1.0
5. 95
28
3
26
75
L A 4
30
0 5
.64
0.5
4. 92
29
3
2b
75
L X4
440
0 3
.10
1 .0
2.89
30
3
26
75
L X4
64 0
0 5
. 00
2. 0
2. 94
ObS
Z 3
D 03
Z4
DU4
Z5
005
UU 6
007
1
1.0
4.41
1.5
5.2 1
2.0
5.0 1
0
0
2
2. 0
3. 80
0.0
0.00
0.0
0.00
0
0
3
2 .0
3.56
0. 0
0.00
0. 0
0. 00
0
0
4
l .5
4.16
2.0
4.1 0
2.5
3.92
0
0
5
1.0
5. 01
1.5
5.28
2.0
4.7 7
0
0

1.0
6 .2 0
1.5
5.80
2.0
4.88
0
0
7
1 5
6.5 7
0.0
0.0 0
0.0
C .00
0
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8
1.0
6. 52
1 O
3.9 7
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0
0
9
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5.06
1 .5
4.85
2.4
3.09
0
0
1 0
1 0
4.97
1 .5
5 o 5
2.4
* 95
0
0
1 1
2.0
4. 19
0.0
0.00
0. 0
0.00
0
0
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2.0
3.79
0.0
0.00
0 .0
0.00
0
0
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1.0
5. 1 9
1.5
5.31
2 D
3.4 1
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1 .0
6.35
1.5
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6.46
1.5
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4.12
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5.55
1.5
4.9 5
2.5
5.92
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0.0
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5.59
1.5
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2. 5
4.39
0
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1.5
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2.0
' 4.86
0
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24
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6. 93
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6.79
2.2
5.50
0
0
25
2.0
5.4 1
0.0
0.00
0. 0
C. 00
0
0
26
l 5
5.99
2.0
5.8 1
0.0
0.00
0
0
27
1.5
6. 1 0
2.0
6.15
2.0
6.20
0
0
28
1 .5
2.87
2.0
<£09
0. 0
0.00
0
0
2 9
1 .4
3.59
0.0
0 .00
0.0
0.00
0
0
30
2.6
3. 05
0. 0
0.00
0.0
0.00
0
0
Z 7
-212-


-287-
CORRELATIUN C U E F F IC I E N T S / PkUB > |R| UNDER H0:RHU=0 / NU
MUER UF OBSERVATIONS
eruc
PPR
0.1 C596
0.4502
S3
SUN
0.10062
0.4735
53
LUP
-0.09721
0.4760
5o
DTP
0 .08707
0. 5234
56
ETUP
0 .08183
05564
54
M I NDO
0.07900
0.5156
70
MONTH
-0.05828
0.6293
7 1
DTP
-0 00 809
0 3 8 0
68
DIC
-C.05 7 74
0.6725
56
TIDE
005526
0.6471
7 1
DTURB
0.0 5487
0.7l21
4 8
DTC
-0.04256
C.7555
56
F COLOR
-0.0342l
0.8297
42
EOP
-0.0332 5
0.8043
58
DCUND
-0.0 3240
0.8805
24
F UP
0.02852
0.8317
58
ECULUR
-0.024 5
0.8786
42
CUM T 1 DE
-0.02297
0. 8*- 92
7 1
A VGD
-0.02097
0. 8b3 2
70
1 R
0 .0 1972
'0.8885
53
DTUC
-0.01004
0.93 4 8
69
TUC
DTUC
l.00000
0.0000
69
DTC
0.86273
C.0001
56
D 1L
-0.41 750
0.0014
56
F QP
0 .30141
0. 0240
5b
FT CiC
0.2 2 8 5 3
0. 05 89
69
BULK
-0.22497
0.0788
62
PGPPM3
0 .20202
0.1551
51
PGPPM2
0.17947
0.2 076
51
TGPP
0.17477
0.2200
51
F TC
0.16951
0.2117
50
ECCJND
C. 1 6667
0. 43 08
24
W ID T H
0.16728
0. 1 o 95
6 9
PP R
0. 16287
0.2535
51
CURBS
0. 161 71
0.1843
69
FCUND
0. 1 5553
0.4680
24
AGE
0.15381
0.2175
66
DUP
0.14667
0.2742
56
TR
0.14430
0. 31 24
51
DAY
-0.13899
0.2547
69
FTP
0.13469
0.2698
69
FCLUR
0.13410
0.3972
42
DTUR
-0.12564
0.3948
4 6
DTP
0.123 1 l
0.3172
68
YEAR
0.1212o
0.3209
69
E TP
0.12044
0.3242
69
ENH3
C. i Ob 1 7
0.3a 53
69
FNH3
0. 10617
0.3853
69
ECUL OR
O'. 1 0545
0.5063
42
EOP
0.10289
0.4505
56
MUNT H
0. 10092
0.4093
69
DCUND
0.09729
0.6511
2 4
ETURB
O.C 96C4
0. 516 1
48
SUN
-0.09277
0. 51 73
51
SECCH1
-C.08 990
0.5139
55
PR M2
-0 .08398
0.55 7 9
5 t
A VGD
0.08149
0.5 089
68
PDOMl N
-0.06014
C .584 1
49
DEVEL
-0.0 763 9
0 5 J1 O
6o
TPR
0 0 b a 6 1
0.6305
49
PPR M3
0.05543
0 o 9 9 3
51
HINCO
0.05541
0.o 8 36
08
F1C
-0.05409
0.6922
56
SILL
0.05261
0 .6773
6 5
T I DE
-0. C4 00 7
C.7438
6 9
DAYL
0.03/04
07o26
69
MAXU
0.03564
0.7730
68
DT UP
C.0u507
C. 7975
56
AREA
-0.03130
0.7985
69
DNH3
-0.C2899
0.8131
69
E IC
-0 .02889
0.8326
56
VULUME
-0 C2240
0.8550
6 9
TEMP
0.02< 7
0.8582
0 8
LE No TH
-0.0 2141
0.8614
6 9
S E Vv E E 3
0.01477
0.9041
69
MDEPTH
-0.01256
0.9184
69
FTURB
-0.01 1 86
0.9362
48
CUMTI DE
0.011 11
0.9278
69
El UC
-0. 0 1 004
0.9348
69
D COLD tx
0.00921
0. 9538
42
ET UP
0.0 9 1 9
0. 94 84
52
MiNRES
C.005 19
0.9ob2
69
E IL
0 .00207
0.9879
56
FTP
-0 .0 0056
0.9969
52


-187-
accumulate on the bottom; surface water turbulence and flushing may
increase because of enhanced surface flow (see dye flushing studies of
Daiber eb al., 1974) The extent of sill formation depends on the canal
depth and the volume of water flow across the canal entrance. Higher
water velocities will naturally result in greater cross sectional areas
at canal mouths.
Clearly, the canal system's dimensions and the local tidal dynamics
are important factors determining the mixing and circulation within a
canal system. However, if the nutrient inputs to the canal water are
small, the manifestation of poor circulation will not necessarily be
poor water quality. Conversely, if the organic and inorganic nutrient
loading rates are high, canal systems with good mixing and flushing
will not necessarily have good water quality. Better water quality
would occur in canal systems near an oceanic inlet than that in a
similar system on a "polluted" estuary.
Looking at the extreme cases for residential canal design may help
put the various factors in perspective. One design extreme would be to
construct a canal so small and so shallow that it essentially goes dry
at low tide and resembles a tidal creek or embayment. The factors
affecting water quality in this type of canal would be those that affect
shallow-water coastal systems. The other design extreme would be to
construct a large and deep canal system with locks at the entrances.
This isolated type of canal system would have essentially no inter
action with the adjacent estuary and could be managed like an artificial
lake, a reservoir, an aquaculture system, a sewage-oxidation pond, or a
stormwater retention basin.
Most canal systems in Florida occupy the mid-point in this range


Table 20. (Continued)
Normalized vectors associated with canonical variables and correlation coefficients
between individual and canonical variables.
METABOLISM
TGPP
TR
PGPPM2
PRM2
PGPPM3
PPRM3
TPR
PPR
PDOMIN
Normalized Vector
1
0.023
-0.017
-0.015
0.065
0.005
-0.138
-0.264
-0.001
' -0.004
2
-0.009
-0.003
0.039
-0.046
-0.051
0.023
0.002
-0.002
-0.028
3
0.067
-0.104
-0.074
. 0.085
0.041
0.022
-0.453
0.259
-0.133
Correlation
Coefficients
1
0.09
0.37
-0.56
-0.18
-0.49
-0.41
-0.79
-0.65
-0.42
2
-0.70
-0.78
-0.32
-0.59
-0.73
-0.67
0.04
-0.16
0.16
3
-0.28
-0.25
-0.48
0.48
-0.10
-0.23
-0.12
0.26
-0.26
WATER QUALITY
ETC
ET0C
ETOP
EOP
ENH3
ETURB
ECOLOR
AVGDO
MAXDO
MIND0
TEMP
SECCHI
Normalized
Vectors
1
-0.016
-0.005
2.248
-0.510
-0.849
0.117
-0.001
-0.026
0.011
-0.022
-0.002
0.037
2
-0.014
0.016
0.511
-0.563
0.257
-0.018
0.001
0.026
-0.046
0.000
0.017
0.072
3
0.014
-0.010
0.597
-0.615
-0.350
0.077
0.001
-0.018
0.028
0.082
0.021
-0.033
Correlation Coefficients
1
-0.52
-0.42
0.17
0.06
-0.16
0.56
0.16
-0.09
-0.20
-0.20
0.06
-0.10
2
-0.11
0.07
-0.58
-0.64
-0.35
-0.29
-0.41
0.09
-0.73
0.40
-0.41
0.55
3
-0.09
-0.43
-0.24
-0.18
-0.05
0.16
0.16
0.36
-0.07
0.47
0.49
-0.37
-122-


-28-
has concrete bulkheading, while the other (LX6) has sloping sides up to
the dredge spoils on one side and to a mangrove community on the other
side. The unbulkheaded canal has a landfill site at the dead end. The
Loxahatchee River in this vicinity is about one meter deep, is lined
with mangrove trees, experiences uniform semi-diurnal tides, and Is
strongly influenced by freshwater inputs during the wet season.
Marco Island (MI. Figure 6). This large and complex development,
constructed by the Deltona Corporation, is an island separated from the
mainland by the Marco River. Canal Mil is large, extensively branched,
and borders a golf course that is sppay-irrigated with the development's
l
sewage treatment plant effluent. The MI3 canal had received maintenance
dredging the year prior to sampling, as part of a canal design experi
ment by the Marco Island Applied Marine Ecology Station. At the ;time
jof sampling (March) the water in the area was more turbid than during
most of the year due to strong westerly winds that kept the Gulf .of
Mexico turbulent. Some Of the Environmental Protection Agency's data
from Marco Island has been incorporated into this study (canals MIH,
MIJ, MIL, MIM, MIN).
Boca Ciega Bay (BC. Figure 7). Located in the southeast section
of Boca Ciega Bay, this site was the only one that had curbed streets
in the development. The stormwater enters directly into the canals via
I
drain pipes. A large boat marina operates at the end of BC3 canal
(station BC32). Westerly winds from the Gulf of Mexico during the
spring and summer afternoons keep Boca Ciega Bay and the canal entrances
turbulent. Tides in the area have irregular amplitudes and frequencies.
On the sampling day the tidal cycle was diurnal, i.e., one high slack
and one low slack tide in 24 hours.


-116-
canonical variables are generated from linear combinations of the
variables in each data set. These linear combinations lead to the
best-correlated values of the respective canonical variables. Details
of the procedure can be found in statistical texts, such as Morrison
(1967), Cooley and Lohnes (1971), and Blackith and Reyment (1971).
Output from the analysis consists of the series of canonical
variables for both data sets, the canonical correlation between the
paired canonical variables, a test of the significance of the canonical
correlations, the coefficients of the normalized individual variables
in each linear combination, and the correlation coefficients between
the values of the individual variables and the values of the canonical
variables (linear combinations). The coefficients for the individual
variables (normalized to a mean of zero and a standard deviation of
one) in the linear combinations reflect the relative importance of each
variable to the value of the canonical variables. The correlations
between the individual variables and the canonical variables indicate
how well the changes in the canonical variable reflect the changes in
the individual variables. If the canonical variables are considered as
possible indices for the attributes contained in the data sets, then
the coefficients in the linear expressions indicate the most important
variables contributing to the indices, and the correlations between the
individual variables and the indices show how well the indices reflect
the changes in each variable.
When pairs of canonical variables are found to be significantly
correlated, an association or dependence of the two data sets is present
Conversely If no pairs of canonical variables are found to be signifi
cantly correlated, then no overall association or dependence of the two


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a:ucfvcDco'^'N>ioo-ii-vjrvo'-MOUiu.|rv-'iuiUj>o>urN
COOOOOOOOOOCOOOOOOOOOOOOOOOOOO
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rououLr. ojo t cGdNffiui m'Hui>csu:>-(CNUo
OOOOOOOOOOOOOOOOOOOOOOOOOOOOOO
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t c a rv u cr o c u o c u o c >i cr re u o a u c c n. c o rv -M
-'----'U'PPP'PUMvtvP'PO'irO'U'^P'PUPU'ii^piv
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-iCucr:-pc*vo'-f:'CO~ffia^O'C'vr-^avi-p'0>i'jojuj'P--P'C. ao
u w u rv iv cu p ui cr - rv <- >- o p p tr c> tr o ve cr p o' fo a-
'lu f=;oa:.c--^'-*ivo*-r\)>-^'U'04rKf'C*iuiucu'0-vnocx:*-vCffi
it ill i i i i i i i i i i i
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CTOD '-rvoUlO'Ufva NUI -'JaDOJ'-^UMVffi-OMOfvUO
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4>-0^vOtU'J>UUl>-fiaOUlUJ>0"l>IVU'|'N'-Cr^'ON
TP P TUP TUKB Nh3 CULP DS CND
50
OCOOOOOOOCOOOOCOCJOOOOOOOOOOOOO c.
pj>p.p-.ppppp.p.cjcJc*;UUGjoj(>-ui vccPNO'cii-t'CJiV'-oca^iO'ui-ts-uiV'-ovca-vio-U'i-u.rv'-
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o
aaanaoojisaiaafflaacs'iN'iNNsNSvKtffiCsaa 2
-t
1
c
UUuiUUUUuU >
tt CP (X os.-*<
-<
NN'JN>|'>IN>|>ISSNNS>IS'J>l-JSN'JS-.JNi'IN'INS (T|
a a- o o a o C7 o O' o a*. o- o o o- cr o o o o o ct- o o-- 00- o o >
O'
H
rcfocr rrcot'rf'cccccrcc'f >
n n n r r> r o cr a. cr c a cr c u cr a- ir cr a ce a a.1 cr c c ce a c' -1
c
2
C
rviv'iv^--fivroivrvfv*-*- **
fv*-0'Oa*^0'>ia'MC'0'-tUfvr--Puro'-ovc'^0'ui-e'Uifv'- 2
fTi
utiO-u uCjOjo-uiuO-oc U'UUOiUivuO.uo.uuiivrvrvrjrviv
ouivMj'<'e^u^ooo'OuiNUO-iCfciicao'aa -1
r
a n -* m o >- o t*i o -P- o o> lv iv cr u O' u1 u Oj o n o y 0 ci o o:
CrUlPUlPPPPO'O>CnpPNPN0''0'0"JC'U10'CXO'UCru)O'-'J i
O
uistr'-NEaN'CpasPasP'£u''J>-uiO!PPa'jO'sfu
oiavis,icNau'P'iC'ua(r'i>''jaP(*(M/''.(*icooci\) o
n
uoo'-uupasoPcffiO''-os--vaMua -270-


-198-
Godwin, W.F. and T.M. Sholar. n.d. A comparison of dredged and
natural channels in North Carolina estuaries. Unpubl. man., Res.
and Devel. Sect., Div. of Commercial and Sports Fisheries.
Golley, F., H.T. Odum, and R.F. Wilson. 1962. Structure and
metabolism of a Puerto Rican red mangrove forest in May. Ecology
43: 9-19.
Gosselink, J.G., E.P. Odum, and R.M. Pope. 1974. The value of the
tidal marsh. Cent, for Wetland Resources, L.S.U. Baton Rouge,
Louisiana. 30 p.
Heald, E.J. 1969. The production of organic detritus in a south
Florida estuary. Ph.D. Dissertation, Univ. Miami. 110 p.
Heinle, D.R. and O.A. Flemer. 1976. Flows of materials between
poorly flooded tidal marshes and on estuary. Mar. Biol. 35:
359-373.
Lindall, W.N., Jr., W.A. Fable, and L.A. Collins. 1975. Additional
studies of the fishes, macro-invertebrates and hydrological con
ditions of upland canals in Tampa Bay, Florida. Fish. Bull. 73
(1): 81-85.
Lindall, William N., Jr., J.R. Hall, and C.H. Saloman. 1973. Fish,
macro-invertebrates and hydrological conditions of upland canals
in Tampa Bay, Florida. Fish. Bull. 71 (31): 155-163.
Lindall, W.N., Jr., and L. Trent. 1975. Housing development canals
in the caostal zone of the Gulf of Mexico: ecological con
sequences, regulations, and recommendations. Mar. Fish. Review
37 (10): 19-24.
Marshall, A.R. 1968. Dredging and filling, p. 107-113. Ln J.D.
Newsom (ed.), Proceedings of the Marsh and Estuary Management
Symposium, Louisiana State Univ., Baton Rouge.
Moore, D., and L. Trent. 1970. Setting, growth and mortality
of Crassostrea virginica in a natural marsh and marsh altered
by a housing development. Proc. Nat. Shellfish Assoc. 61:
51-58.
Morrison, D.F. 1967. Multivariate Statistical Methods. McGraw-Hill.
338 p.
Nixon, S.W., C.A. Oviatt and S.L. Northby. 1973. Ecology of small
boat marinas. Mar. Tech. Rept Serv. 5, Univ. R.I. 20 p.
Paulson, O.L., Jr., G.F. Pessoney, L. Massey, D. Weaver. 1974.
Reconnaissance of the flushing characteristics and water quality
in coastal canals of the Gulf of Mexico. Dept. Geol., Univ. S.
Miss. 21 p.


-261-
LIS 5
M UN TH
DAY
YEAR
STATi UN
TIME
TC
I C
TOC
751
4
2 l
76
BC3
0
38.2
11.7
2 6.5
7S2
4
2 1
76
bC3
1
34.0
13.3
20.7
7 53
4
21
76
oC3
2
37.5
13.1
24. 4
754
4
2 1
76
bC3
3
25.3
1 3 .4
11.9
755
4
2 l
7 6
UC3
4
37.3
14.6
22.7
7 b b
4
2 l
76
BC3
5
3 6.5
15.0
19. 5
75 7
4
21
76
bC3
6
38.3
14 .0
24.3
755
4
2 1
7 6
bC3
7
38.4
15.3
23. 1
759
4
2 1
76
bC3
8
3 7.7
16.0
2 1.7
760
4
2 1
76
fc>C3
9
3 7.2
16.3
20.9
76 1
4
21
76
UU3
10
3 6.2
15.3
20. 9
762
4
21
76
bC3
1 1
36.1
16.1
20.0
765
4
21
76
bC3
l 2
3 4.9
17.2
17.7
764
4
2 1
76
bCb
13
33.3
13.2
20. 1
76 5
4
21
76
BC3
1 4
33.3
13.2
20.1
7 66
4
21
76
BC3
1 5
34. 2
14.2
2 0.0
767
4
20
76
BC1
1 7
39.2
14.2
25.0
7 6 8
4
2 0
76
BCl
18
35.7
1 4 .4
2 1.3
769
4
20
7b
8C1
1 9
37.0
1 7. 1
19,9
770
4
2 l
76
BCl
6
35.7
13 .7
22.0
771
4
2 1
76
bU
6
38.2
14.2
24.0
772
4
2 1
76
UC1
7
3 7.6
14.2
23. 4
773
4
21
76
uci
8
35.2
1 3 .0
22.2
774
4
21
76
be 1
1 0
35.0
13.0
22.0
7 75
4
21
76
BCl
1 1
36.3
12.5
23. 8
776
4
2 1
76
bC 1
12
38.2
12.5
25.7
7 77
4
2 l
76
tie 1
16
35. 5
12.6
23.2
778
4
2 1
7 6
BCl
1 6
35. 2
12.4
22.8
779
5
1 6
76
HI 3
17
47.7
22 .6
25.1
780
5
16
76
HI 3
1 8
50. 1
23.0
27. 1
UBS
TP
UP
TUP
ruKb
NH3
C UE UR
DS
CUNO
75 1
0.178
0.150
0.028
3.5
0.15
l 7
0. 15
249
7 52
0. 186
0.155
0.031
2.2
0.08
16
0.00
253
753
0.193
0.168
0.025
2.2
0. 15
13
-0. 26
2 61
754
0.207
0.172
0 C35
2.9
0.13
15
-0.26
295
7 55
0. 1 88
0.168
0.020
2.5
0.14
20
-0.22
2 6 1
756
0.203
0.168
0.035
5. 2
0. 15
22
-0. 20
245
75 7
0.199
0.167
0 .032
4.0
0.20
34
-0.20
251
758
0.195
0.169
0.026
2. 5
0. 1 1
2 7
-0.14
251
759
0.192
0.1 73
0.019
2. 6
0.15
22
-0.12
24 7
760
0.195
0.163
0.032
2.8
0.11
25
-0.05
24 l
76 1
0.201
0.162
0.039
1.8
0.06
30
0. 00
257
762
0.193
0.161
0.032

0.11
21
-C 03
246
763
0.202
0.166
0 03 6
4.2
0.1 4
28
-0.04
2 55
764
0.189
0.163
0.02o
6.0
0. 05
14
-0. 07
257
765
0.198
0.1 63
0.035
3.0
0.06
18
-0.11
265
766
0.215
0. 1 64
0.051
3. 6
0. 05
1 7
-0.05
251
767
0.197
0.165
0.032
4.7
0.05
22
-0.02
25 1
768
0.198
0 16.1
0.037
3.4
0.03
1 7
0.07
250
769
0.212
0. 1 65
0. 04 7
3. 7
0. 1 2
32
0.08
251
770
0.193
0.158
0 .035
3.5
0.09
2 l
0.2 7
260
7 7 1
0.195
0.158
0.037
3.4
0.05
22
0.30
260
772
0.185
0.159
0.02o
3 1
0. 14
22
0.30
260
7 73
0.1 92
0.158
0.034
1.8
0.13
20
0.32
256
774
0. 187
0.157
O'. 03 0
3.6
0.03
l 7
0.22
265
7 75
0.200
0.155
0.045
3. 2
0. 03
20
0. 1 5
2 76
776
0.198
0.158
0.C4
4, 0
0.05
3 9
0.00
272
777
0.193
0. 162
0.031
4. 2
0. 09
2a
-0.26
2 79
778
0.201
0.1 69
0.032
6.2
0.05
28
-0. 26
286
7 79
0.128
0.112
0.016
l 1
0.11
88
-0.42
304
7 8
0.149
0.137
0.0 12
1. 3
0.16
72
-0.33
309


-55-
histogram suggests that a bimodal distribution was observed for
planktonic production. No canal actually exhibited the mean value of
2
5 g O^/m -day (values were rounded to nearest integer to construct
the histograms). The plankton production for these canals tended to
2
occur in two levels; a low range of 1-4 g O^/m -day, and a higher range
of 6-10 g C^/m^-day.
The distribution and descriptive statistics of the community and
planktonic respiration are shown in Figure 16 and 17, respectively.
2
Community respiration had a mean value of 8.20 g O^/m -day for the 56
2
canal observations, compared to 3.01 g O^/m -day for the plankton. The
standard deviation and range of the community respiration responses
2
(5.45 and 0.0 to 23.5 g O^/m -day) were greater than those of the
2
planktonic component (1.83 and 0.46 to 7.98 g O^/m -day). The relative
variabilities of respiration are comparable for the total community
and plankton (C.V. = 66 and C.V. = 61, respectively).
The frequency distributions and descriptive statistics for the
primary production:respiration ratios of the total community and
planktonic component, are presented in Figures 18 and 19. The mean
value (1.16) of the 56 community observations suggests that these
systems tend to be balanced or slightly autotrophic. However, the
range of values (0.31 to 2.95) indicate that canals can exhibit both
heterotrophic and autotrophic characteristics. The range of P:R ratios
(0.29 to 5.02) for the planktonic component of the total canal com
munities also indicates that both heterotrophic and autotrophic behavior
exists for the plankton. The mean value for plankton P:R ratio (1.93)
indicates greater autotrophy in the water column than for the entire
canal. From a trophic standpoint the planktonic component is relatively


-325-
CORRLLATION C EFE i C 1 EN T S / PRUU -> |R| UNOtH H0:RHU=0 / NU
Mb ER OF OOSLRVAT IONS
MINRES
AVGDU
-0.1b7 7 7
0.1117
73
TPR
-0.18268
0.1861
5 4
PD Ufa1N
-0.181C 6
0 1 8 7 o
5 4
CURES
C.17549
0.134b
74
S EC CHI
0.16015
0.2216
60
TH
0. 15968
0.2392
56
AREA
-0.15610
0.1785
74
OAYL
0.14243
0.2261
74
T GPP
0.1 392 3
C.306l
5 6
DTUP
0.12787
0.3476
bo
WIDTH
0.11787
0. 31 72
74
FNH3
-0.11500
0. 3 3 96
7 1
ENH3
-0.1l500
0.3396
7 1
ECUND
0.11400
0.5958
24
F C UNO
0.10946
0.6106
24
T UR b
0.10440
0.480 1
48
F TURb
0.09251
0.5228
50
DNH3
0. 0 8b93
0.4775
69
OIL
0.08322
0.5420
56
AGE
C.07970
0.5086
7 l
ET UP
-0.07805
0.5748
54
St v< ER S
0.0 7026
0.5520
74
DT C
0.0 665 6
0.6260
56
UUP
-0.06190
0.65C4
5o
VOLUME
-0.0 4787
0.6855
74
ECULUR
-C .04559
0.7744
42
ETUKb
0.02679
0.8427
50
DCUND
-0.02673
0.9013
24
SUN
-0 .0251 1
0.8543
56
FCULOR
0.02l83
0.8909
42
DTP
-0.02C2o
0.869 7
6 a
M EN TH
-0.0 1652
0.8889
74
MAX EU
0. 01555
0.8 961
73
DEV EL
-0. 01173
0.9226
7 1
TEMP
-0.01 1 30
0.9244
73
FTC
0.00952
0 .943<*
58
POPPM2
0.00944
C.9449
5 6
otul
0.0051 9
0.9662
6 *
F T UP
0.00500
0. 97 1 4
54
P Pk M3
0.00475
0. 9/23
56
FEP
0.00 393
0.9766
56
ETC
0.00098
0.9942
58
UMT10E
CUM TIDE
1.00000
0.0000
74
T IDE
C.620 l 1
0.0001
74
PGPPM3
0.52189
0. 000 l
56
PDUM IN
0.3 61 34
0. 00 73
54
M1 NR ES
-0.33097
0. 004 0
74
AGE
0.29039
0.0140
71
P PR
0 .26855
0.0454
5 6
PGPPM2
0.25937
0.0536
5 6
UE VEL
0.20497
0.0 8 '6 4
7 1
FCUNu
-0.19116
0.3709
24
ECUND
-0.1 8865
0.3773
24
EU LK
0. 1 74 24
0.1585
67
SECCHI
0 1 5 8 93
0.19b9
60
YEAR
-0.15809
0.1765
74
SEWERS
- 0. 15059
0.2003
74.
DAYL
-0.1380 7
0.2408
74
W TUT H
-0.13746
0.2428
74
ETC
0.12717
0. 34 1 4
58
ENh 3
-0.1 226C
0.31 56
69
CURES
-0.11527
0.3281
7 4
F TUP
-0.11404
0.411b
54
F TURU
-0.11059
0.4445
50
FTC
0.11041
0.4093
5 8
tic
0.10348
0.4395
58
MUNTh
-0.09674
0.4122
74
L E -(G T H
0. 0 95 63
0.4167
7*t
SUN
-0. 0920 7
0.4997
56
TPR
0.09125
0.5117
54
D IC
-0.08707
0.52 34
56
DTI5
0.08654
0.4828
68
M AXDU
0.07900
C 5 06 4
73
A V uuu
-C.0 7626
0.5213
73
FOP
-0.07534
C 5 7 4 1
58
£ l URb
-0.06686
0.6446
50
AREA
0 .06366
0.5900
74
D TURB
-0.06079
0.6815
48
F TP
-0.0594l
0.6226
7 1
ETP
0.05458
065 1 2
7 1
P PR M3
C 0 53 a 9
0.69bt
56
DT UP
-0. 04 /16
0.7300
5 o
T R
-0.04652
0.7335
56
DUP
-0.0452 6
C. 7405
5 6


-103-
Table 13. Principal
components of
the combined
data (44 variables).
1
2
3
4
TGPP
0.24
0.16
0.06
0.13
TR
0.17
0.25
0.02
0.13
P GPP M2
0.25
-0.09
-0.05
-0.07
PRM2
0.23
0.04
-0.13
0.06
PGPPM3
0.25
0.07
-0.06
-0.20
PPRM3
0.22
0.11
-0.10
-0.08
TPR
0.17
-0.18
0.05
-0.09
PPR
0.20
-0.12
0.01
-0.17
PDOMIN
0.08
-0.19
-0.15
0.01
DTC
0.01
0.13
0.05
0.09
DTOC
0.05
0.10
0.04
0.09
DOP
-0.06
-0.12
-0.08
-0.13
DTOP
-0.11
-0.16
0.07
0.05
DNH3
-0.02
0.01
0.10
0.15
DTURB
0.04
0.15
-0.11
-0.01
DCOLOR
-0.02
0.19
-0.21
0.01
ETC
0.13
-0.16
-0.21
-0.02
ETOC
0.17
-0.17
-0.06
0.20
EOP
0.17
0.22
0.15
0.11
ENH3
0.13
0.11
0.13
-0.04
ETRUB
0.00
0.21
0.08
0.23
ECOLOR
-0.01
0.31
-0.09
0.03
AVGDO
-0.02
0.05
0.33
-0.15
MAXDO
0.02
0.18
-0.05
-0.08
MINDO
-0.07
-0.10
0.31
-0.17
TEMP
-0.02
0.25
-0.03
-0.20
SECCHI
-0.08
-0.26
-0.02 '
0.04
ETOP
0.13
0.20
0.08
0.12
SUN
0.05
0.06
0.23
0.03
LENGTH
0.13
-0.10
0.25
-0.01
WIDTH
0.14
-0.02
0.23
0.27
MDEPTH
0.10
-0.13
-0.21
0.28
AREA
0.12
-0.13
0.26
-0.00
VOLUME
0.14
-0.14
0.24
0.09
SILL
0.08
-0.05
-0.16
0.28
DEVEL
0.19
0.00
0.04
-0.10
AGE
0.23
0.01
-0.11
0.00
BULK
0.17
-0.07
0.09
-0.11
CURBS
0.08
-0.05
0.14
0.15
SEWERS
0.13
-0.18
0.14
0.22
TIDE
0.27
-0.07
-0.05
-0.15
MINRES
-0.08
-0.04
-0.13
0.34
CUMTIDE
0.22
-0.07
-0.15
-0.23
DAYL
-0.11
0.18
0.14
-0.12
EIGENVALUES
8.43
6.02
5.71
4.27
PORTION
0.19
0.13
0.13
0.09
CUM PORTION
0.19
0.32
0.45
0.55
Nomenclature as in Table 2


-70-
Table 7. (Continued)
C M
A
0
Y
F
D

N
N
0
E
F D
F
D T
T
F
D
F
B
A
T
A
A
T T
1
I

T
T
0
5
L
H
Y
R
C C
C
C C
C
P
P
P
24
PB6
9
7
75
41.3 -
0.4 26
.6 1.9 15.0
1
.5
0 .254
-C.016
0.206
2b
LX3
9
12
75
50. 1 -
0.3 32
.7 0.8 17.4
-l
. 1
0.051
-0.002
0.063
26
LX6
9
1 2
75
49.1 -
0.1 33
.1 0.4 16.0
-0
.4
0.048
-0.009
0.058
27
PG6
1 1
21
75
33. 2 -
0.9 18
.5 -0.4 14.7
-0
.5
0.296
-0.030
0.257
28
PG3
1 1
21
75






'
29
PG9
1 I
21
75
34.0 -
0.4 15
.6 -0.S 18.4
0
.7
0.382
0.012
0.356
30
PC3
1 1
23
75
34.4
1.2 21
.5 0.4 12.7
0
. 6
0.349
0. 007
0.303
31
PC 6
1 1
23
75
35.1
0 .0 18
.0 0.0 17.1
0
.0
0.332
0. 022
0. 296
32
PC 9
11
23
75
34.3 -
1.1 19
.9 0.5 14.4
-l
.6
0.346
-0.0 1 l
0 .283
33
P86
1 1
14
75
57.8 -
0.1 41
5 1.3 16.2
-1
. 5
0.236
-0.014
0.203
34
PB9
1 I
l 4
75
5 7.0
0.7 42
. 1 -0.5 14.9
1
.2
0.224
-0.012
0.196
5 b
PB 3
1 1
14
75


...




36
LX3
1 1
1 6
75
49. 4
6.2 34
.0 1.5 15.4
4
6
0.057
0. 003
0.016
37
LX 6
1 1
1 6
75


... .




38
Mil
3
24
76
39.0 -
5.4 23
*3 O.b ib.6
-5
.9
0.067
-0.016
0.043
39
M I 2
3
24
76
36.9 -
1.6 22
.1 -0.9 14. 7
-0
. 7
0.064
0.004
0.043
40
MI 3
3
24
76
3 5.8 -
0.4 24
.2 0.3 15.5
-0
.7
0.082
0.029
0.044
4 1
BC1
4
20
76
36.4
0.9 13
.7 1.2 22.7
-c
. 4
0.193
-0.004
0. 1 58
42
BC 2
4
20
75
3 8. 1
0.9 12
.7 -0.1 25.3
0
.9
0.210
0.008
0.166
43
BC3
4
20
76
37. 5
2.4 12
. 1 2.2 25.4
4
.8
0.184
-0.010
3.159
44
H11
5
1 9
76
49.9
1 .8 21
.1 0.5 2 8.9
1
. 4
0.063
0. 01 1
0. 044
45
HI 2
5
19
76
42.0 -
0.6 16
.4 -1.0 236
0
.2
0 .041
0.002
0.025
46
HI 3
5
1 9
76
47.8
2.5 22
.4 0.3 25.4
2
. 1
0. 120
-0.003
0.104
F
D
F D
C
C
F D
F
0
F
D T T

0
C C
0
D
T
T
N
N U U
L
L
0
B
O
O

H
H R R
0
0
N N
S
P
P
P
3
3 b B
R
R
D D
24
0
0 1 2
0.
048
- 0.004
0.06
-0.184.2 0.
7
112
7

25
-0 .
01 C
0.
000
0.000
0.06
0.03 4.5 -0.
3
124
3

26
-0.
009
0.
000
0.000
0.02
0.03 4.1 0.
2
1 1 5
18

27
-0.
031
0.
038
0.001
0.07
-0.02


28




. .


29
c.
0 14
0.
026
-0.002
0.01
-0.07 .


30
0 .
003
0 .
045
0.003
0.21
0.0 1


31
0.
019
0 .
036
0.004
0.06
C .10 .


32
-0 .
029
0.
0 64
C. 01 9
0.04
0.04 .

33
-0.
002
0.
031
-0.014
0.23
0.00 .


34
-0.
007
0.
028
-0.005
0.23
C. 0 2 .


35




. .


36
0.
004
0.
041
0.000
0 .05
0 .0 1


37




. .


38
-0 .
01 3
0.
025
-0.003
0.10
-C.01 5.7 0.
9
35
2
345 -2
39
0.
002
0.
021
0.002
0.06
0.0 1 3.0 -0.
1
1 4
- 12
343 -8
40
0.
0 1 1
0.
037
0.017
0.05
0.02 4.1 0.
4
26
-13
337 -14
41
-0 .
007
0.
034
0.003
0 .05
0.02 3.1 -2.
1
2 1
-7
260 -20
42
-0.
002
0.
044
0.010
0.15
0.00 5.4 0.
8
2 1
5
274 9
43
-0.
009
0.
025
-0.005
0.10
0.03 2.6 0.
5
1 2
-8
268 9
44
0 .
01 1
0 .
019
0.000
0.14
0.04 1.0 0.
0
52
-2
307 -23
4b
0.
0 02
0.
C 16
0. 000
0.12
0.03 0.5 0.
2
25
- 18
376 21
46
-0 .
003
0 .
016
0.000
0. 11 -0.02 1.2 0.
1
69
4
294 -5


LIST OF TABLES
(Continued)
Table Page
34. Significant factor effects on canal-estuary net
exchange parameters. 176
35. Physical characteristics, water quality, metabolic
levels, and net canal-estuary exchanges for an "average"
residential canal 180
viii


1
2
G.
' X 12
f ¡I!
§
fill
I *
M
m
Figure 6. Canals and sampling stations at the Marco Island site.


-154-
frequency in the net exchange models than do the other factors.
It should be emphasized that these factor rankings are based on
the inclusion frequencies in the models, and not on the magnitudes of
the factor effects on the response parameters.


-148-
standard deviations equal to the unexplained standard deviations shown
in Table 27. Substitution of explanatory variable values for other
existing canal systems or proposed canal systems into the expressions
will result in response parameter estimates for those systems. Then,
by observing the incremental changes in the response parameters when
different values of the explanatory variables are substituted, the
effects of a proposed design change can be assessed. Using the un
explained standard deviation for each expression and standard statistical
methods, confidence intervals for parameter estimates can be obtained.
These models clearly show that canal behavior and condition cannot
be readily predicted on the basis of one or two simple factors. At
least seven significant factors are included in each of the twenty
multiple variable models (except PDOMIN and DOP). Multiplicative
interaction terms are included in all models. None of the independent
variables appear in every model.
The important factors determining the levels of the twenty indi
vidual response parameters are included in the individual multiple-
variable models. Patterns for the important factor effects are dif
ficult to extract from the twenty models. To aid in identifying which
factors are most important in determining overall canal behavior and
condition, the twenty response parameters were grouped into three
categories; metabolism (TGPP, TR, PGPPM2, PGPPM3, PPRM3, TPR, PPR,
PDOMIN), exchange (DTC, DTOC, DOP, DTOP, DNH3, DTURB, DCOLOR), water
quality (AVGDO, MAXDO, MINDO, SECCHI). The significant-factor fre
quencies in the three categories are tabulated in Table 28.
No single dependent variable stands out as the predominating
factor in any of the three categories. The total carbon concentration


-305-
CORRELATICN CQEFFll1LNTS / PKb > jRj UNDER HO:KHO=0 / NU
MQER OF OQSERVAT IONS
T A
YE AR
0 08t>66
0.5254
56
MONTH
-0.07530
0.5813
56
DCUND
C.07337
0.7333
2a
bULK
00 640
0.6352
56
F CLUR
C.06060
0.7103
40
AV GDG
0.06059
0 .6573
56
DIC
-0.05833
0.6843
5 1
SEVERS
0.C5380
0.6937
56
FT C
0.05283
0.7071
53
CUMTiuE
-0.04652
0.7336
86
ENH3
0.04507
0. 7486
53
FNH3
0.04507
0 74 66
53
FTC
0.03379
0.8102
53
SUN
0.02947
0.6293
5
Drop
0.02249
0.8755
51
FI C
-0.02234
C.8738
53
E 1 C
-0 .02234
0.8738
53
ECULUR
C. 02154
0.8950
40
ETUC
0.019 72
0.6885
53
ETC
0.01493
0.9155
53
DNH3
0.0005 7
0.9968
51
PGPPM2
PGPPM2
l .00000
0.0000
56
P6PPM3
0.77093
0.000 1
56
PRM2
0.b348 3
0 COO 1
56
PPR M3
0. 54764
0.0001
56
PDDM 1 N
C. 53 0 1 4
0.0001
54
FTUC
0.499 6 7
0 boo 1
53
AGE
0.48933
0.0C0 1
56
T GPP
0.48033
0.0002
56
TIDE
0 ..4731 5
0.0002
56
ETUC
0.45625
0.0006
53
MAXDU
0.40698
0. 001 9
56
DEVEL
0.40679
0 C 0 1 9
56
T PR
0.3889 1
0.0037
54
ECONO
-0.38260
0 .0650
24
FOUND
-O'. 38 l 24
0 .0660
24
FTC
0.37071
0.0063
53
PPR
0.35336
0.007o
50
ETC
0.35240
0.0097
53
MDLPT H
0.32456
0.C147
56
S ILL
0. 3190 4
0.0165
56
CUR8S
0.31605
0.0176
56
ECLUR
-0.29865
0.06 12
40
TH
0.279 77
0.0368
56
FCOLUK
- C. 26920
0. 0930
40
C LM T I DE
C.25937
0.0536
56
F UP
0.2441b
C.0781
53
VULUME
0.23429
0.0822
56
MON TH
-0.20021
0.1390
5 6
WIDTH
0.19916
0.1412
56
YEAR
0.19408
0.1518
56
DT U
0. 18 93 A
0.1833
51
bU LK
0.1 85 78
0.1704
50
u r uc
0. 179 4 7
0.2076
8.1
DNH3
-0. 1 596 7
02o31
51
AR EA
0.153 78
0.2578
56
SUN
0. 14230
0.2955
56
OTUP
0.13671
0.3388
5 l
ETUftb
-0.13650
0.3549
48
SEWERS
0.13289
C. 3289
5b
LENGTH
0.1327b
0.32 93
56
DTUR
0.12495
0.4080
46
F 1C
-0.11394
0.4166
53
SECCH1
-0.10639
0.4352
56
EIC
-0.10093
0.4721
53
DIC
0.0 94oo
0.5078
51
DUP
-6.0897o
0.5310
51
AV G Du
0. Ocil 4
0.5306
56
ET UP
0. Co 02 5
0.6 uO*
49
M IND
C.04788
0.7260
56
DCULOR
0.04694
0.7 736
40
DT P
0.04660
0.7454
5 1
LDP
-0.04190
0. 7 658
53
ETP
-0.04167
0.7659
53
U AY
0.04 1 12
0 7 o 3 S
56
F TP
-0.04011
0.7 755
53
F TUR d
-0 .0 3921
0.79 l 3
48
DCUND
0.02764
0.89BC
24
DAYL
-0.01818
0.8942
5b
TEMP
0.01723
0.8997
56
FT DP
-0.01038
0.9436
49
MINRE 5
0.00944
0.9449
56
F NH3
0.00390
0 .9779
53
ENH3
0.0 03 9 0
0.9779
53


Observations Observations
-79-
a. Average ebb concentration of ortho-P.
b. Net change (flood-ebb) of ortho-P.
mg/1
.057
N =.56 Mean = +0.005 Std. Dev. = 0.024 Range -0.031 to +0.069
Figure 25. Frequency distributions and descriptive statistics for
(a) weighted-average ebb ortho-phosphate concentrations
(mg/1), and (b) the net changes from average flood con
centrations.


-2-
zone by strengthening the permitting requirements.
The development corporations were not prepared for the rather
sudden imposition of controls on their dredging plans. But, with their
businesses and livelihoods threatened, they resisted the controls by
litigation. In the courts, it became apparent that very little was
known about artificial canal systems and their impacts on the coastal
zone. The developers' lawyers were asking questions for which there
were no answers. Without facts to support their contentions, the
positions of state and federal agencies were weakened in the courts.
This study was initiated in response to the Florida Department of
Environmental Regulation's quest for more scientific facts. Data col
lection occurred in two phases. The first phase was conducted as part
of a one year project (see Fox ejt al. 1976) funded by the Department
of Environmental Regulation. During the first phase, the metabolism
and canal-estuary nutrient exchange patterns of four pairs of similar
canals (Punta Gorda, Port Charlotte, Pompano Beach and Loxahatchee
River sites) were examined on four occasions in 1975. The second phase
of the study consisted of single sampling trips to eight additional
canal locations in 1976. The data from each phase and the combined
data provide different types of information.
The locations of the sampling sites covered most of Florida and
were approximately distributed in proportion to canal densities in
Florida. Most canal dredging has occurred in southern Florida, par
ticularly along the southeast coast (Gold Coast). For example, the
City of Fort Lauderdale has over 150 miles of waterways. Extensive
dredging and filling has also taken place in the Tampa Bay area and,
more recently, along much of the southwest coast of Florida. The


-160-
systems and adjoining estuaries. Many more independent variables could
have been created by making various transformations of the single
factors, more first-order interaction terms, and higher-order interaction
terms. However, the objectives of the analyses were not to build com
plex models but to evaluate the "goodness" of relatively simple equations
in terms of their explained variablities.
The significant factor effects in the metabolic equations and the
2
percentages of total variances explained (R ) by the models are shown
in Table 31. It should be recalled that only factors which explained
a significant portion of the parameters' variabilities were included in
the equations (up to 10 variables).
Except for the extent of plankton-domination of community metabolism
model, the equations explain at least 70 percent of the observed vari
abilities in metabolic patterns. Most of the observable metabolic
differences among these Florida residential canals can be explained on
the basis of the canal systems' physical characteristics or the adjoining
estuaries' and sampling days' characteristics. These results suggest
that it is possible to control or predict, to a certain degree, the
metabolic attributes of existing canal systems and, perhaps, of future
canal systems.
The factor effects in Table 31 and the equations in Table 27 are
self-explanatory. The number of times each factor was included in the
nine equations are shown in Table 28. Table 29 shows the appearance
frequencies for the factors grouped into the four categories: 1) canal
characteristics, 2) tidal dynamics, 3) estuarine water quality, and
4) sampling day characteristics.
It is difficult to establish which factor or type of factor is


-171-
average dissolved oxygen concentration.
The reason that the average dissolved oxygen concentration in a
canal is sensitive to canal depth and cumulated tidal amplitude, plus
their product and their ratio, is not entirely clear. A canal's oxygen
concentration is the end result of the physical, chemical, and bio
logical processes occurring within the system. There are complex
interrelationships among canal design, local tidal dynamics, community
metabolic patterns, exchanges of materials between the canals and
estuaries, and physical mixing within the canals. Some hypotheses
concerning these interrelationships will be presented after discussion
of the nutrient exchange results.
Nutrient Exchange
The nutrient/water quality exchange data provide information on
the nature of the interactions between the canal systems and their
adjacent estuaries. This information is partially shown by the fre
quency distributions of the net-exchange responses in Figures 21-28.
Interpretation of this type of data depends on one's individual bias.
Traditionally, natural coastal systems that are net producers and
exporters of organic matter are considered assets since they provide
food for the estuarine systems. However, when artificial systems such
as canals are found to be net producers and exporters, they can be
viewed as polluting the estuaries by adding organic matter that exerts
a biological oxygen demand and degrades the water quality. Conversely,
if canals are net consumers or importers, it can be argued that they
are removing some of the valuable organic food from the estuary.


-318-
CURRELATION CQEFfICiENTS / FRb ^ | ft | UNDER H0:RHO=0 /
MB ER F BSERVATIUNS
BULK
BULK
1.00000
C. 0000
67
BEVEL
0.58163
0.000 1
64
TIDE
0.45349
0.0001
67
Sr. WE AS
C .38346
0.0014
67
SILL
-0.34802
0.00 52
63
YEAR
-0.32685
0 .0069
6 7
DTC
-0.31G 75
0.0197
56
ENH3
0,3022b
0.0152
64
FNH3
0.3022 5
0.0152
64
PPR
0.29966
0.0249
56
t GP
C. 291 96
0.0262
56
W I D T H
0.2 552 6
0.03 71
67
FTC
-0.25479
0.0536
58
FTP
0 .24251
0.05 35
64
E TP
0.23603
0.0562
64
SUN
0.23801
C. 0773
56
M INRLS
-0.23674
0. 053 7
6 7
MAXDU
0.22763
G.0660
66
D T UC
-0.22497
0.0766
62
FOP
0.22165
0 .0945
58
PGPPM3
0. 204 74
0.1301
5o
e rc
-0.19600
0.1403
56
DAYL
- 0.193 79
0.1161
67
VOLUME
0.19046
0. 1 226
6 7
UCLGR
-C. 1 6971
0.2269
42
T PR
0.1 892 7
0.1705
54
PGPPM2
0.18578
0.1704
56
LENG H
0.10347
0. 1 3 72
67
DAY
-0.18308
0.1381
67
FT U C
-0.182 7 6
0.1463
6 4
ETGP
0. 1625 6
0.1664
64
AREA
0.180 73
0. 1433
67
DTUP
-0.17745
0.1907
56
FCULR
-0.17535
0 .2667
42
cum riue
0 174 24
0 I5d5
67
PDOMIN
0 lo3 1 3
0.2366
5 4
DUP
0.14200
0.2965
5 6
F 1 C
-C.13680
0.3055
56
LCL GR
- 0. 1 3572
0.3915
42
CURBS
0. 1 33 73
0.2807
67
E 1C
-0.13000
0.3307
58
ETURB
-0.12999
0.3683
50
ETOC
-0.1 2780
0.3142
64
T GPP
0.12003
C.3 762
5 6
TEMP
-0.09o53
0.4312
6o
F TOP
0.09516
0.4936
54
MDEP TH
C.0 90 06
0.4066
67
A VGDG
0.06110
0.5174
66
PR M2
0.07616
0.5768
56
D TP
0 .0 7347
0.5704
62
DTURB
0.06867
0.6426
4 8
1 R
0.06460
0 6352
So
FTURB
-0. 061 57
0.6710
50
MN TH
-0.06054
0.6265
67
SEC CHI
0.05291
0.6881
60
DCGND
-0.04824
C. 8229
24
DNH 3
-0.04687
C.7175
62
ECGND
0 03 95 9
0.8543
24
PPRM3
0.0 39 4 l
0 7 731
56
OIL
-C .03803
0. 7608
56
FCUND
00 3Cl9
0.8688
24
Ml NDU
0.02016
0 .8724
66
AGE
0.01126
0.9280
67
CURBS
CURBS
1.00000
0.0000
74
F UP
04 7062
0. 000 2
58
T GPP
0.42030
0.0 C 1 5
5 6
W I U TH
0.4 1 4 ?6
0.0002
74
ECULR
-0.34 705
0.0243
42
F COLOR
-0.33298
0.0312
42
T R
0.33072
0.0126
56
PGPPM2
0.31605
0.0176
56
ECONU
- 0 30 98 6
0.1406
2 4
FCGNB
- 0. 30 SSl
0.1466
24
MUNT H
- 0. 26365
0.0232
74
YEAR
0.28167
0.0243
7 4
L1C
-C 22 775
0.0655
50
F 1 C
-0 .22 748
0.0660
58
F T OC
0 .22258
0.0o21
71
SUN
0.2154 l
C. 1 1 08
56
A VGDG
0.21512
0.0676
73
A Gfc
0.20561
0.0851
7 1
E V E L
0.20479
0.0867
71
SILL
0.20 310
0.0917
70
cTGC
0.18674
0.1150
7 l
NU


-35-
A shallow culvert connects sections of AP2 and AP3, but the interaction
between the two canals is limited to the surface water. The canal
system was dredged in a former mangrove community, had several deep
holes, and had varying widths. Onshore winds were strong (ca. 20 mph)
throughout the sampling period.
Goose Bayou (GB. Figure 11). The three canals sampled on Upper
Goose Bayou, located off North Bay near Panama City, were the most
recently dredged of the canals examined. These canals were also 1
shallowest and experienced the least tidal fluctuations. Marshland
and sparsely populated shorelines predominate in this estuary.
Key Colony (KC. Figure 12). The three canals in Key Colony
Beach are located on Fat Deer Key, about midway down the Florida Keys.
The substrate is limestone and fossilized sand. A sewer system serves
the development. However, the outfall from the treatment plant enters
i
an embayment about 400 meters north of canal KC1. A tropical degres
sion with high winds, heavy rains,, and little solar insolation, was
over the area during the sampling period, making conditions rather
uncharacteristic of the Keys.
North Miami (NM. Figure 13).p One branched canal in North Miami
Beach was sampled for three consecutive days. Each 24 hour period was
considered a canal observation. This canal was the deepest (6 m) of the
canals examined. An anoxic water layer existed below the two meter
depth throughout the three days. A cold weather front came through the
area during the sampling period, bringing cloudiness, shifting winds,
and rain. The development and the adjacent Maul Lake were mangrove
'communities before dredging and filling.


u'JQ S
MUNTH
DAY
YEAR
51 ATT UN
r i me
rc
I C
TOC
JJ 1
1 1
22
75
P 09
1 0
33.6
16.9
16. 7
332
1 1
22
7b
PG9
11
35.7
16.1
1 9.6
333
1 1
22
7b
PG9
12
32. 8
16.2
1 6.6
3 34
1 1
22
75
PG9
1 3
34.0
15.2
18.3
33b
1 1
22
7 b
PG9
1 4
3b. 9
lb .0
20.9
336
11
.22
75
P 69
1 5
32.4
14.6
1 7. 8
337
1 1
22
7b
PG9
16
33.2
1 4 .0
1 9. 2
33a
1 1
22
75
PG9
1 7
3 1.3
16.2
1 5. 1
339
1 1
1 4
7b
Pt>6
16
54.6
40.0
14. 3
340
1 1
1 4
7b
PB6
1 7
5 6.2
40.0
16.2
34 1
1 1
1 4
75
P6
16
62.6
38. b
24.2
342
1 l
1 4
75
PB6
1 9
5b 6
40.4
16.4
343
1 1
1 4
75
Pb6
20
58.0
38.6
19.4
344
1 1
1 4
75
Pd6
21



34b
1 i
1 4
75
PB6
22
55.4
39 .5
15.9
34b
1 1
1 4
7 5
PB6
23
56.0
40 .7
17.3
347
1 1
1 4
75
PU6
24
52.4
37.0
15. 4
346
1 1
1 b
75
Pttb
1
58.7
42.9
15.8
349
1 1
1 5
75
PU6
2



3 b 0
1 1
1 5
75
PB6
3
58.0
4 1.6
16.4
3b 1
1 1
1 5
7 b
Pb6
4
59.5
43.2
16.3
352
1 1
1 5
75
PBb
5
5 6.6
4 0.8
18.0
3b3
1 1
15
75
Pd6
b
57.2
4 C .7
16.5
354
1 1
l b
7 b
PB6
7
5 9.5
41 .8
17.7
3bS
11
1 b
75
Pbb
6



356
1 1
1 5
75
PB6
9


*
357
1 1
1 5
75
Pbb
1 0
5 7.7
4 1 .8
1 5. 9
356
1 1
1 4
75
PB9
l 6
5 1.5
40.0
11.5
3b9
11
1 4
75
PU9
1 7
5 3.5
41 .8
11.7
3o0
1 1
1 4
7 b
Pb 9
1 8



Ub S
TP
UP
TOP
1URU
NM3
CULR
DS
CONO
33 1
0.39 1
0.360
0.031 .
0.14
-0.30
332
0.38C
C 3 53
0.02 7
0.09
-0.27
333
0.382
0.364
0.018
0. 09
-0. 1 0
334
0.378
0.358
0.020
0.01
0. 16
33b
0.405
C. 39 1
0.014
0.00
0.41
336
0.450
0.421
0.02 9 .
0.00
0. 33
33 7
0.4 83
0.448
0 0 3 b .
0.00
0.24
338
0.459
0.446
0.013
C. 05
0.16
339
0 .238
0.209
0.019 .
0.2b
0.40
34 0
0.242
0.212
0.030
0 .24
0.10
34 l
0.256
0.20b
0.05 1
0. 2b
-0.21
342
0 .285
0.2 1 C
0.070
0.23
-0.4 1
343
0. 246
0.210
0.03 6 .
0.2d
-0.45
344

.
. .

-0. 50
34 5
0.241
0.198
0 .043 .
0.23
-0.4 1
346
0.24 0
0. 209
0.Cb1 .
0.22
-0.26
34 7
0 .23 7
0.189
0.04 8 .
0.20
0. 05
34 8
0.228
0.207
0.021
0.24
0.38
349

.
. .

0.56
350
0 .222
0.202
0.020
0.22
0.47
3b 1
0.268
0.2 02
0.Oo .
0.23
0.46
352
0.223
0. 1 98
0.02b .
0. 2 1
0.40
353
0 .22 7
0.197
0.030
0.21
C. 10
354
0. 232
0.202
0.03 0 .
0.24
-0.31
355

.
. .

-0.40
3 5 6

.
. .

-0.45
357
0.251
0.2C2
0.04*
0.21
-0.42
356
0.217
0.192
0 02 o .
0. 24
0.4 0
359
0.231
0.193
0.03 6 .
0.23
0.10
360

.
.

-0.21


-117-
sets is present. Further interpretation of the results of a canonical
correlation analysis becomes subjective. The correlations between the
individual variables and the canonical variables can suggest which
variables in each data set seem to,be most correlated.
The four data subsets for the canal observations (metabolism,
nutrient exchange, water,quality, physical characteristics) lead to six
possible pairings for canonical correlation analyses. The variables
included in each subset are shown in Table 18. A missing value for any
variable in either of the two data sets in an analysis causes that
observation to be deleted. Subsequently the sample sizes vary for the
six analyses.
It should be emphasized that canonical correlation analysis, like
principal component analysis, is an exploratory statistical method.
The analysis indicates the amount of correlation or association between
a series of linear combinations from each data set. Determining what
factors the linear combinations represent, is subjective. The results
that follow were obtained by determining whether an association between
the data sets existed (from the significance levels of the canonical
correlations), and from a subjective interpretation of the factors
responsible for the correlations between the sets (from the correlation
coefficients of the individual variables with the canonical variables).
Metabolism vs. Exchange
The results of the canonical correlation analysis for the metabolism
and nutrient exchange data sets are shown in Table 19. No significant
association between the metabolic and nutrient exchange attributes can
be detected for the 38 canal observations included in the analysis.


-271
OBS
MUNTH
DAY
YEAR
SI AT ION
T 1 ME
TC
IC
T DC
1 051
8
1 8
76
KC 1
23
31.1
25.7
5.4
1 0 52
a
18
76
KC 1
24
41.3
25. 1
1 6.2
1053
8
1 9
76
KC 1
1
43.7
25.4
18. 3
1C 54
8
19
76
KC l
2
35.5
25.7
9.8
1055
8
19
76
KC 1
3 .
32.3
25.6
6.7
1 0 56
a
1 9
76
KC 1
4
28.9
25. 0
3.9
1057
8
l 9
76
KC 1
3
31.2
26.4
4 .8
1058
8
19
76
KC l
6
33. 5
2 5.5
6.0
1059
8
1 9
76
KC 1
7
31 .0
25.3
5.7
1060
8
19
76
KC l
a
32.2
25.4
5.8
1061
a
1 9
76
KC 1
9
36.7
25. 7
13.0
1C 62
8
l 9
7 6
KC 1
10
32.6
26.1
6.5
1063
8
1 9
76
KC l
11
29.0
25. 8
3 .2
10 64
6
1 9
76
KC 1
12
30.7
25. 3
5.4
1 0 65
8
1 9
76
KC l
l 3
3 1.4
24.8
6 .6
1 0 66
8
1 9
76
KC 1
l 4
30.7
25.2
S 5
1 067
8
19
76
KC 1
1 5
30 .7
2 5.4
5.3
1068
8
18
76
KC 2
16
31 .8
24.7
7.1
1 069
8
18
7 6
KL 2
1 7
28.4
24.8
3.6
1 070
a
1 8
76
KC2
1 8
32 .2
23.8
8.4
1071
8
18
76
KC 2
1 9
33.6
24.3
9.5
1 C 72
a
1 8
76
KC 2
20
34.6
24. 3
10.3
1073
8
1 8
76
KC 2
2 1
30 .8
24.3
6.5
1 074
8
1 8
76
. KC 2
22
37.3
25. 7
11.6
1 0 75
8
1 9
76
KC 2
0
32.6
25. 0
7.6
1 0 76
8
19
76
KC 2
1
33.0
25.. 1
7 .9
10 77'
8
1 9
76
KC 2
2
29.8
25. 0
4 d
l 078
8
19
76
KC 2.
3
31.2
25. 1
6.1
1079
8
1 9
76
KC 2
4
32.6
24.8
7.8
1 080
8
19
76
KC2
5
34.0
25. 1
8. 9
UtJ S
TP
OP
T UP
TUKb
NH3
COLOR
OS
CUND
1 051
0.022
0.002
0.020
1 .5
0.04
23
0.23
449
1052
0.027
0. 005
0.022
1.7
0.04
1 8
0.25
449
1 0 53
0.025
0.003
0.022
1 b
0.04 .
1 6
0.30
449
l 054
0.024
0.003
0.021
1 .8
0.11
2 2
0.26
454
1 055
C.022
0.00 0
0. C22
2.0
0.04
26
0.09
444
1 056
0.016
0.003
0.013
1.9
0.04
2 3
0.0 6
449
1 0 57 .
0. 020
0. 002
0. Cl 8
1 .3
0 1 l
1 7
-0.2 1
449
1058
0.018
0. 002
0.016
1.5
C 0 3
23
-0.08
459
1 C 59
0.018
0.002
0.016
1 .4
0.11
22
-0.35
449
1 0 60
0.022
0. 005
0.017
1 5
0.0 7
29
-0.25
449
106 1
0.022
0.019
0.003
4.6
0.19
48
-0.28
449
1 0 62
0. 02 0
0.003
0.017
1 .3
0.04
20
-0.05
444
1063 '
0.018
0. 003
0.0 15
1.5
0.0b
24
-0.12
444
1 0 64
0.016
0.003
0.013
2.4
0.08
36
C .20
444
1065
0.018
C 008
0.0 10
2.1
0.12
28
0.08
444
1066
0.016
0.000
0.01b
2.1
0. 08
26
0.12
444
1067
0.016
0.005
0.011
2.3
0.16
69
0 1 l
439
1068
0.016
0 C05
0.011
2.3
0.02
37
-0 .05
452
1 069
0.016
0.000
0.0 1 D
2.2
0. 03
27
-0.06
449
1070
0.015
C. 000
0.015
2 1
0.04
33
-0.12
454
1071
0.0 18
0.003
0.015
1.5
0.09
43
0.11
444
1 0 72
0.018
0.002
0.0 16
1 .3
0.03
42
-0.2 1
444
10 73
0. 022
0.002
0. 020
2.5
0.02
32
-0.08
4 44
1 074
0.015
0.010
0.003
3.0
0.0 1
3 3
0.2 7
449
1 0 75
0.02 0
0.002
0.018
3.0
0.03
42
0.36
444
1 0 76
0.018
0. 005
0.0 13
2.2
0. 02
47
0 .30
449
10 7/
0.020
0.000
0.020
2.1
0.02
2 7
0.26
449
1 078
0.020
0.002
0.018
2 .2
0.04
32
0.09
4 54
1079
0.0 13
0. C07
0 0 G 6
2.7
0. 01
2 9
0.06
4 44
1 080
0.016
0.002
0.0 14
1.9
0.02
28
-0.21
444


-244-
UB5
MN rn
U AY
YEAR
5 TATI UN
TIME
TC
IC
TQC
24 1
1 l
23
7 6
PC6
1 4
32.1
18.4
13.7
42
1 l
23
75
PC6
15
3 2.0
1 6.2
15.8
243
1 1
23
75
PC6
l 6
42.8
17.8
25. 0
244
1 1
23
75
PC6
1 7
42.8
20 .0
22.8
245
1 1
23
75
PC6
1 6
35.0
16.5
18.5
46
1 1
23
7 5
PC6
19
33.5
16.9
16. 6
247
l 1
23
75
PC5
20
32.4
19.1
l 3.3
4 8
1 1
23
75
PC
2 1



249
1 1
23
75
PC6
22



250
1 1
23
75
PC6
2 3
36.2
16.9
19.3
25 l
1 1
23
75
PC6
24
32.7
19.4
13. 3
252
1 1
24
75
PC6
1



253
1 1
24
75
PC 6

35.7
17.2
1 8. 5
254
11
24
75
PC6
3
33.9
20.0
13. 9
255
1 1
24
75
PCb
4
36.4
17.4
19.0
25 6
1 1
24
75
PC 6
5
3 5.5 '
17.4
1 8. 1
257
1 1
24
7 5
PC6
6
3 5.5
16 .9
18.6
256
1 1
24
75
PCb
7



259
1 1
24
75
PC 6
8
58.3
17.3
41.0
260
1 1
24
75
PC6
9



261
1 1
24
75
PCb
1 0



62
1 1
24
75
PC6
1 1
3 1.4
O

o
11.4
263
1 1
24
75
PC5
1 2



264
1 1
24
75
PC6
1 2
-


65
l 1
21
75
P63
l 8
34.0
19.3
14.7
26 6
1 1
21
75
PG3
1 9
34.9
20.0
14.9
267
1 1
21
75
P63
20
32 b
19.9
12.9
268
1 1
21
75
PG3
2 1
3 3.6
20.4
l 3. 2
269
1 1
21
75
PG3
2 2
32.0
l 6.6
13.4
270
1 1
21
7 5
PG3
2 3
32. 1
20.5
11.6
US
rp
UP
TOP
TU k o
NH3
C UL Uk
DS
CONO
41
0.352
0.307
0.046

0.06

0. 35

242
0.34 C
0.310
0.030
0.03
0.35

2 43
0.358
0.3 00
0.058

0. 07

0. 20

244
0.319
0.285
0.034

0.07

0.15

45
0.332
0.28 1
0. CE1
0.08

0.06

246
0.329
0.2 90
0 CJ9

0.10

-0.03

247
0.316
0.2 72
0.04 <+

0 l

-0.11

248





-0. 12

249






C. 00

50
0.322
0.307
0.015

0.14

0.15

51
0.313
0.2'91
0.022

0. 10

0.25

252






0.20

53
o .31 a
0.276
0. 042

0.09
0.15

54
0.309
0.277
0.032

0.11

0.15

255
0.321
0.269
0 0 5

0.10

0.05

256
0.302
0.264
0.038

0.12

-0.05
57
0 .307
0.269
0.03b

0.11

-0. 15

258




-0.35

259
0.324
0.298
0.02o

0. 29

-0.28

60






-0.30

261






-0.32

262
0.284
0.257
0.02 7

0. 09

-0. 1 7

63






-0.09

264






0.16
2 6 5
0.298
0.2 69
0.03 9

0. 00

0.11

66
0.267
0.234
0.035

0.0 1
0.00

267
0.27 1
0.238
0.033
0. 04
-0.10

d8
0.283
0 .241
0.04 2

0.02

-0. 15

269
0.282
0.264
0.01 8

0.02

-0.06

270
0 .280
0. 238
0.042

0. 00
0.19



LIST OF REFERENCES
Adkins, G., and P. Bowman. 1976. A study of the fauna in dredged
canals of coastal Louisiana. Tech. Bull. No. 18. La. Wild. Fish.
Comm., Oysters, Water Bottoms, and Seafoods Div. 72 p.
American Public Health Association. 1971. Standard Methods for the
Examination of Water and Wastewater, 13th ed. New York. 874 p.
Barada, W., and W.M. Partington. 1972. Report of investigation of the
environmental effects of private waterfront canals. Environ. Info.
Cent. Fla. Cons. Found., Winter Park, Fla. 63 p.
Barr, A.J., J.H. Goodnight, J.P. Sail, and J.T. Helwig. 1976. A
User's Guide to SAS76. Sparks Press. 329 p.
Bellinger, J.W. 1970. Dredging, filling, and the inalienable public
trust the future of Florida's submerged environment, p. 373-382.
In 24th Annual Conf., Southeast. Assoc. Game and Fish Comm.
Blackith, R.E. and R.A. Reyment. 1971. Multivariate Morphometries.
Academic Press. 412 p.
Burk and Associates Inc. 1975. Environmental investigation of Eden
Isles. Rept. prepared for Louisiana Attorney General William
Guste. August 1975. 73 p.
Carpenter, J.H. nd J. Van de Kreeke. 1975. Forecasts of water
quality in the Barfield Bay, Blue Hill Bay, Collier Bay, and Big
Key areas of Marco Island, Florida. Univ. Miami. R.S.M.A.S.
it75023. 55 p.
Carter, M.R., L.A. Burns, T.R. Cavinder, K.R. Dugger, D.B. Hicks,
H.L. Ravells and T.W. Schmidt. 1973. Ecosystems analysis of the
Big Cypress Swamp and estuaries. V.S.E.P.A., Region IV. Surv.
Anal. Div., Athens, Georgia.
Castanza, R. and M. Brown. 1975. Main subsystems and past trends in
South Florida. In H.T. Odum and M.T. Brown (eds.), Carrying
Capacity for Man and Nature in South Florida. Cent. Wetlands,
Phelps Lab., Univ. Fla., Gainesville, Fla.
Chesher, R.H. 1974. Canal Survey, Florida Keys. Marine Res. Found.
Inc., Key West, Fla. 173 p.
Cooley, W.W., and P.R. Lohnes. 1971. Multivariate Data Analysis. John
Wiley & Sons, Inc. 364 p.
-196-


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AUTHOR: Bailey, William
TITLE: Canal-estuary nutrient exchange and metabolic levels in Florida
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PUBLICATION DATE: 1977
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-306-
CURRELATIUN COEFFICIENTS / PRUU > jR|
Mb E R OF OBSERVATIONS
UNDER HO:
RHU=0 / NU
PR M2
PRM2
1 .OOCOO
0.0000
56
PPRM3
0.75353
0.0001
56
PGPPM2
0.63485
0.0001
5o
TR
0.52615
0. 0001
56
T GPP
0.52318
0. 0001
56
PGPPM3
0 .47484
0.0002
56
MAXO
0 .45309
0.0004
5o
OCLR
0 .43459
0.0051
40
MDEP TH
0.365 1 2
0.0057
56
AGE
0.360 l l
0.0064
56
e r uc
0.3364 7
0.013b
53
5 l EL
0.33097
0.0127
5b
OEVEC
C.33091
0.0 127
56
FTOC
0.29990
0.029l
53
FCOND
-0.29690
0.1589
24
MI NO U
-0.28618
0.0325
5 6
PDOMIn
0.284b 7
0. 0370
54
E CU N D
-0.27950
0. 1859
24
UA VL
C 2 7 7 b 8
0. 03 83
56
SUN
0.27003
0.044 1
56
E TC
0 .26884
0.0516
53
DT ORB
0.26646
0.0734
46
MU NTH
-0.26511
0.0463
5 6
MI NR E -o
0.2 5468
0.0562
56
TEMP
0.24969
0.0635
56
PPR
-0.24431
0.0o96
bo
T I DE
0.23342
0.0834
56
FT C
0.23153
0.0953
53
FTOP
0.22267
0.1241
49
A 1 T H
0.21 94 9
0.1041
5 6
F OP
0. 2 1 05 7
0. 1 302
53
VOLUME
0.19855
0. 1424
So
YEAR
0.1 ot) 73
0. 21 38
56
CURBS
0.16411
0.2268
56
ET OP
0.16100
0.2691
49
SE i/EPS
0.14751
0.2 780
56
EOP
0.1399 l
0.3177
53
L TP
0 1 332 7
0.3414
53
f rp
0.13326
0.34 15
53
ECULUR
-0. 124 09
04455
40
DAY
- 0. 1 l644
0.3928
56
DCUND
-0.11421
0.5952
24
DN H3
0.11396
0.4259
51
F NH3 EN H5
-0. 1 138 7 -0.1138 7
0.4 169 0. 4169
53 53
F T UR b
0.1 0780
0. 4658
48
AREA
0.10702
0. 4324
56
DIC
0.10636
0.4575
51
SECCH1
-0.10068
0.4603
5o
F COLOR
-0.0 94 0 7
0.5637
40
El C
-0.0870 1
0.535 6
53
LENOTH
0.08519
0.5324
5o
DT UC
-0.08398
0.5579
51
BULK
0. 0 76 18
0.5 7o8
56
AV GDO
-0.0 7043
0bO 60
56
ETURd
-0.06932
0.6396
48
F 1 C
-0.0 6435
C 6 4 7 l
53
CUMTIOE
0.04053
0.7668
5 6
UT P
0.028 72
0.8414
51
T PR
0.01129
0. 93 54
54
UUP
C .0 09 99
0.9445
5 1
D TCiP
0.00518
0.9712
5 1
D TC
0 .00297
0.9835
51
P6PPM3
PGPPM3
l.00000
0.0000
56
PC.PPM 2
0.77693
0.000 1
50
T 106
0.65677
0.0001
5 6
P PR M3
0.54617
0. OC 01
56
MAXDu
C .54076
0.0001
bb
CUMTIDE
0.52169
0.0001
56
AGE
0.51594
0.0001
56
PR M2
0.47484
0.0002
56
TGPP
0.47033
0.0003
5 6
7 R
0.4l1GJ
0.0017
56
UEVLL
C.38440
0.0034
56
PDL'M I N
0.3 73 1 6
0.0054
54
FCCNU
-0.35946
0 .0845
24
ECUND
-0.34963
0. 094 0
24
P PR
0.34458
0.0093
56
SECCHI
-0.34166 -
0.0100
5 6
MINkES
0.26 bo 2
C.0453
56
DNH3
-0.26580
0. 0594
51
F T UC
0.220 6b
0.1120
5 3
TEMP
0.21733
0.1076
56
F TC
0.21636
0.1197
53


-180-
Table 35. Physical characteristics, water quality, metabolic levels,
and net canal-estuary exchanges for an "average" residential
canal. .
Physical Characteristics
Length 1050
Width 28
Depth 2.8
Water Surface Area 80000
Sill Height 0.86
Bulkheading 80
Development 56
Age 15
Sewer System Present
Tidal Dynamics
Tidal Range maximum 0.68
Cumulated Tidal Amplitude (24 hours) 1.1
Minimum Canal-Water Residence Time 3.5
Exchange Volume 88000
Metabolism
Total Community Gross Primary Production 4.3
Total Community Respiration 4.1
Total Community Net Primary Production 0.2
Planktonic Gross Primary Production 2.5
Planktonic Respiration 1.5
Planktonic Net Primary Production 1.0
Plankton Domination of Community Production 60
Sampling Day Attributes
Solar Insolation 432
Daylength 12.5
Water Quality
Dissolved Oxygen Concentration average 5.6
maximum 8.8
minimum 2.7
Secchi Depth 1.35
meters
11
11
square meters
meters
percent
ri
years
meters
meters/day
days
cubic meters/day
/ 2 +
gm C/m -day1
percent
langleys/day
hours
mg/1
ii
M
meters
' Conversion used: 1 gm O2/111 -day = 0.5 gm C/m^-day
L


oes
CANAL
MONTH
DAY YEAR LENGTH
W IDTH
MDEPTH
i
PG6
3
21 75
747
30
2.8
2
PG3
3
21 75
652
28
2. 2
3
PC3
3
22 75
575
33
3.2
4
PC6
3
22 75
0 18
33
2.7
5
PB3
3
26 75
732
23
3. C
6
P86
3
26 75
7 32
21'
3.2
7
LX3
3
25 75
631
22
1.8
a
LX6
3
25 75
521
1 7
1 .6
9
PG 6
6
14 75
747
30
2.8
1 0
PG3
6
14 75
652
28
2. 2
11
PC 3
6
1 5 75
575
33
3.2
1 2
PC
6
15 75
6 18
33
2.7
13
PB3
6
19 75
732
23
3.0
1 4
P66
6
19 75
732
21
3.2
1 5
LX6
6
1 8 75
521
17
1.6
i 6
LX3
6
18 75
631
22
1.8
17
PG3
9
6 75
652
28
2.2
18
PG6
9
6 75
747
30
2.8
19
PG9
9
6 75
3650
30
3.0
OSS
DEVEL
AGE
BULK CURBS SEWERS
M1NRES
1
30
9
100
0
1
2.9
2
50
9
100
0
1
2. 7
3
1 00
16
100
0
1
5.0
4
100
16
IOC
0
1
4.0
5
100
23
100
0
0
2.0
6
98
23
1 00
0
0
2.1
7
0
16
80
0
0
1.2
8
0
16
0
0
0
1.2
9
30
9
100
0
1
3.6
1 0
50
9
100
0
1
2.9
1 1
100
16
100
0
1
4.2
12
100
16
100
0
1
3.6
1 3
100
23
100
0
0
1.8
1 4
98
23
100
0
0
1 .9
15
0
1 6
0
0
0
1.4
1
0
1 6
80
0
0
1.4
l 7
50
9
1 00
0
1
2.2
18
30
9
100
0
1
2. 7
1 9
50
1 1
100
0
1
2.7
AREA
VOLUME
SILL
22400
62700
0.0
1 9000
60700
0.2
1 9000
60700
1 1
20400
55 1 00
0.8
16800
50500
1 1
1 5400
49200
0.8
1 3900
25000
0.6
8860
14200
1.2
22400
62700
0.2
18300
40200
0.0
19000
60700
0.5
20400
551 00
0.8
16800
5 05 C 0
1.1
15400
49200
0.8
8860
14200
1 .2
13900
25000
0.6
183 00
40200
0.2
22400
62700
0.0
480000
1440000
0.0
TIDE
CUMTIDE
SUN
DAYL
0 .58
0.83
602
12.0
0.58
0. 83
6 02
12.0
0 .58
0.77
642
12.0
0.58
0.77
642
12.0
1 10
2. 14
488
12.0
1.10
7.14
488
12.0
0.70
1.15
434
12.0
0.70
1.15
434
12. 0
0.55
0.74
650
13.5
0. 55
0. 74
650
13.5
C 73
0.83
6 76
13.5
0.73
0.83
676
13.5
1.01
l. 77
342
13.5
1.0 1
1.77
342
13.5
0.52
1.24
378
13.5
0.52
1. 24
378
13.5
0.64
1. 10
4 26
12.3
0.64
1.10
4 26
12 .3
0.64
1. 10

12. 3


Figure 10. Canals and sampling stations at the Apollo Beach site.


-115-
that the canals sampled in areas with smaller tidal ranges tended to
be less developed and consequently less bulkheaded. Alternatively,
greater, tidal ranges may result in accelerated canal bank-slumping and
encourage bulkheading.
Due to these problems the individual correlation coefficients for
all the data will not be discussed, but they are included in the Appen
dix. The correlation matrices for the four data subsets, presented in
the principal components section, include only those canal observations
that had complete data for all variables. The correlation coefficients
in the Appendix are for the entire data set and are ranked in descending
order, with the significance levels and sample sizes given.
Rather than evaluating the correlations between each possible pair
of the 64 variables, considering the correlations between the different
types of data or subsets is more attractive. The degree of inter
dependence of the metabolism, nutrient exchange, water quality, and
physical attributes of these canals is the desired information. The
multivariate statistical technique of canaonical correlation is available
to evaluate the correlation between two data sets.
Canonical correlation analysis, in a manner similar to prinicpal
component analysis, generates linear combinations of variables in two
data sets, such that the values of the linear combinations or canonical
variables of each set are maximally correlated. A series of these
pairs of linear combinations (one for each set) are produced, with the
features that the correlation of the paired canonical variables de
creases along the series and that the respective canonical variables
are uncorrelated with the preceding ones in the series. The procedure
is analogous to univariate correlation, except the pairs of artificial


-207-
BS
MUNTH
DAY
YEAR
S T Al 1UN
EP TH
TGPP
TR
207
1 1
23
75
PC 5
0
11 .0 2
4.80
208
1 1
23
75
PC 6
0
9.87
9 b6
209
1 1
23
75
PC6
1


2 10
1 1
23
76
PC 6
2


2 1 1
1 1
23
76
PC7
0
7.68
6.45
2 1 2
1 1
23
76
PC7
1


2 1 3
1 1
23
75
PC8
0
8.2 6
4 .98
2 1 4
1 1
1 4
7 6
Ptl
0
0.90
0 .20
2 1 5
l 1
1 4
75
Pfcil
1
9

2 1 6
1 1
1 4
75
P81
2
9

2 1 7
1 l
1 4
75
PB2
0
5.52
6.30
218
l 1
14
75
PbJ
0
2.75
3 .6 0
219
1 1
l 4
7 5
P 83
1


220
11
1 4
75
PB3
2


22 1
11
1 4
7 5
PB 4
0
4.8 0
5.45
222
l 1
1 4
7 5
PB4
1


223
1 1
1 4
75
PB4
2
9

224
1 1
1 4
75
PB 5
0
4.02
2.25
225
1 1
1 4
75
PU6
0
1.95
2.25
226
1 1
1 4
75
PB6
1


22 7
1 1
1 4
75
PB6
2


228
1 1
1 4
75
P 87
0
0.00
0.00
229
1 1
1 4
75
pbb
0
0 .00
0.00
230
l 1
1 6
75
LX 1
0
10.62
9.84
23 1
1 1
1 6
75
LX 1
1


232
1 i
1 6
75
LX2
0
4.32
5.10
233
1 i
1 6
7o
LX3
0
0.92
0.00
234
1 1
1 6
75
LX3
1


235
1 1
1 6
75
LX3
2


236
1 1
1 6
75
LX4
0
5.25
4.00
UBS
PG PPM 2
PRM2
PGPPM3 PPKM3
TPR
PPR
SUN
207




2.46

3 34
208
5.35
1.06
4.41
0.13
1.02
5.02
334
209


2.19
0.28


334
2 1 0


0.96
0.48


334
21 1
3. 97
0. 33
3.10
0. 04
1.19
12.00
334
2 12


2.42
0.31


334
2 1 3




1 .66

334
2 1 4
3.84
1.42
4.90
0. 73
4. 50
2. 69
352
21 5


1.39
0.77

352
2 1 6


0. OC
0.29

9
352
2 t 7




0.67

352
2 1 8
2.08
2.50
0.50
2.41
0 .76
0.83
352
2 l 9


1.33
0.65


352
220
0.50
0 o5

9
352
22 1
3. 79
2. 03
1 .50
1 .70
0.84
1.87
352
222


2.68
0. 76

362
223


C 36
0.40


352
224

.
9
1.79

352
22 5
3.1 l
l .82
1.28
1 32
0.87
l. 71
352
22 6


1 55
0.64


352
227

0. 62
0.32


352
228 '



.


352
229

.
.

0
352
230
3.10
0 66
2.82
0. 72
1.06
4.70
204
231


1.13
0.15

204
232


.
.
0.85

204
233
2*64
1. 19
3. 1 C
0.68

2. 20
2 04
234


0.9 1
0.42

2 04
235


0.18
0.43

204
236
J. 69
l 87
4.37
1.37
1.31
1*97
2 04


-175-
canals. 3) The association between the exchange responses and canal
physical characteristics was limited to the color and turbidity re
sponses. The r-squared values for the regression equations (Table 27)
along with the significant factor effects are shown in Table 34 for
each net-exchange parameter. Except for the net exchanges of the
inorganic nutrients (ortho-P and ammonia), more than 80 percent of the
individual net-exchange variabilities could be explained by the
equations.
The appearance frequencies of the four factor categories (canal
characteristics, tidal dynamics, estuarine water quality, and sampling
day characteristics) in Table 29 indicate that each factor-type has
some importance. The estuarine water quality parameters are most
frequently included in the net-exchange equations. The fact that the
canal physical factors were next most frequently included in these
equations, suggests that canal system design can influence the nature
of canal-estuary interactions.
It can be seen from Table 34 that increases in canal surface area
tend to make canals act more as sources of total carbon, organic carbon,
ortho-phosphorus, and organic phosphorus. Large canal systems con
tribute carbon and phosphorus to the estuaries. Canal depth, as a
single factor or as an interaction term, is only a significant factor
in the carbon exchange models. The same pattern of depth-effects exists
for organic carbon exchange as for the average dissolved oxygen model.
Increases in canal depth, as a single factor, tend to enhance the
retention of organic carbon by canals; but increases in the product of
canal depth and cumulated tidal amplitude tend to make canals sources
of organic carbon to the estuaries. The problems associated with the


-101-
Principal component analysis generates a series of linear com
binations (eigenvectors) with the feature that the first eigenvector
of the individual parameters (generally standardized to a mean of zero
and a standard deviation of one) accounts for the maximum amount of
variability of the total data set possible with one linear expression.
The second principal component is the linear combination of the vari
ables in.the data set that accounts for the maximum amount of variability
remaining after the first principal component has removed its share.
Similarly the rest of the series of eigenvectors sequentially account
for the greatest amount of variability remaining after the preceding
components have removed their shares.
The weightings or coefficients of the individual variables in each
linear combination represent the importance or contribution of that
variable (standardized) to that principal component or factor. Since
the variables are standardized, the parameters with the greatest
magnitude of values are not necessarily the most important in control
ling the variability of the data set. Rather, it is those parameters
that are most variable throughout all the observations that receive
the most weight. In the context of this study, the individual para
meters with the most weight are the ones that lead to the greatest
differences between the canal observations for the principal component
or factor being evaluated. The interpretation of the weightings of
each linear combination in terms of the factor that the component
represents is subjective and not always straightforward.
Another feature of principal component analysis is that the por
tion or percentage of the total variability in the data set accounted
for by each principal component is given. Consequently a data set with


Corliss, J., and L. Trent. 1971. Comparison of phytoplankton pro
duction between and. altered areas in West Bay, Texas. Fish. Bull.
69 (4): 829-832.
Daiber, F.C., D. Aurand, W. Bailey, R. Feldheim, and K. Theis. 1972.
Environmental impact of dredge and fill operations in tidal wet
lands upon fisheries biology in Delaware. College of Marine
Stdies and Dept, of Biol. Sci., Univ. of Del. 98 p.
Daiber, F.C., D. Aurand, W. Bailey, and G. Brenum. 1973. Ecological
effects upon estuaries resulting from lagoon construction, dredging,
filling, and bulkheading. College of Marine Studies and Dept. Biol.
Sci., Univ. Del. 19 p.
Daiber, F.C., D. Aurand, W. Bailey and G. Brenum. 1974. Ecological
effects upon estuaries resulting from lagoon construction, dredging,,
filling and bulkheading. College of Marine Studies and Dept.
Biol. Sci., Univ. Del. 124 p.
Daiber, F.C., D. Aurand, G. Brenum, and R. Clarke. 1975. Ecological
effects upon estuaries resulting from lagoon construction, dredging,
filling, and bulkheading. College of Marine Studies and Dept.
Biol. Sci., Univ. Del. 197 p.
Deltona Corporation. 1975. Annual report, Marco Applied Marine Ecology
Station, Marco Island, Florida, July 1, 1974-July 1, 1975. 282+ p.
Douglas, P.A., and R.H. Stroud. 1971. A symposium on the biological
significance of estuaries. Sport Fishing Institute, March, 1971.
7 P-
Environmental Protection Agency, U.S. 1973. Finger-fill canal studies.
Punta Gorda and Big Pine Key, Florida. Surv. and Anal. Div.,
Athens, Georgia.
Environmental Protection Agency, U.S. 1974. Methods for Chemical
Analysis of Water and Wastes. National Environmental Research
Center, Cincinnati, Ohio. 298 p.
Environmental Protection Agency, U.S. 1975. Finger-fill canal studies.
Florida and North Carolina. Surv. and Anal. Div., Athens,
Georgia. 232 p.
Fox, J.L., P.L. Brezonik, W.A. Bailey, T.V. Belanger, L.C. Chesney,
W.G. Hansen, F.M. Kooijman, W.T. Marsh, C.D. Pollman, and H.S.
Prentice. 1976. A field and laboratory evaluation of water quality
in Florida finger canals. Vol. II. Dept. Inv. Engn. Sci., Univ.
Florida. 341 p.
Gilmore, G. and L. Trent. 1974. Abundance of benthic macro inverte
brates in natural and altered estuarine areas. N.O.A.A. Tech.
Rept. NMFS SSRF-677. 13 p.


-91-
observations was -0.005 mg/1, with a standard deviation before adjust
ment for the location and month effects, of 0.022 mg/1. The location
2
and month effects explained 81 percent of the total variance (R in
Table 10), yet only reduced the unexplained standard deviation to
0.014 mg/1.
The variabilities of exchange behavior (unadjusted standard
deviations) in Table 10 represent the degrees of difference between
the eight canals over the four sampling periods. For organic carbon
and ammonia, the unadjusted standard deviations (2.0 and 0.05 mg/1,
respectively) can be interpreted as the exchange variabilities among
these similar canals, since no significant differences in mean values
were detected. In the case of organic phosphorus exchange, where dif
ferences in mean values occurred, the standard deviation of all values
(0.022 mg/1) is reduced to 0.014 mg/1, after the location and month
effects are removed. This adjusted standard deviation can be inter
preted as the variability between the individual canals at each
location for organic phosphorus exchange.
Daily Variability in One Canal
The nutrient/water quality exchanges between one canal (North
Miami site) and its adjacent estuary were measured for three consecutive
24 hour periods. The nutrient exchange results of this three day study
are shown in Table 11, and are included in Table 7.
The observed variabilities (standard deviations) for the exchange
parameters for this on three-day period, are smaller than the un
explained variabilities of the eight canals sampled in 1975 (Table 10).
The unexplained variabilities for the larger sample size with seasonal


-208-
bs
MONTH
DAY
Y LAR
STAT ION
DEPTH
TGPP
TR
237
1 1
1 6
7b
LX4
1


236
1 1
1 6
7 5
LX4
2


39
1 1
1 6
75
LX5
0
5.12
5.64
240
1 1
1 6
7 6
LX6
0
1.70
1.50
24 1
1 1
1 6
75
LX6
1


242
1 1
1 6
75
LX6
2
.

243
1 1
1 6
75
L X 7
0


4 4
1 l
1 6
75
LXB
0


24b
1 1
1 6
75
LX6
1
.

46
3
23
76
M 13
0
6.46
9.06
24 7
3
2 3
76
MI 3
1


248
3
23
7 6
M 3
0
10.60
12.50
24 9
3
23
76
M 1 3
0
10 .30
12.00
2 dO
3
23
76
M 12
0
7.11
7.20
2 b i
3
23
7b
M I 2
i


2 b 2
3
23
76
Ml 1
0
5.58
5.52
2b 3
3
22
76
M 1 l
0
4.71
5.46
254
3
23
76
Mil
0
7.29
6.18
255
4
2 0
76
tC 1
0
27 .30
29 .00
2 5b
4
20
76
ac i
2


257
4
20
76
BCl
0
3 1.80
18.00
258
4
20
76
BC1
0
14.40
6 .60
259
4
20
76
BC 1
2


60
4
20
7 b
BC2
0
16 .00
13.70
26 1
4
20
76
UC2
2


2 62
4
20
76
BC3
0
12.00
1 0.70
26 3
4
20
76
BC3
2


2 64
4
20
76
BC3
0
18.20
16.50
26b
5
l 9
76
H 13
0
16.00
5.97
26 6
5
1 9
76
H 13
0
13.10
4 .40
60S
PGPPM2
PR M2
PGPPM3
PPKM3
TPR
PPR
SUN
237


0.98
0.61
.

2 04
38


0.53
0 56

204
23 9



.
0 .90
*
204
40
2.38
1.12
1.64
0.49
1.13
2.11
204
24 1


t .23
O.ol
.
204
242


0.23
0.27


204
243


.



2 04
24 4
1 .88
0.39
2.3b
0.32

4.75
204
45


l .42
0.47
#
*
204
24 6
3.94
4.9 1
3.40
1.57
0.93
0..6 0
52 0
247


1.49
1 o 5


520
24 8


.

0.84

520
249


.

0.66

52 0
2 50
3.4 6
2.9 1
.99
1 7
0.99
1.19
520
251


1.31
0*40
.
520
52
b 64
3.67
6.38
1.49
1 C 1
1.54
520
253


.

0.66

520
254


.
.
1.18

520
5b
6.24
4.27
4.07
1 bb
0.94
1.46
57 1
2 5 6


0.09
0 *J
*

571
257


.
.
1.77

571
258
9.85
4.44
5o
1.52
2.18
2.22
5 71
259


i. e i
0 .28
.

57 1
260
8.6 1
3.20
4.41
l j 7
1.16
2.69
571
261


1.33
0.6 1


571
262
13.50
5.24
O. 0c
l .88
1.12
2.58
57 1
263
.

2.99
1.12
.

5 71
264




1.11

5 7 1
2 6 5




2.68

515
266
23.90
6.16
16.00
3.10
2.98
3.81
5 15


Table 3. Metabolism results averaged by canal (1 to 5 stations
per canal) for each sampling day.
Nomenclature and units as in Table 2


36'
Figure 11. Canals and sampling stations at the Goose Bayou (Panama
City) site.


-163-
most important in determining canal metabolic patterns. Each of the 21
single-factor variables, either singly or interactively, has significant
effects on at least one metabolic parameter. Sill height, estuarine
total carbon concentration, and the product of estuarine color and
turbidity level are the single variables that appear most frequently
in the metabolism models (5 each). Increases in the values of these
factors tended to increase metabolic levels. Canal depth and the
percent-development were also important factors, but their effects
depended on the levels of other factors, i.e., the interactive terms
were often included.
Among the groups of independent factors, the canal physical
characteristics and the estuarine water quality parameters appeared
most frequently in the metabolism models. The local tidal dynamics and
the sampling day characteristics were less frequently included in the
models. However, when the appearance frequencies were weighted for the
number of variables in each group, the sampling day characteristics
(solar insolation and daylength) and the estuarine water quality ap
peared to be relatively more important. Therefore, it is appropriate
to conclude that the four types of factors have equal importance in
determining canal metabolic patterns.
From a design or management standpoint, only the canal physical
characteristics can be controlled by a developer. Unless the decision
against canal construction in a particular area is made, the effects of
the local water quality and tidal dynamics are unavoidable. Since
most developers would be unwilling to construct a canal system and not
have it developed, the effects of development on canal metabolism are
also unavoidable (unless a detailed study shows that management of the


-178-
turbidity color had varying effects in the different models, and they
often had effects opposite of the individual parameters. For example,
high levels of estuarine organic phsophorus increased the tendency for
canals to be sources of ortho-phosphorus to the estuaries; whereas, the
product of organic phosphorus and organic carbon had the opposite
effect.
General Observations
Numerous mechanisms could be postulated for the reasons that the
individual independent factors were found to have significant effects
on the individual metabolism, water quality, and net-exchange para
meters. However, the purpose of this study was to describe the con
ditions and behavior of a variety of Florida residential canals, and
not to develop a mechanistic model. The regression equations were
derived from the observed data and the canals examined. It would be
incorrect to use the equations to predict the behavior and conditions
of canals with attributes different from those examined. The amount
of error that would result if this were done is unknown. Nevertheless,
in the absence of a clear understanding of the cause and effect
relationships in residential canals, the model equations do describe
the interrelationships between the response parameters and the indepen
dent factors of these existing canal systems, and could be cautiously
used to develop canal design criteria.
It should be emphasized that this study was not intended as a
total evaluation of the ecological and socioeconomic impact of resi
dential canal construction in Florida's coastal zone. The information
from this work provides a foundation for assessing the role and behavior


-31-
Hillsboro Inlet (HI. Figure 8). The three canals sampled near
Hillsboro Inlet are part of Lighthouse Point Township. Canals HI1 and
HI2 form a single complex canal system with two entrances. Both the
HI2 and HI3 canal entrances are approximately 500 meters from the
Hillsboro Inlet. Yet, the influence of the oceanic inlet is quite dif
ferent for each canal. More of the ocean water that passed through the
inlet during flood tide seemed to be flowing north, rather than south
along the Intracoastal Waterway, during the sampling period. As a
result the turbidity and color at the HI2 canal entrance was noticably
less than at the HI3 entrance. Different volumes of freshwater flow
into the respective Intracoastal Waterway sections from upland drainage
were assumed to be affecting the movement of the seawater entering the
inlet. Boat traffic along the Intracoastal Waterway results in much
wave activity at the canal entrances. The large homes in the develop
ment tend to shelter the canal branches from the wind. A sewer system
was installed in the development during the year prior to sampling.
Flagler Beach (FL. Figure 9). The three canals sampled at Flagler
Beach extend off the Intracoastal Waterway about 15 kilometers south of
Matanzas Inlet. This section of Florida's coastline is not extensively
developed. Mangroves and marshland surround most of the Intracoastal
Waterway in the area. The water was quite colored (ca. 200 cpu) at the
time of sampling, and did not have much tidal activity.
Apollo Beach (AP. Figure 10). The Apollo Beach development,
located on the eastern shore of Tampa Bay, is approximately 10 kilo
meters from a phosphate processing plant. One large canal was
sampled as three canal observations. Canal API was taken as the
entire canal. Canals AP2 and AP3 were the major branches of the system.


-99-
N = 60 Mean = 1.35 Std. Dev. = 0.44 Range 0.75 to 2.90
Figure 30. Frequency distribution and descriptive statistics for the
average Secchi depths (m) recorded in all canals.


-203-
S
T P 3
M
A

6
G
P
U
Y
T
E
T
P
P
P
P
u
N
D
E
1
P
G
P
R
P
K
T
P
s

T
A
A
O
T
P
T
M
M
M
M
P
P
u
s
H
y
R
N
H
P
k
2
2
3
3
R
R
N
3 1
3
26
75
P til
0
8.82
9.40
6.16
2.12
1 6.22
1.53
0.94
3,84
4 88
32
3
26
75
Pb 1
1




0.00
0.26

4 88
33
3
26
75
PB1
2




0.04
0.7to


488
34
3
26
75
PB2
0
8.02
9.35



0.86

488
33
3
26
75
PB3
0
6.70
7.60
5.6 7
2.52
10.51
0.84
0.86
2.32
4 88
36
3
26
75
PB3
1

*


0.50
1.20


486
37
3
26
75
PB3
2

.


0.00
0.57


488
33
3
26
75
P 84
0
6.80
o 5 0
7.58
2. 63
1 4. 29
1.07
1.05
2.86
4 88
39
3
26
75
PB4
1

. .


0.22
1.05

486
40
3
26
75
PB 5
0
5 55
5.45




1 .02

488
41
3
26
75
P B6
0
4.70
6.0 0


11.01
0.72
0.78

4 86
42
3
26
75
P 06
1

.


0.00
0.53


488
43
3
26
75
P B7
0
5.3 7
7.40




0.73

488
44
3
25
75
L X t
0
7.45
6.45
4.06
0.5b
3.23
0.2 1
1.15
7.38
4J4
46
3
2b
75
L XI
1



1.5 1
0 .23
'

4 34
46
3
25
75
L X2
0
8. 24
7.75




1.06

434
4/
3
25
7b
LX3
0
6 42
4.22
1.73
0. 7b
2.23
1.00
1.52
2.22
<+ 34
43
3
25
75
L X4
0
3.17
2.20
3.1 6
2.39
1.37
0.06
1 .44
1.17
4 34
49
3
25
7b
u X4
1

.


1. 53
i. i a


434
60
3
25
75
L X5
0
6.77
6.95

*


1.14

4 34
61
3
25
75
L. X6
0
7.65
7. 05
2.6 5
1.12
2.03
1.29
1 08
2.27
4 34
62
3
25
75
LXb
l




0.62
0.24


434
63
3
25
75
L X7
0
2.04
0.63


#

0.56

434
54
3
25
7b
L X8
0
2.72
2.00


1.66
0.4b
1.36

434
56
6
1 4
75
PG1
0
7.77
5.33
3.32
1 74
3.4 1
0.49
1.46
1.91
650
5 6
6
14
75
PG1
1




0.82
0.59


650
67
6
1 4
75
P G1
2




0. 60
0 63


6b 0
6 3
6
1 4
75
PG2
0
8.13
5.44

0


1 .49

650
59
6
1 4
75
PG3
0
6.69
6. 32
1.93
l 56
3.06
0.81
1.26
1 .22
650
60
6
1 4
75
PG3
1




0.38
0.2 8


650
61
6
14
75
PG3
2




0.00
0.60


650
62
6
14
75
PG4
0
8.69
7. 0
1.91
2. 19
2. 41
0. 78
1.21
o

a
6 50
6 3
6
14
75
PG4
1




0.83
0.68


650
64
6
1 4
75
PG4
2




0.47
0.75
*

650
65
6
1 4
75
PG5
0
2.40
1 .46
'



1.68

650
66
6
1 4
75
PG6
0
7.53
5.32
2.68
1 92
1.8b
0.64
l 29
l .50
650
6 7
6
14
75
PG6
1




1.15
T .32


650
68
6
1 4
75
P G6
2



*
0. 45
0. 19


650
69
6
1 4
75
PG7
0
O'
O'

4.00
1 .68
l .43
1.61
0.76
1.25
1.17
650
70
6
1 4
75
PG 7
1




0.14
0.38


50
7 1
o
1 4
75
PG7
2



.
0.74
0.45


6 50
72
6
14
75
PG 8
0
5. 23
3.56

.


1.46

650
73
6
15
75
PC l
0
10. 42
7. 98
1.70
4 65
0. 33
1 86
1.31
0.85
o 76
74
6
1 5
75
PCI
1


.
.
0.50
1.25


6 7b
75
6
1 5
75
PC 1
2



.
l 0 4
1.78


676
76
6
1 5
75
P C 2
0
8.25
7.42

.

1.11

6 76
7 7
6
1 5
75
PC3
0
12.74
9 d4
6.10
4.30
8.35
2.26
1.29
1 .42
6 76
78
6
1 5
75
PC 3
1




1.93
1.2 1


6 76
7 9
6
1 5
75
PC3
2



0.00
1.31


6 76
80
6
1 5
75
PC4
0
4.75
6.00
5.58
10.00
4.65
1 74
0.79
0.56
676
6 1
6
15
75
P C 4
1




l 6 9
2.34


6 76
82
6
15
75
PC4
2



.
1.47
4.53


6 76
83
6
15
75
PCS
0
7.87
10.12

.


0.78

6 76
34
6
15
75
P C6
0
8.30
10.70
7.4 3
5 96
3. 13
1.73
0. 78
1 .25
6 78
35
6
1 5
75
PC6
1



3.79
2.07


6 76
86
6
1 b
75
PC6
2

.

#
2.08
2.02

m
6 76
8 7
6
1 5
75
P C 7
0
4.59
5.70


#

0. 80
676
88
6
1 b
75
PC8
0
4.66
6.2 1




0.75

6 76


-266-
UBS
MONTH
DAY
YEAR
S TATlN
TIME
TC
1 C
TOC
901
6
l 3
76
FL3
6
40.0
20.3
1 9.3
90 2
6
l 3
76
FL3
7
43.1
2C .6
22.5
9 0 3
6
1 3
7 6
FU3
6
40.6
21 .6
18. 7
904
6
1 3
76
FL3
9
40.5
21.1
2 1.4
90 b

13
76
FL3
1 0
4 1.5
2 1.7
19.8
90 6
6
13
76
FL3
1 1
4 7.0
19.3
26. 7
90 7
6
1 3
7 6
FL3
12
41.0
22.5
l 9.5
908
6
13
76
FL3
l 3
4 0.4
21.1
1 9.3
90 9
6
13
76
FL.3
14
4 l .0
24.5
1 6. 5
9 1 0
6
13
7 6
Fl_3
1 5
3 8.4
20.5
17.9
9 l X
6
13
76
FL3
1 7
39.0
1 9.6
1 9. 4
912
7
14
76
API
17
35.1
1 1 .2
23.9
3 1-3
7
14
76
API
1 8
3 4.5
12.5
22.0
9 1 4
7
1 4
76
API
i 9
4 0.5
12.2
28.3
9 15
7
1 4
76
API
20
37.8
14 .0
23.6
9 1 O
7
14
76
API
21
39.1
11.7
2 7.4
9 1 7
7
14
7 6
API
22
40.2
11.5
1 8. 7
9 18
7
1 4
76
API
23
37.0
1 3 .3
23.7
9 l 9
7
1 5
76
API
1
38. 4
12.5
1 5.9
920
7
1 5
76
API
2
36.1
13.3
22.8
92 1
7
l 5
76
API
3
40.0
1 2 .8
27.2
922
7
15
76
AP 1
4
38. 7
19.8
18. 9
923
7
l 5
76
API
5
39.2
1 0 .6
28.6
9 24
7
1 5
76
API
6
39.0
12.3
26. 7
9 25
7
1 5
7 6
API
7
39.0
14.3
24. 7
92 6
7
1 5
76
API
8
44.4
12.1
32.3
927
7
15
76
API
9
3 9. 4
13.6
25.8
92 8
7
1 5
76
API
1 0
4 0.1
12.9
27.2
929
7
1 5
76
API
1 1
3 5.5
13.4
22.1
93 0
7
15
76
API
1 2
3 6.5
10.9
2 5.6
J5
TP
OP
TP
TU R 6
NH3
CEUR
DS
COND
90 1
0
. 079
0.037
0.042
3. 1
0.08
137
-0. 18
3 59
90 2
0
.101
0.056
0.045
3. 2
0. 1 2
i 1 4
-0.12
358
9 03
0
.078
0.0 38
0.040
2. 6
0.06
122
-0. 07
4d
904
0
. 086
0.042
0.044
2.6
0.06
104
0.08
32 1
9 05
0
. 098
0.038
O.CcO
4. 5
0. 1 1
162
0.16
31 6
906
0
.112
0.037
0.075
a. 2
Oo
208
C. 10
32 l
90 7
0
.108
0. 041
0.087
5.3
0.11
185
0.08
322
908
0
.114
0.040
0.074
5. 0
0. 1 2
164
0. 09
322
90 9
0
.101
0.040
0.06 l
5. 2
0.0 6
233
0.02
33 8
9 1 0
0
. 097
0. 038
0.059
4.5
0.02
129
-0.18
353
9 1 1
0
.0 87
0.036
0.05 1
3. 2
0.0 1
1 l 7
-0. 25
352
91 2
0
. 8 73
0.715
0.158
2.7
0.01
97
-0.20
2 7 7
9 1 3
0
.90 1
0.731
0.170
3. 9
0. 00
101
-0.36
278
91 4
0
.837
0.7 18
0.119
4. 0
U. 04
122
-0. 45
2 65
9 Ib
c
.843
0.731
0.112
5. 9
0.00
88
-0.45
27 1
9 1 b
0
.832
0.726
0.106
6. 2
0. 06
1 1 2
-0.40
267
917
0
.906
0.715
0.191
5.5
0.03
1 13
- 0. 30
2 74
*1 8
0
. 84 3
0. 728
0.115
0.6
0.0 1
122
-0.07
269
9 1 9
0
.817
0.728
0 CB9
2. 6
0. Oo
83
0. 48
2 81
92 C
0
.82 5
0.712
0.113
4.5
0.0 1
142
0.44
2 72
921
0
. 861
0.688
0.173
5. 2
0. 06
l 1 7
0.3 1
272
922
0
.800
0.702
0.098
6. 2
0.10
1 2 1
o. i a
2 78
923
0
.873
0.692
0.181
2.6
0.0b
l 1 5
0.08
2 73
924
0
.9 05
0.718
0.187
4. a
0. 09
1 09
-0.08
272
92 5
0
. 82 7
0.7 14
0.113
4. 0
0.07
l 1 0
-0.17
268
9 20
0
. 882
0.693
0.189
4.8
0.0 1
123
-0.27
268
92 7
0
.901
0. 726
0.175
5. 5
0. 01
127
-0.24
2 70
92 8
0
.912
0.707
0.205
3.3
0.01
167
-0. 18
2 78
929
0
.897
0.712
0.185
4. O
0. 02
1 1 1
0.03
273
93 0
0
.874
0.699
0.175
6. 2
0. 0 7
9 1
0.28
2 74


-284-
CURRELATION COEFFICIENTS / PRUb 8 jHl UNDER HO:
MB ER UF UUSERVATIUNS
FlC
PGPPM2
ECULUR
DTURu
FNH3
LNH3
GILL
-0.11394
-0.1 1331
-0.10676
0. 1 0428
0.10428
-0.10417
0.4166
0.4749
0.4702
0.4360
0.4360
0.4364
53
42
4d
58
58
58
PPR
PRM2
DN H3
DT UP
D TU C
TPR
-0.08389
-0.06435
-0.0&394
0.0 5695
-0.0 5409
-C .05158
0.5503
0.6471
0.6396
0. 6767
0.6922
0.7192
53
5 3
56
56
56
5 1
TIDE
ECULUR
1 hi
CUM 7 lDL
DAYL
PGPPM3
0.04909
-0.03576
-0.02cJ4
C 0 l 9 1 4
-C.01381
0.01010
0.7144
0.8221
0.8738
0.6866
0.9180
0.9428
58
42
53
56
58
53
6 I C
E I C
FI C
ecuNu
F C UND
SEWERS
FTC
1.00000
0.98685
0.86281
0.83394
-0.59367
0.55693
0.0000
0.0031
0.0001
0.00 01
0.0001
0.0001
58
58
24
24
5 8
58
ETC
SUN
E T UC
F T UC
F TP
ETP
0 543 86
-0.51686
-0.44297
-0.4 20 61
-0.40192
0.36885
0.0001
0.000l
0.0005
0. 00 10
0.0018
0.0026
58
53
58
58
58
58
F TUP
ETOP
MINKES
E T U R 6
FTuRb
MUNTH
-0 .32879
-0.32659
-0.31616
-0. 30933
-0.2 966 7
C 28 516
0.0152
0.0159
0.0149
C.0288
0.0364
0.0 300
54
54
58
50
50
58
DAY
ECULUR
VOLUME
MU EP 7 H
DUP
CURBS
-0.27607
0.24943
0.2
-0.24299
-C .2 80 1 7
-0.22775
0.0359
0.1112
0.0623
0. 0661
0.0879
0.0855
58
42
58
58
bo
58
YEAR
D1C
a'vgdo
UEVEL
AREA
TEMP
-0.22005
0.21901
- 0. 2 092 6
-0.20775
-0.20069
0. 1865 6
0.0970
0.1049
0.1162
0.1176
0.1309
0.1647
58
56
57
68
58
57
DCUND
LENGTH
DIP
FNH3
ENH3
DTC
- 0.1 83 99
-0.1764 7
0.15656
0.131 19
0.1 8i ll
0.18111
0.3894
0.1851
0.2498
C. 3 2 63
0.3263
0.3655
24
58
56
58
56
56
UULK
SI LL
M*1 NDU
('DOM IN
UNH3
T UPP
-0.13000
-0.1290b
-0.12340
-C.11720
-0. 1 10 96
- C 10 719
0.33 07
0.3343
C.3602
C.4128
0.4156
0.4449
58
58
5 7
51
56
5 3
CUMTIDE
PGPPM2
T iDE
PR M2
PG PPM 3
PPR
0.10348
-0.1 C 0 9 3
0.094 3o
C.087C1
0 .0 55 79
-0.05545
0 .4395
C. 472 1
0.4810
C. 5356
0 D 9 1 5
0.6 933
58
53
5 6
53
53
53
F CUE OR
SECCH1
TR
DAYL
UT UP
PPRM3
-0.03197
0.03191
-0.02284
-0.02123
0. 0 1 552
-0.00547
0 8 4 0 7
0.8137
0.8738
0.8743
C.90 96
0.9690
42
57
bj
58
56
53
RHO=0 / NU
T GPP
-O. 1 03 3 1
0.4617
53
SECCHI
0.051 19
0.7053
57
PPRM3
0.0012 7
0.9928
53
W ID TH
-0.55478
0.0C01
58
tUP
-0.36961
0.0043
58
FOP
-0.28387
0. 0308
58
AGE
0 .224 4 6
0.0903
58
M AX DU
-0 I 85 81
0.1664
57
DTURB
-0.13045
0.3768
48
ECULUR
-0.1 064 1
0.5024
42
T PR
-0 .05251
0.7144
51
DT UC
0.00207
0.98 79
bo


-200-
Taylor, J.L., and C.H. Saloman. 1968. Some effects of hydraulic
dredging and coastal development in Boca Ciega Bay, Florida.
Fish. Bull. 67: 213-241.
Teal, J.M. 1962. Energy flow in the salt marsh ecosystem of Georgia.
Ecology 43: 614-624. :
Thurlow, E.H. 1974. The water quality and bottom sediment character
istics of New Jersey lagoon developments. Ph.D. Thesis. Rutgers
Univ. 344 p.
Trent, W.C., E.J. Pullen, and D. Moore. 1972. Waterfront housing
developments: their effect on the ecology of a Texas Estuarine
area. _In Marine Pollution and Sea Life. Fishing News (Books)
Ltd. 23. Rosemount Ave., West Byflegt, Surrey. 1-7.
Van de Kreeke, J., and M.A. Roessler. 1975a, Addendum to: A statistical
comparison of daily oxygen minima in artificial and natural
waterways, Marco Island, Florida. Rosenstiel School Mar. Atmos.
Sci., Univ. Miami. Tech. Report UM RSMAS 75020. 153 p.
Van de Kreeke, J., and M.A. Roessler. 1975b. A statistical comparison
of daily oxygen minima in artificial and natural waterways, Marco
Island, Florida. Rosenstiel School Mar. Atmos. Sci., Univ. Miami.
Tech. Report UM RSMAS-75020. 52 p.


-110-
of these water quality parameters. The first three components or
factors can account for 63 percent of the differences in water quality
of these canals.
Phosphorus and color levels appear to be the primary parameters
that separate the water quality of these canals in the first principal
component. However, all of the 12 parameters, except average dissolved
oxygen, minimum dissolved oxygen, and organic carbon concentrations,
have some importance in the first component. The second component
seems to be a carbon and dissolved oxygen factor. The third factor
seems to be due to a combination of the minimum dissolved oxygen,
average dissolved oxygen, turbidity, and Secchi depth values.
Canal/Sampling Day Characteristics
The corrleation matrix, eigenvalues, and eigenvectors for the
canal/sampling day characteristics are shown in Table 17. This prin
cipal component analysis illustrates that the physical attributes of
canals and sampling days did not follow a rigid pattern. The first
component accounts for 24 percent of the set variance and appears to
be a canal size factor (length, width, surface area, volume). The
second factor explains an additional 18 percent of the variability and
seem to be associated with canal age, depth, sill height, and tidal
dynamics. The third factor that separates the canal/sampling day
characteristics is a contrast between the minimum residence time/mean
depth of the canal and the local tidal dynamics.


CHAPTER 2
LITERATURE REVIEW
A review of the existing literature concerning dredged canals,
channels, and holes up to 1974 has been prepared by Polis (1974) under
a grant from the State of Maryland. His reviews that pertain to resi
dential canals are described briefly below.
The work of Trent and associates (Moore and Trent, 1970; Corliss
and Trent, 1971; Trent ejt aJ. 1972) in West Bay, Texas includes
hydrographic, water quality, substrate, phytoplankton, benthic in
vertebrate, oyster, fish, and crustacean data for canal, marsh, and
open bay stations. The canal stations were found to contain more silts
and clays than the marsh and bay stations. Turbidity was higher in the
bay than in the canals, but lower in the marsh than in the canal.
Benthic invertebrates, fish, and crustacean numbers were similar in the
marsh and canal, and tended to be higher in the bay. Phytoplanktonic
primary production per unit surface area was greater in the canal than
in the marsh. A large standing crop of oysters was observed on the
bulkheads of the canal but growth and spatfall were reduced in the
canal relative to the marsh. Oyster mortality was greater in the canal
than in the marsh. Blue crabs and grass shrimp were more abundant in
the marsh than in the canal.
Taylor and Saloman (1968) examined the sediments, water quality,
and primary production of canals in Boca Ciega Bay, Florida. They found
dissolved oxygen levels of at least 3.5 ml/1 (4.9 mg/1) at all times
-6


CHAPTER 6
DISCUSSION
The overall approach in this study of Florida residential canals
can be classified as the "snapshot" approach. Rather than intensively
studying one or two canal systems over an extended period, the strategy
was to examine the short-term behavior of a large number of diverse
canals around the state. By collecting enough "snapshots," it was
felt that a realistic characterization of the metabolism and canal-
estuary nutrient exchanges in Florida residential canals could be
achieved. Although the individual canal observations may not have
resulted in truly representative yearly or seasonal mean values for
each canal system examined, the parameter distributions of this large
a sample size are thought to approximate the true situation in this
type of Florida canal.
From a conservative standpoint, the results should only be viewed
as estimated of the conditions and activities of the individual canals
on the sampling days. A more liberal approach would be to assume that
the canals and sampling days were randomly selected from the population
of all possible canals and sampling days, and that the results repre
sent good estimates of the true distributions in Florida residential
canals. The more liberal viewpoint will be invoked for discussion
purposes, since the sample size is large.
-155-


-184-
velocities, canal shape, bottom topography, entrance sill, and wind
(direction and magnitude). Canal metabolism, canal water quality, and
canal-estuary net-exchanges are dependent on current velocities and
circulation patterns. The complex interrelationships among these factors
is,not well understood.
The equations generated from this study only describe the associa
tions among some of these factors, and do not provide analytical solu
tions to the interrelationships. Nevertheless, possible reasons why
canal attributes were found to be significant factors affecting the
response variables are suggested by the equations.
Canal systems with large water surface areas tend to have lower
planktonic metabolism rates and lower planktonic net-production rates
than those with smaller surface areas. However, the production:respira
tion ratio for the total canal community is higher in larger canals.
Larger canals also have a greater tendency to be sources of carbon
(total and organic) and phosphorus (ortho- and organic) to the adjacent
estuaries than do smaller canals. These relationships may represent
associations between the higher average water current velocities in
the canal systems, the lower probability of particle settling, and the
greater liklihood of any net-production being exported.
Canal width was included as a significant factor in 7 of the 20
regression equations. Increases in canal width tend to increase total
community respiration, the retention of carbon (total and organic), the
turbidity of the exchanged water, and the average and maximum dissolved
oxygen concentrations; but, wider canals also have lower Secchi depths.
My interpretation of this curious combination of effects is that the
water surface of wider canals is more exposed to winds blowing across


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APPENDIX C
Nutrient and water quality data for each canal entrance
and sampling interval.
Nomenclature and units as in Table 2


-85-
Table 8. Regression coefficients for the change in nutrient concen
trations versus time of day (transformed). Model y =
Intercept + Slope (NTIME).
Parameter^
y
Number of
Observations
Intercent
Slope
Probability
Slope ^ 0
R2
Total carbon
1105
38.77
-0.035
0.92
0.00
Inorganic carbon
1103
20.80
-0.24
0.45
0.00
Total organic carbon
1101
17.97
0.19
' 0.60
0.00
Total phosphorus
1108
0..253
-0.0010
0.91
0.00
Ortho-phosphorus
1102
0.214
-0.0018
0.84
0.00
Total organic P
1065
0.043
0.0007
0.68
0.00
nh3
1107
0.086
-0.012
0.0005
0.01
Turbidity
951
3.61
0.16
0.16
0.00
Color
850
104.
3.1
0, 36
0.00
Conductivity
532
31.7
0.69
0.86
0.00
transformation: NTIME = sin (0.2618 (Time 12)), Time 0-24 hours
^Units: as in Table 2


Table 20. Canonical correlation analysis of the metabolism and water quality data sets
(34 observations).
Canonical
Variable
Mean of Metabolism Group
Canonical Variable
Mean of Water Quality
Canonical Variable
1
-0.32
-0.66
2
-0.32
-0.03
3
-0.38
1.61
4
0.05
1.13
5
0.03
-2.01
6
-0.19
0.20 '
7
0.28
1.85
8
-0.18
1.01
9
0.48
0.82
Canonical
Correlation
Chi-Square
DF
Prob > i
1
0.96
209
108
0.000
2
0.92
145
88
0.000
3
0.86
102
70
0.007
4
0.81
70
54
0.065
5
0.72
45
40
0.247
6
0.69
28
28
0.427
7
0.50
13
18
0.748
8
0.41
7
10
0.720
9
0.33
2
4
0.591
-121-


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-86-
to the mean concentrations was ammonia. The rate of change of ammonia
concentration per unit transformed time is -0.012 mg/1 (non-linear on
an hourly basis). The transformed values of the hour of the day ranged
from -1.0 at 0600 hours to +1.0 at 1800 hours. Therefore by stustituting
these values into the linear equation (Table 8), it can be seen that
the mean ammonia concentration tends to be 0*012 mg/1 greater at sun
rise than at noon, and 0.012 less at sunset than at noon. This results
in an expected change in ammonia concentration of 0.024 mg/1 from
sunrise to sunset, attributable to a diurnal cycle.
The lack of a significant diurnal effect on nutrient concentra
tions, except for ammonia, suggests that a serious bias is not intro
duced by neglecting the time of day for tidal phases. The possible
bias associated with a diurnal ammonia cycle and the estimated net
movements of ammonia across the canal mouths is limited to Gulf Coast
canal observations that met the conditions given above. The Atlantic
canal systems generally experience semi-diurnal tides.
1975 Data
The nutrient exchange results obtained during the first phase of
this study, wherein four pairs of canals (PG, PC, LX, and PB) were
sampled on four occasions, provide information on the seasonal changes
and on the variabilities between canals that appear identical. The
two-way design (4 locations x 4 seasons, with replication) of this phase
of the study allowed analyses of variance to be performed on the data
in order to test for significant location and season effects. The
nutrient exchange data from the 1975 work are included in Table 7.


-58-
more variable than the total canal community (C.V. = 59 and 50,
respectively).
Figure 20 shows the frequency distribution and descriptive
statistics for the degree of plankton dominance of the total community
gross primary production for the 56 canal observations. The distri
bution seems to be somewhat bimodal with plankton production accounting
for 50 percent or less of the total community production in 31 of the
54 observations. In other words, some canals were plankton dominated
on the day sampled but others were not. The range of values (PGPPM2/
TGPP) was 0.16 to 1,0. The mean value (0.60) for all the observations
may be misleading since few of the responses were this value.
1975 Data
Thirty-two of the fifty-six metabolism observations were obtained
during 1975 in a study for the Florida Department of Environmental
Regulation (see Fox et ai., 1976). The design of the project consisted
of four locations (Punta Gorda, Port Charlotte, Loxahatchee River, and
Pompano Beach) with two similar canals per location, four stations per
canal (bay, mouth, middle, andback), and four sampling seasons (March,
June, September, and November).
This design allowed the factors of location, season, and distance
along the canals to be evaluated for significant effects on the
metabolic levels. In addition to making possible the assessment of
the seasonal and distance variabilities, the unexplained or inherent
variability between canals that appeared identical could be determined
using analysis of variance.
The canal mean metabolic levels from this 1975 work are included


-14-
The factors responsible for the differences in water qualities were
not clear. Rankings of the canal water qualities did not simply reflect
differences in a single factor such as canal depth, age, flushing rates,
or local estuarine water quality.
No clear consensus exists in the literature for the most important
factor affecting water quality in residential canals. Excessive depths
and poor circulation and flushing are most frequently thought to lead
to poor conditions. The dead-end nature of the canals and sill forma
tion at the canal entrances are not conducive to good mixing and flush
ing. Local tidal dynamics and their influences on canal flushing rates
are considered important by several investigators. The water quality
of the adjoining water bodies, while not frequently mentioned by
investigators working in single locations, undoubtedly affects the
canals. In addition to canal depth, other canal characteristics such
as length, width, configuration, bottom topography, orientation to the
wind, and substrate type, are often identified as important factors.
Allochthonous sources of organic and inorganic materials and their
management, appear to be significant in some canal systems.
Many aspects of the impact of canal dredging on the coastal zone
have been discussed by the investigators cited above. Reviews of the
subject can be found in Lindall and Trent (1975), Adkins and Bowman
(1976), and Odum (1970). Possible impacts of canal dredging in the
coastal zone given by these authors and their referenced literature,
include:
1. Destruction and loss of nursery areas for coastal fisheries.
2. Biological productivity losses of dredged areas. Taylor and
Saloman (1968) estimate that $1.4 million of annual revenue is


-120-
This finding is somewhat surprising since one would expect the produc
tion-respiration cycle within the canals to affect the net exchanges
of organic and inorganic nutrients between the canals and adjacent
estuaries.
Metabolism vs. Water Quality
The results of the canonical correlation analysis for the metabolism
and water quality data sets are shown in Table 20. The first three
pairs of canonical variables are significantly correlated. The first
canonical variable of the metabolism set is most closely correlated
(though inversely) with the production:respiration ratios of the total
community and plankton, the plankton production per square meter and
the extent of plankton dominance in the canals. The first canonical
variable of the water quality set is most closely correlated with the
turbidity levels and the total and organic carbon concentrations (in
versely) in the canals. Therefore, the greatest association between the
metabolic characteristics and water quality of these canals appears to
be between the amount of carbon and turbidity in the water, and the
autotrophic tendency of the canals, particularly with the plankton.
Higher levels of carbon are associated with greater autotrophy.
The second pair of canonical variables (independent of the first
pair) appears to represent the association between the total community
and surface plankton metabolism levels and the maximum dissolved oxygen
concentrations, phosphorus levels, Secchi depths, color values, and
water temperatures. Higher metabolic levels are associated with higher
maximum oxygen values, higher phosphorus concentrations, lower Secchi


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Table 24. (Continued)
Normalized Vectors Associated with Water Quality Group
ETC
ETOC
E0P
ETOP
ENH3
ETURB
EC0L0R
AVGDO
MAXDO
MINDO
TEMP
SECCHI
0.007
-0.002
0.893
-0.796
0.806
-0.002
-0.002
-0.008
0.002
0.011
-0.021
0.008
-0.016
0.007
-0.272
-2.050
1.125
0.031
0.000
0.015
0.004
0.011
-0.005
-0.188
-0.003
0.011
-0.301
0.942
1.120
-0.059
0.000
-0.044
0.005
0.018
-0.019
-0.032
0.019
-0.009
-0.021
0.034
1.777
-0.031
-0.001
-0.061
0.005
0.059
0.030
-0.190
-0.014
0.019
-0.423
0.378
0.426
0.026
-0.002
-0.061
0.005
-0.065
0.058
-0.131
-0.007
0.006
-0.356
-1.162
2.031
0.048
-0.003
-0.039
-0.008
-0.010
0.060
0.095
-0.011
-0.013
0.484
-1.588
-0.976
-0.022
0.000
-0.121
0.056
0.033
-0.032
-0.003
0.008
-0.005
0.572
-5.568
-1.251
0.086
0.001
-0.063
0.013
0.024
-0.030.
-0.058
0.011
-0.016
0.898
-6.44
-1.057
-0.062
-0.001
0.058
-0.009
-0.076
-0.056
-0.303
9
-132-


-48-
Table 2.
(Continued)
D-prefix
Difference between flood and ebb concentrations (Flood Ebb)
Sign convention minus sign (-) indicates Flood value was less than
Ebb value
positive sign (+) indicates Ebb value was less than
Flood value
WATER QUALITY
AVGDO
Average dissolved oxygen concentration (mg/1)
MAXDO
Maximum dissolved oxygen concentration (mg/1)
MINDO
Minimum dissolved oxygen concentration (mg/1)
SECCHI
Secchi depth (meters)
TEMP
Water temperature (C)
E-prefix
Nutrient and water quality parameters from Exchange data
LENGTH
CANAL/SAMPLING DAY CHARACTERISTICS
Centerline length, entrance to most distant point (meters)
WIDTH
Average canal width (meters)
MDEPTH
Average canal depth (meters)
AREA
Canal water-surface area, total (meters)
VOLUME
Water volume in canal at mean water level (cubic meters,
MDEPTH AREA)
SILL
Sill height (meters)
AGE
Canal age (years)
BULK
Percent bulkheaded, canal sides
CURBS
Presence or absence of curbs and gutters in development
(1 or 0, respectively)
SEWERS
Presence or absence of a sewer system in development
(1 or 0, respectively)


-167-
correlated pairs of water quality and physical factors also require the
consideration of metabolic patterns to be interpretable. For example,
the correlation of low Secchi depths, high organic phosphorus concen
trations, high color, and high turbidity with greater daylength, more
solar insolation, and greater canal depths, makes little sense until
phytoplanktonic biomass trends are examined. If organic phosphorus is
considered as an indicator of phytoplanktonic biomass, then the expected
relationship between surface plankton biomass, season of the year, and
Secchi depths, was observed. It is the inclusion of greater canal
depths that is puzzling. Deeper canals should have poorer mixing and
greater settling tendencies for particles contributing to turbidity;
therefore, they should have greater Secchi depths. Perhaps this cor
relation represents a special set of circumstances, where inorganic
particles do settle, and the settling allows greater light penetration
and therefore greater phytoplankton growth. The high color require
ments of this correlation, then, suggest that an influx of freshwater
and nutrients (rainy season in the summer) is occurring, which further
promotes phytoplankton growth.
The seventh and eighth pairs of correlated factors (Table 24) in
the water quality and physical characteristics data sets imply that
canals tend to be more turbid and have lower average dissolved oxygen
concentrations during the summer months. For a given season, larger,
deeper, more developed canal systems are less turbid and have greater
average dissolved concentrations. This pattern is substantiated by the
fact that increased canal surface area leads to a decrease in plankton
production (areal and volumetric), a decrease in planktonic net pro
duction, and an increase in the total community's net production of


-24-
Floating debris is regularly removed from the canals. Limited boating
activity was observed. Canals 3 and 6 were sampled four times during
1975, while Canal 9 was sampled twice. Local tidal dynamics are quite
irregular in amplitude and frequency. The adjoining Peace River has high
phosphorus levels as a result of phosphate mines in its drainage basin,
and experiences lowered salinities during the rainy summer season.
Port Charlotte (PC. Figure 3). The three canals in the Port
Charlotte development are across the Peace River estuary from the Punta
Gorda canals, but are older and more developed than Punta Gorda Isles.
A sand bar (exposed at low tides) separates the dredged channel along
the development from the river. Southerly winds in the spring and
summer tend to hold floating debris in the canals. A secondary sewage
treatment plant in Port Charlotte enters the end of a 4,000-foot canal
whose entrance to the Peace River is approximately 2,000 feet east of
the canals. Canals 3 and 6 were sampled four times during 1975. Canal
9 was sampled twice.
Pompano Beach (PB. Figure 4). The three canals sampled at the
Pompano Beach location are representative of many canals in that area.
Extending off the Intracoastal Waterway, the canals are old, narrow,
and completely developed with homes using septic tanks (until 1975).
Considerable boating activity exists along the Intracoastal Waterway
and within the canals. Tides in the area are uniform and semi-diurnal.
The nearest oceanic inlet (Hillsboro Inlet) is approximately six
kilometers north.
Loxahatchee River (LX. Figure 5). Dredged and abandoned about
1960, the two canals at this site are approximately seven kilometers
up the Loxahatchee River from Jupiter Inlet. One of the canals (LX3)


-127-
Table 22. Canonical correlation analysis of the exchange and water
quality data sets (38 observations).
Canonical
Variable
Mean of Exchange Group
Canonical Variable
Mean of Water Quality Group
Canonical Variable
1
-0.00
-0.41
2
0.05
-0.01
3
0.02
-0.33
4
-0.01
-0.09
5
0.04
-0.66
6
0.01
1
o
7
0.00
-1.98
Canonical
Correlation
Chi-Square
DF
Prob > Chi-Sq
1
0.89
107
98
0.238
2
0.79
63
78
0.874
3
0.65
36
60
0.992
4
0.55
21
44
0.997
5
0.46
11
30
0.998
6
0.38
5
18
0.998
7
0.16
0
8
0.999


-169-
Table 32. Significant
factor effects
on canal
water quality
parameters.
AVGDO
MAXDO
MINDO
SECCHI
AREA
WIDTH
+
+

DEPTH
+
DEPTH*SILL
DEPTH*AGE
-
DEPTH*TIDE
DEPTH*CUMTIDE
-
SILL
AGE
-
+
TIDE
-
CUMTIDE
MINRES
+
DEVEL
DEVEL*AGE
+
DEVEL*TIDE
DEVEL*CUMTIDE
+
DEVEL*MINRES
-
BULK
-
CURBS
-
SEWERS
- ' '
+
DAYL
__
SUN
+
-
FTC
+
_
FTOC
-
+
FTOP
-
-
FTOC*FTOP
+
FOP
+
FNH3
FOP*FNH3
-
FTURB
FCOLOR
-
-
-
TURB*COLOR
+
2
R -percent
91
76
88
93
Nomenclature and units as in Table 2
Sign convention as in Table 31


-56-
N = 56 Mean = 8.20 Std. Dev* = 5.45 Range 0 to 23.5
C.V.% = 66
Figure 16. Frequency distribution and descriptive statistics for
total community respiration (g 02/m^-day), averaged
by canal.
2
g O2/111 -day
N = 56 Mean = 3.01 Std. Dev. = 1.83 Range 0.46 to 7.98
C.V.% = 61
Figure 17. Frequency distribution and descriptive statistics for
planktonic respiration (g 02/m^-day), averaged by canal


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728-FLUX -SAS -FT12F001
UBS
MONTH
DAY
YEAH
STATION
TIME
TC
IC
TOC
1
3
21
75
PGO
23
26.0
6.0
18.0
2
3
21
75
Pj 6
23
30. 0
8.3
21.7
3
3
21
75
P G 3
0
25.0
9. 3
15. 7
4
3
21
75
PG3
0
31.5
9.0
22.5
5
3
21
75
PG 6
2
25. 7
9. 5
1 6.2
6
3
21
75
PGO
2
27.7
6.8
18.9
7
3
2 l
75
PG 3
3
26.5
9.0
18.5
a
3
21
75
PG3
3
29.0
13.5
15. 5
9
3
21
75
PG 6
5
27 .0
18.0
9.0
10
3
21
75
PG O
5
28.0
8.8
19.2
1 1
3
21
75
PG 3
5
26.0
7. 3
1 8. 7
1 2
3
2 1
75
PG3
5
32.0
9.0
23.0
1 3
3
21
75
PG 6
a
27. 5
9. 5
18.0
1 4
3
21
75
PG 6
a
2 o 5
9.0
17.5
1 S
3
21
75
PG 3
a
25.5
8.3
17.2
l a
3
2 1
75
PG 3
a
26.5
9. 0
17.5
1 7
3
21
75
PGO
11
27.0
9.7
17.3
1 8
3
21
7 5
PG O
11
27.0
16.3
10.7
19
3
2 l
75
PG 3
1 2
26.5
1 0. 0
16.5
20
3
21
75
PG 3
1 2
30 .5
13.2
17.3
2 l
3
2 1
75
PG 6
14
26.0
16. 0
12.0
22
3
21
75
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1 4
30.7
1 7. 0
13.7
23
3
21
75
PG3
1 5
7.0
9.0
18.0
24
3
2 1
75
PG 3
15
2 /. 5
15.0
14.5
25
3
21
75
PGO
17
24.0
13.0
11.0
26
3
21
75
PG 6
l 7
2 6.5
10.7
15.8
2 7
3
21
75
PG 3
ia
25.5
15. 0
10.5
28
3
21
7b
PG 3
l a
25.0
10.0
15.0
29
3
2 1
75
PG 6
20
24.0
9.0
15.0
30
3
2 1
75
PGO
20
26.5
9. 5
17.0
UBS
TP
OP
TUP
T UKB
NH3
COLOR
US
CON
1
0.431
0.32 0
0.111
2.7
0.02
.
-73

2
0.440
0.375
0.0o5
4.5
0.04
.
-73

3
0.425
0.375
0.050
3.0
0.02

-73

4
0.74 7
0.450
0.2 97
13.0
0 6

- 73

5
0.435
0.350
0.085
3.5
0. 02

-62

6
0.468
0.300
0.1 Go
4.2
0.05

-62

7
0.43 9
0. 360
0.0 79
3.0
0 04
-62

a
0.082
0.370
0.312
a. 2
0.04

-62

9
0.429
0.350
0.0 79
3.4
0.03

18

1 c
0 .404
0. 360
0. 004
4.2
0.03

18

11
0.419
0.350
0.069
3. 1
0.02

1 8

12
0. 778
0.42 5
0.353
11.0
0 06

18

13
0.430
0.385
0.045
3.8
0.0 1

62

1 4
0.459
0.375
0.084
4.0
0.04

62

1 5
0. 431
0.36 0
0.0/1
3.5
0.04

62

1 6
449
0.375
0.0/4
4.4
0. 05

62

1 7
0.425
0.32 5
0.100
3.6
0 .04

1

l a
0.471
0.300
0.0/1
9.5
C. 0 3

1

19
0.420
0.300
0.000
3. 2
0.03

1

2 0
0.488
0.28 0
0.2 08
9.1
0.02
1

21
0.425
0.35 0
0.0 75
*
0. 02
-26

22
0.519
0.31 2
0.207
9*6
G .05

-26

23
0.421
0.36 0
O.Col
2.7
0 .02

-26

2 4
0.408
0.325
0.143
7. 7
0.05

-26

2b
0.4 02
0.400
0.002
2.0
C .0 1

1 5

2b
0. 451
0.360
0.091
8.1
0.02

15

27
0.4 03
0.375
0 C2o
4. 1
0.02

l 5

28
0.552
0.375
0. 107
10.5
C .02
1 5

29
0.392
0. 375
0.017
3. 7
0. 0 l
24

30
0.479
0.400
0.0/9
7.7
0.05

24
m
-236-


CHAPTER 7
CONCLUSIONS
Sixty-one observations of oxygen metabolism, canal-estuary
nutrient exchange, and water quality in 35 residential canals at 12
locations in the State of Florida demonstrate that the conditions and
behavior of canals are highly variable. Simple descriptive models for
the individual metabolism, water quality, and nutrient exchange para
meters were able to explain most (greater than 70 percent for 17 of
the 20 dependent parameters) of the observed variabilities on the basis
of canal and sampling day physical characteristics and the adjoining
estuarine water quality. The major conclusions of this study are
1. Total community gross primary production varied from undetectable
2
to 24.9 gm 02/m -day, with a mean value of 8.59.
2. Planktonic gross primary production varied from 0.40 to 23.9 gm
2
02/m -day, with a mean value of 4.91.
3. From a trophic standpoint, canal systems can be autotrophic or
heterotrophic. Community production:respiration ratios ranged from
0.31 to 2.95, with a mean value of 1.16. Planktonic production:
respiration ratios ranged from 0.29 to 5.02, with a mean value of
1.93.
4. Not all canal systems are plankton-dominated. The percent of total
community gross production accounted for by the planktonic component
varied from 16 to 100. The mean value was 60 percent even though
31 of 54 values were 50 percent or less.
-193-


Table 7. Canal-estuary exchange results for the nutrient and water
quality parameters.
Nomenclature and units as in Table 2


-17-
Figure 1. Sampling sites within Florida.


-304-
CO RKELAT I UN CO EFF 1C IENTS / PRUU > |Rj
MB ER OF OBSERVATIONS
UNDER HO:
RHU= 0 / NU
TGPP
FTP
C.27089
0.0498
S3
TEMP
0.26581
0.0477
5 6
AREA
0.26151
0.0516
bo
F UP
0.25730
0. 0629
53
DUP
-0.25706
0.0686
51
ETUC
0.25 256
0.0681
53
LENGTH
0 .24579
0.0679
56
F TURB
0.24196
C.0975
48
MDEPTH
0.24086
0.073 7
56
TIDE
0.2 3b6o
0.0804
56
F T UP
0.2 26 96
0.1135
49
DTC
0. 21093
0.1373
51
ETURD
0.18877
0.1988
48
ETUP
0.18795
0.1959
49
FTC
0. 18542
0.1838
53
SEWERS
0.17645
0.1933
56
DIOC
0.17477
0.2200
5 1
DTP
-0.17322
0. 224 1
51
YEAR
0.1 6943
0.2119
56
DTUP8
0 16512
0.2 728
46
DC OLOR
0.1 5336
0.34 4 d
40
ETC
0.15036
0.2825
53
MiNRBS
0.13923 -
0.3061
56
DC UNU
0.13820
0519o
24
DAYL
0.13491
0.3215
56
BULK
0. 1 2003
0.3 7 8 2
56
SUN
0.10948
0.4219
56
M IN DU
-0.10884
0.4246
56
ENH3
0.1079 7
0.4416
53
FNH3
0.10797 -
0.4416
53
El C
0.10719
0.44 49
53
F IC
-0.10331
0.4617
53
T PR
0.102 76
0. 4597
54
MONTH
-0.06071
0.6567
56
AVGDU
0 .05992
0.6609
56
OIC
-0.05681
0.6 92 1
51
DTP
0.04275
0.7658
5 1
DNH3
0.03447
0.8 10 2
51
CUMTIUE
-0.03140
0. 81 63
56
ECULUk
-C.02781
0.86 4 7
40
PPR
0.00836
0.9512
56
FCULOR
0.00132
0.9935
40
TR
TP
l.00000
0.0000
56
TGPP
0 .88980
0.0001
56
MAXDU
0.549 7U
0.0001
56
Pk M2
0.5 26 1 5
0.0 0 0 T
56
PPRM3
0. 50 l 92
0.0001
56
AGE
0.42031
0.0013
56
PGPPM3
0.41103
0.0017
56
WIDTH
0.4C31 l
0.0021
56
PUMIN
-0.39180
0.0034
54
T LMP
0.36044
0.0064
5 6
SECCH
-0.34333
0. OC96
56
FTURB
0.33093
0.0216
48
CURBS
0.33072
0.0128
56
SILL
0 .32778
0.0137
56
E TP
0.32 777
0.0166
53
DA Y
-0.32703
0.0139
5 6
FTP
0.3 124 7
0.0227
53
FT UP
0.31175
0.0292
4 9
LP
0.30822
0.0247
53
PGPPM2
0. 2797 7
0 .0368
56
DCOLUR
0.2 773 0
0.0832
40
DEV EL
0.27497
0.0403
56
ETP
0.273 1 l
0.0576
49
F UP
0.2661l
0.0641
53
DT Up f)
0.26367
0. 0766
46
r pp
C 2~>659
0.0823
54
ETURB
0.23245
C 1 1 1 9
48
DAYL
0 .22641
0.0934
56
VULUML
0.21620
0.1095
56
MDEPTH
0.21272 -
0.1155
56
F CUND
0.20289
0.34 l 7
24
MNDU
-0. 1 9560
0 14 81
56
DUP
-0. 1 9492
0.1705
51
ECONU
-0.18849
0.3 777
24
T 1 DE
0.17975
0.1850
56
PPP
-0 1 77 76
0.1900
56
DTC
0.1 74 74
0.2200
51
M INktS
0.15988
0.2392
5u
DT UC
0.144 30
0. 31 24
51
DTP
-C.13912
0.3302
51
LENGTH
0.12247
0.3666
56
AREA
0.1 0645
0.4349
56


763-FLUX
-SAS -FTl2F001
*
UbS
MONTH
DAY
Y LAM
S TAT I UN
DEPTH
T GPP
TM
1
3
22
75
PGl
0. 0
2.04
4.14
2
3
22
7b
PGl
1.0


3
3
22
75
Pol
3.0


4
3
22
75
PG2
0.0
0.00
0.96
5
3
22
7 6
P 63
0 .0
1.4 1
l .08
6
3
22
75
P63
1 0


7
3
22
75
P 63
2.5


8
3
22
75
P64
0.0
1 .95
2 .34
9
3
22
75
P64
1.0


1 0
3
22
75
P 64
2.5


1 1
3
22
7 5
P 6 5
0.0
5 .49
6 .54
1 2
3
22
75
PG6
0.0
2.10
0. 96
1 3
3
22
75
P 66
1 .0


l 4
3
22
75
P6 6
2.5


1 5
3
22
75
P 67
0.0
0.66
1.86
l 6
3
22
75
P67
1 .0


1 7
3
22
75
PG 7
2. 5

.
18
3
22
75
PG8
0.0
5.10
6.30
1 9
3
23
75
PCI
0.0
9 .66
8.70
2 C
3
23
7 5
PC 1
3. 0

.
2 1
3
23
75
PC2
0.0
10 .62
13.10
22
3
23
75
PC 3
0. 0
5.05
8.60
23
3
2 3
75
PC3
1.0

.
24
3
2 3
75
PC3
2 .5

.
25
3
23
75
PC4
0.0
4.89
6.60
2b
3
23
75
PC4
1.0
.
. '
2 7
3
23
75
PC4
3.0

.
28
3
23
75
PCS
0.0
3.2 1
4.14
29
3
23
75
PC6
0.0
8.61
7.16
30
3
23
75
PC7
0.0
2.70
b 1 C
UBS
PGPPM2
PM M2
PGPPM3 PPMM3
rPk
PPM
SUN
1
2.48
3.81
2.82 1.84
0.49
0.65
6 02
2

0.60 1.10


602
3
'

0.17 1 .24


602
4




0. 00

602
5
l 73
0.30
2.24 0.31
1.31
5. 77
602
6


0.21 0.10


602
7


0 .30 0.00


602
8
l .01
1 .39
2.05 0.72
0.83
0.73
602
9


0.00 0.54


602
l 0

0 .00 0 .22
.

. 602
1 1




0 .84

602
1 2
2.27
2.68
2 t>9 0.91
2. 19
0.84
6 02
13


0.41 1.31
.
m
602
14


0.21 0.27


602
1 5
2.08
2.49
2.84 0. oO
0.35
0. 83
602
1 6

#
0 .0 7 0 .6 7
.

602
l 7


0.5b 1.06
.

602
1 8




0. 81

6 02
1 9
7.05
1.14
4.69 0.41
l 1 1
6.18
642
20


0.01 0.35
.

642
21




0.8 1

642
22
1 1.33
10.77
7.13 5.08
0.58
1.05
6 42
23


3.78 3.94


642
24
m

2.10 2.32


b42
25
6. 79
3.05
3.94 4.15
0.72
1.76
6 42
26
'

2.94 1.51


6 42
2 7


0.41 1.70


6 42
28




0.77

642
29
4.80
2.56
3.20 1.70
l 20
1.67
642
30
3.49
2.11
3.49 1.41
0.53
1.65
642
-202-


I certify that I have read this study and that in my opinion it
conforms to acceptable standards of scholarly presentation and is fully
adequate, in scope and quality, as a dissertation for the degree of
Doctor of Philosophy.
Jackson L. Fox, Chairman
Associate Professor of Environmental
Engineering Sciences
I certify that I have read this study and that in my opinion it
conforms to acceptable standards of scholarly presentation and is fully
adequate, in scope and quality, as a dissertation for the degree of
Doctor of Philosophy.
¡attack,
Patrick L. Brezonik
Professor of Environmental
Engineering Sciences
I certify that I have read this study and that in my opinion it
conforms to acceptable standards of scholarly presentation and is fully
adequate, in scope and quality, as a dissertation for the degree of
Doctor of Philosophy.
fames P. Heaney
Associate Professor /6f Environmental
Engineering Sciences


I certify that I have read this study and that in my opinion it
conforms to acceptable standards of scholarly presentation and is fully
adequate, in scope and quality, as a dissertation for the degree of
Doctor of Philosophy.
Suzanne E. Bayley
Assistant Professor of Environmental
Engineering Sciences
I certify that I have read this study and that in my opinion it
conforms to acceptable standards of scholarly presentation and is fully
adequate, in scope and quality, as a dissertation for the degree of
Doctor of Philosophy.
Assistant Professor of Statistics
This dissertation was submitted to the Graduate Faculty of the College
of Engineering and to the Graduate Council, and was accepted as partial
fulfillment of the requirements for the degree of Doctor of Philosophy.
March 1977
Dean, Graduate School


-43-
assumed to have zero slope and have constant area, so that changes in
water level were proportional to the flow volumes.
During the first two sampling periods at the Punta Gorda, Port
Charlotte, Pompano Beach, and Loxahatchee River canals, surface and two
meter depth water samples were taken from the center of the canal
entrance (ca. 50 meters inside). For the remaining exchange observa
tions, hourly surface water samples were taken near the canal shoreline
by Serco Model NW3-8 Automatic Samplers. All water samples were
preserved with a solution of saturated mercuric chloride (1 ml/1) and
kept on ice until returned to the laboratory for analysis.
Total carbon and total inorganic carbon concentrations were deter
mined with a Beckman Model 915 Total Carbon Analyser. Total organic
carbon concentrations were then determined by subtracting the inorganic
carbon concentrations from the total carbon concentrations. Total
phosphorus concentrations were determined by persulfate digestion and
the Murphy-Riley single reagent method (APHA, 1971) Ortho-phosphorus
concentrations were also determined by the Murphy-Riley technique. Total
organic phosphorus concentrations were obtained by subtracting the
ortho-phosphorus value from the total phosphorus value. Ammonia analyses
were performed with an AutoAnalyzer using the indophenol method (E.P.A.,
1974). Turbidity levels were determined with a Hach Model 2100A
Analytical Nephelometer. Apparent-color was measured at a 420 nm
wavelength on a Bausch and Lomb Spectronic 88 spectrophotometer.
Specific conductance (25 C) values were obtained with a Beckman Model
RC 16B2 Conductivity Bridge.


-308-
CORRELATION COEFFICIENTS / PkUb > J R| UNDER HORHO=0 / U
MBER OF OBSERVATIONS
PPRM3
DTC
0.07353
0.6061
51
DP
-0.06749
0.6380
5 l
FC OLOR
0.06710
0.6b06
40
YEAR
0.0 649 6
0.6342
56
DCUND
0.05636
0.7937
24
D TOC
0.05543
0 .6993
51
CUMTIDE
0.05389
0.6932
5 6
FNH3
- 0.05015
0.72 14
53
ENH3
-0.05015
C.72 l 4
S3
TPR
0.03978
0.7752
54
BULK
0.03941
0.7731
56
DTP
0. 036 56
0.7989
5 1
DIC
-0.03204
0.8234
51
ECOLOR
0 .02908
0.858o
40
ETURB
0 .0 1630
0.9017
48
AVGO
0.01803
0.8950
56
CUk b3
0.00610
0.9644
56
E IC
-0 .0 054 7
0.9690
53
MINRE S
0.004 75
0.9723
56
SEwERS
0.00 4C5
0.9764
56
F IC
0.00127
0.9928
53
TP R
TPR
1 .000 00
0.0000
54
F TOC
0.46633
0.0006
51
ETUC
0.46153
0.0007
51
P PR
0.41425
0.0018
54
FTC
.0.4 06 38
0.0029
51
AREA
0.39 6 09
0.0030
54
PGPPM2
0.38891
0.0037
54
ETC
0.363C7
0 .0066
51
LENGTH
0 .36140
0.0073
54
ET LK b
-0.3265 7
0.0 266
46
VOLUME
0. 3 0667
0. 0241
54
SEWERS
0.29524
0.0302
54
T I DE
0.26496
0.0368
54
FTURB
-0.2840 5
0.0557
4 6
DA YL
-0.25338
0.0645
54
TR
-0 .23859
0.082 3
5 4
TEMP
-0.2314/
0.0922
54
E TUP
-0.2 2360
0. 1 3 08
4 7
PDUM1N
0.21942
0.1109
54
PGPPM3
0.21357
0.1210
54
DC OLOR
-0.20061
0.2272
38
BULK
0 .1692 7
0.1705
54
F T OP
-0.1 883 4
0.2049
4 7
FCUNO
- 0. 185 11
0.386 5
24
FNH3
0.18460
0. 1947
51
EN H3
0.18460
0.1947
5 1
M INRE5
-0.18268
c.iaei
54
ECND
-0.1 7838
C. 4043
24
MA XDU
0.17070
0.2172
54
MONTH
0.16333
0.2380
5 4
FCOLOR
-0.15511
0.3524
36
ECULUR
-0.14905
0.3718
3b
fc TP
-0.12583
0.3790
51
FTP
-0. 12134
0.3963
51
AVGOO
0.11601
0.3954
54
WIDTH
C 1 1442
0.4100
54
DE VEL
0.10876
0.433 7
54
E OP
-C.10295
0 .4722
5 1
T GPP
0. 1 02 76
0.4597
54
S1 EL
-C.09561
0.4907
54
SECCHI
0.09572
0.4911
54
CUMT IDE
0.09128
0.5117
54
D TUP
0 .06693
0.5434
49
YEAR
0.0871 0
C.53 l 2
54
M I NO
0.08o52
0.53 8o
54
DTC
C .0 61 2 5
0. 5789
49
U TUKb
0.07433
0.631b
44
DNH3
0.0 7 4 2 8
0 .6120
49
DT OC
0.06881
0.6388
4 9
OOP
-0.06408
0.6616
49
FOP
-0.06288
0.6611
51
Eli-
- 0.0 5 251
0.7144
51
f IC
0.051 56
0. 7l92
5 l
DAY
0. 04 91 8
0.7239
54
DCUND
-0.04 595
0.63 1 2
2 4
PPRM3
0 .03976
C. 7752
54
D IC
-0.03121
0.8314
49
DTP
0 .02346
0.872 9
49
MDEH TH
-0.01259
0. 928 0
54
SUN
0.0 1222
0. 9 30 1
64
PR M2
C.01129
0.9354
54
CURBS
0.00679
0 .96 l 1
54
AGE
0.00021
0.9968
54


-296-
CURRELAT I ON CU E FF 1U EN TS / Pkb > |Rj UNDER H0:RHO=0 / NU
MB L R Of- OBSERVATIONS
ENfl3
FTUKB
0.0 7294
0.6147
50
VULUME
- 0. 0 721 l
0.550 l
7 1
PGPPM3
0634 3
0.651 6
53
\h I D r H
0.0 62 97
0. 60 1 9
71
YtAR
-0.06205
0.6072
7 1
DT UR B
0.06107
0.6601
48
SUN
0 .0603 1
0.6680
53
E TURO
0.05607
0 .,6867
50
DUP
-0.05 1 72
0.7050
5 6
PPRM 3
-0.05015
0.7214
53
TR
0.04507
0.74 86
53
AREA
-0.04259
0.7243
71
LENGTH
-0.03720
0.7581
71
MINDU
-0.03005
0.8050
70
St ifit KS
-0.02259
0.6516
71
FDUMlN
0.02179
0.8794
5 1
T IUt
-0.0 1529
0.699 3
71
E7 UP
0.01153
0.9341
54
DTC
-C.0083b
0. 9513
56
CUMTIDE
0.00715
0.9528
7 1
P GPP M2
0.00390
0.9779
53
DNH3
DNH3
1.00000
0.0000
69
PPR
0.32662
C.0193
5 l
DIG
C.30612
0.0222
66
SUN
0.27424
0.0615
51
PGPPM3
-O .26580
0. 0b 94
5 1
ETURO
0.24494
0.0934
48
DCUNU
-0 .24367
0.2512
24
FCND
-0.21709
0.30B2
24
r I DL
-0.18597
0.1260
6 9
ECUND
-0. 1 84 72
0.3876
24
YEAR
0.18284
0.132b
69
MUN TH
-0.17465
0.150/
6 9
ENH3
0. 1/426
0.1521
69
FNH3
0.17426
0.1521
69
tCOLUR
0.17223
0.2754
42
FT UR b
0.16973
0.2466
48
FCOLUR
0.16442
0.29bl
4 2
FI UP
0.16274
0.2490
52
PGPPM2
-0.15967
0. 2631
5 1
WIDTH
0.14932
0.2207
69
ETUP
0.14647
C. 300 l
52
ETQC
0.14405
0.2377
69
DTC
0.1 3 3 o 5
0.3261
5 6
FTUC
0.13364
0.2 74 0
69
AGE
-0.12705
0.3094
66
M1NDU
-0.12669
0.3032
68
SE Vv ER S
0.12642
0.3006
69
CUMTIDE
-0.12260
0.3156
6 9
PR M2
0 113 9 6
0.4259
51
EIC
-0.11096
C 4 1 5 o
56
FUP
-0. 0963 9
0.4843
6b
SECCHI
-C. 09347
0. 49 73
55
DA YL
0.0 90 16
0.46 12
69
AREA
0 .08 771
0.4 736
69
MAXDU
0.08769
0.4770
68
M1NRLS
0.0 86 93
0.4775
69
PPKM3
0 0 6333
0.5610
5 1
F7L
0.08226
0.546o
6o
MB E P TH
-0.0 /6 12
0. 5234
6 9
TPR
0.0 7426
C 6 t 20
49
DAY
0.07296
0.5513
69
PDUMIN
-0.07131
0.62 63
4 9
LENGTH
0.06650
0.5672
69
FI C
- 0.06394
0.6396
56
A VGDU
- 0. 06066
0.6232
68
TEMP
-0.0 586 7
06335
08
ETC
0.05713
0.0736
60
DTuP
0.05027
0.7129
56
DCOL UR
-0 .04990
0. 7537
42
BULK
-0.04667
0. 7175
62
DLVEL
-0.04480
C. 7209
6
DUP
0.04066
0.7666
66
DTP
C.04023
0.7447
68
I GPP
0.0 34 4 7
0.6102
51
VULUME
0 C 3 2 6 5
0.7900
69
FTP
0.02979
0.8000
6 9
DTC
-0.02699
0.6131
69
E'T P
0 .02506
0.8381
6 9
DT UR b
-0.02109
0.8609
4b
5 I LL
0.01790
0.8875
66
EUP
-0.01008
0. 94 l 2
56
TR
0.00057
0.9968
61
CURBS
-0.00000
1.0000
69


339
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263'


BIOGRAPHICAL SKETCH
William Arthur Bailey was born in Ottawa, Canada,on 28 August 1947
and moved to Delaware in 1956. Following his graduation from the
University of Delaware with a Bachelor of Arts and Science degree in
1968, the United States Government requested that he enter its employ.
Subsequently, as a member of the United States Army Infantry, he toured
South Vietnam for a year. After returning to the University of Delaware
and obtaining a master's degree in marine biology, the author pursued
a doctorate's degree at the University of Florida.
Mary Bailey, his wife, is expecting their first child in February
1977.
-327-


-182-
2
the net community primary production (0.2 g C/m -day) is unknown. It
could be: 1) stored within the canal system as nektonic, benthic, or
fouling organisms biomass, or in the sediments, 2) exported to the
adjacent estuary as nekton or as suspended material, or 3) removed from
the aquatic community by insects, birds, or people.
The net retention of 0.2 mg C/l-exchanged water, which is the
2
equivalent of 0.2 g C/m -day for this "average" canal, does not exclude
the possibility that the net community primary production is exported to
the adjacent estuary in suspended or dissolved form. The net export
of organic phsophorus from the "average" canal does, however, suggest
that some of the planktonic net primary production was exported to the
estuary; even though there was a net total phosphorus and a net organic
carbon flux into the canal.
The "average" canal lowers the color and turbidity of the estuarine
water that enters the canal on an "average" day. Presumably, the mixing
and turbulence of the canal water is less than that in the estuary and
results in enhanced particle settling. Canal water minimum residence
time is a significant factor which is positively associated with net
color change. How much of the retained color and turbidity is returned
to the estuary during periods of overturn or storms is unknown. In
creases in daylength and solar insolation, i.e., during the summer,
accentuate the reduction of estuarine color and turbidity levels by the
canal. The rainy summer season is the period of elevated estuarine
color and turbidity. Increases in estuarine color and turbidity were
found to result in greater color and turbidity retention rates by
canals.
The average dissolved oxygen concentration of this "average" canal


-97-
Table
12.
(Continued)
CBS
CANAL
MONTH
DAY
YEAR
ETC
EIC
ETOC
E TP
E OP
ETOP
57
KC 2
8
18
76
31.9 24.
6 7.3
0.0 17
0.003
0.0 14
58
KC3
8
18
7 o
30.4
> 24.
8 5
0.0 14
0.004
0.009
59
NM1
10
26
76
55.2 12.
0 43.2
0.065
0.036
0 .029
60
NM 2
10
27
7b
55.6 14.
0 41.6
0.062
0.029
0.031
61
NM3
10
28
76
52.7 12.
9 39. 8
0.055
0.026
0.030
62
PEI
8
14
7 a

1 5.4
0.330


63
PE 2
8
1 4
74

14.7
0.220


64
BP3
8
19
74

1 .9
0.040


65
BP 4
8
l 9
74

1 .9
0 .040


66
SA8
a
23
74

1.0
0.030


67
AB3
9
1 7
74
9
3 .4
0 .040


68
AB5
9
1 7
74
9
2.4
0.050


69
MI H
8
8
75

5.8
0.150
70
MI J
8
1 0
75
9
9 .0
0.164


71
MIL
8
6
75
9
6.3
0. 068


72
MI M
8
6
75

6 .3
0 .084


73
MI M
8
8
75

6.1
0 .085


74
MIN
8
7
75

8.6
0.092


oes
ENH 3
ETURB
ECOLOR ECONO AVGDQ
MINOU
MAXD
SECCHI
TEMP
57
0.03
2.0
3 1
442 £
>.29
4.0 1
6.00
1.80
28
58
0.01
1.9
25
447 £
>.33
3.53
6.13
2.90
28
59
0.04
3.0
82
257 1
. 78
0. 00
7.87
1.60
25
60
0.04
3.3
84
262 2
. 08
0.00
9.83
1.58
25
61
0.02
3. 3
88
270 2
. 73
0.00
8.75
1.72
24
62
0.12

. 3
.30
0. 00
8. 70

31
63
0. 1 0


. 2.57
0.00
5.50

3 1
64
0.06

c
>. 90
4.2 0
8. 00
31
65
0.08

. 4
.37
1.10
6.40

31
66
0.04

. 3
. 55
0.60
7.40

31
67
0.09


. 4
>. 30
3. 00
11.70

2 6
68
0.08


. 4
.40
0.00
8.70

26
69
0.02
#

. 4
. 00
C. 00
8.00

31
70
0.03


. 5
. 10
3. 70
6. 70

31
71
0.01

. 5.2 0
0.00
9.00

31
72
0.01
. 4
. 95
0.00
9.80

3 1
73
0.03


. 4
. 95
0.00
9.80

31
74
0.03


. 4
. 85
0.40
8.60

31


-293-
CORRELATION COEFFICIENTS / PkUD > |k|
M6ER OF OBSERVATIONS
UNDER HO
:rho=o / NU
F T UP
CUMTIDE
ETOC
FT UC
OEV EE
DAYL
UULK
AGE
-0.11 4 04
0.10814
0. 1 0063
0.0 9561
0.09651
0.09518
0 .08042
0.4116
0.4363
0.469 1
0. 49 16
0.4921
0.4936
0.5632
54
54
54
54
54
54
54
DCOND
OTUkb
C UR ti S-
DIC
T1 DE
TEMP
DT C
0.07713
0.06557 -
0.05422
0.04428
0.04146
-0.03946
0.0334 8
0.7202
0.6724
0.6970
0.7583
0.7659
0.7791
0.0137
24
4 4
54
52
54
53
52
PPR
PGPPM3
PGPPM2
MDEPTH
MINRES
P DU MIN
DTOC
-0.03014
0.01671 -
0.01038
0.00614
0.003C0
0.00498
-0 .00056
0.8371
0.9093
0.9436
0.9649
0. 9714
0.9735
0.9969
49
49
49
54
54
47
52
L TOP
ET OP
F TOP
cTP
FTP
CUP
£ TUR E
FTURB
1.00000
0.86704
0.75737
0.73914
C.6 79 86
0 .58907
0 .42495
0.0000
0.0001
0.000 1
0.0001
0. 0001
0.0001
0.0032
54
54
54
64
54
46
46
F C UL OR
ECLR
SECCHi
SDN
F IC
EIC
EC UNO
0.40052
0 .39806 -
0.3 582 6
0.33393
0 326 7
-0.32659
-0.32056
0.0127
0.0133
0.C 095
0. 0190
0.0152
0 .0 159
0.1267
38
38
53
49
54
54
24
DT OP
FCUL)
W I D I H
Tk
MAX D
F UP
DAY
- 0.30500
-0.30307
0.28911
0.27611
0.26417
0.2561 1
-0.25383
0.0279
0.1500
0.0 340
0.0576
0.0559
0.061 6
0. 064 0
52
24
54
49
53
54
54
FTC
ETC
MI NU 6
YE Ak
TPk
SEWERS
DCOLR
-C.243 79
-0.23046 -
C.22656
-0.22651
-0.22360
C.20522
0.205l9
0.0756
C.0 93 6
0. 1 02.8
0. 09 95
0.1308
0,1366
0.2165
54
54
53
54
4 7
54
38
LENGTH
PPRM3
T GPP
BULK
UUP
P RM 2
DNH3
0.20373
0.20367
0.18795
0.18255
0.1 756C
0.16100
0.14647
0.1395
C 1 6 0 4
0.1959
0.1864
0.2131
0.269 1
0.3001
54
49
49
54
52
49
52
MON TH
AREA
DTP
VULUME
U1C
LEVEL
DCEND
-0.14590
C.13215 -
0.12968
0.12665
0.1 1 552
0.11277
0. 10484
C.2925
C. 340 8
0.3595
0.3722
0.4148
0.4168
0.6259
54
54
52
54
52
54
24
T 1 OE
AV GDU
CURDS
FT C
t ( uC
PGPPM 3
MINRES
0.10289
C. 1 C02 7 -
0.08426
0.08237
0.08183
C .0 7 97 7
-0.07O05
0.4591
0.4 75 0
0.544o
0.5538
0.5564
0.5850
0. 5 74 8
54
53
64
54
54
49
54
Da YL
PG PPM 2
UTC
AGE
PU DM IN
SILL
CUMTIDE
0.06112
-0.06025 -
0.05112
0.04-520
0.04136
0.03672
0.01840
0.66C6
C.68C9
0.7189
0.7465
0.7625
0.7810
0.8949
54
49
52
54
4 7
54
54
TEMP
LNH3
FNHJ
ML)LPT H
DTC
PPR
D TUR B
0 .01686
0.0l 153
0.01163
- 0.C 1 1 09
0.00919
-0.00792
-0.0025 1
0.9045
0.934 1
0.9641
0. 93 66
0.9464
0.9569
0.9671
53
54
54
54
52
49
44


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ocasO'U'iUN-oaNacf'UN'-oiQ, Naui^ui'- to
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jtrtrtrcoC'C'C-oooa'Ooco c
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p-vocnmC'aoroujUGj-^CE'swtr.e'Cr. rjas-viuiooocjcooo gj
coo-ga)fcrt.o:o''Naooocroooo
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i-
UoC*iOOOU'iCO'iCroC>OOOcOOOOOOOo(XOoOO
e tr i> our O' tr o> cr a tr tr a tr tr u >- U' -r tr t: o c o £ o o o o c
c
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0DC-\O O >-OvCtr l''C O N N O tu O Gj ft' C OOOC'JOOOO
OOCOOOOOoOOOC^4>G,oOOOO^OOOOOOOo N
tr
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Goaoooccoooootr-oc. coaoacccooooooo
c
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00000000000000000000000000000 o
M
N
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a->iNsi-iM-^'JS'N'0'crC'0'C''0'C'0' ooti'tr trtrtntntrour c
OvoOc-sCo'i-P'Girv Ovcoc^iO'tr^-GJfv O'i'cs^otr-Js-ujiv*-
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iv iv rv rv iv rv ro re- rv rv rv rv rv iv rv fv iv iv rv iv rv iv rv rv rv fv iv rv rv rv
rvfvtMivfvroroivtuiviviv'G.ivtvlvivrGivivfvtVGituG.G.G.G.-^*'
-pI -sj '"J ^ -pj
GrtrtrGiour. uitrtrtrtr. trtrtr'tntntrtrmtruiuitrtruioitrtntrtr
ntX'txxrcxtmturcTttTxuttxu
c c cr or r.CGcr.ff.ocf c c c orco r. r. nrrr
Gj Gi G- Gj ft tv fv fv ro ft iv IV fy -* -1~ < - r~ >- or Or o: s g -g *m -g
IV IV IV IV >--*-
a ti' rv a c rv *c tr u vc tr fv >c o u iv vg -g rv u¡ g tr *- g s iv .p o -p o rv Gioiv^>-tr,-G>-tr*- i>^-f>c>-'
o tr, g-1 -> o or o o o tr tr->j tr tr o tr -g o c u a o Gr u. tr tr u >c a rv
ocoooocoooooooocooooooooooaooo
c-G'croC'O'O'^jC'tr. 0'vio>jO'0"M0'C'C>j0"Ja;O'Nc;a.0'0'
Nf:|v^^*-'.-tr>co'i-G.-F-o>os.'*-aiv>-a'-vGi
'OGjO-P'-^'ti-f'OO'G^trtniVG.^-'-O'N-e'N^ivGi-sG''. gj^n>-
p * O
OOOOOOOOOOOOOOOOOOOOOO^JOOOOOOIO
C'O'eo'O'OO'O'O'O'O^O'siO'i'O'O'O'JNO'sciSttma^si'
'g p- -*O->IG.CD0:-P>p- NOI>0)N0(isGOI\Ji-0i(J''^0"JOo
tntr-^ivGTO-goa>Gj4>4>\O>0'-t=--fGJO>-o'Nsi->j'jO'uiiv
N
N
MONTH DAY YEAR STATION TIME Zl DOT 2 DO 2


-119-
Table 19. Canonical correlation analysis of the metabolism and
nutrient exchange data sets (38 observations).
Canonical
Variable
Mean of Metabolism Group
Canonical Variable
Mean of Exchange Group
Canonical Variable
1
0.09
0.04
2
-0.13
-0.03
3
0.06
11
o
o
1
4
-0.34
1
o
o
5
0.53
0.01
6
0.17
-0.02
7
-0.03
-0.04
.
Canonicl
Correlation
Chi-Square
DF
Prob > Chi-Sq
1
0.72
71
63
0.218
2
0.71
49
48
0.406
3
0.61
28
35
0.778
4
0.52
14
24
0.942
5
0.31
4
15
0.993
6
0.22
1
8
0.987
7
0.08
0
3
0.973


Table 28. (Continued)
FOP
FNH3
FOP FNH3
FTURB
FCOLOR
FTURB FCOLOR
Total
Metabolism Exchange Water Quality (including
(9 variables) (7 variables) (4 variables) Subtotals interactions)
-150


748-FLUX
-SAS
r T 1 2F
001
VARIABLE
N
MEAN
51 D UtV
SUM
MINIMUM
MUNTH
74
7.3
2.6
5 39
3
DAY
74
17.2
6.6
1272
6
YE AR
74
75 .2
0 .6
5567
74
rrc
58
38.3
8.3
2223
26
ETC
58
38.0
6.0
2202
24
DIG
56
0.3
2.0
15
-5
F IC
58
20.5
7 .9
1 1 67
9
tic
58
2 0.8
7 .b
1 1 93
8
DIC
56
t
o

o
1 1
- 1
-3
FTUC
71
15.6
8 .3
1119
1
e rue
71
15.6
8.1
1 099
1
DTUC
69
0 .2
2.0
1 7
-6
F TP
71
0 .2
0 .2
1 7
0
t TP
71
0.2
0.2
1 6
0
DTP
68
0 .0
0.0
0
-0
F UP
58
0.3
0 .4
1 6
0
LUP
58
O
.
l\3
0.2
13
c
DUP
56
O

o
O

o
0
-0
F TUP
54
0.0
0.0
2
0
L T UP
54
c .c
0.0
2
0
Ci T UP
56
O

o
0 .0
-0
-0
FNH3
7 1
0. 1
0. 1
6
0
LNH3
71
0.1
0.1
o
0
UN Ft 3
69
o. u
0 .0
-C
-0
F TURB
50
3.6
1.9
i a i
1
t TURB
50
3.4
1 .4
171
1
DTURb
48
0.2
1 1
1 0
-2
FCOLOR
42
106.1
74 .3
4458
I 2
EC OLOR
4 2
1 02 .0
6 5 3
4285
16
DCOLOR
42
5 .o
16.1
2 34
-18
F C uND
24
3 15.8
61 .0
7575
259
MAXI MUM
1 1
31
76
58
58
8
42
43
2
42
43
1 0
1
I
0
3
1
0
0
0
0
0
0
c
11
7
5
256
245
44
448
-277-


Observations
-57-
10
o P
J L
x
a
~i 1 1 1 1 1 1 1 1 K''*-1
0.3 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.9 2.6 2
TGPP/TR
N = 56 Mean = 1.16 Std. Dev. = 0.59 Range 0.31 to 2.95
C.V.% = 50
Figure 18. Frequency distribution and descriptive statistics for
total community production:respiration ratio, averaged
by canal.
PGPPM2/PPM2
N = 56 Mean = 1.93 Std. Dev. = 1.14 Range 0.29 to' 5.02
C.V.% = 59
Figure 19. Frequency distribution and descriptive statistics for
planktonic production:respiration ratio, averaged by
canal.


33-
Figure 9. Canals and sampling stations at the Flagler Beach site.


The person most responsible for my completion of this study is my
wife. Mary worked beside me during more than half of the sampling
trips and encouraged me when things seemed hopeless. She taught school,
under less than ideal circumstances, in order to support us and to pay
for unfunded sampling, trips in 1976. I doubt that I would have com
pleted this work without her.
iii


-309-
PPR
PPR
1.00000
0.0000
56
DAYL
0.4626 7
0.0003
5 6
T IDE
0.4466 c;
0.0005
56
TPk
0.41425
0. CO 18
54
FOUND
-0.411 CO
0. 0460
24
ECOND
-0 .40 495
0.0496
24
M INRE S
-0.38194
0, 0037
56
PDUMIN
036 74 8
0.0063
54
PGPPM2
0.35336
0.0076
56
TEMP
0.34788
0.0086
5b
PGPPM3
0.34458
0.0093
56
DNH3
-0.32662
0.0193
51
MI NDO
0.30465
0 .0224
56
BULK
0.2 9966
0.0249
56
CUMTIDE
0.6655
U.0454
56
YEAR
- 0.25789
0.0550
56
PR M2
-0.24431
0 0696
56
UCGLK
- 0. 2 l 535
0.1820
4 0
AV 6 DU
0.21297
0. 1150
56
DIC
-0.18734
0.1880
5 1
TR
-0.17776
0. 1 900
56
d roc
0.16287
0.2535
51
DEVEL
0.16036
0. 2377
56
A6E
0.16004
0.238 7
56
F TOC
0.15400
0.2709
53
PPRM3
-C.15298
0.2603
56
FCOLOR
-0.13675
0.4001
40
EC OLOR
-0. 12361
0.4473
4 0
MDEPFH
-0.118 93
0.3826
56
DAY
0.11246
0.4093
56
SECCH
- 0. 11087
0.4160
66
E OC
C 1 0 5 96
0. 4502
53
SILL
-C.1C499
0.4412
56
DTC
0 104 12
0.4 6 72
51
CURES
0 .09258
0.4 9 73
56
F 1C
-0.08389
0.5503
53
MA X 0
0.0 7954
C.5596
56
UUP
-0.0 7437
0.6040
51
E19 H 3
0.0 7355
0.6007
53
FNH3
0.07355
0.6007
53
D TOP
0Oo 875
0.6317
51
LENOTH
0.06732
0.6220
56
FTC
0. 062 60
0.6561
53
fcl C
- 00 554 5
0.6933
53
AK EA
C 0 5 0 9 d
0.709 2
56
F UP
0.04662
0.7285
53
DTUKB
0 .0 41 55
0. 78 4 0
46
EOP
-0 .03979
0.7 773
53
FT P
-0 .030 1 4
0. 83 71
49
SUN
-0.02862
0.8341
56
DCUN
-0 .0260 1
0.9040
24
S E W E < S
-0.02414
0.8598
56
F TP
-0.02197
0.8759
53
ETP
-0.02053
0.8640
53
MONT H
0.01997
0.8839
56
FTUR8
0.01664
0.9106
4 a
wIOTH
- 0 C1653
0.9037
56
ETURb
0.01165
0.9374
4 8
T uPP
0.00836
0.9512
56
ET OP
- C 0 0 7 92
0.9569
49
DTP
-0. 0 05 86
0.9675
51
ETC
-0.00490
0.9 72 2
53
VOLUME
-0 .00374
0. 9782
5b
SUN
SUN
1.00000
0.0000
56
MONTH
064 9 86
0.000 1
56
FCUND
0 6 2t>30
0.0011
24
ECONO
-0.61875
0.0013
24
E IC
0.51o 8b
0. 00 0 1
53
F I C
-0.800 8 1
0.0001
53
AVGD
0 .4241 l
0.001 1
5
EUP
0.41438
0.002C
53
FTP
0.4 1 333
0. 0 02 1
5 3
h I C
-0.4020 7
0 0 0 2 o
53
ETP
0.3 9505
0.0034
53
0 UP
0.38923
0.0048
5 1
DAYL
C.34969
0 .0082
56
ETC
-0.34877
0.0105
53
FT UP
0.34665
0.0147
49
ETUP
0.33393
0.0190
49
V*r I L'T H
0.31644
0.0175
56
F OP
0. 3 1 32 1
0.0224
o3
UNH3
0.27424
0. 05 15
51
AGE
-0.27162
0.0429
56
PR M2
0.27003
0.0441
5 b
MI ND
0.2oI92
0.0512
56
MDtPTH
-0 .24697
C.0665
56
ULK
0.23601
0.0773
56
SI LU
-0.2 3664
0.0791
56
PDUMIN
0.21901
C 1 1 1 6
54
CURES
0.21541
0.1108
56
AREA
C.2 1036
0.1197
56


-321-
CRRELATIUN COEFFICIENTS / PkUb > jR| UNDER HOiRHO^O / NU
Mb ER UF OBSERVATIONS
MAXD
MAX DU
1.00000
0.0000
73
T6PP
0.57336
0.000 1
5 6
TK
0.54970
0.000 1
5o
PGPPM3
0.54076
0. 0001
56
PPRM3
0.500 36
0. 000 1
56
FCOND
-0.49811
0.0132
24
ECUNU
-0.47871
0.01 80
24
RRM2
0.453 69
0.0004
SO
UEVEL
0.453b4
0.0001
70
PGPPM2
0.4 0698
0.0019
56
DC ULUR
0.37455
0.0145
42
SECCHI
-0.32534
0.0112
60
DTURB
0.29962
0.0386
48
AVGDU
0.28295
0.0153
7 3
F COLOR
0.26029
0.0722
42
ET P
0.27038
0.02 3 6
70
EUP
0.2 64 9 7
0 46 4
5 7
ET DP
0.264 17
C.0559
53
FTP
0.25445
0. 0335
70
ECULOR
0.24431
0.1189
42
BULK
0.22763
0.06 6 0
66
TIDE
0.22192
0.0592
73
VULUME
0.22141
0.0598
73
D1 C
-0.21 566
0.1136
55
W IDTH
0.21316
0. 07 02
73
FIC
-C.20802
0.1206
57
AREA
0.20118
0.0879
7 3
DAY
-0. 19860
0.0921
73
F T UP
0.19202
0.1684
S3
El C
-0. 1 858 l
0.1 68 4
57
LENGTH
0. 1 764l
0.1354
73
7 PR
0.1 7070
0.2 172
54
DT UP
-0.16872
0.2182
55
FTURB
0.16741
0.2462
50
FNH3
0.152 1 1
C. 2087
70
ENH3
0.15211
0.2087
70
SUN
0.15106
0.2664
5 6
FTUC
0.15016
0.2147
70
M I NO U
0.1 4556
0.2192
73
ET OC
014466
0.2321
70
AGE
0.13658
0.2595
70
MDEPTH
0.13 J 2 9
0.260V
73
SEwERS
0.12499
0.2921
73
TEMP
0.11364
0.3384
73
DT P
-0.11275
03o36
67
DC UNO
- 0. 1 083 6
0. 61 43
24
FP
0.09046
0.5034
57
DNH3
0.08769
0.4 770
68
PPR
0.07964
0.55 96
56
CUMTICE
0.07900
0.5064
73
MONTH
0.07370
0.5355
73
FTC
0.0 522 4
0.6995
5 7
b TC
-0.04665
0. 73 04
5 7
DTC
0 .036 04
0.7730
68
DTC
-0.03150
0.8194
55
SILL
0.02318
0.8500
69
MI NRES
0.01555
0.8961
73
ETURb
-0.01376
0.9244
6 0
YEAR
-0.0 1 C4 1
0.9303
73
DA YL
0.0 0501
0. 97 98
73
PLUM IN
-0. C 01 3 0
0.9925
54
CURBS
0.00049
0.9 96 7
73
DUP
0 .00022
0.9987
65
MINDU
MINDO
1.00000
0.0000
73
AV 6 DU
0.642 l 2
C 0 0 0 1
7 3
DCLUR
0 51652
0.0004
42
FCUL UR
-0.4 9681
0. 0008
42
ECULUk
-0.44554
0. 0031
42
DAY
0.44 399
0.0001
73
MUN TH
-0.43001
0.0001
73
TEAR
0.4 1001
0.00C2
73
MDLPTh
-0.35368
. 0.0021
73
TPk
0.3 046 6
0 0 2 4
5o
L l C
-0.30080
0.0230
67
PR M2
-0. 2861 8
0.0326
56
FTC
-0.27869
0.0358
57
SUN
0.261 92
0.0512
56
ET OP
- 0.22 656
0.1028
53
SILL
-0. 20669
0.0884
69
Lie
-0.20199
0 139 2
bo
TR
-0.19560
0. 14 81
56
M INRE S
-0. 192e 1
0. 1 022
73
PPRM3
-0 18966
0.1615
56
TIDE
-0.18717
0.1128
73


-179-
of canals. No judgements about the propriety of canal construction
should be based solely on this information. For example, if a particular
canal system was found to have good water quality, high levels of
production, and substantial export of organic matter, the canal system
cannot automatically be assumed to be good for the particular estuary
or region. Other ecological factors, such as those outlined in Chapter
2, and possible socioeconomic impacts need to be considered.
"Average" Canal
The observed variabilities of the response parameters suggest that
a discussion of an "average" Florida residential canal may not have
much meaning. However, the percentages of variability explained by
the regression equations indicate that most of the observed deviations
from the mean values can be attributed to differences in the independent
factors. Therefore, by evaluating the attributes of the "average"
canal and the resultant effects of any independent-factor alterations,
hypotheses about canal behavior can be extracted.
The mean values for canal physical characteristics, water quality,
net canal-estuary exchanges, and metabolic parameters are shown in
Table 35 as a representation of an "average" residential canal on an
"average" day.. In this "average" canal, the planktonic component of
the total canal community has a net primary production rate of 1.0 g
2
C/m -day while the total community has a net primary production rate
2 2
of 0.2 g C/m -day. The difference between the two rates (0.8 g C/m -
day) must be attributed to respiration requirements of the nekton, the
benthos, and the fouling communities on the bulkheads. The fate of


-314-
CURRELAT I UN CUEFHLltMS / Pkb > |R| UNDER H0IRHO=0 / NU
M3ER UF OBSERVATIONS
MDEPTH
DNH3
-0.07 12
0.0234
69
ARE A
-0.07785
0.5097
74
FUP
0.07o53
0.5731
58
T IDE
0.0 7449
0. 5282
74
PDUMIN
0.07133
0.6083
54
VULUME
0 .0 6568
0.5782
74
UOP
-0.05305
C. 6978
5 6
D TURB
0.05257
0.7227
48
d rup
0.04522
0.740 7
56
CUMT1DL
0.04316
0.7150
7 4
FTURb
-0.04090
0.7780
50
1C
-0.03530
0.7962
56
UCND
-0.02 3 06
0.9 148
24
DTC
0.01944
0.8869
56
DTP
-0.01473
0.9051
68
TPR
-0 C1 259
0.92 80
54
DTUC
-0.01256
0.9184
69
E T UP
-C.01109
0. 93 66
54
FTUP
0.0 06 1 4
0. 9o4 9
54
FCUNU
-0.00554
0.9795
24
ECUN
-0.00201
0. 9926
24
AREA
AR E A
i.00000
0.0000
74
L ENGT H
0.98145
0.0001
74
VOLUME
0 96 75 8
0.0001
74
1 PR
0.39609
0. 0030
54
SE AtkS
0.39110
0.000o
74
WIDTH
0.29404
0.0110
7 4
TI DE
0.27431
0.0160
74
TGPP
0 .2 1 51
0.0516
56
AVGDO
0.24529
0.0365
73
DAT
-0.22761
0.0511
74
5 UN
0.21036
0.1197
56
EP
0. 20968
0.1142
53
F I C
-0.20 738
0.1183
58
MAXDU
0.201 l 6
0.0879
73
E 1C
- C 2 0 0 69
0.1309
50
FTUP
0. 1 85 75
0.178 7
54
BULK
C. 1 60 73
0.1433
6 7
AGE
-0.16964
0. 15 73
7 1
YEAR
0.1 6423
0. 162 0
74
SILL
-0. 16 129
C. 1822
70
MINRES
-0.15810
0.1785
74
PGPPM2
0.15376
0.2578
56
FP
0.14719
0.2702
58
FIP
0.14356
0.2323
7 i
UlC
-0. 139 o3
0.3047
56
P PR M3
0. 1 3854
03066
56
ETUP
0. 13215
0.3408
54
ETP
0.13107
0.2759
7 1
E roe
0. 1 28 58
C.2852
71
FTOC
0.1 1893
0.3232
7 1
DEVEL
0.11520
0.3o8 7
7 l
D TC
-0.11OoC
0. 41 71
56
DTUP
0.10964
0.4212
56
PRM2
0.10702
0.4 324
56
TR
0.10645
0.434 9
5 6
PD M I N
0.104C5
0.454C
54
DTP
0.1 0326
0.4020
8
EC UNu
- 0.09501
.6588
24
SE CCHi
-C .0 93 60
0.4769
60
DTURo
-0. 091 24
0.5374
46
0UP
C.08936
0.3125
56
FCND
-0.08814
0.6821
24
DNH3
0.08771
0.4736
69
FTURd
-0.0846 8
0.5588
50
fcTC
0.0 7o21
0.5593
3 o
MDEPIH
-C.07785
0.5097
74
DCULUK
-C.0 7333
0.0444
4 2
TEMP
0.06 906
0.5614
73
CUMTIDE
0 .0 6360
0.5900
74
CURBS
0.055/6
0.63 70
74
PbPPM3
0.05204
0.7033
56
PPR
0.0309o
0.7092
56
F TC
0.04623
0.7304
56
DAY L
0.04604
0 o 9 6 9
74
L'COND
0.04467
0.6 358
24
ETUR b
-0. 043 7 l
0.7631
50
ENH3
-0.04259
0.7243
71
FNHJ
-0.04259
0.7243
7 1
D F
-0.03130
07983
0 9
M UN 1 H
C.O 197 1
0. 8676
74
FCULP
-C.01605
0.9196
42
ECULUR
-0.01105
0.9446
42
M I N D U
0.00425
C 9 7 l 6
73


Table 23. Canonical correlation analysis of the exchange and canal/sampling day characteristics
(38 observations).
Canonical
Variable
Mean of Exchange Group
Canonical Variable
Mean of Characteristics Group
Canonical Variable
1
0.05221400
-0.66324930
2
0.00422606
1.34696114
3
-0.01311521
-0.21206553
4
-0.03590690
-3.29793973
5
0.02455735
-1.24480317
6
0.04306521
-0.18771526
7
0.00162257
1.26963005
Canonical
Correlation
Chi-Square
DF .
Prob > Chi-Sq
1
0.89833185
149.93756
112
0.0097
2
0.81116841
103.87572
90
0.1504
3
0.77080694
73.83375
70
0.3540
4
0.68035795
48.58460 '
52
0.6092
5
0.65670775
31.18129
36
0.6973
6
0.50970113
15.37975
22
0.8458
7
0.46903076
6.95655
10
0.7308
-128-


-292-
CUHRE LA TI UN CUEFHCIENTS / PRUb > |R| UNUtR H0¡ KHU=0 / NU
MBER OF OBSERVATIONS
UP
ETURB
-0.16993
0.2482
48
DA Y
-0.15872
0.242 7
5 6
T LC
0.14 867
0.2742
5o
DC ULR
0.14016
0.3557
42
UCUND
-0.14538
0.4979
24
F T UR B
-0. 14423
0 .3281
48
BULK
0.14200
0.2965
56
CURBS
- 0. 10478
0.3220
S 6
FP
0. 1 1837
0.3 84 9
5 6
PGPPM3
-0.10722
0.45j9
51
DT UP
-0.1 05 73
0.4380
50
PDUMIN
0.09971
0.4955
49
E TOC
-0.09721
0.4 760
56
LENGTH
0.09527
0.4 84 9
56
VOLUME
0.09260
0. 4973
56
WIDTH
0.092 4 5
0.4980
5 6
PGPPM2
-0.08978
0.5310
51
AREA
0.0 8930
0. 5125
56
DTC
0.07960
0.559O
56
PPR
-0.07437
0.6040
51
FCLOR
0.07289
0.6464
42
AVGDU
0 .06799
0.6218
55
PPRMJ
-0 .C6749
0 .638 0
5 1
ECGlUR
0. 0 6.4 7 7
06836
4 2
rpR
-C.064 08
0.60 1 6
49
M INRES
-0.Ool90
0.0304
56
MDEPTH
-0.05305
0.6978
56
EN H 3
-0.05172
0.7C50
56
FNH3
-0.05172
0.7050
56
TEMP
0.05103
0.7114
5 5
TI DE
-0.05011
0. 7138
50
FTUC
-0.04953
0.7170
50
CUMTI DE
-0.04o 26
0.7405
56
NH3
-0.04056
0.7 666
56
DTURB
-0.0283 l
0.8485
48
FCN
-C.02166
0.9200
24
MI NDO
-0.02003
0.884b
5 5
DEVcL
-0.01812
0.894o
5 o
PR M2
0. 0 09 99
0.9445
51
DIC
-0.00071
0.9492
56
ECUN D
-0.00337
0.9875
24
MAXUO
0.00022
0.9987
55
TUP
FTGP
1.00000
0.0000
54
E TU P
0.86704
0.0001
54
FT P
0.72914
0.000 i
54
ETP
0.70761
0.0001
54
EOP
C 644 5 8
0.0001
54
ETUR B
0.49o54
0.0004
40
FTURB
0 .4 104 7
0.0046
4 6
V. i O TH
0.37988
0.0040
54
SUN
0.34865
0.0147
4 9
SECCHl
-0.33141
0.0153
5 3
L C
-0.32879
0.0102
54
TR
0.31l75
0.0292
49
FIC
-0.30302
0 .0 259
54
E'CUND
-0.29126
0.1673
24
PPRM3
0.28313
0.0487
49
FLND
-0.2779?
0.1885
24
FCCLUfi
0.27753
0.091o
38
ECULUR
0.70401
0. 10 92
38
SE wERS
0.24115
0.0790
54
LENGTH
0.23797
0.0631
54
DUP
0.235 L 3
0.0934
52
DTP
0.23273
0.0969
52
TGPP
0.22898
0.1135
49
F UP
0.22775
0.097 7
54
PR M2
0.2 22 O 7
C. 124 1
49
ETC
-0.21261
0.1224
54
DAY
-0.20 640
0.1343
54
F TC
-0.19957
0.14 79
54
MAXUO
0 19202
0.1684
53
DCULR
0.190 93
0.2509
3 8
1 PR
- 0-. 1 8fa34
0.20 4 *
4 7
DI UP
C. 1 8793
0.1821
52
ARE A
0. 1 85 75
0.1/87
54
AVoUU
0.18490
0.1850
53
VJLUME
0.17185
0.2 14 0
54
M INDO
-0.16849
0.2278
53
ONU 3
0.16274
0.2490
52
SI LL
0. 15o 90
0.2511
5 4
MUN TH
-0.14C 25
0.3 1 18
54
YEAR
-0.1 1026
0.4025
54
F NH3
-0.11 590
0.4040
54
ENH3
-0.1 1590
0.4040
54


-278-
VAR 1 ABLE
N
M E AN
STD DEV
SUM
MINI MUM
MAXI MUM
tCUND
24
317.5
60 .9
762 1
257
448
DCUND
24
-1.9
9.0
-45
-23
21
T GPP
56
a .o
5 .9
481
0
2b
TM
56
8.2
5.8
4 59
0
24
PGPPM2
56
4 .9
3.9
2 75
0
24
HR M2
56
3.0
1 .8
1 69
0
a
PGPPM3
56
4.7
3.7
2 6o
0
l 8
PPRM3
6 6
1 .6
0 .9
88
0
5
TPR
54
1 .2
0 .6
63
0
3
PPk
56
1 .9
1 1
1 08
0
5
BUN
56
43 1.8
155 .2
24 17 9
72
676
L> A YL
7 4
12.5
0.8
924
1 1
14
PDCiM IN
54
0.6
0.3
31
0
1
LENGTH
74
1047.4
969.6
775 10
173
4 4 63
WIDTH
74
28.3
7.7
2 0 92
9
53
MDfcPTH
74
2 .9
1 .0
2 11
1
6
AM EA
74
81311.8
1 34689.5
60 170 70
1 650
613000
VOLUME
74
219993.9
34 34436
16279550
3950
l 44 0000
GILL
70
0 .9
0.8
60
0
3
DEVEL
71
56.2
36.6
3992
0
l 00
AGE
7 1
15.3
4.8
10 85
5
23
BULK
67
80.0
32.6
5360
0
100
CURBS
7 4
0.0
0.2
3
0
1
S E w E R S
74
0 .o
0 .5
4 4
0
l
A VGD
73
5.6
1 .5
4 0 7
2
9
MAXDD
7 3
8 .6
2.3
639
5
l 6
MI NDG
73
2.7
2 .0
1 94
0
7
TEMP
7 3
2 7.0
3.6
1 969
1 9
33
SECCHI
60
1.4
0 .4
81
1
3
ri DE
74
0.7
0.2
50
0
1
MINHES
74
3.5
2.3
260
1
12
CUMTIDE
74
1 1
-0

o
83
0
7


-126-
The factors associated with the third pair of canonical variables
seem to be the autotrophic tendency of the canal communities as in
fluenced by the plankton production and dominance, and a combination
of the daylength and tidal range on the sampling day. Several other
canal attributes (AREA, LENGTH, VOLUME, SEWERS, and BULK) have some
importance in this correlation. Large canal systems with greater tidal
ranges tend to be more autotrophic for a given season or daylength.
Exchange vs. Water Quality
The results of the canonical correlation analysis for the nutrient
exchange and water quality data sets are shown in Table 22. No signi
ficant correlation between these two data sets was detected by the
analysis. This result is somewhat surprising since one might expect
the net nutrient/water quality exchanges between the canals and adjacent
estuaries to be dependent on the nutrient levels and water quality of
the canals. In general for these canals, the exchange behavior was
independent of the canal water quality.
Exchange vs. Canal/Sampling Day Characteristics
The canonical correlation results for the nutrient exchanges and
canal/sampling day characteristics (Table 23) indicate a significant
correlation between the two sets. Only one correlated pair of linear
combinations can be generated. The two factors most closely associated
with the two linear combinations seem to be the net changes in tur
bidity and color levels from flood to ebb tidal phases, and a perplex
ing combination.of the canal dimensions, the presence of a sewer system,


-47-
Table 2.
TGPP
TR
PGPPM2
PRM2
PGPPM3
PPRM3
TPR
PPR
PDOMIN
SUN
TC
TIC
TOC
TP
OP
TOP
NH3
TURB
COLOR
COND
F-prefix
E-prefix
Nomenclature for the variables.
METABOLISM
Total community gross primary production (g 02/m^-day)
2
Total community respiration (g O^/m -day)
2
Plankton gross primary production (g 0^/m -day)
2
Plankton respiration (g O^/m -day)
3
Plankton surface gross primary production (g O^/m -day)
3
Plankton surface respiration (g O^/m -day)
Community production:respiration ratio (TGPP/TR)
Plankton production:respiration ratio (PGPPM2/PRM2)
Plankton dominance of community production (PGPPM2/TGPP)
Solar insolation (langleys/day)
EXCHANGE
Total carbon concentration (mg/1 as C)
Total inorganic carbon concentration (mg/1 as C)
Total organic carbon concentration (mg/1 as C)
Total phosphorus concentration (mg/1 as P)
Ortho-phosphorus concentration (mg/1 as P)
Total organic phosphorus concentration (mg/1, TP-OP)
Ammonia concentration (mg/1 as N)
Turbidity (NTU)
Apparent color (CPU)
Conductivity (micromhos/cm r 100)
Weighted-average flood tidal phase concentration
Weighted-average ebb tidal phase concentration


Table 21.
Canonical correlation analysis of the metabolism and canal/sampling day characteristics
(53 observations).
Canonical
Variable
Mean of Metabolism Group
Canonical Variable
Mean of Characteristics Group
Canonical Variable
- 1
0.22
0.33
2
0.17
1.23
3
0.42
-0.73
. 4
0.16
-0.89
5
0.14
0.12
6
0.07
-0.50
7
0.21
0.10
8
0.00
-1.19
9
0.08
-0.49
Canonical
Correlation
Chi-Square
DF
Prob > Chi
1
0.94
273
144
0.000
2
0.87
181
120
0.000
3
0.76
124
98
0.038
4
0.73
89
78
0.177
5
0.63
58
60
0.545
6
0.51
37
44
0.736
7
0.48
25
30
0. 709
8
0.47
14
18
0.687
9
0.33
4
8
0.797
-124-


-87-
The mean net changes of total organic carbon, total organic phosphorus,
and ammonia concentrations for the four locations (PG9, PC9, and PB9
not included) and four sampling periods are shown in Table 9. The
descriptive statistics and significant factor effects (as determined
by analyses of variance) for the 1975 data are presented in Table 10.
No significant location or season effect was detected for total
organic carbon and ammonia exchange levels for these four locations
(Table 9). It may actually be that there were organic carbon and
ammonia exchange differences between these locations and seasons, but
the large amount of variability within the pairs of canals and the small
sample size (2 canals per location) prevent the detection of small dif
ferences in mean values.
For the total organic phosphorus (TP-OP) exchange data, there were
significant differences between the mean values. The significant month
x location interaction effect indicates that both location and season
did affect the organic phosphorus exchange activities, but that the
effect of season depended on location. The organic phosphorus exchanges
between canals and estuaries did change with season, but the magnitude
or direction change varied with canal location. For example, the
mean net export of organic phosphorus from the Pompano Beach canals
increased from 0.008 mg/1 in September to 0.010 mg/l in November,
whereas a mean net export (0.011 mg/l) or organic phosphorus from the
Port Charlotte canals in September, had shifted to a net import of
0.009 mg/l in November.
Even though differences between the organic phosphorus exchange
activities among these canals were detected, the variability within
the pairs of similar canals was rather large. The mean value for these


-189-
metabolism and lower average-dissolved oxygen concentrations than those
without a sewer system. The presence of a sewer system was a signifi
cant factor in the regression equations of these water quality para
meters.
Even if the diversion of wastes away from the canals was found to
improve water quality in the canals, the practice is not a very
equitable waste-management solution from the receiving estuary's
standpoint. Interactions between canal systems and their adjacent
estuarine systems should be mutually beneficial. It is simply not
equitable to the receiving estuary that all pollutants originating in
a canal development should be quickly routed (or flushed) out of the
development and into the estuary. Conversely, it is not equitable for
a canal system, which might otherwise be a healthy balanced ecosystem,
to receive pollutants or potential problem-causing materials from the
adjacent estuary.
On the other hand, insofar as the volume of an estuary is increased
by canal construction, the assimilative capacity for organic loading is
increased. In estuarine areas already stressed with pollutant loads;
such as, the Intracoastal Waterway along the Florida East coast, per
haps canal construction aids the self-cleaning processes in the Waterway
or at least slows down the rate of deterioration of the adjacent marine
system.
This viewpoint of canal systems functioning as treatment units has
largely been ignored in favor of considering residential canals only as
recreational facilities in which good water quality must be maintained.
It may be that both objectives could be realized. But just as storm
water retention ponds in upland developments require planning and


-245-
06 S
MONTH
DAY
Y t AR
ST AT [ON
l IML
T C
1C
TOC
271
11
21
7 5
PO 3
24
3 2.7
16.9
13.8
272
1 1
22
75
P 63
1
m


2 73
1 1
22
7 5
PG3
2
9
9

274
1 1
22
75
PG3
3

9

27 5
1 l
22
75
PG3
4



276
1 1
22
75
PG3
5

9

2 77
1 1
22
75
PG3
6

9

276
1 1
22
75
PG3
7

9

2 79
1 1
22
75
PG3
' 6

9

2 80
1 1
22
75
PG3
9
3 3.7
17 .9
15.8
28 1
1 1
22
75
PG3
10
3 9.2
18.1
2 1.1
282
1 l
22
75
PG3
1 1
3 3.6
17.1
1 8. 5
283
1 1
22
75
PG3
l 2
34.3
16.0
16.3
284
1 1
22
7 5
Po3
1 3



2 8 5
1 1
22
7 5
PG3
14
34.1
17.6
16. 5
286
1 1
22
75
PG3
15



287
1 1
22
75
PG3
16
32. 6
16.4
1 6.4
288
1 1
22
75
PG3
1 7



289
1 1
22
75
PG3
18
3 1.4
15.8
15.6
29 0
1 l
21
75
PG6
18
33. 7
1 e. 5
l 5.2
2 91
1 1
21
75
Po6
l 9



292
1 1
21
75
Poo
20
3 4.5
1 9 .6
15.9
293
1 1
21
75
PG 6
2 1



294
1 1
21
7 5
PGfa
22
3 5.5
18.4
17.1
295
1 l
21
75
PG6
23
35.2
18.2
17.0
29 6
11
2 1
75
PG6
24
34.6
20.0
l 4. 6
2 97
1 1
22
75
PG6
1
32.0
18.2
13.8
29 8
1 1
22
75
PG6
2
3 1.3
17.0
14.3
299
1 1
22
75
PG6
3
32.4
16.6
13. 8
30 0
1 1
22
75
PG6
4



BS
TP
OP
TOP
TUH13
Nh3
COL 08
OS
CUND
27 1
0.271
0.238
0.033

G

O
'
0. 26

2 72





0.30

273


.#
9

9
0.20

2 74






0. 1 0

2 75




m

-0.02

2 76





-0.28

2 77





-0.44

278





-0.41

2 79


9
V


-0.35

280
0.343
0.3 10
0.03.3
0.04

-0. 30

t 1
0. 345
0.308
0.03 I

0.04

-0.30

282
0.352
0.313
C 039

0.06

-0. 27
83
0 366
0.336
0.030

0.06

-0. 10

284






0.16
285
0.388
0.352
0.03o

3*
O

o

0. 41

2 86





0.33

26 7
0.450
0.424
0.02o

0.03

0.24

288






0. 16

28 9
0.46C
0. 423
0.033

0.0 1

0.11

290
0.298
0. 260
0.038
0. 08

0.11

29 1

'




0.00

29 2
0.274
0.237
0.03 /

c

o
U
-0.10

293






-0.15
294
0.307
0.262
0.04 6

0.09
9
-0.06

29 5
0.311
0. 270
0.04 1
0. 08

0.19

29 6
0.302
C.250
0.052

0.10
9
0. 26

297
0. 306
0. 275
0.031

0.00
0.30

29 8
0.263
0.233
0.C3 0

0. 1 0
9
0. 20

99
0.285
0.247
0 03 6

0.0 3
9
C. 1 0

3 0 C
9




9
-0.02



-159-
Most of the significant correlations between the metabolism data
set and the canal water quality and canal physical characteristics data
sets were expected. Plankton-dominated canals and autotrophic canals
tend to be more turbid and have higher total and organic carbon con
centrations. Higher metabolic levels are associated with higher maximum
oxygen values, lower Secchi depths, higher water temperatures, and
greater sill development. The plankton metabolism levels were higher
in canals with higher organic carbon concentrations and greater tidal
ranges and frequencies.
The canonical correlation analyses were useful for indicating that
the canals' metabolic patterns were generally independent of the canals'
nutrient exchange behaviors, but were dependent or associated with the
canals' water qualities and physical characteristics. The associated
factors were subjectively identified from the pairs of canonical vari
ables. However, neither the identification nor the quantification of
the interrelationships between the metabolism data and the other
measured parameters were totally satisfying. The stepwise regression
analyses, however, did describe the quantitative relationships for the
metabolic parameters and the independent canal and estuary parameters,
and identified the significant factors and their effects on canal
metabolism.
The regression equations for the nine metabolic parameters (Table
27) are the "best" multiple variable models that relate the observed
metabolic responses to the independent variables. The 32 independent
parameters that were made available for model generation consisted of
21 single-factor variables and 11 first-order multiplicative interaction
terms for the basic physical and chemical characteristics of the canal


-232-
uus
MNTH
LAY
YEAR
srAT ION
T l ME
1
D 1
Z2
DO 2
7 4 1
5
16
76
HI 2
1 830
0
6. 92
1.0
6.45
742
5
1 7
76
H I 2
1 830
0
8 80
i 0
8.21
743
5
1 7
76
H I 2
1830
0
8.37
l 0
8.25
744
5
l 7
76
H i 3
730
c
6. 65
1.0
6.43
745
5
1 7
76
H I 3
730
0
5.40
1 .0
5.62
74 6
5
16
76
Hi 3
1 83 0
0
11.3o
1.0
9.62
74 7
5
16
76
HI 3
1 830
0
7.2 5
1.0
7.10
74 8
5
l 7
76
H i 3
1 83C
0
12.81
1.0
10.81
749
5
1 7
76
H1 3
163 0
0
8.10
1 0
8.83
75 0
6
12
76
FL 1
700
0
5.88
1 0
6. 97
7 51
6
12
76
FL1
1900
0
9.52
1.0
7 99
762
6
1 3
76
F L1
1 9 00
0
8. 73
1 0
7.68
75 3
6
12
76
FL2
700
0
5.00
i .0
5.85
754
6
1 2
76
F L 2
190 0
0
8.8o
1 .0
7.45
76 5
6
13
76
F l_2
1 900
0
8. 80
1.0
9.31
756
6
1 2
7 6
FL3
700
0
6.60
1 .0
6.98
757
6
12
76
FL3
7 CO
0
6.03
1.0
8.62
7 56
6
1 2
76
FL3
1900
0
9.69
1.0
9. 35
759
6
12
76
F L3
1 900
0
12.33
1 .0
11.28
76 C
6
1 3
76
Fl_3
1 900
0
9. 30
1.0
6. 73
7 6 1
6
L 3
76
FL3
1900
0
11.08
1.0
9.49
7 02
7
15
76
AP 1
730
0
5.07
1 .0
5.18
763
7
15
76
AP 1
7j0
0 :
5. 1 2
1.0
4.97
764
7
14
76
AP 1
1900
0
8.23
1.0
8.03
765
7
l 4
76
AP 1
1 9 00
0
7.47
t 0
7.35
76 6
7
1 5
76
AP 1
1900
0
7.97
1.0
8.16
767
7
1 5
76
API
1900

8.42
1.0
8.03
768
7
15
76
AP2
73 0
0
5. 02
1.0
5.45
7 69
7
1 4
76
AP 2
1900
0
8.48
1.0
8.56
770
7
1 5
76
AP2
1900
0
8.86
1 .0
0.81
DBS
Z 3
DUB
Z4
004
Z5
U5
L>U O
0 7
Z6
74 1
2.0
7. 00






742
2.0
7,45



'


743
2. 0
7. 94




*

744
2 .C
6.17
3.0



74b
2.0
5.71
3.0

4,0
itiB


746
2.0
6. 4-2
3.0





747
2.0
7.85
3.0

4.0
6 l O
9

74 8
2.0
10.02
3.0



9

74 9
2.0
8.0 9
3. 0




9
750
2 .0
o. yo
2.5





75 1
2.0
4.20






752
2.0
5.6 3





7 53
2.0
1.00
3.0





754
2. 0
3.37
3.0
9



75 5
2.0
2.68
3.0

*



756
2.0
4.28






757
2.0
4.72
3.0



9

758
2.0
4.48






75 9
2.0
3.89
3.0





760
2.0
5. 46





70 1
2.0
5.73
3.0





76 2
2.0
5.13
3.0

3.3
4.67
763
2.0
4.92
3.0

4. 0
4.95


764
2.0
7.75
3.0

3.3
7.25


76 6
2.0
6. 72
3.0

4. C
6.41
O

l .
7 66
2.0
8.18
3.0
9
3.3
7.78


76 7
2.0
8.3 1
3.0




76 8
2. C
5. 76
3.0





76 9
2.0
8.42
3.0



9
9
77 0
2. 0
8. 76
3.0



9
Z 7


-105-
Table 14. Principal components and correlation matrix for the
metabolism data.
CORRELATION MATRIX
TGPP
TR
PGPPM2
PRM2
PGPPM3
TGPP
1.00
0.87
0.44
0.47
0.43
TR
0.87
1.00
0.22
0.48
0.37
PGPPM2
0.44
0.22
1.00
0.61
0.76
PRM2
0.47
0.48
0.61
1.00
0.44
PGPPM3
0.43
0.37
0.76
0.44
1.00
PPRM3
0.39
0.45
0.51
0.73
0.52
TRP
0.10
-0.24
0.38
0.01
0.21
PPR
0.02
-0.19
0.39
-0.21
0.36
PDOMIN
-0.27
-0.33
0.40
0.24
0.18
PPRM3
TPR
PPR
PDOMIN
TGPP
0.39
0.10
0.02
-0.27
TR
0.45
-0.24
-0.19
-0.33
PGPPM2
0.51
0.38
0.39
0.40
PRM2
0.73
0.01
-0.21
0.24
PGPPM3
0.52
0.21
0.36
0.18
PPRM3
1.00 .
0.03
-0.15
0.29
TPR
0.03
1.00
0.46
0.06
PPR
-0.15
0.46
1.00
0.20
PDOMIN
0.29
0.06
0.20
1.00
EIGENVECTORS
1
2
3
TGPP
0.38
-0.26
0.37
TR
0.34
-0.44
0.22
PGPPM2
0.43
0.29
-0.00
PRM2
0.42
-0.10
-0.31
PGPPM3
0.41
0.18
0.10
PPRM3
0.40
-0.06
-0.33
TPR
0.10
0.42
0.33
PPR
0.70
0.50
0.39
PDOMIN
0.10
0.39
-0.55
EIGENVALUES
3.64
2.16
1.41
PORTION
0.40
0.24
0.15
CUM PORTION
0.40
0.64
0.80
Nomenclature as in Table 2


38
Figure 13. Canals and sampling stations at the North Miami site.


-95-
OdS
CANAL
MN TH
DAY
Y EAR
LTL
E 1
c
E TUC
b TP
E GP
E TCP
1
PG 6
3
21
7 5
27.
3
9

7
1 7 b
0.436
0.333
0.098
2
PG3
3
21
7b
t 7.
7
1 1

b
15.9
C b b 6
0.369
C. 1 6b
3
PC 3
3
22
7 b
2b.
9
7

9
19.3
0.476
0.376
0.095
4
PCti
3
22
7 b
£ b .
9
7

D
19.1
0.43 7
C 3 7 b
0.05b
5
PB3
3
26
7 b
J £.'
7
1.1

7
20.9
0.23 1
0.160
0.051
o
P B 6
3
26
75
J
b
19

C
13.0
0.234
0.187
0.046
7
LX 3
3
25
7b
JO*
7
4

7
1 2 C
0.044
0 .026
C 0 1 o
8
L X 6
3
25
7b
Jo
1
24

1
1 2.0
0.049
0.037
0.0 12
9
PG 6
6
1 4
7b
J 2 *
1
1 9

2
12.9
0.468
0.478

1 0
PG3
b
1 4
7b
JO .
6
1 9

8
1 0 .3
0.4 b 7
0.490

1 1
PC 3
6
1 5
7b
1
i 8
#
6
10.6
0.545
0.581

1 2
PCb
6
1 5
7b
32 .
3
1 7

5
14.0
0.515
0.570

13
PB3
b
l 9
7 5
4
9
29

b
13.1
0.221
0.170
0.049
1 4
PU6

1 9
7b
4 3#
1
29

5
1 3 b
0.234
0.177
0.052
1 5
L X 6
b
1 6
7b
*+*+
7
32

5
12.2
0.0 b 8
0. C20
0.049
1 b
L X3
6
1 6
7 b
44 #
8
34

1
10 i 7
0.084
0 .027
0 .059
1 7
PG3
9
6
75
J2.
4
16

9
l 4 b
0.4 83
0.43b
0.046
1 B
PG6
9
6
7b
32
9
1 b

7
16.2
0.476
0.453
0.025
1 9
PG 9
9

75
. J J *
1
1 6

2
1 b 2
0 .4 63
0.434
0.049
20
PC3
9
9
7 b
j j
4
1 6

6
1 b 7
0.552
0.472
0. 061
2 1
PC6
9
9
7 5
35 .
2
1 5

d
19.4
0.b42
0.467
0.0 55
22
PC 9
9
9
7b
3 5.
6
16

0
19.6
0.535
0.456
0.077
2 3
PB3
9
7
7b
b9
3
2 6

5
11.9
0.247
0.200
C 04 7
24
Po6
9
7
7 5
4 ci
0
H

b
1 3 b
0.270
0.2 18
C .052
'25
LX3
9
1 2
7b
50.
4
31

9
1 8 b
0.053
0.073
0.000
2 o
LX6
9
1 2
7 b
*9 .
2
32

7
16.4
0.057
0.067
0 .000
27
PG 6
1 1
2 l
75
4 .
1
16

9
1 5 .4
0.326
0 ..288
0.037
26
PG3
1 i
2 1
7b






Ub S
ENH3
E TUI-ifJ
t COLOR LLONU AV GDO
Ml NU
MAX LU
5ECCHI
T tMP
1
0.03
4.5

b 0 5
2.80
9 6 0
1.45
24
2
0.05
b. 9

b 9 C
3.00
1 0 .0 0
1 33
24
3
0.05
b 1

b 3 4
2 b b
6. 1 0
1.52
2 3
4
0.0 l
4.5

6.97
5 1 C
o 50
1.48
22
5
0.10
4.3

5.72
4.10
7.80
1 .00
2 b
6
0.10
3.7
. b 2 8
4.60
a. 60
0. 93
25
7
0.01
3 1

5.7 b
4.70
c. 5 0
1.26
2 5
8
0.0 1
3.1
. 5.78
o 50
o 6 0
1.27
23
9
0 .05
1.4
6 b
5.97
3.4b
6 o b
2.27
29
1 0
0.07
1.4
4 7
b 3 5
2.35
7 .90
2.31
2 3
1 1
0.05
1 0
5 1
. 6.49.
1.90
9.4 0
1.60
3 0
1 2
0.04
1 0
73
. 6.8b
2.2 0
9.20
2.0 7
30
l 3
0.09
2. 2
9 2
. 5 <+ 0
0.65
1 4.00
0.97
29
1 4
0.07
2.2
1 0 1
5 9
2.00
10.20
0.90
29
1 5
0.05
3.3
124
. 4.19
0.90
5.85
1.07
2 9
1 6
0.05
4. 3
125
. 4.82
3.4b
6.05
0.92
28
1 7
0.2 1
4.6
225
. 3.51
1.80
4.67
1.13
29
1 8
0.22
cl'
24 5
. 3.8b
2.40
5. 35
1.22
29
19
0.17
'2.8
2 1 9
. 5. 63
2.40
12.00
0. 98
26
20
0.24
4.7
2 1 4
. 4.39
C 1 2
1 b.00
0.98
29
2 1
0.18
5.6
220
4.02
0.10
14.10
0.98
29
22
0.11
3 6
2 1 5
. 7.97
0.7 5
l 3. 25
0.84
30
23
0.06
2.2
69
. 6 60
3.3 7
1 b 3 0
0.98
3 3
24
0.0Q
3. 5
1 05
. 5.48
3.6b
9.47
0.92
32
25
0.06
4.8
12 1
. 4.4-2
3.02
6.85
l 23
32
2b
0. 02
3.9
9 7
. 4.9 J
2.0o
7.4 C
1.30
32
2 7
0. 07


. 7.62
5.8 7
8.9 5
1.47
22
28
'


. 7.71
1.2b
9. 50
1.42
22


Abstract of Dissertation Presented to the Graduate Council
of the University of Florida in Partial Fulfillment of the Requirements
for the Degree of Doctor of Philosophy
CANAL-rESTUARY NUTRIENT EXCHANGE AND METABOLIC LEVELS IN
FLORIDA RESIDENTIAL CANALS
By
William Arthur Bailey
March 1977
Chairman: Jackson L. Fox
Major Department: Environmental Engineering Sciences
Sixty-one observations of oxygen metabolism, canal-estuary nutrient
exchange, and water quality in 35 residential canals at 12 locations in
the State of Florida were made over a 20 month period. The free-water
diurnal oxygen method and in situ light-dark bottle 24 hr oxygen in
cubations were used to estimate the oxygen metabolism of the total canal
communities and the planktonic components. Total community gross
2
primary production varied from undetectable to 24.9 g O^/m -day and
had a mean value of 8.59. Planktonic gross primary production varied
2
from 0.40 to 23.9 g O^/m -day and had a mean value of 4.91. Community
gross primary production:community respiration ratios varied from 0.31
to 2.95 and had a mean value of 1.16. Regression equations for the
metabolic parameters explained more than 70 percent of the observed
variabilities using canal physical attributes, daylengths, solar in
solation levels, and local estuarine water quality as independent
variables.
Net canal-estuary exchanges of carbon (total C mass and organic C),
phosphorus (total P mass, ortho-P, and total organic P), ammonia
xii


-9-
characteristics of four New Jersey canal developments. Substantial
data on four pairs of canals in Florida have been reported by Fox ej; al.
(1976) and by Piccolo et. al. (1976) .
Chesher (1974) discusses his physical, chemical, geological, and
biological work on 50 canals in the Florida Keys, and finds the canals
generally to be in good condition. Canal orientation to the wind and
the substrate type were found to be the most important factors affecting
canal water quality. Chesher feels that the advantages of such systems
outweigh the disadvantages to the productivity and economy of the Keys.
Paulson jet _al. (1974) report physical, hydrological, phytoplankton,
benthic fauna, and sediment composition data for single collections in
two canal systems in Florida and two in Texas. They believe that the
lower dissolved oxygen concentrations at the dead-end stations might be
alleviated by restricting the depths of the canals and eliminating
dead ends. Paulson's 1975 report includes physical, biological, and
chemical data for a canal system and a natural bayou in southern
Mississippi. They found essentially no differences in flushing rates
and biota between the two systems. However, dissolved oxygen values
tended to decrease and coliform levels tended in increase toward the
dead end of the canal. The canal was shallower than the adjacent water
body.
Nixon ej: aJ. (1973) evaluated the production, metabolism, suspended
material, dissolved organics, nutrients, phytoplankton,. bacteria, fish,
fouling communities, and sediments of a small boat marina and a natural
marsh embayment in Rhode Island. The two types of systems were similar
and were felt to be compatible coastal systems in Rhode Island. The
authors regarded the fouling communities of the bulkheads, pilings, and


-283-
CQRKLLATIN CUEFF iC I fc-NTS / ('HQb > |R| UNDER H0:RHC3=0 / NU
M3EK OF OBSERVATIONS
OTC
DEVtL
W I DT H
EeUNU
YEAR
Ak tA
LENGTH
TI DE
-0.129C9
0.12571
-0.12316
0.1 2270
-0.11060
-0.10 9 10
-0.10586
0.3430
0.3559
0.5664
0. 3676
0.4 17 1
0.4232
0.4375
56
5
24
56
. 56
56
56
PPR
VOLUME.
UP
ETe
PUDMIN
FCULLR
MUNTH
0.10412
-0.1 01 2 7
0.09926
0.09686
-0.09660
0.09560
0.09424
0. 46 72
0.457 7
0.4667
0.4685
0.49 94
0 .5462
0.4896
51
56
5o
56
49
42
56
ETURB
TPR
UUP
3 P R M 3
DAY
EOP
MINUU
0.0b442
0.08125
C.07960
0.0 73 53
-C.0 7240
-0.07239
-0.07049
0.5684
0.5789
0.559d
0.6061
0. 595 9
0.5960
0.6091
48
4 9
56
51
5o
56
55
MINKES
SteOH 1
TEMP
Die
DeUND
ETP
DTURt
0.0 6b 56
-0.064 18
-0.06342
0. 06262
C. 0 59 4 6
-0.05879
-0. 055 74
0.6260
0.6416
0.6455
0.64 66
0.7826
0.6669
0.7067
56
55
55
56
2 4
5 6
48
ETOP
LTO C
D/vYE
teL R
FTP
eUMTIDE
FT UP
-0.CS112
- 0.042 5
0. 041 71
0.0 38 72
-0.03651
0.03475
0.03348
C.7189
0.7555
0.7602
0. 80 78
0.7693
0.7993
C. 81 3 7
52
5 6
50
42
56
56
52
MAXDU
F TUR B
MDEPTH
AVGDU
enhj
FNH3
PP M2
-0.03150
0 C2 2 d 8
0.01944
-0.01801
0.0 0835
-0.00835
0.00297
0.8194
0.8773
0.8669
0.8962
0.9513
0.9513
0.9835
55
48
5o
55
56
56
5 1
FIC
F I C
E1C
ECND
F LUND
SE WEPS
ft e
ETC
1.00 0 00
0.96685
0.87243
0.832 76
-0. 569c 7
C.08495
0.551 74
0.0000
0.0001
0.000 1
0.0001
0.0001
0 .000 1
0.0001
58
58
24
24
58
58
58
WIDTH
SUN
Fiue
FTP
ETOC
ETP
EOP
- 0.54568
- 0.5008 1
-0.4261 o
-0.42360
-0.42028
-0.41451
-0 J95CS
0.0001
0.0001
0.0009
0.0009
0.0010
0.0012
0.0C2 1
58
53
5o
56
58
56
58
QIC
E TP
F LP
FT UP
ETURB
MINKES
DeOL QR
0.34303
0.32667
-0.3236l
-C.30J02
-0.3C283
-0.26814
0.28789
0.0096
0.0152
0.0 132
0.0259
0.0325
0.0 263
0.0645
56
54
58
54
5 0
58
42
MONTH
F TUR B
C6NU
VULUME
DAY
MUEPTH
OOP
0.27686
-0.27404
-0.25540
-0 .2531 l
-0.2 52 73
-C 23909
-0.23003
0.0354
0.0541
0.2264
0. C5o2
0.0556
C.0707
0.08 81
58
50
24
58
58
58
56
A VG DU
eURBS
AGE
DE VfcL
Y E AK
MAXDO
AREA
-0.22870
-0.22 745
0.2 1624
-0.21607
-0.21319
-0. 20 6 02
-0.80738
0.08 71
0 0860
C.095o
0 1 033
0.1048
0.1205
0.1133
57
58
58
5 8
5 6
5 7
58
LENGT H
TEMP
M IN Uu
BULK
DTC
POMIN
DTP
-C 18904
0.15309
-0.1525/
-0.13688
0.13590
-0. 13 130
-0.12443
0.1553
0.2556
0.257 2
0.3055
0.3180
0.3 58 4
0.3609
56
5 7
5 7
5b
56
51
56


APPENDIX D. Descriptive statistics and correlation coefficients for
all parameters.
Nomenclature and units as in Table 2


-30-
Figure 7. Canals and sampling stations at the Boca Ciega Bay site


Table 17.
(Continued)
AGE BULK
CURBS
SEWERS
SEWERS
-0.27 0.33
0.18
1.00
TIDE'
0.55 0.45
0.01
0.03
MINRES
0.02 -0.26
0.18
0.16
CUMTIDE
0.40 0.17
-0.11
-0.24
DAYL
-0.01 -0.29
-0.00
-0.16
Nomenclature as in Table 2
1
EIGENVECTORS
2
SUN
0.13
-0.28
LENGTH
0.40
-0.17
WIDTH
0.36
-0.09
MDEPTH
0.12
0.36
AREA
0.41
-0.19
VOLUME
0.44
-0.12
SILL
0.08
0.30
DEVEL
0.22
0.25
AGE
0.16
0.44
BULK
0.20
0.11
CURBS
0.22
0.03
SEWRES
0.29
-0.12
TIDE
0.19
0.35
MINRES
0.00
0.07
CUMTIDE
0.02
0.32
DAYL
0.00
-0.25
EIGENVALUES
3.91
2.83
PORTION
0.24
0.17
CUM PORTION
0.24
0.42
TIDE
MINRES
CUMTIDE
DAYL
0.03
0.16
-0.24
-0.16
1.00
-0.50
0.61
-0.36
-0.50
1.00
-0.30
0.11
0.61
-0.30
1.00
-0.17
-0.36
0.11
-0.17
1.00
3
-0.05
-0.13
0.20
0.37
-0.09
0.02
0.37
-0.08
-0.02
-0.26
0.18
0.14
-0.34
0.54
-0.31
0.09
2.71
0.17
0.59
-112-


obs
CANAL
MONTH
DAY YEAR LENGTH
WIDTH
MDEPTH
20
PC3
S
9 75
5 75
33
3.2
2 1
PC 6
9
9 75
618
33
2. 7
22
PC 9
9
9 75
1350
30
2.5
23
PB3
9
7 75
732
23
3.0
24
PB6
9
7 75
732
21
3.2
25
LX3
9
12 75
63 1
22
1.8
26
LX6
9
12 75
52 1
1 7
1.6
27
PG6
1 1
21 75
747
30
2.8
28
PG 3
1 1
21 75
6 52
28
2.2
29
PG9
1 1
21 75
3650
30
3.0
30
PC 3
1 1
23 75
575
33
3.2
31
PC 6
1 1
23 75
616
33
2.7
32
PC9
1 1
23 75
1350
30
2.5
33
P 86
1 1
14 75
732
21
3.2
34
PB9
1 1
14 75
7 38
23
2.5
35
PB3
1 1
14 75
732
23
3.0
36
LX3
1 1
16 75
631
22
1.8
37
LX6
1 1
16 75
521
1 7
1.6
38
MI 1
3
24 76
2637
30
2.7
DBS
DEVEL
AGE
BULK CURBS SEWERS
M1NRES
20
IOC
16
100
0
1
4 .4
21
100
16
100
0
1
3.8
22
75
14
90
0
1
3.1
23
IOC
23
100
0
0
1 .8
24
98
23
100
0
0
2. 0
25
0
16
80
0
0
1 .5
26
0
16
0
0
0
1 .6
27
30
S
100
0
1
2.5
28
5 C
9
100
0
1
1 .9
29
50
1 1
100
0
1
2.9
30
100
16
l 00
0
1
6.6
31
100
16
100
0
1
2.9
32
75
14
90
0
1
3.0
33
98
23
100
0
0
2.4
34
ICO
20
100
0
0
2.1
35
100
23 '
100
0
0
2.3
36
0
16
80
0
0
1 .2
37
0
16
0
0
0
1.2
38
50
1 0
100
0
l
3.3
AREA
VOLUME
SILL
1 9000
60700
0.5
20400
55100
0.8
182000
455000
1.5
16800
50500
1.1
1 5400
4 92 CO
o. a
13900
25000
C .6
8860
1 42 00
1 .2
22400
62700
0.0
18300
40200
0.2
480000
1440000
0. 0
1 9000
60700
0.5
20400
55100
0.8
182000
455000
1.5
15400
49200
0.8
70000
175000
l .0
1 6600
505C0
1 1
13900
2 50 00
0 .6
8860
1 42 00
l .2
312000
842000
0.0
Table 1. (Continued)
TIDE
CUMTIDE
SUN
DAYL
0 .57
0.81
446
12.3
C 57
C. 81
446
12.3
0.57
0.81

12.3
0.98
1.67
238
12.3
0.98
1.67
238
12.3
0.64
1 14
296
12.3
0 .64
1.14
296
12.3
0.74
l. 02
2 96
11.0
0.74
1.02
296
11.0
0.74
1.02

11.0
0.80
0. 83
334
11.0
0 .80
0.83
334
11.0
0.80
0. 83

11.0
0.73
1.17
352
11.0
0.73
1.17

11.0
0.73
1.17
352
12.3
0.63
1.37
204
11.0
0 .63
1.37
204
11.0
0. 67
0.81
52 0
12.0


Table 27. (Continued)
Parameter One Variable Model
Multiple Variable Model Unexplained
Std. Dev.
PPRM3
0.20+2.5(0.61)TIDE
0.34
-9.4+0.0016(0.00083)SUN
-0.0000022(1.lxlO-6)AREA+0.29(0.15)SILL
+0.038(0.016)DEVEL+4.9(0.90)TIDE
-8.7(2.9)FNH3-0.0016(0.00078)DEVEL AGE
+0.00090(0.00025)TURB COLOR+0.56(0.20)DAYL
0.72
0.59
TPR
0.42+0.037(0.OIDFTOC
0.28
-0.40+0.0000016(0.00000073)AREA
+0.0036(0.0018)BULK+0.041(0.014)FTOC
+0.030(0.012)FTC-4.8(2.2)FTOP
-0.19(0.062)FTURB-0.050(0.022)DEPTH SILL
+0.00053(0.00024)TURB COLOR
0.77
0.36
PPR
1.1+0.0092(0.0024)DEVEL *
CUMTIDE
0.29
18.-0.0000025(0.00000012)AREA
-0.45(0.15)SILL+1.5(0.49)CURBS-8.0(1.8)TIDE
+3.7(0.77)CUMTIDE+9.0(1.8)FOP
+25.(5.5)FNH3+0.0070(0.003)DEVEL* CUMTIDE
-88.(18.)FOP FNH3-1.3(0.28)DAYL
0.74
0.58
PDOMIN
0.030+0.21(0.055)DEPTH *
CUMTIDE
0.31
-0.27+0.036(0.017FTOC+0.14(0.065)DEPTH *
CUMTIDE-O.25(0.16)FTOC*FTOP
0.41
0.64
DTC
1.6-0.018(0.0096)BULK
0.10
-10.-0.000014(0.0000018)AREA
+0.22(0.026)WIDTH+0.19(0.029FTC
0.86
0.92
+2.2(0.37)FOP-0.0053(0.0025)FCOLOR
+0.057(0.010DEPTH* AGE-3.1(0.35)DEPTH TIDE
-0.14(0.032)DEVEL* TIDE+0.095(0.019)DEVEL *
CUMTIDE
-VV T-


Table 24. (Continued)
Normalized Vectors Associated with Physical Characteristics Croup
S'tJN
LENGTH
vi on!
MDKPTU
AREA
VOLITE
SILL
DEVEL
AC!*;
j-Mjr v
CURBS
SEVERS
TIDE
MINRES
cu>:tide
DAYL
1
0.000
0.000
0.003
0.000
.000
0.Q00
0.002
0.000
0.013
0.000
0.107
0.187
0.574
0.023
-0.303
-0.004
2
0.000
0.000
0.010
0.000
0.000
0.000
-0.035
0.003
-0.015
0.000
0.137
-0.188
-0.163
-0.008
-0.068
-0.060
2
o.coo
0.000
-0.003
0.000
0.000
0.000
0.051.
0.001
-0.0IV
0.001
0.137
0.137
-0.764
0.042
0.675
-0.043
i.
0.000
0.000
0.006 .
o.oco
0.000
0.000
-0.004
0.001
-0.004
0.001
0.001
-0.230
-0.558
-0.032
0.318
-0.128
i
0.000
0.000
0.004
0.000
0.000
O.QOQ
0.003
0.00 3
0.016
-0.002
-0.030
-0.243
-0 155
-0.003
-0.040
-0.168
6
-0.001
-0.000
-0.C05
C.000
0.000
0.000
0.009
0.000
0.023
0.000
0.184
0.027
0.210
-0.046
-0.495
-0.128
7
o.ooo
o.coo
-Q.C02
0.000
0.000
0.000
-0.012
0.003
-0.007
0.001
-0.294
0.131
0.087
-0.011
-0.027
0.062

0.001
o.coo
0.008
-0.000
n.ooo
0.000
-Q.Ohi
-0.002
0.016
-0.001
-0.202
-0.064
-0.289
-0.013
0.008
-0.251
0.000
-0.001
-0.017
0.000
0.000
0.000
-0.082
-0.002
0.02 3
0.000
0.052
0.201
1.965
0-.032
-6.13
0.205
134


Table 12. Water quality characteristics for all canal observations.
Nomenclature and units as in Table 2


-77-
mg/1. The mean value for net organic carbon exchange was a net reten
tion of 0.2 mg/1 of exchanged water, with a standard deviation of 2.0
mg/1. The values ranged from a net export of 5.9 mg/1 at Marco Island
canal Mil, to a net retention of 10 mg/1 at Apollo Beach 2. The most
frequent response, however, was no significant change in the organic
carbon concentration between estuarine water entering and that leaving
the canals.
The range of total phosphorus concentrations (Figure 24) in these
canals was large, reflecting the presence of phosphate mining in the
vicinity of some of the canals. The highest values observed (ca. 0.8
mg/1) were at the Apollo Beach site. The higher values make the mean
value (0.231 mg/1) somewhat misleading, considering that nearly half
of the observations had values less than 0.1 mg/1. The net changes in
total phosphorus concentrations from flood to ebb tides had a mean
value of +0.003 mg/1, with a standard deviation of 0.020 mg/1 and a
range of -0.067 to +0.093 mg/1. As in the case of total carbon, these
canals differ in the phosphorus mass transport activities, but most
frequently have little or no effect on the phosphorus loads of the
exchanged water.
The frequency distributions and descriptive statistics for the
ortho-phosphate levels and exchange responses of these canals are
presented in Figure 25. The ortho-phosphate distribution follows a
pattern similar to that of total phosphorus. The range of net exchange
responses (-0.031 to +0.069 mg/1) indicates that some canals can be
sources of ortho-phosphate to the estuaries, while other canals can be
sinks. The most frequent response was essentially no effect on the
ortho-phosphate concentrations, whereas the mean value (+0.005 mg/1)


-303-
CORRELAT I ON COEFFICIENTS / PRClb > (R| UNDER H0:RH=0 / NU
MUER UF OBSERVATIONS
OCCND
DCNO
1.00000
0.0000
24
DIC
-0.43051
0.0357
24
FOP
0.28703
0. 17 39
24
DTP
-0.2 6 738
0.2065
24
F IC
0.2 56 40
0.2284
24
DNH3
-0.24367
0.2512
24
TEMP
0.23628
0.2663
2 4
BEVEL
0.22127
0.2008
24
TP
-0.22021
0.3012
24
HC
-0.18399
0.3894
24
AGE
0.1 6968
0. 42 80
24
SILL
C 1 6867
0.4308
24
UTURB
0.16810
0.4324
24
MONTH
0.16600
0.4382
24
P TC
-0.16491
0.4413
24
DA Y L
0.15421
0.4719
24
PD CMIN
0. 15110
0.4B09
24
E re
0. 1 50 56
0.4825
24
EuP
0.14835
0.4891
24
ETP
0. 14561
0.4972
24
DQP
-0.1 453 8
0.4979
24
TGPP
-0.13820
0.5196
24
FT P
0.13366
0.5335
24
PKM2
-0.11421
0. 5952
24
L EN GT H
0.11191
0. 6026
24
MaXOU
-0.1C 8 Jo
0.Ol43
24
ETUP
0 10 46 4
0.6 25 9
24
UCOLUK
-0.10143
0.63 72
24
D TOC
0.09729
0.6511
24
FMH3
0.08179
0.704 0
2 4
ENH 3
0.081 79
0.7040
24
F CUND
0.06042
0.70 88
24
FT DP
0.0 7 7 1 3
0.7202
-2 4
Ml NDG
0.07378
0.7 319
24
TR
-0.0733 7
0.7333
24
ECOND
-0.06972
0.7461
24
ETUR B
-0.06419
0.7657
24
VULUMt
0. 05 55 8
0.7621
24
d re
-C .0 5946
0. 7826
24
PPRM3
0 .0 563o
0.7937
24
CURBS
0.05162
0.8107
24
PGPPM3
-0.04889
0.82 05
24
BULK
-0.04824
0.8229
24
TPR
-0.04 595
0.6312
24
AREA
0.0 446 7
0.8 35 6
2 4
5 UN
-0.0 40 75
0.8500
24
vV 1 D T H
-0.03820
0.8593
24
T IDE
C.0 3 685
0.864 3
24
ETUC
-0.0324 0
0.8805
24
DAY
- 0. 029 70
0.8904
24
PGPPM2
0.02764
0.898 0
24
CUMTIDE
-0. 0 2.09 5
0.9005
24
MiNNES
-0.02673
C. 901 3
24
P PR
-0.02601
0. 904 0
24
MDEPTH
-0.02306
0.9146
24
SECCHl
-0 .0l974
0. 92 71
24
FCOLOR
-0.01677
0.9380
24
F TUR B
0 .01421
0.94 74
24
S E hLR 5
-0.013o0
0.949 7
24
ECULUR
0.0ll8C
0.9564
24
FT
-0.049
0.ydl9
24
AV GDO
-0.00304
0.9887
24
YEAR
0.00000
1.0000
24
TGPP
I G PP
1 .00000
0 .0000
56
r r
0.86980
0.0001
56
MAXDu
0.57330
0.000 1
56
PR M2
0.52318
0.0001
56
v IDTFl
0.3 05 3 1
0.0001
56
PGPPM2
0.48033
0.0002
56
PGPPM3
0.4 7C33
0.0003
56
PPRM3
0.44079
0.0007
bb
Age
0.4263 7
0.00 1 1
56
CUKuS
C.42030
0.0013
56
F CONI)
-0.40507
0. 04 96
24
ECOND
-0.38094
0.0663
24
VULUME
0 3 7 4 9 0
0.0044
56
SILL
0.34197
0.0099
56
SECCH I
-0.31493
0.0 1 b 1
56
PDMIN
-O'. 2991 1
0.0260
54
BEVEL
0.29514
0.0272
56
FTUC
0.2 8764
0.0366
53
E TP
0. 28745
.0.0369
53
DAY
-0.28113
0.0356
56
EUP
0.2 781 7
0.0437
53


LIST OF FIGURES
(Continued)
Figure
28. Frequency distribution and descriptive statistics for
(a) weighted-average ebb turbidity levels (NTU), and
(b) the net changes from average flood concentrations. .
29. Frequency distribution and descriptive statistics for
(a) average dissolved oxygen concentrations (mg/1), and
(b) minimum dissolved oxygen values recorded in all
canals . . .
30. Frequency distribution and descriptive statistics for
the average Secchi depths (m) recorded in all canals .
Page
. 83
98
99
xi


Observations
-59-
10
5 h
0
i i "i i i 1 1 1
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
PGPPM2/TGPP
N = 54 Mean = 0.60 Std. Dev. = 0.28 Range 0.16 to 1.0
C.V.% = 101
Figure 20. Frequency distribution and descriptive statistics for
plankton domination of community production.


-62-
The community production:respiration ratio analysis does not
yield the same:pattern as the production and respiration results. No
significant differences were found for the 64 combinations of location,
distance and month factors. The mean value for all observations was
1.36 with a coefficient of variation equal to 132 percent. This para
meter was relatively more variable than production and respiration for
the replicate canals, resulting in the inability to detect differences
among the means.
Analysis of the planktonic metabolism data yields inferences some
what different from those of the whole community metabolism. The level
of planktonic gross primary production and respiration on a square
meter basis depends on the season and the location. No significant
differences in the levels of planktonic production and respiration for
the entire water column could be detected along the lengths of the
canals.
There were significant differences among the means of the plank
tonic P:R ratio. The changes in the P:R ratio with season varied
depending on the distance up the canals.. No significant differences in
the patterns of planktonic P:R ratios was detected for the four
locations.
The results of the analysis of variance for the surface values of
planktonic metabolism were similar to those for the entire water columns.
The effect of distance and season varied with canal location for the
surface plankton production, whereas only the effect of season varied
with location for the entire water column. In fact, no effect of
distance up the canal could be detected for the planktonic metabolic
levels on a square meter basis, for these canals.


-42-
days was measured with a Belfort pyrheliometer.
Nutrient Exchange and Water Quality
The net exchanges of total carbon, inorganic carbon, total organic
carbon, total phosphorus, ortho-phosphorus, total organic phosphorus,
ammonia, turbidity, color, and conductivity across the canal entrances
were estimated by determining the total mass of each material entering
and leaving the canals during 24 hour periods. The concentrations/
values of these parameters were measured in surface water samples taken
periodically at the canal entrances. The volume and direction of water
flow across the canal mouths were determined from a recording tide
gauge and the canal water surface area. By summing the products of
the concentrations and volumes of flow for each sampling interval, the
total mass exchange for each material and each tidal phase was obtained.
Since the ebb and flood tidal phase volumes were not always equal, the
total mass exchange for each tidal phase was divided by the respective
total flow volume, to obtain weighted-average concentrations of each
material. The difference between the weighted-average concentrations
(flood-ebb) yield the net exchanges in concentration units. The mass
exchange values are not shown in the Results section but can be obtained
for each material by multiplying the weighted-average exchange concen
trations (Table 7) by the canal surface area (AREA) and the cumulated
24 hr tidal range (CUMTIDE) in Table 1.
Several assumptions were included in this approach to estimating
net exchanges. The water samples collected and the concentrations
measured were assumed to represent the average concentrations of the
water transported during the sampling intervals. The water surface was


-210-
8S
MUNTH
DAY
Y 6. AH
STATION
DEP TH
TGPP
TH
297
7
31
76
683
0
1 .85
2 .00
29 8
7
3 1
76
6 8 3
1


299
a
1 8
76
KC1
0
5.14
8.6 1
300
a
i a
7b
KC 1
2

30 1
a
i a
76
K.C 2
0
5.24
5.84
3 02
a
i a
76
KC2
2


30 3
8
i a
7b
KC 3
0
l .53
5.16
3 04
8
1 8
76
KC j
2


305
10
26
76
N MI
0


30 6



1


307
1 0
2 7
76
NMl
0
9.84
2.64
30 8



1


309
10
28
76
N MI
0
14.74
1 1 .40
310

*

1
t

3 1 1
10.
25
7b
NM2
0
1 .92
2 .04
31 2



1


3 1 3
10
26
76
NM2
0
12.54
6.00
31 4



1


3 1 5
10
2 7
76
N M2
0
15.78
13.80
3 1 6



1


bs
PGPPM2
PKM2
PGPPM3
P P H M 3
TPH
PPK
SUN
297
0.96
0.46
1.34
0.21
0.92
2.09
554
29 ti
.
.
0.58
0.71


04
299
1.39
2.01
0.87
0.86
0 .60
0.69
72
300

.
0.21
0 4o


72
30 1
1 .53
2.09
.43
0 56
0.90
0.73
72
JO 2

.
0.44
0.5 1


72
303
0.40
1 36
0.38
0.60
0.30
0.29
72
304


0.0 1
0.38


72
30 5
3.62
1.32
1.68
0.23


3 l 6
30 6


1.89
0. 4b



307
11.63
9.73
6.28
0 .89
9.73
3.72
346
3 0 3


5.66
0.30



309
6.13
3.84
4.49
1 .34
1.29
l 59
1 83
3 1 0


2.59
1 .27



3 1 1
9.06
5.02
3.61
3.10
0.94
l .80
3 1 6
312


4.77
1 .39



313
9. 80
2.40
6.24
2.00
2.09
2 .4 0
346
314


4.45
l 23



31 5
6.67
1.40
4.2b
2.17
1.14
1 .69
183
3 l 6


3.03
1.47




-61-
Table 4. Results of the analyses of variance for the total community
and planktonic metabolism data (1975).
Source of
Variation
Community
Plankton
Per Square Meter
Per Square Meter
Surface
GPP*
R*
P/R*
GPP
R
P/R
GPP
R
Location
NS
NS
Distance
NS
NS
NS
NS
Month
, NS
Location x Distance
, NS
NS
NS
NS
**
NS
Location x Month
NS
**
**
NS
**
**
Distance x Month
NS
NS
NS,
**
NS
NS
Location x Distance
**
**
; NS
NS
NS
NS
NS
NS
x Month
Mean
7.80
7.49
1.36
4.01
2.56
2.30
4.71
1.47
S.D. (adjusted)
2.95
3.30
1.80
1.69
1.64
1.52
1.68
0.91
C.V. %
37
44
132
42
64
65
35
62
R2
0.88
0.87
0.50
0.83
0.77
0.77
0.92
0.77
Unadjusted S.D.
6.22
6.49
1.77
2.63
2.20
2.01
* GPP gross primary production; R respiration;
P/R production : respiration ratio (GPP/R)
** Indicates the term is a significant source of variation
NS Indicates the term is not a significant source of variation
Blank indicates that an exact test for the term cannot be made
2 3
Units-, g O^/m -day or g O^/m -day


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-224-


-141-
independent variables. The dependent variables for which models were
generated, and the independent variables made available for model
generation, are shown in Table 26. The products of several independent
variables were subjectively included to allow for significant multi
plicative interaction terms to be incorporated in the models. Many more
two-way interaction terms could have been included with the independent
variables, as well as higher-order terms. But only those combinations
of variables that I thought might have an interactive effect, i.e.,
the effect of one depended on the level of the other, were generated.
Output from the procedure for each dependent variable consists of
the linear expression, its r-squared value, variable-inclusion signifi
cance tests, and the unexplained variances for each model size. The
model size was limited to ten independent variables.
The "best" one variable models, the "best" multiple variable
models (up to 10), the r-squared values, and the unexplained standard
deviations for the twenty dependent parameters are shown in Table 27.
The multiple variable models in Table 27 were the largest equations that
contained only significant variables (as determined by t-tests) or that
improved the r-squared value of the previous model by 0.02.
These descriptive models give the functional relationships between
the observed responses of the twenty dependent parameters and the
independent variables found to have significant effects. The models do
not establish cause and effect relationships. They do quantify the
associations between the important independent canal-estuary-sampling
day factors and the dependent response parameters. For example, the
average dissolved oxygen (AVGDO) model indicates that wider canals
tended to have higher average dissolved oxygen concentrations than more


-80-
suggests a slight retention of inorganic phosphate by the canals.
Figure 26 shows the frequency distributions and descriptive
statistics for the total organic phosphorus (TP-OP) concentrations and
net exchanges. The organic phosphorus concentrations are more normally
distributed around the mean value (0.043 mg/1) than are the total and
ortho-phosphorus concentrations. The net organic phosphorus exchange
estimates also exhibit a wide range of values (-0.069 to +0.042 mg/1),
and a mode of essentially zero effect on the organic phosphorus levels
of the estuarine water entering the canals. The mean value (-0.002
mg/1), though, suggests that a net export of organic phosphorus took
place.
The frequency distribution and descriptive statistics for the ebb
concentrations and net exchanges of ammonia for these canals are shown
in Figure 27. The ranges of concentration (0.00 to 0.26 mg N/l) and of
net exchange (-0.18 to +0.08 mg N/l) are wide. The mean value of ammonia
exchange (0.00 mg/1) indicates that the "average canal" has no effect
on the ammonia levels of the estuarine water. The distribution of the
exchange responses shows that some canals are sources of ammonia to
the estuary, whereas other canals are sinks.
The distributions of the average ebb turbidity levels and the net
changes in turbidity levels from ebb to flood tide for these, canals
(Figure 28), show the ranges of values and of effects on the flooding
waters. The mean net change value (+0.2 NTU) suggests that the "average
canal" lowers the turbidity level of the estuary. But the range of
values (-2.1 to +5.0 NTU) show that canals can either decrease or
increase the turbidity levels of the entering water.


-108-
Table 15. Principal components and correlation matrix for the net
nutrient exchange data.
CORRELATION MATRIX
DTC
DTOC
DOP
DTOP
DTC
1.00
0.87
-0.33
0.23
DTOC
0.87
1.00
-0.30
0.13
DOP
-0.33
-0.30
1.00
-0.20
DTOP
0.23
0.13
-0.20
1.00
DNH3
0.11
-0.03
-0.00
0.09
DTURB
-0.09
-0.07
-0.10
-0.29
DCOLOR
0.18
0.00
0.20
0.01
DNH3
DTURB
DCOLOR
DTC
0.11
-0.09
0.18
DTOC
-0.03
-0.07
0.00
DOP
-0.00
-0.10
0.20
DTOP
0.09
-0.29
0.01
DNH3
1.00
-0.02
-0.04
DTURB
-0.02
1.00
0.32
DCOLOR
-0.04
0.32
1.00
EIGENVECTORS
1
2
3
DTC
0.62
0.18
0.11
DTOC
0.59
0.15
-0.07
DOP
-0.37
0.03
0.54
DTOP
0.29
-0.34
0.37
DNH3
0.07
-0.15
0.47
DTURB
-0.12
0.64
-0.23
DCOLOR
0.00
0.61
0.51
EIGENVALUES
2.18
1.41
1.06
PORTION
0.31
0.20
0.15
CUM PORTION
0.31
0.51
0.66
Nomenclature as in Table 2


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-274-


-269-
UbS
MONTH
DAY
Y EAk
ST AI I UN
TIME
I C
1C
TUC
y 9 i
8
1
7b
63 1
5
'32.0
16.3
l 5. 7
992
8
1
76
6 1
6
35.1
1 5. 3
1 9. 8
99 b
8
1
76
Gd 1
7
29.4
15.4
14.0
994
8
1
76
63 1
8
28.5
l 5. 2
13.3
9 95
8
1
76
6b 1
9
33.8
15.3
18.5
996
Q
1
76
6 B 1
1 0
32.3
15.3
17.0
997
8
1
76
63 1
11
31.3
16. 5
14.8
998
8
1
76
O 1
1 2
31 .6
15.6
16.0
999
8
1
76
03 1
l 3
27.8
16.3
11.5
1 COO
8
1
76
OB 1
14
29.9
1 6. 6
13.3
100 1
8
1
76
Ob 1
1 5
27.4
15.8
11.6
1002
7
3 l
76
03 2
1 b
2o.3
15. 3
11.0
1003
7
3 1
76
0b2
1 7
46.6
26.2
20,4
1004
7
3 1
76
03 2
1 8
28.6
16.2
12.4
1005
7
3 l
7 6
OB 2
1 9
28. 7
14.7
14.0
1 006
7
3 1
76
OB 2
20
28 .9
14.7
14.2
100 7
7
3 1
76
GB2
2 1
31 .3
15.7
15.6
1008
7
3 1
76
OB 2
22
28.6
15. 7
12.9
1009
7
3 1
7 6
OB2
23
27.9
14.8
13.1
10 10
7
3 l
76
03 2
24
28.0
16. 2
11.8
10 11
8
1
76
OB 2
1
28.8
1 7. 5
11.3
10 12
8
1
76
032
2
26.9
16.7
10.2
10 13
8
1
76
03 2
3
29. 4
13. 8
15.6
10 14
8
1
76
OB2
4
28.7
15. 3
13.4
10 15
8
1
7 6
6c) 2
5
28.0
13.8
14.2
10 16
8
1
76
63 2
6
2 6.6
1 6. 5
12. 1
1 C 1 7
8
1
76
63 2
7
28.1
16.3
11.6
10 18
8
1
76
63 2
8
27.5
1 6. 3
11.2
10 19
8
1
76
602
9
29.2
15. 5
13.7
1020
8
1
76
60 2
l 0
25.5
15.6
9.9
UbS
T P
UP
1 UP
T OKO
NH3
CULUP
DS
CuNO
99 1
0
.020
0.02 0
0. 000
2.5
0.07
1 C 7
-0.01
2 69
99 2
0
. 020
0.020
0.000
3 1
0.07
l C 3
-0.08
2 65
993
0
.015
0.013
0.000
2.9
0.04
1 l 7
-0.12
268
994
0
.003
0 C03
0.000
3.2
0.09
1 13
-0 C8
2 74
995
0
. 01 9
0.019
0 .000
3.2
0.15
88 .
-0.02
263
99 6
0
.019
0.019
0.000
3.8
0.04
1 0 7
-0.14
266
99 7
0
.02 9
0.029
0.000
3.9
0.0 7
1 20
0.00
267
99b
c
.018
0.018
0.000
3.9
0.07
103
0.03
267
999
0
.030
0.019
0.011
4.2
0.2 3
167
0.02
277
1000
0
.033
0.029
0.004
3.4
0.11
1 23
0.00
2 70
1 00 1
0
. 028
0. 020
0.008
4.4
.05
9 1
0.0 2
2 73
1 CO 2
0
.024
0. 023
0.00 l
2.7
0. 02
104
-0.0 6
2 64
1003
0
.032
0. C l l
0 .021
2.7
0.14
9 7
0.01
267
100 4
0
. 023
0. C2 3
0.000
2.6
0.04
74
-0.08
2 68
1 005
0
.0 15
0.0 1 l
0.004
2.7
0.0 3
100
-0.12
2 70
1 OOo
0
.032
0.023
0.009
2.8
0.03
1 37
-0.05
264
100 7
0
.020
0.02 0
0.000
3. 1
0.05
1 G 7
-0.07
267
l 008
0
.022
0.015
0.007
3.5
0.06
84
-0.05
2 64
1009
0
.022
0. Cl 5
0.00 7
2.7
0.16
1 1 1
0.23
260
l 0 l 0
0
.022
C 0 1 3
0.009
2.4
0.04
66
0.09
2 74
10 11
0
. 023
0.01b
0.0 0 f
2.1
0.05
63
0.07
276
10 12 ,
0
. 020
0.015
0. 005
2.8
C .05
79
0.11
283
10 13
0
.024
o.oia
0.006
2.0
0. 04
99
0.05
2 70
10 14
0
.01 8
0.008
0.010
2.2
0.06
1 GO
-0.07
262
10 15
c
.02 7
0.020
0.007
2 7
0. 06
120
-0.0 1
2 70
10 16
0
.02 0
0.000
0.0 2 G
2.2
0.04
62
-0.08
269
1 01 7
0
. 025
0.025
0.000
3 .4
0.06
90
-0.12
269
10 18
0
.020
0.011
0. 009
2.9
0. 1 l
97
-0.00
2 62
1019
0
.022
0.017
0.0 0 5
3.1 .
0.12
1 1 5
-C 02
2 62
10 20
0
. 025
0.015
0.010
4 .9
0 1 6
1 2 1
-0.14
261


Table 27. (Continued)
Parameter
DTOC
DOP
DTOP
DNH3
DTURB
One Variable Model
R
Multiple Variable Model R^ Unexplained
Std. Dev.
-0.07+1.9(0.69)FOP
0.19
-11.-0.000015(0.0000023)AREA
+0.25(0.033)WIDTH+0.75(0.31)DEPTH
-0.018(0.0079)BULK+0.17(0.043)FTC
+3.4(0.48)FOP-1.4(0.29)DEPTH CUMTIDE
-0.23(0.045)DEVEL TIDE+0.16(0.027)
DEVEL CUMTIDE
0.82
1.20
None
0.018-0.00000006(0.00000002)AREA
-0.0092(0.0025)SILL-0.32(0.15)FTOP
-0.0027(0.0010)FTURB+0.023(0.0070)FTOC FTOP
0.39
0.031
0.049-0.00014(0.0000031)
TURB COLOR
0.39
-0.011-0.00000002(0.00000001)AREA
-0.0035(0.0010)SILL-0.016(0.0021)CUMTIDE
+0.00083(0.000014)FTC-0.0037(0.0013)FOP
+0.20(0.026)FTOP-0.000019TURB COLOR
0.88
0.0041
-0.04240.00010(0..000043)
SUN
0.14
-0.0075+0.00015(0.000047)SUN+0.0024(0.0020)
AGE-0.14(0.045)FOP-O.018(0.0070)FTURB
-0.00057(0.00019)FCOLOR-O.00073(0.00027)
DEVEL TIDE+0.026(0.010)FTOC* FTOP
+1.2(0.41)FOP *FNH3+0.00011(0.000040)
TURB COLOR
0.52
0.032
-1.3+0.41(0.077)FTURB
0.45
-6.1-0.035(0.016)WIDTH-0.037().011)DEVEL
-1.5(0.35)CURBS+1.2(0.28)SEWERS
+0.12(0.048)MINRES-17.(3.0)FTOP+O.56(0.046)
FTURB-0.012(0.0060)DEPTH AGE
+0.0026(0.00058)DEVEL AGE+0.38(0.17)DAYL
0.90
0.40
-145-


-233-
bS
MNTH
DAY
Y BAR
STATION
T I Mb
Z1
D 1
Z2
D02
771
7
15
76
AP3
730
0
5.08
1 .0
5.03
772
7
15
7b
AP3
73 0
0
5. 40
1.0
5.40
773
7
1 4
76
AP3
l 90 0
0
8.16
t .0
8.25
774
7
14
76
A P 3
1 900
0
a.2
i 0
7.17
7 7b
7
l 5
7 b
AP 3
1 900
0
8.24
1.0
7.90
77b
7
15
76
AP3
1900
0
8.09
l .0
7 .80
777
7
31
76
Gb 1
l 930
0
8. 26
l 0
9.05
778
7
31
7o
082
1 93 0
0
7.68
1.0
7.71
779
7
31
76
Gb3
1 930
0
8.05
1.0
7.60
780
, 7
3 1
76
ou 3
1930
0
7. 59
1.0
7.42
781
8
l
76
Gb 1
63 0
0
7. 28
0.5
7.13
762
6
1
7
Gd 1
1900
0
7.90
0.5
7.74
7 8b
8
1
76
G 2
63 0
0
6. 78
1.0
6.55
7 64
8
1
76
Gb 2
190 0
0
6.82
0.5
6.69
785
8
1
76
Gb 3
63 0
0
6 82
1.0
7.08
788
8
1
76
G63
630
0
6 78
0. 5
6. 16
78 7
8
1
76
G b 3
1 900
0
7.73
1 .0
7.52
788
8
1
76
Gb 3
1 900
0
7.40
0. 5
7.22
789
8
1 9
76
KC1
800
0
4.45
1.0
4.84
790
8
1 8
76
KC 1
l 900
0
6.05
1.0
6.00
79 l
8
19
7 6
KC i
1900
0
5 03
1.0
5.02
792
8
1 9
76
KC 2
800
0
5.02
1.0
5.18
7 93
8
1 8
76
KC 2
1 900
0
u 01
1 0
5.88
7 94
8
1 9
76
KC 2
1900
0
5. Ib
l 0
5.28
79b
8
1 9
76
KC 3
800
0
5.07
1.0
5.26
796
8
18
76
KC 3
l 900
0
6. 09
1.0
b 1 0
79 7
8
1 9
76
KC 3
1 900
0
5.32
1.0
5.21
798
1 0
26
7b
IxM 1
745
0
b 1 6
2 .0
5.77
7 9 9
l 0
27
76
IMM 1
74 5
0
5. 0 l
l 0
3 66
800
i 0
26
76
NM 1
1 81 5
0
6.33
1 .0
5.65
BS
Z 3
DO 3
4
UU4
5
D5
DUO
DU7 Z6
77 1
1.5
3. 66






772
2.0
b 3 8
2.5



773
1 .5
6 .6 7






774
2. 0
6. 7 7
2. 5






77b
1.5
6.28




*


7 7b
2.0
8.0 7
2.5






777








778
1.5
7.40







779
2.0
6.48






780









781
l .0
7.80







782
1.0
6. 97






783
l 5
o. 35







784
1.0
6.93



9



785
2. 0
6. 93






786
1 .0
6 b5







787
2.0
b 96







788
1 .0
7.44






789








790
2.0
6.00
3.0

3.5
5.5 2



79 l
2.0
4.92
3. 0

3.5
4.61


7 92




.



793
2. 0
5. 72
3.0

4.0
5.76



794
2.0
5.17
3.0

4. 0
4.0 1



795









796
2.0
6.09
3.0






797
2.0
5.21
3.0

1.0




79b
3.0
0.00
3.0

4.0
0.00
0
0

799
2.0
1.80
3.0

4.0
C. 0 0
0
0
5
800
2.0
0.10
3.0

4. 0
0.00
0
0
5


-194-
5. Comparisons between four pairs of similar canals (pairs served as
replicate observations) in 1975 revealed that canal community
metabolism was significantly different between canal locations,
along the lengths of the canals, and from season to season; the
effects of the three factors depended on the values of the other
two. No significant differences in the community production:respir
ation ratios were detected between seasons, between locations, or
within the canals.
6. Plankton metabolism patterns differed from those of the total com
munity for the 1975 data. Planktonic metabolism, on a square meter
basis, was significantly affected by the season of the year and the
canal location but not by the distance,along the canals. Surface
primary production, however, was affected by distance along the
canals. Planktonic production¡respiration ratios did not differ
significantly from location to location but.did differ with the
seasons and the distances.along the canals.
7. Interactions between Florida residential canals and their adjacent
estuaries vary from a substantial retention to a substantial export
of materials by canals. Most frequently there was little or no
net-exchange of carbon (total mass and total organic), phosphorus
(total mass and total organic), ammonia, turbidity, and color
between the canals and estuaries.
8. Average-dissolved oxygen concentrations recorded in the canals had
a mean value of 5.58 mg/1, with a range of 1.78 to 9.07. Most of
the canals had average-dissolved oxygen concentrations of 4 mg/1 or
greater. Minimum-oxygen values recorded in the canals ranged from
0.01 to 7.13 mg/1, with a mean value of 2.05. Seventy percent of


-49-
Table 2.
MINRES
CUMTIDE
TIDE
DAYL
(Continued)
Minimum residence time of canal water (days, MDEPTH/CUMTIDE)
Cumulated tidal amplitude in 24 hr period (meters)
Maximum tidal amplitude in 24 hr period (meters)
Hours of daylight on sampling day
SUN
Solar insolation (langleys/day)


-3-
varying densities of canal developments along Florida's coastline can
be seen in the sampling-site figures (Site Description).
A complete inventory of the number or acreage of Florida canal
developments has not been made. However, some reported figures will
illustrate the extent, of this type of activity. Chesher (1974) estimated
that there were about 321 canals in the Florida Keys. Marshall (1968)
believes that 24000 ha or about 7 percent of Florida's estuarine habi
tat less than 2 m deep has been filled by coastal developers. Castanza
and Brown (1975) found that 5,600 ha of mangroves (2.3 percent) in
south Florida (below Lake Okeechobee) have been developed since 1900.
Several classification schemes have been proposed to categorize or
distinguish the various types of dredged canals (or lagoons). Polis
(1974) distinguishes between dead-end canals and open-ended canals.
Within these two major categories, Polis classifies canals as "bay-fill"
or "upland" types; the former are created in shallow estuarine areas,
and the,latter, in upland areas. The presence of a sill at the canal
entrance is also thought by Polis to be a distinguishing feature.
Lindall and Trent (1975) classify canals as "bayfill, inland, and
intertidal"; the mean-low and mean-high tide marks separate the three
types of dredged areas. The Florida Department of Environmental
Regulation describes the extent of canal branching as first-order
canals, second-order canals, etc.
The canals examined during this study were mostly dead-ended
(exceptions are identified in Site Description section) and upland
(intertidal and inland).
This study was designed to increase the data base and the under
standing of the role and behavior of Florida residential canals in the




Table 27. One variable and multiple variable models for 20 dependent response variables (metabolism,
exchange, water quality). Nomenclature and units as in Table 2. Standard errors of
regression coefficients are in parentheses.
Parameter One Variable Model
R
Multiple Variable Model
_2 Unexplained
Std. Dev.
TGPP -1.3+0.70(.20)AGE 0.27 -21.+7.3(1.9)SILL+0.052(0.021)DEVEL 0.74 3.77
+0.45(0.13)FTC-1.6(0.44)DEPTH* SILL
+12.(2.2)DEPTH TIDE-5.8(1.2)DEPTH CUMTIDE
+0.0062(0.0014)TURB COLOR
62.+0.42(0.082)WIDTH+4.5(1.5)SILL 0.87 2.63
-0.056(0.024)BULK+260.(55)FT0P-52.(ll.)FNH3
-1.1(0.31)DEPTH *SILL+0.0054(0.00084)DEVEL AGE
-10. (2.5)FT0C FTOP+0.0070(0.001DTURB COLOR
-5.3(1.1)DAYL
-15.+0.011(0.0033)SUN-0.000016(0.0000050)AREA 0.78 2.44
+3.6(1.1)SEWERS+0.32(0.062)FTC
+9.4(2.8)FOP+0.009 7(0.013)FCOLOR
+0.089(0.015)DEVEL TIDE-2.1(1.0)FTOC *FT0P
-110.(49.)FOP*FNH3
PRM2 1.9+0.79(0.23)DEPTH* TIDE 0.26 -9.8+0.0092(0.0016)SUN-1.4(0.61)DEPTH 0.83 0.84
-0.023(0.0067)BULK+2.7(0.55)SEWERS
+0.53(0.18)MINRES-0.31(0.046)FTOC+0.28(0.034)FTC
+2.3(0.51)DEPTH* TIDE+0.0011(0.00027)DEVEL* AGE
+0.0014(0.00033)TURB COLOR
TR -0.63+0.63(.19)AGE 0.25
PGPPM2 2.4+0.080(0.020)DEVEL*TIDE 0.33
PGPPM3 -2.4+12.(2.2)TIDE 0.47 -12.+7.4(1.4)SILL-24.(6.9)TIDE 0.83 1.89
+0.14(0.069)FT0C+0.35(0.075)FTC+0.46(0.20)FTURB
-2.7(0.51)DEPTH SILL+7.4(1.6)DEPTH TIDE
+0.051(0.01DDEVEL CUMTIDE
-0.0061(0.0030)DEVEL MINRES
-143-


Observations
-76-
a. Average ebb concentration of organic C.
1.0 4.0 7.0 10 13 16 19 22 25 28 31 40
43
mg/1
3
N = 71 Mean = 15.5 Std. Dev. =8.3 Range 1.0 to 43.2
b. Net change (flood-ebb) of organic C.
15
10
5
0
nig/1
3.6
N =69 Mean = +0.2 Std. Dev. = 2.0 Range -5.9 to +10.0
Figure 23. Frequency distributions and descriptive statistics for
(a) weighted-average ebb total organic carbon concentrations
(mg/1), and (b) the net changes from average flood con
centrations.


LIST OF TABLES
Table Page
1. Canal and sampling day physical characteristics 19
2. Nomenclature for variables 47
3. Metabolism results averaged by canal for each sampling
day 51
4. Results of the analyses of variance for the total com
munity and planktonic metabolism data (1975) 61
5. Community and plankton gross primary production mean
values for the 1975 data. 64
6. Metabolism results for three consecutive days of
sampling on one canal (North Miami site) 66
7. Canal-estuary exchange results for the nutrient and
water quality parameters. . 69
8. Regression coefficients for the change in nutrient con
centrations versus time of day 85
9. Mean values for 1975 net-exchange data 88
10. Descriptive statistics and analyses of variance results
for 1975 net-exchange data 90
11. Nutrient/water quality exchange results for three
consecutive days at the North Miami site . 92
12. Water quality characteristics for all canal observations. 95
13. Principal components of the combined data (44 variables). 103
14. Principal components and correlation matrix for the
metabolism data 105
15. Principal components and correlation matrix for the
net nutrient exchange data 108
16. Principal components and correlation matrix for the
water quality data 109
vi


-60-
in Table 3 for the eight canals and four seasons. The individual
station results are presented in the Appendix. The results of the
analyses of variance on the data are shown in Table 4.
The analyses indicate that there are significant differences in
the levels of community production and respiration with the season of
the year, with the location of the canal, and with distance up a canal.
This three way interaction indicates tht the spatial and temporal
distribution of metabolic levels in these residential canals is a
non-additive function of the distance, location and season factors.
The seasonal changes have different effects on community metabolism
depending on the canal location and on the distance up the canal. The
lack of simple trends for any of the three factors can be illustrated
by the fact that the highest community metabolism levels occurred
during September for all locations except Punta Gorda, where the level
was the lowest recorded for the year.
The sources of variation listed i'n Table 4 account for 88 and 87
2
percent (R value) of the community production and respiration vari
ability, respectively. The remaining 12 percent of the variability
is composed of the error involved with the determinations of the
metabolic levels and with the difference in metabolism levels of the
individual canals within the pairs, which were treated as replicate
observations; the latter source of residual variance could be a result
of factors such as plankton patchiness, water circulation patterns, and
nutrient inputs. This small amount of unexplained variability indicates
that the individual canals within the pairs of canals do not differ
appreciably in the patterns and levels of metabolic activity, relative
to the total variability for all locations, seasons, and distances.


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MONTH DAY YEAR STATIUN TIME 2t DO 1 22


-191-
which coastal fisheries may also beneift. For example, several authors
have suggested that fish find shelter in deep canals during cold
periods.
Whether the detrimental impacts of canals and canal dredging,
outlined in the literature review, outweigh the possible beneficial
aspects of residential canal developments (including the socioeconomic
considerations not mentioned in this discussion) should be assessed on
a case by case basis. Canal systems are complex and variable. Coastal
zone planners should assess the behavior and conditions of existing
canals and the possible role of future canal systems before deciding
whether the existing canal systems need modification or management,
and whether any further canal construction is included in their plans.
This study substantially increases the data base for the conditions
within residential canals and the exchanges between canals and estuaries
of several materials, and identifies and quantifies the relationships
between these behavioral attributes and basic canal and estuary
characteristics. Future studies should focus on quantifying the total
impact of residential canal construction in the coastal zone and on
the mechanisms associated with factors that were found to have sig
nificant effects on the individual response parameters in this study.
Difficult but necessary tasks are to quantitatively assess the total
impact of canal systems on coastal fisheries, including comparisons
with natural wetland systems, and development of canal system manage
ment policies to maximize the production of coastal fisheries.
An extensive investigation of the role of canal bulkheads in
canal ecosystems, compared to alternative canal-edge designs, would
aid in the development of canal design and management policies.


-74-
a. Average ebb concentration of total C.
mg/1
N = 58 Mean = 38.0 Std. Dev. =8.0 Range 24.1 to 57.9
b. Net change (flood-ebb) of total C.
N = 56 Mean = +0.2 Std. Dev. 2.05 Range -5.4 to +7.5
Figure 21. Frequency distribution and descriptive statistics for
(a) weighted-average ebb total carbon concentration (mg/1),
and (b) the net changes from average flood concentrations.


Table 29. Appearance frequencies of the grouped factor-types in the metabolism, exchange,
and water quality models (grouped).
Metabolism
Exchange
Water Quality
(9 variables)
(7 variables)
(4 variables)
Canal Characteristics
33
21
18
(DEPTH, AREA, DEVEL, etc.)
18 parameters
(0.20)
(0.17)
(0.25)
Tidal Dynamics
12
Q
(TIDE, CUMTIDE)
4
6 parameters
(0.22)
(0.21)
(0.17)
Estuarine Water Quality
29
25
14
(FTOC, FNH3, FCOLOR, etc.)
10 parameters
(0.32)
(0.36)
(0.35)
Sampling Day
£
(SUN, DAYL)
0
2 parameters
(0.33)
(0.21)
(0.38)
Totals 80 (1.07) 58 (0.95) 39 (1.15)
Values in parentheses are the relative-significance frequencies (see text for explanation).
Totals
72
(0.62)
25
(0.60)
68
(1.03)
12
(0.92)
-152-


-100-
of 2.66 mg/1, with a standard deviation of 2.05 mg/1 and a range of
0.00 to 7.13 mg/1. The most frequently observed minimum concentration
was zero (values were rounded to the nearest integer for histogram),
though a second mode at 3 mg/1 is apparent in Figure 29b.
The average Secchi depths recorded in these canals ranged from
0.75 to 2.90 meters, with a mean value of 1.35 meters and a standard
deviation of 0.44 meters (Figure 30). The frequency distribution
shows that most (48 of 60) of these canals had Secchi depths of 1.6
meters or less.
Structure of the Data Principal Components Analyses
The individual metabolic, nutrient exchange, and water quality
parameters, and their distributions among these Florida residential
canals are interesting from a descriptive standpoint and useful for
comparing with other ecosystems. The next step in evaluating the con
ditions and behavior of these canals is to reduce the number of variables
to a more manageable figure, so that elucidating interrelationships
among the various types of data is simplified. The approach used was
to use statistical methods to generate linear combinations of the
individual parameters that lead to adequate descriptions of the data in
fewer but artificial variables, with minimum loss of information.
Principal components analysis is a useful multivariate statistical
technique for initial exploration and elucidation of the structure of
a data set. Only a brief conceptual discussion of the technique will
be presented here. For a more detailed description a multivariate
statistical text should be consulted, such as Morrison (1967) or
Pielou (1969) .


-118-
Table 18. Variables included in the metabolism, nutrient exchange,
water quality, and physical characteristics data sets for
correlation analyses.
Metabolism
Nutrient
Exchange
Water
Quality
Physical
Characteristics
TGPP
DTC
ETC
SUN
TR
DTOC
ETOC
LENGTH
PGPPM2
DOP
ETOP
WIDTH
PRM2
DTOP
EOP
MDEPTH
PGPPM3
DNH3
ENH3
AREA
PPRM3
DTURB
ETURB
VOLUME
TPR
DCOLOR
ECOLOR
SILL
PPR
AVGDO
DEVEL
PDOMIN
MAXDO
AGE
MINDO
BULK
TEMP
CURBS
SECCHI
SEWERS
TIDE
MINRES
CUMTIDE
DAYL
Nomenclature and units as in Table 2


-11-
and general ecological condition of the canals are dependent on the
adjacent water body. It is difficult to obtain healthy canals on a
stressed bay.
Daiber et^ jil. (1975) reported additional benthic invertebrate data
from the Little Bays area of Delaware, in addition to intertidal inver
tebrates and vegetation, and ichthyoplankton results. The numbers of
individuals and species of benthic invertebrates were generally lower
in canal stations than in marsh and bay stations during the summer and
fall. However, the uniqueness of each canal system and its environ
mental conditions was again emphasized. The three habitats were found
to have similar fauna during the winter and spring. Biomass comparisons
between different types of canal shorelines indicated that old bulkheads
have higher standing crops of plants and animals than do bare banks.
The old bulkheads had fewer macrophytic plants, but higher animal biomass
than did the salt marsh environment. The ichthyoplankton data, though
limited, suggested that canals are not as favorable a habitat for larval
fish as is the salt marsh.
The information reported by the University of Miami group
(Carpenter and Van de Kreeke, 1975 and Van de Kreeke and Roessler,
1975a and b) on the Marco Island, Florida development consists of
oxygen data, estimates of production and respiration, and a model to
predict oxygen levels. Their model was developed for the main flow
through arterial channels fifteen fet in depth. The model revealed
that dissolved oxygen concentrations for Marco Island canals are sig
nificantly dependent on the vertical mixing coefficient and the detritus-
supported respiration, and not sensitive to atmospheric transfer,
photosynthesis and respiration. For the dead-end tributary canals,


-26-
Figure 4. Canals and sampling stations at the Pompano Beach site.


-273-
JUS
MONTH
UA Y
YEAR
STAT ION
T I ME
TC
IC
TC
lili
a
1 9
76
KC3
12
30.1
24. 4
5. 7
1112
e
1 9
76
KC3
1 3
31.0
24.8
6.2
1113
e
1 9
76
KC 3
14
28. 1
24. 7
3.4
1114
1 0
2 6
76
NM 1
10
53.4
8.3
45. 1
1115
1 0
26
76
NM 1
1 1
55.2
10.7
44.5
1116
10
26
76
NM 1
1 2
54. 3
13.3
41.0
1117
1 0
2 6
76
NM l
l 8
55.4
12.4
43.0
1116
1 0
26
76
NM 1
1 4
55.5
16.7
38.8
1119
10
26
76
NM 1
1 5
55.2
13.4
41.8
1 1 20
l 0
26
76
NM 1
16
56.4
15.7
40.7
112 1
10
26
76
NM 1
1 7
5 4.3
13.3
41.0
1 1 22
1 0
26
76
NM 1
i a
5b 7
12.4
44.3
1 1 23
1 0
26
76
NM 1
i y
54.3
7.7
4 5.6
1 1 24
1 0
26
7 6
NM 1
20
56.2
11.7
44 .5
1125
1 0
26
76
NM 1
2 l
6 5.2
14.1
40.6
1 1 26
10
2b
76
NM 1
22
56.3
14.4
41 .9
1 1 2 7
10
26
76
NM 1
23
54.9
11.5
43. 4
1 1 2t
10
26
76
NM 1
24
56.4
17.0
39.4
1 1 29
1 0
26
76
NM 1
1
53.0
12. 7
40.3
1 1 30
10
26
76
NM 1
2
55.8
14.2
3 9.6
l 1 31
1 0
26
76
NM 1
3
52.3
11.1
41 .2
1 132
10
26
76
NM 1
4
55. 3
9. 7
45 .6
1 1 33
1 0
26
76
NM 1
5
56.3
15.9
40.4
1134
10
2 6
76
NM 1
6
54.3
12.6
4 1.7
1 1 35
1 0
26
76
NM l
7
5 0.4
9.2
47.2
1 136
l 0
26
76
NM 1
8
55.3
10.9
44.4
1137
10
2 7
76
NM 2
1 0
58.6
14.1
44.5
1 1 3t
1 0
27
76
NM 2
1 2
57.5
14.2
43. 3
1 1 39
10
2 7
76
NM 2
1 3
5 7.4
10.3
47.1
1 1 40
1 0
27
76
NM 2
14
57.6
l 5. 9
41.7
U s
TP
P
TUP
TUR
NH3
CUL U f<
DS
cuno
lili
0.015
0.010
0.00o
2 .0
0.00
2 3
0.20
4 33
1112
0.013
0.002
0.01 1
2.0
0 .0 l
22
C .0 8
4 39
1113
0.011
0.002
0.009
1 8
0. 04
2 3
0.23
439
1114
0.0 72
0.02 0
0.04
3.2
0.06
9b
0.45
2 6b
1115
0. C63
0. 03 9
0.024
2.9
0.05
89
0.45
2 62
1116
0.062
0.040
0 .022
3.0
0.04
7 1
0.45
258
1117
0.068
0.038
0 .0 30
3.5
0.05
87
0.45
2 59
lile
0.0 73
0.043
0.030
5.5
0.04
97
0.00
261
1119
0.067
0.032
0.0 35
3.1
0. 0 1
9 2
-0.43
2 59
112 0
0.065
0.035
0.030
2.6
0.03
82
-0.43
2 58
112 1
0.060
0.03 1
0.029
2.9
0. 0 0
68
-0.43
262
l 1 22
0 .059
0.037
0.022
2 .3
0.00
83
-0.43
2 52
1 1 23
0 06 8
0.028
0.04 0
3 .4
0.00
73
-0.43
2 58
1124
0 066
0.0 32
0.037
4.8
0. 04
82
-0.43
2 58
1125
0.061
0.030
0.051
2 .9
0.02
73
0.38
256
1 1 26
0.059
0.033
0.026
3 .4
0.04
9 1
0.38
2 59
1 127
0.073
0.03b
0.037
3.9
0.02
88
0.38
2 63
11 2e
0.063
0.038
0 .0 25
2.5
0.02
84
0.38
2 56
1 1 29
0.0 62
0.035
0. 027
2.1
0. 03
81
0.38
260
1 l 30
0.061
0.037
0.04
2.5
0.04
79
0.0.0
265
1131
0.057
0.035
0.022
2.1
0.04
84
-0.43
262
1 1 32
0.065
0.040
0.025
2.5
0.02
86
-0.43
257
1 1 33
C. 07 0
0.039
0.0 8 1
4.1
0.03
83
-0.43
2 52
1 1 34
0. 067
0.042
0. 025
5.4
0.06
87
-0.43
2 59
1135
0.067
0.042
0.025
2.8
C. 05
60
-0.43
2 58
1136
0.074
0.04 7
0.02/
2 .0
0.06
93
-0.20
2 58
l 1 37
0.065
0.034
0.021
5.6
0. 05
95
0 .60
2 62
1 1 36
0.066
0.03 4
0.032
4 .0
C .03
93
0 60
264
113 9
0. 076
0.030
0.04o
5.6
0.12
90
0 .40
258
1140
0.068
0. 03 1
0. 057
3.0
0. 02
98
0.40
2 5b


-209-
BS
MONTH
O AY
YtAR
S TAT IN
UfcPTH
TOPP
TR
67
b
l 9
76
Hl 3 >
2


26 8
5
1 9
76
H1 1
0
6.24
1 .74
269
5
1 9
76
H I 1
2


2 70
b
i 9
76
HI 1
0
8.30
J.02
27 1
5
1 9
76
HI 1
0
8.08
2 .58
272
5
1 9
76
HI 1
1


2 73
b
1 9
7o
H I 2
0
8.54
2.92
274
b
1 9
76
H 12
2


7b
5
1 9
76
H2
0
6.30
1.76
27 6
6
1 2
76
6 L1
0
7 .80
7.55
277
6 .
1 2
76
f L 1
1


76
6
12
76
FL2
0
11.90
11.10
279
6
1 2
7 6
FL2
1


80
6
1 2
76
FL3
0
6.14
7.44
26 1
6
1 2
76
FL3
1


2 8
6
l 2
76
FU
0
9.76
12.20
26 3
7
1 4
76
A P 2
0
14.20
14.30
64
7
1 4
76
AP2
1


8b
7
1 4
76
AP2
2


2 d 6
7
1 4
76
AP3
0
8.91
9.24
26 7
7
14
76
AP3
0
11.40
9 .70
286
7
1 4
76
A P3
1


89
7
1 4
76
API
0
19.00
18.50
290
7
l 4
76
AP l
0
22 .20
16.30
29 1
7
l 4
76
API
1


292
7
3 l
76
OBI
0
1 .38
2.50
293
7
3 1
76
OBI
1


294
7
3 l
76
062
0
2.0 5
3. 1 2
95
7
3 1
76
GB2
1
*

296
7
3 l
76
OB3
0
1.80
1 76
BBS
PGPPM2
PR M2
P6PPM3
PPRM3
TPR
PPR
SUN
267


3.96
1.02
m

5 1 5
268
7.0 1
3.92
5.69
2.4 1
3.59
1 .79
51 5
69


1. 12
0.66


5 l 5
70




2.75

5 l 5
7 1
5. 97
1.03
5.5b
1.16
3.13
5.74
5 1 5
72


3.30
0.30


515
273
7.43
2.99
b 1 5
1.96
2.92
2.4 6
5 15
274


1 b
C .53


5 15
275




3.58

51 5
7 6
3.19
3.92
3.2 6
2.17
1.03
0.81
504
2 7 7


1.04
1 .42


504
278
2.91
4 .98
1.77
1.75
1.07
0.58
5 04
279


1.3b
2.07


504
280
4.12
3.48
3. 2b
1 01
0.63
1.18
504
28 l


2.50
1.91


504
62




0.60

504
263
7.71
3. 75
1 U c4
2.86
C .99
2.05
506
28 4


1.74
1.14


506
28b


l .30
0.79


506
266

'


0. 96

5 06
267
3.30
2.95
4.22
2.04
1 78
1.12
506
266


1.19
1.14


506
289




1.03

5 06
2 90
4.00
3.94
3.96
2.40
1.36
1 .02
506
291


1.3b
0.79


506
292
1.20
1.45
1.67
1 o2
0.55
0.83
554
293



0 .26


554
294
0.77
0.74
1.16
1.12
0.66
1 .0 4
554
295


0.16
0.18


54
29 6


.
.
1 .0 2

54


-319-
CRKELATIUN CU EFF 1Cl ENT5 / PRU6 > ik¡
MBER F OBSERVATIONS
UNDER HOI
RHO=0 / NU
CURBS
DTURt
-0.18729
0 .2024
4 6
MI ND
0.17800
0.1319
73
MINRE5
0.17549
0.1348
74
5L WER5
0. 1 6973
0.1482
74
PRM2
0.16411
0.2268
56
ETURB
0.16305
0.2579
50
MDEP T H
0.16209
0. 16 77
74
DTUC
0.16171
0.1843
69
DCULR
0.1555 5
0.3253
42
VLUME
0. 14 19 1
0.2299
74
D TC
0.13663
0. 3153
5 c
OOP
-0.10478
0.3220
5o
BULK
0. 1 3 373
0 .2807
6 7
F NH3
0.12859
0.2852
71
ENH3
0.12889
0.2882
7 1
CUMTIDE
-0.11827
0.328 l
7 9
TEMP
-0. 11504
0.3325
73
PPR
0.09256
0.4973
56
DAY
0. 08 796
0.4560
74
ETUP
-0.08428
0.5446
54
D1C
-0 .0 7838
05658
56
d r up
0.06901
0.6133
86
SLCCH I
-0.0673 1
0.6093
60
EQP
-0.06101
0.6991
58
ETC
-0 .0 596 9
0.6b 63
56
AREA
0.05576
0.6370
74
F TOP
- 0.05422
0.6970
54
DCUND
0.05162
0.8107
24
DTP
- 0.04589
0.7120
60
FTP
- 0.03735
0.757 1
71
LE NOT El
0.03356
0.7765
79
E TP
- C. 03 1 79
0.7924
7 1
FTC
-0.02824
0.8333
56
P GP P M 3
0. 02191
0.8726
5o
FTUR
0.01 1 80
0.9352
50
TI DE
- 0.0 0 7 93
0. 946 5
74
TPR
0.006 7 9
C.961 1
54
PPRM3
0.006 l 0
0.964 4
56
PD UM IN
0.0 02 12
0.9876
54
DA YL
0.002 03
C9o 68
74
MA XDU
0.00049
0 .9967
73
UNH3
-0.00000
l .0000
6 9
SEVERS
SEWERS
1.00000
0.0000
74
WIDTH
0 .6460 7
0.000.1
79
E I C
-0.5 936 7
0.0001
58
F I C
0.56927
0. 0001
58
EGP
0.46508
0.0002
5 8
FTP
0.43765
0 .000l
7 l
DC OLOR
-0.41672
0.0060
42
E TP
0.41913
0.0003
71
VLUME
0.4104 C
0.0003
79
ARLA
0. 391 10
0.00Go
7 4
LENGTH
0.38706
0. 000 7
74
BULK
0.36346
0.00 14
67
SECCHI
0.36475
C .0042
60
AGE
0.363 8 8
0.0018
71
YEAR
0 .35898
0.0017
74
F UP
0 .31826
0.0149
58
E UC
0.31019
0.0085
71
FT C
C 3 0 4 0 7
0.G099
71
TPR
0.29524
0.0802
54
ETC
-0.29374
0 .0 252
58
FTC
-0.293 1 1
0.025o
58
FCUCR
-0.28619
0 .0661
42
DEV EL
0.24298
0.0412
7 1
FTOP
0.24115
0.0790
5 4
DP
0 2 2 b 0 0
G. 094C
5 6
Mi DEPTH
0.22082
0. 0587
7 4
D I C
-0.21388
0.1135
56
ECULUR
0.20652
0l89d
42
E T UP
0.20 522
0.136
54
SUR
0 .20469
0. 1 30 2
56
DTP
0. 19 6 13
0 106 9
66
TUPP
0.17645
0.1933
56
AVuD
0.17583
0. 1367
73
CU R bS
0.1 6973
0.1482
74
T IDE
0. 16371
0.1634
74
CUM! I DE
- 0. 150 59
0.2003
74
T EMP
-0.14821
0.2108
7 3
PRM2
0. 1 4 751
0.2780
5o
LTC
C 14 0 29
0.3024
56
PGPPM 2
13289
0.3269
56
DNH3
0. 12642
0.3006
69
MAXDU
0.12499
0.292l
73


-316-
CURR ELAT I UN COEFFICIENTS / PROU > |R|
MUER OF OBSERVATIONS
UNDER HO:
RHO=0 / NU
SILL
WIDTH
0.21536
0.0733
70
DT C
.20951
0. 1212
5 6
M IND U
-0.20669
0.0b84
69
CURBS
0.20310
0. 091 7
70
TcAR
0.19747
0. 1013
70
DCUND
0.16867
0.4308
24
LENG th
-0.16356
0.1761
70
ARLA
-0.16129
0.1822
70
FNH3
-0. 16092
0.1933
67
LNHJ
-0. 16092
0.1933
67
F T UP
0.1 5890
0.2511
54
EP
-0.13924
0.2972
58
E 1C
-0.12905
0.3343
58
MON TH
0.123l9
0.3096
70
LCLR
-0.12226
0.4406
42
PGPPM3
0.11173
0.4123
56
ppk
-0.10499
0.4412
56
F 1C
-0.1 04 1 7
0.4364
58
U 1C
0.09997
0. 4 63b
56
L TURB
0 .09 60 6
0.5070
50
TPR
-0.0958 1
0.4907
54
F TURO
0.09 199
0.52 52
50
FCCILR
-0.0906 4
0.668 1
42
SL WLKo
-0.0 889 5
0 46 36
70
r- T P
-0.0 84 09
0.4987
67
U C U L G ft
0. 05140
0.o 083
42
ET P
-0.07954
0.5223
67
VULUME
- C 065 7o
0.58 86
70
SLCCHI
- 0.05589
0.6715
60
DT C
0.05261
0.6773
6 5
DT P
-0. 04569
0.7166
64
UAVL
-0.0 4 1 76
0. 7314
70
L T UP
G .0 38 72
0.7810
54
D T UR B
0.03487
0.8140
48
DEVLL
0 .03235
C. 7904
70
T I DL
-0.03061
0.8014
70
PDUMlN
0.02696
0.8466
54
MAXDU
0.023 1 6
0.8500
6 9
ONHJ
0.01790
0.8675
65
CUMTIDL
-0.01619
0.8942
70
T EMP
-C.01540
0.9001
69
F UP
0.00244
0.9855
58
OEVEL
DLVEL
l .00000
0.0000
71
BULK
0.58163
0.000 1
64
MAXOU
0.45364
0.0001
70
aGL
0.4-1646
0.0004
68
PGPPP2
0. 4 06 79
0.0019
56
ENH3
0.38548
0.0012
68
FNH3
0.3 854 8
0.0012
68
POPPM3
0.38440
0.0034
56
T IDE
0.38406
0.0009
7 1
PPKM3
0.33740
0.0110
5 6
PRM2
0.33091
0.0127
56
T GPP
C.295 14
0.02 72
56
DTUR
0.28787
0.0473
48
PD UM I N
0 .2 7505
0.0441
54
TR
0.27497
0.04 03
56
WIDTH
0.26733
0.0242
71
S L V L R 3
0.242 98
0 .0412
71
F UP
0.2246 6
0.0897
58
FTP
0. 22393
0.0664
68
LTP
C.22363
0.0665
68
CCUN
0.2212 7
0.2988
24
F IC
-0.21607
0.1033
58
M DEPTH
0.21083
0.0776
7 1
HC
-0.2 0775
O.I17o
56
CUM TIDE
0.20497
0. 0864
71
SUN
0.20482
0.1300
56
CURBS
C .20 4 79
0.0867
7 1
ETUR6
-0.20417
0.1550
50
ETUC
0 .2033 t
0.0962
68
LUP
0.19966
0.1329
58
AVGDu
0 18 103
0. I 33 7
70
f rue
0.1 60 70
0.1403
68
tCuRU
-0.16309
0.4464
24
PPR
0. 16038
0.2377
56
TEMP
-0.15606
0.1970
70
Y EAR
0.15362
0.2009
7 l
FCULUR
-0.15182
0.3372
42
LCOLOR
-0.15003
0343 5
4
f r c
-0.13434
0. 31 47
58
f CUNQ
-0.13289
0. 5359
24
DTC
-0.12909
0.3430
51>
AREA
0 1 1520
0.33 87
7 1


-158-
primary production ranged from 16 to 100 percent (see Figure 20).
Values of 50 percent or less were observed most frequently. The mean
value of the plankton-domination data (60 percent) suggests that the
"average" canal is a slightly plankton-dominated system.
The principal component analysis of the metabolism data showed that
80 percent of the variability in metabolic patterns between these canals
can be attributed to three different aspects of canal metabolism. The
magnitudes of primary production and respiration were the character
istics that best differentiated the metabolic patterns of these canals.
The degree of autotrophy, particularly that associated with the canal
plankton, was the second most distinguishing feature. The third factor
was also associated with the atotrophic nature of the canals; but with
that of the non-plankton component of the communities, instead of the
plankton. A wide range of metabolic levels, extent of plankton
domination, and net production was found within the canals.
The canonical correlation analysis between the metabolism data set
and the nutrient exchange, canal water quality, and canal physical
characteristics data sets produced both expected and unexpected results.
The most surprising result was that the overall metabolic patterns of
the canals were independent of the net nutrient exchange patterns. It
would have been reasonable to expect that net-producing canal communi
ties would tend to import inorganic materials from the adjacent
estuaries, transform the inorganics to organic metter, and then export
the net production back to the estuaries. If this were the case, then
the metabolism and exchange data sets would have been correlated. The
lack of correlation indicates that the net exchanges between canals
and estuaries are generally not affected by the metabolism within the
canals.


Table 1
Canal and sampling day physical characteristics.
Units: LENGTH, WIDTH, MDEPTH, SILL, TIDE, CUMTIDE meters
AREA square meters
VOLUME cubic meters
DEVEL, AGE percent
AGE YEARS
CURBS, SEWERS 1 present, 0 absent
MINRES (Minimum residence time) days
SUN langleys/day
DAYL (Daylength) hours
See Table 2 for more complete identification of the parameters.


-41-
at each sampling interval were used to compute the community metabolism.
Oxygen stratification generally was present. Oxygen diffusion across
the air-water interface was neglected, since the mean values for the
water column and not the surface values were used in the computations.
Ignoring diffusion leads to Underestimates of metabolism, but was not
felt to be a serious source of error due to the generally quiescent
nature of the canal water.
After the first two sampling trips, oxygen profiles were taken at
every station for a sunrise-sunset-sunrise or a sunset-sunrise-sunset
sequence. The resulting three mean values for the water columns were
used to comput the daytime net production rates and the nighttime
respiration rates. The total community gross primary production and
2
total respiration were estimated on an areal (m ) basis from the two
rates, allowing for daylength on the sampling day and for water depth.
The planktonic contribution to the total community oxygen metabolism
was determined by light-dark bottle 24 hour In situ incubations at one
or more stations per canal. Pairs of light and dark bottles were sus
pended at one meter intervals throughout the water column. The changes
in dissolved oxygen levels were determined by Winkler titrations. To
2
obtain metabolism estimates on an areal (m ) basis, the values at the
discrete depths were integrated over the depth of the water column.
The production:respiration ratios for the total community and
plankton component were calculated from the respective 24 hour gross
2
primary production and respiration values (m ). The extent of plankton
dominance of the community primary production was calculated as the
ratio of the plankton GPP to the community gross primary production
values (canal means). The amount of solar insolation on the sampling


-183-
(5.6 mg/1) does not violate the water quality standard (4 mg/1), but the
minimum oxygen value (2.7 mg/1), which is most likely near.the canal
bottom at sunrise, does violate the water quality standard. The oxygen
levels suggest that the "average" canal may be a stressful environment
for some estuarine organisms but within the tolerance limits of others.
Design and Management Implications
If the conditions and behavior of this "average" canal are deemed
unsatisfactory, then, for design or management purposes, the regression
equations suggest what the resultant effects of changing the canal
systems' physical attributes might be. It has already been mentioned
that little can be done about the effects of the local tidal dynamics,
the estuarine water quality (in the absence of good regional management
practices), and the sampling day characteristics. Whether these un
controllable factors dominate canal behavior and conditions to such a
degree that any canal design changes will not have a meaningful effect,
will depend on the particular estuary. Substitution of the background
values into the regression equations (Table 27) will give the baseline
conditions for a canal on a particular estuary. Then, by substituting
various combinations of canal physical attributes (using units of
Table 2) into the expressions, the possible influences of canal design
on canal behavior and conditions could be assessed.
The mixing conditions within a canal have a major influence on
canal conditions. Mixing depends on the average water current velocity
in the canal. Average current velocity depends on the canal water
surface area, canal width, canal depth, and the cumulated tidal ampli
tude. Circulation patterns in canals are dependent on current


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-311-
CURRELATI UN CEFF1CI ENTS / PRUB > |kj UNDER H0:RHG=0 / NU
MUER OF OBSERVATIONS
DAYL
D I C
0.03989
C.7703
be
D TOC
0.03704
0.7626
69
SECCH1
- 0.03177
0.8096
6 0
ftlDT H
0.02966
0.8006
74
E IC
-0.02123
0.6743
58
PSPPM2
-0.01 81 8
0.8942
56
FIC
-0.01381
0.9180
58
VOLUME
-0.00850
0.9427
74
fc CULO R
-0.0071 7
0.9641
42
FT P
0.00671
0.955 7
7 1
FCULUR
00 C 4 55
0. 9/72
42
M AX DU
0.00301
0. 9 7 9b
73
ETP
-0 .0022 1
0.9854
7 1
CURBS
0 .00203
0.9863
74
PDUMIN
PDJM IN
1 .00000
0.0000
54
PGPPM2
0.530 l 4
0.000 1
54
T R
-0.39160
0.0034
84
PGPPM3
0.37316
0.0054
54
PPR
0.36748
0.0063
54
CUMT I DE
C.36134
0.0 073.
54
TIDE
0.354 3 2
0.0035
54
E TOC
0 .352 75
0.0111
5 1
FTOC
0.33380
0.0167
5 1
EC END
-0.32203
0.1249
24
T GPP
-C.29911
0.0680
54
F CO NO
-0. 29903
0.1558
24
DAY
0.29464
0.0306
54
PRM 2
0.2 84 5 7
0.0370
54
FCULUR
-0.28435
0 .0836
38
ECULR
-0.2834 3
0.084 6
3 8
DEV EL
C. 2750 5
0.044 l
54
3 P K M 3
0.26915
0.0491
54
TEMP
-0.26402
0. 05 3 7
54
MUN TH
-0.26375
0.0 540
54
ETC
0.24148
0.0b78
51
DAYL
0.22 3 64
0.0963
54
TPR
0.21942
0.1109
54
SUN
0.21901
0 .11 lo
54
ALE
0.20271
0.141b
54
FTC
0.19737
0.1651
51
M I N R t S
-0. 1 02 06
0 1876
54
W I D T H
-0.16445
0 .234 7
54
BULK
0. 16313
0 .2386
54
DCOND
0.15110
C 4 8 0 9
24
EUP
0.13663
0.3313
5 l
F 1C
-0.1 3 1 30
0. 3584
51
DTP
C 1 2037
0.4100
. 49
M I ND
0.11822
0.3945
54
EIC
-0.11720
0.4128
51
E TP
-0.11589
0.4180
5 1
F TP
-0.10910
0.4460
5 1
AREA
0 .10^0 5
0.4540
54
D OP
0.09971
0.4955
49
DT C
-C.0988C
C.4994
4 9
VULUME
0.08902
0.5221
54
LENGTH
0.08889
0.5227
54
DTUKB
0.08239
0.5949
44
DT GC
-0.08014
0.884 1
4 9
FOP
0.08004
0.5 76 6
51
YEAk
-C.07353
0.5 9 72
54
MDEP TH
0.07133
0. 6083
54
0 NH 3
-C.0 7l31
0.6 26 3
49
DCULOR
-0 .06764
0.6866
38
D I C
-0.04827
0.7419
49
SEWER 5
-0.04338
0.7555
54
ET UP
0.04130
0.7 6 25
47
AVijD
0.04124
0.7672
54
DT OP
C 0 3 l 1 5
0.83 1 7
49
' CTURU
-0.02837
0.6515
4 6
S ILL
0 02 o 9 5
0.8466
54
FNH3
0.02179
0.8794
51
LNH3
0.02179
0.8 7 9 4
5 1
SECoHI
0. 01 306
0.9256
54
FT OP
0.0 0498
0. 9735
47
F TURB
0.00445
0. 97 66
46
CURBS
C.00212
0.9878
54
MAXU
-0 .00130
0.992s
54
LENGTH


LIST OF TABLES
(Continued)
Table Page
17. Principal components and correlation matrix for the
canal/sampling day characteristics ..... Ill
18. Data set variables used in correlation analyses 118
19. Canonical correlation analysis of the metabolism and
nutrient exchange data sets 119
20. Canonical correlation analysis of the metabolism and
water quality data sets 121
21. Canonical correlation analysis of the metabolism and
canal/sampling day data sets 124
22. Canonical correlation analysis of the exchange and
water quality data sets. 127
23. Canonical correlation analysis of the exchange and
canal/sampling day characteristics 128
24. Canonical correlation analysis of the water quality and
canal/sampling day characteristics day sets 131
25. Summary table for canonical correlation results 139
26. Dependent and independent variables used in the stepwise
regression analyses. 142
27. Descriptive models for 20 dependent response parameters. .143
28. Significant-factor frequencies for the metabolism,
exchange, and water quality models 149
29. Appearance frequencies of the grouped factor-types in
the metabolism, exchange, and water quality models
(grouped) 152
30. Gross primary production levels for different aquatic
systems !. 157
31. Significant factor effects on canal metabolic parameters 161
32. Significant factor effects on canal water quality
parameters 169
33. Organic carbon net-exchanges for several coastal systems 174
vii


-102-
a high degree of structure or with recurring patterns between the
variables for all the observations, will have most of the total vari
ability of the data set included in the first few principal components
It is this feature that makes the analysis a useful exploratory tech
nique when no £ priori pattern for the variables has, been established.
Combined Data '
Elucidation of the interrelationships between the canal attributes
determined during this study logically begins with the entire data set.
If these residential canals are basically simple systems with simple
recurring patterns between dynamic behavior (metabolism and nutrient
exchange), water quality, physical characteristics, and driving forces,
then a few simple linear combinations of the parameters should account
for most of the variability observed. Therefore, to evaluate the
amoung of structure in the data, a principal components analysis was
performed on the combined metabolism, exchange, water quality, and
physical characteristics data.
Forty-four variables from Tables 1, 3, 7, and 10 were included
in the combined data set for the principal components analysis. Thirty-
four canal observations had values for each variable and were included
in the analysis. Table 13 shows the first four eigenvectors and their
associated eignevalues with the portion and the cumulated portion of
the total variability explained by each. The first principal component
only accounts for 19 percent of the total variance and suggests that
canal behavior and characteristics do not have simple patterns. It
can be seen from the coefficients in the first principal component


-172-
The net-exchange results demonstrate that canals exhibit different
types of interactive behaviors with the adjacent estuaries. Some
canals are sources for some materials, whereas others are sinks for
the same materials. Most frequently there was little or no composi
tional change in the estuarine water that exchanged with the canal
water. Even though there were considerable variabilities in the ex
change responses, some interesting inferences, though perhaps mis
leading, can be drawn from an evaluation of the mean exchange values
for the carbon and phosphorus forms.
The sum of the mean net-exchanges of organic and inorganic forms
of carbon and phosphorus are in close agreement with the net total-mass
exchanges, even though the sample sizes were different (E.P.A. data for
TOC and TP are included). The mean values for total carbon and total
phosphorus mass transport indicate that a sink type of activity was
occurring for these elements. The mean net-movement of organic carbon
and organic phosphorus are not in agreement. If the mean values
represent an "average" canal, then organic carbon seems to be removed
from the estuarine water, whereas organic phosphorus seems to be added
to the estuarine water. The direction of inorganic carbon and inorganic
phosphate movements are likewise reversed. The "average" canal is a
sink for ortho-phosphate but a source for inorganic carbon.
An explanation for these results could be that organic detritus,
low in phosphorus, enters this "average" canal and tends to settle out .
of the water column. The phytoplankton in the water column, being net
producers of organic matter, could be transforming the inorganic
phosphorus entering from the estuary into organic phosphorus, which is
then exported back to the estuary. The increase in planktonic organic


-8-
relative to natural areas in North Carolina.
The work of Daiber at _al. (1972, 1973) in Delaware provided at that
time the most comprehensive study of biological, chemical and physical
aspects of any canal system. Conditions were generally poorer in the
canals than in the adjacent natural salt marsh embayments, but the
uniqueness of each canal system was recognized. A dye flushing study
of one 800-meter canal showed that the initial surface concentration at
the dead-end was reduced by only 56 percent after five days, and that
the bottom water exchanged much more slowly.
Since Polis' review, several other studies have appeared. Chesher
(1974) reported biological and hydrological data on 50 canals in the
Florida Keys. Paulson et al. (1974, 1975) studied four canal systems
along the Gulf of Mexico. Nixon et al. (1973), in an ecological study,
compared a small boat marina with a natural marsh embayment in Rhode
Island. The Environmental Protection Agency (1973, 1975) has issued
preliminary reports on several canal systems in the Florida Keys,
Charlotte Harbor, Florida area, and North Carolina. Daiber et^ al.
(1974, 1975) have completed two more reports on Delaware canals. The
Marco Island, Florida project has been studied by a group from the
University of Miami (Van de Kreeke and Roessler, 1975a and b, and
Carpenter and Van de Kreeke, 1975) and by the Deltona Corporation
(1975). Adkins and Bowman (1976) have prepared an informative document
on the canals dredged for oil drilling rigs in Louisiana. Burk and
Associates, Inc. (1975) examined the condition of a residential canal
development in Louisiana, and evaluated several developments in Florida
in an attempt to forecast water quality in the Louisiana development.
Thurlow (1974) did research on the water quality and sediment


Table 27.
(Continued)
-
Parameter
One Variable Model
R2
Multiple Variable Model
R2
Unexplained
Std. Dev.
DCOLOR
15.-18.(4.4)SEWERS
0.33
-98.+0.024(0.Oil)SUN+3.4(0.70) MINRES
-21.(6.8)CUMTIDE-2.9(0.45)FTOC
+3.1(0.31)FTC-480.(200)FTOP+O.13(0.016)
FCOLOR+O.36(0.056)DEVEL* TIDE
+25.(9.3)FTOC*FTOP
0.90
5.5
AVGDO
7.0-0.46(0.11)DEPTH *
CUMTIDE
0.34
7.0+0.081(0.021)WIDTH+0.90(0.29)DEPTH
-0.11(0.035)AGE-2.4(0.37)SEWERS
-32.(10.)FTOP-0.010(0.0016)FCOLOR
-1.1(0.17)DEPTH CUMTIDE+0.027(0.0037)
DEVEL CUMTIDE+1.8(0.47)FTOC FTOP
-0.0027(0.001)DEVEL*MINRES
0.91
0.56
MAXDO
6.5+0.0024(0.00046)DEVEL*
AGE
0.43
21.+0.0099(0.0029)SUN-0.0000044(0.0000030)
AREA+0.12(0.050)WIDTH-0.039(0.014)BULK
-4.6(1.4)CURBS-0.19(0.075)FTOC+0.13(0.06 3)FTC
+0.0042(0.00059)DEVEL AGE+0.0014(0.00068)
TURB* COLOR-1.7(0.72)DAYL
0.76
1.62
MINDO
6.0-0.91(0.24)DEPTH
0.30
9.6-0.0000044(0.0000018)AREA+0.084(0.02 7)
FTOC-O.12(0.031)FTC+6.8(1.6)FOP
+22.(6.5)FNH3-0.02(0.0026)FCOLOR
-0.044(0.0063)DEPTH AGE-75.(17.)FOP FNH3
0.88
0.86
SECCHI
2.0-0.0018(0.00046)SUN
0.31
2.3-0.0010(0.00024)SUN-0.024(0.0054)WIDTH
+0.056(0.011)AGE+0.63(0.10)SEWERS-1.3(0.22)
TIDE+0.088(0.021)MINRES-2.7(1.1)FTOP
+3.3(0.94)NH3-0.0018(0.00031)DEVEL MINRES
-0.0043(0.00067)FCOLOR
0.93
0.14
-146-


-123-
depths, higher color levels, and higher water temperatures.
The third pair of canonical variables is more difficult to inter
pret but seems to relate planktonic respiration (per square meter) to
the levels of organic carbon, average and minimum dissolved oxygen, and
water temperature in the canals. Canals with greater organic carbon
and water temperature levels tend to have higher planktonic respiration
and lower average and minimum oxygen values.
Metabolism vs. Canal/Sampling Day Characteristics
The results of the canonical correlation analysis for the metabolism
and canal/sampling day characteristics are presented in Table 21. The
significant correlations for the first three canonical variables sug
gest that three separate pairs of associated factors are present in
these two data sets.
The factors with the greatest correlation between the metabolic
and physical Characteristics seem to be the level of total community
metabolism (including the plankton) and the mean depth of the canals
and to a lesser extent, the canal width, sill height, presence of curbs
in the development, and the canal minimum residence time. This result
suggests that the deeper and wider canal systems with a sill and curbed
streets present, had higher metabolic levels.
The second pair of canonical variables seems to be derived prin
cipally from the surface planktonic production and secondarily from the
levels of respiration (TR, PRM2, and PPRM3) in the metabolism data
set, and from the tidal range and cumulated tidal range in the canals.
The canals with greater tidal ranges and frequencies, tended to have
greater surface plankton production and greater respiration levels.


-147-
narrow canals, by 0.081 mg/1 oxygen per meter of width. It does not
prove that greater canal widths cause higher average oxygen levels.
The regression coefficients given for the independent variables
in the models are the "best" estimates of the effects of those variables
However the coefficients have standard errors (shown in parentheses in
Table 27) associated with them that lead to ranges of possible values.
Therefore, these equations should not be considered absolute and must
be interpreted and applied with knowledge of their limitations. They
should not be applied to canal systems with attribute values outside
the ranges of those sampled.
The one variable models for these twenty canal attributes are
largely inadequate in accounting for the variabilities between the
canals sampled. Less than 50 percent of the individual variances can
be explained with single independent variables. The highest one-
variable r-squared values are for surface plankton production (PGPPM3)
2
versus tidal range (R = 0.47), and the maximum dissolved oxygen con
centration (MAXDO) versus the product of canal age and percent develop-
2
ment (R = 0.43). Most of the one variable models include factors
associated with the adjacent estuaries, sampling days, or canal age,
rather than the physical characteristics of the canal systems. Excep
tions to this generalization are the DTC-BULK, DC0L0R-SEWERS, and
MIND0-DEPTH models.
The individual models are self-explanatory. The utilities of the
models arise from being able to substitute the required explanatory
parameter values into the expressions and obtain estimates of the
response variables for a canal system. If this is done for every canal
observation, then the resultant populations of estimates should have


-7-
and stations, lower turbidities in the canals than in the bay, and no
significant differences in phytoplankton primary production levels
between natural and dredged areas. Silts and clays predominated in
the canal sediments, as compared to sand and shell in the bay sediments.
Fewer species of fish were netted in the canals than in the bay (49
versus 80), but thirty percent more fish were caught in the canals.
Sykes and Hall (1970) sampled the mollusks of canals and natural
areas in Boca Ciega Bay, Florida, concomitantly with Taylor and Saloman.
Their results show a marked reduction in numbers of individuals and
species in the soft sediments of the canals as compared to those of
the bay.
Lindall, Hall and Saloman (1973) followed the fish populations of
a newly opened canal system off Tampa Bay, Florida. Only anchovies
(Anchoa mitchilli) were caught in the system three months after inunda
tion, but during the following year 36 species were netted. Lindall
et al. thought that newer canals provide a more favorable habitat for
fishes than do older canals.
Barada and Partington's (1972) report on waterfront developments
in Florida, while supplying no new data on canals, was instrumental in
bringing the problem of canal dredging to the public's attention. Their
report, citing several of the above investigations, discusses the lack
of good circulation and flushing, excessive depths, stratification,
fish kills, odor, and bacterial problems of canals. An image of canals
as open sewers and as having detrimental effects on ground and surface
waters, was projected.
Godwin and Sholar (n.d.) found increased silt and clay fractions
and decreased benthic invertebrate diversities in dredged canal sediments,


Table 31. Significant factor effects on canal metabolic parameters.
TGPP TR P GPP M2 PRM2 PGPPM3 PPRM3 TPR PPR PDOMIN
AREA
-
WIDTH
+
DEPTH

DEPTH*SILL
_

DEPTH*AGE
DEPTH*TIDE
+
+
+
DEPTH*CUMTIDE
-
SILL
+
+
+
AGE
TIDE
_
CUMTIDE
MINRES
+
DEVEL
+
DEVEL*AGE
+
+
DEVEL*TIDE
+
DEVEL*CUMTIDE
DEVEL*MINRES

BULK
-
_
CURBS
SEWERS
+
+
DAYL
' _
SUN
+
+
+
+
+
+
+
+
+
+
+
+
FTC
FTOC
FTOP
FTOC*FTOP
+
+
+
+ +
+
+
+ +
-T9T-


-54-
2
g 02/m -day
N = 56 Mean = 8.59 Std. Dev. = 5.87 Range 0.00 to 24.9
C.V.% = 66
Figure 14. Frequency distribution and descriptive statistics for
total community gross primary production (g 02/m^-day),
averaged by canal. Values are rounded to nearest integer.
N = 56 Mean = 4.91 Std. Dev. = 3.91 Range 0.40 to 23.9
C.V.% =80
Figure 15. Frequency distribution and descriptive statistics for
planktonic gross primary production (g C>2/m2-day) averaged
by canal. Values are rounded to nearest integer.


-253-
UBS
MONTH
DAY
Y EAR
STAT ION
TIME
TC
I C
TOC
5 1 1
9
7
75
P69
4
32.5
16.0
1 6.5
SI 2
9
7
75
PG9
5

0

SI 3
9
7
75
PG9
6
3 1.0
15.4
15.6
SI 4
9
7
75
PG9
7
32. 9
1 8.0
14.9
S l 5
9
7
75
PG9
b
32.2
16.6
15.6
SIS
9
7
75
PG9
9
3 6.5
15.5
11.0
5 1 7
9
7
75
PG9
1 0
42.7
12.2
3 0.5
sis
9
7
75
PG9
1 1
34.6
16.8
17.7
51 9
9
6
75
PG 3
1 2
33.2
15.9
1 7.3
520
9
6
7 5
PG3
13
31.3
17.3
14.0
2 1
9
6
75
PG3
1 4
32. 4
1 6.4
l 6. 0
522
9
6
75
PG3
1 5
36.0
17.8
17.2
5 2 3
9
6
75
PG3
1 6
40.0
16.5
23.5
524
9
6
75
PG3
1 7
32.4
1 7.2
t 5.2
525
9
6
75
PG3
18
3 1.4
16.6
14.8
526
9
6
75
PG3
1 9
3 1.3
17.8
13.5
52 7
9
6
7 5
PG3
20



52 8
9
6
7 5
PG3
2 l
32.6
14.2
18.4
5 29
9
6
75
PG3
22
33.9
14.5
19.4
53C
9
6
75
PG3
23
32.0
1 6.3
1 5. 7
53 1
9
6
75
PG 3
4
32.0
16.5
15.5
532
9
7
75
PG3
l
32. 0
16.7
15.3
533
9
7
75
PG3
2
3 3.0
15.0
1 8. 0
53 4
9
7
75
PG3
3
36 8
l 6 .2
20.6
535
9
7
7 5
PG3
4
32. 0
1 7.0
15.0
53S
9
7
75
PG3
5
30.5
19.5
11.0
537
9
7
75
PG 3
6
3 1.6
19.5
12.1
53 8
9
7
75
PG3
7
3 l 7
15.5
1 6. 2
539
9
7
75
PGi
5
3 1.5
1 7 .8
13.7
540
9
7
75
PG 3
9
3 8.8
l 7.0
11.8
Ob 5
TP
UP
TOP
lURb
NH3
CU.OR
DS
COND
5 1 1
0.536
0.450
0.086
2 .8
0.19
2 1 4
0. 08

512



.

.
-0.17

5 13
0.469
0.442
0.02 7
3.2
0. 1 5
2 08
-0. 35

51 4
0 .474
0.437
0.037
3.8
0. 16
187
-0.40

5 15
0.482
C.4 00
0.062
2.1
0 15
2C3
-0.35

516
0.529
0 .458
0.071
2 1
0. 40
236
-0.30

51 7
0 .503
0.44C
0.063
3.7
0.22
240
-0.23

518
0.529
0.5 15
0.014
2.9
0.19
23 9
-0.03

51 9
0.532
0.490
0 .042
2.8
0. 1 8
260
C 36

52 0
0.500
0.4 55
0.045
2.1
0.22
255
0.36

521
0.465
0.4C8
0.057
2.0
0.23
203
0.33

522
0.432
0 .399
0 03 J
2 .0
0.20
1 80
0. 26

523
0.439
0.415
0.024
11.0
0.23
258
0.13

524
0.412
0.477

3.3
0. 1 7
2 1 0
-0.15

32 5
0.392
0.428

1 .6
0.25
216
-0.35
52 6
0.482
0.445
C. 037
1 .8
0.11
24 2
-0.39
t
527





.
-0.38

32 8
0.562
0.4 98
0.064
3 .0
0.14
27 2
-0.31

52 9
0.555
C. 510
0. 045
4 .5
0.12
245
0.1 D

3 3 0
0.512
0.458
0.054
2.2
0. 27
3 1
0. 1 1

53 l
0.528
0.489
0.039
4 .6
C. 19
263
0.34

532
0.516
0.512
0.GC4
2. 7
0.2 6
24 1
0.39

533
0 .579
0 .4 87
0 .092
3.5
0.18
25 8
0. 32

53 4
0.550
0.4 82
0.068
2 .2
0.18
238
0.24

535
0.543
0.463
0.060
1 7
0.25
236
0. 06

53 6
0.4 03
C 3 66
0.037
2 .4
0.29
193
-0.17

53 7
0.491
0.350
0.141
5.0
0.25
180
-0.35

5 3 8
0.480
0.428
0.052
2.8
0.22
12
-0. 40

53 5
0.469
0.437
0.032
14 .C
0.2 1
2 19
-0.35

540
0.533
2.069

2.5
0. 1 7
248
-0.30



Table 30.
Gross primary production levels for different aquatic systems,
gm C/m -day.*
System Type
Location
GPP
Source
Marine
.Open ocean
0.2
See E.P. Odum (1971) p. 51
Coastal zone
0.5
ft
Upwelling zones
1.
It
Coral reefs
4.-15.
See H.T. Odum (1971) p. 83
Tropical marine
2.-14.
II
meadows
Estuarine
Tampa Bay area
0.3-0.9
See Steidinger (1973)
North Carolina
0.1-0.5
II.
Georgia
0.7
II
Texas Bay
3.
II
Long Island
2.
See E.P. Odum (1971) p. 46
Waste-receiving
Texas
8.-23.
See H.T. Odum (1971) p. 83
marine bay
Wetlands
Mangroves
-fringing
South Florida
13. 1.1
Stanford (1976)
(Card Sound)
-scrub
. If
12. 1.0
II
Puerto Rico
8. 0.90
Golley et al. (1962)
Salt marsh
Jrncus
South Florida
4. 1.4
Stanford (1976)
Spartina
Georgia
9. 1.1
Teal (1962)
Canals residential
Florida
0-12. 0.31-2.9
This study
(4.3 mean) (1.1 mean)
* Conversions used to
2
obtain gm C/m -day
from reported values: 1 Kcal
x 0.1 = 1 mg C;
1 year/365 = 1 day;
1 gm C>2 x 0.5 = 1
gm C
-ST-


-181-
Table 35. (Continued)
Canal-Estuary Net-Exchanges
Carbon Total
Organic
Phosphorus Total
Ortho-
Organic
Ammonia
Turbidity .
Color
Imports 0.2 mg/1 exchanged water
" 0.2 "
" 0.003 "
" 0.005 " "
Exports 0.002 " "
None
Lowers 0.2 NRU "
" 6 CPU


-214-
UBS
MONTH
DAY
Y PAR
S TAT 1UN
T'l ME
Zl
DU 1
Z 2
DU2
6 1
3
25
75
LX7
1 645
0
6.28
0.7
o 4 0
62
3
25
75
LX7
1 646
0
6. 08
0.5
6.17
63
3
25
75
LX 7
2156
0
6.2 3
0.5
6.35
4
3
25
75
LX8
125
0
5.46
0 .5
5.26
65
3
25
75
LX8
6 00
0
5.09
1 .0
5.15
66
3
25
75
LXb
800
0
5.15
1 .0
5.32
67
3
25
75
LX6
1040
0
5. 73
0.5
5.74
68
3
25
75
LX6
1 340
0
6.37
0.5
5.39
69
3
25
75
LX6
1415
0
5.95
0 .5
u 95
70
3
25
75
LX6
1 637
0
6. 22
1.0
6. 95
7 1
3
25
75
LX8
19 10
0
6 .22
0 .5
6.23
72
3
25
75
LX6
2220
0
5 o2
0.5
5 .53
73
3
27
75
PU1
730
0
4.30
0.5
4. 2 1
74
3
27
75
Pul
1 7 JO
0
7.24
0 .5
7.04
7b
3
26
75
PO 1
1 905
0
6.69
1.0
6.92
76
3
2 7
7 5
PB2
746
0
4.24
0.5
4. 1 0
77
3
2 7
75
P62
1 746
0
b .90
C 5
5.57
76
3
2 6
7 5
PB2
1920
0
0.67
1 0
6.56
79
3
26
7 5
Pb3
820
0
4.74
0.5
4.6 1
80
3
26
75
Po3
1 76C
0
5.75
0.5
5.73
81
3
26
75
PB3
1 92 5
0
29
1.0
.3 9
b 2
3
2 7
75
P134
865
0
4.8 1
0.5
4.41
83
3
27
75
Pb 4
1 82 0
0
8.13
0.5
5.73
84
3
2b
75
PU4
2020
0
6.78
1.0
6.02
85
3
27
75
Pu5
845
0
4.6 1
0 .5
4,46
86
3
27
7o
PU5
1815
0
6. 3o
0.5
b 3 7
87
3
26
75
PB5
2010
0
6.99
1.0
6.4b
88
3
2 7
75
Pbu
84 0
0
5.31
0.5
5.25
89
3
27
75
Pbo
l 8 06
0
6.23
0. 5
6.06
90
3
26
7 5
Pb
1 955
0
6.4 1
1 .0
6.62
UBS
73
OQ 3
4
DU 4
DU 5
Du6 DU7
Z 6
Z 7
61
0. C
0.00
0.0
0 OC
0

0
0 .
00
0
0

62
1.0
6.17
0.0
0.00
0

0
0.
00
c
0

63
1.0
6.35
0.0
0 .00
0

0
0.
00
0
0

64
1.0
5. 1 9
0. 0
. 00
0

0
0.
00
0
0

6 b
1.5
5.15
C 0
0.00
0

0
0.
00
0
0

66
2.0
5.40
0.0
0.00
0

0
0 .
00
0
0

67
1 .5
5.8 1
2. 0
5.77
2

6
b
70
0
0

68
1.0
5.31
1.5
5.46
2

0
b
72
0
0

69
1.0
6. 1 1
1.5
5 95
1

7
6
1 7
0
0

70
2.0
5.77
0.0
0.00
0

0
0.
00
0
0
7 1
1.0
6.22
1.5
6.29
2

0
G
1 0
c
0

72
1.0
5.62
1.5
5.65
2

0
b
52
0
0

73
1.0
4 .2.1
1 5
4.21
2

0
2.
90
0
0

74
1.0
3.05
0 .0
0 .00
0

0
0.
00
0
0

7 b
2.0
4.3 0
0. 0
0.00
0
m
0
0.
00
0
0

76
1.0
4.06
l .5
4.04
2

5
G
4 1
0
0

77
1.0
5.50
1.5
5.41
2

0
4
83
0
0

78
2.0
6 ob
2.6
3. 76
0

0
0.
00
0
0

79
1 0
4.57
1.5
4 66
2

5
4 .
5 9
0
0

80
1.0
5. 92
1.5
6 4 o
2

0
b .
86
0
0

81
2.0
6.39
3.0
6.29
0

0
C.
00
u
0

02
1.0
4.2 8
l 5
3.90
2

5
3
25
0
0

63
1.0
6.20
l 5
i 60
0

0
0.
00
0
0

84
2.0
5.68
2.7
4.4 6
0

0
0 .
00
0
0

85
l 0
4. 33
2 .0
4.4 8
3

0
4 .
1 3
0
0

8 6
1.0
6.38
1.5
u 6 4
2

0
3 .
85
0
0

8 7
2.0
6.35
3.0
3.43
0

0
0.
00
0
0

88
1.0
5. 1 7
1.5
5.15
2

5
5 .
1 0
0
0

89
1.0
6.0 1
1 5
5. 90
0

0
' 0.
00
0
0

90
2.0
6.6 2
2.5
u .00
0

0
0 .
00
0
0



-299-
CURRELATIN COEFFICIENTS / PUb > |Rj
MER OF OUSE HV ATlON S
UNDER HOT
RH = 0 / NU
DTUR6
ETC
BULK
F T UP
ENH3
F NH3
CUMTIDE
DTC
-0.07239
0.0666 7
0.06657
0.06107
0.06107
-0.06079
-0.05574
0.6249
0.6428
0.6 72 4
0.6801
0.6801
0.6815
0.7067
48
48
44
48
48
40
46
LTC
MDEPHI
FUP
PPR
T DE
S ILL
MONTH
0.05467
0.05257
-0. 043 7 5
0.04165
-0.03760
0.03487
0.03481
0.7121
0.7227
0.7676
0.7840
0.7987
0.8140
0.8143
48
48
48
46
46
4
48
DUP
UN H3
Fl UC
5 UN
A VU DO
SEWERS
E TOP
-0.02831
-0 .02109
0.01702
0.0 1676
-0.01558
0.01 175
-0.00251
0. 84 85
0.8869
0.9054
0.912C
0.91 63
0.9368
0.9871
48
48
46
46
46
48
44
PCULQR
FCLR
LCLR
SECCH1
U A Y
MUN TH
ENH3
FNH3
1.00000
0.98001
-0.'59499
-0.54292
0.50666
0.50649
0.50649
C.0000
0.0001
0.0001
0.00C2
0.0006
0 .0006
0.0006
42
42
42
42
42
42
42
M1NUQ
FTUR8
DCOLUk
YEAR
ETP
ETUR
TEMP
-0.49681
0.4632 8
0.44196
-0.403 9 7
0.40052
0.39376
0.35297
0.0000
0.0012
0.0034
0. 0060
0.0127
0.0099
0.0219
42
42
42
42
38
42
42
CURBS
U T UR B
E7P
F TP
SE KER S
PDMlN
MAXD
-0.33298
0 .33050
0.3 1 1 6
C .3 1 6 1 2
-0.28619
-0.28435
0.28029
0.0312
C. 0325
0.0414
0.0414
0.0661
0 .0036
0.0722
42
4 2
4 2
42
4 2
38
42
F TOP
PGPPM2
AV OU
E UP
Vi i U1 H
T IDE
FCOND
0.27753
-0.26920
0.26651
0. 2 6362
0.2 5568
-0.23325
-0.21835
0 .09 1 6
C.0 93 0
0.0880
0.0914
0.1022
0.1371
0.3053
38
40
42
42
42
42
24
ECUND
AGE
UULK
DNH3
TPR
MDEPTH
DEVEL
-0.21702
-0.18313
-0. 1 7 53 5
0.16442
-0.15511
-0. 15 166
-0. 15182
0.30B4
0.2457
0.2667
0. 296 1
0.3524
0 .3370
0.3372
24
42
42
42
38
4 2
42
PPR
UTOC
uTC
PR.M2
S ILL
UTOP
OOP
-0.13675
0.13410
0.09680
-0. 09407
-0.09064
-0.08036
0.07289
0.4001
0.3972
0.5462
0.5637
0.5681
0.6129
0.6464
40
42
42
40
42
42
4 2
PfRM 3
TR
FQP
E TC
OIL
LENGTH
F 1 C
0.Oo 7 1 0
0 .06060
-0.05 726
-C.057 16
-0.05205
-0.04148
-0.035 76
0.6808
C.7103
0.7166
0.7192
07434
0.794 2
0.8221
40
40
42
42
42
42
42
PGPPM3
LTUC
E i C
FTC
MINRES
SUN
CUMT IDE
-C.03471
-0.03421 -0. 031 97
-0.02403
0. C2183
-0.01928
-0.91741
0.8316
0.829 7
0.840 7
0.87 49
0.8909
0.9060
0.9129
40
4 2
42
42
42
40
42
OCND
AREA
FTUC
VULUME
DTP
D AYL
TGPP
-0.01677
-0.01605
0.00906
-C .00 719
C. 00o7 T
0.00455
0.00132
0.936 C
0.9196
0.9546
0.9b40
0.9661
0.9 772
0.9935
24
4 2
42
42
42
42
4 0


-107-
nutrient exchange subset are shown in Table 15. The first principal
component accounts for 31 percent of the observed variability in ex
change behavior for these canals. This factor appears to be one of net
total carbon and organic carbon exchange and, to a lesser extent, of
net organic phosphorus versus net ortho-phosphorus exchange. The second
component explains an additional 20 percent of the pattern of exchange
responses, and appears to be primarily associated with net changes in
the color and turbidity of the water entering the canals. The third
component explains 15 percent more of the total variability and is a
combination of net inorganic nutrient exchange (ammonium and ortho-P),
net changes in color somewhat contrasted to changes in turbidity, and
the net exchange of organic phosphorus.
The pattern of the net exchange responses is not as structured as
the metabolic responses since the first principal component of the
former explains just 31 percent of the total observed variability
compared to 40 percent for the latter. Also, the first three com
ponents account for 66 percent of the total variance, whereas those of
the metabolism set account for 80 percent. The lack of correlation
between the organic carbon and organic phosphorus exchanges (r = 0.14)
and between the ortho-phosphorus and ammonium exchanges (r = 0.10)
further illustrates the complexity of the observed exchange responses.
Water Quality
The principal component analysis for the water quality subset is
presented in Table 16. The results indicate that a simple water quality
index would not be adequate to classify these canals, since the first
principal component explains just 29 percent of the total variability


-204-
S
r
P
P
M
A
O
G
G
P
0
Y
T
£
T
P
P
P
P

N
D
E
1
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G
P
k
P
R
T
P
s

T
A
A

T
P
T
M
M
M
M
P
P
u
5
H
y
R
N
H
P
k
2
2
3
3
R
R
N
8 9
6
1 9
7b
PB1
0
15.
24
1 1

9 4
7 .
51
6
46
12. 65
3

44
1

28
l
1 6
342
90
6
1 9
75
PB 1
1


.
1.19
2

1 7

342
9 1
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l 9
75
Pbl
2


0
0.00
2

57

342
92
6
1 9
75
PU2
0
9.
53
12
0
3 6
0


0

77
342
93
6
1 9
75
P83
0
3.
55
9.
86
0
6.4 o
3

26
0

36
342
94
6
l 9
75
PB3
1

0
0
0.83
2

2 6
0
342
95
6
1 9
75
PB 3
2

0

0.23
2

48
0
342
96
6
19
75
PB4
0
14.
64
16
0
9 2
8.
3 1
5
3 7
11.20
3

84
0
0
86
1
64
342
9 7
6
1 9
75
PB4
1
9
0

2.7 1
0

46
0
342
98
6
1 9
75
PB5
0
5.
97
10
0
1 2



0
0
59
342
99
o
19
75
PB6
0
4 .
60
10
0
1 2
4.
60
7
30
7.92
5

53
0
0
45
0
63
342
i 00
6
1 9
75
P 06
1

0

0.64
2
#
50
0
342
10 1
6
1 9
75
PB6
2

0

0.00
2

04
0
342
1 02
6
1 9
75
PB7
0
0 .
00
2
0
68



0
0
00
342
103
6
1 9
75
PB 8
1
0.
00
a
0
92



0
0
CO
342
1 04
6
1 8
75
LX 1
0
0.
00
1
0
1 8
4.
69
2
46
5.19
1

06
0
0
00
l
90
3 76
1 Cb
6
1 8
75
LX1
1

0
0
0.64
0

9 1
0
3 78
106
6
1 8
75
LX2
0
b
82
5
0
8 6
0


l
0
16
378
1 0 7
6
1 8
75
LX3
0
6 .
7 7
5
0
1 4
2.
7 o
1
45
3. 86
0

9 l
l
0
32
1
90
3 78
1 08
6
1 8
75
LX3
1

0

C 57
0

73
9
3 78
109
6
1 8
75
LX3
2

0

0.53
0

27
0
3 78
1 1 0
6
l a
75
LX4
0
4.
99
5
0
80
2.
07
2
87
4.14
1

83
0
9
86
0
72
378
1 1 1
6
18
75
LX4
l

0

0 .0 l
0

43
9
3 70
1 1 2
6
1 8
75
L X4
2

0

0. 00
1

5 3
9
3 78
1 13
6
l 8
75
LX5
0
b
55
9
0
98



0
9
65
3 78
1 1 4
6
1 8
75
L X6
0
7.
34
9
0
08

4.97
1
0
06
0
0
81
378
1 1 5
6
1 8
75
L Xb
1

0

0. 84
0
0
7 7
9
3 78
1 1 6
6
1 8
75
LX6
2

0

0.29
0
0
48
9
378
1 i 7
6
l 8
75
LX7
0
3.
63
2
0
86

.
0
1
9
27
378
1 l 8
6
1 8
75
LX6
0
2 .
82
2
0
30

2.45
0

50
1
9
23
3 78
1 1 9
6
1 8
75
LX6
1

0
0
0.19
1

1 1
9
3 78
120
9
6
75
PG 1
0
o.
00
0
0
00
0.
60
1
31
1.21
0

84
9
0
45
426
1 21
9
6
75
FGl
1

0

0. C
0
0
65
0
426
122
9
6
75
PG1
2
0
0

0.00
0
0
1 6
0
426
1 2 3
9
6
75
PG2
0
0.
00
0
0
00
0

0
9
426
1 24
9
6
75
PG3
0
0 .
00
0
0
0 0
0 .
37
0
19
0.34
0
0
la
0
1
95
426
125
9
6
75
PG3
1

0
0
0.18
0
0
1 0
0
420
1 2o
9
6
75
PG3
2

0
0
0.05
0
0
00
0
4 26
1 2 7
9
6
75
PG4
0
0 .
00
0
0
00
0 .
43
0
84
0.54
0
0
25
9
0
51
426
128
9
6
75
PG 4
1
0
0
0
0.00
0

l 0
9
4 26
1 29
9
6
75
PG4
2

0
0.16
0

4 1
9
426
1 30
9
6
75
PG5
0
0.
00
0
0
G0


0
0
4 26
1 3 1
9
6
75
Pc6
0
0 .
00
0
0
00
0.
80
0
15
l. 59
0
0
2 7
9
5
33
426
132
9
6
75
PG6
1

0

0 cc
0
0
00
9
426
1 33
9
6
7 5
PGO
2

0

0.01
0
0
C 9
0
4 26
134
9
6
75
PG 7
0
0 .
00
0
0
24
0 .
23
0
21
C. 46
0
0
0 3
0
9
00
1
07
426
136
9
6
75
PG 7
1

0

C .00
0
0
20
9
4 2b
136
9
6
75
PG 7
2

0

0. 00
0
0
00
0
42o
l 3 7
9
6
7 5
POS
0
2 .
1 6
1
0
20
0

0
1
0
ao
4 2b
138
9
a
75
PCI
0
27.
1 0
2 6
0
70
3.
35
4
74
4.98
2
0
48
1
0
0 1
0
71
4 46
139
9
8
75
PC 1
1
0
0

0.86
1
0
00
9
446
140
9
8
75
PCI
2

0
0
0.00
1
0
67
9
446
1 41
9
8
75
PC 2
0
2 0.
90
1 8
0
20
0
.
0
1
9
15
446
l 42
9
8
75
PC3
0
13.
50
6
0
22
- *
23
2
aO
. 34
1
0
60
1
9
64
l
l 5
4 46
1 43
9
8
75
PC3
1

0

0.07
0
0
80
0
446
1 44
9
8
75
PC 3
2

0
9
0.00
0
0
6 0
9
446
1 4b
9
8
75
PC4
0
34.
1 0
35
0
9 0
7.
b2
6
45
10. 11
3
0
2 1
0
.
95
1
i a
446
l 46
9
8
75
PC 4
1

0
0
2. 13
1
0
97

446


-312-
CORRELATION COEFFICIENTS / PRUb > |R| UNDER H0:RHO=0 / NU
MB ER OF OBSERVATIONS
LENGTH
LENGTH
l COOOO
O.OOOC
74
AREA'
0.98145
0.000 1
74
VOLUME
09364^
0.0001
7 4
SE WLRS
0.38706
0. 0007
74
1PR
0.36140
0.0073
54
WIDTH
0.31708
0.0059
74
TIDE
0 .31094
0.0070
74
E OP
0.26530
0.0441
58
UA r
-0.25414
0.0289
74
re>PP
0.24679
0.067 9
5 D
AVGUU
0.2 3 6 L1
0.0424
73
F T OP
0.2 3 7 9 7
0.0831
54
ETUP
0. 20373
0.1395
54
FTP
0.20300
0.0695
71
ETP
0. 1 94 79
0.1036
71
MINRE S
-0.19078
0.1035
74
F l C
-C.18904
0.1553
56
BULK
0.18347
0.1372
67
E 1C
-0.17647
0. 1 851
58
MA XLO
0 17 64 1
0.1354
73
YEAR
0.1 74 4 7
0.1371
74
FOP
0.18767
0.2078
50
DIG
-0.16579
0.2220
56
SILL
0.1635b
0 176 1
70
SUN
C.16084
0.23 63
56
PPRM3
0. 14645
0.2749
56
ET C
C. 13913
0.2472
71
PGPPM2
0.132 78
0.3293
56
F TO C
0.13215
0.2719
71
Tk
0.12247
0.3686
5 6
DCUNU
0.11191
0.6 02 o
24
DTC
-0.10918
0. 4232
56
BEVEL
0.10833
0.3665
7 l
AGE
-0.10815
0.3693
7 1
C UM TIDE
0.09583
C. 41 67
74
OOP
0.09527
C.4849
5b
DCULR
-0.09129
0.5653
42
MDEP1H
-0.0 8894
0.4o l 1
74
PD UM1N
0.0 8869
0.522 7
54
DTUKb
-0.08864
0.5491
48
PGPPM3
0.08729
0.5224
56
PRM 2
0.085l9
0.5324
56
ETC
0.08497
0.5260
50
TEMP
0.C8333
0.4834
73
SECLHI
C 0 80 6 6
0.540 1
60
DAYL
C.07834
0. 50 70
74
FTUKts
-0.076 47
0. 5976
50
DTP
0 .0 7424
0.5474
60
DT UP
0.06637
0.61 66
56
P PR
0.06732
0.622 0
56
DNH 3
0.0665 0
0.5672
69
ECUNU
0.0 56 1 3
0.7946
24
FTC
0 0 5 4 6 6
0.6836
58
FCULR
-0.04146
0.7942
42
FCCND
- 0.03869
0.8576
24
FNH3
-0. C372 0
0.7581
7 l
ENH3
-0.03720
0.7681
71
MI NO
0.03606
0.7620
73
ECOLuH
-0.03569
0.8t 1 5
42
CURBS
0.0 3 3 5 6
0. 77 65
74
E TUKU
-0.03103
0. 830 o
50
DTUC
-0.02141
0.6614
69
MONTH
-0.00698
C.953 0
74
w IDTH
WIDTH
l OOOOC
0.0000
74
SEWERS
0.64 6 0 7
0.0001
74
E IC
-0.5 5a78
0.CCO 1
56
FI C
0.54 8 68
0.0001
58
EOP
0.52459
0.0001
56
T GPP
0.50 53 1
0.0001
56
F TP
0.4 809 8
0.00 0l
71
L TP
0 .47262
0.0001
71
CURBS
0.41476
0.0002
74
T k
0.40311
0.0021
66
F TOP
C .37986
0.C 04b
54
FT DC
0.3 4 025
0.0037
71
VLLUME
0.33650
0.0034
74
FOUND
-0.331 76
0.1132
24
ECONO
C .32623
0.1198
24
YEAR
0.32313
0.0050
74
LENGTH
0.3 1 7 0 6
0.0059
7 4
SUN
0.31644
0. 01 75
56
tree
0.31245
0.0080
7 l
DCLLR
-0.30 92 5
0.0463
42
AREA
0.29404
0.01 to
74


-320-
CURRELATIUN CU tF(- 1 c 1 ENTS / PRuB > |K| UNDER El0:RH=0 / NU
MBLR UF OBSERVATIONS
SEVERS
PGPPM3
-0.123 73
0.36 26
66
DA YL
-0.11193
0.3424
74
DAY
-0.10193
0.3874
74
ECUNU
0.0 9686
0.6458
24
ECUND
0.09785
0.6492
24
SILL
-0.03898
0.4638
70
DT UP
-0.08357
0.5403
56
MINRES
0.07025
0 552 0
74
M I ND
0.06562
0.6818
73
MUNT H
- 0.05896
0.6176
7 4
TR
0.05380
0.6937
56
PDUM 1N
-0.04338
0. 7555
54
ETURB
-0 .03 750
0.7960
50
PPR
-0.92414
0.05 9 8
56
FNH3
-0.02259
0.651b
71
ENH 3
-0.02259
0.8516
7 1
D I UC
0 01 4 7 7
0.9041
6 9
DC ONU
-0.0 i860
0.94 97
24
D TURO
0.0l175
0.9368
48
ETURB
-0.00628
C .9 655
50
PPR M3
0.0040 5
0.9764
5o
AVGDU
AVGUU
1.00000
C.0000
73
MI ND 0
0.64212
0.000 l
73
ETC
- 0.4 7031
0.0002
5 7
ETC
0.48506
0.0C07
57
SUN
0. 424 1 1
0.00l 1
56
MDEPTH
-0.39150
0.0006
73
MONTE)
-0.33883
0.0034
73
YEAR
0.324 2A
0.0051
73
S ILL
-0.29501
0.0139
6 9
MAXDu
0.28295
0.0153
7 3
EC UL R
-0.2 6o51
0.0880
42
ECULR
-0.25*08
0.0976
42
AREA
0 .2452 9
0.0365
73
LENGTH
0.236 21
0.0424
73
e rp
0 .23443
0. 05 08
70
F IC
-0.22070
0.087 l
5 7
ETP
0.22.322
0 .0682
70
C UK US
0.21512
0 06 76
73
PPR
0.21297
C.1150
56
EIC
- 0. 20 92 6
0.1 l e2
57
VOLUME
0.2 06 72
0.0793
73
WIDTH
0.19616
0.0963
73
M NRES
-0. 18777
0.1117
73
FTUP
0.18490
0.1850
53
DEV EL
0. 1 81 03
0. 1337
70
A GE
-C.16008
0. 1358
70
DAY
0.17648
0 1 353
73
SEWERS
0.17503
0.1367
73
UP
0.1 7334
0. 1 9 72
57
DI C
-0 15942
0.2450
55
E NH j
-0.1545o
0.20 l 4
70
ENH3
0. 1 545o
0.20 l 4
70
Ic MP
-0.15412
0.1930
73
PGPPM3
0.13195
0.3323
56
DT OP
0.12149
0.3769
55
T I DE
-C.12046
0.3100
73
TPR
0.11801
0.3954
54
DI P
0.11248
C. 364 8
67
F UP
0.10564
0. 4342
57
ETuP
0.10027
0. 4750
53
DA YL
C 06892
0.4344
73
DTOC
0.08149
0.5089
60
PGPPM2
0.08142
0.5506
56
BULK
o o a 11 o
0.5174
6 6
cumtide
-0.07628
0.521o
7 3
PKM2
0.0 70 43
0.6060
56
UUP
0. 06 7 99
06216
5b
SECCHI
-0.06599
0.6164
60
DCOlUR
-0.06109
0.6970
4 2
DNH3
- 0.06 C65
0.6232
68
TR
0.06 0 59
0.65 73
5 6
16 P P
0 .0 599:
0.6'o 0 9
56
PDOW 1N
0.04124
0. 76 72
54
ETURB
-0.02291
0.8745
50
E TOC
-C.02097
0.8632
70
PPKMJ
0.01803
0. 895 0
56
O TC
-0.01801
0.6962
55
D TURt
0.01558
0.9163
48
ETURb
-0.00950
0.9478
50
ECU ND
-C.C 06 79
0.9749
24
FT CC
-0.00494
0.9G 76
70
DCCND
-0.00304
0 .9887
2 4
ECUND
-0. 0 02 86
0.9894
24


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-246-
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TC
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30 1
1 1
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75
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5
33.1
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30 1
1 1
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PG6
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1 1
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PG6
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19.4
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30 5
t 1
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PG6
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32.7
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30 7
1 1
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75
PG6
1 1

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1 1
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PG6
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30 9
1 1
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PG6
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PG6
1 6



313
1 1
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PG6
1 7



314
1 1
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75
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1 8
33.2
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14.2
315
1 1
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75
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33.5
18.0
15.5
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1 1
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75
PG9
19
3 1.0
17.6
13.4
317
1 1
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75
PG9
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33.2
17.9
15.3
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1 1
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75
PG9
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32.9
15. 6
1 7. 3
31 9
1 1
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75
PG9
22
33.9
15.0
18.9
320
1 1
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PU9
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34.7
15.8
18.9
32 1
1 1
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PG9
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15.8
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322
1 1
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PG9
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33.0
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PG9
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PG9
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PG9
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39. 3
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1 1
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PG9
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33.4
15.7
17.7
328
1 1
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PG9
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33.9
15.9
18.0
329
1 1
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PG9
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32.7
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14. 1
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PG9
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35.4
16.1
19.3
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UP .
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30 1
0.304
0.271
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302
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C .31 3
0.282
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xml record header identifier oai:www.uflib.ufl.edu.ufdc:UF0008974600001datestamp 2009-02-09setSpec [UFDC_OAI_SET]metadata oai_dc:dc xmlns:oai_dc http:www.openarchives.orgOAI2.0oai_dc xmlns:dc http:purl.orgdcelements1.1 xmlns:xsi http:www.w3.org2001XMLSchema-instance xsi:schemaLocation http:www.openarchives.orgOAI2.0oai_dc.xsd dc:title Canal-estuary nutrient exchange and metabolic levels in Florida residential canals dc:creator Bailey, William Arthurdc:publisher William Arthur Baileydc:date 1977dc:type Bookdc:identifier http://www.uflib.ufl.edu/ufdc/?b=UF00089746&v=00001000185249 (alephbibnum)03334690 (oclc)dc:source University of Floridadc:language English


-10-
boats as an important food source for juvenile fish populations and
which may serve the same detritus-producing role as do the marsh grass
in the natural marsh embayment. The fouling communities reached a
maximum biomass of 5,000 g/m^, about five times the standing crop of
marsh grass. The respiration rate of the fouling communities was quite
2
high (mean = 1.80 g O^/m -hr) with no net production and was about 20
times the oxygen demand of the sediments.
The preliminary E.P.A. (1973, 1975) reports represent the most
exhaustive sampling sessions on selected canals in Florida and North
Carolina. Impressive amounts of water quality, sediment, microbial,
hydrodynamic, mass transport, and biological data were collected twice
for two pairs of canals near Punta Gorda and Big Pine Key, Florida, and
once at sites in Marathon, Florida, Panama City, Florida, and Atlantic
Beach, North Carolina. Their preliminary but unofficial recommendations
were to restrict canal depths to 41 to 6 feet, to centralize the waste
treatment facilities of the development and discharge the effluent at
points remote from the canals, to have the developer provide sufficient
bonding to correct any water quality violations in the canals or to
isolate the canals from receiving waters, to design developments so
that stormwater runoff does not enter the waterways, to avoid sills at
the canal mouths, and to require an assessment of a proposed canal
development's impact on any local shallow freshwater aquifers.
Daiber ej: _al. (1974) expanded on their earlier work and presented
seasonal data on seven canal systems in Delaware. Hydrological,
coliform, BOD, fish and benthic invertebrate results are reported along
with more flushing characteristics and a simple tidal excursion model
for transport within a canal. They concluded that the flushing rates


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en cr tn en en ai en tn ai tn en ai en ai en en ai en en en en ai en en a> en cr en ai ai
tttTI-cXfDTITttttttfCTTttXDtXXtTt
c c. o a a c a a cr cr tr cr c c cr ce c c c c c a a cr a a cr cr a a
C'C'C'tetruteuiUCetetuceteteteajCcOiCececetecetetea-crc'cr
>-o'CceNcrtrpterv>-o>£'a;
uciea en a.te u u
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O N
OjPPpUCiUUC.'uUUteUpPP
ce u o o a o: a en c cr oa.Noa>aoPo
te u
ivo's'UiacnivrvoNcnsj-^oaicno
rv no iv rv rv rv
Q'-J(7'cncEa'OvocE
rv rv
00 -V
ivivrvrvajfvfvrvNrvfvfvrvfvrvfvfv
oC'cntno-sjCECE-sic03a arvacnc rvoa
>- fv
ouoooaNfcaoociocipoff
>-* iv - *- rv rv "
NOUIOJ -sJO03C
pm
o
ocrcncnccoocr^-'eoprv-ece-icn
rvi-oai-sj-vCDP'Oi
ru -
rvs-vuj0esop>N'fN>-c3'P-
iv rv n
tntcfvo'Cc:NcrtnPierv*Pteiv
UBS MONTH DAY YtAR TATICJN TIMfci TC IC TOC


TABLE OF CONTENTS
(Continued)
Page
Metabolism vs. Canal/Sampling Day
Characteristics 123
Exchange vs. Water Quality 126
Exchange vs. Canal/Sampling Day
Characteristics 126
Water Quality vs. Canal/Sampling Day
Characteristics 130
Summary 138
Regression Equations 140
CHAPTER 6 DISCUSSION 155
Metabolism 156
Water Quality. . : 164
Nutrient Exchange 171
General Observations 178
"Average" Canal ....... 179
Design and Management Implications 183
CHAPTER 7 CONCLUSIONS. 193
LIST OF REFERENCES . 196
APPENDIX A Oxygen metabolism data for all individual stations. 201
APPENDIX B Oxygen profiles for all stations and sampling
times 211
APPENDIX C Nutrient and water quality data for each canal
entrance and sampling interval 235
APPENDIX D Descriptive statistics and correlation coefficients
for all parameters 276
BIOGRAPHICAL SKETCH. 327
v


-188-
of extremes. They have varying water qualities and different types of
interactions with the adjoining estuaries. The ultimate questions
from a coastal zone management standpoint are: Should any more resi
dential canals be constructed? and What should be done with existing
canals? Some considerations concerning canal construction in the
coastal zone, other than those outlined in the literature review,
should be mentioned.
Instead of viewing canal systems as simple extensions of an estuary
in which water quality must be maintained for recreational purposes,
canal systems might be considered as semi-natural treatment units.
From a planning standpoint, the problems of stormwater runoff and
wastewater management may be somewhat alleviated by including canal
systems that give additional treatment to the wastewater and stormwater
before it enters the estuary. If it is assumed that the land around an
estuary will be developed and that the stormwater runoff and wastewater
will eventually reach the estuary, what will be the net effect on the
estuary if canals are constructed through high ground or in place of
wetlands?
Several researchers have recommended that central sewer systems
be installed in canal developments and that the sewage effluent and
stormwater runoff be routed away from the canals. Presumably, by
eliminating the possible septic tank leachate into the canals and
keeping street-runoff away from the canals, better water quality could
be maintained. Such reasoning seems intuitively correct. The data
collected during this study, however, do not substantiate this theory.
Canal developments with a central sewer system were found to have
higher Secchi depths; but, they also tended to have higher planktonic


-5-
relationships among 20 response parameters (metabolism, net-exchange,
and water quality) and their significant explanatory factors (canal
physical attributes, estuarine water quality, and local tidal dynamics).
The analysis did not provide the mechanistic relationships for the
response and explanatory variables but did, however, identify and
quantify the associations among the response parameters and the ex
planatory factors. Since the regression equations have been derived
from data on existing canals, they constitute a foundation from which
future workers can develop canal design criteria, canal management
policies, and mechanistic theories for the controlling factors in
canals.
This study substantially increases the data base for the conditions
within Florida residential canals, provides heretofore lacking infor
mation on the exchanges of materials between canals and estuaries, and
presents equations that can be cautiously used to estimate the condi
tions and behavior of existing or future canal systems. It does not,
however, attempt a total evaluation of the ecological and socioeconomic
impacts of residential canals in the coastal zone.


-294-
CURRELATIUN CUEFF Id ENTS / PRUb > Jfij UNDER HORHU-O / NU
MUER UF OBSERVATIONS
D T UP
DTUP
1. ooooo
0.0000
50
DT P
0.60103
0.000 l
56
ETUP
-0.30500
0.0279
52
utc
0.30318
0. 0231
5o
SILL
0.28198
0. 05 1 l
56
EOP
-0.25092
0.0621
56
ETP
-0 .24399
0.0700
56
YEAR
0 .23021
0.0878
5b
DT C
0.22 544
0.0948
56
DCuND
- 0.2202l
0.30 1 2
2 a
DAY
0.21451
0.1124
56
TEMP
-0.204 88
0.1335
55
AGE
0. 19401
0.1519
56
FT UP
0.18793
0.1821
52
FTP
-0.17956
0.1854
56
BULK
-0.17745
0.1907
56
ECUND
0. 1 752 5
0.4127
24
FNH3
-0.1 7338
0. 20 13
56
ENH3
-0173j6
0.2013
56
MAXD
-C 16872
0.2182
55
0 TUR B
0.16116
0.2738
48
MI NOU
0.15497
0.2586
55
SLCCH l
-0. 14871
0.2 785
55
ECCJLUk
- 0.1 4 5 16
0.359 0
42
FTC
0.1 4 A 85
0.2868
So
F C U ND
0. 14261
0.5062
24
FOP
-0. 1 4235
0.2953
56
POPPM2
0.13671
0.3386
51
SUN
-0. 131 62
C 3572
51
MINRES
0.12787
C.3476
56
AV GUU
0.12149
0.3769
5 5
AR EA
0.10964
0. 42 12
56
UUP
-0.1 0573
0.4380
bo
VOLUME
0.10162
0.4 561
56
PPRM3
0.09666
0.4998
51
f TUC
0.09578
0.4825
56
7 PR
0.08893
0.5434
49
F. T UC
0.08707
0 .523a
bo
ETC
0C 80 65
0.5254
56
S E W LK3
0. 0 83 6 7
0.5403
56
FT U R B
G.08285
0 .5 756
48
F C L 0 R
-0.08036
0.6129
42
DAY L.
- 0.0 80 2 1
0.5568
56
CURBS
0.06901
0.6133
5 6
PPR
0.0 68 76
0.6317
51
LENGT H
0.06837
0.6166
66
F IC
0.05695
0.O76 7
56
WIDTH
0 .05468
0.68 79
56
DNH J
0.05027
0. 71 2 9
56
CUMTIOE
-0.04716
0. 7300
56
MUEPTH
0.04522
C. 7407
56
T GPP
0.0 42 75
0 7o58
5 1
DTOC
C. 03507
0.79 75
56
PUMIN
0.03115
0.8317
49
T I DE
-0.02 693
0 .8438
5 6
TR
0. C22 4 9
0.8755
5 1
MONTH
-0.01977
0.8850
56
ETURU
-0.01641
0.9119
48
E IC
0. 0l552
0.90Vu
50
DCOL OR
0.0 1 172
0. 941 3
42
PR M2
0 .00518
0. 9712
5 1
PGPPM3
-C .0 0470
0.9739
5 1
DEVEL
0 .0040 4
0.9764
56
FNH3
FNH3
1 .00000
0.0000
71
ENH3
1 .00000
0.0000
7 1
ECOLOR
0.54478
0.0002
4 2
FC OLOR
0.60649
0. OC C6
42
DEVEL
0.386 4 8
0.0012
68
BULK
C .30225
0.0152
64
E TP
0 .24501
0.03 95
71
SECCHI
-0 .2288 1
0.0869
57
FTP
0.21949
0.0659
7 l
MONTH
C.21810
0.067 7
71
DAY
-0.21078
0.0 7 7 7
71
UAYL
0 20o*82
0.0791
71
U7 P
-0.20159
0.0993
68
ECUND
-0.19981
0.3492
24
EOP
0.1 92 C7
0.1486
58
FCND
-0.19039
0.3729
24
7 PR
0.184o0
0. 194 7
51
AGE
0.1 7733
C. 1480
6 8
DNH3
0.17426
0.1521
69
U TOP
-0.17338
0.2 013
56
SI LL
-0.16092
0. 1933
67


-104-
that the metabolic parameters, canal age, local tidal dynamics, and to
a lesser extent the physical dimensions and nutrient levels of the
canals, carry the most weight in distinguishing differences between
the canals sampled. On the other hand the exchange parameters, basic
water quality parameters, and minimum residence times do not contribute
appreciably in explaining the variability between the canals.
The next three principal components explain an additional 35
percent of the total variance of the data set (13, 13, and 9 percent,
respectively). This brings the cumulative percent explained to 55
percent. In other words, only slightly more than half of the differences
between the canals can be explained by the differences in values of
these four linear combinations or factors.
Rather than to attempt to interpret the factors these lengthy
linear combinations represent, it is perhaps more useful and easier to
separate the data into the four subsets (metabolism, nutrient exchange,
water quality, and physical characteristics) and to evaluate the im
portance of the individual parameters in determining canal differences
for each of these types of attributes.
Three principal components were extracted from the correlations
matrices of the four subsets. The eigenvalues, eigenvectors, and
correlation matrices for each of the subsets are shown in Tables 14-17.
Metabolism
The first principal component (Table 14) of the metabolism subset
accounts for 40 percent of the total variability of this set. This
component appears to be associated with the general level of canal


-89-
Table 9. (Extended)
September
November
Location Means
TOC
TOP '
nh3
TOC
TOP
nh3 '
TOC TOP NH3
1.5
-0.009
-0.01
0.1
0.001
-0.04
0.3
-0.019
-0.01
0.2
-0.011
0.04
-0.3
0.009
-0.02
-0.6
0.008
0.01
-0.8
0
0
4.6
0
0.01
0.7
-0.003
0
0.5
-0.008
f-H
*1
O
1
-0.1
-0.010
0.01
0
-0.008
-0.02
0.5
-0.008
-0.01
0.4
0.001
-0.01
0.1
-0.005
-0.01


-268-
UBS
MONTH
DAY
YEAH
ST AT ICJN
T I ME
IX
IC
TOC
96 1
7
1 4
76
AP3
23
43. 0
l 8. 6
24.4
962
7
1 4
76
AP 3
24
35.8
17.9
17.9
963
7
1 5
76
AP 3
1
37.2
18.3
18.9
964
7
1 5
7 6
AP 3
2
48.8
11.0
3 7.8
965
7
1 5
76
AP 3
3
40.0
10.7
29.3
966
7
15
76
AP 3
4
40.3
11.9
28.4
967
7
1 5
76
AP 3
5
39.3
12. 1
27.
968
7
1 5
76
AP3
6
40.1
19.0
2 1.1
969
7
15
76
AP3
7
39.5
16. 5
21.0
970
7
1 5
76
AP3
8
4 1.9
12.6
29.3
971
7
15
76
AP 3
9
42.7
25.7
17.0
9 72
7
1 5
7 6
AP 3
10
39.0
12.3
2b 7
973
7
15
76
AP3
1 1
44 .6
12.5
32.1
974
7
l 5
76
AP 3
1 2
4 0.3
13.9
26.4
975
7
1 5
76
AP 3
13
38.7
12. 3
26. 4
976
7
1 5
76
AP 3
14
40.2
13.3
26.9
9 77
7
l 5
76
AP 3
15
37.0
13. 7
23.3
9 78
7
1 5
76
AP 3
1 6
37.1
19.4
17.7
979
7
1 3
70
6b 1
16
31 .0
14.9
16.0
980
7
13
76
63 1
l /
32.3
1 5. 8
l 6.5
98 1
7
l 3
76
Gb 1
18
30.3
15.4
14.9
982
7
l 3
76
63 1
19
32.0
15.0
17.0
983
7
l 3
76
GB 1
20
3 1.7
1 5. 4
16.3
9 84
7
1 3
76
6b 1
2 1
30.1
15.6
14.5
985
7
1 3
7 6
63 1
22
31.9
14.5
17.4
966
7
13
76
GB 1
23
28.6
1 4. 7
13.9
9 87
7
1 3
76
Gb 1.
24
4 5'. 1
13.8
31 .3
988
8
1
76
Gb 1
1
44.3
13.4
3 0.9
989
8
1
76
Gd 1
2
25.9
13.8
12.1
990
8
1
76
Gb l
4
28.7
15.7
13.0
BS
TP
OP
1 UP
T UR B
NH3
CULOH
DS
COND
96 1
0.780
0.731
0.0<+9
5.6
0.02
147
-0.14
2 72
962
0.805
0.697
0.106
6 .2
C 02
1 39
0.14
269
963
0.810
0. 722
0.085
4.6
0.0 7
1 28
0.4 1
266
964
0.792
0. 755
0.037
7.0
0.10
1 J 6
0.44
268
965
0.823
0. 74 0
0.083
4.7
0.06
103
0.31
276
9 66
0.807
0 736
0.071
9. C
0.0 6
123
C 1 8
2 71
96/
0.605
0.702
0.103
3 .5
0.02
1 03
0.08
270
968
0. 775
C. 765
0.010
3.9
0.06
169
-0.08
270
969
0.787
0.744
0.043
5.0
0. 05
128
-0.17
2 71
970
0.808
0.385
0.133
3.5
0.02
107
-0.27
266
971
0 .847
0. 76 3
0.064
5.7
0. 03
98
-0.24
2 62
9 72
0.917
0.749
0.166
5.1
0.0 7
1 l 6
-0. 17
261
9 73
0.863
0.722
0.141
6.7
0.05
1 37
0.03
269
9 74
0 .843
0.707
0. 1 36
7.5
0.06
l 62
0.28
2 69
975
0.927
0.728
0.199
7.0
0.07
1 25
0.35
2 70
976
0.918
0. 73 7
0.181
6 .8
0.04
1 34
0.40
2 60
97 7
0.840
0.72 0
0.120
3.6
0. 02
96
0.25
2 63
978
0.797
0.779
0.0 18
3 .9
0.02
1 04
0 10
2 77
97 9
0.027
0.020
0.007
2 .9
0.09
1 1 7
-0 .06
269
980
0.028
0.018
0.010
3.1
0.17
132
0.0 l
2 O 7
98 1
o. 02 a
0.01 7
0.0 l 1
3.1
0.06
120
-0.08
276
982
0.030
0.030
0.000
4.8
0.05
1 2 1
-0.12
267
983
0.030
0.016
0 l 4
2.6
0.14
124
-C.05
274
984
0.0 28
0. 0 l 0
0.018
3 .2
0.04
1 13
-0 .07
269
985
0.035
0.010
0. 025
2.6
0. 1 3
120
-0.05
269
986
0.017
0.017
0.000
2.7
0.03
1 18
0.23
2 66
987
C 033
0.017
0.016
2.5
0.09
102
0.09
266
988
0.023
0.023
0. oco
2.4
G. 0 H
93
0.07
261
96 9
0.017
0.017
0.000
2.9
0.14
1 1 /
0.11
26o
990
0.017
0.017
o.ooc
2.2
0.09
9 7
-0 .07
73


' 0-77
ACKNOWLEDGMENTS
Numerous individuals, to whom I am much indebted, helped me with
the field collections. During- the 1975 collections, William Marsh,
Deborah Lupton, and Warren and Ann Hansen forfeited many hours that are
normally devoted to sleeping. Florinus Kooijman volunteered to accom
pany me to Marco Island and Boca Ciega Bay; David Price to Hillsboro
Inlet and Panama City; and Richard Brightman to Apollo Beach.
The members of the department's chemistry laboratory, particularly
Hugh Prentice and Lloyd Chesney, were invaluable as troubleshooters
when I was having problems with water analyses. Without the Department
of Environmental Engineering Science's truck and boat, and without
Dr. Patrick Brezonik's ability to keep the chemistry laboratory stocked
with chemicals, I would have been unable to collect and analyze samples
during 1976.
I am grateful to Dr. B.A. Christensen and Fred Morris of the
Hydraulic Laboratory, Department of Civil Engineering, for providing me
with the 1975 hydrographic data and for loaning me a tide recorder
during 1976. I am also grateful to Dr. Emmett Bolch for providing me
an assistantship on his Florida Power Corporation Project during 1976.
I would like to thank my committee members for their comments and
guidance throughout this investigation. Dr. Jackson L. Fox, my chairman,
has spent many hours listening to my problems. His efforts are greatly
appreciated.
ii


-288-
CORRLLATlON COEFFICIENTS / PRUB > | R | UNDER H0:RHU=0 / NU
Mb ER OF OBSERVATIONS
FTP
F TP
1.00000
0.0000
71
ETP
0.99344
0.000 1
71
EUP
0.9842 0
0.000 l
58
ET UP
0.73914
0.0001
54
F T UP
0.72914
0.000l
54
W I DT H
0.48098
0.00C1
7 1
FOP
0.44262
0.0005
58
SEW EKS
0 .43 765
0.0001
71
FIC
- 0.423 6 0
0.0009
58
SUN
0.41333
0.002 1
53
E 1C
-0.4 01 92
0. 0C1 6
58
ECLUK
0 .38525
0. 01 18
42
ECUND
-0.38193
0.0 655
2 4
DUP
0.37809
0.00 4 1
. 56
ETC
- 0 .37596
0.0036
6B
FTC
-0.37126
C.004 1
58
FCUND
-0.35992
0.0841
24
FCLUR
0.31612
0.0414
42
TR
0. 31247
0.022 7
53
DAY
- 0. 30 707
0.0092
71
ETURB
0.294 03
0.0382
50
FTUK
0.27755
0.0510
50
TGPP
0.27089
0.0498
53
D U
0.2 654 a
0.0460
5b
MAX DU
0.25445
0.0335
70
BULK
C .24251
0. 0535
64
AVGDO
0.23443
0.0 50 8
70
DEVEL
0.22393
0.0664
68
ENH3
0.219 49
0.0659
71
F NH 3
0.21949
0.0659
7 1
LENG1 H
0.203C0
0.0695
7 1
F I UC
0.20181
0.0915
71
MINRES
-0. 194 02
0. 1050
71
PPRM3
0.19365
0.1643
53
SECCH1
-0.1 8426
0.1700
57
DTOP
-0.17956
0.1854
56
El UC
0. 177d 9
0.1 3 7 a
7 1
VOLUME
0.14765
0.2191
7 1
AH E A
0.14356
0.2323
71
DT UC
C 1 34 69
0. 2698
69
DC UNO
0.1 3 3 6 6
0.5335
24
PR M 2
0.13326
C* 34 1 5
53
rpR
-0.12134
C.3963
5 1
MEPTH
-0.11592
0.3357
7 1
TIDE
0.11004
0.3o 1 0
71
DT P
0. 1 0999
0.3719
b8
PDUM1N
-0.10910
0.44 60
51
DTURB
0.10 1 02
0.4945
48
PGPPM3
0.09C94
0.5173
53
S I LL
- 0. C84 09
0 .4987
67
CUMTIDE
- 0.05941
0.6226
7 1
V EAh
- 0. 05 8 74
062b 5
71
PGPPM2
-0.040 1 1
0.7755
53
C UR 8 3
-0.0 37 35
0. 7571
7 1
DTC
-0.0365l
0.7893
5,6
DNH 3
0 .029 79
0.8080
69
PPK
-0-. 02 1 97
0.6759
53
TEMP
0.02093
0.8635
70
ACE
0. 01 928
0.8 760
68
MONTH
0.00833
0 94 5 0
71
UAVL
0.00871
0.9557
7 1
DCULUR
-0.00206
0.9897
42
MINUO
0.000 69
0.9955
70
TP
E TP
1.00000
0.0000
71
FTP
0.99344
' 0.0001
7 l
EUP
C.98644
0.000 1
56
ETUP
0. 7 5 737
C.0001
54
FI UP
0.7076l
0.0001
54
W I DT H
0.47262
0 .000 1
7 1
F OP
0.44b3 8
0.0004
58
F IC
-0.41451
0.0012
58
'SEWERS
0.41413
C.0003
7 1
SUN
0.3 9505
0.0034
53
EC UL UR
C .36952
0. 01 08
42
L1C
-0.38885
0.0026
58
ECUND
-0.36699
0.0 61 7
24
ETC
0.36526
0.0048
58
F TC
-0 .363 72
0.0050
5b
FCUND
-0 .3632 6
0.081C
24
lH
0.32777
0.0166
53
F C UL UR
0.31616
0.0414
42
ETUFb
0. 3 1 544
C .0257
50
DUP
0.30570
0.0220
5 6
DAY
-0.2 99 79
0.0111
71


-185-
the canals; this can induce circulation and more homogeneous conditions.
Homogeneous conditions favor higher average oxygen levels and more
turbid surface waters; hence, the export of turbidity and the lower
Secchi depths. Mixed conditions also enhance.the aerobic digestion of
organic detritus entering the canals; this results in the greater total
respiration levels and the greater tendencies for such canals to be
sinks for organic carbon.
Canal depth is an important factor; but, depth effects are not
straightforward. Increases in canal depth lead to lower average water
velocities and more particle settling for a given canal size and loca
tion. As a single factor, depth is positively associated with increased
organic carbon retention, higher average dissolved oxygen levels, and
lower plankton respiration. Evidently, higher oxygen levels are
maintained in the water column as a result of organic matters sinking
and a concomitant reduction of heterotrophic respiration. However, the
effect of depth is not quite so simple.
The effect of the significant interaction between canal depth and
cumulated tidal amplitude has already been shown for the dissolved oxygen
equation. Greater depths result in higher average oxygen levels and
organic carbon retention rates, whereas the depth cumulated tidal
amplitude interaction term has the opposite effects. When the cumulated
tidal amplitude is high, turbulence and mixing in the water column is
enhanced. Better vertical mixing keeps the suspended material from
settling; whereupon, more heterotrophic respiration occurs in the water
column and lowers the average dissolved oxygen level.
It has been generally thought by many investigators that good
mixing and flushing result in good water quality, particularly from a


MONTH DAY YEAR bI AT I ON T Mh TC IC TOC
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AJ
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-i(M;0jfin/)MIOO''!'inin)N3 3'O- a o r- a- r n n n n n r. n ce co so o'
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a o o o a o >0 oon.nnnnn-nnnxbj'
3 :r)

-170-
impossible to establish a generally applicable optimum design for
residential canals. The background conditions of the local estuary
must be specified before canal design features can be addressed with
these models. For example, the appropriate canal depth for the
maximization of the average dissolved oxygen concentrations is highly
dependent on the cumulated 24 hour tidal amplitude in the area. By
considering just the contribution from the DEPTH and DEPTH *CUMTIDE
terms in the AVGDO model in Table 27 and different values for DEPTH
and CUMTIDE, this point is well illustrated:
Effect n AVGDO = +0.90 DEPTH 1.1 DEPTH *CUMTIDE
EFFECT (mg/1 02)
+0.7
+1.05
+1.4
-0.4
-0.6
-0.8
-1.5
-2.25
-3.0
DEPTH (m)
2
3
4
2
3
4
2
3
4
CUMTIDE (m)
0.5
0.5
0.5
1.0
1.0
1.0
1.5
1.5
1.5
In addition to the product of depth and cumulated tidal amplitude
being a significant factor, the ratio of the two parameters is also an
important consideration. The canal minimum residence time, as used in
this study, is essentially the canal depth divided by the cumulated
tidal amplitude (actually, the canal volume divided by the cumulated
exchange volume but the common dimension of canal surface area cancels
in each term). The product of canal minimum residence time and
percent-development was found to be a significant factor affecting the


Table 33. Organic
carbon net-exchanges
for several coastal
systems.
System.Type
Location
Organic Carbon
Flux'1"
Units
Source
Mangrove
South Florida
-0.9
ppm
Stanford (1976)
-4.48
gm C/m -day
II
-0.59
It
Heald (1969)
Puerto Rico
-1.14.
II
Golley et al. (1962)
-1.37
II
Snedaker and Lugo (1973)
Big Cypress Swamp
South Florida
+0.8
mg/1
Carter et al. (1972)
(River)
+0.3
1
II
+3.2
II
II
-1.0
. 1!
n
Drainage Canal
South Florida
-0.3
II
it
-0.5
If
it
Tidal Marsh
Patuxent River
-0.4
mg/1 particulate C
Heinle and Flemer (1976)
(low salinity)
(Maryland)
Salt Marsh
Georgia'
-292
gm/m2-yr
De la Cruz (1965)
(see Heinle and Flemmer,
1976)
Residential Canals
Florida
-5.9 to +10.0
mg/1
This study
mean +0.2
mg/1 +L
II
(or gm C/m -day)11
t Positive sign shows net flux into system; negative sign, the reverse
it Using average canal dimensions and exchange volume
-174-


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(VI
O'
N
JriS MONTH UAY YEAR -SIATIGN TIME 21 O1 22 2


-286-
CORRELATION COEFE IC1 ENTS / PROD > |RJ
Mu ER OF OBSERVATIONS
UNDER HO:
RHO= 0 / NU
FT UC
DAY
0.26119
0.02 78
7 1
DAYL
-0.25653
0.0308
7 1
DTUC
0.22663
0.0569
69
C UR BS
0. 22256
0.0621
71
PUPPM3
0.22086
0.1120
53
MI NR LS
0.21636
0.0673
71
ore
0.21124
0.1 1 8 1
56
ET P
0.20466
0.0869
7 1
FTP
0.2018 1
0.0916
7 l
ETURB
0.20113
0. 16 12
50
BULK
-0.1 82 76
0.1483
64
LEVEL
0.18070
0. 1 4 03
68
DIC
-0.17844
0.1882
56
FTURB
0.15570
0.2603
5 0
PPR
0.16400
0.2709
53
MAXDQ
0.16016
0.2147
70
VOLUME
0.1402 7
0.2 7 1
SECCH1
-0.13891
0. 30 28
5 7
FNH3
0. 1 3371
0.2663
71
LNH3
0. 13371
0.2663
71
DNH3
0.13354
0.2740
69
LENGTH
0.13215
0.2719
71
AREA
0.11893
0.3232
7 1
. FUP
0 114 4 4
0. 3923
56
DC LUR
-0.10814
0. 4954
42
F 1UR
0.10063
0. 4691
54
D TOP
0.09578
0.4825
56
MINDU
0.08877
0.4649
70
E TOP
0 .082 37
0.5538
54
SUN
0.06471
0.6452
53
TIDE
0.05756
0.6334
71
Tk
0.0 52 83
0.7071
53
UOP
-0. 04 95 3
0.7170
66
CUMT IDE
0.04296
0 .7220
71
MONTH
-0. 034 75
0.7736
71
DTP
-0.02151
0.8618
68
DTUKB
C 0 1 762
0.9054
48
E COL UR
C.01017
0.949 0
42
FCULUR
C. G09C8
0.9545
42
EUR
-0.00892
0. 94 7 0
5d
AVGDU
-0.00494
0.9676
70
DCOND
-0.004 90
0.9819
24
L TOC
ET U C
l.COOOO
0.0000
7 1
FTDC
0.96564 -
0.0001
7 1
FCuNU
0 65333
0.0005
24
L CUND
-0.65087
0. 0006
24
YEAR
0.5718C
0.0001
71
ETC
C 49619
0.0001
58
F TC
0 .46599
0.0002
58
TPR
0.46153
0 .0007
51
PGPPM2
0.45625 -
0.0006
5 3
El C
0.4 429 7
0.00C 5
56
F 1C
-0.42026
0.0010
58
3 ILL
0.4 1682
0.0005
67
PDQMIN
0.352 75
0.0 l 1 1
5 1
MDEPT H
0.33810
0.0039
7 1
PRM2
0.3364 7
0.0138
53
T EMP
-0.32701
0.0057
70
AOE
C.32690
0.0065
66
V. I D 1 It
0.31245
0. 0C6G
7 1
PPR M3
C 31233
0.0226
53
SEwER S
0.31C19
0.0085
7 1
DAY
0.30 184
0.0105
71
DA YL
-0 .26799
0.0239
71
T GPP
0 2 52 5 6
0.0681
5 3
MINRE5
0.22765
06 6 0
71
DE VEL
0.2 0 33 7
0.09 62
6 8
CURBS
0. 1 6874
0.1l5C
71
ETP
0. 18472
0.1230
7 1
FTP
0.17789
0.1376
71
ETURB
0. 1 76 13
0.2211
50
POPPM3
0. 1660 2
0.2348
53,
FTURb
0.16315
0.257o
50
VOLUME
0.14737
0.2201
7 1
MAXDQ
0.144 68
0.2321
70
DNH3
0.14405
0.2377
69
LENGTH
0.13913
0.2472
7 1
AREA
0.12858
C.2852
71
BULK
-0,12 780 -
0.3142
64
DCULL'k
0.11409
0.4/ly
42
F NH3
0.11206
0.3622
71
LNH3
0.11205
0.3622
71
SEC CH1
-0. 10653
0.4216
57
FT OP
0.10814
0.4363
54


-280-
CURRELATIUN COEFFICIENTS / PKUb > |R| UNDER HO:RHO=0 / NU
MUER OF OBSERVATIONS
DAY
FIC
- 0.2 52 73
0.0556
58
T IDE
-0.24972
0.0319
7 4
AREA
-0.22761
0. 05 1 1
74
SILL
0.224 15
0. 0621
70
DA YL
-0.22373
0.0553
74
MINRES
0.22159
0.0578
74
DT P
0.21451
0.1124
5 6
F NH 3
-0.21078
0.0777
71
E Ni 13
-0.21078
0.0777
71
F T P
-0.20640
0 1 3 4 3
54
VOLUME
-0.2 0512
0.0796
74
NiA X D 0
-0. 19860
0.0921
73
FP
-0 1 8 729
0.1592
58
BULK
-0.1 8308
0. 1381
67
AVGU
0.17848
0.1053
73
UOP
-0.15872
0.2427
56
Die
0.15411
0.2568
5o
0 I G
-0.13899
0. 2547
69
0 TUR
0.1 36 23
0. 34 6 7
48
PPRM3
-0.13603
0.3175
56
SUN
0.12608
0.3545
56
SE CCUI
0.11803
o 3 y i
60
PR M2
-0.11644
0.3928
56
PPR
0 11346
0.4093
5 6
MDLPTH
0.10697
0.3 554
74
St*ERS
-C. 10195
0.3874
74
PGPPM3
-0.08951
0.5118
56
CUR BS
0.08798
0.4560
74
F1URB
-0.07371
0.6109
50
DNH3
0.0 72 96
0.5513
69
dt e
-C 072'f 0
0.5959
56
ftg
-0.06252
0. 64 1 1
58
A ID TH
0 05873
0. 61 92
74
DTP
-0.05562
0.6512
68
AGE
0 .0 54 72
0.6504
7 1
l Te
-0.05364
0.6892
58
TPR
0.04918
0.72 3 9
5 4
PGPPM2
0.04112
07633
56
DEV EL
-0.0 3350
0. 78 1 5
71
DGND
-C.02970
0.8904
24
ETUR B
C. C2620
0.8567
50
CUMTI DE
-0.01 91 3
0.8715
74
YEAR
YEAR
1 00000
0.0000
74
F TOC
0.5854 8
0.000 l
71
ET u
0.57160
0.0C0 1
71
LCLUR
-0.42720
0.004b
42
M I N U
0.4 1801
0.0CC2
73
FGULOR
-0.40397
0.0080
42
SEVERS
0.356 98
0.0017
74
E OP
-0.35653
0.006 0
58
MINRES
0.35106
0.0C22
74
BUCK.
0.3 2 6b 5
0.0 Cb 9
6 7
AVGU
0.32424
0. 0051
73
ilDlh
0.323 13
0.0050
74
MONTH
-0.2/761
0.0166
74
DAY
0.27132
0.0194
74
e un u s
0.26167
0.0243
74
PPR
-0.25789
0.0550
56
DCULUR
- 0. 23549
0.1333
42
DT P
0.23021
0.0678
56
e r cjh
-C.2651
0.0995
54
LIG
-0. 22 005
0.0970
58
F 1 C
-0.21519
0.1048
58
T I DE
-0.20907
0.C738
74
DUP
-0.19755
0.1445
56
SILl
0.19747
0. 1013
70
p Te
0.1956y
0. 14 10
58
PGPPM2
0.1 94 0 8
0.1516
56
NH3
0. 16 264
0.1 326
69
E TC
0.1 6262
0. 1700
58
LLNG TH
0.17447
0.13 71
74
TGPP
0 16 943
0.2119
56
MDEPT rl
C 1 688 3
0.1304
74
PR M2
0. 1 68 73
0.2130
5 6
AR t A
0. 1 6423
0.1620
74
VOLUME
0. 15 8 14
0.1784
74
CUMTI DE
-0.15809
0.1785
74
DTURD
-0.13o89
C .2 86 9
48
TEMP
-0.15555
0.1888
7 3
DEVEL
0. 1536 2
0.2009
7 1
DA YL
0.15043
0. 20 08
74
DTC
0.12270
0 J o 7b
56
d roe
0.12128
0.3209
69
FT UP
-0.11626
0.40 2 5
54


-52-
Table
OBS
3. (Continued)
CANAL MONTH
DAY
YEAR
TGPP
TR
PGPPM2
29
PG9
1 1
21
75



JO
PC3
1 1
23
75
9.33
9.91
2.04
31
PC6
11
23
75
8.49
4.52
3.43
32
PC9
11
23
75



33
PB6
1 1
1 4
75
3. 39
3.06
3.45
34
PB9
1 1
14
75



35
PB3
11
14
75
3. 45
3.09
2.96
36
LX3
1 1
16
75
5.09
4 .60
2.87
37
LX6
11
16
75
3.42
3.67
3.03
38
MI 1
3
24
76
5. 86
5.72
5. 64
39
MI 2
3
2*4-
76
7.11
7.20
3.46
40
MI 3
3
24
76
9. 79
11.19
3.94
41
BC1
4
20
76
24.89
18.65
8. 04
42
BC2
4
20
76
16.30
14.30
8.61
43
BC3
4
20
76
1 5. 40
14.19
13.50
44
HI 1
5
19
76
7.65
2 .66
6.46
45
H I 2
5
1 9
76
7. 53
. 2.55
7.43
46
H 13
5
19
76
1 4. 79
5.65
23. 90
47
FL1
6
1 2
76
8.34
8 .63
3.19
48
FL2
6
12
76
1 2. 69
12 .69
2.9 1
49
FL3
6
12
76
8. 66
11.22
4.12
50
AP l
7
14
76
21.84
19 .89
4.00
51
AP2
7
1<4
76
15. 22
16.34
7. 71
52
AP3
7
14
76
10.63
10.82
3.30
53
GB1
7
31
76
1.56
2.86
1.20
54
GB2
7
31
76
2. 27
3. 57
0. 77
5b
GB3
7
31
76
1.95
2.15
0. 96
56
KC 1
8
18
76
5. 53
9.39
1 .39
OBS
PR M2
PGPPM3
PPRM3
TPR
P PR
POOMIN
SUN
29







30
0.74
2.01
0.56
0.94
1 .98
0.22
334
31
0.53
2.93
0.06
1.86
5.02
0.41
334
32







33
1.92
1 .39
1.51
1.11
1.79
1.02
352
34







35
1 .96
2.7 1
1.57
0.90
1.76
0.47
352
36
0.92
2.96
0.70
1.11
3.45
0.56
204
37
1 .49
3.10
0.93
1.13
2.04
0.78
204
38
3.67
6 .38
1.49
1.02
1.54
0.96
520
39
2.91
2.99
1 .27
0.99
1.19
0.49
520
40
4.9 1
3.40
1.56
0.87
0.80
0.40
520
41
4.35
4.81
1.54
1.33
l .64
0.32
571
42
3.20
4.41
1.37
1.14
2.69
0.53
57 1
43
5.24
6.02
1.68
1.08
2.58
0.88
5 71
44
2 .47
5.55
1.76
2.87
3.76
0.84
5 15
45
2.99
5.15
1.93
2.95
2.48
0.99
5 15
46
6.16
18.00
3.10
2. 62
3.81
1.00
51 5
47
3.92
3.26
2.17
0.97
0.6 1
0.38
504
48
4.98
1.77
1.75
1.00
0.58
0.23
5 04
49
3.48
3 .25
1.01
0.77
1.18
0.46
504
50
3.94
3.96
2.40
1.10
1.02
0.18
506
51
3.75
10.64
2.66
0.93
2.05
0.5 1
50 6
52
2.95
4.22
2.04
l .00
1.12
C .30
5 06
53
1.45
1 .67
1.62
0.55
0.83
0.77
554
54
0.74
1.18
1.12
0.64
1.04
0.34
554
55
0.46
1 .34
0.21
0.91
2.09
0.49
554
56
2.0 1
0.87
0.86
0. 59
0.69
0.25
72


-93-
observations versus those of the single North Miami canal are 2.0 versus
0.9 mg/1 for total organic carbon exchange, 0.014 versus 0.001 mg/1
for total organic phosphorus exchange, 0.05 versus 0.03 mg/1 for ammonia
exchange. The results in Table 11 suggest that the daily variations in
exchange behavior are not as large as the seasonal variations.
Water Quality
In addition to the metabolic characteristics and nutrient con
centrations of the canals, several other water quality parameters were
measured for each canal. The average dissolved oxygen concentrations
were computed from all the oxygen values recorded in each canal. The
minimum and maximum dissolved oxygen concentrations, the Secchi depths,
and the water temperatures were also recorded for each canal. The
nutrient/water quality parameters determined for the exchange studies
are shown in Table 12 for every canal observation.
The frequency distributions and descriptive statistics for the
weighted-average ebb concentrations of the carbon forms, phosphorus
forms, ammonia, and turbidity have been presented in Figures 21-28.
The frequency distributions and descriptive statistics for the average
and minimum dissolved oxygen concentrations, and Secchi depths are
shown in Figures 29 and 30, respectively.
The average dissolved oxygen concentration of all the canals was
5.58 mg/1, with a standard deviation of 1.50 mg/1 and a range of 1.78
to 9.07 mg/1 (Figure 29a). The frequency distribution shows that most
of the canals observed had an average dissolved oxygen level of 4 mg/1
or greater.
The minimum oxygen values recorded in all canals had a mean value


-166-
distinguishing features of canal water quality. High phosphorus levels
characterize the canal systems in the vicinities of phosphate mining
industries, whereas elevated color levels identify the canal systems
with lower salinities and more freshwater inputs. Carbon and oxygen
concentrations provide the next level of differentiation of canal water
qualities.
The canonical correlation analysis of the water quality and the
canal and sampling day.characteristics demonstrated a substantial
association between the two types of attributes. Several of the nine
pairs of correlated factors seemed to couple certain geographical canal
locations and their characteristic features; while, others had more
general implications. The association of high phosphorus levels with
large, bulkheaded, and sewered systems is suggestive of the Punta Gorda,
Port Charlotte, and Apollo Beach sites. The association of older
canals with greater tidal ranges and.frequencies, and lower average
dissolved oxygen concentrations, identified the conditions in the North
Miami and. Pompano Beach sites. On the other hand, the association of
higher organic carbon and higher average oxygen concentrations with
the spring and fall seasons implies a general relationship resulting
from the reduced stratification and better mixing conditions during the
two seasons. The fact that canals with better mixing and flushing
(lower minimum residence times) have lower Secchi depths and higher
surface ammonia levels, suggests that well mixed canals have greater
surface turbidities and reducing conditions.
The association between older, deeper, more developed canals with
a sill and higher maximum and lower minimum oxygen concentrations re
flects the higher metabolic levels of these kinds of canals. Other


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MONTH DAY YEAR STATION TIME TC IC TOC


-176-
Table 34. Significant factor effects on canal-estuary net exchange
parameters.
DTC
DTOC
DOP
DTOP
DNH3
DTURB
DCOLOR
AREA
_
WIDTH
+
+
-
DEPTH
+
DEPTH*SILL
DEPTH*AGE
+
DEPTH*TIDE
. -
DEPTH*CUMTIDE
-
SILL
-
-
AGE
+
TIDE
CUMTIDE
-
-
MINRES
+
+
DEVEL
-
DEVEL*AGE
+
DEVEL*TIDE
-
-
-
+
DEVEL*CUMTIDE
+
+
DEVEL*MINRES
BULK
-
CURBS
-
SEWERS
+
DAYL
4-
SUN
+
+
FTC
+
+
+
+
FTOC
-
FTOP
-
+
-
-
FTOC*FTOP
+
4-
+
FOP
+
+
-
-
FNH3
FOP*FNH3
+
FTURB
-
-
+
FCOLOR
-
-
+
TURB*COLOR
-
4-
R -percent
86 82 39
88
52
90
90
Nomenclature and
Sign convention
units as in Table 2
as in Table 31 and Table
2 (for
direction
of net
movement)


324-
C(J PR ELAT I UN COEFFICIENTS / PKuB > |Hj UNDER H0:HHCJ=0 / NU
MBEH UF OBSERVATIONS
TIDE
1 IDE
1.00000
0.0000
74
PGPPM3
0.85677
0.0001
5 6
CUMT 1 Dt_
C.62011
0.000 1
7 4
MI NR fcS
-0.52530
0.0001
74
PGPPM2
0.473 1 5
0.0002
56
UULK
0.45349
0.00C1
67
PPR
0 .44862
0.0005
56
DEVEL
0.38406
C.00C9
7 I
PDUMI N
0.35482
0.C0Q5
54
PPRM3
0.31 79 1
0.0170
56
LENOIH
0.31094
0.0070
74
T PK
0.28496
C.0366
54
AREA
0.2 743l
C.0180
74
AGE
0.2 7403
0 .0208
71
FCOND
-0.26480
0.2111
24
ECN
-0.25998
0.2199
24
VOLUME
0.25552
0.0280
7*
ETC
0.25488
0.0535
58
DA YL
-0.25454
0. 0266
74
DAY
-0.24972
0.0319
74
TGPP
0.2 3566
0. Ob 04
56
PKM2
0.23342
0.C334
56
F COL UK
-0.23325
0.1371
42
MAXDu
0.22192
0.0592
73
F TC
0.21643
0.0995
58
ECULUk
-0.2l635
0.16 66
4 2
D I C
-0.21265
0.1156
56
YEAR
-0.20907
0.0738
74
V. IDT H
0.20591
0.0704
74
EUP
0.19780
0.1367
5 8
M I N DU
-0.1 871 7
0.1128
73
DN H3
0.1 85 97
0. 1260
69
T R
0.1 79 76
0. 185 C
56
SEWERS
0.16371
0.1634
74
FTUK
-0.1 5391
0.2659
50
ETUHB
-0.1 4 469
0.3 16 1
50
StCCH1
-0.14 184
0.279 7
60
DC ULUK
-0 1 331 1
0.4007
42
AV6DU
-0.12046
0.3100
73
tTP
0.1 1 1 58
0.3 6 4 2
71
FTP
0. 1 1 004
0.3610
7 1
DT C
-0.10586
0.43 75
56
SUN '
-0.10566
0.4383
56
ETUP
0.10289
0 .459 1
54
FUP
0. 10144
0.44(30
58
b 1C
0.0 9 438
0.48 10
58
MDEPTH
0.07449
0.5262
74
DTP
0.05821
0.6373
68
F rue
0.05758
0.63 3 4
7 1
MONTH
0.0 5 6 75
0.6311
74
ETUC
0.05526
0.64 7 1
7 1
DUP
-0.05011
0.7138
56
F 1 C
0.04909
0.7144
5 8
TEMP
-0.04J70
0.7 1 35'
73
F TUP
0.04146
0.7659
54
DT UC
-0.04007
0.7438
69
DT URB
-0.03780
0.7987
48
DC UNO
0 03685
0.8643
24
SILL
-C.03061
0.8014
70
DT UP
-C.026 93
0.8438
5 6
ENFI3
-0.01529
0.3993
71
FNH3
-0 01 52 9
0.899 3
7 1
CUR EIS
-0.00793
0. 9465
74
MINRE S
MlNRES
1.00000
0.0000
74
MDEPT H
0.71045
C.0001
74
T IDu
0.5 283 0
0.0001
74
SILL
0.5196b
C. 00 01
7 0
PPR
-0.86194
0. 0 08 7
66
year
0.35106
0.0022
74
CUMT I DE
-0 .3309 7
0.0040
7 4
E IC
-0.31816
0.0149
58
DCULK
0.29729
C.0559
42
in.
-0.28614
0 .0 28 j
5 6
POPPM8
0.2 68 o2
0.0453
56
PR M2
0. 2 5 4 G 6
0.0662
66
EOP
-0.23799
0.0720
56
BULK
-0.23679
0.0537
6 7
ETC
C.22785
0.0560
71
DAY
0.22159
0.0578
74
f rue
0.2103 d
0.0678
7 1
fc TP
-0.1 95 78
C. 10 18
71
FTP
-0.19402
0. 1 050
7 l
MI NDO
-0 ..1928 1
C 1 C 2 2
73
LENGTH
-0.19078
0.1 C35
74


-84-
Diurnal Cycle of Nutrient Concentrations
A diurnal cycle of nutrient concentrations in the canal and bay
waters could influence the estimates of the net direction and magnitude
of exchange. If a diurnal cycle were superimposed on the tidal cycle,
a bias in the estimate would result, particularly for those canals
where essentially only one ebb and one flood tidal phase occurred
during the 24 hour period. For example if planktonic primary production
during the daylight hours raises the levels of organic carbon in the bay
and canal waters, and if water continually floods into a canal during
the day, the rising levels of organic carbon would be recorded as
increasing flood phase concentrations. Then as photosynthesis stopped,
the tide reversed, and respiration continued, a decreasing organic
carbon concentration would be recorded for the ebb tidal phase. That
canal would be labelled a sink for organic carbon. Conversely a canal
could mistakenly be labelled a sink for organic carbon, when in fact
only a diurnal cycle was observed, superimposed on a tidal cycle having
predominantly ebb phase during daylight.
To determine whether diurnal cycles were occurring for the exchange
parameters that could bias the results, the mean concentrations of the
response parameters for all observations were regressed against the
hour of the day, transformed with a sine function. The transformation
(sin (0.2618 (Time 12))) was used so that a sunusoidal function with
a period of 24 hours, the minimum value at 0600 hours, and the maximum
value at 1800 hours, would result and would coincide with the diurnal
cycle. The results of these regressions are summarized in Table 8.
The only parameter observed to have a significant diurnal component


-114-
Canonical Correlations
The principal components analyses revealed that a high degree of
structure does not exist within the entire set of variables recorded,
nor within the four subsets. The lack of structure implies that all
variables are not highly correlated with all other variables (an ex
pected result). The next step in extracting the information contained
in the data is to evaluate the correlations of the individual parameters
and of the various types of data.
The correlations between the individual parameters, while not con
clusively demonstrating causes and effects, represent the associations
or covariances of variables. Evaluating these correlations can provide
insight into the interrelationships of the attributes of these canals.
However, several problems arise in attempting to extract much informa
tion from the correlation coefficients.
The first problem is the number of possible correlation coeffi
cients. With 64 variables in the entire data set, the total number of
correlations is 4096. The lack of significant correlations as well as
the signficiant correlations between the variables provides some infor
mation, but the task of extracting it becomes unmanageable. The second
problem with evaluating single correlation coefficients is that a true
correlation may not appear if one of the two variables in inversely
correlated with a third variable which may actually be controlling the
variable's level. The third problem is the likelihood of spurious or
illusory results, wherein a significant correlation seems like nonsense.
For example, the percent bulkheading within these canals was signifi
cantly correlated with the tidal range in the area (r = 0.45, P = 0.001,
N = 67). Such an association seems ridiculous, until it is recognized


-242-
BS
MONTH
U AY
Y t Af<
STAT IUN
TI M£
TC
IC
TUC
1 tl
6
1 9
75
PB 6
1 7
37.5
31.0
6.5
l 82
6
1 9
75
P66
20
43.0
2 8.0
15.0
l 83
6
19
75
PB 6
20
4 1.3
29.4
11.9
i 84
6
1 9
75
Pb 6
22
42.8
29.4
13 .4
1 85
6
19
75
Pd 6
22
42.3
28. 9
13.4
1 8t>
6
20
75
PB6
2
44.0
30.0
14.0
187
6
20
75
P8 6
2
42.3
30.0
12.3
1 88
6
20
75
Pd 6
5
43.2
30.0
13.2
189
6
2 0
75
PB6
5
32.5
30.0
2.5
190
6
20
75
Pd 6
8
4 6.5
32. 2
14.3
i 9 1
6
20
75
PB6
8
42.7
28.5
14.2
l 92
6
20
75
Pd 6
1 1
44.0
29.9
14.1
193
6
20
75
Pd 6
1 1
42.8
30. 1
12.7
1 94
6
20
75
PU6
1 4
43.0
29.8
13.2
195
6
20
75
Pd 6
1 4
46.0
29.4
16.6
1 96
6
20
7b
Pd o
1 7
43.6
30.0
13.6
197
6
20
75
Pd 6
1 7
44 .C
29.0
15.0
1 9 8
6
18
75
LX6
6
42.0
29. 0
13.0
1 99
6
18
75
LX6
8
39.0
30.2
8.8
200
6
1 8
75
LX o
l 2
56 .3
38.6
17.7
20 1
6
18
75
LX 6

50.0
35.0
15.0
202
6
1 8
75
LX 6
1 4
51 .8
40.0
11.8
203
6
18
7b
LX 6
l 4
32.6
29.4
3.2
204
6
i a
75
LX 6
l 7
46.5
35. 7
10.6
205
6
1 8
75
LX 6
1 7
49.3
33.0
16.3
206
6
1 8
7b
LX 6
2 0
4 9.2
33.0
16.2
20 7
6
1 8
75
LX 6
20
42.5
29.0
13.5
208
6
1 8
75
LX 6
23
53.3
35.3
16.0
209
6
1 8
75
L X 6
23
37.3
31 .2
6.1
2 1 0
6
1 9
75
LX 6
2
51 .0
37.8
13.2
DBS
TP
P
TOP
T KB
NH 3
CULUP
DS
CONO
18 1
0.220
0.178
0.04^
2 .7
0.00
85
168.
00
182
0.238
0.168
0.070
2.5
0. 02
62
-21 8.
00
1 83
0.238
0.165
0.073
2.6
C 03
1 12
-2 18.
00
184
0.215
0.172
0. 0 43
2.6
0.0 1
1 32
-248.
00 .
1 85
0.208
0.172
0.036
i o* oa
93
-246.
oc
1 86
0.217
0.183
0.034
1.6
0.09
ICO
1 76.
00 .
1 87
0.218
0.184
0. C 34
2.2
0.11
90
1 76.
00
1 88
0.252
0.186
0.064
1 .7
0.12
1 1 5
243.
00
1 89
0.218
0.176
0.042
2 .2
0.10
121
243.
0 0 .
1 90
0 .222
0. 1 82
0.040
1.9
0.13
90
- 19 8.
00
1 9 1
0 .220
0.195
0.025
2.1
0.13
121
- 1 98.
00 .
192
0.263
0. 178
0.0 85
1 .9
0.07
60
-260 .
00
1 93
0.263
0.185
0.07o
id % 3
0.06
1 l 7
-260.
00
t 94
0.260
0.178
0.082
id
0.03
92
148.
00
195
0.230
0.178
0.052
3.3
0.03
133
148.
00
1 96
0 .229
0.172
0.057
2.5
0. 02
91
22 7.
00
1 97
0.236
0.177
0.059
2.7
0.13
1 38
22 7 .
00
1 98
0.072
0.022
0. C50
2.8
0.06
97
-107.
00
1 99
0 .072
0.022
0.050
2.3
0.0 1
86
-10 7.
00 .
2 00
0.091
0.02 1
0.070
2.7
0.09
99


20 l
0 065
0. 020
0.043
2.4
0. 05
roo


202
0 .063
0.034
0.029
3.2
C 03
109
l 32 .
00
203
0.058
0.019
C 03 9
2.5
0.08
1 02
1 32 .
00
2 04
0.0 90
0.021
0.069
3.1
0.03
1 24

205
0.052
0.018
0.034
3.6
0.02
148
.

2 06
0.050
0.0 11
0.035
3.1
0. 06
1 59
- 1 00.
co
2 07
0.0 72
C. 02 0
0.052
3.3
0.05
l 1 5
- 1 00.
00
2 08
0.072
0.0 22
0. 05 0
2.7
0.02
1 08


209
0.072
0.015
0.057
2.7
0. 05
1 0 8


2 l 0
0.065
0.03C
0.035
3.3
0.07
1 36




LIST OF FIGURES
Figure Page
1. Sampling sites within Florida 17
2. Canal and sampling stations at Punta Gorda sites 23
3. Canal and sampling stations at Port Charlotte
site 25
4. Canal and sampling stations at Pompano Beach
site 26
5. Canal and sampling stations at Loxahatchee River
site 27
6. Canal and sampling stations at Marco Island site ..... 29
7. Canal and sampling stations at Boca Ciega Bay
site 30
8. Canal and sampling stations at Hillsboro Inlet
site 32
9. Canal and sampling stations at Flagler Beach
site 33
10. Canal and sampling stations at Apollo Beach site 34
11. Canal and sampling stations at Goose Bayou (Panama City)
site 36
12. Canal and sampling stations at Key Colony site 37
13. Canal and sampling stations at North Miami site 38
14. Frequency distribution and descriptive statistics for
total community gross primary production (g C^/m^-day),
averaged by canal 54
15. Frequency distribution and descriptive statistics for
planktonic gross primary production (g C^/m^-day),
averaged by canal 54
16. Frequency distribution and descriptive statistics for
total community respiration (g C^/m^-day), averaged by
canal 56
ix


-130-
and the canal minimum residence time. The canal length, width, surface
area, and volume appear to be inversely correlated with the net ex
changes of turbidity and color, i.e., smaller canals have a greater
tendency to be sinks for turbidity and color. The canal mean depth
and minimum residence time, however, seem to be positively correlated
with the tendency of the canal to reduce the color and turbidity of the
estuarine water. This combination of the canal dimensions and flushing
rate likely reflects the current velocities across the canal mouths.
Large canal systems have greater water velocities across the mouths
which result in more turbulence and less likelihood of turbidity and
color settling out of the water column. Similarly, canal systems with
longer 'minimum residence times have lower mean current velocities that
are more conducive to settling.
Water Quality vs. Canal/Sampling Day Characteristics
The canonical correlation analysis between the canal water quality
and the canal/sampling day characteristics data sets is shown in Table
24. Nine separate pairs of linear combinations were found to be sig
nificantly correlated. The factors associated with the linear combina
tion are not readily interpretable, as might be expected considering
the diversity and complexity of the variables in each data set.
The first pair of canonical variables seems to reflect the high
levels of phosphorus in the large, bulkheaded, and sewered canal systems
sampled in Punta Gorda, Port Charlotte, and Apollo Beach. The second
pair of factors appears to be a combination of the average and minimum
dissolved oxygen concentrations contrasted to the total carbon levels
and Secchi depths in the water quality data set, versus the combination


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MONTH DAY YEAR STATION TIME TC IC TOC


UBS
CANAL
MONTH
DAY YEAR
LENGTH
WIDTH
MDEPTH
AREA
VOLUME
SILL
Table 1
58
KC3
8
18
76
730
29
3.9
21200
82700
0.8
59
NM 1
10
26
76
624
3 1
6.2
38500
233000
2.9
60
NM2
1 0
27
76
624
31
6.2
38500
238000
2.9
6 1
NM3
1 0
28
76
624
31
6.2
38500
238000
2.9
62
PEI
8
1 4
74
762
30
2. 1
22900
48000
1 .2
63
PE2
8
1 4
74
6 10
25
2. 1
15200
32000
0.6
64
BP 3
8
1 9
74
457
1 2
2.7
5480
1 5000
0.0
65
BP4
8
1 9
74
1 83
9
2. 4
l 650
3950
0.0
66
S A 8
8
23
74
8 73
26
5.4
52400
283000
3.1
67
AB3
9
1 7
74
671
43
3.3
28900
95200
1 .2
68
AB5
9
1 7
74
4 88
30
3.6
1 4600
52700
0.6
69
MIH
8
8
75
1267
30
3.1
120000
373000

70
MI J
8
1 0
75
458
30
2.0
1 3800
27600

71
MIL
8
6
75
660
30
3.4
63000
214000

72
MI M
a
6
75
2837
30
2.7
312000
842000
0.0
73
MIM
8
8
75
2837
3 0
2. 7
312000
842 000
0.0
74
MIN
8
7
75
4^63
30
2.2
613000
1350 0 C 0
9
OSS
OEVEL
AGE
BULK CURBS SEVERS
MINRES
TIDE
CUMTIDE
SUN
DAYL
58
20
16
40
0
1
6 .6
0 .4 1
0.59
72
13.0
59
50
20
50
0
1
7.8
0.80
1.42
3 16
11.5
60
50
20
50
0
1
8.7
0.7 1
l .36
346
11.5
61
50
20
50
0
1
8.7
0.71
1.23
l 83
11.5
62
0
1 9

0
0
2.6
0.70
0. 80

13.0
63
30
1 9

0
0
2.6
0.70
0.80

13.0
64
0
15
0
0
3.9
0.3 1
0.69
9
13.0
65
30
15

0
0
3.5
0.31
0.69

13.0
6
0


0
0
11.5
0 .31
0.47

13.0
67
75


0
0
2.2
0.91
1.52

12.3
68
40


0
0
2.4
0.9 1
1.52

12. 3
69
80
1 0
1 00
0
1
1 .7
1 .03
1.81

13.0
70

10
100
0
1
1.3
0.82
1.49

13.0
7 1

10
100
0
1
2.1
1.02
1.6 1

13. 0
72
50
10
100
0
1
3.3
1 .02
1 .62

13.0
73
50
1 0
100
0
1
3.3
0.95
1. 62

13.0
74

a
80
0
1
1.2
1 .03
1.79

13.0
(Continued)
i
N?
N5
I


-281-
CORR ELAT ION COEFHULMS / PRU > |RJ UNDER H0:RHU=0 / NU
MdbR UF OBSERVATIONS
YEAR
P TURB
UI C
SECCH1
PGPPM3
T PR
T R
PDMIN
-0.1 0600
-0.10033
0.1 OCOb
-0.09534
0.08710
0.08666
-0.07353
0.4638
0.4619
0.4470
0.4846
0.5312
0.5254
0.5972
SO
56
60
56
54
56
54
FTP
PPRM3
ENH3
FNH3
F TP
SUN
DTP
-0.C6620
0.C6498
-00 620 5
-C.0 62 05
-0.05874
0.04694
0.04073
0.6833
0.6342
C.6072
0. 60 72
0.62 65
0.7202
0.7416
71
56
71
71
71
56
68
P OP
ETURB
ACE
MAX LO
FOUND
ECUNU
CUND
-0.037b 0
-0.03057
0.01 7b**
- C. 0 1 04 1
0.00000
0.00000
0.00000
0.7799
0.8331
08b4o
0.9303
1.oooc
1 OOOC
1.0000
68
50
71
73
24
24
24
FTC
F TC
ETC
PIC
E IC
FTOC
AGE
ETUC
l .00000
0.96076
0.5649b
0. 55693
C. 60508
0.46824
0 .46599
0.0000
0.0001
0.000 1
0.0001
0.0001
0.0002
0.0002
58
58
58
58
56
58
58
AVGDG
TPk
SUN
SI LL
E UP
FTP
PGPPM2
-0.43508
0.40838
-0.40207
0.39678
-0.37 952
-0.37126
0.37071
0.0007
0. 0C2 9
0.0028
0.0020
0.0033
0.0041
0.0063
67
5 1
53
58
56
58
53
FCOND
E TP
MONTH
LCUND
DTC
PPRM 3
SEWER S
-0.36729
-0 36372
0. 3457b
- 0. 34437
0.32210
0.29800
-0 .293 1 1
0.0775
0.0050
0.0079
0.0994
0.015b
0.0 3C2
0.0256
24
58
5d
24
56
53
58
MI NDU
DUP
BULK
E TUP
MUEPTH
PKM2
T IDE
- 0 .47869
-0 .27092
-0.254 79
0243 79
0.24013
C.23153
0.21843
0.0358
0.0434
0.053 6
0.0756
0.Ob 94
0 .0953
0.0995
57
5 6
58
54
5b
53
58
PGPPM3
F UP
F TUP
PDM1N
YEAR
DAYL
TgPP
0 .21 036
-0.2041 0
- 0. 19957
0.1 973 7
0. 1 95 69
-0.19300
0.18542
0.119 7
0.1244
0.14 7 9
0.1651
0.1410
0.1466
0. 1838
53
58
54
5 1
56
56
53
WIDTH
OTOC
UlC
DC JN
U 1 UP
UE VEL
DCULOR
-0.1 70 21
0.16951
0 16 4 9 6
-0.16491
0. 14465
-C.13434
0. 1 2603
0.2015
0.2117
02244
0.4413
0 286a
0.3147
0.4264
58
56
56
24
56
58
42
U TP
C LMTIDE
f'NHJ
E Nrl3
ECULUR
SECCHl
F TURB
-0.11275
0.11041
C. 1 09 6 4
0. 1 0 9b 4
-0.0 9022
-0.08685
-0.08636
0.4080
0.4093
0.4126
0.4126
056 99
0.5206
0.5509
56
58
58
58
42
57
50
D TURB
UN H 3
PPK
U AY
ETUR B
LENGTH
MAXDU
- 0.0 8 2 4 7
0.08228
0.06460
-0.0 6252
-0.06161
0.05466
-0.05224
0. 57 74
05466
0.6561
0.6411
0.6698
0 .603 6
C .6995
48
56
53
58
50
56
5 7
AREA
TR
VULUME
CUR ES
FCULOk
M INRES
TEMP
0.04623
0.03379
0.03163
-0.02624
-C. C24 03
0.00952
-0 .00564
0.7304
C.8102
0.8125
0.8333
0.8799
0.9434
0.9666
58
53
58
58
42
58
57


APPENDIX A
Oxygen metabolism data for individual stations.
Nomenclature and units as in Table 2


-259-
UtJS
MONTH
DAY
Y BAR
STATION
T IMt
1C
IC
TUC
69 1
3
24
76
MI 1
I 0
38.0
25.3
12.7
692
3
24
76
MI 1
1 1
39.3
21 .2
l 8. 1
693
3
24
76
Mil
1 2
41.5
22.4
19. 1
694
3
24
76
MI 1
1 3
38. 1
21.7
16.4
095
3
24
76
M I 1
14
41.0
23.3
17. 7
696
3
24
76
Mil
1 5
40.1
23.5
16.6
097
3
23
76
MI 3
17
40.2
35.8
4.4
698
3
23
7 6
M 13
18
39.6
2 3.8
1 5. 8
099
3
23
76
MI 3
1 9
39.8
24.4
15.4
700
3
23
76
M 13
20
39.2
23.3
1 5. 9
70 i
3
23
76
M I 3
22
39.9
25.2
14.7
70 2
3
2 3
76
M l 3
23
4 1.3
21.8
1 9. 5
703
3
23
76
MI3
24
40.0
23.8
1 6. 2
70 4
3
24
76
M1 3
1
39.6
25.1
14.5
705
3
2 1
76
M I 3
2
42. 0
26.3
15. 7
706
3
2 1
76
M1 3
3
40.8
24 .2
16.6
707
3
2 l
76
MI 3
4
3 9.8
24 .4
15.4
708
3
2 1
76
M13
5
39.3
23.3
16. 0
709
3
2 1
76
M I 3
t>
39.7
28.2
11.5
7 1 0
3
21
76
MI 3
7
45.2
22 .6
22.6
7 1 1
3
2 l
76
M 13
8
38.7
3 1.1
7. 6
7 1 2
3
21
7 6
M1 3
9
38.4
22 .4
16.0
713
3
2 1
76
M I 3
1 0
39.4
22.7
16.7
714
3
21
76
M I 3
1 1
38.9
22.3
16.6
715
3
2 1
76
Ml 3
1 2
39.6
2 1 .4
18.2
7 1 6
3
2 1
76
M 13
1 3
40.5
23. 1
17.4
71 7
3
21
76
M1 3
1 4
38.2
23.8
14.4
7 18
3
2 1
7 6
MI 3
1 5
39. 9
2 1.0
18.9
719
3
2 l
76
M I 3
1 6
40.4
22.0
1 8. 4
720
4
20
76
BC2
16
39.5
12.9
26.6
UBS
T P
OP
TUP
TURb
NH3
COLOR
DS
CUNU
69 1
0.082
0. 043
0. C39
7. 0
C. 07
O 9
0.24
340
692
0.077
0.041
0.036
4. 6
0.07
3 1
-0.03
336
693
0.082
0.04 9
0.033
6. 5
0.07
52
-0.25
344
694
0.079
0.049
0.030
5. 7
0. 1 7
33
-0.20
356
695
0.06 8
0.043
0.026
5. 7
0.12
5o
-0. 17
360
696
0 .081
0.050
0.03 1
5. 8
0.11
28
-0.02
325
697
0.058
0.0 29
0.029
4.2
0.0 1
42
0.04
343
6 98
0.042
0.028
0.0 14
2.9
0.02
32
0.26
385
699
0.049
0.028
0.C21
3. 2
0. 02
22
0.24
371
70 0
0 .0 52
0.033
0.0 19
3.3
0.03
3 l
0. 14
36 1
70 1
0. 049
0.031
0.018
3.1
0.02
4 1
-0.25
333
7C2
0.058
0.032
0 C2o
4. 2
0. 03
37
-0. 25
357
703
0.052
0.033
0.019
4.2
0.03
49
-0. 25
352
70 4
0.04 7
C. 030
0.017
3.3
0.02
52
-0.28
347
705
0.049
0.036
0.013
3.3
0.06
41
-0. 33
343
70 6
0.050
0.031
0.0 19
3. 7
0.04
52
-0.34
368
70 7
0.054
0.033
0.02 1
4. 0
0. 02
4 l
-0.35
348
708
0.076
0.048
0.028
4.2
0.03
1 7
-0. 19
353
709
0.068
0. 048
0.020
3. 8
0.08
32
0.20
347
7 1 0
0 .334
0.123
0.211
6. 2
0. 06
22
0.2 7
256
7 1 1
0 .052
0.035
0 C 17
4.2
0.12
24
0. 31
356
71 2
0.052
0.038
0.014
3.2
0.0 1
7
0.36
329
71 3
0.059
0.038
0.021
5. 2
0. Oo
3o
0. 40
3 33
71 4
0.063
0.040
0.028
4.4
0.05
29
0.41
326
7 1 5
0. 063
0. 038
0.026
3.2
0.05
32
0.24
337
71 6
0.057
0.031
0 .026
3*2
0.05
2 5
-0. 03
357
71 7
0. 050
C.032
0.0 18
3.8
0.04
40
-0.25
368
718
0 .053
0.032
0.021
3. 1
0. 01
26
-0.20
346
71 9
0.055
0.035
0.020
3. 2
0.02
33
-0.17
343
720
0.212
0.160
0.052
6. 0
0.19
28
-0.02
268


CANAL-ESTUARY NUTRIENT EXCHANGE AND METABOLIC LEVELS
IN FLORIDA RESIDENTIAL CANALS
By
WILLIAM ARTHUR BAILEY
A DISSERTATION PRESENTED TO THE GRADUATE COUNCIL OF
THE UNIVERSITY OF FLORIDA
IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE
DEGREE OF DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
1977

' 0-77
ACKNOWLEDGMENTS
Numerous individuals, to whom I am much indebted, helped me with
the field collections. During- the 1975 collections, William Marsh,
Deborah Lupton, and Warren and Ann Hansen forfeited many hours that are
normally devoted to sleeping. Florinus Kooijman volunteered to accom
pany me to Marco Island and Boca Ciega Bay; David Price to Hillsboro
Inlet and Panama City; and Richard Brightman to Apollo Beach.
The members of the department's chemistry laboratory, particularly
Hugh Prentice and Lloyd Chesney, were invaluable as troubleshooters
when I was having problems with water analyses. Without the Department
of Environmental Engineering Science's truck and boat, and without
Dr. Patrick Brezonik's ability to keep the chemistry laboratory stocked
with chemicals, I would have been unable to collect and analyze samples
during 1976.
I am grateful to Dr. B.A. Christensen and Fred Morris of the
Hydraulic Laboratory, Department of Civil Engineering, for providing me
with the 1975 hydrographic data and for loaning me a tide recorder
during 1976. I am also grateful to Dr. Emmett Bolch for providing me
an assistantship on his Florida Power Corporation Project during 1976.
I would like to thank my committee members for their comments and
guidance throughout this investigation. Dr. Jackson L. Fox, my chairman,
has spent many hours listening to my problems. His efforts are greatly
appreciated.
ii

The person most responsible for my completion of this study is my
wife. Mary worked beside me during more than half of the sampling
trips and encouraged me when things seemed hopeless. She taught school,
under less than ideal circumstances, in order to support us and to pay
for unfunded sampling, trips in 1976. I doubt that I would have com
pleted this work without her.
iii

TABLE OF CONTENTS
Page
ACKNOWLEDGMENTS. . -. ii
LIST OF TABLES vi
LIST OF FIGURES ix
ABSTRACT xii
CHAPTER 1 INTRODUCTION 1
CHAPTER 2 LITERATURE REVIEW. 6
CHAPTER 3 SITE DESCRIPTIONS 16
CHAPTER 4 MATERIALS AND METHODS 40
Metabolism 40
Nutrient Exchange and Water Quality 42
Canal/Sampling Day Characteristics . 44
Statistical Analyses 44
CHAPTER 5 RESULTS 45
Metabolism 46
Combined Data 46
1975 Data . 58
Daily Variability in One Canal 65
Nutrient Exchange. 67
Combined Data 67
Diurnal Cycle of Nutrient Concentrations. ... 84
1975 Data 86
Daily Variability in One Canal 91
Water Quality 93
Structure of the Data Principal Components .... 100
Combined Data 102
Metabolism 104
Exchange. . 106
Water Quality 107
Canal/Sampling Day Characteristics 110
Summary 113
Canonical Correlations 114
Metabolism vs. Exchange 117
Metabolism vs. Water Quality 120
iv

TABLE OF CONTENTS
(Continued)
Page
Metabolism vs. Canal/Sampling Day
Characteristics 123
Exchange vs. Water Quality 126
Exchange vs. Canal/Sampling Day
Characteristics 126
Water Quality vs. Canal/Sampling Day
Characteristics 130
Summary 138
Regression Equations 140
CHAPTER 6 DISCUSSION 155
Metabolism 156
Water Quality. . : 164
Nutrient Exchange 171
General Observations 178
"Average" Canal ....... 179
Design and Management Implications 183
CHAPTER 7 CONCLUSIONS. 193
LIST OF REFERENCES . 196
APPENDIX A Oxygen metabolism data for all individual stations. 201
APPENDIX B Oxygen profiles for all stations and sampling
times 211
APPENDIX C Nutrient and water quality data for each canal
entrance and sampling interval 235
APPENDIX D Descriptive statistics and correlation coefficients
for all parameters 276
BIOGRAPHICAL SKETCH. 327
v

LIST OF TABLES
Table Page
1. Canal and sampling day physical characteristics 19
2. Nomenclature for variables 47
3. Metabolism results averaged by canal for each sampling
day 51
4. Results of the analyses of variance for the total com
munity and planktonic metabolism data (1975) 61
5. Community and plankton gross primary production mean
values for the 1975 data. 64
6. Metabolism results for three consecutive days of
sampling on one canal (North Miami site) 66
7. Canal-estuary exchange results for the nutrient and
water quality parameters. . 69
8. Regression coefficients for the change in nutrient con
centrations versus time of day 85
9. Mean values for 1975 net-exchange data 88
10. Descriptive statistics and analyses of variance results
for 1975 net-exchange data 90
11. Nutrient/water quality exchange results for three
consecutive days at the North Miami site . 92
12. Water quality characteristics for all canal observations. 95
13. Principal components of the combined data (44 variables). 103
14. Principal components and correlation matrix for the
metabolism data 105
15. Principal components and correlation matrix for the
net nutrient exchange data 108
16. Principal components and correlation matrix for the
water quality data 109
vi

LIST OF TABLES
(Continued)
Table Page
17. Principal components and correlation matrix for the
canal/sampling day characteristics ..... Ill
18. Data set variables used in correlation analyses 118
19. Canonical correlation analysis of the metabolism and
nutrient exchange data sets 119
20. Canonical correlation analysis of the metabolism and
water quality data sets 121
21. Canonical correlation analysis of the metabolism and
canal/sampling day data sets 124
22. Canonical correlation analysis of the exchange and
water quality data sets. 127
23. Canonical correlation analysis of the exchange and
canal/sampling day characteristics 128
24. Canonical correlation analysis of the water quality and
canal/sampling day characteristics day sets 131
25. Summary table for canonical correlation results 139
26. Dependent and independent variables used in the stepwise
regression analyses. 142
27. Descriptive models for 20 dependent response parameters. .143
28. Significant-factor frequencies for the metabolism,
exchange, and water quality models 149
29. Appearance frequencies of the grouped factor-types in
the metabolism, exchange, and water quality models
(grouped) 152
30. Gross primary production levels for different aquatic
systems !. 157
31. Significant factor effects on canal metabolic parameters 161
32. Significant factor effects on canal water quality
parameters 169
33. Organic carbon net-exchanges for several coastal systems 174
vii

LIST OF TABLES
(Continued)
Table Page
34. Significant factor effects on canal-estuary net
exchange parameters. 176
35. Physical characteristics, water quality, metabolic
levels, and net canal-estuary exchanges for an "average"
residential canal 180
viii

LIST OF FIGURES
Figure Page
1. Sampling sites within Florida 17
2. Canal and sampling stations at Punta Gorda sites 23
3. Canal and sampling stations at Port Charlotte
site 25
4. Canal and sampling stations at Pompano Beach
site 26
5. Canal and sampling stations at Loxahatchee River
site 27
6. Canal and sampling stations at Marco Island site ..... 29
7. Canal and sampling stations at Boca Ciega Bay
site 30
8. Canal and sampling stations at Hillsboro Inlet
site 32
9. Canal and sampling stations at Flagler Beach
site 33
10. Canal and sampling stations at Apollo Beach site 34
11. Canal and sampling stations at Goose Bayou (Panama City)
site 36
12. Canal and sampling stations at Key Colony site 37
13. Canal and sampling stations at North Miami site 38
14. Frequency distribution and descriptive statistics for
total community gross primary production (g C^/m^-day),
averaged by canal 54
15. Frequency distribution and descriptive statistics for
planktonic gross primary production (g C^/m^-day),
averaged by canal 54
16. Frequency distribution and descriptive statistics for
total community respiration (g C^/m^-day), averaged by
canal 56
ix

LIST OF FIGURES
(Continued)
Figure Page
17. Frequency distribution and descriptive statistics for
planktonic respiration (g C^/m^-day), averaged by
canal 56
18. Frequency distribution and descriptive statistics for
total community production:respiration ratio, averaged
by canal 57
19. Frequency distribution and descriptive statistics for
planktonic productionrrespiration ratio, averaged by
canal 57
20. Frequency distribution and descriptive statistics for
plankton domination of community production. ....... 59
21. Frequency distribution and dscriptive statistics for
(a) weighted-average ebb total carbon concentration
(mg/1), and (b) the net change from average flood
concentrations 74
22. Frequency distribution and descriptive statistics for
(a) weighted-average ebb inorganic carbon concentrations
(mg/1), and (b) the net changes from average flood
concentrations 75
23. Frequency distribution and descriptive statistics for
(a) weighted-average ebb total organic carbon concen
trations (mg/1), and (b) the net changes from average
flood concentrations 76
24. Frequency distribution and descriptive statistics for
(a) weighted-average total phosphorus concentrations
(mg/1), and (b) the net changes from average flood
concentrations 78
25. Frequency distribution and descriptive statistics for
(a) weighted-average ebb ortho-phosphate concentrations
(mg/1), and (b) the net changes from average flood
concentrations 79
26. Frequency distributions and descriptive statistics for
(a) weighted-average ebb total organic phosphorus con
centrations (mg/1), and (b) the net changes from average
flood concentrations 81
27. Frequency distribution and descriptive statistics for
(a) weighted-average ebb ammonia concentrations (mg/1),
and (b) the net changes from average flood concentrations. 82
x

LIST OF FIGURES
(Continued)
Figure
28. Frequency distribution and descriptive statistics for
(a) weighted-average ebb turbidity levels (NTU), and
(b) the net changes from average flood concentrations. .
29. Frequency distribution and descriptive statistics for
(a) average dissolved oxygen concentrations (mg/1), and
(b) minimum dissolved oxygen values recorded in all
canals . . .
30. Frequency distribution and descriptive statistics for
the average Secchi depths (m) recorded in all canals .
Page
. 83
98
99
xi

Abstract of Dissertation Presented to the Graduate Council
of the University of Florida in Partial Fulfillment of the Requirements
for the Degree of Doctor of Philosophy
CANAL-rESTUARY NUTRIENT EXCHANGE AND METABOLIC LEVELS IN
FLORIDA RESIDENTIAL CANALS
By
William Arthur Bailey
March 1977
Chairman: Jackson L. Fox
Major Department: Environmental Engineering Sciences
Sixty-one observations of oxygen metabolism, canal-estuary nutrient
exchange, and water quality in 35 residential canals at 12 locations in
the State of Florida were made over a 20 month period. The free-water
diurnal oxygen method and in situ light-dark bottle 24 hr oxygen in
cubations were used to estimate the oxygen metabolism of the total canal
communities and the planktonic components. Total community gross
2
primary production varied from undetectable to 24.9 g O^/m -day and
had a mean value of 8.59. Planktonic gross primary production varied
2
from 0.40 to 23.9 g O^/m -day and had a mean value of 4.91. Community
gross primary production:community respiration ratios varied from 0.31
to 2.95 and had a mean value of 1.16. Regression equations for the
metabolic parameters explained more than 70 percent of the observed
variabilities using canal physical attributes, daylengths, solar in
solation levels, and local estuarine water quality as independent
variables.
Net canal-estuary exchanges of carbon (total C mass and organic C),
phosphorus (total P mass, ortho-P, and total organic P), ammonia
xii

turbidity, and color were determined from flow-weighted mean concen
trations during flood and ebb tidal phases over complete tidal cycles
(24 hrs). Net exchanges varied from a substantial export to a sub
stantial retention of these materials by canals. Most frequently, there
was little or no compositional change of the estuarine water than ex
changed with the canal water. Canonical correlation analyses showed
that, in general, the net fluxes of materials across canal entrances
were independent of the metabolic levels within the canals and canal
water quality; the general correlation between material flux and canal/
sampling day characteristics seemed to be derived from an association
between turbidity and color exchanges and the current velocities within
the canals. Regression equations, however, explained more than 80 percent
of the observed exchange variabilities, except for that of ammonia and
ortho-P.
Daily and spatially averaged dissolved oxygen concentrations re
corded in the canals ranged from 1.78 to 9.07 mg/1 and had a mean value
of 5.58. Most canals had average dissolved oxygen levels of 4 mg/1 or
greater. Minimum oxygen values ranged from zero to 7.13 mg/1 and had
mean value of 2.05; 70 percent of the canals had minimum-oxygen values
below 4 mg/1. Regression equations for average and minimum dissolved
oxygen concentrations explained 91 and 88 percent, respectively, of the
observed variabilities.
xiii

CHAPTER 1
INTRODUCTION
Residential canals and canal construction in the coastal zone are
sensitive environmental and political issues in Florida and other
Atlantic and Gulf coast states. Land developers argue that they are
filling a need by providing the public with attractive waterfront
property. Environmentalists and regulatory agencies contend that the
loss of wetlands and shallow estuarine areas outweighs housing benefits.
Regional planners are in a dilemma because the principles governing the
behavior and conditions of canals in the coastal zone and the percentage
of the coastal wetlands that can be developed before the estuarine
systems suffer serious damage are unknown.
The conversion of wetlands (mangrove and salt marshes) and shallow
estuarine areas into waterfront developments via dredge and fill opera
tions proceeded largely unchecked until the early 1970s. Following the
Earth Days of the late 1960s, the public became more environmentally
conscious and, therefore, more concerned about the destruction of
estuarine habitats. A widely circulated 1972 publication by Barada and
Partington, which portrayed residential canals as open sewers and as
sources of toxic materials to the adjoining estuaries, added impetus to
the movement against dredge and fill operations. In response to public
pressures, state legislators imposed a moratorium on dredge and fill
operations in Florida. The federal and state governments became
actively involved in attempts to curtail further dredging in the coastal
-1-

-2-
zone by strengthening the permitting requirements.
The development corporations were not prepared for the rather
sudden imposition of controls on their dredging plans. But, with their
businesses and livelihoods threatened, they resisted the controls by
litigation. In the courts, it became apparent that very little was
known about artificial canal systems and their impacts on the coastal
zone. The developers' lawyers were asking questions for which there
were no answers. Without facts to support their contentions, the
positions of state and federal agencies were weakened in the courts.
This study was initiated in response to the Florida Department of
Environmental Regulation's quest for more scientific facts. Data col
lection occurred in two phases. The first phase was conducted as part
of a one year project (see Fox ejt al. 1976) funded by the Department
of Environmental Regulation. During the first phase, the metabolism
and canal-estuary nutrient exchange patterns of four pairs of similar
canals (Punta Gorda, Port Charlotte, Pompano Beach and Loxahatchee
River sites) were examined on four occasions in 1975. The second phase
of the study consisted of single sampling trips to eight additional
canal locations in 1976. The data from each phase and the combined
data provide different types of information.
The locations of the sampling sites covered most of Florida and
were approximately distributed in proportion to canal densities in
Florida. Most canal dredging has occurred in southern Florida, par
ticularly along the southeast coast (Gold Coast). For example, the
City of Fort Lauderdale has over 150 miles of waterways. Extensive
dredging and filling has also taken place in the Tampa Bay area and,
more recently, along much of the southwest coast of Florida. The

-3-
varying densities of canal developments along Florida's coastline can
be seen in the sampling-site figures (Site Description).
A complete inventory of the number or acreage of Florida canal
developments has not been made. However, some reported figures will
illustrate the extent, of this type of activity. Chesher (1974) estimated
that there were about 321 canals in the Florida Keys. Marshall (1968)
believes that 24000 ha or about 7 percent of Florida's estuarine habi
tat less than 2 m deep has been filled by coastal developers. Castanza
and Brown (1975) found that 5,600 ha of mangroves (2.3 percent) in
south Florida (below Lake Okeechobee) have been developed since 1900.
Several classification schemes have been proposed to categorize or
distinguish the various types of dredged canals (or lagoons). Polis
(1974) distinguishes between dead-end canals and open-ended canals.
Within these two major categories, Polis classifies canals as "bay-fill"
or "upland" types; the former are created in shallow estuarine areas,
and the,latter, in upland areas. The presence of a sill at the canal
entrance is also thought by Polis to be a distinguishing feature.
Lindall and Trent (1975) classify canals as "bayfill, inland, and
intertidal"; the mean-low and mean-high tide marks separate the three
types of dredged areas. The Florida Department of Environmental
Regulation describes the extent of canal branching as first-order
canals, second-order canals, etc.
The canals examined during this study were mostly dead-ended
(exceptions are identified in Site Description section) and upland
(intertidal and inland).
This study was designed to increase the data base and the under
standing of the role and behavior of Florida residential canals in the

-4-
coastal zone. The specific goals were to 1) evaluate the conditions
within canals, in terms of their metabolic levels and water qualities,
2) determine the magnitudes and direction of material exchanges across
canal entrances, 3) elucidate any recurring patterns or associations
between canals' behavioral and physical attributes, and 4) generate
and evaluate simple regression equations for the response variables
from relatively simple independent factors.
In order to achieve these objectives four types of data were col
lected for each canal: 1) metabolism levels, 2) nutrient water quality
net-exchanges between the canals and adjacent estuaries, 3) several
basic water quality parameters, and 4) the canal and sampling day
physical characteristics. The metabolism and water quality data pro
vide information on the conditions within the canals, whereas the
exchange data provide information on the nature of the canal-estuary
interactions.
Rather than intensively studying one or two canal systems over an
extended period, the strategy was to examine the short-term behavior of
a large number of canals around Florida. By sampling canals with wide
geographical distribution and varying physical attributes, the vari
abilities of the response parameters were assessed for Florida resi
dential canals. Once the variabilities of canal behavior and conditions
were known, then the degrees of interdependence among the response
parameters and the canal and sampling day characteristics, plus the
amounts of variability explained on the basis of canal physical attri
butes, estuarine water quality, and local tidal dynamics, were evaluated
using standard statistical methods.
Multiple regression analysis was employed to determine quantitative

-5-
relationships among 20 response parameters (metabolism, net-exchange,
and water quality) and their significant explanatory factors (canal
physical attributes, estuarine water quality, and local tidal dynamics).
The analysis did not provide the mechanistic relationships for the
response and explanatory variables but did, however, identify and
quantify the associations among the response parameters and the ex
planatory factors. Since the regression equations have been derived
from data on existing canals, they constitute a foundation from which
future workers can develop canal design criteria, canal management
policies, and mechanistic theories for the controlling factors in
canals.
This study substantially increases the data base for the conditions
within Florida residential canals, provides heretofore lacking infor
mation on the exchanges of materials between canals and estuaries, and
presents equations that can be cautiously used to estimate the condi
tions and behavior of existing or future canal systems. It does not,
however, attempt a total evaluation of the ecological and socioeconomic
impacts of residential canals in the coastal zone.

CHAPTER 2
LITERATURE REVIEW
A review of the existing literature concerning dredged canals,
channels, and holes up to 1974 has been prepared by Polis (1974) under
a grant from the State of Maryland. His reviews that pertain to resi
dential canals are described briefly below.
The work of Trent and associates (Moore and Trent, 1970; Corliss
and Trent, 1971; Trent ejt aJ. 1972) in West Bay, Texas includes
hydrographic, water quality, substrate, phytoplankton, benthic in
vertebrate, oyster, fish, and crustacean data for canal, marsh, and
open bay stations. The canal stations were found to contain more silts
and clays than the marsh and bay stations. Turbidity was higher in the
bay than in the canals, but lower in the marsh than in the canal.
Benthic invertebrates, fish, and crustacean numbers were similar in the
marsh and canal, and tended to be higher in the bay. Phytoplanktonic
primary production per unit surface area was greater in the canal than
in the marsh. A large standing crop of oysters was observed on the
bulkheads of the canal but growth and spatfall were reduced in the
canal relative to the marsh. Oyster mortality was greater in the canal
than in the marsh. Blue crabs and grass shrimp were more abundant in
the marsh than in the canal.
Taylor and Saloman (1968) examined the sediments, water quality,
and primary production of canals in Boca Ciega Bay, Florida. They found
dissolved oxygen levels of at least 3.5 ml/1 (4.9 mg/1) at all times
-6

-7-
and stations, lower turbidities in the canals than in the bay, and no
significant differences in phytoplankton primary production levels
between natural and dredged areas. Silts and clays predominated in
the canal sediments, as compared to sand and shell in the bay sediments.
Fewer species of fish were netted in the canals than in the bay (49
versus 80), but thirty percent more fish were caught in the canals.
Sykes and Hall (1970) sampled the mollusks of canals and natural
areas in Boca Ciega Bay, Florida, concomitantly with Taylor and Saloman.
Their results show a marked reduction in numbers of individuals and
species in the soft sediments of the canals as compared to those of
the bay.
Lindall, Hall and Saloman (1973) followed the fish populations of
a newly opened canal system off Tampa Bay, Florida. Only anchovies
(Anchoa mitchilli) were caught in the system three months after inunda
tion, but during the following year 36 species were netted. Lindall
et al. thought that newer canals provide a more favorable habitat for
fishes than do older canals.
Barada and Partington's (1972) report on waterfront developments
in Florida, while supplying no new data on canals, was instrumental in
bringing the problem of canal dredging to the public's attention. Their
report, citing several of the above investigations, discusses the lack
of good circulation and flushing, excessive depths, stratification,
fish kills, odor, and bacterial problems of canals. An image of canals
as open sewers and as having detrimental effects on ground and surface
waters, was projected.
Godwin and Sholar (n.d.) found increased silt and clay fractions
and decreased benthic invertebrate diversities in dredged canal sediments,

-8-
relative to natural areas in North Carolina.
The work of Daiber at _al. (1972, 1973) in Delaware provided at that
time the most comprehensive study of biological, chemical and physical
aspects of any canal system. Conditions were generally poorer in the
canals than in the adjacent natural salt marsh embayments, but the
uniqueness of each canal system was recognized. A dye flushing study
of one 800-meter canal showed that the initial surface concentration at
the dead-end was reduced by only 56 percent after five days, and that
the bottom water exchanged much more slowly.
Since Polis' review, several other studies have appeared. Chesher
(1974) reported biological and hydrological data on 50 canals in the
Florida Keys. Paulson et al. (1974, 1975) studied four canal systems
along the Gulf of Mexico. Nixon et al. (1973), in an ecological study,
compared a small boat marina with a natural marsh embayment in Rhode
Island. The Environmental Protection Agency (1973, 1975) has issued
preliminary reports on several canal systems in the Florida Keys,
Charlotte Harbor, Florida area, and North Carolina. Daiber et^ al.
(1974, 1975) have completed two more reports on Delaware canals. The
Marco Island, Florida project has been studied by a group from the
University of Miami (Van de Kreeke and Roessler, 1975a and b, and
Carpenter and Van de Kreeke, 1975) and by the Deltona Corporation
(1975). Adkins and Bowman (1976) have prepared an informative document
on the canals dredged for oil drilling rigs in Louisiana. Burk and
Associates, Inc. (1975) examined the condition of a residential canal
development in Louisiana, and evaluated several developments in Florida
in an attempt to forecast water quality in the Louisiana development.
Thurlow (1974) did research on the water quality and sediment

-9-
characteristics of four New Jersey canal developments. Substantial
data on four pairs of canals in Florida have been reported by Fox ej; al.
(1976) and by Piccolo et. al. (1976) .
Chesher (1974) discusses his physical, chemical, geological, and
biological work on 50 canals in the Florida Keys, and finds the canals
generally to be in good condition. Canal orientation to the wind and
the substrate type were found to be the most important factors affecting
canal water quality. Chesher feels that the advantages of such systems
outweigh the disadvantages to the productivity and economy of the Keys.
Paulson jet _al. (1974) report physical, hydrological, phytoplankton,
benthic fauna, and sediment composition data for single collections in
two canal systems in Florida and two in Texas. They believe that the
lower dissolved oxygen concentrations at the dead-end stations might be
alleviated by restricting the depths of the canals and eliminating
dead ends. Paulson's 1975 report includes physical, biological, and
chemical data for a canal system and a natural bayou in southern
Mississippi. They found essentially no differences in flushing rates
and biota between the two systems. However, dissolved oxygen values
tended to decrease and coliform levels tended in increase toward the
dead end of the canal. The canal was shallower than the adjacent water
body.
Nixon ej: aJ. (1973) evaluated the production, metabolism, suspended
material, dissolved organics, nutrients, phytoplankton,. bacteria, fish,
fouling communities, and sediments of a small boat marina and a natural
marsh embayment in Rhode Island. The two types of systems were similar
and were felt to be compatible coastal systems in Rhode Island. The
authors regarded the fouling communities of the bulkheads, pilings, and

-10-
boats as an important food source for juvenile fish populations and
which may serve the same detritus-producing role as do the marsh grass
in the natural marsh embayment. The fouling communities reached a
maximum biomass of 5,000 g/m^, about five times the standing crop of
marsh grass. The respiration rate of the fouling communities was quite
2
high (mean = 1.80 g O^/m -hr) with no net production and was about 20
times the oxygen demand of the sediments.
The preliminary E.P.A. (1973, 1975) reports represent the most
exhaustive sampling sessions on selected canals in Florida and North
Carolina. Impressive amounts of water quality, sediment, microbial,
hydrodynamic, mass transport, and biological data were collected twice
for two pairs of canals near Punta Gorda and Big Pine Key, Florida, and
once at sites in Marathon, Florida, Panama City, Florida, and Atlantic
Beach, North Carolina. Their preliminary but unofficial recommendations
were to restrict canal depths to 41 to 6 feet, to centralize the waste
treatment facilities of the development and discharge the effluent at
points remote from the canals, to have the developer provide sufficient
bonding to correct any water quality violations in the canals or to
isolate the canals from receiving waters, to design developments so
that stormwater runoff does not enter the waterways, to avoid sills at
the canal mouths, and to require an assessment of a proposed canal
development's impact on any local shallow freshwater aquifers.
Daiber ej: _al. (1974) expanded on their earlier work and presented
seasonal data on seven canal systems in Delaware. Hydrological,
coliform, BOD, fish and benthic invertebrate results are reported along
with more flushing characteristics and a simple tidal excursion model
for transport within a canal. They concluded that the flushing rates

-11-
and general ecological condition of the canals are dependent on the
adjacent water body. It is difficult to obtain healthy canals on a
stressed bay.
Daiber et^ jil. (1975) reported additional benthic invertebrate data
from the Little Bays area of Delaware, in addition to intertidal inver
tebrates and vegetation, and ichthyoplankton results. The numbers of
individuals and species of benthic invertebrates were generally lower
in canal stations than in marsh and bay stations during the summer and
fall. However, the uniqueness of each canal system and its environ
mental conditions was again emphasized. The three habitats were found
to have similar fauna during the winter and spring. Biomass comparisons
between different types of canal shorelines indicated that old bulkheads
have higher standing crops of plants and animals than do bare banks.
The old bulkheads had fewer macrophytic plants, but higher animal biomass
than did the salt marsh environment. The ichthyoplankton data, though
limited, suggested that canals are not as favorable a habitat for larval
fish as is the salt marsh.
The information reported by the University of Miami group
(Carpenter and Van de Kreeke, 1975 and Van de Kreeke and Roessler,
1975a and b) on the Marco Island, Florida development consists of
oxygen data, estimates of production and respiration, and a model to
predict oxygen levels. Their model was developed for the main flow
through arterial channels fifteen fet in depth. The model revealed
that dissolved oxygen concentrations for Marco Island canals are sig
nificantly dependent on the vertical mixing coefficient and the detritus-
supported respiration, and not sensitive to atmospheric transfer,
photosynthesis and respiration. For the dead-end tributary canals,

-12-
wind induced motion and diurnal density induced motion were thought to
be important factors affecting dissolved oxygen distribution.
Adkins and Bowman (1976) provide an informative review of the
impact of canal dredging in the coastal zone, as well as the results of
a two year study on canals dredged in Louisiana marshland for oil
drilling rigs. Fish, blue crab, shrimp, water chemistry, and sedi-
mentology data were presented for open, semi-open, and closed canals,
and for unaltered areas. The greatest number of animals were found in
the unaltered areas. Dissolved oxygen levels remained within tolerance
limits of marine organisms during most of the study, though fish kills
were observed in the semi-open and closed canals (one each).
Burk and Associates (1975) conducted a one day study of water
quality and biota at five stations within a 5,300 acre development off
Lake Pontchartrain, Louisiana. By evaluating the conditions of five
Florida canal developments and reviewing canal literature, Burk and
Associates made several recommendations for improving the future water
quality in the Louisiana development. Recommendations to improve flush
ing and water circulation in the existing canals were to create flow
through systems via culverts and saltwater wells, and to install bottom
aerators or air injection systems. Design criteria for new canals in
the area were to limit canal depths to 6 to 8 feet and canal lengths to
800 feet, to provide sloping sides and smooth bottoms in the canals, to
allow canals to be as wide as possible, and to align the canals with
the prevailing winds. Other recommendations included the construction
of grassy swales in the development, the establishment of natural
vegetation buffer zones between homes and canals, and the spray-
irrigation of the sewage treatment plant effluent onto the local golf
course.

-13-
Thurlow (1974) examined the water quality and sediment character
istics of four canal developments in New Jersey. He concluded that each
canal system was unique and that depth had a major influence on water
quality, particularly on the bottom water quality. Canals with sills
were "more polluted" at points remote from the entrances. Accumulations
of nutrients and heavy metals plus, anaerobic conditions were observed
in excessively deep areas. Water quality was similar in old and new
canals, even though the new canals were deeper. Canal developments
with homes utilizing septic tanks had better water quality than those
with a sewage treatment plant whose effluent was discharged into the
canals. The water quality was best in the canal system that had a
sewage treatment plant and a remote discharge point. Thurlow recommended
canal depths of 8 to 10 feet, maintenance dredging of sills, sewered
developments with remote discharge points, and the reductions of organic
inputs to the canals, in the use of lawn fertilizers, and in the sub
stitution of stones for lawns.
Two groups of investigators at the University of Florida (Piccolo
et al., 1976 and Fox ejt al., 1976) jointly examined four pairs of
similar canals at different locations in Florida, on a seasonal basis.
Piccolo e_t al. provided the hydrography of the canals and a pollutant
dispersion model. Fox ej: al. reported the water and sediment chemistry,
the metabolism levels, the phytoplankton and benthic invertebrate
populations, the canal-estuary net nutrient exchanges, the benthic
oxygen demand, and the hydrocarbon levels of the canals. They concluded
that canals constitute complex and variable systems. The individual
canals within the essentially identical canal pairs (directly adjacent)
often had dissimilar attributes. Not all canals had poor water quality.

-14-
The factors responsible for the differences in water qualities were
not clear. Rankings of the canal water qualities did not simply reflect
differences in a single factor such as canal depth, age, flushing rates,
or local estuarine water quality.
No clear consensus exists in the literature for the most important
factor affecting water quality in residential canals. Excessive depths
and poor circulation and flushing are most frequently thought to lead
to poor conditions. The dead-end nature of the canals and sill forma
tion at the canal entrances are not conducive to good mixing and flush
ing. Local tidal dynamics and their influences on canal flushing rates
are considered important by several investigators. The water quality
of the adjoining water bodies, while not frequently mentioned by
investigators working in single locations, undoubtedly affects the
canals. In addition to canal depth, other canal characteristics such
as length, width, configuration, bottom topography, orientation to the
wind, and substrate type, are often identified as important factors.
Allochthonous sources of organic and inorganic materials and their
management, appear to be significant in some canal systems.
Many aspects of the impact of canal dredging on the coastal zone
have been discussed by the investigators cited above. Reviews of the
subject can be found in Lindall and Trent (1975), Adkins and Bowman
(1976), and Odum (1970). Possible impacts of canal dredging in the
coastal zone given by these authors and their referenced literature,
include:
1. Destruction and loss of nursery areas for coastal fisheries.
2. Biological productivity losses of dredged areas. Taylor and
Saloman (1968) estimate that $1.4 million of annual revenue is

-15-
lost from Boca Ciega Bay, Florida as a result of dredging and
filling. Douglas and Stroud {1971) concluded that 535 pounds
of fish products from the continental shelf are lost per acre
of estuary that is obliterated; Gosselink ejt _al. (1974) value
the non-competing uses of marshland at $4,000 per acre per
year.
3. Changes in upland drainage patterns.
4. Changes in water depths and substrate types of dredged areas.
5. Harmful silt release during dredging operations and after
canal completion via resuspension.
6. Alteration of the local water currents and circulation patterns.
7. Estuarine detritus retained by canals.
8. Low dissolved oxygen concentrations and unfavorable conditions
in the canals and the resultant effects on estuarine organisms
entering the canals.
9. Possible spill-over of accumulated sludge and poisonous wastes
from canals to estuaries (Barada and Partington, 1972).
10.Saltwater intrusion into shallow freshwater aquifers and
former freshwater areas.
Deleterious effects of an active dredging operation on local
residents and wildlife.
11.

CHAPTER 3
SITE DESCRIPTIONS
Thirty-three canals at twelve locations throughout the State of
Florida (Figure 1) were sampled over a twenty month period. The indi
vidual canals and sampling stations are shown in Figures 2 through 13,
Several canals were sampled more than once, resulting in a total of
sixty-one canal observations. In addition, data for thirteen canals
were obtained from the Environmental Protection Agency and have been
included in some analyses.
Canal geometries (length, width, mean depth, water surface area,
water volume, sill height), canal age, percent of shoreline bulkheaded,
canal water minimum residence time, and some of the canal development's
attributes (presence or absence of curbed streets and sewer systems,
percent development) are shown in Table 1 for each canal observation.
The levels of solar insolation, tidal ranges, and cumulated tidal
amplitudes on the sampling days are also given in Table 1. Additional
information and distinguishing features of each canal site are given
below.
Punta Gorda (PG. Figure 2). The three canals at this location
are part of the Punta Gorda Isles development. The developer made an
effort to design this rather new canal system so that circulation and
flushing were maximized by dredging to uniform depths and leaving
sloping banks. Management of the canal system includes regulations
against the discharge of grass clippings and fish heads into the canals.
-16-

-17-
Figure 1. Sampling sites within Florida.

Table 1
Canal and sampling day physical characteristics.
Units: LENGTH, WIDTH, MDEPTH, SILL, TIDE, CUMTIDE meters
AREA square meters
VOLUME cubic meters
DEVEL, AGE percent
AGE YEARS
CURBS, SEWERS 1 present, 0 absent
MINRES (Minimum residence time) days
SUN langleys/day
DAYL (Daylength) hours
See Table 2 for more complete identification of the parameters.

oes
CANAL
MONTH
DAY YEAR LENGTH
W IDTH
MDEPTH
i
PG6
3
21 75
747
30
2.8
2
PG3
3
21 75
652
28
2. 2
3
PC3
3
22 75
575
33
3.2
4
PC6
3
22 75
0 18
33
2.7
5
PB3
3
26 75
732
23
3. C
6
P86
3
26 75
7 32
21'
3.2
7
LX3
3
25 75
631
22
1.8
a
LX6
3
25 75
521
1 7
1 .6
9
PG 6
6
14 75
747
30
2.8
1 0
PG3
6
14 75
652
28
2. 2
11
PC 3
6
1 5 75
575
33
3.2
1 2
PC
6
15 75
6 18
33
2.7
13
PB3
6
19 75
732
23
3.0
1 4
P66
6
19 75
732
21
3.2
1 5
LX6
6
1 8 75
521
17
1.6
i 6
LX3
6
18 75
631
22
1.8
17
PG3
9
6 75
652
28
2.2
18
PG6
9
6 75
747
30
2.8
19
PG9
9
6 75
3650
30
3.0
OSS
DEVEL
AGE
BULK CURBS SEWERS
M1NRES
1
30
9
100
0
1
2.9
2
50
9
100
0
1
2. 7
3
1 00
16
100
0
1
5.0
4
100
16
IOC
0
1
4.0
5
100
23
100
0
0
2.0
6
98
23
1 00
0
0
2.1
7
0
16
80
0
0
1.2
8
0
16
0
0
0
1.2
9
30
9
100
0
1
3.6
1 0
50
9
100
0
1
2.9
1 1
100
16
100
0
1
4.2
12
100
16
100
0
1
3.6
1 3
100
23
100
0
0
1.8
1 4
98
23
100
0
0
1 .9
15
0
1 6
0
0
0
1.4
1
0
1 6
80
0
0
1.4
l 7
50
9
1 00
0
1
2.2
18
30
9
100
0
1
2. 7
1 9
50
1 1
100
0
1
2.7
AREA
VOLUME
SILL
22400
62700
0.0
1 9000
60700
0.2
1 9000
60700
1 1
20400
55 1 00
0.8
16800
50500
1 1
1 5400
49200
0.8
1 3900
25000
0.6
8860
14200
1.2
22400
62700
0.2
18300
40200
0.0
19000
60700
0.5
20400
551 00
0.8
16800
5 05 C 0
1.1
15400
49200
0.8
8860
14200
1 .2
13900
25000
0.6
183 00
40200
0.2
22400
62700
0.0
480000
1440000
0.0
TIDE
CUMTIDE
SUN
DAYL
0 .58
0.83
602
12.0
0.58
0. 83
6 02
12.0
0 .58
0.77
642
12.0
0.58
0.77
642
12.0
1 10
2. 14
488
12.0
1.10
7.14
488
12.0
0.70
1.15
434
12.0
0.70
1.15
434
12. 0
0.55
0.74
650
13.5
0. 55
0. 74
650
13.5
C 73
0.83
6 76
13.5
0.73
0.83
676
13.5
1.01
l. 77
342
13.5
1.0 1
1.77
342
13.5
0.52
1.24
378
13.5
0.52
1. 24
378
13.5
0.64
1. 10
4 26
12.3
0.64
1.10
4 26
12 .3
0.64
1. 10

12. 3

obs
CANAL
MONTH
DAY YEAR LENGTH
WIDTH
MDEPTH
20
PC3
S
9 75
5 75
33
3.2
2 1
PC 6
9
9 75
618
33
2. 7
22
PC 9
9
9 75
1350
30
2.5
23
PB3
9
7 75
732
23
3.0
24
PB6
9
7 75
732
21
3.2
25
LX3
9
12 75
63 1
22
1.8
26
LX6
9
12 75
52 1
1 7
1.6
27
PG6
1 1
21 75
747
30
2.8
28
PG 3
1 1
21 75
6 52
28
2.2
29
PG9
1 1
21 75
3650
30
3.0
30
PC 3
1 1
23 75
575
33
3.2
31
PC 6
1 1
23 75
616
33
2.7
32
PC9
1 1
23 75
1350
30
2.5
33
P 86
1 1
14 75
732
21
3.2
34
PB9
1 1
14 75
7 38
23
2.5
35
PB3
1 1
14 75
732
23
3.0
36
LX3
1 1
16 75
631
22
1.8
37
LX6
1 1
16 75
521
1 7
1.6
38
MI 1
3
24 76
2637
30
2.7
DBS
DEVEL
AGE
BULK CURBS SEWERS
M1NRES
20
IOC
16
100
0
1
4 .4
21
100
16
100
0
1
3.8
22
75
14
90
0
1
3.1
23
IOC
23
100
0
0
1 .8
24
98
23
100
0
0
2. 0
25
0
16
80
0
0
1 .5
26
0
16
0
0
0
1 .6
27
30
S
100
0
1
2.5
28
5 C
9
100
0
1
1 .9
29
50
1 1
100
0
1
2.9
30
100
16
l 00
0
1
6.6
31
100
16
100
0
1
2.9
32
75
14
90
0
1
3.0
33
98
23
100
0
0
2.4
34
ICO
20
100
0
0
2.1
35
100
23 '
100
0
0
2.3
36
0
16
80
0
0
1 .2
37
0
16
0
0
0
1.2
38
50
1 0
100
0
l
3.3
AREA
VOLUME
SILL
1 9000
60700
0.5
20400
55100
0.8
182000
455000
1.5
16800
50500
1.1
1 5400
4 92 CO
o. a
13900
25000
C .6
8860
1 42 00
1 .2
22400
62700
0.0
18300
40200
0.2
480000
1440000
0. 0
1 9000
60700
0.5
20400
55100
0.8
182000
455000
1.5
15400
49200
0.8
70000
175000
l .0
1 6600
505C0
1 1
13900
2 50 00
0 .6
8860
1 42 00
l .2
312000
842000
0.0
Table 1. (Continued)
TIDE
CUMTIDE
SUN
DAYL
0 .57
0.81
446
12.3
C 57
C. 81
446
12.3
0.57
0.81

12.3
0.98
1.67
238
12.3
0.98
1.67
238
12.3
0.64
1 14
296
12.3
0 .64
1.14
296
12.3
0.74
l. 02
2 96
11.0
0.74
1.02
296
11.0
0.74
1.02

11.0
0.80
0. 83
334
11.0
0 .80
0.83
334
11.0
0.80
0. 83

11.0
0.73
1.17
352
11.0
0.73
1.17

11.0
0.73
1.17
352
12.3
0.63
1.37
204
11.0
0 .63
1.37
204
11.0
0. 67
0.81
52 0
12.0

06S
CANAL
MONTH
DAY
YEAR
LENGTH
WIDTH
MDEPTH
39
MI 2
3
24
76
3 97
30
2.6
40
MI 3
3
24
76
640
3 0
2.7
4 1
BC l
4
20
76
1320
53
4.0
42
BC2
4
20
76
964
48
3.0
43
BC3
4
20
76
1310
30
4.0
44
HI 1
c
1 9
76
3370
30
1 .5
4b
HI 2
5 '
1 9
76
3370
30
2.0
46
H I 3
5
l 9
76
690
30
2.9
47
FL1
6
1 2
76
520
2 1
2.8
48
FL2
6
12
76
450
24
3.1
49
FL3
6
12
76
800
24
4.9
50
API
7
14
76
39 10
46
2.6
5 1
AP2
7
1 4
76
11 40
52
2.7
52
A P3
7
1 4
76
27 10
38
2.0
5j
GB1
7
31
76
2 64
25
1 1
54
Gfl 2
7
31
76
1 73
25
1.7
55
683
7
31
76
427
20
l 2
56
KC 1
e
1 8
76
730
29
0.8
57
KC2
8
1 8
76
730
29
4. 1
OBS
CEVEL
AGE
BULK. CURBS SEWERS
MINRES
39
25
7
100
0
1
3.2
40
1 0
8
100
0
1
3.5
41
75
20
100
1
1
6.0
42
1 00
20
100
1
1
4 .5
43
100
20
100
1
1
6.0
44
100
18
100
0
1
1.0
45
1 00
l 8
100
0
1
1 .3
46
100
16
100
0
1
1.9
47
2 0
1 1
20
0
0
9.0
48
40
15
40
0
0
10.0
49
80
20
50
0
0
9.4
50
50
1 9
75
0
1
2.7
51
1 0
9
10
0
1
2. a
52
45
19
50
0
1
2. 1
53
60
7
l 0
0
0
3.7
54
80
15
100
0
0
5. 7
55
30
5
5
0
0
4.0
56
50
16
50
0
1
6 .4
57
80
16
80
0
1
6.9
AREA
VOLUME
SILL
1 2700
33000
0.5
41100
111OCO
0.0
184000
736000
1 1
46800
140000
2.3
122000
488000
1.4
385000
577000
0. 0
38 5000
770000
0.0
36000
1040C0
0.3
1 1000
30800
0.9
1 1 000
341 00
1 .4
50000
1450C0
1.2
402000
1040000
2.7
56000
151000
1.5
238000
476000
0.1
9200
10000
0.6
4300
7300
1.2
22000
26000
0.3
21200
80400
2.1
21200
86900
0.3
Table 1. (Continued)
TIDE
CUMTIDE
SUN
DAYL
0 .67
0.81
520
12. 0
0.67
0.81
5 20
12.0
0.67
0. 67
571
12.5
0.67
0.67
571
12.5
0.67
0.67
571
12.5
0.82
1. 50
515
13.0
0 .82
1.50
5 15
13.0
0.32
1.50
5 15
13.0
0 .3 1
0.47
504
13.5
0.31
0.47
504
13.5
0.31
0. 47
504
13.5
0.72
0.95
506
13.5
0.72
0.95
506
13.5
0.72
0. 95
506
13.5
0.21
0.30
554
13.5
0.21
0.30
554
13.5
0.2 1
0.30
554
13. 5
0.4 1
0.59
72
13.0
0.41
0. 59
72
13.0

UBS
CANAL
MONTH
DAY YEAR
LENGTH
WIDTH
MDEPTH
AREA
VOLUME
SILL
Table 1
58
KC3
8
18
76
730
29
3.9
21200
82700
0.8
59
NM 1
10
26
76
624
3 1
6.2
38500
233000
2.9
60
NM2
1 0
27
76
624
31
6.2
38500
238000
2.9
6 1
NM3
1 0
28
76
624
31
6.2
38500
238000
2.9
62
PEI
8
1 4
74
762
30
2. 1
22900
48000
1 .2
63
PE2
8
1 4
74
6 10
25
2. 1
15200
32000
0.6
64
BP 3
8
1 9
74
457
1 2
2.7
5480
1 5000
0.0
65
BP4
8
1 9
74
1 83
9
2. 4
l 650
3950
0.0
66
S A 8
8
23
74
8 73
26
5.4
52400
283000
3.1
67
AB3
9
1 7
74
671
43
3.3
28900
95200
1 .2
68
AB5
9
1 7
74
4 88
30
3.6
1 4600
52700
0.6
69
MIH
8
8
75
1267
30
3.1
120000
373000

70
MI J
8
1 0
75
458
30
2.0
1 3800
27600

71
MIL
8
6
75
660
30
3.4
63000
214000

72
MI M
a
6
75
2837
30
2.7
312000
842000
0.0
73
MIM
8
8
75
2837
3 0
2. 7
312000
842 000
0.0
74
MIN
8
7
75
4^63
30
2.2
613000
1350 0 C 0
9
OSS
OEVEL
AGE
BULK CURBS SEVERS
MINRES
TIDE
CUMTIDE
SUN
DAYL
58
20
16
40
0
1
6 .6
0 .4 1
0.59
72
13.0
59
50
20
50
0
1
7.8
0.80
1.42
3 16
11.5
60
50
20
50
0
1
8.7
0.7 1
l .36
346
11.5
61
50
20
50
0
1
8.7
0.71
1.23
l 83
11.5
62
0
1 9

0
0
2.6
0.70
0. 80

13.0
63
30
1 9

0
0
2.6
0.70
0.80

13.0
64
0
15
0
0
3.9
0.3 1
0.69
9
13.0
65
30
15

0
0
3.5
0.31
0.69

13.0
6
0


0
0
11.5
0 .31
0.47

13.0
67
75


0
0
2.2
0.91
1.52

12.3
68
40


0
0
2.4
0.9 1
1.52

12. 3
69
80
1 0
1 00
0
1
1 .7
1 .03
1.81

13.0
70

10
100
0
1
1.3
0.82
1.49

13.0
7 1

10
100
0
1
2.1
1.02
1.6 1

13. 0
72
50
10
100
0
1
3.3
1 .02
1 .62

13.0
73
50
1 0
100
0
1
3.3
0.95
1. 62

13.0
74

a
80
0
1
1.2
1 .03
1.79

13.0
(Continued)
i
N?
N5
I

23
Figure 2. Canals and sampling stations at the Punta Gorda site.

-24-
Floating debris is regularly removed from the canals. Limited boating
activity was observed. Canals 3 and 6 were sampled four times during
1975, while Canal 9 was sampled twice. Local tidal dynamics are quite
irregular in amplitude and frequency. The adjoining Peace River has high
phosphorus levels as a result of phosphate mines in its drainage basin,
and experiences lowered salinities during the rainy summer season.
Port Charlotte (PC. Figure 3). The three canals in the Port
Charlotte development are across the Peace River estuary from the Punta
Gorda canals, but are older and more developed than Punta Gorda Isles.
A sand bar (exposed at low tides) separates the dredged channel along
the development from the river. Southerly winds in the spring and
summer tend to hold floating debris in the canals. A secondary sewage
treatment plant in Port Charlotte enters the end of a 4,000-foot canal
whose entrance to the Peace River is approximately 2,000 feet east of
the canals. Canals 3 and 6 were sampled four times during 1975. Canal
9 was sampled twice.
Pompano Beach (PB. Figure 4). The three canals sampled at the
Pompano Beach location are representative of many canals in that area.
Extending off the Intracoastal Waterway, the canals are old, narrow,
and completely developed with homes using septic tanks (until 1975).
Considerable boating activity exists along the Intracoastal Waterway
and within the canals. Tides in the area are uniform and semi-diurnal.
The nearest oceanic inlet (Hillsboro Inlet) is approximately six
kilometers north.
Loxahatchee River (LX. Figure 5). Dredged and abandoned about
1960, the two canals at this site are approximately seven kilometers
up the Loxahatchee River from Jupiter Inlet. One of the canals (LX3)

-25-
Figure 3. Canals and sampling stations at the Port Charlotte site

-26-
Figure 4. Canals and sampling stations at the Pompano Beach site.

27
Figure 5. Canals and sampling stations at the Loxahatchee River site.

-28-
has concrete bulkheading, while the other (LX6) has sloping sides up to
the dredge spoils on one side and to a mangrove community on the other
side. The unbulkheaded canal has a landfill site at the dead end. The
Loxahatchee River in this vicinity is about one meter deep, is lined
with mangrove trees, experiences uniform semi-diurnal tides, and Is
strongly influenced by freshwater inputs during the wet season.
Marco Island (MI. Figure 6). This large and complex development,
constructed by the Deltona Corporation, is an island separated from the
mainland by the Marco River. Canal Mil is large, extensively branched,
and borders a golf course that is sppay-irrigated with the development's
l
sewage treatment plant effluent. The MI3 canal had received maintenance
dredging the year prior to sampling, as part of a canal design experi
ment by the Marco Island Applied Marine Ecology Station. At the ;time
jof sampling (March) the water in the area was more turbid than during
most of the year due to strong westerly winds that kept the Gulf .of
Mexico turbulent. Some Of the Environmental Protection Agency's data
from Marco Island has been incorporated into this study (canals MIH,
MIJ, MIL, MIM, MIN).
Boca Ciega Bay (BC. Figure 7). Located in the southeast section
of Boca Ciega Bay, this site was the only one that had curbed streets
in the development. The stormwater enters directly into the canals via
I
drain pipes. A large boat marina operates at the end of BC3 canal
(station BC32). Westerly winds from the Gulf of Mexico during the
spring and summer afternoons keep Boca Ciega Bay and the canal entrances
turbulent. Tides in the area have irregular amplitudes and frequencies.
On the sampling day the tidal cycle was diurnal, i.e., one high slack
and one low slack tide in 24 hours.

1
2
G.
' X 12
f ¡I!
§
fill
I *
M
m
Figure 6. Canals and sampling stations at the Marco Island site.

-30-
Figure 7. Canals and sampling stations at the Boca Ciega Bay site

-31-
Hillsboro Inlet (HI. Figure 8). The three canals sampled near
Hillsboro Inlet are part of Lighthouse Point Township. Canals HI1 and
HI2 form a single complex canal system with two entrances. Both the
HI2 and HI3 canal entrances are approximately 500 meters from the
Hillsboro Inlet. Yet, the influence of the oceanic inlet is quite dif
ferent for each canal. More of the ocean water that passed through the
inlet during flood tide seemed to be flowing north, rather than south
along the Intracoastal Waterway, during the sampling period. As a
result the turbidity and color at the HI2 canal entrance was noticably
less than at the HI3 entrance. Different volumes of freshwater flow
into the respective Intracoastal Waterway sections from upland drainage
were assumed to be affecting the movement of the seawater entering the
inlet. Boat traffic along the Intracoastal Waterway results in much
wave activity at the canal entrances. The large homes in the develop
ment tend to shelter the canal branches from the wind. A sewer system
was installed in the development during the year prior to sampling.
Flagler Beach (FL. Figure 9). The three canals sampled at Flagler
Beach extend off the Intracoastal Waterway about 15 kilometers south of
Matanzas Inlet. This section of Florida's coastline is not extensively
developed. Mangroves and marshland surround most of the Intracoastal
Waterway in the area. The water was quite colored (ca. 200 cpu) at the
time of sampling, and did not have much tidal activity.
Apollo Beach (AP. Figure 10). The Apollo Beach development,
located on the eastern shore of Tampa Bay, is approximately 10 kilo
meters from a phosphate processing plant. One large canal was
sampled as three canal observations. Canal API was taken as the
entire canal. Canals AP2 and AP3 were the major branches of the system.

-32-
Figure 8. Canals and sampling stations at the Hillsboro Inlet site.

33-
Figure 9. Canals and sampling stations at the Flagler Beach site.

Figure 10. Canals and sampling stations at the Apollo Beach site.

-35-
A shallow culvert connects sections of AP2 and AP3, but the interaction
between the two canals is limited to the surface water. The canal
system was dredged in a former mangrove community, had several deep
holes, and had varying widths. Onshore winds were strong (ca. 20 mph)
throughout the sampling period.
Goose Bayou (GB. Figure 11). The three canals sampled on Upper
Goose Bayou, located off North Bay near Panama City, were the most
recently dredged of the canals examined. These canals were also 1
shallowest and experienced the least tidal fluctuations. Marshland
and sparsely populated shorelines predominate in this estuary.
Key Colony (KC. Figure 12). The three canals in Key Colony
Beach are located on Fat Deer Key, about midway down the Florida Keys.
The substrate is limestone and fossilized sand. A sewer system serves
the development. However, the outfall from the treatment plant enters
i
an embayment about 400 meters north of canal KC1. A tropical degres
sion with high winds, heavy rains,, and little solar insolation, was
over the area during the sampling period, making conditions rather
uncharacteristic of the Keys.
North Miami (NM. Figure 13).p One branched canal in North Miami
Beach was sampled for three consecutive days. Each 24 hour period was
considered a canal observation. This canal was the deepest (6 m) of the
canals examined. An anoxic water layer existed below the two meter
depth throughout the three days. A cold weather front came through the
area during the sampling period, bringing cloudiness, shifting winds,
and rain. The development and the adjacent Maul Lake were mangrove
'communities before dredging and filling.

36'
Figure 11. Canals and sampling stations at the Goose Bayou (Panama
City) site.

-37'
Figure 12. Canals and sampling stations at the Key Colony site

38
Figure 13. Canals and sampling stations at the North Miami site.

-39-
Environmental Protection Agency Data. Observations 62-74 were
obtained from the Environmental: Protection Agency. Descriptions of
their Punta Gorda (PG), Big Pine Key (BP), Marathon (SA), and Atlantic
1 Beach, North Carolina (AB) canal studies can be found in their report
(E.P.A., 1975). Their Marco Island data (MIH, MIJ, MIL, MIM, MIN) has
not been published.

CHAPTER 4
MATERIALS AND.METHODS
Metabolism
The oxygen metabolism rates for the total canal communities and
the planktonic components were determined for each canal, except Punta
Gorda 9, Port Charlotte 9, and Pompano Beach 9.
Community metabolism was estimated by the free-water diurnal oxygen
method (Odum and Hoskins, 1958, see also Slack et^ al., 1973 for a
detailed outline). This technique assumes that the dissolved oxygen
change from sunrise to sunset in a volume of water can be attributed to
either net oxygen production of the biotic community in contact with the
water, or to oxygen diffusion across the air-water interface. Similar
ly, any change in dissolved oxygen levels from sunset to sunrise is
assumed to be due to either community respiration or to diffusion. By
neglecting or adjusting for oxygen diffusion, estimates of daytime net
production and nighttime respiration are obtained. By further assuming
that the daytime respiration rate equals the nighttime respiration rate,
the total gross primary production and respiration levels for a 24 hour
period can be calculated.
For the .first two sampling trips in 1975 (March and June), dis
solved oxygen profiles were taken every three hours for 24 hours at
four stations along each canal (32 stations on 8 canals). Oxygen values
were determined by Winkler titrations. Mean values for the water column
-40-

-41-
at each sampling interval were used to compute the community metabolism.
Oxygen stratification generally was present. Oxygen diffusion across
the air-water interface was neglected, since the mean values for the
water column and not the surface values were used in the computations.
Ignoring diffusion leads to Underestimates of metabolism, but was not
felt to be a serious source of error due to the generally quiescent
nature of the canal water.
After the first two sampling trips, oxygen profiles were taken at
every station for a sunrise-sunset-sunrise or a sunset-sunrise-sunset
sequence. The resulting three mean values for the water columns were
used to comput the daytime net production rates and the nighttime
respiration rates. The total community gross primary production and
2
total respiration were estimated on an areal (m ) basis from the two
rates, allowing for daylength on the sampling day and for water depth.
The planktonic contribution to the total community oxygen metabolism
was determined by light-dark bottle 24 hour In situ incubations at one
or more stations per canal. Pairs of light and dark bottles were sus
pended at one meter intervals throughout the water column. The changes
in dissolved oxygen levels were determined by Winkler titrations. To
2
obtain metabolism estimates on an areal (m ) basis, the values at the
discrete depths were integrated over the depth of the water column.
The production:respiration ratios for the total community and
plankton component were calculated from the respective 24 hour gross
2
primary production and respiration values (m ). The extent of plankton
dominance of the community primary production was calculated as the
ratio of the plankton GPP to the community gross primary production
values (canal means). The amount of solar insolation on the sampling

-42-
days was measured with a Belfort pyrheliometer.
Nutrient Exchange and Water Quality
The net exchanges of total carbon, inorganic carbon, total organic
carbon, total phosphorus, ortho-phosphorus, total organic phosphorus,
ammonia, turbidity, color, and conductivity across the canal entrances
were estimated by determining the total mass of each material entering
and leaving the canals during 24 hour periods. The concentrations/
values of these parameters were measured in surface water samples taken
periodically at the canal entrances. The volume and direction of water
flow across the canal mouths were determined from a recording tide
gauge and the canal water surface area. By summing the products of
the concentrations and volumes of flow for each sampling interval, the
total mass exchange for each material and each tidal phase was obtained.
Since the ebb and flood tidal phase volumes were not always equal, the
total mass exchange for each tidal phase was divided by the respective
total flow volume, to obtain weighted-average concentrations of each
material. The difference between the weighted-average concentrations
(flood-ebb) yield the net exchanges in concentration units. The mass
exchange values are not shown in the Results section but can be obtained
for each material by multiplying the weighted-average exchange concen
trations (Table 7) by the canal surface area (AREA) and the cumulated
24 hr tidal range (CUMTIDE) in Table 1.
Several assumptions were included in this approach to estimating
net exchanges. The water samples collected and the concentrations
measured were assumed to represent the average concentrations of the
water transported during the sampling intervals. The water surface was

-43-
assumed to have zero slope and have constant area, so that changes in
water level were proportional to the flow volumes.
During the first two sampling periods at the Punta Gorda, Port
Charlotte, Pompano Beach, and Loxahatchee River canals, surface and two
meter depth water samples were taken from the center of the canal
entrance (ca. 50 meters inside). For the remaining exchange observa
tions, hourly surface water samples were taken near the canal shoreline
by Serco Model NW3-8 Automatic Samplers. All water samples were
preserved with a solution of saturated mercuric chloride (1 ml/1) and
kept on ice until returned to the laboratory for analysis.
Total carbon and total inorganic carbon concentrations were deter
mined with a Beckman Model 915 Total Carbon Analyser. Total organic
carbon concentrations were then determined by subtracting the inorganic
carbon concentrations from the total carbon concentrations. Total
phosphorus concentrations were determined by persulfate digestion and
the Murphy-Riley single reagent method (APHA, 1971) Ortho-phosphorus
concentrations were also determined by the Murphy-Riley technique. Total
organic phosphorus concentrations were obtained by subtracting the
ortho-phosphorus value from the total phosphorus value. Ammonia analyses
were performed with an AutoAnalyzer using the indophenol method (E.P.A.,
1974). Turbidity levels were determined with a Hach Model 2100A
Analytical Nephelometer. Apparent-color was measured at a 420 nm
wavelength on a Bausch and Lomb Spectronic 88 spectrophotometer.
Specific conductance (25 C) values were obtained with a Beckman Model
RC 16B2 Conductivity Bridge.

-44-
Canal/Sampling Day Characteristics
The canal geometries and tidal exchange information for the Punta
Gorda, Port Charlotte, Pompano Beach, and Loxahatchee River sites, were
provided by B.A. Christensen, Hydraulics Laboratory, Department of Civil
Engineering, University of Florida. For the remaining canal sites, this
information was obtained from scaled maps, tide recordings and depth
profiles.
The recorded canal lengths were the distances along the canals from
the entrances to the most distant points. The mean centerline depths
and entrance-sill heights were determined from depth recordings. The
canal water surface areas were obtained from scaled maps. The canals
were assumed to be rectangular channels to that canal volumes were taken
as the product of the surface areas and mean depths. Canal ages were
obtained from local residents or estimated from comparisons of aerial
photographs and maps. The canal-water minimum residence times were
calculated as the ratios, mean depth:cumulated tidal amplitude, where
the cumulated tidal amplitude was the sum of the tidal ranges during
the 24 hour period.
Statistical Analyses
Descriptive statistics, principal components analyses, canonical
correlation analyses, and stepwise multiple regression analyses were
performed by an IBM 370 computer using the Statistical Analysis System
(Barr et al., 1976) package. Brief conceptual descriptions of the
multivariate methods and references for each are given in Chapter 4.

CHAPTER 5
RESULTS
As stated in the introduction, the data for this study were
collected in two phases. The first phase (1975 data) was done in con
junction with a more extensive team study (see Fox jilt 1. 1976 and
Piccolo e_t al., 1976) wherein pairs of similar canals at four locations
(Punta Gorda, Port Charlotte, Pompano Beach, Loxahatchee River) were
examined four times. The second phase consisted of single sampling
trips to eight other locations. At seven of these locations, data were
collected for three canals over single 24 hour periods. At the eighth
location (North Miami), data were collected for one canal over three
consecutive 24 hour periods.
Four types of data were collected for each canal: 1) metabolism
levels, 2) nutrient/water quality net-exchanges between the canals and
adjacent estuaries, 3) several basic water quality parameters, and
4) canal and the sampling day physical characteristics (shown in Site
Description section).
Analysis of the data has been done in four steps. The first step
is a presentation of the raw data, frequency distributions, and descrip
tive statistics for the metabolism, exchange, and water quality
responses. The second step is an attempt to evaluate the structure
of the data and to reduce the number of variables to a more manageable
figure without loss of information. The third step is an examination
of the association or correlations between the four data types, and the
-45-

-46-
final step is the generation of descriptive models that relate the
responses of the dependent variables to the levels of the independent
variables.
Sixty-four variables appear in the metabolism, exchange, water
quality, and physical characteristics data sets. The nomenclature for
the variables is shown in Table 2.
Metabolism
Combined Data
The metabolism results for the individual stations are included in
the Appendix. The mean values for the individual canals are presented
in Table 3. The frequency distributions and descriptive statistics
for the metabolic parameters are shown in Figures 14-20.
The mean value of total community gross primary production was
2
8.59 g O^/m -day for the 56 individual canal observations, with a
2
standard deviation of 5.87 g O^/m -day. These two values lead to a
coefficient of variation (C.V.) of 66 percent. The frequency distri-
2
bution and range (0.0 to 24.9 g O^/m -day) of the 56 observations are
shown in Figure 14.
The planktonic component of the total community had a mean gross
2
primary production of 4.91 g 02/m -day and a standard deviation of
2 2
3.91 g 02/m -day. The range of values (0.40 to 23.9 g.O /nr-day) and
the frequency distribution are shown in Figure 15. The coefficient
of variation (80 percent) suggests that plankton production is
relatively more variable in the canals than is the total community
gross primary production (C.V. = 66 percent). The frequency distribution

-47-
Table 2.
TGPP
TR
PGPPM2
PRM2
PGPPM3
PPRM3
TPR
PPR
PDOMIN
SUN
TC
TIC
TOC
TP
OP
TOP
NH3
TURB
COLOR
COND
F-prefix
E-prefix
Nomenclature for the variables.
METABOLISM
Total community gross primary production (g 02/m^-day)
2
Total community respiration (g O^/m -day)
2
Plankton gross primary production (g 0^/m -day)
2
Plankton respiration (g O^/m -day)
3
Plankton surface gross primary production (g O^/m -day)
3
Plankton surface respiration (g O^/m -day)
Community production:respiration ratio (TGPP/TR)
Plankton production:respiration ratio (PGPPM2/PRM2)
Plankton dominance of community production (PGPPM2/TGPP)
Solar insolation (langleys/day)
EXCHANGE
Total carbon concentration (mg/1 as C)
Total inorganic carbon concentration (mg/1 as C)
Total organic carbon concentration (mg/1 as C)
Total phosphorus concentration (mg/1 as P)
Ortho-phosphorus concentration (mg/1 as P)
Total organic phosphorus concentration (mg/1, TP-OP)
Ammonia concentration (mg/1 as N)
Turbidity (NTU)
Apparent color (CPU)
Conductivity (micromhos/cm r 100)
Weighted-average flood tidal phase concentration
Weighted-average ebb tidal phase concentration

-48-
Table 2.
(Continued)
D-prefix
Difference between flood and ebb concentrations (Flood Ebb)
Sign convention minus sign (-) indicates Flood value was less than
Ebb value
positive sign (+) indicates Ebb value was less than
Flood value
WATER QUALITY
AVGDO
Average dissolved oxygen concentration (mg/1)
MAXDO
Maximum dissolved oxygen concentration (mg/1)
MINDO
Minimum dissolved oxygen concentration (mg/1)
SECCHI
Secchi depth (meters)
TEMP
Water temperature (C)
E-prefix
Nutrient and water quality parameters from Exchange data
LENGTH
CANAL/SAMPLING DAY CHARACTERISTICS
Centerline length, entrance to most distant point (meters)
WIDTH
Average canal width (meters)
MDEPTH
Average canal depth (meters)
AREA
Canal water-surface area, total (meters)
VOLUME
Water volume in canal at mean water level (cubic meters,
MDEPTH AREA)
SILL
Sill height (meters)
AGE
Canal age (years)
BULK
Percent bulkheaded, canal sides
CURBS
Presence or absence of curbs and gutters in development
(1 or 0, respectively)
SEWERS
Presence or absence of a sewer system in development
(1 or 0, respectively)

-49-
Table 2.
MINRES
CUMTIDE
TIDE
DAYL
(Continued)
Minimum residence time of canal water (days, MDEPTH/CUMTIDE)
Cumulated tidal amplitude in 24 hr period (meters)
Maximum tidal amplitude in 24 hr period (meters)
Hours of daylight on sampling day
SUN
Solar insolation (langleys/day)

Table 3. Metabolism results averaged by canal (1 to 5 stations
per canal) for each sampling day.
Nomenclature and units as in Table 2

-51-
03 S
CANAL
MONTH
o a v
YtAk
ToPP
T R
PGPPM2
1
PC. 6
3
^l
73
3.1o
3 .28
1.64
2
PG 3
i
2 1
7b
1.15
4.06
2.10
3
PC3
3
2 2
75
0.44
10. 12
9. 1 9
4
PC b
3
4
7 5
3.37
b.03
5.79
5
Pu3
3
2 6
75
7. 64
8.85
7.01
b
Pb
3
2 o
75
5 bt
5 9t
7.56
7
LX 3
3
2 3
7 5
7.37
6.14
2.89
t
LXo
3
2b
7 5
b. fcb
5.06
2 ob
9
Pij b

l 4
73
b 5 o
5.51
2.3 9
1 0
PG 3
6
i 4
75
7.91
6.13
2.62
i 1
PC 3
b
l 3
75
1 1 C 7
9.61
3.90
1 2
PCo
6
1 5
7
/ b 3
10.22
6.50
1 3
P33
6
1 9
75
10.25
13.01
7.5 1
1 +
POb
6 '
1 9
7 5 ..
9.2d
14.15
6.45
1 5
LXc
6
1 t
75
6.8t
9 .46
2.07
1 b
LX J
6
l o
75
4.82
4.64
3.72
1 7
PG3
9

75
0 co
0.00
0.4d
1 t
PG
9 '
O
75
0.00
0 .00
0.61
l 9
PG9
9
b
75

'
#
30
PC3
9
9
75
2 0.73
18.15
3.29
1
PCD
9
9
7 5
4 3 9 3
23.51
5.93
32
PC i
9
9
7 5



23
P 83
9
7
7b
17.04
20.1 3
7.5b
24
Pb
9
7
75
14.15
l 4.05
10.04
2 5
LX J
9
1 4
.73
6 o t
6.47
3.67
26
LX6
9
1 4
75
11.47
t .87 '
7.12
27
PG
l 1
4 1
75
b. 10
3.25
2.80
2d
PG3
1 1
2 1
75
4.02
5.64
2.73
03 S
PRM2
P GPPM3
PPRM3
Pu
PPK
PDMIN
SUN
1
2.03
2.47
0 o 1
0.9 7
0.7o
0.52
602
2
2.05
2.23
1.07
O.DC
3.2 1
1.00
6 02
3
5.95
5.91
2.74
0 O 3
, 3.61
1.09
6 4 2
4
3 .20
3.57
2.94
0. 64
1 l
l 04
64 2
5
2.32
1 J .36
1.1o
0 fc>9
3.0 t
C t 9
4 88

2.63
12.65
0. t9
0.9 5
4 ,t6
1 .00
488
7
0 bb
2.73
O.dC
1.20
4 o 0
0.39
434
ti
1 75
2.00
0.67
1.1o
1.74
0.49
4 34
9
2.05
2.13
0.71
1.19
1 1 t
0.36
65 0
1 0
1.6b
3.23
0 .03
1.29
1 36
0.3t
650
1 1
4.57
4.34
2.0o
1.13
0 o
0.35
o 76
. i 2
7.9ti
3.99
1.73
0.7 5
0.90
0
o 76
1 3
6.4b
9.55
J.JS
0 79
1 1 o
0. 7 3
342
I 4
O.J3
9.5b
4,68
0 6b
1 Ot
0.69
342
1 5
2 t 7
4.55
1.44
0.7 3
0.72
0.30
37o
1 6
1 95
4.52
0.95
1 Oh
1 90
0.77
3 7 t
1 7
0.75
0.77
0.51

1 .2 0

426
l t
0.49
1.0b
0.4 c

2.92

426
1 9




.


20
3.77
5.66
2.04
1 1 4
0.93
0.16
4 4b
2 1
6.03
t .6 8
3.40
1.02
0.9b
0.25
4 4 6
22







23
2.74
11.69
2 .
0 fcO
o b ^
0.43
238
2 4
3.17
1J .72
1.90
1.01
3.4 1
0. 71
2 3 t
2 S
1.96
3.76
1 0 o
1 o 7
1 o 7
0.41
2 96
2 O
4.72
6.02
2. b4
1.29
1.49
0.62
29o
27
0.79
3.7o
0 o 2
1 t t
4.24
0.46
2 96
2 t
1 .37
4.4 1
4.10
4 t 9
1 .97 .
0.47
29o

-52-
Table
OBS
3. (Continued)
CANAL MONTH
DAY
YEAR
TGPP
TR
PGPPM2
29
PG9
1 1
21
75



JO
PC3
1 1
23
75
9.33
9.91
2.04
31
PC6
11
23
75
8.49
4.52
3.43
32
PC9
11
23
75



33
PB6
1 1
1 4
75
3. 39
3.06
3.45
34
PB9
1 1
14
75



35
PB3
11
14
75
3. 45
3.09
2.96
36
LX3
1 1
16
75
5.09
4 .60
2.87
37
LX6
11
16
75
3.42
3.67
3.03
38
MI 1
3
24
76
5. 86
5.72
5. 64
39
MI 2
3
2*4-
76
7.11
7.20
3.46
40
MI 3
3
24
76
9. 79
11.19
3.94
41
BC1
4
20
76
24.89
18.65
8. 04
42
BC2
4
20
76
16.30
14.30
8.61
43
BC3
4
20
76
1 5. 40
14.19
13.50
44
HI 1
5
19
76
7.65
2 .66
6.46
45
H I 2
5
1 9
76
7. 53
. 2.55
7.43
46
H 13
5
19
76
1 4. 79
5.65
23. 90
47
FL1
6
1 2
76
8.34
8 .63
3.19
48
FL2
6
12
76
1 2. 69
12 .69
2.9 1
49
FL3
6
12
76
8. 66
11.22
4.12
50
AP l
7
14
76
21.84
19 .89
4.00
51
AP2
7
1<4
76
15. 22
16.34
7. 71
52
AP3
7
14
76
10.63
10.82
3.30
53
GB1
7
31
76
1.56
2.86
1.20
54
GB2
7
31
76
2. 27
3. 57
0. 77
5b
GB3
7
31
76
1.95
2.15
0. 96
56
KC 1
8
18
76
5. 53
9.39
1 .39
OBS
PR M2
PGPPM3
PPRM3
TPR
P PR
POOMIN
SUN
29







30
0.74
2.01
0.56
0.94
1 .98
0.22
334
31
0.53
2.93
0.06
1.86
5.02
0.41
334
32







33
1.92
1 .39
1.51
1.11
1.79
1.02
352
34







35
1 .96
2.7 1
1.57
0.90
1.76
0.47
352
36
0.92
2.96
0.70
1.11
3.45
0.56
204
37
1 .49
3.10
0.93
1.13
2.04
0.78
204
38
3.67
6 .38
1.49
1.02
1.54
0.96
520
39
2.91
2.99
1 .27
0.99
1.19
0.49
520
40
4.9 1
3.40
1.56
0.87
0.80
0.40
520
41
4.35
4.81
1.54
1.33
l .64
0.32
571
42
3.20
4.41
1.37
1.14
2.69
0.53
57 1
43
5.24
6.02
1.68
1.08
2.58
0.88
5 71
44
2 .47
5.55
1.76
2.87
3.76
0.84
5 15
45
2.99
5.15
1.93
2.95
2.48
0.99
5 15
46
6.16
18.00
3.10
2. 62
3.81
1.00
51 5
47
3.92
3.26
2.17
0.97
0.6 1
0.38
504
48
4.98
1.77
1.75
1.00
0.58
0.23
5 04
49
3.48
3 .25
1.01
0.77
1.18
0.46
504
50
3.94
3.96
2.40
1.10
1.02
0.18
506
51
3.75
10.64
2.66
0.93
2.05
0.5 1
50 6
52
2.95
4.22
2.04
l .00
1.12
C .30
5 06
53
1.45
1 .67
1.62
0.55
0.83
0.77
554
54
0.74
1.18
1.12
0.64
1.04
0.34
554
55
0.46
1 .34
0.21
0.91
2.09
0.49
554
56
2.0 1
0.87
0.86
0. 59
0.69
0.25
72

-53-
Table 3. (Continued)
OBS
CANAL
MONTH
OAY
YEAR
T GPP
TR
P6PPM2
57
KC2
8
1 8
76
5. 51
6. 37
1.53
58
KC3
8
. 18
76
1.76
5.63
0.40
59
NM1
10
26
76
1.88
1 .96
9.06
60
NM2
10
2 7
76
11.10
4.15
10. 71
61
NM3
10
28
76
15.01
12. 10
6.40
62
PEI
8
14
74



63
PE2
8
1 4
74



64
BP3
8
19
74



65
BP4
8
19
74



66
SA8
8
23
74

67
AB3
9
17
74



68
AB5
9
1 7
74


69
MIH
8
8
75



70
MI J
8
1 0
75


71
MIL
8
6
75



72
MIM
8
6
75


73
MIM
8
8
75



74
MIN
8
7
75


UBS
PRM2
PGPPM3
PPRM3
TP R
PPR
PDOMIN
SUN
57
2.09
0.43
0.56
0.86
0.73
0.28
72
58
1 .36
0.38
0.60
0.31
0.2 9
0.23
72
59
5.02
3.81
3.10
0.96
1.80
1 .00
316
60
6.06
6.26
1.45
2.68
1 77
0.96
346
61
2.62
4.37
1.75
1.24
1.64
0.43
1 83
62







63


#



64






65






66




67







68





69






70







71
'






72




m


73


'



74








-54-
2
g 02/m -day
N = 56 Mean = 8.59 Std. Dev. = 5.87 Range 0.00 to 24.9
C.V.% = 66
Figure 14. Frequency distribution and descriptive statistics for
total community gross primary production (g 02/m^-day),
averaged by canal. Values are rounded to nearest integer.
N = 56 Mean = 4.91 Std. Dev. = 3.91 Range 0.40 to 23.9
C.V.% =80
Figure 15. Frequency distribution and descriptive statistics for
planktonic gross primary production (g C>2/m2-day) averaged
by canal. Values are rounded to nearest integer.

-55-
histogram suggests that a bimodal distribution was observed for
planktonic production. No canal actually exhibited the mean value of
2
5 g O^/m -day (values were rounded to nearest integer to construct
the histograms). The plankton production for these canals tended to
2
occur in two levels; a low range of 1-4 g O^/m -day, and a higher range
of 6-10 g C^/m^-day.
The distribution and descriptive statistics of the community and
planktonic respiration are shown in Figure 16 and 17, respectively.
2
Community respiration had a mean value of 8.20 g O^/m -day for the 56
2
canal observations, compared to 3.01 g O^/m -day for the plankton. The
standard deviation and range of the community respiration responses
2
(5.45 and 0.0 to 23.5 g O^/m -day) were greater than those of the
2
planktonic component (1.83 and 0.46 to 7.98 g O^/m -day). The relative
variabilities of respiration are comparable for the total community
and plankton (C.V. = 66 and C.V. = 61, respectively).
The frequency distributions and descriptive statistics for the
primary production:respiration ratios of the total community and
planktonic component, are presented in Figures 18 and 19. The mean
value (1.16) of the 56 community observations suggests that these
systems tend to be balanced or slightly autotrophic. However, the
range of values (0.31 to 2.95) indicate that canals can exhibit both
heterotrophic and autotrophic characteristics. The range of P:R ratios
(0.29 to 5.02) for the planktonic component of the total canal com
munities also indicates that both heterotrophic and autotrophic behavior
exists for the plankton. The mean value for plankton P:R ratio (1.93)
indicates greater autotrophy in the water column than for the entire
canal. From a trophic standpoint the planktonic component is relatively

-56-
N = 56 Mean = 8.20 Std. Dev* = 5.45 Range 0 to 23.5
C.V.% = 66
Figure 16. Frequency distribution and descriptive statistics for
total community respiration (g 02/m^-day), averaged
by canal.
2
g O2/111 -day
N = 56 Mean = 3.01 Std. Dev. = 1.83 Range 0.46 to 7.98
C.V.% = 61
Figure 17. Frequency distribution and descriptive statistics for
planktonic respiration (g 02/m^-day), averaged by canal

Observations
-57-
10
o P
J L
x
a
~i 1 1 1 1 1 1 1 1 K''*-1
0.3 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.9 2.6 2
TGPP/TR
N = 56 Mean = 1.16 Std. Dev. = 0.59 Range 0.31 to 2.95
C.V.% = 50
Figure 18. Frequency distribution and descriptive statistics for
total community production:respiration ratio, averaged
by canal.
PGPPM2/PPM2
N = 56 Mean = 1.93 Std. Dev. = 1.14 Range 0.29 to' 5.02
C.V.% = 59
Figure 19. Frequency distribution and descriptive statistics for
planktonic production:respiration ratio, averaged by
canal.

-58-
more variable than the total canal community (C.V. = 59 and 50,
respectively).
Figure 20 shows the frequency distribution and descriptive
statistics for the degree of plankton dominance of the total community
gross primary production for the 56 canal observations. The distri
bution seems to be somewhat bimodal with plankton production accounting
for 50 percent or less of the total community production in 31 of the
54 observations. In other words, some canals were plankton dominated
on the day sampled but others were not. The range of values (PGPPM2/
TGPP) was 0.16 to 1,0. The mean value (0.60) for all the observations
may be misleading since few of the responses were this value.
1975 Data
Thirty-two of the fifty-six metabolism observations were obtained
during 1975 in a study for the Florida Department of Environmental
Regulation (see Fox et ai., 1976). The design of the project consisted
of four locations (Punta Gorda, Port Charlotte, Loxahatchee River, and
Pompano Beach) with two similar canals per location, four stations per
canal (bay, mouth, middle, andback), and four sampling seasons (March,
June, September, and November).
This design allowed the factors of location, season, and distance
along the canals to be evaluated for significant effects on the
metabolic levels. In addition to making possible the assessment of
the seasonal and distance variabilities, the unexplained or inherent
variability between canals that appeared identical could be determined
using analysis of variance.
The canal mean metabolic levels from this 1975 work are included

Observations
-59-
10
5 h
0
i i "i i i 1 1 1
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
PGPPM2/TGPP
N = 54 Mean = 0.60 Std. Dev. = 0.28 Range 0.16 to 1.0
C.V.% = 101
Figure 20. Frequency distribution and descriptive statistics for
plankton domination of community production.

-60-
in Table 3 for the eight canals and four seasons. The individual
station results are presented in the Appendix. The results of the
analyses of variance on the data are shown in Table 4.
The analyses indicate that there are significant differences in
the levels of community production and respiration with the season of
the year, with the location of the canal, and with distance up a canal.
This three way interaction indicates tht the spatial and temporal
distribution of metabolic levels in these residential canals is a
non-additive function of the distance, location and season factors.
The seasonal changes have different effects on community metabolism
depending on the canal location and on the distance up the canal. The
lack of simple trends for any of the three factors can be illustrated
by the fact that the highest community metabolism levels occurred
during September for all locations except Punta Gorda, where the level
was the lowest recorded for the year.
The sources of variation listed i'n Table 4 account for 88 and 87
2
percent (R value) of the community production and respiration vari
ability, respectively. The remaining 12 percent of the variability
is composed of the error involved with the determinations of the
metabolic levels and with the difference in metabolism levels of the
individual canals within the pairs, which were treated as replicate
observations; the latter source of residual variance could be a result
of factors such as plankton patchiness, water circulation patterns, and
nutrient inputs. This small amount of unexplained variability indicates
that the individual canals within the pairs of canals do not differ
appreciably in the patterns and levels of metabolic activity, relative
to the total variability for all locations, seasons, and distances.

-61-
Table 4. Results of the analyses of variance for the total community
and planktonic metabolism data (1975).
Source of
Variation
Community
Plankton
Per Square Meter
Per Square Meter
Surface
GPP*
R*
P/R*
GPP
R
P/R
GPP
R
Location
NS
NS
Distance
NS
NS
NS
NS
Month
, NS
Location x Distance
, NS
NS
NS
NS
**
NS
Location x Month
NS
**
**
NS
**
**
Distance x Month
NS
NS
NS,
**
NS
NS
Location x Distance
**
**
; NS
NS
NS
NS
NS
NS
x Month
Mean
7.80
7.49
1.36
4.01
2.56
2.30
4.71
1.47
S.D. (adjusted)
2.95
3.30
1.80
1.69
1.64
1.52
1.68
0.91
C.V. %
37
44
132
42
64
65
35
62
R2
0.88
0.87
0.50
0.83
0.77
0.77
0.92
0.77
Unadjusted S.D.
6.22
6.49
1.77
2.63
2.20
2.01
* GPP gross primary production; R respiration;
P/R production : respiration ratio (GPP/R)
** Indicates the term is a significant source of variation
NS Indicates the term is not a significant source of variation
Blank indicates that an exact test for the term cannot be made
2 3
Units-, g O^/m -day or g O^/m -day

-62-
The community production:respiration ratio analysis does not
yield the same:pattern as the production and respiration results. No
significant differences were found for the 64 combinations of location,
distance and month factors. The mean value for all observations was
1.36 with a coefficient of variation equal to 132 percent. This para
meter was relatively more variable than production and respiration for
the replicate canals, resulting in the inability to detect differences
among the means.
Analysis of the planktonic metabolism data yields inferences some
what different from those of the whole community metabolism. The level
of planktonic gross primary production and respiration on a square
meter basis depends on the season and the location. No significant
differences in the levels of planktonic production and respiration for
the entire water column could be detected along the lengths of the
canals.
There were significant differences among the means of the plank
tonic P:R ratio. The changes in the P:R ratio with season varied
depending on the distance up the canals.. No significant differences in
the patterns of planktonic P:R ratios was detected for the four
locations.
The results of the analysis of variance for the surface values of
planktonic metabolism were similar to those for the entire water columns.
The effect of distance and season varied with canal location for the
surface plankton production, whereas only the effect of season varied
with location for the entire water column. In fact, no effect of
distance up the canal could be detected for the planktonic metabolic
levels on a square meter basis, for these canals.

-63-
The variability or standard deviation remaining after the re
sponses were adjusted for the three factors and their interactions is
also shown in Table 4. These unexplained variances represent the
dissimilarity between canals that appear identical, for the individual
parameters. For example, the community gross primary production values
2
had a standard deviation of 6.22 g C^/m day before adjustment for the
2
factor effects, and 2.95 g O^/m -day after adjustment. The latter
value indicates the variability of community production estimates once
the canal location, the season of the year, and the distance along the
canal have been specified. The corresponding unexplained variability
2
for the plankton production data is 1.69 g O^/m -day.
While the analyses of variance for the metabolic parameters in
dicated that no consistent trends existed for all the locations and
sampling periods, the mean values (Table 5) computed by location, by
season, and by distance for all the data show the average pattern for
these different factors.
Community gross primary production was lowest in March (5.13
2
g O^/m day)> increased through June, peaked in September (11.2 g
2
O^/ni -day), and then declined in November. The production:respiration
ratio for the total communities increased each sampling season to a
peak in November (mean P:R = 2.34), whereas the planktonic P:R ratio
was highest in the fall and lowest in June.
The mean values of the metabolic parameters with distance along
the canal (Table 5) suggest that the community and plankton production
tends to increase from the adjacent estuary (Bay) to the middle and
back of the canals. It would be tempting to conclude that these canals
were more productive than the adjacent estuaries. However, the

-64-
Table 5. Community and plankton gross primary production (g 0 /m -day)
means for the four locations sampled in 1975, averaged by
location, by season, and by distance along canal.
TGPP
PGPPM2
TPR
PPR
Means by Location
PG
3.74
1.85
1.56
2.11
PC
10.5
4.87
1.71
2.35
PB
8.48
6.43
0.98
2.39
LX
6.15
3.46
1.18
2.44
Std. Dev.
2.92
1.96
0.34
0.15
Means by Month
March
5.13
4.78
0.94
2.55
June
6.63
4.16
0.98
1.21
September
11.2
4.47
1.32
1.92
November
5.53
2.89
2.34
3.40
Std. Dev.
2.79
0.83
0.65
0.93
Means by Distance Along Canal
Bay
5.33
2.53
1.29
3.23
Frong
6.68
3.96
1.11
2.27
Middle
8.28

1.16

Back
8.20
4.40
1.87
2.07
Std. Dev.
1.40
0.98
0.35
0.62
Grand Mean
7.18
3.98
1.36
2.31
Nomenclature as in Table 2
2
Units g 0 /m -day

-65-
analysis of variance detected no significant differences for plankton
production between the bay and canal stations, and indicated that the
effect of distance on community metabolism depended on the location
and month. No significant differences for community production:
respiration ratio could be detected for distance, season, or location,
though the highest mean value was found at the backs of the canals.
For the planktonic P:R ratio the lowest mean value occurred at the
backs of the canals; the highest mean value occurred in the bay, but
again this cannot be considered a consistent pattern since the analysis
of variance found that the effect of distance depended on the month of
sampling.
Daily Variability in One Canal
One canal (North Miami site) was sampled for three consecutive
days to obtain an estimate of the day-to-day variability for one canal;
the metabolism results are shown in Table 6.
The estimates of planktonic primary production were quite repro
ducible when the level of solar insolation is considered. The planktonic
production:respiration ratios were also consistent (mean = 1.74,
C.V. % = 5) for the three days. The community metabolism results,
2
however, were not as uniform (mean TGPP = 9.33 g 0^/m -day, C.V. % =
72). The changes of community primary production, community respiration
and the community production:respiration ratio estimates did not
parallel those of the plankton for the three day period.
The most likely explanation of the seemingly sporadic total com
munity results for the three consecutive days at the North Miami site,
is the limitation of the estimation technique. The free-water diurnal

-66-
Table 6. Metabolism results for three consecutive days of sampling on
one canal
(North Miami
site).
Date
TGPP
TR
PGPPM2
PRM2
PGPPM3
PPRM3
26 Oct 76
1.88
1.96
9.06
5.02
3.81
3.10
27 Oct 76
11.10
4.15
10.7
6.06
6.26
1.45
28 Oct 76
15.0
12.1
6.40
2.62
4.37
1.75
Mean
9.33
6.07
8.72
4.57
4.81
2.10
Std. Dev.
6.73
5.33
2.17
1.76
1.28
0.88
C.V. %
72
88
25
39
27
42
Date
TPR
PPR
PDOMIN
SUN
26 Oct 76
0.96
1.80
4.82
316
27 Oct 76
2.68
1.72
0.96
346
28 Oct 76
1.24
1.64
0.43
183
Mean
1.63
1.74
2.07
281
Std. Dev.
0.92
0.08
2.40
87
C.V. %
57
5
1.16
31
Nomenclature as in Table 2
2 3
- g O^/m -day or g 02/m -day
Units

-67-
method requires a homogeneous water column, to be reasonably accurate
and precise. The North Miami canals were approximately six meters deep
and were anaerobic below the two meter depth throughout the three days.
The chemical oxygen demand of the hydrogen sulfide (strong odor present)
in the large anoxic layer could remove varying amounts of oxygen from
the surface layer. The weather conditions during the three day study
in October were also not conducive to uniform conditions within the
canal (a cold front was passing through the area, producing colder air
and strong shifting winds). The deep stratified North Miami canal
during a period of water column overturn, was inappropriate for appli
cation of this technique. The only other occasion when a canal with
anoxic bottom water was sampled during a period of overturn was Port
Charlotte (Canal PCI) in November 1975.
Nutrient Exchange
Combined Data
The weighted-average flood concentrations, the difference between
the flood and ebb concentrations for the nutrient/water quality para
meters determined for each canal observation during this study, plus
those obtained from the Environmental Protection Agency, are shown in
Table 7. The frequency distributions and descriptive statistics for
the weighted-average ebb concentrations and net changes of the carbon
forms, phosphorus forms, ammonia, and turbidity are presented in
Figures 21-28. A positive (+) sign with the net exchange values in
dicates a net retention or sink type of activity. Conversely a negative
(-) sign indicates a net export or source type of activity.

Table 7. Canal-estuary exchange results for the nutrient and water
quality parameters.
Nomenclature and units as in Table 2

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p p p cr c o -v ce o vii p *m o cr. >
ii i lili i
0--CU-^00--Uoo^,"0
Crc O'CQ C- p V'-P f CI-hP
O' ~J P CV (V
I I I
o o rv rv
x c r c n x
ii i
ri a o, a p, cp u cr.rv rv p o cr e serene
rvcrPcntrP'croorvrvtnuCPPoorvrvcntrPP
per NUU;P-aO'v-c.OMCiiPrv-opc'P
u *- o- en o *o cr- >i cr 0: a G to g rv g o -v a -
i
i i
i
i
r > z > n
i i i
o o o
k c>- c> rv rv pop--'
c o cr o cr p o o p g g ex c pc,c ere. c c p p, o
c vr cr rvto cr p- cr a cr g o rv < 0 p u r "¡ rv p rv
i lili i ii i
o o o-c'orrcoo-oooco o rv o
-V o P P 0.1 Cv P- o 0- tv P- -J G G. P cr
OOSPiC--- COOCN'C -vlCC -0 C
n'
o ~i r
r x
r c
n r
n c h o
TiX
1
o o o o
OOOOOOOoOoOOoOOOO oooo
orvo-'-errorvoo ooop oo o oo o
PO'a'i'iP'a;iv)-uouiNU-p(r __ tv g as cn
no p p p cr Ppoo --o'cruicroorv^'ppuicj
o cr ->i cr o p o- rv rv -g a o a p Cv rv rv o cr o rv ov-si
~oc,|OCrtoNtna.PGOoto-vicoG''JtP g -* u g n
x h r
X O X
CT\
vo
I

-70-
Table 7. (Continued)
C M
A
0
Y
F
D

N
N
0
E
F D
F
D T
T
F
D
F
B
A
T
A
A
T T
1
I

T
T
0
5
L
H
Y
R
C C
C
C C
C
P
P
P
24
PB6
9
7
75
41.3 -
0.4 26
.6 1.9 15.0
1
.5
0 .254
-C.016
0.206
2b
LX3
9
12
75
50. 1 -
0.3 32
.7 0.8 17.4
-l
. 1
0.051
-0.002
0.063
26
LX6
9
1 2
75
49.1 -
0.1 33
.1 0.4 16.0
-0
.4
0.048
-0.009
0.058
27
PG6
1 1
21
75
33. 2 -
0.9 18
.5 -0.4 14.7
-0
.5
0.296
-0.030
0.257
28
PG3
1 1
21
75






'
29
PG9
1 I
21
75
34.0 -
0.4 15
.6 -0.S 18.4
0
.7
0.382
0.012
0.356
30
PC3
1 1
23
75
34.4
1.2 21
.5 0.4 12.7
0
. 6
0.349
0. 007
0.303
31
PC 6
1 1
23
75
35.1
0 .0 18
.0 0.0 17.1
0
.0
0.332
0. 022
0. 296
32
PC 9
11
23
75
34.3 -
1.1 19
.9 0.5 14.4
-l
.6
0.346
-0.0 1 l
0 .283
33
P86
1 1
14
75
57.8 -
0.1 41
5 1.3 16.2
-1
. 5
0.236
-0.014
0.203
34
PB9
1 I
l 4
75
5 7.0
0.7 42
. 1 -0.5 14.9
1
.2
0.224
-0.012
0.196
5 b
PB 3
1 1
14
75


...




36
LX3
1 1
1 6
75
49. 4
6.2 34
.0 1.5 15.4
4
6
0.057
0. 003
0.016
37
LX 6
1 1
1 6
75


... .




38
Mil
3
24
76
39.0 -
5.4 23
*3 O.b ib.6
-5
.9
0.067
-0.016
0.043
39
M I 2
3
24
76
36.9 -
1.6 22
.1 -0.9 14. 7
-0
. 7
0.064
0.004
0.043
40
MI 3
3
24
76
3 5.8 -
0.4 24
.2 0.3 15.5
-0
.7
0.082
0.029
0.044
4 1
BC1
4
20
76
36.4
0.9 13
.7 1.2 22.7
-c
. 4
0.193
-0.004
0. 1 58
42
BC 2
4
20
75
3 8. 1
0.9 12
.7 -0.1 25.3
0
.9
0.210
0.008
0.166
43
BC3
4
20
76
37. 5
2.4 12
. 1 2.2 25.4
4
.8
0.184
-0.010
3.159
44
H11
5
1 9
76
49.9
1 .8 21
.1 0.5 2 8.9
1
. 4
0.063
0. 01 1
0. 044
45
HI 2
5
19
76
42.0 -
0.6 16
.4 -1.0 236
0
.2
0 .041
0.002
0.025
46
HI 3
5
1 9
76
47.8
2.5 22
.4 0.3 25.4
2
. 1
0. 120
-0.003
0.104
F
D
F D
C
C
F D
F
0
F
D T T

0
C C
0
D
T
T
N
N U U
L
L
0
B
O
O

H
H R R
0
0
N N
S
P
P
P
3
3 b B
R
R
D D
24
0
0 1 2
0.
048
- 0.004
0.06
-0.184.2 0.
7
112
7

25
-0 .
01 C
0.
000
0.000
0.06
0.03 4.5 -0.
3
124
3

26
-0.
009
0.
000
0.000
0.02
0.03 4.1 0.
2
1 1 5
18

27
-0.
031
0.
038
0.001
0.07
-0.02


28




. .


29
c.
0 14
0.
026
-0.002
0.01
-0.07 .


30
0 .
003
0 .
045
0.003
0.21
0.0 1


31
0.
019
0 .
036
0.004
0.06
C .10 .


32
-0 .
029
0.
0 64
C. 01 9
0.04
0.04 .

33
-0.
002
0.
031
-0.014
0.23
0.00 .


34
-0.
007
0.
028
-0.005
0.23
C. 0 2 .


35




. .


36
0.
004
0.
041
0.000
0 .05
0 .0 1


37




. .


38
-0 .
01 3
0.
025
-0.003
0.10
-C.01 5.7 0.
9
35
2
345 -2
39
0.
002
0.
021
0.002
0.06
0.0 1 3.0 -0.
1
1 4
- 12
343 -8
40
0.
0 1 1
0.
037
0.017
0.05
0.02 4.1 0.
4
26
-13
337 -14
41
-0 .
007
0.
034
0.003
0 .05
0.02 3.1 -2.
1
2 1
-7
260 -20
42
-0.
002
0.
044
0.010
0.15
0.00 5.4 0.
8
2 1
5
274 9
43
-0.
009
0.
025
-0.005
0.10
0.03 2.6 0.
5
1 2
-8
268 9
44
0 .
01 1
0 .
019
0.000
0.14
0.04 1.0 0.
0
52
-2
307 -23
4b
0.
0 02
0.
C 16
0. 000
0.12
0.03 0.5 0.
2
25
- 18
376 21
46
-0 .
003
0 .
016
0.000
0. 11 -0.02 1.2 0.
1
69
4
294 -5

-71-
Table 7. (Continued)
C M
A

Y
F
D
o
N
N
D
E
F

F D
7
T
F
O
B
A
T
A
A
T
T
1 1
O
O
T
T
S
L
H
Y
R
C
C
C C
C
C
P
P
47
FL1
6
1 2
76
41.0
1.1
22.6 -0.3
18.
4
1

4
0 .
0 90
0.004
48
FL.2
6
12
76
40.3
1 1
23.8 1.0
16.
5
0
9
1
0.
092
0.009
49
Fl_3
6
l 2
76
41.3
2.0
22.5 1.2
18 .
9
1

0
0 .
095
0.007
50
AP 1
7
14
76
37.6
- 1 j
13.1 0.5
22.
9 -
2

5
0.
842
-0.025
5 1
AP2
7
1 4
76
44.6
7.5
16.8 2.5
27 .
7 10

0
0 .
807
0.020
52
AP3
7
14
76
40.3
0.0
13.6 -1.5
26.
7
1

7
0 .
842
0.006
53
GB 1
7
3 1
76
32.7
1.6
1 4.4 -0.9
18.
3
2

5
0.
02 1
-0.001
54
GB2
7
3 1
76
28.0
-0.1
15.S 0.2
12 .
1 -
0

3
0 .
023
0.001
55
GB 3
7
31
76
30. 1
-2.5
16.2 0.0
13.
9 -
2

5
0 .
030
-0.007
56
KC1
8
1 8
76
34.9
1.7
25.4 0.0
9 .
5
1

7
0.
02 1
0.002
57
KC2
8
1 8
76
32.4
0.5
25.0 0.4,
7 .
3
0

0
0.
0 18
0 .00 l
58
KC3
8
1 8
76
30.6
0.2
24.9 0. 1
5.
7
0

1
0.
01 4
0.000
59
NM1 10
2 6
76
54 .8
-0 .4
12.6 0.6
42.
2 -
1

0
0 .
065
0.000
60
NM2 10
2 7
76
56.7
1 1
15.6 C.4
42 .
0
0

4
0 .
066
0 .004
6 1
NM3 10
28
76
53.0
0.3
12.6 -0.4
40.
6
0

7
0.
054
-0.001
62
PE 1
8
14
74

-
'
15 .
6 -
0

2
0.
310
-0.020
63
PE 2
8
1 4
74



15.
3
0
9
6
0.
200
-0.020
6 4
BP3
8
1 9
74



1 .
a -
0
9
1
0.
040
0.000
65
BP 4
8
1 9
74
9
9
9
1 .
9
0
9
0
0 .
030
-0.010
66
SA8
8
23
74


9 9
1 .
0
0
9
0
0.
030
0.000
67
AB3
9
1 7
74

m
9 9
3 .
3 -
0
9
l
0.
030
9
6 b
AB5
9
1 7
74

9
9 9
2 .
6
0
9
2
0 .
040
-0.0 10
69
MIH
8
8
75

9
9 9
7.
0 -
1
9
2
0.
179
0.029
F
D
F
D
C
C
F
D
F
o
F
D
T
T
0
0
C
C
O
F
D
T
T
N
N
U

L
L
O
O
B
0
0
0

H
H
R
R
O
0
N
N
S
P
P
P
P
3
3
B
B
R
R
D
D
47
0.037
0.
004
0. 053
C.
000 0.OS 0
. 01
4.
5
0
. 8
236
43
341
-2
48
0.035
0 .
002
0.059
0.
008 0.05 0
.01
4.
7
0
. 6
219
43
337
-5
49
0.03 8

0.
001
0.057
0.
009 0.08 0
.02
4 .
8
1
.3
1 70
44
3 35
-4
50
0.692
0 .
028
0.151
0.
003 0. 04 0
.01
3.
9
-0
. 9
l 07
-6
274
3
51
0. 747
0 .
025
0.076
0.
001 0.06 0
.00
5 .
0
-0
.3
1 09
-6
275
1
52
0.731
0.
02 7
0.111
0.
004 0.06 0
.02
6.
0
0
.4
126
1
268
1
53
0.015
0 *
00 1
0.003
-0 .
00 1 0. 07 0
.00
2.
8
-0
. 4
1 12
0
266
-3
54
0.0 16
0 .
000
0.007
c.
001 0.09 0
.02
2.
8
-0
.3
93
-7
269
4
d5
0. 019
-
0 .
005
0.011
-0.
002 0.07 0
.00
4 .
8
0
.2
140
-12
285
0
56
0.003
0 .
003
0.0 18
0 .
005 0.07 -0
. 04
1 .
8
-0
. 2
26
-3
448
0
57
0. 004
0 .
001
0.014
0 .
001 0.03 -0
.0 1
2.
4
0
.4
37
6
446
3
58
0.004
0.
000
0.0 10
0 .
00 1 0. 01 0
.00
1 .
8
-0
. 1
20
-5
443
-4
59
0.034
0 .
002
0.029
0.
000 0.04 0
.0 1
3.
0
0
. 0
85
3
260
2
60
0.032
0.
003
0.032
0.
001 0. 04 0
.03
3.
4
0
. 1
9 1
7
259
-4
6 1
0.025
0 .
000
0.028
-0.
00 1 0. 02 0
. 03
3. 4
0
. 1
85
-3
265
-4
62




0.12 -0
.01






63
9

9

0.10 -0
.04

9




64




0.06 0
.00

9




65

9

9
0.08-0
.02

9


9

66

9

9
0.04 -0
.01
9
9

9

67



9
0.09 0
.00
9
9
9

9

68




0.08 -0
.02
9
9
9
9

9
69




0. 02 0
.00
9
9
9

9

-72-
Table 7. (Continued)
C
M
A
0
Y
G
N
N
D
E
F

F
B
A
T
A
A
T
T
I
S
L
H
Y
R
C
C
C
70
MI J
8
10
75



71
MIL
8
6
75



72
MI M
8
6
75



73
M IM
9
8
75

*

74
MIN
8
7
75



F
O
F
0
D
F
D
r
T
N
B
T
0
O
G
G
H
S
P
P
P
P
P
3
70
0.0 93




0 .0 3
71
0.004




0.0 1
72
0.006




0.01
73
0.010



0.03
74
0.003




0.03
F D
D T T F
10 O T
C C CP
. 10.7 1.7 0.257
. 6.2 -0.1 0.072
. 6.6 0.3 0.090
. 6.2 0.1 0.095
. 8.4 -0.2 0.095
F D
F D C C F 0
D T T C C C C
N U U L L G O
H R R G O N N
3 B B R R D D
0.01 . .
0.01 . .
0.00 . . .
0.01 .
0.01 . .

-73-
The total mass exchange of each material is not shown in Table 7
but can be calculated for each canal observation from the net change in
concentrations (weighted-average flood concentration minus weighted-
average ebb concentration) in Table 7 and the information in Table 1.
The product of the cumulated 24 hr tidal amplitude (CUMTIDE, Table 1)
and canal surface area (AREA, Table 1) for a particular canal observa-
3
tion yields the tidal exchange volume (m ) for the sampling day. The
product of the exchange volume and the net changes in concentration from
3
flood to ebb tidal phases (D values in Table 7, mg/1 or g/m ) gives
the net mass transport (g/day) of each material.
The average total carbon concentrations (Figure 21) ranged from
24.1 mg/1 to 57.9 mg/1, with a mean of 38.0 mg/1. The estimates of
net exchange of total carbon ranged from a net export of 5.4 mg/1 of
exchanged water, to a net retention of 7.5 mg/1 of exchanged water.
The mean value for net exchange was a net retention of 0.2 mg/1, with
a standard deviation of 2.0 mg/1. The distribution of net exchange
responses indicates that all canals do not exhibit the same type of
behavior. About equal numbers of these canals were found to be sources
of carbon to the adjacent estuaries, as were found to be sinks for
carbon from the estuaries.
The average inorganic carbon concentration (Figure 22) was 20.6
mg/1, with a standard deviation of 7.6 mg/1 and a range of 7.8 to 42.6
mg/1. The mean value for inorganic carbon exchange was a net export of
0.1 mg/1 of exchanged water, with a standard deviation of 1.1 mg/1 and
a range of -3.4 to +2.1 mg/1.
The mean total organic carbon concentration (Figure 23) was 15.5
mg/1, with a standard deviation of 8.3 mg/1 and a range of 1.0 to 43.2

-74-
a. Average ebb concentration of total C.
mg/1
N = 58 Mean = 38.0 Std. Dev. =8.0 Range 24.1 to 57.9
b. Net change (flood-ebb) of total C.
N = 56 Mean = +0.2 Std. Dev. 2.05 Range -5.4 to +7.5
Figure 21. Frequency distribution and descriptive statistics for
(a) weighted-average ebb total carbon concentration (mg/1),
and (b) the net changes from average flood concentrations.

-75-
a. Average ebb concentration of inorganic C.
4-1
o
u
D
cn
C
O
H
U
>
M
CL)
M
!a 43
o
15
10
5
0
N = 58 Mean = 20.6 Std. Dev. = 7.6 Range 7.8 to 42.6
b. Net exchange (flood-ebb) of inorganic C.
mg/1
N = 56 Mean = -0.1 Std. Dev. = 1.1 Range -3.4 to +2.1
Figure 22. Frequency distributions and descriptive statistics for
(a) weighted-average ebb inorganic carbon concentrations
(mg/1), and (b) the net changes from average flood con
centrations.

Observations
-76-
a. Average ebb concentration of organic C.
1.0 4.0 7.0 10 13 16 19 22 25 28 31 40
43
mg/1
3
N = 71 Mean = 15.5 Std. Dev. =8.3 Range 1.0 to 43.2
b. Net change (flood-ebb) of organic C.
15
10
5
0
nig/1
3.6
N =69 Mean = +0.2 Std. Dev. = 2.0 Range -5.9 to +10.0
Figure 23. Frequency distributions and descriptive statistics for
(a) weighted-average ebb total organic carbon concentrations
(mg/1), and (b) the net changes from average flood con
centrations.

-77-
mg/1. The mean value for net organic carbon exchange was a net reten
tion of 0.2 mg/1 of exchanged water, with a standard deviation of 2.0
mg/1. The values ranged from a net export of 5.9 mg/1 at Marco Island
canal Mil, to a net retention of 10 mg/1 at Apollo Beach 2. The most
frequent response, however, was no significant change in the organic
carbon concentration between estuarine water entering and that leaving
the canals.
The range of total phosphorus concentrations (Figure 24) in these
canals was large, reflecting the presence of phosphate mining in the
vicinity of some of the canals. The highest values observed (ca. 0.8
mg/1) were at the Apollo Beach site. The higher values make the mean
value (0.231 mg/1) somewhat misleading, considering that nearly half
of the observations had values less than 0.1 mg/1. The net changes in
total phosphorus concentrations from flood to ebb tides had a mean
value of +0.003 mg/1, with a standard deviation of 0.020 mg/1 and a
range of -0.067 to +0.093 mg/1. As in the case of total carbon, these
canals differ in the phosphorus mass transport activities, but most
frequently have little or no effect on the phosphorus loads of the
exchanged water.
The frequency distributions and descriptive statistics for the
ortho-phosphate levels and exchange responses of these canals are
presented in Figure 25. The ortho-phosphate distribution follows a
pattern similar to that of total phosphorus. The range of net exchange
responses (-0.031 to +0.069 mg/1) indicates that some canals can be
sources of ortho-phosphate to the estuaries, while other canals can be
sinks. The most frequent response was essentially no effect on the
ortho-phosphate concentrations, whereas the mean value (+0.005 mg/1)

-78-
a. Average ebb concentration (ppm) of total P.
mg/1
N = 71 Mean = 0.231 Std. Dev. = 0.226 Range 0.014 to 0.867
b. Net change (flood-ebb) of total P.
-.022 -.012
-.032
.017 .027
.043
.093
-.002 .007
mg/1
N = 68 Mean = +0.003 Std. Dev. = 0.030 Range -0.067 to +0.093
Frequency distributions and descriptive statistics for
(a) weighted-average total phosphorus concentrations (mg/1),
and (b) the net changes from average flood concentrations.
Figure 24.

Observations Observations
-79-
a. Average ebb concentration of ortho-P.
b. Net change (flood-ebb) of ortho-P.
mg/1
.057
N =.56 Mean = +0.005 Std. Dev. = 0.024 Range -0.031 to +0.069
Figure 25. Frequency distributions and descriptive statistics for
(a) weighted-average ebb ortho-phosphate concentrations
(mg/1), and (b) the net changes from average flood con
centrations.

-80-
suggests a slight retention of inorganic phosphate by the canals.
Figure 26 shows the frequency distributions and descriptive
statistics for the total organic phosphorus (TP-OP) concentrations and
net exchanges. The organic phosphorus concentrations are more normally
distributed around the mean value (0.043 mg/1) than are the total and
ortho-phosphorus concentrations. The net organic phosphorus exchange
estimates also exhibit a wide range of values (-0.069 to +0.042 mg/1),
and a mode of essentially zero effect on the organic phosphorus levels
of the estuarine water entering the canals. The mean value (-0.002
mg/1), though, suggests that a net export of organic phosphorus took
place.
The frequency distribution and descriptive statistics for the ebb
concentrations and net exchanges of ammonia for these canals are shown
in Figure 27. The ranges of concentration (0.00 to 0.26 mg N/l) and of
net exchange (-0.18 to +0.08 mg N/l) are wide. The mean value of ammonia
exchange (0.00 mg/1) indicates that the "average canal" has no effect
on the ammonia levels of the estuarine water. The distribution of the
exchange responses shows that some canals are sources of ammonia to
the estuary, whereas other canals are sinks.
The distributions of the average ebb turbidity levels and the net
changes in turbidity levels from ebb to flood tide for these, canals
(Figure 28), show the ranges of values and of effects on the flooding
waters. The mean net change value (+0.2 NTU) suggests that the "average
canal" lowers the turbidity level of the estuary. But the range of
values (-2.1 to +5.0 NTU) show that canals can either decrease or
increase the turbidity levels of the entering water.

Number of Observations
-81-
a. Average ebb concentration of organic P.
b. Net change (flood-ebb) of organic P.
-.049 -.038 -.017 -.007 +.002
-.027
mg/1
.012
.022
.042
N = 56 Mean = 0.002 Std. Dev. = 0.017 Range -0.069 to +0.042
Figure 26. Frequency distributions and descriptive statistics for
(a) weighted-average ebb total organic phosphorus con
centrations (mg/1) and (b) the net changes from average
flood concentrations.

-82-
a. Average ebb concentration.
N = 71 Mean = 0.08 Std. Dev. = 0.06 Range 0.00 to 0.24
b. Net change (flood-ebb).
3 15
<4-1 O
O -ri
j-i ta 10
a) >
S u
B a)
3 to c i_
2 3 D I
O
0
-i V,
s
i 1 1 1 1 1 1 1
-.18 -.10-.07-.04 -.03-.02 -.01 .00 +.01.02 .03 .04
mg N/l
N = 69 Mean = 0.00 Std. Dev. = 0.03 Range -0.18 to +0.08
.08
Figure 27. Frequency distributions and descriptive statistics for
(a) weighted-average ebb ammonia concentrations (mg/1) and
(b) the net changes from average flood concentrations.

-83-
a. Average ebb value of turbidity.
NTU
N = 50 Mean = 3.4 Std. Dev. = 1.4 Range 0.7 to 6.9
b. Net change (flood-ebb) of turbidity.
N 48. Mean = +0.2 Std. Dev. = 1.1 Range -2.1 to +5.0
Figure 28. Frequency distributions and descriptive statistics for
(a) weighted-average ebb turbidity levels (NTU) and (b) the
net changes from average flood concentrations.

-84-
Diurnal Cycle of Nutrient Concentrations
A diurnal cycle of nutrient concentrations in the canal and bay
waters could influence the estimates of the net direction and magnitude
of exchange. If a diurnal cycle were superimposed on the tidal cycle,
a bias in the estimate would result, particularly for those canals
where essentially only one ebb and one flood tidal phase occurred
during the 24 hour period. For example if planktonic primary production
during the daylight hours raises the levels of organic carbon in the bay
and canal waters, and if water continually floods into a canal during
the day, the rising levels of organic carbon would be recorded as
increasing flood phase concentrations. Then as photosynthesis stopped,
the tide reversed, and respiration continued, a decreasing organic
carbon concentration would be recorded for the ebb tidal phase. That
canal would be labelled a sink for organic carbon. Conversely a canal
could mistakenly be labelled a sink for organic carbon, when in fact
only a diurnal cycle was observed, superimposed on a tidal cycle having
predominantly ebb phase during daylight.
To determine whether diurnal cycles were occurring for the exchange
parameters that could bias the results, the mean concentrations of the
response parameters for all observations were regressed against the
hour of the day, transformed with a sine function. The transformation
(sin (0.2618 (Time 12))) was used so that a sunusoidal function with
a period of 24 hours, the minimum value at 0600 hours, and the maximum
value at 1800 hours, would result and would coincide with the diurnal
cycle. The results of these regressions are summarized in Table 8.
The only parameter observed to have a significant diurnal component

-85-
Table 8. Regression coefficients for the change in nutrient concen
trations versus time of day (transformed). Model y =
Intercept + Slope (NTIME).
Parameter^
y
Number of
Observations
Intercent
Slope
Probability
Slope ^ 0
R2
Total carbon
1105
38.77
-0.035
0.92
0.00
Inorganic carbon
1103
20.80
-0.24
0.45
0.00
Total organic carbon
1101
17.97
0.19
' 0.60
0.00
Total phosphorus
1108
0..253
-0.0010
0.91
0.00
Ortho-phosphorus
1102
0.214
-0.0018
0.84
0.00
Total organic P
1065
0.043
0.0007
0.68
0.00
nh3
1107
0.086
-0.012
0.0005
0.01
Turbidity
951
3.61
0.16
0.16
0.00
Color
850
104.
3.1
0, 36
0.00
Conductivity
532
31.7
0.69
0.86
0.00
transformation: NTIME = sin (0.2618 (Time 12)), Time 0-24 hours
^Units: as in Table 2

-86-
to the mean concentrations was ammonia. The rate of change of ammonia
concentration per unit transformed time is -0.012 mg/1 (non-linear on
an hourly basis). The transformed values of the hour of the day ranged
from -1.0 at 0600 hours to +1.0 at 1800 hours. Therefore by stustituting
these values into the linear equation (Table 8), it can be seen that
the mean ammonia concentration tends to be 0*012 mg/1 greater at sun
rise than at noon, and 0.012 less at sunset than at noon. This results
in an expected change in ammonia concentration of 0.024 mg/1 from
sunrise to sunset, attributable to a diurnal cycle.
The lack of a significant diurnal effect on nutrient concentra
tions, except for ammonia, suggests that a serious bias is not intro
duced by neglecting the time of day for tidal phases. The possible
bias associated with a diurnal ammonia cycle and the estimated net
movements of ammonia across the canal mouths is limited to Gulf Coast
canal observations that met the conditions given above. The Atlantic
canal systems generally experience semi-diurnal tides.
1975 Data
The nutrient exchange results obtained during the first phase of
this study, wherein four pairs of canals (PG, PC, LX, and PB) were
sampled on four occasions, provide information on the seasonal changes
and on the variabilities between canals that appear identical. The
two-way design (4 locations x 4 seasons, with replication) of this phase
of the study allowed analyses of variance to be performed on the data
in order to test for significant location and season effects. The
nutrient exchange data from the 1975 work are included in Table 7.

-87-
The mean net changes of total organic carbon, total organic phosphorus,
and ammonia concentrations for the four locations (PG9, PC9, and PB9
not included) and four sampling periods are shown in Table 9. The
descriptive statistics and significant factor effects (as determined
by analyses of variance) for the 1975 data are presented in Table 10.
No significant location or season effect was detected for total
organic carbon and ammonia exchange levels for these four locations
(Table 9). It may actually be that there were organic carbon and
ammonia exchange differences between these locations and seasons, but
the large amount of variability within the pairs of canals and the small
sample size (2 canals per location) prevent the detection of small dif
ferences in mean values.
For the total organic phosphorus (TP-OP) exchange data, there were
significant differences between the mean values. The significant month
x location interaction effect indicates that both location and season
did affect the organic phosphorus exchange activities, but that the
effect of season depended on location. The organic phosphorus exchanges
between canals and estuaries did change with season, but the magnitude
or direction change varied with canal location. For example, the
mean net export of organic phosphorus from the Pompano Beach canals
increased from 0.008 mg/1 in September to 0.010 mg/l in November,
whereas a mean net export (0.011 mg/l) or organic phosphorus from the
Port Charlotte canals in September, had shifted to a net import of
0.009 mg/l in November.
Even though differences between the organic phosphorus exchange
activities among these canals were detected, the variability within
the pairs of similar canals was rather large. The mean value for these


-89-
Table 9. (Extended)
September
November
Location Means
TOC
TOP '
nh3
TOC
TOP
nh3 '
TOC TOP NH3
1.5
-0.009
-0.01
0.1
0.001
-0.04
0.3
-0.019
-0.01
0.2
-0.011
0.04
-0.3
0.009
-0.02
-0.6
0.008
0.01
-0.8
0
0
4.6
0
0.01
0.7
-0.003
0
0.5
-0.008
f-H
*1
O
1
-0.1
-0.010
0.01
0
-0.008
-0.02
0.5
-0.008
-0.01
0.4
0.001
-0.01
0.1
-0.005
-0.01

-90-
Table 10. Descriptive statistics and analyses of variance results for
organic carbon, organic phosphorus, and ammonia data;
4 locations x 4 seasons x 2 canals per location.
TOC TOP NH3
Mean
+0.0 -0.005 -0.01
Standard Deviation
(unadj usted)
2.0 0.022 0.05
Range
-3.5 to +5.7 -0.069 to +.042 -0.18 to 0.08
Significant Factor
Effects (Anova, a < .05)
None Month x Location None
Within Paired-Observation
, Standard Deviation
(adjusted)
0.014
R2
39 81 62
N = 29

-91-
observations was -0.005 mg/1, with a standard deviation before adjust
ment for the location and month effects, of 0.022 mg/1. The location
2
and month effects explained 81 percent of the total variance (R in
Table 10), yet only reduced the unexplained standard deviation to
0.014 mg/1.
The variabilities of exchange behavior (unadjusted standard
deviations) in Table 10 represent the degrees of difference between
the eight canals over the four sampling periods. For organic carbon
and ammonia, the unadjusted standard deviations (2.0 and 0.05 mg/1,
respectively) can be interpreted as the exchange variabilities among
these similar canals, since no significant differences in mean values
were detected. In the case of organic phosphorus exchange, where dif
ferences in mean values occurred, the standard deviation of all values
(0.022 mg/1) is reduced to 0.014 mg/1, after the location and month
effects are removed. This adjusted standard deviation can be inter
preted as the variability between the individual canals at each
location for organic phosphorus exchange.
Daily Variability in One Canal
The nutrient/water quality exchanges between one canal (North
Miami site) and its adjacent estuary were measured for three consecutive
24 hour periods. The nutrient exchange results of this three day study
are shown in Table 11, and are included in Table 7.
The observed variabilities (standard deviations) for the exchange
parameters for this on three-day period, are smaller than the un
explained variabilities of the eight canals sampled in 1975 (Table 10).
The unexplained variabilities for the larger sample size with seasonal

-92-
Table 11. Nutrient/water quality exchange results for three consecu
tive days at the North Miami site.
Date
DTC
DIC
DTOC
DTP
DOP
DTOP
26 Oct 76
-0.4
0.6
-1.0
0.000
-0.002
0.000
27 Oct 76
1.1
-0.4
0.4
0.004
0.003
0.001
28 Oct 77
0.3
-0.4
0.7
-0.001
0.000
-0.001
Mean
0.3
1
o
I*
0.0
0.001
0.000
0.000
Std. Dev.
0.7
0.6
0.9
0.003
0.003
0.001
Date
DNH3
DTURB
DCOLOR
DCOND
26 Oct 76
.01
0.0
3
2
27 Oct 76
.03
0.1
7
-4
28 Oct 76
-.03
0.1
-3
-4
Mean
0.00
0.1
2
-2
Std. Dev
0.03
0.1
5
-3
Nomenclature and units as in Table 2

-93-
observations versus those of the single North Miami canal are 2.0 versus
0.9 mg/1 for total organic carbon exchange, 0.014 versus 0.001 mg/1
for total organic phosphorus exchange, 0.05 versus 0.03 mg/1 for ammonia
exchange. The results in Table 11 suggest that the daily variations in
exchange behavior are not as large as the seasonal variations.
Water Quality
In addition to the metabolic characteristics and nutrient con
centrations of the canals, several other water quality parameters were
measured for each canal. The average dissolved oxygen concentrations
were computed from all the oxygen values recorded in each canal. The
minimum and maximum dissolved oxygen concentrations, the Secchi depths,
and the water temperatures were also recorded for each canal. The
nutrient/water quality parameters determined for the exchange studies
are shown in Table 12 for every canal observation.
The frequency distributions and descriptive statistics for the
weighted-average ebb concentrations of the carbon forms, phosphorus
forms, ammonia, and turbidity have been presented in Figures 21-28.
The frequency distributions and descriptive statistics for the average
and minimum dissolved oxygen concentrations, and Secchi depths are
shown in Figures 29 and 30, respectively.
The average dissolved oxygen concentration of all the canals was
5.58 mg/1, with a standard deviation of 1.50 mg/1 and a range of 1.78
to 9.07 mg/1 (Figure 29a). The frequency distribution shows that most
of the canals observed had an average dissolved oxygen level of 4 mg/1
or greater.
The minimum oxygen values recorded in all canals had a mean value

Table 12. Water quality characteristics for all canal observations.
Nomenclature and units as in Table 2

-95-
OdS
CANAL
MN TH
DAY
Y EAR
LTL
E 1
c
E TUC
b TP
E GP
E TCP
1
PG 6
3
21
7 5
27.
3
9

7
1 7 b
0.436
0.333
0.098
2
PG3
3
21
7b
t 7.
7
1 1

b
15.9
C b b 6
0.369
C. 1 6b
3
PC 3
3
22
7 b
2b.
9
7

9
19.3
0.476
0.376
0.095
4
PCti
3
22
7 b
£ b .
9
7

D
19.1
0.43 7
C 3 7 b
0.05b
5
PB3
3
26
7 b
J £.'
7
1.1

7
20.9
0.23 1
0.160
0.051
o
P B 6
3
26
75
J
b
19

C
13.0
0.234
0.187
0.046
7
LX 3
3
25
7b
JO*
7
4

7
1 2 C
0.044
0 .026
C 0 1 o
8
L X 6
3
25
7b
Jo
1
24

1
1 2.0
0.049
0.037
0.0 12
9
PG 6
6
1 4
7b
J 2 *
1
1 9

2
12.9
0.468
0.478

1 0
PG3
b
1 4
7b
JO .
6
1 9

8
1 0 .3
0.4 b 7
0.490

1 1
PC 3
6
1 5
7b
1
i 8
#
6
10.6
0.545
0.581

1 2
PCb
6
1 5
7b
32 .
3
1 7

5
14.0
0.515
0.570

13
PB3
b
l 9
7 5
4
9
29

b
13.1
0.221
0.170
0.049
1 4
PU6

1 9
7b
4 3#
1
29

5
1 3 b
0.234
0.177
0.052
1 5
L X 6
b
1 6
7b
*+*+
7
32

5
12.2
0.0 b 8
0. C20
0.049
1 b
L X3
6
1 6
7 b
44 #
8
34

1
10 i 7
0.084
0 .027
0 .059
1 7
PG3
9
6
75
J2.
4
16

9
l 4 b
0.4 83
0.43b
0.046
1 B
PG6
9
6
7b
32
9
1 b

7
16.2
0.476
0.453
0.025
1 9
PG 9
9

75
. J J *
1
1 6

2
1 b 2
0 .4 63
0.434
0.049
20
PC3
9
9
7 b
j j
4
1 6

6
1 b 7
0.552
0.472
0. 061
2 1
PC6
9
9
7 5
35 .
2
1 5

d
19.4
0.b42
0.467
0.0 55
22
PC 9
9
9
7b
3 5.
6
16

0
19.6
0.535
0.456
0.077
2 3
PB3
9
7
7b
b9
3
2 6

5
11.9
0.247
0.200
C 04 7
24
Po6
9
7
7 5
4 ci
0
H

b
1 3 b
0.270
0.2 18
C .052
'25
LX3
9
1 2
7b
50.
4
31

9
1 8 b
0.053
0.073
0.000
2 o
LX6
9
1 2
7 b
*9 .
2
32

7
16.4
0.057
0.067
0 .000
27
PG 6
1 1
2 l
75
4 .
1
16

9
1 5 .4
0.326
0 ..288
0.037
26
PG3
1 i
2 1
7b






Ub S
ENH3
E TUI-ifJ
t COLOR LLONU AV GDO
Ml NU
MAX LU
5ECCHI
T tMP
1
0.03
4.5

b 0 5
2.80
9 6 0
1.45
24
2
0.05
b. 9

b 9 C
3.00
1 0 .0 0
1 33
24
3
0.05
b 1

b 3 4
2 b b
6. 1 0
1.52
2 3
4
0.0 l
4.5

6.97
5 1 C
o 50
1.48
22
5
0.10
4.3

5.72
4.10
7.80
1 .00
2 b
6
0.10
3.7
. b 2 8
4.60
a. 60
0. 93
25
7
0.01
3 1

5.7 b
4.70
c. 5 0
1.26
2 5
8
0.0 1
3.1
. 5.78
o 50
o 6 0
1.27
23
9
0 .05
1.4
6 b
5.97
3.4b
6 o b
2.27
29
1 0
0.07
1.4
4 7
b 3 5
2.35
7 .90
2.31
2 3
1 1
0.05
1 0
5 1
. 6.49.
1.90
9.4 0
1.60
3 0
1 2
0.04
1 0
73
. 6.8b
2.2 0
9.20
2.0 7
30
l 3
0.09
2. 2
9 2
. 5 <+ 0
0.65
1 4.00
0.97
29
1 4
0.07
2.2
1 0 1
5 9
2.00
10.20
0.90
29
1 5
0.05
3.3
124
. 4.19
0.90
5.85
1.07
2 9
1 6
0.05
4. 3
125
. 4.82
3.4b
6.05
0.92
28
1 7
0.2 1
4.6
225
. 3.51
1.80
4.67
1.13
29
1 8
0.22
cl'
24 5
. 3.8b
2.40
5. 35
1.22
29
19
0.17
'2.8
2 1 9
. 5. 63
2.40
12.00
0. 98
26
20
0.24
4.7
2 1 4
. 4.39
C 1 2
1 b.00
0.98
29
2 1
0.18
5.6
220
4.02
0.10
14.10
0.98
29
22
0.11
3 6
2 1 5
. 7.97
0.7 5
l 3. 25
0.84
30
23
0.06
2.2
69
. 6 60
3.3 7
1 b 3 0
0.98
3 3
24
0.0Q
3. 5
1 05
. 5.48
3.6b
9.47
0.92
32
25
0.06
4.8
12 1
. 4.4-2
3.02
6.85
l 23
32
2b
0. 02
3.9
9 7
. 4.9 J
2.0o
7.4 C
1.30
32
2 7
0. 07


. 7.62
5.8 7
8.9 5
1.47
22
28
'


. 7.71
1.2b
9. 50
1.42
22

-96-
Table 12. (Continued)
OBS
CANAL
MONTH
DAY
YEAR
fcTC
EIC
ETOC
E TP
E OP
ETOP
29
PG9
1 1
2 1
75
34. 4
16.7
1 7.7
0.370
0.342
0.0 28
30
PC3
I 1
23
75
33.2
21.1
12.1
0.342
0 .30 0
0.042
3 1
PC6
1 1
23
75
35.1
18.0
l 7. 1
0.3 10
0.277
0.032
32
PC 9
1 1
23
75
35.1
19.4
16.0
0 .357
0.312
0.045
33
PB6
1 1
1 4
75
57. 9
40.2
17.7
0.250
0.205
0. 045
34
PB9
1 1
14
7 5
56.3
42 .6
13.7
0 .236
0.203
0.033
35
PB3
1 1
14
75






36
LX3
1 1
1 6
75
43.2
32.5
o

0>
0. 054
0.012
0.0 41
37
LX6
1 1
1 6
75






38
MI 1
3
24
76
44. 3
22.8
21.5
0.084
0.056
0.028
39
M 12
3
24
7b
38. 5
23.0
15.5
0.060
0.041
0.019
40
MI 3
3
24
76
40.2
23.9
16 .2
0.053
0.033
0 .0 20
4 1
BC 1
4
20
76
35. 5
12. 6
23.1
0.197
0.165
0.032
42
BC2
4
20
76
37.2
12.8
24.5
0.203
0.169
0.033
43
BC3
4
20
76
35. 1
14.3
20 .5
0.198
0.168
0 .030
44
HI 1
5
19
76
46. 1
20. 6
27.5
0.052
0.033
0.019
45
H I 2
5
1 9
76
*2.8
19 .3
23 .5
0.040
0.023
0.0 16
46
HI 3
5
1 9
76
45.3
22.1
23.2
0.123
0.107
0.016
47
FLl
6
12
76
40.0
22.9
17.0
0. 086
0.034
0.0 53
48
FL2
6
1 2
76
39.1
22.8
16.4
0 .083
0.032
0.050
49
FL3
6
12
76
39.3
21.3
18.0
0. 088
0.039
0.048
50
API
7
1 4
76
38.9
12.6
25 .4
0.867
O'. 720
0.148
51
AP2
7
14
76
37.0
1 9.3
17.7
0.787
0.722
0 .065
52
AP3
7
1 4
7 o
40. 3
15.2
24.9
0.836
0. 704
0. 1 07
53
GB1
7
31
7 6
31.1
1 5 .3
15 .8
0.022
0.0 14
0.005
54
GB 2
7
31
7b
28. 1
15.7
12 .4
0.022
0 .0 16
0 .006
55
GB3
7
31
76
32. 7
16.2
16.5
0.037
0.024
0.013
56
KC1
8
18
76
33.2
25.4
7.7
0.019
0.006
0.0 13
OBS ENH3 ETURB ECOLOR ECONO AVGOO MINDO MAXOO SECCHI TEMP
29
0.01



9.07
2.80
11.80
1.33
22
30
0.21



2. 71
0. 00
7.37
1.15
20
31
0. 08



6.27
5.28
9.07
1.45
19
32
0.04


6.62
1.13
l 0.55
1.09
20
33
0.23


4.10
1.93
6. 01
1. 70
21
34
0.23








35




4.28
2.02
5.97
1.52
21
36
0.05



5.56
1.0 6
6. 75
1.57
21
37




5.66
0.65
7.53
1.52
2 1
38
0.10
4.8
33
347
6.13
4.60
7.53
1.43
24
39
0.06
3. 1
26
351
6. 11
5.18
6.78
l .20
24
40
C. 05
,3.6
40
351
5.68
4.91
6.70
1.49
24
41
0.09
5.2
28
281
7. 75
3.96
9. 40
1.22
25
42
0.15
4.6
16
65
7.56
6.14
8.69
1.03
25
43
0. 10
3. 2
20
260
6.08
3.13
8.18
1 .42
25
44
0. 14
1 1
54
330
7.22
5. 72
9. 55
1.73
26
45
0. 12
0.7
43
355
7.03
5.54
9.21
1.81
26
46
0. 1 1
1 1
6 5
3 C 0
7. 50
5.40
12.81
1.47
26
47
0.09
3.7
192
3*3
6.76
1 .80
9. 60
0. 88
27
48
0. 05
4. 1
176
342
4.40
0.00
9.31
0.88
27
49
0.08
3.5
126
340
6. 45
0.00
1 1.08
0. 96
27
50
0.04
4.8
1 l 3
271
6.78
4.62
8.42
0.75
30
51
0.06
5. 4
1 1 5
274
7.1 1
5.10
8.68
0.96
30
52
0.06
5.7
125
266
6.96
3. 66
8. 32
0.92
30
53
0.07
3.3
1 12
269
7.86
7.13
9.13
1.16
29
54
0.09
3. 1
100
65
7.01
6.35
7.80
1 .23
29
55
0.07
4.6
152
285
7.18
6. 8
6. 05
0.90
29
56
0. 07
2.0
30
448
5.93
4.45
6.08
2.70
28

-97-
Table
12.
(Continued)
CBS
CANAL
MONTH
DAY
YEAR
ETC
EIC
ETOC
E TP
E OP
ETOP
57
KC 2
8
18
76
31.9 24.
6 7.3
0.0 17
0.003
0.0 14
58
KC3
8
18
7 o
30.4
> 24.
8 5
0.0 14
0.004
0.009
59
NM1
10
26
76
55.2 12.
0 43.2
0.065
0.036
0 .029
60
NM 2
10
27
7b
55.6 14.
0 41.6
0.062
0.029
0.031
61
NM3
10
28
76
52.7 12.
9 39. 8
0.055
0.026
0.030
62
PEI
8
14
7 a

1 5.4
0.330


63
PE 2
8
1 4
74

14.7
0.220


64
BP3
8
19
74

1 .9
0.040


65
BP 4
8
l 9
74

1 .9
0 .040


66
SA8
a
23
74

1.0
0.030


67
AB3
9
1 7
74
9
3 .4
0 .040


68
AB5
9
1 7
74
9
2.4
0.050


69
MI H
8
8
75

5.8
0.150
70
MI J
8
1 0
75
9
9 .0
0.164


71
MIL
8
6
75
9
6.3
0. 068


72
MI M
8
6
75

6 .3
0 .084


73
MI M
8
8
75

6.1
0 .085


74
MIN
8
7
75

8.6
0.092


oes
ENH 3
ETURB
ECOLOR ECONO AVGDQ
MINOU
MAXD
SECCHI
TEMP
57
0.03
2.0
3 1
442 £
>.29
4.0 1
6.00
1.80
28
58
0.01
1.9
25
447 £
>.33
3.53
6.13
2.90
28
59
0.04
3.0
82
257 1
. 78
0. 00
7.87
1.60
25
60
0.04
3.3
84
262 2
. 08
0.00
9.83
1.58
25
61
0.02
3. 3
88
270 2
. 73
0.00
8.75
1.72
24
62
0.12

. 3
.30
0. 00
8. 70

31
63
0. 1 0


. 2.57
0.00
5.50

3 1
64
0.06

c
>. 90
4.2 0
8. 00
31
65
0.08

. 4
.37
1.10
6.40

31
66
0.04

. 3
. 55
0.60
7.40

31
67
0.09


. 4
>. 30
3. 00
11.70

2 6
68
0.08


. 4
.40
0.00
8.70

26
69
0.02
#

. 4
. 00
C. 00
8.00

31
70
0.03


. 5
. 10
3. 70
6. 70

31
71
0.01

. 5.2 0
0.00
9.00

31
72
0.01
. 4
. 95
0.00
9.80

3 1
73
0.03


. 4
. 95
0.00
9.80

31
74
0.03


. 4
. 85
0.40
8.60

31

-98-
a. Average oxygen values.
mg A
N = 73 Mean =5.58 Std. Dev. =1.50 Range 1.78 to 9.07
b. Minimum oxygen values.
mg/1
N = 73 Mean =2.66 Std. Dev. =2.05 Range = 0.00 to 7.13
Figure 29. Frequency distributions and descriptive statistics for
(a) average dissolved oxygen concentration (mg/1) and
(b) minimum dissolved oxygen values recorded in all canals

-99-
N = 60 Mean = 1.35 Std. Dev. = 0.44 Range 0.75 to 2.90
Figure 30. Frequency distribution and descriptive statistics for the
average Secchi depths (m) recorded in all canals.

-100-
of 2.66 mg/1, with a standard deviation of 2.05 mg/1 and a range of
0.00 to 7.13 mg/1. The most frequently observed minimum concentration
was zero (values were rounded to the nearest integer for histogram),
though a second mode at 3 mg/1 is apparent in Figure 29b.
The average Secchi depths recorded in these canals ranged from
0.75 to 2.90 meters, with a mean value of 1.35 meters and a standard
deviation of 0.44 meters (Figure 30). The frequency distribution
shows that most (48 of 60) of these canals had Secchi depths of 1.6
meters or less.
Structure of the Data Principal Components Analyses
The individual metabolic, nutrient exchange, and water quality
parameters, and their distributions among these Florida residential
canals are interesting from a descriptive standpoint and useful for
comparing with other ecosystems. The next step in evaluating the con
ditions and behavior of these canals is to reduce the number of variables
to a more manageable figure, so that elucidating interrelationships
among the various types of data is simplified. The approach used was
to use statistical methods to generate linear combinations of the
individual parameters that lead to adequate descriptions of the data in
fewer but artificial variables, with minimum loss of information.
Principal components analysis is a useful multivariate statistical
technique for initial exploration and elucidation of the structure of
a data set. Only a brief conceptual discussion of the technique will
be presented here. For a more detailed description a multivariate
statistical text should be consulted, such as Morrison (1967) or
Pielou (1969) .

-101-
Principal component analysis generates a series of linear com
binations (eigenvectors) with the feature that the first eigenvector
of the individual parameters (generally standardized to a mean of zero
and a standard deviation of one) accounts for the maximum amount of
variability of the total data set possible with one linear expression.
The second principal component is the linear combination of the vari
ables in.the data set that accounts for the maximum amount of variability
remaining after the first principal component has removed its share.
Similarly the rest of the series of eigenvectors sequentially account
for the greatest amount of variability remaining after the preceding
components have removed their shares.
The weightings or coefficients of the individual variables in each
linear combination represent the importance or contribution of that
variable (standardized) to that principal component or factor. Since
the variables are standardized, the parameters with the greatest
magnitude of values are not necessarily the most important in control
ling the variability of the data set. Rather, it is those parameters
that are most variable throughout all the observations that receive
the most weight. In the context of this study, the individual para
meters with the most weight are the ones that lead to the greatest
differences between the canal observations for the principal component
or factor being evaluated. The interpretation of the weightings of
each linear combination in terms of the factor that the component
represents is subjective and not always straightforward.
Another feature of principal component analysis is that the por
tion or percentage of the total variability in the data set accounted
for by each principal component is given. Consequently a data set with

-102-
a high degree of structure or with recurring patterns between the
variables for all the observations, will have most of the total vari
ability of the data set included in the first few principal components
It is this feature that makes the analysis a useful exploratory tech
nique when no £ priori pattern for the variables has, been established.
Combined Data '
Elucidation of the interrelationships between the canal attributes
determined during this study logically begins with the entire data set.
If these residential canals are basically simple systems with simple
recurring patterns between dynamic behavior (metabolism and nutrient
exchange), water quality, physical characteristics, and driving forces,
then a few simple linear combinations of the parameters should account
for most of the variability observed. Therefore, to evaluate the
amoung of structure in the data, a principal components analysis was
performed on the combined metabolism, exchange, water quality, and
physical characteristics data.
Forty-four variables from Tables 1, 3, 7, and 10 were included
in the combined data set for the principal components analysis. Thirty-
four canal observations had values for each variable and were included
in the analysis. Table 13 shows the first four eigenvectors and their
associated eignevalues with the portion and the cumulated portion of
the total variability explained by each. The first principal component
only accounts for 19 percent of the total variance and suggests that
canal behavior and characteristics do not have simple patterns. It
can be seen from the coefficients in the first principal component

-103-
Table 13. Principal
components of
the combined
data (44 variables).
1
2
3
4
TGPP
0.24
0.16
0.06
0.13
TR
0.17
0.25
0.02
0.13
P GPP M2
0.25
-0.09
-0.05
-0.07
PRM2
0.23
0.04
-0.13
0.06
PGPPM3
0.25
0.07
-0.06
-0.20
PPRM3
0.22
0.11
-0.10
-0.08
TPR
0.17
-0.18
0.05
-0.09
PPR
0.20
-0.12
0.01
-0.17
PDOMIN
0.08
-0.19
-0.15
0.01
DTC
0.01
0.13
0.05
0.09
DTOC
0.05
0.10
0.04
0.09
DOP
-0.06
-0.12
-0.08
-0.13
DTOP
-0.11
-0.16
0.07
0.05
DNH3
-0.02
0.01
0.10
0.15
DTURB
0.04
0.15
-0.11
-0.01
DCOLOR
-0.02
0.19
-0.21
0.01
ETC
0.13
-0.16
-0.21
-0.02
ETOC
0.17
-0.17
-0.06
0.20
EOP
0.17
0.22
0.15
0.11
ENH3
0.13
0.11
0.13
-0.04
ETRUB
0.00
0.21
0.08
0.23
ECOLOR
-0.01
0.31
-0.09
0.03
AVGDO
-0.02
0.05
0.33
-0.15
MAXDO
0.02
0.18
-0.05
-0.08
MINDO
-0.07
-0.10
0.31
-0.17
TEMP
-0.02
0.25
-0.03
-0.20
SECCHI
-0.08
-0.26
-0.02 '
0.04
ETOP
0.13
0.20
0.08
0.12
SUN
0.05
0.06
0.23
0.03
LENGTH
0.13
-0.10
0.25
-0.01
WIDTH
0.14
-0.02
0.23
0.27
MDEPTH
0.10
-0.13
-0.21
0.28
AREA
0.12
-0.13
0.26
-0.00
VOLUME
0.14
-0.14
0.24
0.09
SILL
0.08
-0.05
-0.16
0.28
DEVEL
0.19
0.00
0.04
-0.10
AGE
0.23
0.01
-0.11
0.00
BULK
0.17
-0.07
0.09
-0.11
CURBS
0.08
-0.05
0.14
0.15
SEWERS
0.13
-0.18
0.14
0.22
TIDE
0.27
-0.07
-0.05
-0.15
MINRES
-0.08
-0.04
-0.13
0.34
CUMTIDE
0.22
-0.07
-0.15
-0.23
DAYL
-0.11
0.18
0.14
-0.12
EIGENVALUES
8.43
6.02
5.71
4.27
PORTION
0.19
0.13
0.13
0.09
CUM PORTION
0.19
0.32
0.45
0.55
Nomenclature as in Table 2

-104-
that the metabolic parameters, canal age, local tidal dynamics, and to
a lesser extent the physical dimensions and nutrient levels of the
canals, carry the most weight in distinguishing differences between
the canals sampled. On the other hand the exchange parameters, basic
water quality parameters, and minimum residence times do not contribute
appreciably in explaining the variability between the canals.
The next three principal components explain an additional 35
percent of the total variance of the data set (13, 13, and 9 percent,
respectively). This brings the cumulative percent explained to 55
percent. In other words, only slightly more than half of the differences
between the canals can be explained by the differences in values of
these four linear combinations or factors.
Rather than to attempt to interpret the factors these lengthy
linear combinations represent, it is perhaps more useful and easier to
separate the data into the four subsets (metabolism, nutrient exchange,
water quality, and physical characteristics) and to evaluate the im
portance of the individual parameters in determining canal differences
for each of these types of attributes.
Three principal components were extracted from the correlations
matrices of the four subsets. The eigenvalues, eigenvectors, and
correlation matrices for each of the subsets are shown in Tables 14-17.
Metabolism
The first principal component (Table 14) of the metabolism subset
accounts for 40 percent of the total variability of this set. This
component appears to be associated with the general level of canal

-105-
Table 14. Principal components and correlation matrix for the
metabolism data.
CORRELATION MATRIX
TGPP
TR
PGPPM2
PRM2
PGPPM3
TGPP
1.00
0.87
0.44
0.47
0.43
TR
0.87
1.00
0.22
0.48
0.37
PGPPM2
0.44
0.22
1.00
0.61
0.76
PRM2
0.47
0.48
0.61
1.00
0.44
PGPPM3
0.43
0.37
0.76
0.44
1.00
PPRM3
0.39
0.45
0.51
0.73
0.52
TRP
0.10
-0.24
0.38
0.01
0.21
PPR
0.02
-0.19
0.39
-0.21
0.36
PDOMIN
-0.27
-0.33
0.40
0.24
0.18
PPRM3
TPR
PPR
PDOMIN
TGPP
0.39
0.10
0.02
-0.27
TR
0.45
-0.24
-0.19
-0.33
PGPPM2
0.51
0.38
0.39
0.40
PRM2
0.73
0.01
-0.21
0.24
PGPPM3
0.52
0.21
0.36
0.18
PPRM3
1.00 .
0.03
-0.15
0.29
TPR
0.03
1.00
0.46
0.06
PPR
-0.15
0.46
1.00
0.20
PDOMIN
0.29
0.06
0.20
1.00
EIGENVECTORS
1
2
3
TGPP
0.38
-0.26
0.37
TR
0.34
-0.44
0.22
PGPPM2
0.43
0.29
-0.00
PRM2
0.42
-0.10
-0.31
PGPPM3
0.41
0.18
0.10
PPRM3
0.40
-0.06
-0.33
TPR
0.10
0.42
0.33
PPR
0.70
0.50
0.39
PDOMIN
0.10
0.39
-0.55
EIGENVALUES
3.64
2.16
1.41
PORTION
0.40
0.24
0.15
CUM PORTION
0.40
0.64
0.80
Nomenclature as in Table 2

-106-
metabolism, and not with the plankton dominance or autotrophic nature.
The planktonic component parameters are weighted somewhat more than the
total community metabolism. These weightings suggest that the greatest
amount of variability in canal metabolic patterns is attributable to
the magnitude of primary production and respiration.
The second most important factor (second principal component)
leading to differences in the metabolic patterns of these canals appears
to be.the autotrophic nature of the canals, particularly of the plank
ton, because the plankton productionrrespiration ratio receives the most
weight. To a lesser extent the total community P:R ratio and the
plankton dominance ratio received positive weightings. The total
community production and respiration variables received negative weight
ings which further suggests that this second factor is a contrast
between the plankton dominance-autrophic patterns and the total com
munity metabolism.
The third component extracted from the metabolism data set again
appears to be associated with the autotrophic nature of the canals but
with the total community instead of the plankton, in contrast to plank
ton domination and planktonic respiration.
These three components or factors cumulatively account for 80
percent of the total variability in the metabolic patterns. It should
be emphasized that these factors describe only the patterns or struc
ture of the metabolic parameters for the canals and times sampled, and
do not consider the nutrient levels, season, or canal characteristics.
Exchange
The eigenvectors, eigenvalues, and correlation matrix of the

-107-
nutrient exchange subset are shown in Table 15. The first principal
component accounts for 31 percent of the observed variability in ex
change behavior for these canals. This factor appears to be one of net
total carbon and organic carbon exchange and, to a lesser extent, of
net organic phosphorus versus net ortho-phosphorus exchange. The second
component explains an additional 20 percent of the pattern of exchange
responses, and appears to be primarily associated with net changes in
the color and turbidity of the water entering the canals. The third
component explains 15 percent more of the total variability and is a
combination of net inorganic nutrient exchange (ammonium and ortho-P),
net changes in color somewhat contrasted to changes in turbidity, and
the net exchange of organic phosphorus.
The pattern of the net exchange responses is not as structured as
the metabolic responses since the first principal component of the
former explains just 31 percent of the total observed variability
compared to 40 percent for the latter. Also, the first three com
ponents account for 66 percent of the total variance, whereas those of
the metabolism set account for 80 percent. The lack of correlation
between the organic carbon and organic phosphorus exchanges (r = 0.14)
and between the ortho-phosphorus and ammonium exchanges (r = 0.10)
further illustrates the complexity of the observed exchange responses.
Water Quality
The principal component analysis for the water quality subset is
presented in Table 16. The results indicate that a simple water quality
index would not be adequate to classify these canals, since the first
principal component explains just 29 percent of the total variability

-108-
Table 15. Principal components and correlation matrix for the net
nutrient exchange data.
CORRELATION MATRIX
DTC
DTOC
DOP
DTOP
DTC
1.00
0.87
-0.33
0.23
DTOC
0.87
1.00
-0.30
0.13
DOP
-0.33
-0.30
1.00
-0.20
DTOP
0.23
0.13
-0.20
1.00
DNH3
0.11
-0.03
-0.00
0.09
DTURB
-0.09
-0.07
-0.10
-0.29
DCOLOR
0.18
0.00
0.20
0.01
DNH3
DTURB
DCOLOR
DTC
0.11
-0.09
0.18
DTOC
-0.03
-0.07
0.00
DOP
-0.00
-0.10
0.20
DTOP
0.09
-0.29
0.01
DNH3
1.00
-0.02
-0.04
DTURB
-0.02
1.00
0.32
DCOLOR
-0.04
0.32
1.00
EIGENVECTORS
1
2
3
DTC
0.62
0.18
0.11
DTOC
0.59
0.15
-0.07
DOP
-0.37
0.03
0.54
DTOP
0.29
-0.34
0.37
DNH3
0.07
-0.15
0.47
DTURB
-0.12
0.64
-0.23
DCOLOR
0.00
0.61
0.51
EIGENVALUES
2.18
1.41
1.06
PORTION
0.31
0.20
0.15
CUM PORTION
0.31
0.51
0.66
Nomenclature as in Table 2

-109-
Table 16. Principal components and correlation matrix for the water
quality data.
CORRELATION MATRIX
ETC
ETOC
ETP
EOP
ENH3
ETURB
ETC
1.00
0.68
-0.34
-0.38
-0.26
0.10
ETOC
0.68
1.00
-0.03
-0.07
-0.01
0.20
ETP
-0.34
-0.03
1.00
0.98
0.29
0.23
EOP
-0.38
-0.07
0.98
1.00
0.27
0.15
ENH3
-0.26
-0.01
0.29
0.27 ,
1.00
0.15
ETURB
0.10
0.20
0.23
0.15, ,)n 0.15
1.00
ECOLOR
-0.11
-0.02
0.38
0.34
0.54
0.38
AVGDO
-0.46
-0.32
0.13
0.14
0.00
-0.09
MAXDO
0.01
0.10
0.25
0.22
0.29
-0.02
MINDO
-0.27
-0.20
-0.15
-0.13
-0.05
-0.06
TEMP
-0.24
-0.48
0.42
0.43
-0.02
0.04
SECCHI
-0.15
-0.12
-0.23
-0.14
-0.29
-0.62
ECOLOR
AVGDO
MAXDO
MINDO
TEMP
SECCHI
ETC
-0.11
-0.46
0.01
-0.27
-0.24
-0.15
ETOC
-0.02
-0.32
0.10
-0.20
-0.48
-0.12
ETP
0.38
0.13
0.25
-0.15
0.42
-0.23
EOP
0.34
0.14
0.22
-0.13
0.43
-0.14
ENH3
0.54
0.00
0.29
-0.05
-0.02
-0.29
ETURB
0.38
-0.09
-0.02
-0.06
0.04
-0.62
ECOLOR
1.00
-0.25
0.24
-0.44
0.37
-0.56
AVGDO
-0.25
1.00
. 17
0.67
0.09
-0.07
MAXDO
0.24
0.17
1.00
-0.29
0.19
-0.33
MINDO
-0.44
0.67
-0.29
1.00
-0.07
0.10
TEMP
0.37
0.09
0.19
-0.07
1.00
-0.20
SECCHI
-0.56
-0.07
-0.33
0.10
-0.20
1.00
EIGENVECTORS
1
2
3
ETC
-0.20
0.47
0.04
ETOC
-0.09
0.44
0.14
ETP
0.44
-0.08
-0.13
EOP
0.42
-0.12
-0.19
ENH3
0.29
0.05
0.16
ETURB
0.22
0.24
0.43
ECOLOR
0.40
0.21
-0.02
AVGDO
0.05
-0.44
0.43
MAXDO
0.24
0.08
0.03
MINDO
-0.14
-0.39
0.48
TEMP
0.30
-0.17
-0.23
SECCHI
-0.30
-0.23
-0.47
EIGENVALUES
3.43
2.63
1.46
PORTION
0.28
0.21
0.12
CUM PORTION
0.28
0.50
0.62
Nomenclature as in Table 2

-110-
of these water quality parameters. The first three components or
factors can account for 63 percent of the differences in water quality
of these canals.
Phosphorus and color levels appear to be the primary parameters
that separate the water quality of these canals in the first principal
component. However, all of the 12 parameters, except average dissolved
oxygen, minimum dissolved oxygen, and organic carbon concentrations,
have some importance in the first component. The second component
seems to be a carbon and dissolved oxygen factor. The third factor
seems to be due to a combination of the minimum dissolved oxygen,
average dissolved oxygen, turbidity, and Secchi depth values.
Canal/Sampling Day Characteristics
The corrleation matrix, eigenvalues, and eigenvectors for the
canal/sampling day characteristics are shown in Table 17. This prin
cipal component analysis illustrates that the physical attributes of
canals and sampling days did not follow a rigid pattern. The first
component accounts for 24 percent of the set variance and appears to
be a canal size factor (length, width, surface area, volume). The
second factor explains an additional 18 percent of the variability and
seem to be associated with canal age, depth, sill height, and tidal
dynamics. The third factor that separates the canal/sampling day
characteristics is a contrast between the minimum residence time/mean
depth of the canal and the local tidal dynamics.

Table 17.
Principal components and correlation matrix for the canal/sampling day characteristics.
SUN
SUN
1.00
LENGTH
0.15
WIDTH
0.28
MDEPTH
-0.28
AREA
0.20
VOLUME
0.17
SILL
-0.23
DEVEL
0.16
AGE
. -0.27
BULK
0.19
CURBS
0.21
SEWERS
0.17
TIDE
-0.11
MINRES
-0.05
CUMTIDE
-0.08
DAYL
0.31
AGE
SUN
-0.27
LENGTH
0.16
WIDTH
0.04
MDEPTH
0.41
AREA
0.12
VOLUME
0.17
SILL
0.52
DEVEL
0.49
AGE
1.00
BULK
0.09
CURBS
0.20
CORRELATION MATRIX
LENGTH
WIDTH
MDEPTH
AREA
VOLUME
SILL
DEVEL
0.15
0.28
-0.28
0.20
0.17
-0.23
0.16
1.00
0.38
-0.11
0.97
0.90
-0.04
0.12
0.38
1.00
0.24
0.40
0.50
0.21
0.19
-0.11
0.24
1.00
-0.09
0.12
0.60
0.25
0.97
0.40
-0.09
1.00
0.94
-0.03
0.13
0.90
0.50
0.12
0.94
1.00
0.14
0.13
-0.04
0.21
0.60
-0.03
0.14
1.00
0.05
0.12
0.19
0.25
0.13
0.13
0.05
1.00
0.16
0.04
0.41
0.12
0.17
0.52
0.49
0.12
0.20
0.05
0.11
0.11
-0.33
0.56
0.09
0.46
0.17
0.15
0.32
0.23
0.20
0.30
0.72
0.30
. 0.32
0.37
-0.04
0.15
0.23
0.05
0.15
0.16
0.15
0.04
0.37
-0.20
0.18
0.70
-0.13
0.03
0.49
0.05
0.04
-0.22
0.06
-0.00
-0.03
0.02
0.19
0.17
0.03
-0.23
. 0.17
0.10
0.02
-0.02
BULK
CURBS
SEWERS
TIDE
MINRES
CUMTIDE
DAYL
0.19
0.21
0.17
-0.11
-0.05
-0.08
0.31
0.12
0.09
0.30
0.23
-0.20
0.04
0.17
0.20
0.46
0.72
0.05
0.18
-0.22
0.03
0.05
0.17
0.30
0.15
0.70
0.06
-0.23
0.11
0.15
0.32
0.16
-0.13
-0.00
0.17
0.11
0.32
0.37
0.15
0.03
-0.03
0.10
-0.33
0.23
-0.04
0.04
0.49
0.02
-0.02
0.56
0.20
0.15
0.37
0.05
0.19
-0.02
0.09
0.20
-0.27
0.55
0.02
0.40
-0.01
1.00
0.15
0.33
0.45
-0.26
0.17
-0.29
0.15
1.00
0.18
0.01
0.18
-0.11
-0.00
-111-

Table 17.
(Continued)
AGE BULK
CURBS
SEWERS
SEWERS
-0.27 0.33
0.18
1.00
TIDE'
0.55 0.45
0.01
0.03
MINRES
0.02 -0.26
0.18
0.16
CUMTIDE
0.40 0.17
-0.11
-0.24
DAYL
-0.01 -0.29
-0.00
-0.16
Nomenclature as in Table 2
1
EIGENVECTORS
2
SUN
0.13
-0.28
LENGTH
0.40
-0.17
WIDTH
0.36
-0.09
MDEPTH
0.12
0.36
AREA
0.41
-0.19
VOLUME
0.44
-0.12
SILL
0.08
0.30
DEVEL
0.22
0.25
AGE
0.16
0.44
BULK
0.20
0.11
CURBS
0.22
0.03
SEWRES
0.29
-0.12
TIDE
0.19
0.35
MINRES
0.00
0.07
CUMTIDE
0.02
0.32
DAYL
0.00
-0.25
EIGENVALUES
3.91
2.83
PORTION
0.24
0.17
CUM PORTION
0.24
0.42
TIDE
MINRES
CUMTIDE
DAYL
0.03
0.16
-0.