United States
Environmental Protection
Agency
Science and Ecosystem
Support Division
Region 4 and
Office of Research &
Development
EPA-904-R-98-002
October, 1998
South Florida Ecosystem Assessment
Vol I. Final Technical Report
Phase I
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Monitoring for Adaptive Management:
Implications for Ecosystem Restoration
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EPA 904-R-98-002
SOUTH FLORIDA
ECOSYSTEM ASSESSMENT
MONITORING FOR ADAPTIVE MANAGEMENT:
IMPLICATIONS FOR ECOSYSTEM RESTORATION
Final Technical Report - Phase I
by
Jerry Stober, Project Manager
US Environmental Protection Agency Region 4
Science and Ecosystem Support Division
Athens, GA
Daniel Scheidt, Assistant Project Manager
US Environmental Protection Agency Region 4
Water Management Division
Athens, GA
Ron Jones
Florida International University
Southeast Environmental Research Program
Miami, FL
Kent Thornton and Lisa Gandy
FTN Associates, Ltd.
Little Rock, AR
Don Stevens
Dynamac, Inc.
Corvallis, OR
Joel Trexler
Florida International University
Southeast Environmental Research Program
Miami, FL
Steve Rathbun
University of Georgia
Athens, GA
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EXECUTIVE SUMMARY
The South Florida Ecosystem Assessment Project is an innovative, large-scale monitoring
and assessment program designed to measure current and changing conditions of ecological
resources in South Florida using an integrated holistic approach. Using the United States
Environmental Protection Agency (EPA 1992) ecological risk assessment framework as the
foundation, the ultimate goal of this program is to provide decision makers with sound ecological
data needed to improve environmental management decisions for the restoration of the
Everglades ecosystem. Furthermore, through an ecological risk assessment approach, the South
Florida Ecosystem Assessment Project addresses multiple issues that are thought to be critical to
the restoration of the Everglades ecosystem and addresses the interactions among issues. These
issues include mercury contamination, eutrophication, marsh habitat alteration and hydroperiod
modification. Guided by a set of policy-relevant questions, this project strongly supports the
federal and state Everglades restoration efforts and provides a means to evaluate present and
future management actions.
A statistical Environmental Monitoring and Assessment Program (EMAP) survey design
was used to select 200 canal and 500 marsh sampling stations within the 10,000 km2 (4000 mi2)
Everglades ecosystem. A quarter of these sampling stations were sampled during successive wet
and dry seasons from 1993 to 1996. The data collected at these sampling locations permits
quantitative estimates of the relative risk to the ecological resources from the multiple interacting
environmental stressors.
Among the key findings: water discharged from Everglades Agricultural Area canals is
loading the public Everglades with excess phosphorus, carbon and sulfur; from 1993-1996 about
44% of Everglades canals had total phosphorus concentrations exceeding the Phase I 50 parts per
billion control target, as compared to 4% of the marsh area; from 1946 to 1996 portions of the
public Everglades lost substantial amounts of peat soil due to drainage and subsidence - northern
Water Conservation Area 3A and Northeast Shark Slough may have lost over 50% of soil depth;
and about 65% of the marsh had prey fish mercury concentrations that exceed United States Fish
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and Wildlife Service 100 parts per billion guideline for protection of predators such as wading
birds.
Synoptic monitoring of canal and marsh populations during wet and dry seasons was
designed to determine the extent and magnitude of total mercury (THg) and methylmercury
(MeHg) in water, sediment/soil, and mosquitofish (Gambusia holbrooki) in conjunction with
associated water quality and hydrologic parameters. Factor and principal component analyses of
canal and marsh data partitioned THg in fish and MeHg in water as two independent
components, with total phosphorus (TP), total organic carbon (TOC), and total ionic sulfate
(TS04) aggregated as a third component accounting for the variance in THg in fish. Statistically
significant north to south spatial gradients in these constituents were observed. The interactions
among these constituents along this gradient correlated well with the extent and magnitude of Hg
contamination in the Everglades.
In order to further synthesize and integrate the interactions of these variables, the central
Everglades flowway was parsed by latitude into seven units averaging approximately 27 km in
length (north-south) over a total distance of 189 km. Latitudinal parsing of the data aggregated
the subtle patterns in plant and floating periphyton responses relative to TP concentrations in the
system. These data indicated that TP affects emergent plant communities, floating periphyton
presence, aquatic habitat and food web complexity, which in turn affect microbial activity,
mercury methylation, biodilution and bioaccumulation of MeHg in the system.
The canal data appear to indicate that mercury interactions with TOC and TS04 and
biodilution of Hg in mosquitofish where TP concentrations were high resulted in lower
mosquitofish Hg concentrations north of Alligator Alley. However, south of Alligator Alley,
where TP, TOC and TS04 concentrations declined, there was increased bioaccumulation of Hg in
mosquitofish and periphyton, until TP declined to a median of 14 ug/L, when both biodilution
and bioaccumulation of Hg declined. These data suggest that high MeHg concentrations in water
in the northern Everglades did not lead to high THg in mosquitofish (THg in mosquitofish = 95%
MeHg) due to interactions with other constituents, biodilution, and associated changes in the
food chain.
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The marsh data were more definitive in suggesting the interactions between mercury, TOC,
TS04 and Hg biodilution north of Alligator Alley. As median TP declined from 16 to 12 ug/L
progressing north to south, however, the median Hg concentration in mosquitofish nearly
doubled to 208 ug/kg and remained high southward through northern Everglades National Park
(ENP). However, as TP continued to decline (median = 8.6 ug/L) the Hg concentration in
mosquitofish declined to 156 ug/kg in the southern portion of Everglades National Park.
Median MeHg concentrations in water declined north to south in both canal (i.e., 0.3 to 0.06
ng/L) and marsh (i.e., 0.54 to 0.15 ng/L) habitats indicating higher methylation occurred in the
marsh. The marsh median mosquitofish bioaccumulation factor (BAF) for Hg increased from 0.6
x 105 in the north to 8.5 x 105 in the southern portion of ENP indicating an increasing
bioaccumulation efficiency in the food chain from north to south. THg in periphyton, great
egrets, and mosquitofish also was spatially correlated with a Hg "hot spot" between Alligator
Alley and Tamiami Trail. The stimulatory effects of TP on the plant communities and the
methylating microbes appears to be a key component in mercury contamination.
The problems facing the Everglades ecosystem are not independent; they are highly
interactive. Management approaches to restore the Everglades ecosystem, therefore, should be
coordinated so that a system-wide approach is taken. Without this perspective, approaches that
focus on a single problem or problems at a single location might, in fact, correct one problem
while exacerbating other problems in the Everglades.
Phase II of the South Florida Ecosystem Assessment Project is scheduled to begin in 1999.
Time series monitoring will identify changes occurring since Phase I 1993-1996 data collection.
Increased emphasis will be placed on vegetation, phosphorus and mercury assessment, providing
data for input to various ecosystem models such as an Everglades mercury cycling model under
development by the EPA Office of Research and Development.
iii
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TABLE OF CONTENTS
Executive Summary i
List of Acronyms xxiv
Acknowledgments xxvi
1.0 INTRODUCTION 1-1
1.1 Change in the Everglades Ecosystem 1-1
1.2 Everglades Restoration Efforts and Scientific Studies 1-1
1.3 South Florida Ecosystem Assessment Project 1-2
1.4 Purpose and Organization of This Report 1-4
1.5 Key Everglades Restoration Issues 1-5
1.5.1 Hydropattern Modification 1-5
1.5.2 Florida Mercury Problem 1-6
1.5.3 Eutrophication 1-7
1.5.4 Habitat Alteration and Loss 1-9
1.5.5 Endangered and Exotic Species 1-9
1.5.6 Interaction Among Issues 1-9
2.0 STUDY DESIGN 2-1
2.1 Design Rationale 2-1
2.1.1 Sampling Method 2-3
2.1.2 Sample Points 2-5
2.1.3 Design-Based Estimation 2-5
2.1.4 Variable Probability Estimation 2-7
2.2 Indicators 2-10
2.3 Design Summary 2-15
3.0 MATERIALS AND METHODS 3-1
3.1 Field 3-1
3.1.1 Logistical Rationale and Needs 3-1
3.1.2 Apparatus 3-1
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TABLE OF CONTENTS (Continued)
3.1.3 Schedule 3-5
3.1.4 Sampling Routine 3-6
3.2 Laboratory Analyses 3-9
3.3 QA/QC 3-14
3.4 Data Analysis 3-15
3.4.1 Data Verification and Validation 3-15
3.4.2 Descriptive Statistics 3-16
3.4.3 Exploratory Analyses 3-16
3.4.4 Inferential Statistics 3-19
3.4.5 Spatial Statistics 3-19
3.4.6 Mass Estimates 3-19
4.0 GENERAL CHARACTERISTICS OF THE WATER REGIME 4-1
4.1 Precipitation 4-1
4.2 Canals 4-3
4.2.1 Discharge 4-3
4.2.2 Water Depth 4-3
4.2.3 Temperature 4-4
4.2.4 Conductivity 4-5
4.2.5 Dissolved Oxygen 4-5
4.2.6 Turbidity 4-6
4.2.7 pH 4-6
4.3 Marsh 4-6
4.3.1 Water Depth 4-6
4.3.2 Conductivity and General Flow Paths 4-8
4.3.3 Temperature 4-9
4.3.4 Dissolved Oxygen 4-10
4.3.5 Turbidity 4-11
v
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TABLE OF CONTENTS (Continued)
4.3.6 pH 4-11
4.4 Synthesis 4-11
5.0 HABITAT 5-1
5.1 Introduction 5-1
5.2 Results 5-3
5.2.1 Spatial Distribution of Dominant Plant Communities 5-3
5.2.2 Presence and Distribution of Cattails and Floating Periphyton Mats .. 5-4
5.3 Synthesis 5-6
6.0 SOILS 6-1
6.1 Introduction 6-1
6.2 Marsh Grid 6-2
6.2.1 Soil Thickness and Subsidence 6-2
6.2.2 Percent Organic Matter 6-4
6.2.3 Bulk Density 6-5
6.2.4 Soil Redox 6-6
6.3 Transects 6-6
6.3.1 Soil Thickness 6-6
6.3.2 Soil Organic Matter 6-7
6.3.3 Soil pH 6-7
6.3.4 Soil Redox 6-7
7.0 NUTRIENT CONDITIONS 7-1
7.1 Introduction 7-1
7.2 Results 7-3
7.2.1 Canals 7-3
7.2.2 Transects 7-6
7.2.3 Marsh 7-7
vi
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TABLE OF CONTENTS (Continued)
7.2.4 Vegetation and Periphyton Relationships 7-10
7.3 Synthesis 7-10
8.0 MERCURY 8-1
8.1 Introduction 8-1
8.2 Initial Conceptual Mercury Cycling Model 8-2
8.3 Results 8-8
8.3.1 Mercury Loading 8-8
8.3.2 Water Quality Patterns 8-9
8.3.3 Transect Gradients 8-13
8.3.4 Marsh Characteristics 8-16
8.3.5 Eastern Mosquitofish 8-22
8.4 Synthesis 8-23
9.0 MERCURY MASS ESTIMATES 9-1
10.0 SYNTHESIS AND INTEGRATION 10-1
10.1 Critical Factors 10-1
10.2 Mercury Bioaccumulation and Environmental Conditions 10-1
10.2.1 Vegetation Responses 10-2
10.2.2 Water Quality 10-3
10.2.3 Food Habits 10-7
10.3 Conceptual Models 10-8
10.3.1 North of Alligator Alley 10-9
10.3.2 Alligator Alley to Tamiami Trail 10-9
10.3.3 South of Tamiami Trail 10-10
10.4 Testable Hypotheses 10-10
11.0 MANAGEMENT IMPLICATIONS 11-1
11.1 Policy-Relevant Questions 11-1
vii
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TABLE OF CONTENTS (Continued)
11.1.1 Magnitude - What is the magnitude of the problem(s) in the
Everglades? 11-1
11.1.2 Extent - What is the extent of the problem(s)? 11-3
11.1.3 Trend - Is the problem(s) getting better, worse, or staying the same? . 11-4
11.1.4 Cause - What factors are associated with or causing the problem(s)? . 11-4
11.1.5 Source - What are the sources contributing to the causes and what is
the importance of different sources to the problem(s)? 11-5
11.1.6 Risk - What are the risks to different ecological systems and species
from the stressors or factors causing the problem(s)? 11-5
11.1.7 Solutions - What management alternatives are available to
ameliorate or eliminate the problem(s)? 11-6
11.2 Potential Considerations 11-6
11.3 Relevance 11-8
12.0 FUTURE DIRECTION 12-1
12.1 Introduction 12-1
12.2 . Objectives 12-1
12.3 Approach 12-2
12.3.1 Revised Monitoring Design 12-2
12.3.2 Aerial Photo Vegetation Assessment 12-4
12.3.3 Plant Biomass Estimation 12-5
12.3.4 Food Habits Analysis 12-6
12.4 Monitoring & Assessment Indicators 12-7
12.5 Statistical Analyses 12-8
12.6 QA/QC Requirements 12-14
12.6.1 Data Quality Requirements and Validation 12-14
12.6.2 Specific Data Package Requirements 12-16
12.8 Mercury Modeling 12-16
viii
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TABLE OF CONTENTS (Continued)
12.9 Comparative Ecological Risk Assessment 12-17
12.10 Ecosystem Restoration Modeling and Assessment 12-17
13.0 REFERENCES 13-1
APPENDICES
APPENDIX A Sampling Apparatus
APPENDIX B Data Quality Objectives
APPENDIX C Summary of Data Review Findings
APPENDIX D Eastern Mosquitofish Studies
APPENDIX E Response to Peer Review Comments
IX
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LIST OF TABLES
Table 2.1 Water and soil/sediment chemical measurements to be taken at each site
with the general rationale for measurement 2-11
Table 2.2 Physical and biotic measurements taken at each site with the general
rationale for the measurement 2-12
Table 2.3 Analytical parameters for marsh and canal samples 2-13
Table 3.1 Distribution of parameter analyses for multiple laboratory design 3-11
Table 3.2 Statistical analyses performed on data 3-17
Table 4.1 Precipitation summaries for the 9 stations used to establish the long-term
norm and baseline precipitation conditions 4-2
Table 4.2 Average annual flow (cms) through selected structures (Water years ending
September 30) 4-3
Table 4.3 Median values for selected canal constituents 4-4
Table 4.4 Median values for selected constituents in marsh 4-8
Table 5.1 Proportion of marsh habitat sampled dominated by the major plant
community classes within the six latitudinal subdivision along a north to
south gradient 5-5
Table 5.2 Proportion of marsh area sampled in each latitudinal subdivision where
cattail (Typha domingensis) and floating periphyton mats were present 5-7
Table 6.1 Summary statistics for soil parameters by subarea. Mean plus or
minus standard deviation is presented 6-3
x
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LIST OF TABLES (Continued)
Table 6.2 Everglades soil volumes by subarea reported for 1946 and 1995 through
1996 6-5
Table 7.1 Annual comparison of TP concentrations in water O-ig/L) in Everglades
canals and marsh 7-4
Table 7.2 Comparison of geometric mean of TP, APA, and chlorophyll a
concentrations in canal water by subarea during May 1995 sampling cycle .. . 7-5
Table 7.3 Geometric mean of TP concentrations (//g/kg) in canal sediments by four
geographic subarea within the Everglades 7-6
Table 7.4 Seasonal comparison of canal and marsh TP geometric mean
concentrations Cwg/L) in water by latitudinal subarea 7-9
Table 7.5 Geometric mean TN (mg/L) in water in the Marsh 7-9
Table 8.1 Initial Hg hypotheses developed in the Interagency Scope of Study
(Stoberetal. 1992) 8-3
Table 8.2 Comparison of canal constituent geometric means concentrations in water
by latitude 8-12
Table 8.3 Comparison of canal constituent geometric mean concentration, by latitude
and by season 8-13
Table 8.4 Comparison of geometric means of marsh constituents by latitude 8-19
Table 8.5 Comparison of marsh geometric mean constituents by latitude and season .. 8-20
Table 9.1 Mercury mass estimate models 9-1
Table 9.2 South Florida THg mass estimates (kg) 9-2
Table 9.3 South Florida MeHg mass estimates (kg) 9-3
xi
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LIST OF TABLES (Continued)
Table 10.1 Latitudinal divisions used to characterize canal and marsh constituent
gradients 10-3
Table 10.2 Latitudinal gradients for canal constituent medians, and confidence
intervals from north to south 10-4
Table 10.3 Latitudinal gradients for marsh constituent medians, and confidence
intervals from north to south 10-5
Table 10.4 Testable Hypotheses 10-12
Table 12.1 Everglades Jan '99 Pilot Study and Laboratory Intercalibration
(triplicate analysis) 12-9
Table 12.2 Proposed REMAP Phase II parameters by cycle 12-11
xii
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LIST OF FIGURES
Figure 1.1 South Florida study area 1-10
Figure 1.2 Ecological risk assessment framework 1-11
Figure 2.1 Location of four marsh transects sampled in April 1994 and canal water
control structures sampled on a biweekly basis from February 1994
through February 1997 2-16
Figure 2.2 General schematic for clipping canal segments from the individual
hexals and then randomly arranging them in a linear order so a systematic
sample of 50 sites/cycle could be selected to sample 2-17
Figure 2.3 200 sampling sites are located on over 1,200 km of canals 2-18
Figure 2.4 500 sampling sites are located on over 7,800 km2 of marsh 2-19
Figure 3.1 Methods development timeline 3-9
Figure 4.1 Location of precipitation stations from which period of record data
were collected to establish long-term norm and baseline period precipitation
conditions 4-13
Figure 4.2 Comparison of monthly precipitation during the 5-year study period to
normal monthly precipitation over the period of record at precipitation
Station S5A, with marsh and canal sampling periods indicated 4-14
Figure 4.3 Comparison of monthly precipitation during the 5-year study period to
normal monthly precipitation over the period of record at precipitation
Station S6, with marsh and canal sampling periods indicated 4-14
Figure 4.4 Comparison of monthly precipitation during the 5-year study period to
normal monthly precipitation over the period of record at Belle Glade
precipitation station with marsh and canal sampling periods indicated 4-15
xiii
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LIST OF FIGURES (Continued)
Figure 4.5 Comparison of monthly precipitation during the 5-year study period to
normal monthly precipitation over the period of record at Royal Palm
precipitation station, with marsh and canal sampling periods indicated 4-15
Figure 4.6 Comparison of monthly precipitation during the 5-year study period to
normal monthly precipitation over the period of record at Devil's Garden
precipitation station, with marsh and canal sampling periods indicated 4-16
Figure 4.7 Comparison of monthly precipitation during the 5-year study period to
normal monthly precipitation over the period of record at precipitation
Station S39, with marsh and canal sampling periods indicated 4-16
Figure 4.8 Comparison of monthly precipitation during the 5-year study period to normal
monthly precipitation over the period of record at Tamiami Trail
precipitation station, with marsh and canal sampling periods indicated 4-17
Figure 4.9 Comparison of monthly precipitation during the 5-year study period to
normal monthly precipitation over the period of record at precipitation
Station S9, with marsh and canal sampling periods indicated 4-17
Figure 4.10 Comparison of monthly precipitation during the 5-year study period to
normal monthly precipitation over the period of record at precipitation
Station S8, with marsh and canal sampling periods indicated 4-18
Figure 4.11 Daily discharge through selected SFWMD structures during the study
period 4-19
Figure 4.12 Notched box and whisker plots comparing water depths in canals by
subareas with all of the sampling data, and data grouped into dry and wet
season measurements 4-20
Figure 4.13 Notched box and whisker plots comparing canal surface water temperature
in subareas during dry and wet seasons 4-21
Figure 4.14 Notched box and whisker plots comparing canal bottom water temperature
in subareas during dry and wet seasons 4-22
xiv
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LIST OF FIGURES (Continued)
Figure 4.15 Canal conductivity reflects dilution of EAA discharge by precipitation 4-23
Figure 4.16 Notched box and whisker plots comparing canal conductivity in subareas
during dry and wet seasons 4-24
Figure 4.17 Notched box and whisker plots comparing canal bottom DO in subareas
during dry and wet seasons 4-25
Figure 4.18 Notched box and whisker plots comparing canal surface DO in subareas
during dry and wet seasons 4-26
Figure 4.19 Notched box and whisker plots comparing canal turbidity in subareas
during dry and wet seasons 4-27
Figure 4.20 Plots of the medians of the canal turbidity measurements for each of the
subareas with a vertical line indicating the 95% confidence interval about
each median 4-28
Figure 4.21 Notched box and whisker plots comparing canal pH measurements in
subareas during dry and wet seasons 4-29
Figure 4.22 Locations of SFWMD water depth gaging stations used for exceedance
frequency analysis 4-30
Figure 4.23 Exceedance frequency curves for SFWMD gaging stations with water
depths measured during each of the sampling cycles at nearby marsh
sampling sites 4-31
Figure 4.24 Kriged surface showing water depths in marsh during each sampling cycle . . 4-32
Figure 4.25 Kriged surface showing marsh water conductivity illustrates flow patterns
during each of the sampling cycles 4-33
Figure 4.26 Notched box and whisker plots comparing marsh water temperature in
subareas during dry and wet seasons 4-34
Figure 4.27 Notched box and whisker plots comparing marsh DO in subareas during
dry and wet seasons 4-35
xv
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LIST OF FIGURES (Continued)
Figure 4.28 Notched box and whisker plots comparing marsh turbidity in subareas
during dry and wet seasons 4-36
Figure 4.29 Notched box and whisker plots comparing marsh pH in subareas during
dry and wet seasons 4-37
Figure 5.1 The number of marsh sampling stations occurring within each of the
dominant plant communities 5-9
Figure 5.2 Distribution of dominant plant community classes, cattails and floating
periphyton by latitude 5-9
Figure 5.3 Percent relative frequency of selected plant communities, cattails, and
floating periphyton in six broad latitudinal subdivisions 5-10
Figure 5.4 Six latitudinal subdivisions within the Everglades marsh with locations of
sampling points contained in each 5-11
Figure 5.5 Marsh sampling sites where wet prairie was classified as the dominant plant
community 5-12
Figure 5.6 Marsh sampling stations where cattails were noted to be present
during sampling 5-13
Figure 5.7 Marsh sampling stations where floating periphyton mat was present
during sampling 5-14
Figure 5.8 Marsh sampling stations where sawgrass was classified as the dominant
plant community 5-15
Figure 6.1 Comparison of 1946 peat thickness (Davis, 1946) and 1995-1996 soil
thickness from the present study 6-8
Figure 6.2 Water conservation areas created in early 1960s: LNWR, WCA-2A,
WCA-2B, WCA-3A, and WCA-3B 6-9
xvi
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LIST OF FIGURES (Continued)
Figure 6.3 Notched box and whisker plots of marsh soil thickness, bulk density and
organic matter by subarea 6-10
Figure 6.4 Maximum and minimum difference in peat thickness 1946 to 1996 6-11
Figure 6.5 Percent organic matter observed for all cycles 6-12
Figure 6.6 Bulk density for all cycles 6-13
Figure 6.7 Linear relationship between Log (bulk density) and percent organic matter.. 6-14
Figure 6.8 Mean corrected soil Eh vs. marsh subarea 6-14
Figure 6.9 Average soil Eh for all cycles 6-15
Figure 6.10 Average soil Eh for each cycle 6-16
Figure 6.11 Soil thickness along each transect 6-17
Figure 6.12 Percent organic matter along each transect 6-17
Figure 6.13 Soil pH along each transect 6-18
Figure 6.14 Soil Eh along each transect 6-18
Figure 7.1 TP concentrations in surface water in the Everglades marsh were lower in
1996 than 1995 and during the wet season 7-13
Figure 7.2 TP concentrations in canals are highest in canals north of Alligator Alley ... 7-14
Figure 7.3 Cumulative distributions of canal TP in subareas 7-15
Figure 7.4 Notched box and whisker plots of canal TP in each of the subareas 7-16
Figure 7.5 Plot of selected constituents showing latitudinal gradients in canals 7-17
Figure 7.6 APA in canals is highest in areas where TP concentrations are lowest 7-18
Figure 7.7 TP concentrations in canal sediments by geographic subarea show no
spatial patterns 7-19
Figure 7.8 TP concentrations in canal sediments by latitudinal subarea show no
spatial patterns 7-20
Figure 7.9 TP concentrations in canal sediments by cycle show no temporal patterns... 7-21
Figure 7.10 TP concentrations in canal sediments by longitude for all cycles combined .. 7-21
xvii
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LIST OF FIGURES (Continued)
Figure 7.11 Location of four April 1994 marsh transects and canal water control
structures sampled on a biweekly basis 7-22
Figure 7.12 TP in water along transects decreases with distance from the canals 7-23
Figure 7.13 TP in soil along transects decreases with distance from the canals 7-23
Figure 7.14 Kriged surfaces showing TP in the marsh for each sampling cycle based
on sampling data 7-24
Figure 7.15 Cumulative distributions of TP concentrations in the marsh for selected
cycles 7-25
Figure 7.16 Cumulative distributions of TP concentrations in the marsh subareas 7-26
Figure 7.17 Kriged surfaces showing TP concentrations in the marsh using dry and
wet season data 7-27
Figure 7.18 Notched box and whisker plots comparing marsh TP in subareas during
dry and wet seasons 7-28
Figure 7.19 Plots of the medians of marsh TP measurements in each of the subareas
with a vertical line indicating the 95% confidence interval about
each median 7-29
Figure 7.20 Kriged surfaces showing patterns of TP and APA in the marsh 7-30
Figure 7.21 Kriged surfaces showing APA in the marsh for each sampling cycle 7-31
Figure 7.22 Notched box and whisker plots comparing marsh TN in subareas during
dry and wet seasons 7-32
Figure 7.23 Kriged surface showing marsh TN concentrations in water during the
May and September 1996 cycles 7-33
Figure 7.24 Kriged surface showing marsh soil TP concentrations over the study period . 7-34
Figure 7.25 Notched box and whisker plots comparing marsh soil TP in latitudinal
subareas during dry and wet seasons 7-35
Figure 7.26 Notched box and whisker plots comparing marsh soil TP in geographic
subareas during dry and wet seasons 7-36
xviii
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LIST OF FIGURES (Continued)
Figure 7.27 Kriged surfaces showing TP concentrations in marsh water and soil during
study period 7-37
Figure 7.28 Kriged surface of TP in marsh soils with sampling stations where cattails
were present 7-38
Figure 8.1 Schematic figure depicting atmospheric deposition of Hg 8-5
Figure 8.2 Biogeochemical cycling of Hg in the Everglades ecosystem 8-24
Figure 8.3 Notched box and whisker plots comparing canal TOC in subareas during dry
and wet seasons 8-25
Figure 8.4 TS04 concentrations in canals during the study period 8-26
Figure 8.5 Notched box and whisker plots comparing canal TS04 in subareas during dry
and wet seasons 8-27
Figure 8.6 Notched box and whisker plots of canal TP in subareas during dry and wet
seasons 8-28
Figure 8.7 Plots of median canal TP for subareas with vertical lines indicating 95%
confidence interval of each median 8-29
Figure 8.8 Notched box and whisker plots comparing canal THg in water by subareas
during dry and wet seasons 8-30
Figure 8.9 Plots of median canal THg in water for subareas with vertical lines indicating
the 95% confidence interval for each median 8-31
Figure 8.10 Notched box and whisker plots comparing canal MeHg in water for subareas
during dry and wet seasons 8-32
Figure 8.11 Box and whisker plots comparing canal THg in mosquitofish by subareas
during dry and wet seasons 8-33
Figure 8.12 Medians of THg in mosquitofish in canals for subareas with vertical lines
indicating the 95% confidence interval for each median 8-34
Figure 8.13 Plot of selected constituents showing latitudinal gradients in canals 8-35
xix
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LIST OF FIGURES (Continued)
Figure 8.14 Location of four marsh transects sampled in April 1994 and canal water
control structures sampled on a biweekly basis from February 1994 through
February 1997 8-36
Figure 8.15 Measurements of TP in water along marsh transects 8-37
Figure 8.16 TOC concentrations along marsh transects 8-37
Figure 8.17 TS04 concentrations along marsh transects 8-38
Figure 8.18 Measurements of THg in water along marsh transects 8-38
Figure 8.19 MeHg concentrations along marsh transects 8-39
Figure 8.20 Ratio of MeHg to THg in water along marsh transects 8-39
Figure 8.21 THg in mosquitofish collected along marsh transects 8-40
Figure 8.22 Sulfide in soils along marsh transects 8-40
Figure 8.23 TP in soils along marsh transects 8-41
Figure 8.24 THg in soils along marsh transects 8-41
Figure 8.25 MeHg in soils along marsh transects 8-42
Figure 8.26 Bioaccumulation along marsh transects 8-42
Figure 8.27 Notched box and whisker plots comparing marsh TOC in subareas during
dry and wet seasons 8-43
Figure 8.28 Notched box and whisker plots comparing marsh TS04 in subareas during
dry and wet seasons 8-44
Figure 8.29 Median marsh TS04 values for subareas with a vertical line indicating the
95% confidence interval for each median 8-45
Figure 8.30 Notched box and whisker plots comparing marsh TP in subareas during
dry and wet seasons 8-46
Figure 8.31 Median marsh TP values for subareas with vertical line indicating 95%
confidence interval for each median 8-47
Figure 8.32 Notched box and whisker plots of marsh comparing TN in water during
dry and wet seasons 8-48
xx
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LIST OF FIGURES (Continued)
Figure 8.33 Notched box and whisker plots comparing marsh THg in subareas during
dry and wet seasons 8-49
Figure 8.34 Median values of marsh THg for subareas with a vertical line indicating the
95% confidence interval for each median 8-50
Figure 8.35 Notched box and whisker plots comparing marsh MeHg in subareas during
dry and wet seasons 8-51
Figure 8.36 Median values of marsh MeHg for subareas with vertical lines indicating the
95% confidence interval for each median 8-52
Figure 8.37 Notched box and whisker plots comparing THg in fish in marsh in subareas
during dry and wet seasons 8-53
Figure 8.38 Notched box and whisker plots comparing marsh BAF factor in subareas
during dry and wet seasons 8-54
Figure 8.39 Notched box and whisker plots comparing THg in floating periphyton in
subareas during dry and wet seasons 8-55
Figure 8.40 Median values of THg in floating periphyton for subareas with a vertical line
indicating the 95% confidence interval for each median 8-56
Figure 8.41 Notched box and whisker plots comparing MeHg in floating periphyton in
subareas during dry and wet seasons 8-57
Figure 8.42 Notched box and whisker plots comparing THg in soil periphyton in
subareas during dry and wet seasons 8-58
Figure 8.43 Notched box and whisker plots comparing MeHg in soil periphyton in
subareas during dry and wet seasons 8-59
Figure 8.44 Notched box and whisker plots comparing marsh soil THg in subareas
during dry and wet seasons 8-60
Figure 8.45 Notched box and whisker plots comparing marsh soil MeHg in subareas
during dry and wet seasons 8-61
Figure 8.46 Selected marsh parameters shown by latitude 8-62
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LIST OF FIGURES (Continued)
Figure 8.47 Kriged surfaces indicating marsh TOC concentrations during each
sampling cycle 8-63
Figure 8.48 Kriged surfaces indicating marsh TS04 concentrations during each
sampling cycle 8-64
Figure 8.49 Kriged surfaces showing TP in the marsh for each sampling cycle based on
sampling data 8-65
Figure 8.50 Kriged surfaces indicating marsh MeHg concentrations during each of the
sampling cycles 8-66
Figure 8.51 Locations of floating periphyton samples with kriged surfaces indicating
concentrations of MeHg in floating periphyton 8-67
Figure 8.52 Locations of soil periphyton samples with kriged surface indicating
concentrations of MeHg in soil periphyton 8-68
Figure 8.53 Kriged surfaces indicating concentrations of MeHg in marsh soils during
study period 8-69
Figure 8.54 Kriged surfaces indicating concentrations of THg in mosquitofish collected
in the marsh during each sampling cycle 8-70
Figure 8.55 Hg concentrations in Great Egret chick feathers and mosquitofish indicate
spatial distribution of Hg bioaccumulation 8-71
Figure 9.1 Marsh data THg in water (top) and soil (bottom) 9-5
Figure 9.2 Marsh data MeHg in water (top) and soil (bottom) 9-6
Figure 10.1 Six canal compartments with locations of sampling points contained in
each 10-13
Figure 10.2 Six marsh compartments with locations of sampling points contained
in each 10-14
Figure 10.3 Median values of selected parameters in canal subareas 10-15
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LIST OF FIGURES (Continued)
Figure 10.4 Median values of selected parameters in marsh subareas 10-16
Figure 10.5 Median marsh TP and BAFs in subareas 10-17
Figure 10.1 Six canal compartments with locations of sampling points contained in
each 10-13
Figure 10.2 Six marsh compartments with locations of sampling points contained
in each 10-14
Figure 10.3 Median values of selected parameters in canal subareas 10-15
Figure 10.4 Median values of selected parameters in marsh subareas 10-16
Figure 10.5 Median marsh TP and BAFs in subareas 10-17
Figure 12.1 Potential monitoring network configurations combining probability,
compliance and fixed sites 12-18
xxiii
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LIST OF ACRONYMS
AA
Alligator Alley
AA-N
Alligator Alley north
AFS
atomic fluorescence spectrometer
ANOVA
Analysis of Variance
APA
alkaline phosphatase activity
BAF
bioaccumulation factor
BCNP
Big Cypress National Preserve
BMPs
Best Management Practices
cdf
cumulative distribution function
CRMS
Center for Remote Sensing and Mapping Science
°C
degree Celsius
DO
Dissolved oxygen
DQO
data quality objective
EAA
Everglades Agricultural Area
EAB
Ecological Assessment Branch
ESAT
Environmental Services Assistance Team
Eh
redox
EMAP
Environmental Monitoring and Assessment Program
ENP
Everglades National Park
ENR
Everglades Nutrient Removal
EPA
Environmental Protection Agency
ESD
Environmental Sciences Division
EtHg
cthylmercury
FAMS
Florida Atmospheric Mercury Study
FDEP
Florida Department of Environmental Protection
FGFWFC
Florida Game and Fresh Water Fish Commission
FIU
Florida International University
FIU-SERP
FlU-Southeast Environmental Research Program
FTN
FTN Associates, Ltd.
GC/AFS
gas chromatography/atomic fluorescence spectrometry
GF/F
glass fiber filter
GIS
geographic information system
GPRA
Government Performance and Review Act
GPS
global positioning system
Hg
mercury
LNWR
Loxahatchee National Wildlife Refuge
MDL
minimum detection limit
MeHg
methylmercury
MSL
Battelle Marine Sciences Laboratory
NAD
North Atlantic Datum
NAPP
USGS National Aerial Photography Program
NERL
National Exposure Research Laboratory
NOAA
National Oceanic and Atmospheric Administration
N PS
US National Park Service
NTU
nephelometric turbidity unit
ORD
Office of Research and Development
OQA
Office of Quality Assurance
QA/QC
quality assurance/quality control
ppt
part per trillion
RTS
random tessellation stratified
SESD
Science and Ecosystem Support Division
SFMSP
South Florida Mercury Science Program
SFWMD
South Florida Water Management District
(SoFAMMS)
South Florida Atmospheric Mercury Monitoring Study
SOP
standard operating procedure
STA
stormwater treatment area
xxiv
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LIST OF ACRONYMS
THg
total mercury
THgF
total mercury in fish
TOC
total organic carbon
TN
total nitrogen
TP
total phosphorus
tso4
total sulfate
TT
Tamiami Trail
USACE
US Army Corps of Engineers
USEPA
US Environmental Protection Agency
USGS
US Geological Survey
UTM
Universal Transverse Mercator
WCA
water conservation area
WY
water year
XXV
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ACKNOWLEDGMENTS
PARTICIPANTS IN US EPA REGION 4
EVERGLADES ASSESSMENT PROJECT
US EPA Region 4
Program Offices
APTMD
L. Anderson-Carnahan
D. Dubose
L. Page
S. Gent-Howard
ORC
P. Mancusi-Ungaro
SESD
D. France
B. Berrang
P. Meyer
C. Halbrook
M. Parsons
D. Smith
W. McDaniel
M. Wasko
J. Scifres
M. Birch
P. Mann
T. Slagle
T. Stiber
J. Davee
D. Colquitt
D. Kamens
R. Howes
G. Collins
J. Bricker
B. Noakes
US EPA-Office of Research
and Development
EMAP
R. Linthurst
K. Summers
T. Olsen
NERL-RTP
R. Stevens
R. Bullock
J. Pinto
NERL-ATHENS
R. Ambrose
R. Araujo
C. Barber
N. Loux
L. Burns
NERL-LAS VEGAS
D. Chaloud
E. Heitmier
FIU-SERP
R. Jaffe
Y. Cai
A. Alii
N. Black
I. MacFarlane
W. Loftus
J. Thomas
Florida Department of
Environmental Protection
T. Atkeson
South Florida Water
Management District
L. Fink
Contractors
J. Maudsley, Mantech
B. Lewis, Mantech
M. Weirich, Mantech
D. Stevens, Mantech
M. McDowell, Mantech
C. Laurin, FTN Associates, Ltd.
D. Lincicome, FTN Associates, Ltd.
J. Benton, FTN Associates, Ltd.
R. Remington, FTN Associates, Ltd.
T. Schmidt, FTN Associates, Ltd.
S. Ponder, Integrated Laboratory Systems
K. Simmons, Integrated Laboratory Systems
S. Pilcher, Integrated Laboratory Systems
D. Winters, Integrated Laboratory Systems
J. Chandler, Integrated Laboratory Systems
S. Allen, Integrated Laboratory Systems
C. Appleby, Integrated Laboratory Systems
E. Crecelius, Battelle Marine Sciences
B. Lasorsa, Battelle Marine Sciences
xxvi
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1.0 INTRODUCTION
1.1 Change in the Everglades Ecosystem
The Everglades ecosystem has been greatly altered during the last century to provide for
urban and agricultural development. Since 1880, 50% of the historic Everglades wetlands have
been drained, and an expanding South Florida human population of nearly 6 million competes for
this ecosystem's water and land (Davis and Ogden 1994).
At present, most of the remaining Everglades are found in the US Fish and Wildlife
Service's Loxahatchee National Wildlife Refuge (LNWR), the National Park Service's
Everglades National Park (ENP), or in the Water Conservation Areas (WCA), specifically,
WCA2 and WCA3 (Figure 1.1). Today, the ENP includes only one-fifth of the original
Everglades that once encompassed over 2 million acres (7,800 km2). One-fourth of the historic
Everglades is now in extensive agricultural production within the 2,600 km2 (1,000 mi2)
Everglades Agricultural Area (EAA), where sugar cane and vegetables are grown on drained
Everglades soils. Big Cypress National Preserve (BCNP) located in western South Florida,
protects forested swamp resources within the Everglades watershed. Although one-half of the
41,000 km2 (16,000 mi2) Everglades watershed is in public ownership, a number of
environmental issues must be simultaneously resolved to protect and restore the remnant
Everglades ecosystem. These issues include hydropattern modification; water supply conflicts;
eutrophication; mercury (Hg) contamination of gamefish, wading birds, and other top predators;
habitat loss and alteration; endangered species protection; and exotic species introductions.
1.2 Everglades Restoration Efforts and Scientific Studies
A series of efforts are underway to protect and restore the South Florida Everglades
ecosystem. In 1994, Florida's governor established the Governor's Commission for a Sustainable
South Florida to make recommendations for achieving a healthy Everglades ecosystem that can
coexist with and be mutually supportive of a sustainable South Florida economy and quality
communities. The federal Water Resources Development Act of 1996 established the South
Florida Ecosystem Restoration Task Force, composed of representatives of federal agencies, state
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agencies, indian tribes, and local governments, to coordinate the development of consistent
strategies for restoration, protection, and preservation of the South Florida ecosystem (US
Congress 1996). The Science Subgroup of this task force has developed integrated scientific
information needs for the ecosystem restoration effort (Science Subgroup 1996) along with
success criteria for South Florida ecosystem restoration (Science Subgroup 1997). The US Army
Corps of Engineers (USACE) is currently conducting a restudy of the Central and Southern
Florida Project to evaluate the feasibility of structural or operational modifications to the project,
and identify those modifications that are essential to restoration of the Everglades and Florida
Bay ecosystems while providing for other water-related needs (USACE 1994). The state of
Florida has many other ecosystem restoration efforts underway (SFWMD 1997a) including a
comprehensive plan to address Everglades eutrophication through land acquisition, construction
projects, research, and regulation, as required by Florida's 1994 Everglades Forever Act
(SFWMD 1997b). In addition other federal and state agencies and universities, including the
US Environmental Protection Agency (EPA), the US Geological Survey (USGS), US National
Park Service (NPS), Florida Department of Environmental Protection (FDEP), and South Florida
Water Management District (SFWMD), currently are conducting studies within the Florida
Everglades to evaluate the condition of Everglades resources and restoration alternatives.
1.3 South Florida Ecosystem Assessment Project
This report summarizes the data collected and the efforts of the EPA's South Florida
Ecosystem Assessment Project. The South Florida Ecosystem Assessment Project is an
innovative, large-scale monitoring and assessment program designed to measure the current and
changing conditions of ecological resources in South Florida using an integrated, holistic
approach. Using the EPA (1992) ecological risk assessment framework as the foundation (Figure
1.2), the ultimate goal of this program is to provide decision makers with sound ecological data
needed to improve environmental management decisions for the restoration of the Everglades
ecosystem. Furthermore, through an ecological risk assessment approach, the South Florida
Ecosystem Assessment Project addresses the multiple issues that are thought to be critical to the
restoration of the Everglades ecosystem and also addresses the interactions among these issues.
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The South Florida Ecosystem Assessment Project is guided by seven policy-relevant
assessment questions:
1) Magnitude - What is the magnitude of the problem(s) in the Everglades?
2) Extent - What is the extent of the problem(s)?
3) Trend - Is the problem(s) getting better, worse, or staying the same?
4) Cause - What factors are associated with or contribute to the problem(s)?
5) Source - What are the source(s) and what is the contribution and importance of
each source to the problem(s)?
6) Risk - What are the risks to different ecological systems and species from the
stressors or factors causing the problem(s)?
7) Solutions - What management alternatives are available to ameliorate or eliminate
the problem(s)?
These policy-relevant questions are applicable to each major issue identified by the
Science Subgroup as impacting the Everglades ecosystem (i.e., hydropattern modification, Hg
contamination, eutrophication, habitat alteration, and endangered and exotic species). Initial
conceptual models and testable hypotheses were developed around these key issues and
policy-relevant questions.
A number of studies will be required to test all of the hypotheses and to refine the
conceptual models and complete the ecological risk assessment in the Everglades. Initially, the
South Florida Ecosystem Assessment Project has focused on a subset of hypotheses that are
directly related to the first four policy-relevant assessment questions identified above. These
hypotheses are discussed in Chapter 8.0. Additional coordinated studies directed at addressing
other high priority elements of the interagency program will be conducted and merged with this
project as additional resources are made available.
Unlike other studies in support of the Everglades restoration effort, the South Florida
Ecosystem Assessment Project is unique in a number of ways.
(1) Scale - The South Florida Ecosystem Assessment Project is a multimedia study
being conducted on over 41,000 km2 (16,000 mi2) in South Florida extending
from the EAA in the north to the Florida Bay in the south. Few ecological studies
have been conducted at this scale. This large-scale, multimedia approach will
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improve the ability to assess patterns in individual resources throughout the whole
Everglades ecosystem and the interactions among these resources or patterns.
(2) Study Design - The South Florida Ecosystem Assessment Project uses a unique
probability-based, statistical survey design to select sample locations throughout
the Everglades marsh and canals. This sampling design permits the development
of unbiased population estimates of resource condition with known confidence.
Furthermore, this design also permits spatial analyses and associations that
provide insight into functional relationships among observed ecological effects
and multiple stressors.
(3) Risk Based Approach - The South Florida Ecosystem Assessment Project
evaluates multiple impacts and stressors on the Everglades ecosystem
simultaneously using an ecological risk based approach. By using a risk based
approach, issues that are critical to the restoration efforts and the interaction
among these issues and stressors will be identified for decision makers.
(4) Complementary Interagency Efforts - This project was designed to address critical
policy-relevant questions in a complementary manner not previously used by other
agencies or studies. Not only will the South Florida ecosystem assessment project
contribute to the Interagency Task Force on Ecosystem Restoration efforts, the
results of this project will be closely coordinated with the State of Florida and
other agencies findings to provide the scientific information needed to assess
restoration efforts proposed for the Everglades ecosystem. For example, the data
collected will be used by other agency scientists and engineers to calibrate
hydrodynamic, water quality, and landscape ecology models that are being used to
predict responses of the Everglades to various management alternatives.
1.4 Purpose and Organization of This Report
The purposes of this report are to (1) present and summarize the data collected in the
Everglades ecosystem by the EPA, (2) to provide preliminary answers to the first four policy
relevant assessment questions pertaining to the magnitude and extent and current conditions
within the Everglades canal and marsh ecosystems, and (3) to establish a baseline for assessing
future trends in resource condition. This report provides the results of the data collection efforts
conducted within the Everglades from 1993 through 1996. The information provided by this
project will be critical to the South Florida Interagency Ecosystem Restoration Task Force to
determine if the precursor and ecological restoration success criteria identified by the task force
are being achieved.
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This report is organized into two volumes. In this volume (Volume I) the background
information, study design, data and results, management implications, and research
recommendations relevant to the specific ecosystem restoration issues identified earlier in this
chapter (i.e., hydropattern modification, eutrophication, habitat alteration) are provided. All
figures have been placed at the end of their respective chapter. Supporting data and background
information are either provided in appropriate chapters or included in Volume II, which contains
the appendices to this report. Appendices include the following: Appendix A - Sampling
Apparatus; Appendix B - Data Quality Objectives; Appendix C - Summary of Data Review
Findings; Appendix D - Eastern Mosquitofish Studies; and Appendix E - Response to Peer
Review Comments. Volume II also contains peer review comments received on the draft report
and responses to the comments.
1.5 Key Everglades Restoration Issues
Several issues have been agreed on by the numerous agencies as key Everglades
restoration issues. These include hydropattern modification, Hg contamination, eutrophication,
habitat alteration and loss, and endangered and exotic species. Each of these issues and the
interaction among them is more fully described in the following sections.
1.5.1 Hydropattern Modification
Change in natural hydropattern (i.e., depth, timing, duration, and distribution of surface
water) of the Everglades is one of several key issues to be addressed for the restoration of the
Everglades ecosystem. Canal drainage systems, levees, flood control structures, and water supply
diversions have collectively contributed to large-scale changes in hydropattern and resultant
changes in structure, function, and nutrient cycling of the Everglades ecosystem. The USACE
Central and Southern Florida Project Restudy (USACE 1994) is evaluating the modification of
canals and levees to return the hydropattern to a more natural regime. Determining the natural
flow regime and hydropattern and subsequently implementing the required flows in the
Everglades are major restoration activities.
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1.5.2 Florida Mercury Problem
Since the initial detection of elevated levels of total mercury in freshwater fish (THgF) in
1989, it has become increasingly apparent that South Florida has an extensive THgF problem.
The state of Florida has issued a human health fish consumption advisory due to THgF
contamination that either bans or restricts the consumption of largemouth bass and other
freshwater species from about 2 million acres of water encompassing the Everglades and BCNP
(Figure 1.1). In 1995 the advisory was expanded to cover several fish species in Florida Bay. The
maximum THgF concentrations found in largemouth bass (4.4 ppm) and bowfm (over 7 ppm)
collected from an Everglades canal within WCA3A are the highest concentrations found in
Florida to date. The maximum concentrations found in bowfin are the highest reported
nationwide. While THgF contamination has been found to be greatest in the Everglades, it is also
found at levels of concern in largemouth bass throughout Florida's surface waters.
Transformation of inorganic Hg into methylmercury (MeHg), which is the most toxic form of
Hg, and its subsequent bioaccumulation in predatory game fish, is a cause for concern for human
health. Human consumption of MeHg contaminated game fish can lead to neurotoxicological
risk to human populations, especially to the developing nervous system of fetuses and infants
(EPA Mercury Report to Congress 1997). Food serves as the primary source of MeHg absorbed
by humans, and fish typically have the highest Hg concentrations of foods consumed by humans.
The intake of inorganic Hg from air or water ranges from one-hundredth to one-tenth of the
intake of MeHg from food (EPA 1997).
In addition to the potential risks to human health, the ecological health of the South
Florida ecosystem also is at potential risk from Hg transformations and cycling. Elevated levels
of MeHg have been found in various Everglades biota, including fish, the endangered Florida
panther, raccoons, wading birds, and alligators. A Florida panther (a federally and state listed
endangered species) found dead in ENP in 1989 had an extremely high liver MeHg concentration
of over 110 ppm. MeHg contamination not only poses a potentially serious threat to the
continued existence of the Florida panther, but also many other species in South Florida
ecosystems.
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While Everglades MeHg contamination has received widespread attention since 1989,
and atmospheric deposition of Hg as a potential dominant source of Everglades Hg are well
studied (Delphino et al. 1993; Pollman et al. 1995; Guentzel 1997; USGS ACME), the extent and
magnitude, transport, transformation, and pathways of Hg and MeHg through South Florida
ecosystems, particularly in peat, are still largely unknown. Atmospheric emissions from global,
regional, or local sources, such as fossil fuel fired electrical generating plants, solid waste
incinerators, and medical waste incinerators, and subsequent transport and wet and dry
deposition are known to be one source of Hg to the Everglades ecosystems. However, it is
unknown what portion of the atmospherically deposited Hg is methylated and accumulated
through the food chain. Other possible sources of Hg in Florida include natural mineral and peat
deposits, and paint and agricultural operations (Science Subgroup 1995).
Although there are multiple interactions among these sources and several possible
pathways for Hg transport and MeHg bioaccumulation through the Everglades ecosystem, none
of these individual sources appears to adequately explain the vast area with MeHg
contamination. Various degrees of uncertainty still remain in the quantitative understanding of
sources, transport, and transformation that limit the ability to make fully informed management
decisions at this time. These uncertainties are expected to be reduced substantially over the next
2 years as the monitoring, research, modeling, and assessment data collected over the last 5 years
are further analyzed, synthesized, and integrated into a more complete, accurate, and precise
predictive quantitative model. The South Florida ecosystem assessment project is expected to
make an important contribution to this effort.
1.5.3 Eutrophication
Nutrient loading from the EAA and urban areas has significantly increased nutrient
concentrations, particularly phosphorus, in the downstream WCAs and ENP (Scheidt et al. 1989;
Walker 1991; Walker 1995) and major eutrophic impacts to wetland systems downstream have
occurred (Nearhoof 1992). Among the progressive eutrophic impacts are increased soil
phosphorus content (Doren et al. 1996; DeBusk et al. 1994), altered natural periphyton
communities (Raschke 1993; McCormick et al. 1996), loss of water column dissolved oxygen
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(DO) and changed community metabolism (Belanger et al. 1989; McCormick et al. 1997),
conversion of wet prairie and sawgrass (Cladium Jamaciensis) plant communities to cattails
(Typha domingensis) (Davis 1994; Jensen et al. 1995), and subsequent loss of important wading
bird foraging habitat (Fleming et al. 1994, Hoffman et al. 1994). These collective changes are
systemic and impact the structure and functions of the aquatic ecosystem (Belanger et al. 1989;
Nearhoof 1992; McCormick et al. 1997).
FDEP concluded that eutrophication of the Everglades resulted in the violation of four
Florida water quality standards protecting fish and wildlife and created an imbalance in natural
populations of aquatic flora and fauna, with a resulting loss in biological integrity (Nearhoof
1992). Some eutrophic impacts, such as periphyton community changes, are thought to be
short-term and reversible if nutrient additions can be significantly decreased. Other impacts are
considered long-term (decades or centuries), such as loading peat soil with excess phosphorus
that triggers the loss of native plant communities and foraging habitat. The nutrient levels
required to sustain the natural balance of oligotrophic plants and animals into future decades and
centuries are currently under debate. There are still many marsh areas where total phosphorus
(TP) concentrations in surface water are near natural concentrations (i.e., 10 ppb and less) and
recent studies have shown that TP concentrations entering ENP are lower than concentrations
recorded in 1986 (Walker 1997). It is unknown however, how much changing hydrological
conditions and flow patterns in the Everglades have confounded these lower recorded TP
concentrations since 1986.
Nevertheless, a combination of agricultural best management practices (BMPs) and
construction of approximately 43,000 acres (174 km2) of wetlands known as stormwater
treatment areas (STAs) (Figure 1.1) is being implemented in the EAA in an attempt to control
phosphorus loadings to the Everglades. The goal of Phase I of the phosphorus control program is
to decrease total phosphorus (TP) concentrations in the water discharged to the Everglades to at
least 50 /^g/L. The effectiveness of these controls in reducing nutrient concentrations to near
natural TP concentrations of 10 ppb is not yet known.
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1.5.4 Habitat Alteration and Loss
Over 1 million acres of the original "River of Grass" have been drained and altered for
other uses since the turn of the 20th century. In addition to the habitat lost, much of the
remaining habitat has been altered because of unnatural flooding and drying, groundwater
removal, or similar perturbations. This habitat alteration is still ongoing as the population of
South Florida continues to expand. Unlike eutrophication and Hg contamination, habitat loss is,
for the most part, irreversible. In addition, habitat alteration aggravates other environmental
problems, and these interactions are poorly understood.
1.5.5 Endangered and Exotic Species
The South Florida ecosystem is known for its great diversity of plants and animals, many
of which are endangered (SFWMD 1997a). Florida also has a large number of introduced and
normative fish and birds, which compete with the native species. These introduced or exotic
species are not restricted to fauna; there are also significant numbers of normative plants. The
melaleuca tree (Melaleuca quinquenervia), for example, has taken over large areas of the
Everglades. This species was originally introduced because of its ability to transpire water and
help drain the wetland areas (Bodle et al. 1994). Eliminating introduced species altogether is
unlikely. Practices for minimizing their impact on native habitat and preventing continued
expansion into the Everglades are needed to sustain native Everglades communities, elements,
sensitive, threatened, or endangered species, and to maintain overall biological diversity of the
Everglades ecosystem.
1.5.6 Interaction Among Issues
None of the issues discussed above are independent of the others. These issues are all
intertwined, each problem affecting other problems. For example, hydropattern modification
affects the fate and transport of both TP and Hg within the South Florida ecosystem, as well as
habitat for endangered species. Addressing these issues requires a large-scale perspective.
Integrated, holistic studies of the multiple issues impacting the Everglades need to compare the
risks associated with all impacts and their interactions.
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Everglades Ecosystem:
LOXAHATCHEE
NATIONAL
WILDLIFE REFUGE
(LNWR)
Ft. Lauderdale
Stormwater Treameni Area
Figure 1.1 South Florida study area.
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Problem Formulation
A
n
® Characterization of
s Exposure •<—~ Ecological
j Effects
Risk Characterization
Figure 1.2 Ecological risk assessment framework.
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2.0 STUDY DESIGN
The EPA Region 4 South Florida Ecosystem Assessment Project, was designed to permit
synoptic sampling of the canals and marshes of South Florida. The design was based on the
sample survey procedures developed in the EPA Environmental Monitoring and Assessment
Program (EMAP). The study design is presented in this chapter. In addition, four marsh transects
were sampled along known nutrient gradients, and canal water control structures were sampled
for Hg in water on a biweekly schedule for 3 years (i.e., February 1994 through February 1997)
(Figure 2.1).
2.1 Design Rationale
There are two distinct paradigms for evaluating regional ecological status and trends. The
two paradigms are rooted in very different perceptions of regional evaluation and lead to
correspondently different methods for making regional inferences. In one, the sites are selected
based on their anticipated ability to reflect regional characteristics. The site features used in site
selection may be physical characteristics, spatial pattern, expected sensitivity to stress,
anticipated exposure level, or any other aspect that might influence the response of the site to
known or suspected environmental stresses. The quality of the resulting data depends on the
judgement of the investigator. This approach can lead to biased estimates of environmental
parameters. Moreover, it is difficult to assess sampling variability using this approach. An
example of this approach is the design used to sample the marsh transects along known nutrient
gradients.
EMAP uses an alternative approach that requires a probability sample. A key property of
a probability sample is that every element in the population has some chance of being included in
the sample. If this were not the case, then some parts of the population might as well not exist,
because their condition could have no influence on estimates of population characteristics. This
property has a side benefit, in that it forces an explicit and complete definition of the population
being described. This may seem trivial; however, in practice, it is almost never easy to tightly
delimit a real, physical population. Another requirement of a probability sample is that the
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chance of being included in the sample is known for every element in the population. This
requirement is satisfied if there is an explicit, well-understood mechanism that incorporates a
random process in the selection of the sample. Thus, a probability sample has three crucial
characteristics that distinguish it from other types of samples: (1) the population being sampled is
explicitly described; (2) every element in the population has some opportunity of actually being
sampled; and (3) the selection is carried out by a process that includes an explicit random
element. These three characteristics ensure that a probability based sample provides a degree of
comprehensive coverage that is not easily achieved with other methods. Furthermore, the
probability based sampling approach can lead to more precise estimates.
A probability sample does not have to be a purely random sample, and in most cases
should not be. In the case of environmental samples, there is almost always a great benefit in the
spatial context of the sample sites. In simplest terms, spatial context is the information required
to locate a sample point on the landscape, for example, latitude and longitude. However, there is
a richer connotation in all of the available landscape information that can be attached to
geographic coordinates: ecoregion, land use, soil type, vegetation cover, topography, and so on.
Knowing the spatial context of a sample (i.e., knowing where the samples are located and
knowing their spatial relationship to one another) provides the link of proximity to admit the
joint evaluation of multiple responses, and to evaluate the effects of stresses with known spatial
properties. The value of a probability sample is greatly enhanced if it is structured so that the
sample preserves the spatial context of the population. Although any random sample
accomplishes this in a sense, there is a great advantage to placing some spatial constraints on the
sample so that the spatial distribution of the sample closely matches the spatial distribution of the
population (i.e., the sample should in some sense be evenly distributed over the spatial extent of
the population). EMAP's sampling methodology uses a grid, as described in the next section, to
accomplish spatial dispersion of the sample while retaining the essential characteristics of a
probability sample. The probability based sampling approach used in this study, for example, can
be used to estimate the percent of canals with TP concentrations greater than some maximum or
minimum threshold, or the percent of the marsh sampled where THg concentrations are greater
than a maximum concentration specified.
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2.1.1 Sampling Method
An obvious means to ensure sample distribution over the extent of the population is to
use a systematic sample, say regularly spaced samples down the length of a canal or at the nodes
of a regular grid placed over a marsh. The major disadvantage of a systematic sample is that a
rigorous, design-based estimate of variance is impossible, even if there is an explicit random
placement of the grid or start of the regularly spaced linear sample. The requirement for a
probability sample is that every element of the population has positive probability of being in the
sample; a variance estimate is possible if, in addition, every pair of elements in the population
has positive probability of being in the sample simultaneously. A systematic sample does not
satisfy this latter requirement.
The design used to sample the Everglades is based on a grid in order to ensure spatial
coverage, but includes some additional randomization, to ensure that a variance estimate is
possible. The basic concept is to randomly locate a grid over the area to be sampled and, within
each polygon defined by the grid cells, to select one point at random. The basic design is called a
random tessellation stratified (RTS) design (Bellhouse 1977, Dalenius et al. 1961, Olea 1984,
Overton and Stehman 1993, Stevens 1997).
The basic RTS design results in every element of the population having the same chance
of being included in the sample. Extensions that allow for variable inclusion probability are
discussed in Overton et al. (1990) and Stevens (1997). The concept behind the variable
probability extensions is to group the grid cells together to form larger polygons that also
constitute a tessellation by congruent polygons. Figure 2.2 illustrates the concept, where the
tessellation hexagons of a triangular grid are joined in groups of seven to form a collection of
larger tessellation polygons represented by the solid lines. Variable probability is accomplished
by picking one or more points from each group, and allowing the number of points picked to vary
by spatial region. Stevens (1997) gives complete details of the variable probability versions of
the RTS design, and Stevens and Kincaid (1997) give an easily computable and nearly unbiased
variance estimator.
The design of the sampling in the Everglades was intended to obtain samples from both
canals and marshes, to extend over 2 years, and to sample in both wet and dry seasons in each
2-3
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year. Thus, there would be four sampling periods (2 seasons in 2 years) in both canals and
marshes. A spatially interpenetrating design given by a 4-fold decomposition of EMAP's basic
triangular grid (Overton et al. 1990, Stevens 1994) was chosen. In this approach, the grid cells
composing the tessellation are split into four interlocking sets, and one set of cells is sampled
each period.
The marsh sample was a straightforward application of these concepts. The area to be
sampled was defined by a Geographic Information System (GIS) coverage and consisted of
LNWR, WCA2, WCA3, ENP, and the eastern sector of BCNP. The sample was equiprobable
with the exception of BCNP, which was sampled at one-third the intensity of the rest of the
Everglades. A final design criterion of a maximum of 125 sampling sites per synoptic cycle,
which included consideration of logistical and laboratory efficiencies, was placed on the marsh
design.
The canal sample was selected differently because of the linear, essentially
one-dimensional nature of the canals. The base EMAP grid was intensified by a factor of 7,
resulting in a triangular grid with hexagonal cells having an area of approximately 90.1 km2 each.
A GIS was used to extract and randomly order the canal segments within each cell, where
segments were defined by confluences or cell boundaries. The grid cells, along with the
associated canal segments, were then randomly ordered, using the randomization procedure
based on spatial partitioning described in Stevens (1994). This randomization gave it a linear
order that preserved some of the spatial proximity relationship. The result of this process was a
random mapping of the entire length of canals onto a single line in such a manner that every
point on the line represented a known canal location (Figure 2.2). This line was then split into
four pieces using the same grid decomposition as in the marsh sample and a sample selected
from each piece using a systematic sample with a random start. The random mapping prior to the
systematic sample ensures that every pair of points on the canals had a positive probability of
being included in the sample, and the spatial-partitioning-based randomization ensures that the
sample is well-distributed over the extent of the canals. A criterion of a maximum of 50 sampling
sites per synoptic cycle was placed on the canal design.
2-4
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2.1.2 Sample Points
This random probability-based sampling strategy was used to select sites in the
Everglades ecosystem from south of Lake Okeechobee to the mangrove fringe on Florida Bay
and from the ridge along the eastern coast into BCNP on the west. The distribution of 200 canal
sample sites is shown in Figure 2.3 while the distribution of 500 marsh sample sites is shown in
Figure 2.4. The sample points represent the current ecological condition in over 1,200 km
(750 miles) of canals and in over 7,800 km2 of marsh (3,000 mi2 of marsh [over 2 million acres]).
The canals were sampled in September 1993, May and September 1994, and May 1995. The
marshes were sampled in April and September 1995 and May and September 1996. This
corresponds to two dry (April and May) and two wet (September) seasons for both systems over
a 2-year period. The project sampling included water, canal sediment, marsh soil, fish,
macrophytes, and algae/periphyton at each canal and marsh sampling location during each
sampling period. The parameters that were measured at each site can be used to answer questions
on multiple issues, including eutrophication, Hg contamination, habitat alteration, and
hydropattern modification.
2.1.3 Design-Based Estimation
There are two approaches to regional inference that are roughly parallel to the two
methods of sample selection. (See Hansen et al. [1983] and the following discussion for a good
contrast of these two approaches.) Briefly, a "model-based" approach uses conceptual, statistical,
and mathematical models to draw inferences to regional populations based on in-depth
information from a limited number of sites. The model may not be explicit (e.g., it may be
embodied in the set of criteria used to select representative sites). The model specifies the
relationship of the sites to the regional population, and the validity of the population inferences
rests on the validity of the model. Model-based inference makes inferences about parameters of
the model that generates the data and not about the population itself. In contrast, a design-based
program is essentially an empirical approach. The design specifies what information is to be
collected where, and the design stipulates the population inference. The validity of the inference
rests on the ability of the design to produce regionally representative information. In general,
2-5
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design-based programs rely on the methods of statistical survey sampling (see, for example,
Cochran 1977) and are valid only with a probability sample.
Both approaches draw inferences by calculating estimators of population quantities
(e.g., mean values, variance, and spatial pattern), and both rely on statistical theory to describe
properties of the estimators. The properties most often used are descriptions of the expected
behavior of the estimators: their variance, mean square error, bias, consistency, etc. The clearest
contrast between model-based and design-based approaches lies in the basis for that expectation.
Model-based methods rely on an assumed statistical model that describes the error distribution
(i.e., the distribution of the discrepancies between reality and model results); expectations are
then averages over possible error realizations. Design-based approaches rely on the explicit
randomization used in selection of sample locations; expectations are averages over all possible
samples.
A model-based approach uses information from sites in the population regardless of how
they came to be selected. The sites may have been purposefully selected, they may be available
because of historical circumstances, or they may be the result of a designed probability sample. In
any case, inference to an associated population rests on the assumption that the behavior of the
selected sites reflects and is typical of the behavior of the population. In a long-term monitoring
program aimed at status and nonspecific change in a spatially distributed population subjected to
nonuniform stresses, that assumption does not seem tenable under a judgmental sample selection
protocol.
A probability sample allows the use of both design- and model-based analyses. Moreover,
even if the model-based analysis does not make explicit use of the probability structure of the
sample, the model-based inference is strengthened by the characteristics of a probability sample.
Model-based parameter estimates can be biased under a judgement sampling design.
Hansen et al. (1983) makes several relevant points in their discussion of
design-based versus model-based inference. One that is particularly relevant for an
environmental monitoring program is that a probability sample permits inferences that are free of
even the appearance of subjectivity. A probability sample from an explicitly defined resource
population is a means of certifying that the data collected are free from any selection bias,
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conscious or not. This requirement is essential for a program such as EMAP that aims at
describing the condition of our national ecological resources. Moreover, analysis methods that
are as free as possible from the appearance of subjectivity are also available under a design-based
protocol.
2.1.4 Variable Probability Estimation
A requirement of a probability sample is that the probability of being included in the
sample must be known for every element in the population. In a continuous, extensive population
like the Everglades, this knowledge is contained in an inclusion probability density function 7i(s).
The requirement is that 71(5) be a known function, and that 71(5) > 0 for every point s in the
Everglades. Besides controlling the random selection process, 11(5) plays a critical role in the
inference and analysis stage. The inclusion function specifies the density of sample points;
therefore, it has units with dimensions like the number of sample points per unit of area (e.g.,
1 sample point in 635 km2 [245 mi2]). Conversely, the reciprocal of the inclusion function has
units of area per sample point, and thus gives the amount of area that each sample point
represents. A design-based analysis of a sample with varying inclusion density function needs to
account for the different weight attached to each observation (i.e., the different amount of area
represented by each point). From the above discussion, the proper way to give each observation
its correct weight is to multiply each observation by the reciprocal of the inclusion density
function at the observation site. For example, if we have samples at locations s„ s2,..., s„, with
corresponding observations z,, z2,..., z„, then the estimate of the mean value of z is
n
» „ . Ez
-------
In general, the variance of a quantity estimated from a probability sample depends not
only on the inclusion density function, but also on the pairwise probabilities of any two points
being included. Again, the general estimating equations are given in Horvitz and Thompson
(1952), Cordy (1993), or Stevens (1997). There is, however, a simplifying assumption that leads
to a simple estimate of variance. The assumption is that the sample arose from independent
drawings from the population. If the population has the characteristic that values measured on
sites that are close together tend to be more similar than values measured on sites that are far
apart, then that simplifying assumption leads to a conservative (i.e., larger than the true value)
estimate of variance. To apply this assumption to estimate the variance of jj. z, we first calculate
the quantities d(s) = [z(s )-£ lw(.s ). Then Var(Q) = —^— , where S2(d) is the
I Z Z n
£ HO]2
1=1
familiar estimator of the sample variance of the dt from a simple random sample, that is,
ta,-dy ±d,
S2(d) = — = — (since (since d = —— = 0). As noted above, this method
n-1 n-\ n
will generally understate the true precision of the estimate. The degree of understatement
depends on the smoothness of the sampled surface, that is how smoothly z(s) changes over the
population domain. If the surface is very rough in the sense that there is likely to be a little more
correspondence between two adjacent points than between two widely separated points, then
there should be little or no understatement. If the surface is very smooth, then the variance
estimate could be too large by a factor of 2 or more (Stevens and Kincaid 1997).
The above discussion deals with estimating a population mean value and its variance. The
same technique can be used to estimate the proportion of a population that meets some criteria or
falls within some category. For example, we may be interested in the proportion of the
Everglades covered by cattails, or the proportion of the Everglades with water concentration of
TP less than x. To do this, we form a new response variable that takes on the value 1 if a sample
site meets the criteria or is in the category, and 0 otherwise. We call this new response the
indicator variable for the criteria or category. For the category {land cover = cattails}, the
2-8
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. . ,, . , /x [l, if s is covered with cattails _ , „ ,
indicator variable is Llln,iXsi) = . . The mean value of the
cattails^ ,/ |^o, otherwise
indicator variable is the proportion we want, and we estimate it and its variance using the same
n
£ }ca„a,ls(SMS,)
method as for any other mean. Thus, for example, pcatlaih = — would give the
/ = i
estimated proportion of the sampled population in the land cover class "cattails".
The indicator variable technique can be used to obtain an estimate of the entire population
distribution via a function known as the cumulative distribution function (cdf). The cdf for a
variable z , say F.(x), gives the proportion of the population with z value less than or equal to x.
For example, if z is TP concentration in (units), then FTP(U) is the proportion of the population
with TP concentration less than or equal to # (units). The cdf of z is estimated by picking a set of
levels x,, x2,..., xk that span the range of z, and then estimating the mean values of the indicator
n
fl ifzfs) is < x - Xj
variables /, X?) = j ' ' . J , so that F (x ) = — .
(z s Vv '' 0, otherwise J'
/ = 1
The concept of the indicator variable seems very simple, but it is in fact a very powerful
tool for doing exploratory and comparative analyses of a complex probability sample. For
example, the formulae above show how to compute the cdf for the entire population (e.g., the
entire Everglades). But we can also use an indicator variable to estimate the cdf for a subset of
our population. For example, suppose we want the cdf of TP concentration for only that portion
of the Everglades covered with cattails. We use the "cattail" indicator variable in the cdf
n
estimator equation to get FTplcallails(Xj) = — . At any particular value
£ LuaUs^M*,)
( = 1
xj' Frp\cauaiis
-------
"sawgrass" using a "sawgrass" indicator variable, and compare the two cdf s. One way to make a
quick and informative visual comparison is to calculate the two subpopulation cdfs at the same
levels of the x-variable (TP in the example), and then plot corresponding values against one
another, producing a plot known as a Q-Q plot (Q for "quantile"). If the two distributions are
approximately equal, then they should plot on roughly a 1:1 line.
Subpopulation analyses via indicator variables also can be used to examine associations
between several variables. For example, we could split the range of TP concentration into "high,"
"medium," and "low," and then for each corresponding subpopulation, calculate the cdf of Hg in
fish tissue. We could further define several geographical areas, for example, north of Alligator
Alley (AA), between Alligator Alley and Tamiami Trail (TT), and south of Tamiami Trail, and
then compare Hg concentration for all nine subpopulations given by all combinations of TP
concentration and geographic region. The complexity of the association one can examine, or the
number of variables involved is limited only by the availability of data. In the above, we
suggested comparing the cdfs. For adequate precision in the estimate, a cdf estimate should be
based on 30 or more points. With fewer than 30 points in each subpopulation, it would be
advisable to compare proportions or means. In this case, the subpopulation analysis could look
very much like an analysis of variance (ANOVA).
2.2 Indicators
An array of indicators was selected to address the water management, habitat,
eutrophication, and Hg issues under investigation that could be accommodated within the scope
of the sampling design and the logistical limitations (Table 2.1 and 2.2). Surface water
measurements included water depth, temperature, DO, pH, specific conductivity, redox (Eh),
turbidity, TP, total nitrogen (TN), total organic carbon (TOC), total ionic sulfate (TSO„), alkaline
phosphatase activity (APA), chlorophyll a (canals only), and THg and MeHg (Table 2.3).
Whenever canal sites indicated a vertical differential existed between surface and bottom
measurements of temperature and DO, a vertical profile was made through the water column to
define the stratification. In this report the term "soil" refers to those samples obtained from the
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Table 2.1 Water and soil/sediment chemical measurements to be taken at each site with the
general rationale for measurement.
Indicator
Rationale for Inclusion
Water Quality
DO
Anaerobic condition promotes methylation; impacted by
eutrophication, water quality standard
Specific conductivity
Ionic strength influences metal toxicity, indicates water
source/history
pH
MeHg often found in low pH systems
Turbidity
Particulate metal transport, reduces water clarity for primary
production
TOC
Affects metal partitioning
APA
Sensitive indicator of eutrophication
THg
Total mercury pool, by media
MeHg
Biologically accumulated Hg species
TP
Indicator of eutrophication
TN
Indicator of eutrophication
tso4
Influences Hg methylation, microbial processes, eutrophication
Soil/Sediment Quality
Bulk density
Measure of compaction
% Mineral content
Estimate of non-carbonaceous material
THg
part of available pool
MeHg
Biologically accumulated Hg species
TP
Indicator of eutrophication
pH
Low pH promotes methylation
Eh
Influences Hg methylation, phosphorus cycling
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Table 2.2 Physical and biotic measurements taken at each site with the general rationale for the
measurement.
Indicator
Rationale for Inclusion
Physical
Site location
Spatial distribution
Resource class (e.g., canal, marsh)
Habitat classes of interest
Water depth
Affected by management; critical to ecosystem
restoration; may influence anaerobic conditions
Temperature
Influences rates of chemical reactions and
biological processes
Weather
Explanatory variable
Soil thickness
Potentially available Hg; pool affected by water
management; important for marsh preservation;
subsidence or accretion trends
Biological Quality
Fish tissue contaminants (Selected species)
Hg exposure in aquatic organisms
Periphyton, chlorophyll a
Indicator of eutrophication
Vegetation
Indicator of resource class diversity and integrity
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Table 2.3 Analytical parameters for marsh and canal samples.
Indicator Variable
Media
Water1
Soil2
Sediment3
Periphyton2
Fish4
Temperature
/
Turbidity
/
Conductivity
/
DO
/
pH
/
/
/
Eh (Rodox potential)
/
/
TOC
/
/
TN
/
TP
/
/
/
tso4
/
/
APA
/
THg
/
/
/
/
/
MeHg
/
/
/
/
Ethylmercury (EtHg)
/
/
/
/
% Ash Free Dry Weight
/
/
Bulk density
/
Fish length
/
Fish weight
/
Fish sex
/
Chlorophyll c?
/
1 Marsh, canal and structure sampling
2 Marsh sampling only
3 Canal sampling only
4 Canal and marsh sampling
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marsh system while the term "sediment" is used to refer to the samples obtained from the canal
substrate. The marsh soil measurements included soil thickness; type; pH; Eh; bulk density;
percent organic matter; TS04; TP; THg; MeHg; and EtHg (Table 2.3). Sediments from the canals
were analyzed for percent mineral content, TP, pH, THg, MeHg, and EtHg. THg and MeHg were
measured in the discharge from the structures on a biweekly frequency.
Biological tissue samples included floating and soil periphyton in which THg, MeHg, and
EtHg were analyzed. Fish tissue samples were exclusively eastern mosquitofish (Gambusia
holbrooki). Individual whole fish were analyzed for THg and the length, weight, and sex of each
fish was recorded to provide population level statistics. The eastern mosquitofish was selected as
a key indicator organism for Hg bioaccumulation because it is a prey species for a number of top
predators in the system. This indicator species compliments the Florida Game and Fresh Water
Fish Commission (FGFWFC) long-term monitoring efforts on largemouth bass. Mosquitofish
has the following advantages as a systemwide biological indicator organism: (1) ubiquitous
across the system, occurring in both canal and marsh habitats; (2) short life span; (3) small home
range; (4) biomagnifies Hg; (5) important in the aquatic food web; (6) omnivorous; (7) easily
captured; and (8) minimal size versus Hg concentration relationships.
Plant community composition and presence or absence of cattails (Typha spp.) and
Periphyton mats were used as qualitative indicators of marsh habitat (Table 2.2). The dominant
and secondary plant communities occurring at each site were identified as well as the community
sampled. In addition, the presence or absence of cattails and floating periphyton mats were made
from a secondary review of two 35 mm photographs taken at different angles at each marsh
sampling location. The presence of a single cattail or periphyton mat was enough to indicate
presence as long as these indicators were visible in both photographs taken at each sampling
point. Although no formal plot size or distance criteria were established for habitat indicators,
plant species or plant types had to be identifiable in the photograph to be included in the
qualitative assessment of marsh habitat.
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2.3 Design Summary
The EPA Region 4 South Florida Ecosystem Assessment Project design was RTS
probability sample of the canals and marshes of South Florida. The project was designed around
the seven policy questions listed in Section 1.3, and focused on providing preliminary answers to
assessment questions pertaining to magnitude, extent, and current conditions, and on providing a
baseline for assessing future trends.
Because the sample was a probability sample, model-free inferences to the sampled
population are possible. The sampled population was approximately 1, 200 km (750 mi) of
canals, which were sampled in September of 1993, May and September of 1994, and May of
1995, and approximately 7,800 km2 of marsh that were sampled in April and September of 1995,
and May and September of 1996. Design-based descriptions of this population regarding extent,
magnitude, and current condition can be obtained without appeal to any additional statistical,
biological, or mechanical model. In particular, a model of spatial or temporal correlation is not
required. Such models may be built using the data resulting from this program, but estimates of
magnitude, extent, and current condition are available from a strictly design-based approach.
The canals and marshes were sampled independently. The canal sample was
equiprobable, as was the marsh sample except for the BCNP. The BCNP was sampled at one
third the intensity of the remainder of the marsh. Thus, the only instance when the probability
weights need to be accounted for in analyzing the data is when BCNP data is mixed with other
marsh data (e.g., if a median value for the entire marsh were being estimated). Furthermore, the
RTS design capitalizes on any spatial pattern that exists in the response on a scale comparable to
the grid spacing in such a way as to give a more precise result than would ordinary random
sampling. These two facts, the equiprobable sampling and the increased precision of the RST,
mean that standard statistical analyses will yield unbiased estimates of population characteristics,
and conservative estimates of precision.
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Figure 2.1 Location of four marsh transects sampled in April 1994 and canal water control
structures sampled on a biweekly basis from February 1994 through February
1997. 2-16
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Figure 2.2 General schematic for clipping canal segments from the individual hexals and
then randomly arranging them in a linear order so a systematic sample of
50 sites/cycle could be selected to sample.
2-17
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CANAL SAMPLING LOCATIONS
£
a>
La
WD
V
•a
E
"3
•o
O
H
H
<
-
-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 2.3 200 sampling sites are located on over 1,200 km of canals.
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MARSH SAMPLING LOCATIONS
£
-------
3.0 MATERIALS AND METHODS
3.1 Field
3.1.1 Logistical Rationale and Needs
The large spatial scale of this study required design of the field sampling around
helicopters (Bell Jet Rangers four-passenger with floats) to make the sampling as efficient and
rapid as possible. All stations were located with handheld global positioning system (GPS)
equipment (Trimble® Pathfinder Pro) corrected to within ±25 m. A synoptic sample over the
entire ecosystem proceeding from south to north was completed in a 6-day period for canals
(50 stations) and transects (45 stations) and an 8-day period for the marsh grid (125 stations). To
reduce costs, about 60% of the 50 canal sampling stations in each cycle were accessed by a single
helicopter and the remainder by jon boat. The helicopter was idled at mid-channel while the canal
samples were being collected to maintain position and to prevent damage to the aircraft. The
helicopter was shut down at all marsh sampling sites. To sample the marsh transects, a single
helicopter was used for all mid-marsh sites; however, some sites near the canals were accessed
with an airboat. The marsh grid was sampled with two crews and two helicopters. A two-person
sampling team was used in each aircraft and all gear and sample containers were designed to fit
in the fourth seat and the aft storage compartment.
3.1.2 Apparatus
The development and application of clean sampling methods was a primary goal of this
project. During project initiation the first canal sampling cycle and the marsh transect sampling
effort were used to work out a final sampling protocol for the remaining canal and marsh
sampling cycles. During these pilot studies the water samples were dipped by submerging the
water bottles under the surface of the water until filled. The dip method had several limitations:
(1) water samples could not be collected from water that was less deep than the width of the
bottle eliminating samples from large areas of shallow marsh, (2) there was no way to prevent
large particulate matter from entering with the water, and (3) there was little assurance that a
clean sample could be collected by dipping. A hand-operated vacuum water sampling chamber
was developed and used to consistently collect a screened ultra trace level water sample.
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(Specifications and pictures of sampling equipment are provided in Appendix A.) The intake
wand was fitted with a 105/^m replaceable Nitex® screen to prevent large particle matter from
entering the sample container. The screen was held over the end of the wand by a plastic coated
magnetic ring (Gelman magnetic filter funnel with funnel cut off) and easily and quickly replaced
between stations. The samples were not filtered to permit quantification of total constituent
concentration, which can be ecologically significant. The chamber was made of machined '/4-inch
Plexiglas® with an o-ring seal for the lid. All intake and exit lines fitted into the lid were of
'/4-inch Teflon® tubing. The chamber was sized to hold a 2-liter Teflon® bottle required for clean
low level Hg samples.
The sampling procedure was initiated at each station by placing a 2-liter polypropylene
bottle in the chamber and pumping the bottle about 25% full. This water was used to rinse the
bottle and discarded. The bottle was then pumped 75% full and this sample was used for TS04,
TP, TOC, TN, turbidity, and APA samples. The low level Hg sample was taken immediately
after by placing the 2-liter Teflon® bottle into the chamber and pumping it full with no
headspace. A 2-liter bottle was filled in about 5 minutes with about 380 mm (15 inches) Hg of
vacuum. The bottle was labeled, its number recorded, inserted into a Fisher® plastic bag, and
placed in a cooler inside a black plastic bag. The device was flushed twice before each clean low
level Hg sample was collected at each station when this sampling sequence was followed. During
this procedure, the operator was gloved with PVC rubber gloves covered with shoulder length
polyethylene gloves and clothed in chest waders and/or a flight suit. Water samples were
collected near the helicopter at about 1 foot below the surface when sampling in deep water and
at mid-depth when sampling shallow water. Acidification of the Hg samples was made the same
day following return to the clean laboratory on the Florida International University (FIU) campus,
where 1 ml of trace metal grade HC1 per 1000 ml of sample was added to each Hg sample on the
same day. Water field blanks (carry along controls) of Hg free deionized water were taken into
the field with each crew each day and analyzed for ultra trace level THg before and after
transport to the field. Sampling near the helicopter had the potential for sample contamination
especially on the canals where the helicopter had to be operated continuously to maintain
position and when landing in shallow marsh. Water samples collected at various distances from
the helicopter as well as the field blanks indicated no contamination of the samples was evident.
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Additional information on quality assurance/quality control (QA/QC) can be found in the data
quality objectives (DQO) (Appendix B).
Chlorophyll a and particulate samples were collected from the canals using a 140 cc
plastic syringe fitted with a 0.45/u glass fiber filter (GF/F) membrane filter cartridge. An effort
was made to pass 2 to 3 volumes of the syringe through the filter. The final water volume filtered
was recorded and the filter removed with clean forceps and placed into a microfuge tube and
capped. The chlorophyll a sample was stored on ice in the dark and transported to the laboratory.
A stainless steel petite ponar dredge, previously cleaned and sealed in plastic, was used to
obtain canal sediment samples. A sample was used only when the dredge was retrieved full with
no apparent disturbance to the surface of the sediment. The sample was placed in a clean glass
pan and mixed thoroughly with a plastic spoon. Large pieces of plant material, mollusc shells,
and other debris were separated from the fine sediment and discarded. Three 120-milliliter plastic
cups were filled approximately 75% full at each station and sealed in Fisher® plastic bags and
placed on ice. The dredge was thoroughly rinsed in canal water between stations.
After testing numerous commercially available soil sampling devices a 3-inch diameter
clear polycarbonate coring tube (0.125-inch wall thickness) was developed to collect marsh soil
samples. This tube diameter was selected because it was large enough to minimize compaction of
the soil in the tube and retain the sample in wet conditions. The leading edge was serrated and
sharpened to facilitate cutting through dense peat and plant roots. Coring tubes were designed to
sample depths to 45 cm and tested during the transect study. Following that effort a
determination was made to focus all remaining marsh soil sampling on the top 10 cm. A stainless
steel tube top (Appendix A) was developed with a threaded receiver for the threaded lexan®
tubes, which were cut to 25 cm in length. The tube top was designed with a flapper valve for the
escape of air and water, a foot pad and a receiver for a stainless steel handle were also included.
Stainless steel handles in 4-foot lengths could be added with stainless steel attachment pins when
the water depth required. This soil sampling device allowed quick assembly and disassembly.
The soil cores could be rapidly retrieved, the tube unscrewed, and a clean PVC/rubber plunger
used to push the core top to the 10 cm mark on the tube. The excess soil was sliced off with a
Teflon® coated spatula and the remainder of the core placed in the sample. A sealed 1-gallon
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plastic container was used to transport triplicate cores from each station to the laboratory in a
cooler.
Upon arrival at the laboratory at the end of each day, the soil samples were processed by
technicians wearing PVC gloves. A clean polypropylene spoon was used to mix and homogenize
the soil cores, which were composited in the plastic container. During the mixing, large debris
(e.g., large plant roots and sticks) that occurred in the samples were removed. Depending on the
sample volume requirements, from five to seven 4-ounce plastic sample containers were filled
approximately 75% full, labeled, and tagged. One hundred milliliters of deionized water was
mixed with the soil remaining in the 1-gallon plastic container. Temperature, pH, and Eh probes
were inserted into the soil slurry and allowed to equilibrate for 5 minutes, after which the
temperature, pH, and Eh measurements were made.
An in situ Eh probe was developed by recessing 1 cm square platinum electrodes into the
outside of a 1%-inch PVC pipe. The electrodes were attached at intervals of 2.5, 5, 10, 15, and
20 cm from the top. A wire was silver soldered to the inside of each electrode and run through a
water tight connector at the top of the pipe to a 5-position switch. An adjustable stainless steel
stop plate with friction screws was designed with an extension to protect the water tight fitting
and to provide a receptacle for the attachment of a 4-foot stainless steel handle (Appendix A).
During development a solution of known Eh was used to test the response of each system. A
millivolt meter with an attached AgCl2 reference electrode completed the instrument. The probe
was inserted into the soil so that the stop plate was against the soil surface. The millivolt meter
was plugged together with the probe with the reference electrode in the water. The system was
allowed to equilibrate for 15 minutes, at which time the electrodes were queried sequentially
from top to bottom with the switching device and the readings recorded on the field data sheet.
The same protocol was repeated at each station. Soil pH and Eh along the marsh transects were
measured on site by inserting an Eh electrode into an intact soil core.
A Hydrolab Scout 2 Water Quality Data System (Hydrolab) was used to measure water
temperature (°C), DO (mg/L), specific conductivity (mS/cm), pH, and Eh (mV). The data sonde
was suspended in the water column at mid-depth and the DO probe was allowed to equilibrate
prior to recording the readings on the field data sheet. The Hydrolab calibration procedure
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defined in the EPA Science and Ecosystem Support Division (SESD) Standard Operating
Procedure (SOP) was executed in the laboratory prior to entering and leaving the field each day.
Mosquitofish were collected with a Turtox Indestructible dipnet (800 x 900 mm
multifilament nylon net) with a 40-inch wooden handle. The sampler used the net in an
aggressive manner in an attempt to capture a complete size range of the fishes in the area near the
helicopter. When necessary, both crew members used the same technique to collect the required
number of mosquitofish to shorten the time on station. The fish captured with each swipe of the
net were handled with latex gloves and placed in a 5x8-inch Fisher® plastic bag and labeled
according to station number (place) and documented on the field data sheet. A minimum of
20 fish were collected at each site except when additional fish were collected for isotope or food
habits analyses. After the fish were bagged, the bag was placed on ice in a small cooler for
transport to the FIU laboratory. In the laboratory the bags of fish were visually checked for
completeness and placed immediately in a freezer for storage until analysis for Hg, which
occurred within a 1-month holding time. There was concern that the preservation of fish in air
evacuated sealed bags may result in the desiccation of these small fish. An experiment was
conducted to test for dessication and it was found that weight loss resulting from this method of
preservation and freezing did not exceed 5% (B. Loftus personal communication).
3.1.3 Schedule
A typical daily schedule started with the arrival of the support personnel at the FIU
laboratory around 6 AM to calibrate the Hydrolabs, pack the sampling equipment and supplies,
and disconnect the GPS unit from the charger and pack the instruments. Around 7 AM the field
personnel arrived to load equipment and supplies into vans for transport to the helicopter landing
zone. The sampling teams secured and prepared personal gear and safety equipment (flight suits
and helmets). The helicopter/boat was loaded at 8 AM, and the crew(s) departed for the field.
While the field team was collecting samples, the support team serviced and repaired the field
equipment, completed analyses from the previous day, labeled/packaged samples, completed
chain-of-custody forms, shipped samples to other laboratories, and made up packs of sample
containers for the next day. With return of the sampling crew(s) around 5 PM the helicopter was
unloaded and the samples, equipment, and supplies were delivered to the FIU laboratory, where
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the field data sheets were verified, sample preservatives added, the GPS unit(s) downloaded, and
the Hydrolab(s) end-calibrated. The support team remained on duty tracking the samples with
computer software (FORMS), labeling, processing sediments, performing bench-top analyses of
water samples for turbidity, APA, and sulfide. The support team completed their duties around
10 PM each evening.
3.1.4 Sampling Routine
A field sampling routine was developed that facilitated the efficient collection of water,
sediment, and biota from remote sites using a helicopter. Sampling from an airboat or a jon boat
was slower and less demanding but followed a similar routine. All tasks were divided among a
two-person sampling crew. The crew person in the front seat usually operated the handheld GPS
equipment so that it could be compared with the helicopter GPS readings and in case of failure of
the handheld unit be used as a substitute. The crew person in the rear seat managed the water
sampling gear and all the sample containers, which were stored in Fisher® plastic bags inside two
ice chests. The sediment and fish sampling gear was stored in the rear compartment of the
helicopter. The sampling stations were selected for each helicopter each day by identifying a
group of 8 to 10 stations, which minimized flight time, refueling, and potential interaction with
the other helicopter. During each sampling event, stations were sampled from south to north,
moving upstream. Flight following was practiced with ENP radio dispatch by each helicopter
each day with the preselected stations for the day. To initiate field sampling the pilot was given
the coordinates for each sampling station that the team wanted to visit during the day. These
coordinates were usually keyed into the helicopter GPS to aid navigation from point to point. The
helicopter GPS was used to navigate to within 0.5 km of the sampling site and the handheld GPS
was used for final approach and landing on the site. In rare cases if the landing site was unsafe
due to extremely tall cattails, sawgrass, or cypress trees, the pilot was directed to move to the
nearest safe landing site. Upon landing, the GPS coordinates were recorded on the field data
sheet along with the start time and logged electronically for 3 minutes before the unit was turned
off.
Immediately following landing, preparations were made to initiate water sampling, which
was always carried out first in the sequence to minimize contamination and disturbance of the
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water column. The application of clean sampling methods were most critical for water and the
vacuum bottle sampler was used to begin the sampling sequence at each station. The water
sampling sequence resulted in two 125-milliliter polyethylene bottles for TP, APA, TOC, TN,
and turbidity; a 500-milliliter HDPE bottle for TS04; and a 2-liter Teflon® bottle for Hg. Each
Teflon® bottle was etched with a unique number, which was recorded on the field data sheet at
the time of sampling. An additional 125-milliliter polyethylene bottle was filled for H2S by
dipping and preserved with two drops of zinc acetate. The number of bottles and types of
samples were recorded on the field data sheet. The collection of water samples was followed
immediately by placing the Hydrolab sonde at a mid-depth position and recording the
temperature, DO, pH, conductivity, and Eh on the field data sheet. This unit is equipped with a
stirrer to maintain constant water flow across the membrane.
The following basic information was entered on the field data sheet: the station number,
date, helicopter number and pilot, crew members' initials, water field blanks (when taken),
duplicate samples (when taken), Eh probe number, Hydrolab number, and camera model. A
marquee indicating station number, date, cycle, and film roll number was completed and
photographed as one in a series of 35 mm color slides including the marquee, a ground level
scene, a soil core, and an oblique photo of the sampling site from an altitude of approximately
100 ft. The film roll number and frame numbers of these images were recorded on the field
sheets at each station.
Plant community composition and presence or absence of cattails (Typha spp.) and
floating periphyton mats were recorded at each of the sampling sites. A visual assessment of the
vegetation types and their relative dominance at each site was made by each sampling team while
onsite. Two 35 mm photographs were also taken for later review. The dominant and secondary
plant communities occurring at each site were identified as well as the community sampled.
In addition, the presence or absence of cattails and floating periphyton mats were made
from a secondary review of the two 35 mm photographs taken at each marsh site. The presence
of a cattail or floating periphyton mat was enough to indicate presence, as long as the indicator
was visible from both photographs taken at each point. Although no formal plot size or distance
criteria were established, in order for a specific plant type to be included in the qualitative habitat
assessment, it had to be identifiable in the photographs.
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Observations made by the crew included weather, surface water flow, soil type, and
vegetation type/fish habitat, which were qualitatively coded on the field data sheet.
The remaining tasks carried out to obtain soil/sediment measurements and tissue samples
were organized by each sampling team to maximize speed and efficiency. The in situ Eh probe
was inserted into the marsh soil and connected to the reference electrode, switch box, and meter,
and the start time was recorded. This probe was allowed to equilibrate for 15 minutes prior to
switching across the soil depths and recording the readings on the field data sheet. The surface
water and soil depths were measured by using a rod, marked in tenths of feet, which could be
lengthened by screwing on additional sections. These readings were recorded on the field data
sheet. Three soil cores were collected at each site, and the soil periphyton, which could be
separated as a distinct surface layer, was placed in a separate soil periphyton sample container.
Only the top 10 cm of the soil column from three cores was retained. When floating periphyton
occurred at a site it was collected with gloved hands and placed in three sealed, 4-ounce plastic
containers. Fish were collected last with a dipnet, immediately placed in Fisher® plastic bags, and
stored in a cooler on ice until placement in a laboratory freezer.
Deviations from this routine were made when sampling the canals and the marsh
transects. The primary deviations from this routine when sampling the canals were the omission
of the Eh probe and the addition of particle samples, chlorophyll a samples, and Hydrolab
measurements throughout the water column except for temperature and DO. Sediment samples
were collected with a clean stainless steel petite ponar dredge. The primary deviations from this
routine for the transects were that water samples were dipped and not screened, soil cores were
collected to a depth of 45 cm, and soil Eh and pH were measured onsite in intact soil cores.
Water samples were collected by filling water bottles underwater at each site.
Upon completion of sampling at each site, the samples and equipment were packed into
the helicopter. The field data sheet was checked for completeness and signed by both members of
the sampling team before the helicopter departed for the next site.
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3.2 Laboratory Analyses
A flow chart showing the progression of methods development for this project is
presented in Figure 3.1. The development of analytical methods for THg in water, soil, and fish
was initiated in early 1993 prior to the first sample cycle in September.
Method
Gambusia Hg
Water Sampler
THg-Water
MeHg-Soil
Key
New method development
— Method refinement
— Routine method
1992
1993
1994
1995
1996
Battelle Fill
i i
1QQR
Figure 3.1 Methods development timeline.
The measurement of trace level quantities of THg and MeHg in water were required to
successfully carry out this project with minimum detection limits (MDLs) at 0.3 and 0.02 ng/L,
respectively. At the outset, it was known that there was no standard method available for the
analysis of THg and MeHg in any media and most methods used a slower batch process with
small sample throughput; however, there were several research methods in use around the world.
Because there was no trace level Hg analytical capability in EPA in 1992 to 1993, it was
determined that the project would use three laboratories to allow intercalibration and comparison.
The FlU-Southeast Environmental Research Program (FIU-SERP) laboratory in Miami was
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selected because a trace level Hg laboratory was already under development with US National
Park Service (ENP), and the proximity and experience of FIU-SERP in analyzing Everglades
samples was a definite advantage. The FIU-SERP laboratory had considerable experience in
developing state-of-the-art methods for several other parameters that the project also wanted to
use. The Battelle Marine Sciences Laboratory (MSL) in Sequim, WA was chosen to analyze
MeHg and THg in water samples, to analyze MeHg in soils and sediments, and to provide
QA/QC on split and duplicate samples. The EPA Region 4 Science and Ecosystem Support
Division laboratory in Athens, GA began development of the capability to analyze THg in soil,
sediment, and fish tissue. Table 3.1 shows the distribution of parameter analyses among the
laboratories and the primary and secondary QA/QC responsibilities. Due to the large sample
volume generated during the project it was equally necessary to use multiple laboratories to
distribute the work load in order to achieve timely completion of sample analysis.
Atomic fluorescence-based methods were developed for measuring ultra trace levels of
Hg in environmental (water, soil) and biological (fish tissue) samples (Jones et al. 1995). In
addition, methods for preparation of water, soil, and tissue samples were developed. For the
analysis of THg in soil, sediment, and fish, the samples were digested with concentrated nitric
acid in sealed glass ampules and subsequently autoclaved. Following digestion, the digestate in
the sealed ampules could be stored for later analysis to better manage the flow of work. Water
samples were digested using standard brominating procedures. A Merlin Plus, PS Analytical
atomic fluorescence spectrometer (AFS) system equipped with an autosampler, vapor generator,
fluorescence detector, and a PC-based integrator package was used in the determination of THg.
Prior to and during development of the vacuum water sampling chamber full-scale deflection was
30 ng/L; however, following development of the chamber full-scale was limited to 10 ng/L. The
determination of Hg species in water, without prederivitization, involved adsorbent
preconcentration of the organomercurials onto sulfhydryl cotton fibers. The organic Hg
compounds were eluted with a small volume of acidic potassium bromide (KBr) and copper
sulfate (CuS04) and extracted into dichloromethane. Sediment, soil, and tissue samples were
homogenized, and the organomercurials first released from the sample by the combined action of
acidic KBr and CuS04 and extracted into dichloromethane. The initial extracts are subjected to
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Table 3.1 Distribution of parameter analyses for multiple laboratory design.
LABORATORY
PARAMETER
FIU-SERP
BATTELLE
EPA-SESD
WATER
THg
Primary
Splits/Duplicates
MeHg
Splits/Duplicates
Primary
tso4
Primary
Turbidity
Primary
TOC
Primary
TP
Primary
Splits/Duplicates
TN
Primary
Splits/Duplicates
APA
Primary
Chlorophyll a
Primary
SOIL/SEDIMENT
THg
Splits/Duplicates
Primary
MeHg
Primary 1
Splits/Duplicates
EtHg
Primary
tso4
Primary
TP
Primary
Ash Free Dry Weight (AFDW)
Primary
Bulk Density
Primary
PERIPHYTON (Floating & Soil)
THg
Primary
Splits/Duplicates
MeHg
Primary
EtHg
Primary
GAMBUSIA
THgF
Primary
1 Initially Battelle following cycle 0
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thiosulfate clean-up and the organomercury species are isolated as their chloride derivatives by
cupric chloride addition and subsequent extraction into a small volume of dichloromethane.
Analysis of organic Hg compounds was accompanied by capillary column chromatography
coupled with atomic fluorescence detection.
Following the MSL analysis of the initial canal sediment samples collected in September
1993, it was apparent that the detection levels were not sufficiently low to allow the reporting of
other than the MDLs. Since this would not provide the desired information for which this project
had been designed, FIU-SERP was charged with the development of a method to determine
organic Hg compounds in soil and sediment. A sensitive method for the determination of MeHg,
and EtHg in soil and sediment was developed (Alii et al. 1994). The organomercurials are
released from the sample matrix by the combined action of acidic KBr and cupric ions and
extracted into dichloromethane. The initial extracts are subjected to thiosulfate clean-up, and the
organomercury species are isolated as their chloride derivatives by cupric chloride addition and
subsequent extraction into a small volume of organic solvent. Capillary gas chromatography
coupled with an atomic fluorescence detector system proved a very selective and sensitive
technique with excellent separation efficiencies for MeHg and EtHg. The absolute detection limit
for both MeHg and EtHg was 0.2 pg.
A new method based on capillary gas chromatography/atomic fluorescence spectrometry
(GC/AFS) was developed for the determination of MeHg and EtHg in water samples (Cai et al.
1996). An improved sample preparation methodology was developed, which involved
preconcentration of the alkylmercury species from water samples, drawn with a 12-channel
peristaltic pump, onto sulfhydryl cotton fibers adsorbent packed in a screening column, elution of
MeHg and EtHg with a mixture of acidic KBr and CuS04 solution, and back-extraction using
methylene chloride. Analysis was performed by capillary GC/AFS with a DB-1 column (Cai
et al. In Press a). Some important parameters, including sample pH, presence of anions and
cations, concentration of TOC, eluent type, and eluent volume were evaluated. With AFS as a
detector, the capillary gas chromatographic technique provides high selectivity, high sensitivity,
and a straightforward method for organomercury halide analysis. It eliminates possible spectral
interferences to the detector from other sample components and from chemicals used in the
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sample preparation procedure. The detection limit was 0.01 ng/L in a 1-liter water sample for
both MeHg and EtHg. The result for organomercury analysis in a number of natural water
samples was comparable to MeHg analysis using other methods with the following advantages.
The method following the solid phase extraction procedure based on the sulfhydryl cotton fibers
offers a number of advantages over other sample preparation methods, including higher
concentration factors, large sample throughput, less use of organic solvents, and improved
sample clean-up during the solid phase extraction procedure. This method also allows detection
of EtHg, which cannot be determined with ethylation-purge-trap methods, and avoids steam
distillation (Cai et al. 1997b). Steam distillation has been shown to generate artificial MeHg
(Bloom et al. 1997).
Finally evaluation of some isolation methods for organomercury determination in soil and
fish samples by capillary GC/AFS were made (Cai et al. In Press b). Three extraction methods,
acidic KBr/CuS04 isolation-methylene chloride extraction, acidic KBr/CuS04
isolation-methylene chloride extraction with an alkaline digestion pretreatment, and an extraction
method at a milder condition with citrate buffer and dithizone in chloroform, were tested for
MeHg and EtHg determination in soils, sediments, and fish samples by the recently developed
capillary GC/AFS. The acidic KBr/CuS04-methylene chloride extraction and the acidic
KBr/CuS04-methylene chloride extraction with an alkaline digestion pretreatment were shown to
be the effective methods for soil and sediment analysis and fish sample analysis, respectively.
The presence of EtHg species in soils of the Florida Everglades, observed with the acidic
KBr/CuS04 isolation and methylene chloride extraction procedure, was further confirmed with
the dithizone complexation/extraction procedure (Cai et al. 1997b). The GC/AFS analytical
method offers high sensitivity and selectivity for the determination of organomercury halides.
Since serious limitations have been found with both the distillation and the ethylation procedures
used to analyze both MeHg and EtHg species in soils, sediments, and biological samples, the
modified acidic isolation/organic solvent extraction combined with the GC/AFS technique
provides a useful analytical tool for organomercury speciation and an alternative for the current
methods available in the literature. Development and refinement of soil and sediment extraction
and analytical methods continued throughout the study until spring 1996 (Figure 3.1).
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Unfiltered water samples were used for the determination of TOC, TP, and TN. TOC was
measured by acidifying to pH <2 with 3N HC1, purging the sample with C02-free air, and
analyzing for total carbon using a hot platinum catalyst direct injection analyzer. TP was
determined using a dry ashing and acid hydrolysis technique (Solorazano and Sharp 1980).
Turbidity was determined by nephelometry using formizan calibration standards. TN was
measured by high temperature oxidation in an ANTEK 7000N Total Nitrogen Analyzer, using
the methods described by Frankovich and Jones (1998).
Soils and sediments were analyzed for TP, bulk density, and percent organic matter.
TP was analyzed using the ashing method described by Solorzano and Sharp (1980). Soil bulk
density was determined by drying a known volume at 80° C to a constant weight. Organic matter
was determined by loss on ignition at 550° C (Nelson and Sommers 1982).
Chlorophyll a was determined using the fluorometric method described by Strickland and
Parsons (1972). APA was measured using the method described by Jones (1997).
3.3 QA/QC
Numerous QA/QC exercises in water, soil, sediment, and tissue were conducted among
the project laboratories during the study. Differences in methods were expected to produce
differences in results, and every effort was made to achieve agreement, whenever possible, even
though standard methods could not be required. An internal Quality of Science Review was
conducted by EPA Office of Research and Development (ORD) National Exposure Research
Laboratory (NERL) Environmental Sciences Division (ESD) during the project (1) to identify
quality-related issues and provide recommendations for correction or improvement and (2) to
provide the project participants with the necessary tools to enable them to continue to monitor
data quality. Onsite visits were made to all active project participants and copies of all
preliminary data sets were reviewed. Data analyses included calculation of data quality indicators
(e.g., completeness, precision, accuracy); investigations of potential variability due to
transportation means, crew, or season; and analyses of issues relating to THg and MeHg in water
methods. The review described results of the onsite visits and data analyses, identified particular
strengths and weaknesses of the project, and provided recommendations for corrective actions.
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An adjustment was made in the calculation of the standard curve for THg in water data
developed by FIU-SERP using a flow-thru atomic fluorescence system without gold
amalgamation to make the data more comparable with those developed by Battelle MSL, which
used a cold vapor atomic fluorescence batch method with gold amalgamation. Data package and
validation/verification issues have been addressed by EPA Region 4 SESD.
Decision-Based DQOs (Appendix B) were prepared generally following the Guidance for
the Data Quality Objectives Process EPA QA/G-4 (USEPA 1994). This EPA guidance
document, however, is not entirely appropriate for research projects. The EPA ORD Quality
Assurance Management Staff are in the process of preparing DQO guidance for research
projects, but this guidance was not available. This project is a research project that in part, is
developing risk-based criteria for decisions because the existing criteria are not appropriate or no
criteria exist. Two separate but complementary approaches were used to develop project DQOs:
(1) using the EPA QA/G-4 documentation and (2) revising the DQOs originally proposed in the
REMAP Research Plan (Stober et al. 1993). The DQOs are presented with statements for data
representativeness, completeness, comparability, precision, and accuracy for each of the
constituents measured by the project (Appendix B). The canal and marsh data were evaluated
using the DQO criteria. Evaluation of the canal and marsh data field precision showed that a
consistent database was developed by the project with no canal or marsh parameters having
outlier in excess of 4% and 2.9%, respectively. The database has a very high degree of internal
consistency, and future monitoring should endeavor to continue this consistency and
comparability to minimize the introduction of artifacts into the baseline that has been established.
3.4 Data Analysis
3.4.1 Data Verification and Validation
Data verification and validation analyses were conducted on the data, both for QA/QC
and to establish the database for statistical and spatial analyses. This data set, with associated
meta data, can be obtained from EPA Region 4 SESD, Athens, GA. Inquiries can be sent to the
address on the title page. OA/OC findings are summarized in Appendix C.
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A number of statistical analyses were performed on these validated/verified data. These
analyses are listed in Table 3.2 and are briefly discussed below.
3.4.2 Descriptive Statistics
Descriptive statistics, including the range, mean, median, standard deviation, and
quartiles for each constituent, by media, sampling cycle, and system type, were computed for
various subpopulations (WCAs, ENP, area north of Alligator Alley, marsh, canals, etc.). These
descriptive statistics provided initial insight into the structure and attributes of these
subpopulations in the South Florida Everglades ecosystems. Box and whisker plots also were
computed and displayed by constituent, media, and subpopulation to provide a visual image of
the subpopulation attributes.
Cumulative distributions also were computed for each constituent, by media, cycle, and
subpopulation to characterize the structure of subpopulations and to provide initial insight into
any data transformations that might be required for parametric statistical analyses.
Constituent information was sorted by latitude and longitude to determine if there might
be north to south or east to west gradients that could provide insight into possible Hg sources or
indicate other factors that might be contributing to the elevated fish Hg concentrations measured
in the Everglades ecosystem.
3.4.3 Exploratory Analyses
A number of exploratory analyses were conducted on the data to gain greater insight into
the structure and attributes of various subpopulations of interest. These exploratory analyses
included scatter plots or multiple bivariate plot matrices, principal component, factor,
discriminant and cluster analyses. These analyses identified several factors or principal
components that contributed to the distribution of Hg in various media throughout the
Everglades.
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Table 3.2 Statistical analyses performed on data.
Analysis
Canal
Marsh
Structures
Transects
Descriptive Statistics
/
/
/
/
by sampling cycles
/
/
by seasons
/
/
by subpopulations
/
/
by year
/
Notched Box and Whisker Pots
/
/
/
by sampling cycle
/
/
~
by season
/
/
by subpopulation
/
/
Cumulative Distributions
/
/
by sampling cycle
/
/
by subpopulation
/
/
Scatter Plots
/
/
/
/
by latitude
/
/
by longitude
/
/
by depth
/
Scatter Plot Matrices
/
/
/
/
untransformed
/
/
/
/
transformed
/
/
/
Principle Component Analysis
/
/
untransformed
/
/
transformed
/
/
by season
/
/
transformed and season
/
/
Factor Analysis
/
/
by season
/
/
transformed, by season
/
/
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Table 3.2 (Continued).
Analysis
Canal
Marsh
Structures
Transects
Discriminant Analysis
by subpopulation
/
transformed by subpopulation
/
transformed
/
un transformed
/
Cluster Analysis
/
/
un transformed
/
/
transformed
/
/
by season
/
/
Cramer Von Mises
/
/
ANOVA
/
/
by subpopulation
/
/
by subpopulation and season
/
/
Analysis of Covariance
/
by cycle
/
by subpopulation
~
Linear Regression
/
/
/
untransformed
/
/
/
transformed
/
/
~
by subpopulation
/
/
Frequency Tables
/
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3.4.4 Inferential Statistics
Once the population and subpopulation attributes were described, statistical tests were
performed to test various hypotheses about differences among subpopulation characteristics.
These tests included the Cramer von Mises test (Kiefer 1959) for differences among cumulative
distributions and analyses of variance and covariance to determine if various constituent
combinations were contributing to differences among subpopulations. General linear models also
were used to determine the proportion of the variance in fish Hg concentrations accounted for by
a suite of other factors and constituent concentrations. Frequency tables were used to evaluate
possible differences among the distribution of selected constituents.
3.4.5 Spatial Statistics
Kriging was used to characterize the spatial patterns of constituent concentrations
throughout the marsh ecosystems. The kriging predictor of a constituent Z(s0) at an unsampled
site s0 is equal to the linear combination of the data
z (*<,)= E \ z(s,).
1=1
where Z (s,) is the value of the constituent at the i-th sample site s,. The A,s are chosen to
minimize the mean squared prediction error subject to the constraint that the resulting predictor is
unbiased (Cressie 1991). The values of the X,s are functions of the spatial correlation structure of
the data. However, the kriging predictor is not sensitive to misspecification of that correlation
structure (Cressie and Zimmerman 1992). In practice, kriging predictors are obtained at a fine
grid of sites (here, every 0.1° latitude and longitude), from which a contour map of predicted
values can be obtained. The contour map of predicted constituent concentrations was obtained
using Surfer® for Windows, Version 6 (Golden Software, Inc. 1995).
3.4.6 Mass Estimates
Mass estimates for THg and MeHg were calculated for the study area. Hg concentrations
and discharges through the structures were measured and used to estimate Hg loads to the WCAs
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and ENP. Atmospheric loads were estimated by the Florida Atmospheric Mercury Monitoring
Program (Pollman et al. 1997). Periphyton and fish Hg concentrations were measured and biotic
densities estimated from the literature. Water and soil Hg concentrations were measured and the
mass estimates were based on the spatial weighting factors associated with each probability
sample. The methods and results of these mass estimates are discussed more fully in Chapter 9.0.
3-20
-------
4.0 GENERAL CHARACTERISTICS OF THE WATER REGIME
The South Florida Everglades water regime characterized in this study consists of over
1,200 km of canals and over 7,600 km2 of marsh extending from Lake Okeechobee in the north
to the Florida Bay in the south and from the edge of the urban area on the east into the central
portion of BCNP (Figure 1.1) on the west. The general patterns in precipitation, water depth, and
in situ parameters (conductivity, temperature, turbidity, DO, pH) measured during the study
period are described in this section.
4.1 Precipitation
Precipitation records for nine stations within and bordering the South Florida Everglades
ecosystem (Figure 4.1) were analyzed to determine the relation of the 5-year (1992 to 1996)
study period to the period of record. The periods of record varied from 66 years for the northern
Belle Glade station to 27 years at the S-8 station (Table 4.1). Annual precipitation comparisons
and monthly comparisons were made for the baseline period and the period of record (Table 4.1,
Figures 4.2 through 4.10). There was considerable spatial variability in precipitation among
stations with annual precipitation estimates for the 5-year baseline ranging from 111 cm/yr
(43.7 in/yr) at S-39 to 164 cm/yr (64.8 in/yr) at S-6. This spatial variability was expected because
of the convective storms occurring during the wet season. The long-term norms ranged from 119
to 142 cm/yr (46.9 to 56.1 in/yr). In general, 1994 was a wet year throughout most of South
Florida with annual precipitation averaging about 127% of the norm and ranging from 87% of
the norm at the Royal Palm station to 153% of the norm at the S-5A station (Table 4.1). The
other years were generally within 10% to 15% of the long-term norm (Table 4.1). For most
stations, the period from November 1994 through October 1995 was considerably above the
long-term monthly norms (Figures 4.2 through 4.10). The first canal sampling cycle (i.e., cycle 0)
occurred during a relatively normal wet season (September) in 1993. However, the remainder of
the canal sampling cycles (i.e., May and September 1994, May 1995) occurred during periods of
above normal seasonal precipitation. The marsh sampling cycles were also initiated in periods of
above average precipitation (April and September 1995). May and September 1996 sampling
4-1
-------
Table 4.1 Precipitation summaries for the 9 stations used to establish the long-term norm and
baseline precipitation conditions.
STATIONS
S5A
BELLE
GLADE
DEVILS
GARDEN
S6
S39
S8
S9
TAM1AMI
TRAIL
ROYAL
PALM
LONG TERM AVERAGE PRECIPITATION (cm)
142.5
137.3
132.2
140.8
126.7
131.4
119.1
120.6
127.5
NUMBER OF YEARS
38
66
58
36
32
27
35
56
47
ACTUAL PRECIPITATION (cm)
1992
151.1
146.8
141.0
109.9
M
133.6
122.3
88.6
121.3
1993
128.0
133.3
140.9
91.7
99.4
141.9
108.4
146.0
114.1
1994
217.5
195.5
144.3
193.0
114.2
167.9
181.0
171.1
111.6
1995
144.8
146.9
163.5
137.6
138.6
140.5
137.3
112.9
141.6
1996
159.8
129.8
119.0
126.6
91.6
126.6
103.8
127.4
96.8
PERCENT OF LONG TERM AVERAGE PRECIPITATION
1992
106%
107%
107%
78%
M
102%
103%
73%
95%
1993
90%
97%
107%
65%
78%
108%
91%
121%
89%
1994
153%
142%
109%
137%
90%
128%
152%
142%
87%
1995
102%
107%
124%
98%
109%
107%
115%
94%
111%
1996
112%
95%
90%
90%
72%
96%
87%
106%
76%
5 YEAR AVERAGE PRECIPITATION (cm)
160.2
150.5
141.8
164.7
110.9
142.1
130.6
129.2
117.1
PERCENT OF 5 YEAR AVERAGE PRECIPITATION
1992
94%
98%
99%
67%
M
94%
94%
69%
104%
1993
80%
89%
99%
56%
90%
100%
83%
113%
97%
1994
136%
130%
102%
117%
103%
118%
139%
132%
95%
1995
90%
98%
115%
84%
125%
99%
105%
87%
121%
1996
100%
86%
84%
77%
83%
89%
79%
99%
83%
M = missing data
4-2
-------
seasons had above average precipitation, but the precipitation quantities were not as extreme as
in 1995.
Because the SI 2D flow is strongly influenced by water management decisions, the total
Shark Slough flow (S12ABCD+S333) provided a better frame of reference (Walker personal
communication). It should be noted that all 3 years were wet and 1995 was extremely wet. The
Shark Slough flow was 4 times the average flow experienced in water years 1979 through 1998
and 1.6 times the maximum flow.
4.2 Canals
4.2.1 Discharge
Discharge through the S-5A, S-6, S-7, S-8, and S-12 structures (Figure 2.1) are shown in
Figure 4.11. Discharge through these five structures varied by year (Table 4.2). The South
Florida canals and structures are a highly managed water system and drainage through this
system is not similar to drainage from a natural watershed. Managing for a more natural,
historical flow regime is one of the major Everglades restoration goals.
Table 4.2 Average annual flow (cms) through selected structures (Water years ending
September 30). (Walker personal communication)
Water Year
Structures
S5A
S6
S7
S8
S12ABCD +
S333
1979-1993
9.1
6.4
8.8
11.4
24.5
1994
13.4
13.8
9.8
11.0
33.5
1995
16.2
23.9
18.0
25.0
97.5
1996
11.5
12.7
9.7
14.0
58.0
4.2.2 Water Depth
Water depths in the canals generally increased from the north to the south, with the
greatest median depth of 4.6 m (15 feet) in the ENP (Table 4.3, Figure 4.12). Median depths in
the WCA were about 4 m (13 feet), during both the wet and the dry seasons. Median depths in
4-3
-------
the EAA canals varied about 0.8 m (4 feet) from 3.2 m (10.5 feet) in the wet season to 2.0 m
(6.5 feet) in the dry season. Water depth also varied seasonally in the ENP from about 4.6 m
(15 feet) in the wet season to 3.9 m (12.75 feet) in the dry season. Depths in the BCNP canals
were similar during the wet and dry seasons.
Table 4.3 Median values for selected canal constituents.
Area
Season
Depth
(m)
Surface
Temp.
(°C)
Bottom
Temp.
(°C)
Cond.
(^mhos)
Surface DO
(mg/L)
Bottom DO
(mg/L)
Turb.
(NTU)
pH
(su)
n
Median
(CI)*
it
Median
(CI)
n
Median
(CI)
n
Median
(CI)
n
Median
(CI)
n
Median
(CI)
n
Median
(CI)
n
Median
(CI)
EAA
Wet
38
3.2
(±0.7)
38
27.7
(±0.3)
37
27.3
(±0.4)
38
1015 0
(±254)
38
1.8
(±0.4)
37
1.3
(±0.4)
38
2.0
(±0.5)
38
7.19
(±0.05)
Dry
33
2.0
(±0.6)
33
29.8
(±0.5)
33
28.5
(±0.3)
33
646.0
(±84.7)
33
6.4
(±0.7)
33
4.8
(±1.2)
33
6.5
(±2.5)
33
7.63
(±0.11)
WCA
Wet
30
4.0
(±0.5)
30
27.9
(±0.4)
30
27.3
(±0.4)
30
736.5
(±77.3)
30
2.1
(±0.8)
30
0.9
(±0.4)
30
1.3
(±0.5)
30
7.32
(±0.05)
Dry
38
4.0
(±0.3)
38
29.3
(±0.5)
38
27.5
(±0.9)
38
739.0
(±73.8)
38
3 7
(±0.9)
38
0.3
(±0.3)
38
2.1
(±0.6)
38
7.40
(±0.08)
ENP
Wet
15
4.6
(±0.4)
15
27.4
(±0 9)
15
27.1
(±1.0)
15
567 0
(±39.4)
15
3.0
(±0.7)
15
2.0
(±0 5)
15
0.7
(±0.4)
15
7.32
(±0.90)
Dry
14
3.9
(±0 5)
14
29.2
(±0.7)
14
26.1
(±1.0)
14
578.5
(±38 0)
14
53
(±1.1)
14
1.6
(±1.1)
14
1.4
(±0.3)
14
7.44
(±0.10)
BCNP
Wet
16
2.1
(±0.8)
16
28.7
(±0 4)
16
28.1
(±0.9)
16
292 0
(±54.1)
16
3 1
(±1.4)
16
2.0
(±1.1)
16
0.4
(±0.2)
16
7.36
(±0.19)
Dry
15
1.9
(±0.8)
15
28.9
(±0.8)
15
27.9
(±0.9)
15
334.0
(±66.1)
15
2.9
(±1.5)
15
0.8
(±0 5)
15
1.2
(±1.7)
15
7.23
(±0 19)
* CI-95% confidence on median = 1.58 25/o) ^gpgg 1996)
J"
4.2.3 Temperature
Median surface temperatures ranged between IT and 30° C in canals during both wet
and dry seasons (Table 4.3, Figure 4.13). Median surface temperatures were about 1° C wanner
during the dry season (i.e., April, May) than during the wet season (i.e., September). Median
bottom temperatures in the canals were lower than surface temperatures ranging from
approximately 26° and 28.5° C during the wet and dry seasons (Table 4.3, Figure 4.14). The
4-4
-------
canals did exhibit thermal stratification during the dry season, particularly in WCA and ENP
canals, with as much as a 3° C difference between the surface and the bottom temperatures. At
these temperatures (i.e., 27° to 30° C), a 3° C difference in temperature represents a strong
density stratification. Because of the nonlinear relationship between density and temperature, a
3° C difference in temperature from 27° to 30° C is equivalent to the density difference between
4° C and 18° C in a strongly stratified, temperate northern lake (Hutchinson 1957).
4.2.4 Conductivity
Conductivity values decreased from north to south, reflecting the increased dilution of the
discharge from the EAA by precipitation (Table 4.3, Figures 4.15). Conductivity was
significantly higher (P< 0.05) in the EAA compared to other management areas during the wet
season because of the greater discharge from the EAA during the wet season (Table 4.3,
Figure 4.16). Conductivity values in the other management areas, (WCA, ENP, BCNP) were
similar regardless of season, with slightly higher conductivity values during the dry season. For
areas outside the EAA, evapoconcentration likely contributes to higher conductivity during the
dry season with dilution contributing to lower conductivity during the wet season.
4.2.5 Dissolved Oxygen
About 65% of the canal miles had hypoxic bottom waters (i.e., DO concentrations
< 2.0 mg/L) while 89% of the canal miles had bottom DO concentrations less than 5 mg/L. The
DO water quality standard in Class III Florida waters is 5 mg/L. Saturated DO concentrations
range from 8 mg/L to 7.6 mg/L based on water temperatures of 27° to 30° C, respectively. With
the exception of the EAA, median bottom DO concentrations were lower during the dry season
than during the wet season (Table 4.3, Figure 4.17). Median surface DO ranged from 1.8 mg/L
(23% saturation) to 6.4 mg/L (84% saturation) in the EAA canals during the wet and dry cycles,
respectively (Table 4.3, Figure 4.18). Median surface DO outside of the EAA ranged from
2.1 mg/L (27% saturation) to 5.3 mg/L (69% saturation) in WCAs, ENP, and BCNP. With the
exception of BCNP, surface DO typically was higher in the canals during the dry season than the
wet season (Table 4.3). Weak thermal stratification in the canals outside the EAA during the dry
4-5
-------
season likely contributed to decreased bottom DO. In the EAA canals, median DO concentrations
were over 3 times higher during the dry season, than the wet season. There was little thermal
stratification of the EAA canals, and with shallower depths than the canals in other areas during
the dry season, bottom DO in the EAA canals during the dry season was nearly at the water
quality standard of 5 mg/L. During the dry season, median surface DO in the EAA met the water
quality standard of 5 mg/L (Table 4.3). Wet season loadings to the EAA canals also might have
contributed to lower DO concentrations. During both wet and dry seasons, median surface DO in
WCAs and BCNP did not meet the water quality standard for Class III waters. Median surface
DO in the ENP satisfied the water quality standard during the dry season but not during the wet
season.
4.2.6 Turbidity
Turbidity values were more variable and highest in the EAA canals with median values of
about 4 Nephelometric Turbidity Unit (NTU) then decreased downstream (Table 4.3, Figure 4.19
and 4.20). Median values with 95% confidence interval plotted from the upstream to downstream
direction show this spatial trend (Figure 4.19). Dry season turbidity values in all management
areas were 2 to 3 times higher than during the wet season.
4.2.7 pH
The median pH values in the canals were circumneutral regardless of the season and
exhibited little seasonal variation (Table 4.3, Figure 4.21). Canal values throughout the network
had median pH values around 7.3 su. These circumneutral pH values in the canals are likely a
result of surface water contact with the limestone strata in the canals.
4.3 Marsh
4.3.1 Water Depth
Exceedance frequency analyses were conducted for 3 stations in the marsh: 3A-NE in the
northern portion of WCA3; 3A-28 in the southern portion of WCA3; and P-33 in Shark River
Slough in ENP (Figure 4.22). The 3A-NE site is considered to have shallower water depths and
4-6
-------
have a greater frequency of drying compared to predrainage conditions while water depths are
deeper at the 3A-28 site where water pools behind the levee compared to predrainage conditions.
Water depths in Shark River Slough are variable compared to predrainage conditions, but this
site typically is wet. These conditions are reflected in the exceedance frequency curves
(Figure 4.23). The periods of record for 3A-NE, 3A-28, and P-33 are 27,41, and 35 years,
respectively. The 3A-NE site is dry about 50% of the time while the 3A-28 and P-33 sites are dry
only about 15 and 5% of the time, respectively. The 1995 sampling year was exceptionally wet
with less than a 1% probability of observing greater water depths at stations 3A-NE and 3A-28
during the wet season (September 1995). During 1996, water depth exceedances ranged from
about a 40% probability of observing greater water depths at 3A-NE to about a 50% probability
of observing greater water depths at 3A-28 and P-33. Marsh sampling during the 2-year baseline
period, therefore, occurred during an above average precipitation and water depth period.
Water depths varied with time and space in the marsh. Water depths were deepest in the
eastern portion of WCA3 roughly following the L67 canal from the Miami Canal to Tamiami
Trail (Table 4.4, Figure 4.24), regardless of season. In general, WCA2 was inundated during both
the wet and dry sampling seasons in 1995 and 1996. The western portion of WCA3 and the
southern portion of ENP were dry during the 1995 and 1996 dry seasons. As previously stated,
1995 was an above average precipitation year with maximum depths of 1.8 m (6 feet) in the
eastern portion of WCA3. Almost all of the study area had water depths of at least 0.3 m (1 foot)
(Figure 4.24) during the wet season in 1995. During the wet season in 1996, the western edge of
the study area and the southern area in ENP had water depths less than 0.3 m (1 foot). The dry
season in 1995 also was wetter than usual, with the water depths similar to those observed during
the wet season in 1996 (Figure 4.24).
Hydroperiod can be inferred from the change in water depths between the wet and dry
seasons. The long hydroperiod areas are located in the eastern portion of WCA2 and WCA3,
paralleling the L67 canal in WCA3, and extending down Shark River Slough in ENP
(Figure 4.24). These areas did not dry between the wet and dry seasons and contained water
continuously throughout the study period. During the 1996 dry season, water depths in Shark
River Slough in ENP did decrease to less than 0.3 m (1 foot), but the slough did not become dry.
4-7
-------
The maximum water depths throughout the marsh reached only to 0.6 m (2 feet) during this May
1996 dry season. During both wet season sampling events the entire system was covered with
surface water. In April 1995 and May 1996 (i.e., dry season sampling events) 16% and 29%,
respectively, of the marsh was dry and exposed.
Table 4.4 Median values for selected constituents in marsh.
Area
Season
Depth
(m)
Temp.
<°C)
Cond.
(^mhos/cm)
DO
mg/L)
Turb.
(NTU)
pH
(su)
n
Median
(CO*
n
Median
(CO
it
Median
(CI)
n
Median
(CI)
n
Median
(CI)
tt
Median
(CI)
LNWR
Wet
21
0.518
(±0.06)
21
29.4
(±0.7)
21
69.0
(±76.4)
21
5.9
(±1.1)
21
1.6
(±0.6)
21
6.54
(±0.03)
Dry
20
0.29
(±0.07)
20
26.7
(±1.0)
20
161.5
(±56.3)
20
3.0
(±0.88)
20
10.3
(±5.0)
20
6.26
(±0.19)
WCA2
Wet
22
0.73
(±0.23)
22
29.4
(±1.1)
22
684
(±112)
22
3.5
(±0.7)
22
0.8
(±0.3)
22
7.125
(±0.13)
Dry
20
0.305
(±0.12)
19
26.6
(±1.3)
19
935
(±108)
19
4.5
(±0.8)
19
1.2
(±1.3)
19
7.37
(±0.13)
WCA3
Wet
90
0.762
(±0.06)
89
29.9
(±0.6)
90
416
(±40.8)
90
4.5
(±0.5)
90
0.7
(±0.1)
90
7.29
(±0.06)
Dry
91
0.396
(±0.06)
84
25.7
(±0.5)
84
576.5
(±43.3)
84
3.6
(±0.5)
84
1.9
(±0.7)
84
7.29
(±0.06)
ENP
Wet
75
0.396
(±0.06)
75
30.5
(±0.6)
75
350
(±29.4)
74
7.3
(±0.8)
75
0.7
(±0.1)
75
7.63
(±0.08)
Dry
78
0.152
(±0.05)
56
26.3
(±0.9)
56
578.5
(±38.6)
56
5.9
(±1.0)
57
2.4
(±13)
56
7.425
(±0.12)
BCNP
Wet
24
0.198
(±0.10)
24
29.1
(±1.2)
24
228.5
(±30.5)
24
5.6
(±1.8)
24
1.0
(±0.2)
24
7.345
(±0.17)
Dry
26
0.3
(±0.04)
13
27.3
(±2.0)
13
375
(±45.6)
13
5.4
(±1.7)
14
2.8
(±2.4)
13
7.61
(±0.15)
* CI-95% confidence on median = 1.58 25/o) ^gpgg 1996)
>fn
4.3.2 Conductivity and General Flow Paths
Water conductivity is useful for understanding the source of the water and its flow path.
Precipitation in the Everglades region has a very low ionic content, with the specific conductivity
4-8
-------
of volume-weighted annual precipitation as low as 12 //mhos/cm. The flow patterns across the
marsh are illustrated by the water conductivity isolines (Figure 4.25). Very low conductivity was
observed in the interior of LNWR and the western portions of WCA3A and BCNP indicating
that these portions of the system are largely rainfall-driven. High conductivity water is
transported downstream by canals draining the EAA and can be used to indicate surface water
flow patterns across the marsh system (Figure 4.25, Table 4.4). There is a progressive decrease in
conductivity from WCA2 through WCA3 to ENP regardless of the season (Table 4.4).
Conductivity in WCA2B is also high, but consistent with the surrounding area. WCA2B is
generally considered to be a rain-driven system. Water typically flows from the EAA through
canals on the eastern side of the Everglades ecosystem through WCA2 and the eastern part of
WCA3 into ENP and Florida Bay. This general flow path is observed during the wet season and
the dry season (Figure 4.25, Table 4.4.). Marsh conductivity is higher during the dry season
(Figure 4.25, Table 4.4), while canal conductivity within the EAA peaks during the wet season
(Table 4.3). The dry season marsh patterns indicate significant (P< 0.05) increases in
conductivity due to diminished dilution by precipitation, the drying of large areas of the marsh
and resulting evapoconcentration, and the greater influence of canal water as the marsh flow
pattern becomes restricted to the central flowway. The observed gradient is consistent with that
reported throughout the system by Mattraw et al. (1987) and McPherson et al. (1976), and
reported in canals near ENP by Flora and Rosendahl (1982b). Waller (1982) documented
changes in ionic content and conductivity observed in ENP from 1959 to 1997 due to water
management and canal water influence. The origin of the higher ionic content of EAA discharge
water may be due to the influence of highly mineralized groundwater (Miller 1988), leaking of
highly weatherable materials from oxidizing soils, and agricultural amendments.
4.3.3 Temperature
Water temperatures in the marsh were significantly warmer (P< 0.05) during the summer
wet season than during the winter dry season (Table 4.4, Figure 4.26). Average summer water
temperatures were about 3° to 4° C warmer than the winter water temperatures throughout the
marsh. In general, there was an inverse relationship between water depth and water temperature
4-9
-------
with the shallower areas having warmer water temperatures and the deeper areas having cooler
water temperatures, particularly during the dry season in both 1995 and 1996. Because almost all
biological and chemical rates are temperature dependent, high reaction and metabolic rates would
be expected throughout the year with the highest rates during the wet summer months.
4.3.4 Dissolved Oxygen
DO concentrations were usually greater than 2 mg/L throughout the South Florida
Everglades ecosystem with median DO concentrations ranging from 3 mg/L (38% saturation) in
LNWR during the dry season to over 7 mg/L (96% saturation) in ENP during the wet season
(Table 4.4, Figure 4.27). About 10% of the total area of the marsh was hypoxic, (i.e.,
DO <2 mg/L) while over 45% of the marsh had DO concentrations less than 5 mg/L. The
hypoxic areas were not as extensive during the 1995 above normal precipitation year compared
with the 1996 year.
Previous investigators have found that DO in ENP wet prairies and slough communities
exhibits a strong diel cycle, with concentration at a particular location ranging from around
0 mg/L in early morning to 12 mg/L in late afternoon. (McCormick et al. 1997). In contrast,
oxygen levels at nutrient rich locations within WCA2A have been shown to often be
undetectable and rarely exceed 2 mg/L. Excessive nutrient enrichment is also associated with
reduced periphyton productivity, changed water column community metabolism toward
heterotrophy, and protracted periods of oxygen depletion (Belanger et al. 1989, McCormick et al.
1997). McCormick et al. (1997) noted that although wetland plant and animal species are well
adapted to the natural diel cycle of anoxia that often characterizes pristine marsh ecosystems, it is
improbable that many native Everglades fish species are tolerant of prolonged oxygen depletion
(e.g., less than 2 mg/L) in the water column. There are some fish species that are surface gulpers
of oxygen (air), which could give them a competitive advantage over fish species less tolerant to
low DO.
4-10
-------
4.3.5 Turbidity
Turbidity and water depth were generally inversely related (Table 4.4). As water depth
increased, turbidity decreased. The 1995 dry season water depths were greater than the 1996
water depths, and correspondingly, turbidity values in the 1995 dry season were significantly less
than in the 1996 dry season (P< 0.05). Turbidity was noticeably lower throughout the Everglades
ecosystem during the wet seasons compared to dry season median values (Figure 4.28). Turbidity
was typically low, throughout the marsh, with the exception of LNWR during the dry season
(Table 4.4). The reason for this elevated turbidity is unknown.
Some of the elevated turbidity at the shallow water sites might have occurred because of
the very shallow water depths. There might have been disturbance from sampling very shallow
waters, where the sampler intake was very close to the bottom and disturbed very fine particle
size sediment. Deeper water sites had turbidity values less than 1 NTU.
4.3.6 pH
The pH of the Everglades marsh system is circumneutral with median values ranging
from 6.3 to 7.6 su. LNWR was slightly acidic with a median pH value of 6.5 while the remainder
of the marsh was slightly alkaline with median pH values between 7.1 and 7.6 (Table 4.4,
Figure 4.29). Acidic conditions in LNWR result from the thickness of the peat soil in this
subarea, which isolates lower pH rain water from the underlying limestone bedrock (Newman
et al. 1997, Richardson et al. 1990).
4.4 Synthesis
Canal and marsh sampling both occurred during a period when precipitation and water
depth were above normal. The last marsh sampling cycle (September 1996) occurred during a
period approaching average seasonal precipitation. Water depths during the sampling period were
significantly higher than normal. Most of the marsh was flooded, even during the first dry season
sampling cycle (April 1995). Recurrence intervals for flooding at selected marsh sites indicated
that higher water levels would be expected at these sites less than 20% of the time.
4-11
-------
Specific conductivity patterns provide an indication of the contribution of the EAA to the
downstream system in both the canal and the marsh and also provides an indication of the flow
path of water from north to south through the marsh. The change in specific conductivity values
indicates the importance of precipitation not only in the water balance, but also in constituent
loading to the South Florida Everglades ecosystems. Water temperatures that are consistently
greater than 25°C in both the canal and the marsh indicate that because reaction rates are
temperature dependent, biogeochemcial reaction rates in the warm tropical Florida systems might
be expected to be relatively rapid in temperate systems. Temperature and DO profiles also
indicate the canal bottom waters stratify and become anoxic. DO concentrations typically are low
in both the marsh and canal, in part, because of higher temperatures and therefore, lower
saturation of DO in water. Almost 90% of the canal miles had DO concentrations less than the
Class III Florida water quality standard of 5 mg/L during the sampling period while less than
50% of the marsh area had DO concentrations that were less than the water quality standard.
Turbidity was typically low in both canal and marsh samples. Both the canal and the marsh
systems had circumneutral pH, although the LNWR had lower pH values, consistent with a bog
ecosystem.
4-12
-------
LONGITUDE, decimal degrees
Figure 4.1 Location of precipitation stations from which period of record data were collected
to establish long-term norm and baseline period precipitation conditions.
4-13
-------
MONTHLY PRECIPITATION AT S5A
OBSERVED DATA AND MONTHLY NORMALS
50
NORMAL
MARSH AND CANAL SAMPLING
1994
1995
1996
Figure 4.2 Comparison of monthly precipitation during the 5-year study period to normal
monthly precipitation over the period of record at precipitation Station S5A, with
marsh and canal sampling periods indicated.
50
MONTHLY PRECIPITATION AT S6
OBSERVED DATA AND MONTHLY NORMALS
40 .
E
o
~
NORMAL
OBSERVED
MARSH AND CANAL SAMPLING
1992
1993
1994
1995
1996
Figure 4.3 Comparison of monthly precipitation during the 5-year study period to normal
monthly precipitation over the period of record at precipitation Station S6, with
marsh and canal sampling periods indicated.
4-14
-------
MONTHLY PRECIPITATION AT BELLE GLADE
OBSERVED DATA AND MONTHLY NORMALS
J M
N J M M J
FAJAODFAJAODFAJAODFAJAODFAJAOD
1992 1993 1994 1995 1996
Figure 4.4 Comparison of monthly precipitation during the 5-year study period to normal
monthly precipitation over the period of record at Belle Glade precipitation station
with marsh and canal sampling periods indicated.
MONTHLY PRECIPITATION AT ROYAL PALM
OBSERVED DATA AND MONTHLY NORMALS
60
50 4-
E"
o40 -I-
t—
<
Q.
5 30 4-
UJ
CC
CL
>
x20 - -
t-
2
o
10
~
NORMAL
OBSERVED
MARSH AND CANAL SAMPLING
Figure 4.5
JMMJ SNJMMJ SNJMMJ SN JVM J SN JMMJ SN
FAJAODFAJAODFAJAODFAJAODFAJAOD
1992 1993 1994 1995 1996
Comparison of monthly precipitation during the 5-year study period to normal
monthly precipitation over the period of record at Royal Palm precipitation
station, with marsh and canal sampling periods indicated.
4-15
-------
MONTHLY PRECIPITATION AT DEVILS GARDEN
OBSERVED DATA AND MONTHLY NORMALS
50
NORMAL
OBSERVED
MARSH AND CANAL SAMPLING
J MM J S N J M M J S N 'j' M V J S N Y M W "J S N' 'j' V 'M 'J' S N
FAJAODFAJAODFAJAODFAJAODFAJAOD
1992 1993 1994 1995 1996
Figure 4.6 Comparison of monthly precipitation during the 5-year study period to normal
monthly precipitation over the period of record at Devil's Garden precipitation
station, with marsh and canal sampling periods indicated.
MONTHLY PRECIPITATION AT S39
OBSERVED DATA AND MONTHLY NORMALS
50
NORMAL
MARSH AND CANAL SAMPLING
FAJAODFAJAODFAJAODFAJAODFAJAOD
1992 1993 1994 1995 1996
Figure 4.7 Comparison of monthly precipitation during the 5-year study period to normal
monthly precipitation over the period of record at precipitation Station S39, with
marsh and canal sampling periods indicated.
4-16
-------
50
E40
o
o
< 30
H
Q.
O
11)
tr
20
>
MONTHLY PRECIPITATION AT TAMIAMI TRAIL
OBSERVED DATA AND MONTHLY NORMALS
~
NORMAL
OBSERVED
MARSH AND CANAL SAMPLING
A A
j'm m 'j' s' 'n' 'j'm w j' 's' n' 'j' vr m j s1 n' 'j' vr vr j s V j m m j s W
FAJAODFAJAODFAJAODFAJAODFAJAOD
1992 1993 1994 1995 1996
Figure 4.8 Comparison of monthly precipitation during the 5-year study period to normal
monthly precipitation over the period of record at Tamiami Trail precipitation
station, with marsh and canal sampling periods indicated.
MONTHLY PRECIPITATION AT S9
OBSERVED DATA AND MONTHLY NORMALS
J' M M J S N J M M J S N J M M J S N J M M J S N J' NT W 'J 'S 'N'
FAJAODFAJAODFAJAODFAJAODFAJAOD
1992 1993 1994 1995 1996
Figure 4.9 Comparison of monthly precipitation during the 5-year study period to normal
monthly precipitation over the period of record at precipitation Station S9, with
marsh and canal sampling periods indicated.
4-17
-------
50
40 ..
z
O
< 30 ..
MONTHLY PRECIPITATION AT S8
OBSERVED DATA AND MONTHLY NORMALS
NORMAL
MARSH AND CANAL SAMPLING
OBSERVED
FAJAODFAJAODFAJAODFAJAODFAJAOD
1992 1993 1994 1995 1996
Figure 4.10 Comparison of monthly precipitation during the 5-year study period to normal
monthly precipitation over the period of record at precipitation Station S8, with
marsh and canal sampling periods indicated.
4-18
-------
Structure S5
Structure S6
150
100
50
0
93
i r
94
95 96
Year
Structure S7
~i r
Structure SI 2D
III
97
150
100
50
0
93
_o
u.
~i r
94 95
Year
urn
96 97
Structure S8
96 97
Figure 4.11 Daily discharge through selected SFWMD structures during the study period.
4-19
-------
Canal Data
CONFIDENCE
ON MEDIAN
O > 75V. ~ 3 MID RANGE
* > 75% ~ I 5 MIDRANGE
75V. ~ 1 5 MIDRANGE
75%
> MIDRANGE
25%
L 25% - I 5 MIDRANGE
EAA
WCA
ENP
BCNP
ja
a
Q 4
a
2 -
EAA
WCA
ENP
BCNP
EAA WCA ENP BCNP
Figure 4.12 Notched box and whisker plots comparing water depths in canals by subareas with
all of the sampling data, and data grouped into dry and wet season measurements.
4-20
-------
Canal Data
0> 75% ~ 3 MID RANGE
~ > 75V. ~ I 5 MIDRANGE
75V. ~ I 5 MIDRANGE
75%
> MIDRANGE
25V.
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Figure 4.13 Notched box and whisker plots comparing canal surface water temperature in
subareas during dry and wet seasons.
4-21
-------
0>75V. + 3 MIDRANGE
* > 75V. » I 5 MIDRANGE
T
Canal Data onmewanL
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75% ~ I 5 MIDRANGE
75V.
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CONFIDENCE < > < MEDIAN > MIDRANGE
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Figure 4.14 Notched box and whisker plots comparing canal bottom water temperature in
subareas during dry and wet seasons.
4-22
-------
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LONGITUDE, decimal degrees
Figure 4.15 Canal conductivity reflects dilution of EAA discharge by precipitation.
4-23
-------
0> 75% ~ 3 MID RANGE
~ > 75% ~ I 5 MIDRANGE
T 75% ~ I 5 MIDRANGC
75%
Canal Data
EAA
WCA
ENP
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Figure 4.16 Notched box and whisker plots comparing canal conductivity in subareas during dry
and wet seasons.
4-24
-------
0> 75% ~ 3 MID RANGE
* > 75 V# * I 5MIDRANGC
75V, < I 5 MLDRANGH
75V.
Canal Data
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ENP BCNP
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WCA
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BCNP
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ENP
BCNP
Figure 4.17 Notched box and whisker plots comparing canal bottom DO in subareas during dry
and wet seasons.
4-25
-------
Canal Data~B^
0> 75V, ~ ) MIDRANGE
* > 75% ~ | 5 MIDRANGE
75% ¦» I 5 MIDRANGE
75V.
MEDIAN ) MIDRANGE
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WCA
ENP
BCNP
Figure 4.18 Notched box and whisker plots comparing canal surface DO in subareas during dry
and wet seasons.
4-26
-------
Canal Data
ti'4
CONFIDENCE <
ON MEDIAN I
3
H
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10 -
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Canal Data
3
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BCNP
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WCA BCNP ENP
10
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2 -
EAA WCA BCNP ENP
Figure 4.20 Plots of the medians of the canal turbidity measurements for each of the subareas
with a vertical line indicating the 95% confidence interval about each median.
4-28
-------
Canal Data
CONFIDENCE
ON MEDIAN
0> 7SV. + 3 MIDRANGE
* > 75V. -» 1 5 MIDRANGE
75% * I 5 MrDRANGE
75V.
MEDIAN > MIDRANGE
25V. ¦ I 5 MIDRANGE
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7 -
EAA
WCA
ENP
BCNP
X
a.
7 -
EAA
WCA
ENP
BCNP
X
a.
EAA WCA ENP BCNP
Figure 4.21 Notched box and whisker plots comparing canal pH measurements in subareas
during dry and wet seasons.
4-29
-------
26.6-
-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 4.22 Locations of SFWMD water depth gaging stations used for exceedance frequency
analysis.
4-30
-------
100
#
TJ
4)
T3
O
V
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K
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= 40
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POR = 6/71 to 1/98 J
0 1
Water Depth, m
'
' 3A-28
-
\ POR = 4/53 to 1/94 _
-
J
\ 1
1
0 1 2
Water Depth, m
P-33
_
\ POR = 10/52 to 11/87 _
-
1
-1
Dry Season
® April 1995
n May 1996
o l
Water Depth, m
Wet Season
A September 1995
x September 1996
Figure 4.23 Exceedance frequency curves for SFWMD gaging stations with water depths
measured during each of the sampling cycles at nearby marsh sampling sites.
Frequency curves are based on daily period of record (POR) noted.
4-31
-------
WATER DEPTH IN METERS
26.4-
25.6-
-81.0 -80.8 -80.6 -80.4 -81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 4.24 Kriged surface showing water depths in marsh during each sampling cycle.
4-32
-------
CONDUCTIVITY IN WATER
26.6-
26.4-
-81.0 -80.8 -80.6 -80.4
-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 4.25 Kriged surface showing marsh water conductivity illustrates flow patterns during
each of the sampling cycles.
4-33
-------
Marsh Data
CONFIDENCE
ON MEDIAN
O > 75V. + 3 MIDRANGE
* > 75% + I 5 MIDRANGE
75*/. + I 5 MIDRANGE
75%
> MIDRANGE
25%
J- 25% - I 5 MIDRANGE
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ENP
BCNP
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LNWR WCA2 WCA3 ENP BCNP
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in
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a
B
£
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35
30
25
20
15
LNWR WCA2 WCA3 ENP BCNP
Figure 4.26 Notched box and whisker plots comparing marsh water temperature in subareas
during dry and wet seasons.
4-34
-------
Marsh Data
95%
CONFIDENCE
ON MEDIAN
0> 75% 4 3 MIDRANGE
* > 75% ~ I 5 MIDRANGE
t 75% + 1 5 MIDRANGE
J • 75%
25%
25% ¦ I 5 MIDRANGE
IS
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to
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WCA3
ENP
BCNP
15
10
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a
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>>
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2 s
Dry Season's
*
it
i
k
+
* .
K
O
-a
u
>
o
LNWR WCA2 WCA3 ENP BCNP
Figure 4.27 Notched box and whisker plots comparing marsh DO in subareas during dry and
wet seasons.
4-35
-------
0> 75V. + 3 MIDRANGE
* > 75% ~ I S MIDRANGE
r 75% ~ I 5 MIDRANGE
75%
Marsh Data
95%
CONFIDENCE
ON MEDIAN
MEDIAN > MIDRANGE
25%
25% - I S MIDRANGE
3
H
z
y>
IS
U
3
H
1000
100 -
10
LNWR WCA2 WCA3 ENP BCNP
P
H
z
;o
15
i-
a
H
1000
100
10
100
H 10
z
•o
IE
3
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LNWR WCA2
WCA3
ENP
BCNP
Wet Season's
*
i
t
r *
- ^
i
e
t
1
*
*
*
i
LNWR WCA2 WCA3 ENP BCNP
Figure 4.28 Notched box and whisker plots comparing marsh turbidity in subareas during dry
and wet seasons.
4-36
-------
Marsh Data
CONFIDENCE
ON MEDIAN
0> 75*/. + 3 MIDRANGE
* > 75V. 4 | 5 MIDRANGE
t 75% ~ | 5 MIDRANGE
J 75%
MEDIAN
> MIDRANGE
25%
J- 25% - I 5 MIDRANGE
All E^ata
X
o.
S
I
a
s &
LNWR WCA2 WCA.3 ENP BCNP
X
a.
7 -
LNWR WCA2 WCA3
ENP
BCNP
X
Cl.
7 -
6 -
LNWR WCA2 WCA3 ENP BCNP
Figure 4.29 Notched box and whisker plots comparing marsh pH in subareas during dry and
seasons.
4-37
-------
5.0 HABITAT
5.1 Introduction
The Florida Everglades ecosystem is one of the largest freshwater wetland complexes in
the US. This wetland complex, which extends from Lake Okeechobee south to Florida Bay, west
to BCNP, and east to the coastal ridge (Gunderson 1994), has been studied intensively, resulting
in an extensive literature base on the flora of the Everglades. Everglades plant community
associations, spatial and temporal distribution of plant communities, and natural or
anthropomorphic factors influencing these distributions have been studied, as well as factors
contributing to and accelerating changes in plant community distributions and composition. For
example, Gunderson and Loftus (1993), Olmsted and Loope (1984), Craighead (1971), Loveless
(1959), Robertson (1953), Davis (1943), and others provide accounts of historical and current
vegetative characteristics of the Everglades. Recent vegetation classification maps have been
published for LNWR (Richardson et al. 1990), WCA2A (Jensen et al. 1995, Rutchey and
Vilcheck 1994), and Shark River Slough (Gunderson et al. 1986). Gunderson (1994), Bodle et al.
(1994), and Davis (1994) provide overviews and syntheses of factors affecting change in this
ecosystem.
The natural mosaic of plant community types in the Everglades provides a diverse array
of habitats for wildlife, including many threatened and endangered species. Wet prairies and
open water areas void of dense emergent macrophytes serve as preferred wading bird foraging
habitat (Hoffman et al. 1994). Fleming et al. (1994) note the importance of habitat heterogeneity
to Everglades wood stork populations.
Changes in plant community composition, structure, and spatial distributions as a result
of ecosystem stressors can lead to changes in animal populations, communities, and wildlife
species diversity. For example, changes in the plant community composition, structure, and
spatial distributions are hypothesized to be important factors in the potential bioavailability and
bioaccumulation of MeHg in fish and wading birds in the marsh (see Chapter 8.0 for further
discussion). A consistent characterization of plant community attributes concomitant with the
characterization of other indicators of ecosystem stressors or conditions, however, has not been
5-1
-------
conducted to date on an ecosystem scale in the Everglades. A preliminary characterization of the
plant communities at the marsh sampling stations, therefore, was conducted as part of the
Everglades ecosystem assessment project.
Data were collected on the dominant and secondary plant communities present at the
marsh sampling sites to provide an initial characterization of habitats within the marsh. Using a
simplified vegetation classification scheme based on dominant species, Everglades marsh habitat
was qualitatively grouped into six broad dominance classes: (1) wet prairie, (2) sawgrass marsh,
(3) cattail marsh, (4) cypress, (5) Muhlenbergia prairie, and (6) mangroves. The habitat classes
were further divided into nine secondary plant community classes: (1) wet prairie, (2) sawgrass
marsh, (3) cattail marsh, (4) cypress, (5) Muhlenbergia prairie, (6) mangroves, (7) willow (Salix
sp.), (8) Melaleuca (Melaleuca quinquenervia), and (9) pine. The field crew selected the
dominant and secondary vegetation community type based on field observations and recorded
these observations on field sheets. In addition, three 35 mm color slides were taken at each marsh
sampling location as described in Chapter 3.0. Dominant and secondary communities recorded
from 35 mm color slides were compared to field sheets to verify consistency in community
characterization between sampling crews. In addition, the presence or absence of cattail (Typha
spp.), an opportunistic species that outcompetes the more slowly growing species adapted to the
low nutrient environment of the unimpacted Everglades (Davis 1994), was recorded from the
slides.
Attached and floating periphyton mats are common in Everglades habitats, particularly in
wet prairies and deeper slough areas. These biological communities have been shown to serve
multiple functions. Periphyton productivity oxygenates the water column (Belanger et al. 1989,
McCormick et al. 1997). Everglades periphyton also influence calcium carbonate deposition and
nutrient cycling in the marsh (Swift and Nicholas 1987), and serve as a food web base (Browder
et al. 1994). Recent studies by Cleckner et al. (Personal communication) also demonstrate that
floating periphyton mats can be sites for Hg methylation in the Everglades ecosystem. Slight
increases in nutrient concentrations, particularly phosphorus can cause changes to the periphyton
assemblage, including species composition and biomass (Raschke 1993, McCormick et al. 1997).
The presence or absence of floating periphyton mats, which are a sensitive indicator of marsh
5-2
-------
ecosystem status (Raschke 1993, MeCormick et al. 1997), was noted on field sheets and also
recorded from photographs taken at each sampling station.
The preliminary habitat data (i.e., plant community, cattail presence, floating periphyton
mat presence) were evaluated using various descriptive statistics and spatial presentations to
identify patterns in plant community distributions, species occurrences, and the potential
relationships among these patterns within the Everglades marsh ecosystem.
5.2 Results
5.2.1 Spatial Distribution of Dominant Plant Communities
Figure 5.1 provides a histogram showing the number of marsh sampling locations within
each dominant vegetation class. Out of the six dominant plant community classes, sawgrass
marsh and wet prairies were recorded most often as the dominant plant community class at the
sampling locations. Subsequent data analyses, therefore, focused on these predominant marsh
habitat types. Scatter plot diagrams of sawgrass dominated plant communities, wet prairie
dominated plant communities, and the presence of cattails and floating periphyton mats along a
north to south latitudinal gradient are shown in Figure 5.2. The dominant plant community
classes and the presence of cattails and floating periphyton are not equally distributed across a
north to south latitudinal gradient in the Everglades. Further examination of the distribution of
vegetation classes on a finer scale (Figure 5.3) shows that changes in plant community
composition in the marsh occur over 6 broad latitudinal subdivisions, which are enumerated as
follows: (1) LNWR composed of LNWR, northern WCA2A, Holeyland, and Rotenberger tract;
(2) Alligator Alley north (AA-N) composed of the area north of Alligator Alley to LNWR and
including most of WCA2A, WCA2B, and northern portions of WCA3 and BCNP; (3) central
WCA3 (WCA3-C) composed of the central third of WCA3 and BCNP; (4) southern WCA3
(WCA3-S) composed of the southern third of WCA3 and BCNP; (5) northern ENP (ENP-N)
composed of the northern half of ENP; and (6) southern ENP (ENP-S) composed of the southern
freshwater half of ENP (Figure 5.4). Figures 5.3 and 5.5 show that wet prairie is the dominant
plant community class in latitudinal subdivision LNWR with sawgrass as the secondary
dominant plant community type. Few cattails or floating periphyton mats were recorded from
5-3
-------
sampling stations found in this subdivision (Figures 5.6 and 5.7). Figure 5.6 shows that where
cattails are present in LNWR, they are located on the exterior of LNWR near the canals.
A shift in the dominant plant community class occurs in latitudinal subdivision north of
Alligator Alley, where sawgrass replaces wet prairie as the dominant plant community class
(Figures 5.3 and 5.8). Approximately 58% of the total marsh area sampled in this latitudinal
subdivision is dominated by sawgrass and approximately 14% of the marsh area sampled is
dominated by wet prairie (Table 5.1). In comparison, 39% of the marsh area sampled is
dominated by sawgrass and 51 % of the area sampled is dominated by wet prairie in the LNWR
latitudinal subdivision (Table 5.1).
Preliminary observations of the sawgrass dominated community in the latitudinal
subdivision north of Alligator Alley also revealed that the sawgrass vegetation in this latitude is
more robust in its overall growth as represented by observed height and density. Turner et al.
(1995) documented macrophyte heights of over 4 m (13 ft) in WCA3A compared to about 1 to
3 m (3.5 to 10 ft) in ENP.
In central and southern WCA3 and in the northern portion of ENP, there is a shift back to
wet prairie as the dominant plant community (Figures 5.3 and 5.5). In these areas, the percentage
of marsh area sampled that is dominated by wet prairie ranges from 43% to 57%. In contrast, the
percent marsh area sampled that is dominated by sawgrass in these same areas ranges from 29%
to 41% (Table 5.1). In the southern portion of ENP, however, the dominant plant community
again shifts to sawgrass dominated marsh (Figure 5.3) with 52% of the total marsh area in the
southern portion of ENP dominated by sawgrass compared to 29% dominated by wet prairie
(Table 5.1).
5.2.2 Presence and Distribution of Cattails and Floating Periphyton Mats
Figures 5.2, 5.3, and 5.6 show that there is a distinct spatial distribution of cattails within
the Everglades marsh communities. Cattails are present within the marsh more frequently north
of Alligator Alley than in any other subarea. Figure 5.6 also shows that in the WCA3-C the
presence of cattails within the marsh community is concentrated near the L67 canal. Cattails are
also common in the Holeyland and WCA2A.
5-4
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Table 5.1 Proportion of marsh habitat sampled dominated by the major plant community
classes within the six latitudinal subdivision along a north to south gradient.
Proportion represents the proportion of marsh area sampled within each latitudinal
subdivision.
Dominant Plant Community Class
Area
km2
Proportion
%
LNWR
Wet Prairie
424
51%
Sawgrass
331
39%
Cypress
0
0%
Cattail
79
10%
North of Alligator Alley (AA-N)
Wet Prairie
212
14%
Sawgrass
887
58%
Cypress
199
13%
Cattail
146
10%
Central WCA3 (WCA3-C)
Wet Prairie
715
43%
Sawgrass
503
30%
Cypress
437
26%
Cattail
0
0%
Southern WCA3 (WCA3-S)
Wet Prairie
755
52%
Sawgrass
410
29%
Cypress
172
12%
Cattail
13
10%
Northern ENP (ENP-N)
Wet Prairie
688
57%
Sawgrass
503
41%
Cypress
0
0%
Cattail
26
2%
Southern ENP (ENP-S)
Wet Prairie
318
29%
Sawgrass
569
52%
Cypress
13
1%
Muhlenbergia
146
13%
Cattail
26
2%
Mangrove
13
1%
5-5
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Figure 5.7 shows the distribution of the presence of floating periphyton mats in the
Everglades marsh. Preliminary observations on the periphyton community in LNWR, indicate
that the periphyton community is distinctly different in species composition than the rest of the
Everglades (Browder et al. 1994). These preliminary observations suggest that the periphyton
community in LNWR has developed in response to a different set of controlling variables or
factors (e.g., water pH, conductivity, hydrologic source, temporal patterns in hydrology, etc.) than
found elsewhere in the Everglades. Swift and Nicholas (1987) documented different periphyton
characteristics in LNWR attributed to water chemistry. Figure 5.3, which provides the percent
frequency of occurrence of floating periphyton mats within each of the six latitudinal
subdivisions, shows that floating periphyton mats are present most frequently in southern and
central WCA3 and northern ENP. The presence of floating periphyton within the marsh is lowest
in LNWR and north of Alligator Alley.
Table 5.2 summarizes the percent of the total marsh area sampled where cattails and
floating periphyton mats are present within each of the six latitudinal divisions in the Everglades.
The percent of the marsh area sampled where cattails are present is highest in the Alligator Alley
north (i.e., 21% of the total marsh area sampled) and LNWR (i.e., 16% of the total marsh area
sampled). In contrast, the percent of the total marsh area where periphyton mats are present is
lowest in the latitudinal subdivision LNWR (i.e., 16%), increases along a north to south
latitudinal gradient, and is highest in southern WCA3 and the northern ENP (i.e., 64% and 77%,
respectively). Similar patterns are observed for floating periphyton along a latitudinal gradient
from north to south in the marsh (Figure 5.3 and 5.7).
5.3 Synthesis
Several patterns in the spatial distribution of plant communities and habitat types within
the Everglades emerge from the preliminary data collected at the Everglades marsh sampling
locations. Most noticeable are (1) that the dominant plant community classes are not equally
distributed across the Everglades, (2) there are shifts in sawgrass and wet prairie dominant plant
communities over 6 latitudinal subdivisions (Figure 5.3), (3) the presence of cattails and cattail
dominant communities north of Alligator Alley near the EAA (Figure 5.6), and (4) the presence
5-6
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Table 5.2 Proportion of marsh area sampled in each latitudinal subdivision where cattail
(Typha domingensis) and floating periphyton mats were present.
Presence of Cattails and Floating
Periphyton Mat
Area
km2
Proportion
%
LNWR
Cattail
132
16%
Floating periphyton mat
132
16%
North of Alligator Alley (AA-N)
Cattail
318
21%
Floating periphyton mat
331
22%
Central WCA3 (WCA3-C)
Cattail
93
6%
Floating periphyton mat
807
49%
Southern WCA3 (WCA3-S)
Cattail
79
6%
Floating periphyton mat
914
64%
Northern ENP (ENP-N)
Cattail
40
3%
Floating periphyton mat
940
77%
Southern ENP (ENP-S)
Cattail
13
1%
Floating periphyton mat
609
56%
of floating periphyton mats in the central and southern portions of WCA3 and in northern ENP
where cattails are largely absent (Figures 5.6 and 5.7).
In general, sawgrass dominant communities and the presence of cattails have the highest
frequency of occurrence north of Alligator Alley, and wet prairie dominant communities and the
presence of floating periphyton mats occur more frequently in the central and southern portions
of WCA3 and in the northern half of ENP. There is a noticeable shift from wet prairie dominant
5-7
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communities in LNWR to either cattail dominant plant communities or sawgrass dominant plant
communities with a high presence of cattails north of Alligator Alley, and a noticeable shift back
to wet prairie dominant communities in the central and southern portions of WCA3 and northern
ENP.
Although data were not collected on the density, height, and aboveground biomass of
marsh vegetation, sawgrass and cattail plants were noticeably taller and appeared to be denser
north of Alligator Alley and in the marsh adjacent to the canals based on field observations.
These observations suggest that where plant species density, height, and aboveground biomass
are high, shading may preclude the development or presence of floating periphyton mats
(Grimshaw et al. 1997). For example, in the central and southern thirds of WCA3 and the
northern half of ENP, where the wet prairie community is dominant and where macrophyte
species density, height, and aboveground biomass appear to be low, the frequency of periphyton
mats is high. These observations are consistent with Browder et al. (1994) who indicates that
epiphytic and floating periphyton mats are an integral component of wet prairie communities and
plant communities of deeper slough areas of the Everglades.
Changes in the composition, structure, and the spatial and temporal distribution of plant
communities within the Everglades are driven by numerous factors, including changes in natural
hydroperiod, salinity, and nutrient concentrations, and natural disturbances such as fire, frosts,
and hurricanes (Gunderson 1994). However, subtle changes in vegetation and habitat within the
Everglades marsh and the subsequent effects of habitat changes on the condition of the
Everglades ecosystem are not well understood. Additional research on factors contributing to
these habitat changes is critical if ecosystem restoration is to succeed. While the focus of the
habitat data collection efforts in the Everglades in this study has been to characterize the habitat
at marsh sampling locations and not to determine the causes of vegetation changes in the
Everglades, Chapter 7.0 discusses some of the relationships between nutrients and community
and species distributions within the Everglades ecosystem based on the available data. Chapter
8.0 further integrates the relationship between habitat, nutrient concentrations, and Hg
concentrations in the Everglades.
5-8
-------
250
200
150
100
50
Plant Community Code
WP = Wet Prairie
SG = Saw Grass
Cat = Cattail
Cyp = Cypress
Muh = Muhlenbergia
Man = Mangrove
tsa ess ^
WP SG Cat Cyp Muh
Dominant Plant Community Code
Man
Figure 5.1 The number of marsh sampling stations occurring within each of the
dominant plant communities.
Marsh Habitats
x Cattail
Dominant
O Wet Prairie
Dominant
^ Sawgrass
Dominant
~ Cattail Present
* Floating
Periphyton
Present
27 27 26 26 25
Latitude
##* ##***
3 (ED i n l (D QD ~
X XOODOtt
u
: o
: <
: H
: i
' s
: E
: £
iTuwnr^rvmi'.^ GGDCnpEDBBD
Figure 5.2 Distribution of plant community classes, cattails and floating periphyton
by latitude.
5-9
-------
I
o
O
o
70
60 -
50
:>» M
o «i
g "a,
40
&> ed
£ 04
« #
> \
¦>-' C/5
.2 » 30
U U
pes a
„ ID
1 20
o
10
0
LNWR AA-N WCA3-C WCA3-S ENP-N ENP-S
Marsh Habitats
~ Cattail Present
o Wet Prairie
Dominant
A Sawgrass
Dominant
* Floating
Periphyton
Present
Figure 5.3 Percent relative frequency of selected plant communities, cattails, and floating periphyton in six broad latitudinal
subdivisions.
-------
MARSH LATITUDINAL DIVISIONS
J I I L
-------
-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 5.5 Marsh sampling sites where wet prairie was classified as the dominant plant
community.
5-12
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26.6-
26.4-
26.2-
%
u
eo
o
TJ
"3
.§ 26.0H
a
v
"O
W
H
<
-J
25.8-
25.6-
25.4-
PRESENCE OF CATTAILS
# = CATTAILS PRESENT
0 =S AMP LING STATION, ALL CYCLES
-81.0
-80.8
-80.6
-80.4
LONGITUDE, decimal degrees
Figure 5.6 Marsh sampling stations where cattails were noted to be present during sampling.
5-13
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26.6-
PRESENCE OF FLOATING
PERIPHYTON MAT
25.6-
25.4-
• •• A r
• I • •
• J
° • 0 n*
# = FLOATING PERIPHYTON PRES
SAMPLING STATION, ALL CYCLES
1
-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 5.7 Marsh sampling stations where floating periphyton mat was present during sampling.
5-14
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SAWGRASS
DOMINANT COMMUNITY
®=DOMLNANCE OF SAWGRASS
o = SAMPLING STATION, ALL CYCLES'
-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 5.8 Marsh sampling stations where sawgrass was classified as the dominant plant
community.
5-15
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6.0 SOILS
6.1 Introduction
A variety of soil types are found in the Everglades study area. Higher elevation rockland
occupies the ridge along the southeastern urban coast, while soils in BCNP to the west are
primarily sandy. The wetland soils of the central Everglades are primarily organic Histosols and
Inceptisols (Gunderson and Loftus 1993). Another major soil type found within Everglades
wetlands is a calcitic mud, commonly referred to as marl. It is commonly found in the shallower
peripheral marshes of the Everglades subjected to shorter periods of surface water inundation
(Jones 1948).
Peat and marl soils are derived in wetland regions from decaying plant matter. Stephens
(1956) reported that the Florida Everglades once contained the largest single body of organic
soils in the world, covering over 8,000 km2 (3,100 mi2). These peats and mucks accumulated to a
thickness of up to 6 meters (17 feet) in what is now EAA (Stephens and Johnson 1951). The
origin and perpetuation of peat and marl soils is greatly dependent upon water depth and
resulting wetland vegetative communities. Soil loss or composition changes due to diminished
surface water inundation may in turn result in altered vegetative communities and subsequent
changes in soil type and depth as this new plant community eventually decomposes into soil.
Soil is an important characteristic of an ecosystem and soil preservation is an important
aspect of ecosystem protection. The South Florida Ecosystem Restoration Task Force has
adopted a series of success indices in order to define restoration goals, track ecosystem status,
and measure restoration effectiveness. The Science Subgroup of the Task Force established
20 indicators and success criteria. Among these is "restoration of the natural balance of organic
soil accretion and subsidence throughout the system (reduce subsidence)" (Science Subgroup
1997). Among the 23 planning objectives adopted by the Florida Governor's Commission for a
Sustainable South Florida for the USACE Central and Southern Florida Re-Study is "restore
more natural organic and marl soil formation processes and stop soil subsidence" (FDCA 1996;
USACE 1994).
6-1
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6.2 Marsh Grid
6.2.1 Soil Thickness and Subsidence
Peat and muck soils are subject to subsidence and surface elevation loss when drained.
Stephens (1984) states that soil subsidence and the resulting loss of surface elevation are due to
six processes: (1) shrinkage due to desiccation; (2) consolidation by loss of the buoyant force of
groundwater; (3) compaction by tillage; (4) wind erosion; (5) burning; and (6) biogeochemical
oxidation. Oxidation and burning are considered the dominant forces, and are irreversible. Early
in the twentieth century the peat soils of the 3,000-square-kilometer (700,000-acre) EAA were
drained to facilitate agricultural production. Stephens (1956) reported that conditions were
conducive for peat formation until 1906, when the first efforts began to cut canals from Lake
Okeechobee through the EAA to the coast. The process of soil accumulation was reversed within
the EAA and subsidence began. It soon became apparent that drainage was contributing to soil
subsidence. The first soil subsidence transects within the agricultural lands were established in
1913. This led to efforts by the US Department of Agriculture and others to understand and
minimize the subsidence of EAA soils. Subsidence within the EAA and efforts to control it on
these agricultural lands are well documented (Clayton et al. 1942, Jones 1948, Stephens and
Johnson 1951, Stephens 1969, Stephens 1984, Glaz 1997).
In contrast, subsidence of peat soils within the protected Everglades is poorly
documented. The only historic images of soil thickness in the Everglades were published by
Davis (1946) and Jones (1948) (Davis image scanned to generate a computer image and
presented as Figure 6.1). They reported peat thickness as ranging from 0 to over 4 m (12 feet).
Subsidence in the Everglades is due largely to changing water management practices during this
century. The major canals draining the EAA extended southeast through the Everglades to the
Atlantic Ocean and were completed by 1917. However, unimpeded surface water flow from the
EAA south through the Everglades to ENP, Florida Bay, and the Gulf of Mexico occurred until
the late 1950s, when levees were constructed forming the southern boundary of the EAA. During
the early 1960s additional levees were completed that partitioned the Everglades into the five
WCAs (Figure 6.2) (Light and Dineen 1994). By this time Everglades surface water conditions,
flow, and inundation periods had been greatly altered.
6-2
-------
A krig of soil thickness documented by the present study at 479 sampling sites during
1995 and 1996 is presented in Figure 6.1. Soil thickness was determined by inserting a metal rod,
marked in tenths of feet, to the point of refusal. The rod could be lengthened by screwing on
additional sections to reach a maximum length of 12 feet. Soil thicknesses throughout the study
area range from 0 to over 4 m (12 feet) (Figures 6.1 and 6.3, Table 6.1). Soil depths greater than
12 feet (about 4 m) in LNWR could not be determined due to the maximum length of the
sampling rod. Davis (1946) reported peat thicknesses in this area in excess of 12 feet. The
deepest soils are the peat deposits within LNWR with a mean soil thickness 2.6 m (8.7 feet).
Mean soil thickness for remaining portions of the study area were 1.3 m (4.3 feet) in WCA2,
0.4 m (1.5 feet) in WCA3A north of Alligator Alley (1-75), 0.8 m (2.8 feet) in WCA3 south of
1-75, 0.4 m (1.3 feet) in ENP, and 0.4 m (1.2 feet) in BCNP. The deepest peat in the Everglades
outside of LNWR is within WCA2 and the southern portion of WCA3, areas which receive
longer surface water inundation.
Table 6.1 Summary statistics for soil parameters by subarea. Mean plus or minus standard
deviation is presented. The number of samples is provided in parenthesis.
Subarea
Soil
Thickness
(m)
Soil
Thickness
(ft)
Bulk Density
(g/cc)
Percent
Organic Matter
Rotenber ger /Holey 1 and
0.9±0.5 (18)
2.9±1.6 (18)
0.21±.06 (15)
76±16 (18)
WCA1
2.6±0.8 (41)*
8.7±2.6 (41)*
0.07±.02 (41)
92±7 (41)
WCA2
1.3±0.4 (42)
4.3±1.5 (42)
0.11 ±.04 (42)
85±6 (42)
WCA3
0.7±0.4 (180)
2.4±1.4 (180)
0.19±.16 (177)
71±23 (180)
WCA3 North of 1-75
0.4±0.3 (52)
1.5±1.1 (52)
0.30±.18 (50)
47±27 (52)
WCA3 South of 1-75
0.8±0.4 (128)
2.8±1.3 (128)
0.15±.12 (127)
77±19 (128)
ENP
0.4±0.3 (152)
1.3±1.0 (152)
0.34±.19 (153)
38±25 (153)
BCNP
0.4±0.3 (46)
1.2±0.9 (46)
0.77±.35 (46)
17±15 (46)
ENTIRE SYSTEM
0.8±0.8 (479)
2.7±2.5 (479)
0.28±.26 (475)
59±31 (480)
soil thickness at some locations within WCA1 exceeded the maximum soil probe length of 12 feet
6-3
-------
Figure 6.4 presents the difference in peat thickness throughout the Everglades as reported
by the present study (1995 to 1996) and Davis (1946). The difference was determined by
subtracting the soil thickness indicated by the 1946 contour map from the 1996 measured soil
thickness at each of the 479 EPA sample stations (Figure 6.1). Davis (1946) reports peat
thickness in 2-foot (0.6-meter) intervals and does not provide raw data. Consequently, soil
thickness differences from 1946 to 1996 are presented as a maximum and minimum, depending
upon whether the high or low threshold value within each 2-foot (0.6-meter) contour interval
from Davis (1946) is used. Calculation of soil loss during the last 50 years indicates that the
portion of WCA3 north of Alligator Alley has lost between 39% and 65% (6.0 x 108 m3) of its
soil. Davis (1946) reports that this area had 3 to 5 feet of peat in 1946, while the present study
found only 1 to 3 feet of soil, with less than 1 foot in some areas. The worst case estimate
indicates that the southeastern part of WCA3 (WCA3B) and the northeast Shark Slough portion
of ENP may have lost up to 0.9 m (3 feet) of soil or a loss of 53% of volume in Northeast Shark
Slough, and a loss of 42% of volume in WCA3B. These three portions of the Everglades all have
been subjected to less surface water inundation since completion of the WCAs about 40 years
ago. Estimates of soil volume change for the Everglades Protection Area during the last 50 years
vary from an average loss of 5.4 x 108 m3 (11% loss in soil volume) to a maximum of 17 x
108 m3 (28% loss in volume).
6.2.2 Percent Organic Matter
A krig of soil percent organic matter for 0 to 10 cm observed during 1995 and 1996 at
480 points within the marsh is presented in Figure 6.5. Percent organic matter at sampling sites
ranged from <1% to 97% (Table 6.1, Figures 6.3 and 6.5). Peat soils are highly organic, while
marl soils and sandy soils are primarily mineral. Highest organic matter was found in the peat
soils within LNWR with a mean of 92 ± 7%. WCA2A, the Rotenberger Tract, and WCA3 south
of 1-75 also had soils exceeding 75% organic matter. These highly organic zones coincide with
the current deeper soil portions of the system. Soils in the ENP, which include the peat soils
within the Shark Slough trough as well as the marl soils of adjacent shorter hydroperiod areas,
had a mean organic content of 38 ±25%. The area of maximum soil loss within WCA3 north of
6-4
-------
1-75 had a mean soil organic matter content of 47%, the lowest within the WCAs. The sandy
soils of BCNP had a mean percent organic matter of 17 ±15%. Portions of ENP outside the
Central Shark Slough trough also had lower organic matter content, often in the 10% to 20%
range.
Table 6.2 Everglades soil volumes by subarea reported for 1946 and 1995 through 1996. The
1946 data are from Davis (1946), and 1995 through 1996 data are from the present
study. Volumes are reported as cubic meters x 108. Note: A minus (-) indicates soil
loss while a plus (+) indicates soil gain.
Subarea
1946
Thickness
(feet)
1946
Volume
1995-1996
Volume
Volume
Minimum
Change (%)
Volume
Maximum
Change (%)
WCA1
7.9±1.9
11-15
14.5
-0.2 (-1%)
+3.0(+23%)
WCA2
4.9±1.4
6.8-10
7.31
+0.53 (+8%)
-2.7 (-27%)
WCA3AN
3.4±1.0
5.2-9.2
3.21
-2.0 (-39%)
-6.0 (-65%)
WCA3AS
3.0±1.5
8.6-16
11.3
+2.7 (+32%)
-4.5 (-28%)
WCA3B
4.8± 1.4
3.4-5.1
2.94
-0.4 (-13%)
-2.1 (-42%)
NESS
2.4±1.7
1.6-3.2
1.49
-0.1 (-0.1%)
-1.7 (-53%)
ENP
0.83±0.65
0.81-4.5
4.02
+3.2 (+400%)
-0.4 (-9%)
TOTAL
3.4±2.5
38-62
44.8
+6.9 (+18%)
-17.7 (-28%)
6.2.3 Bulk Density
A krig of soil bulk density for 0 to 10 cm as sampled in 1995 and 1996 at 475 marsh
points is presented in Figure 6.6. Bulk density ranged from 0.05 to 1.50 g/cc. The highly organic
peat soils of LNWR had the lowest bulk density with a mean 0.07 ±0.02 g/cc as compared to the
mineral soils of BCNP, which had a mean of 0.77 ±0.35 g/cc (Table 6.1, Figure 6.3). Bulk
density in WCA3 north of Alligator Alley had an average of 0.30 g/cc, the highest in the WCAs.
Within the WCAs, this portion of northern WCA3 had the lowest organic matter content, the
highest bulk density, and the greatest soil loss. All of these observations are consistent with
formerly deeper peat soils being subjected to drier conditions due to water management changes
6-5
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over the last 50 years. Surface water inundation has been reduced, soils have subsided, and the
resulting surface soil has become less organic. There was a very strong negative linear correlation
(r2 =0.84) between the logarithm of bulk density and percent organic matter (Figure 6.7). These
bulk densities are consistent with those recently observed in 1992 for WCA3 (Reddy et al. 1994),
those reported for WCA2 (Reddy et al. 1991a), those observed in LNWR in 1991
(0.06 ±0.003 g/cc, Newman et al. 1997), and those observed in the Holeyland (Reddy et al.
1991b). The present study is the first to consistently document bulk density throughout the entire
system.
6.2.4 Soil Redox
Marsh soil Eh was measured with an in situ probe described in Chapter 3.0.
Measurements were made at 2.5-, 5-, 10-, 15-, and 20-centimeter depths. Eh data are presented as
the mean of all five depths at a sample location. A box and whisker plot of the mean reference
corrected Eh is presented by subarea in Figure 6.8. Figure 6.9 shows the average Eh for all
cycles. The only subarea in which the median Eh was found to be less than 100 mV was WCA2.
The presence of an Eh less than 100 mV indicates anoxic or reducing conditions are occurring in
the soils in this subarea. It is also apparent, that while the occurrence of anoxia was exhibited in
each of the other subareas in isolated locations, most of the areas had oxic soil conditions. The
presence of oxic soils throughout most of the Everglades marsh is atypical of most marsh
systems. Most wetland ecosystems have anoxic or reducing soil conditions similar to those found
in WCA2 on at least a seasonal basis (Mitch and Gosselink 1986). Figure 6.10 shows the average
soil Eh for each cycle.
6.3 T ransects
6.3.1 Soil Thickness
Soil thickness along the four April 1994 marsh transects (Figure 2.1) is presented in
Figure 6.11. Soil thickness was highly variable depending upon location. Soil thicknesses
observed in WCA3 and ENP were generally about 0.3 m (1 foot), while soil thickness within
WCA2 was about 1.5 m (5 feet). Soil thickness in LNWR exceeded 7 feet (about 2 m) (the
6-6
-------
maximum depth that could be measured with the field probe used for the April 1994 transect
sampling).
6.3.2 Soil Organic Matter
Soil organic matter observed along marsh transects also varied depending upon location
(Figure 6.12). LNWR had the highest organic matter content (about 90%). ENP had the lowest
soil organic matter observed (about 40%) while WCA2 and WCA3 soils were of intermediate
organic content.
6.3.3 Soil pH
Transect soil pH is presented in Figure 6.13. Soils were of neutral pH with one exception.
The interior soils of WCA1 were acidic with a low pH of 5.8 at several interior sites. A
pronounced pH gradient was observed in this transect with pH increasing approaching the
L7 canal. This gradient may be due to the influence of alkaline water in the L7 canal. This
observation is consistent with that of McPherson (1973).
6.3.4 Soil Redox
Soil Eh observed along the transects during April 1994 is presented in Figure 6.14. A soil
core was collected in a clear polycarbonate corer. Eh measurements were made onsite by
inserting probes into the intact soil core at a soil depth of 5 cm and allowing 15 minutes for
equilibration. The only negative Eh measurements occurred within LNWR at the two stations
closest to the L-7 canal. During the transect sampling Eh measurements were not obtained at the
other likely location of negative Eh, along WCA2A transect at the eutrophic stations immediately
downstream of S-10C, because of an equipment malfunction.
6-7
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25.4-
-80.4
-81.0
LONGITUDE, decimal degrees
Figure 6.1 Comparison of 1946 peat thickness (Davis, 1946) and 1995-1996 soil thickness from the present study.
-------
Everglades Ecosystem:
LOXAHATCHEE
NATIONAL
WILDLIFE REFUGE
(LNWR)
Ft- Lauderdale
Blacayne
Bay
Stcrmwater Treament Area
Figure 6.2 Water conservation areas created in early 1960s: LNWR, WCA-2A, WCA-2B,
WCA-3A, and WCA-3B.
6-9
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150
12.0 -
9.0
H 6.0
o
n
3.0 -
0.0
0> 75V. ~ 3 MIDRANCE
» > 75V. ~ I 5 MIDRANGL
75V. ~ I 5 MIDRANCiC
75V.
M1DRANGE
LNWR
WCA2
WCA3
ENP
BCNP
LNWR
WCA2
WCA3
ENP
BCNP
LNWR
WCA2 WCA3
ENP
BCNP
Figure 6.3 Notched box and whisker plots of marsh soil thickness, bulk density and organic
matter by subarea.
6-10
-------
LONGITUDE, decimal degrees
Figure 6.4 Maximum and minimum difference in peat thickness 1946 to 1996.
-------
SOIL
ORGANIC MATTER
(0-10 cm)
-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 6.5 Percent organic matter observed for all cycles.
6-12
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SOIL
BULK DENSITY
(0-10 cm)
-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 6.6 Bulk density for all cycles.
6-13
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1
1 1 1
R2 = 0839
y^x
X ** -
* x >V T X
" * «1o"<
X *V x X . X "
»
x *. x~ Tr—jl jooi£oo<
-
* x xx xr XKUPCHtyjK —
X X
x «:»KW *
xx !.¦*:
1
x aoMt
1 1 1
20
40 60
Organic Matter. 9
80
100
Figure 6 7 Linear relationship between Log(bulk density) and percent organic matter
>
E
- 500
o o o
U
C -200 1 1 1 1 1
2 LNWR WCA2 WCA3 ENP BCNP
Figure 6.8 Mean corrected soil Eh vs marsh subarea
6-14
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AVERAGE SOIL Eh
ALL CYCLES, 1995 & 1996
Note: Average Eh-5 values were used (2.5-20 cm)
-81.0
mV
-80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 6.9 Average soil Eh for all cycles.
>100
<100
6-15
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AVERAGE SOIL Eh*
J 1 I I L
26.6-
26.4H
t r—
-81.0 -80.8 -80.6 -80.4
1 1—
-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
"Average Eh values were used (2.5-20 cm)
Figure 6.10 Average soil Eh for each cycle.
6-16
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Distance from Canal, m
Figure 6 11 Soil thickness along each transect
Distance from Canal, m
Figure 6.12 Percent organic matter along each transect
6-17
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Distance from Canal, m
Figure 6.13 Soil pH along each transect.
Distance from Canal, m
Figure 6.14 Soil Eh along each transect.
6-18
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7.0 NUTRIENT CONDITIONS
7.1 Introduction
Historically, the Everglades ecosystem was nutrient poor, with phosphorus concentrations
less than 10 ppb over large areas of the ecosystem (Davis and Ogden 1994). The hydrology of the
marsh was predominantly precipitation driven, with lateral overland flows supplying a large
proportion of the water to the southern half of the marsh. There were no canals in the Everglades
region prior to the early part of the twentieth century.
Significant land use changes have occurred in the Everglades since the early 1900s. Over
50% of the original marsh has been converted to agricultural, urban, and residential uses (Davis
and Ogden 1994). The EAA for example, is located below Lake Okeechobee in areas that
historically were freshwater Everglades marsh. To facilitate the conversion of marsh for
agricultural production, a network of canals was constructed to drain the Everglades marsh,
making these areas suitable for agricultural production and urban and residential development.
Nutrient loading from the EAA and urban areas has significantly increased nutrient
concentrations, particularly TP, in the downstream WCAs and ENP (Scheidt et al. 1989, Walker
1991, Walker 1995). This resulted in major eutrophic impacts to downstream wetland systems
(Nearhoof 1992). Increased soil phosphorus content (Doren et al. 1996, DeBusk et al. 1994),
altered periphyton communities (Raschke 1993, McCormick et al. 1996), loss of water column
DO and changed aquatic community metabolism (Belanger et al. 1989, McCormick et al. 1998),
conversion of wet prairie and sawgrass plant communities to cattail (Davis 1994, Jensen et al.
1995), and subsequent loss of important wading bird foraging habitat (Fleming et al. 1994,
Hoffman et al. 1994) are examples of the progressive eutrophic impacts observed in the
Everglades. These collective changes are systemic and impact the structure and function of the
aquatic ecosystem (Belanger et al. 1989, Nearhoof 1992, McCormick et al. 1998). Increased
nutrient concentrations, particularly TP concentrations, have also been hypothesized as being one
of several variables that influences Hg methylation processes in the Everglades ecosystem (see
Chapter 10.0 for hypotheses regarding TP and Hg methylation).
7-1
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From 1994 through 1996, TP control strategies were implemented in the EAA through a
combination of agricultural BMPs and construction of about 10% of the approximately
43,000 acres of constructed wetlands, known as STAs. The Everglades Nutrient Removal Project
(ENR), which is the initial STA totaling 3,700 acres adjacent to the northwest corner of LNWR
(Figure 1.1), began discharging in August 1994. A recent study of Everglades water quality
trends documents that TP entering ENP from 1993 to 1996 was lower than concentrations
recorded from 1984 to 1992 (Walker 1997), and the data from this study show that marsh median
TP concentrations were lower in 1996 than in 1995 (Figure 7.1). However, whether the lower
observed concentrations are due to changing water management practices, the initiation of
phosphorus control efforts, the specific hydrologic conditions that occurred during a particular
sampling event, or some combination of these factors, is unclear.
Initial results from the ENR indicate that TP loads from the EAA can be reduced. For
example, the mean flow-weighted TP concentration at the ENR inflow and outflow for the first
2 years are as follows: August 1994 to November 1995, 124 ^ug/L and 21 ,wg/L; December 1995
to November 1996, 107 //g/L and 24 //g/L. (SFWMD 1998).
Agricultural BMPs were phased in over several years, with 1996 being the first year
during which all lands within the EAA had fully implemented BMPs. Annual EAA basin
phosphorus load reductions attributed to the BMP program were as follows: water year 1993,
44%; 1994, 17%; 1995, 31%; and 1996, 68%. Even with these reductions, the TP concentration
discharged from the EAA basin was still about 100 >ug/L for each of these years, (SFWMD
1997c) much higher than natural Everglades concentrations. However, caution should be used in
predicting long-term annual BMP and STA TP control performance under the varied hydrologic
conditions in South Florida based on the initial 2 or 3 years of implementation.
Because multiple Everglades restoration issues and several hypotheses regarding Hg
methylation in the Everglades are linked to nutrient concentrations, an extensive spatial
characterization of nutrients in the Everglades ecosystem, was initiated as part of this project.
Water and sediment samples were collected from the canals from September 1993 through May
1995 and analyzed for TP and for other indicators of nutrient enrichment. Similarly, water and
soil samples were collected from the marsh from April 1995 through September 1996, and along
7-2
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four transects within the marsh during the dry season in April 1994. These transects, previously
sampled by Doren et al. (1996) and Raschke (1993), originated at the canals and extended into
the marsh. These transects were placed along known nutrient gradients and are of varying
distances, with a maximum distance of over 10 km from the canal. Numerous statistical analyses
were completed on these data to identify the magnitude, extent, and spatial patterns in four
indicators of eutrophication: TP, chlorophyll a, APA, and TN. Statistical analyses and graphical
presentations of both marsh and canal data included: univariate and multivariate descriptive
statistics, ANOVA and covariance, distributional tests, kriging, box and whisker plots, and
spatial displays. These results were evaluated to identify the dominant and consistent patterns in
the data collected in the marsh and in the canals. Relationships among TP concentrations in water
and soils and plant community dominance or composition and periphyton occurrences were also
investigated to identify possible correlations between nutrient enrichment and habitat changes in
the Everglades ecosystem and relationship(s) to MeHg contamination in the Everglades.
7.2 Results
The results for the canal, marsh, and transect sampling are presented separately in this
section. A synthesis section integrates these results to provide an overall perspective of
eutrophication during the 1993 through 1996 sampling period.
7.2.1 Canals
7.2.1.1 Canal Surface Water
Several consistent patterns were observed in the canal water quality data that provide a
picture of the potential sources of, and transport mechanisms for, TP in the Everglades
ecosystem. From 1993 to 1995, the canal sampling period, TP concentrations consistently were
found to be highest in the canals north of Alligator Alley (Figure 7.2). Table 7.1 shows geometric
mean TP concentrations in canal water throughout the South Florida Everglades ecosystem. TP
concentrations in water collected from canals located above Alligator Alley are significantly
higher (PO.05) than TP concentrations in canals located between Alligator Alley and Tamiami
Trail, and in canals located below Tamiami Trail; and TP concentrations in canals between
7-3
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Alligator Alley and Tamiami Trail are significantly higher (P<0.05) than in canals below
Tamiami Trail.
Table 7.1 Annual comparison of TP concentrations in water (//g/L) in Everglades canals and
marsh. Data presented are the geometric means for the lognormally distributed data
and sample size in parentheses. (> or < is statistically significant, P<0.05)
Total Phosphorus in Water (/^g/L)
SUBAREA
North of
Alligator Alley
Alligator Alley to
Tamiami Trail
South of
Tamiami Trail
Canal
79 (113)
> 24 (63)
> 14 (18)
Marsh
18 (146)
> 12(157)
10 (138)
The highest TP concentrations are found in the EAA canals. Approximately 80% of the
canal miles in the EAA and north of Alligator Alley had TP concentrations greater than the Phase
I STA design target of 50 /ug/L. The percentage of canal miles exceeding the 50 /ug/L TP design
target drops rapidly from 80% to 15% for canals in the area between Alligator Alley and
Tamiami Trail, and further to 1% for canals in the area south of Tamiami Trail (Figure 7.3). Box
and whisker plots of TP concentrations within the EAA, WCAs, ENP, and BCNP (Figure 7.4)
show that the median TP concentrations in the EAA are significantly different (P<0.05) from TP
concentrations in the WCAs, ENP, and BCNP. Furthermore, TP concentrations in surface water
in the canal within the WCAs are significantly higher (P<0.05) than TP concentrations in the
ENP canals.
TP concentrations in the canals decrease with increasing distance from the EAA or with
decreasing latitude (Figures 7.2 and 7.5). This north to south concentration gradient corresponds
to the direction of flow from the EAA south through the Everglades ecosystem to ENP or Florida
Bay. Geometric mean concentration of TP in canal water north of Alligator Alley was
approximately 3 times higher than the geometric mean TP concentration in canal water in the
7-4
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area between Alligator Alley and Tamiami Trail, and over 5 times higher than in the canals south
of Tamiami Trail (Table 7.1).
TP concentrations in canal water were slightly higher during the dry season through the
Everglades with the exception of the EAA, where TP concentrations in the canal water were
higher in the wet season than the dry season. The increases observed during the dry season,
however, were not significant. Overall, little seasonal differences were observed in TP
concentrations in canal water between wet and dry seasons. The presence of a north to south
gradient in TP was the same between the dry and wet seasons.
Although not as pronounced as TP concentration patterns, similar patterns exist for
chlorophyll a and APA in the canal water during the 1995 dry season (Table 7.2). Higher
chlorophyll a concentrations were found in the EAA compared to concentration in the WCAs,
BCNP, and the ENP. In general, APA throughout the canals exhibited an inverse relationship
with TP in water (Figures 7.2 and 7.6). The lowest APA was observed in the EAA where TP
concentrations in canal water were highest. The highest APA was found in the ENP where TP
concentrations in canal water were lowest. Table 7.2 shows a comparison of mean TP
concentrations, APA, and chlorophyll a concentrations during May 1995, which is the only cycle
when all three constituents were sampled.
Table 7.2 Comparison of geometric mean of TP, APA, and chlorophyll a concentrations in
canal water by subarea during the May 1995 sampling cycle. Sample size n is
shown in parentheses. (> or < is statistically significant, P<0.05)
Parameter
Geographic Subarea
EAA
WCAs
ENP
BCNP
TP (/ig/L)
73.30(14)
> 44.20(19)
> 14.20 (5)
< 28.70 (7)
APA (/^Mol/hr)
0.12(14)
< 0.32 (20)
0.65 (8)
0.36 (8)
Chlorophyll a (/ug/L)
8.43 (14)
> 4.54 (20)
> 1.52(8)
< 4.67 (8)
7.2.1.2 Canal Sediment Data
No spatial or temporal relationships were observed in TP concentrations in canal
sediments throughout the study. Table 7.3 and Figure 7.7 provide the results of TP concentrations
7-5
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in canal sediments by geographic subarea. Figures 7.8 and 7.9 provide the results of the TP
sediment analyses in canals in the three latitudinal subareas in the Everglades and by cycle. Some
higher concentrations were noted in BCNP when the data were parsed by longitude (Figure 7.10).
TP concentrations in canal sediments in BCNP were significantly higher and in ENP were
significantly lower compared with TP canal sediment concentrations in the other geographic
subareas (Table 7.3).
Table 7.3 Geometric mean of TP concentrations (^g/kg) in canal sediments by four geographic
subarea within the Everglades. (> or < is statistically significant, P<0.05)
Total Phosphorus in Canal Sediments (//g/kg)
Geographic Subarea
EAA
WCAs
ENP
BCNP
Geometric Mean (n)
829.9 (71)
= 727.8 (67)
> 495.4 (29)
< 1,603.2 (29)
Minimum
17.5
103.3
77.7
94.6
Maximum
9,099.7
3,834.8
4,165.0
7,907.4
7.2.2 Transects
Figure 7.11 shows the locations of the 4 transects that were established within the marsh
to evaluate contributions of the canals to TP concentrations in the marsh. These 4 transects
originate at the edge of the canal and extend into the marsh for varying distances. Two of these
transects, the LNWR and the WCA2 transects, are located in close proximity to the EAA north of
Alligator Alley. The remaining 2 transects, the WCA3 and ENP transects, are located
perpendicular to Tamiami Trail at S-12C.
TP concentrations in water, plotted as a function of distance from the canal, show that TP
concentrations were of greater magnitude and spatial extent for the two transects located in close
proximity to the EAA than for those along Tamiami Trail. A rapid decline in TP concentrations
was observed as distance from the canal increased within these two transects. This decline
approaches an exponential decline in TP concentrations. The TP concentrations in WCA3 and
ENP adjacent to Tamiami Trail were lower both in magnitude and spatial extent than
7-6
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concentrations observed in the transects north of Alligator Alley. Although concentrations
entering the marsh from the canals were lower at these two transects than the transects near the
EAA, the transect data show that TP concentrations in the marsh are highest at locations closest
to the canal (Figure 7.12) supporting the hypothesis that phosphorus is being delivered to the
marshes via the canals. The delivery of TP to the marsh is highest in the WCAs north of Alligator
Alley.
Similar to the patterns observed for TP in water along the transects, TP in soil samples
collected within these transects show decreasing concentrations with distance from the canal
(Figure 7.13). The pattern of elevated TP soil concentration near the canal that decreases with
distance from the canal, was more pronounced in the soil data than in the water data. Other
investigators have documented this phosphorus water and soil gradient within WCA2A (Walker
1995; Urban et al. 1993; Doren et al. 1986).
7.2.3 Marsh
TP concentrations in water in the marsh from 1995 to 1996 show important patterns
relative to proposed ecosystem restoration objectives. Figure 7.1 shows that overall, median TP
concentrations in the Everglades were lower in 1996 compared to 1995 and that TP
concentrations generally were lower during the wet season.
Although TP patterns are quite different in the marsh between the 1995 and 1996
sampling years (Figure 7.1) and between the wet and dry seasons (Figure 7.14), several
noticeable patterns appear to support the hypothesis that TP is transported to the marsh from the
canals. Data from 1996, which was approaching normal precipitation, showed that during the dry
season, approximately 85% of the marsh had TP concentrations below the 50 /ig/L design target
for the STAs (Figure 7.15). Furthermore, approximately 85% of the marsh had concentrations
greater than 10 ^g/L during the dry season in 1996. During the wet season of 1996, TP
concentrations were greater than 10 ngfL in LNWR, WCA2, the northernmost portion of WCA3,
and only one location in the marsh near the Miami Canal in WCA3 (Figure 7.14). A more
extensive "front" of elevated TP concentrations (i.e., TP concentrations greater than the 10 ppb
natural TP concentration) in the marsh was observed during the wet season in 1995 when
7-7
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precipitation and flows in the canals were above normal. Over 60% of the marsh had TP
concentrations in water greater than 10 /zg/L during the wet season in 1995 (Figure 7.15).
The percentage of the marsh area sampled with concentrations greater than the Phase I
STA design target of 50 //g/L was quite small. Only approximately 8% of the marsh area above
Alligator Alley had a concentration greater than 50 Mg/L. Only approximately 5% to 2% of the
marsh area sampled below Alligator Alley and Tamiami Trail had TP concentrations in surface
water greater than the 50 /ugfL STA design target. Approximately 92 to 98% of the marsh had
surface water TP concentrations less than or equal to 50 /ug/L (Figure 7.16). Geometric mean TP
concentrations in surface water in the marsh were approximately two times higher above
Alligator Alley than concentrations south of Tamiami Trail (Table 7.1).
During the 1995 and 1996 dry seasons (Figure 7.14), a few locations in WCA2 and ENP
near the canals had TP concentrations greater than 50 /ugfL. These TP "hot spots" were not as
prevalent during the wet season when more dilution from increased precipitation and surface
flow occurred.
Under more normal rainfall conditions and water depths, TP concentrations were higher
in marsh during the 1996 dry season than the 1996 wet season (Figure 7.14). The seasonal
differences in TP concentrations in water in the marsh were more pronounced below Alligator
Alley than north of Alligator Alley, which is adjacent to the EAA (Table 7.4 and Figure 7.17).
When the data for each subarea were evaluated by season, TP concentrations in marsh water
were lower during the wet seasons than during the dry seasons (Figures 7.17 through 7.19). Little
change was observed in the overall pattern of TP concentrations in marsh water by subarea, when
evaluated on a seasonal basis (Figures 7.18 and 7.19). TP concentrations in marsh water were
highest in WCA2, and lowest in ENP and BCNP, regardless of the seasonal differences in TP
concentrations in marsh water (Figures 7.18 and 7.19).
Patterns of APA in marsh water were inverse to TP patterns (Figure 7.20). Lowest APA
occurred in areas where TP concentrations were highest. For example, during the 1996 wet
season when TP concentrations were highest above Alligator Alley, APA activity was lowest
(Figure 7.21). The interior marsh within LNWR always had high APA indicative of a low
phosphorus, rain driven marsh system (Newman et al. 1997, Browder et al. 1994).
7-8
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Table 7.4 Seasonal comparison of canal and marsh TP geometric mean concentrations (^g/L)
in water by latitudinal subarea. Sample size n is shown in parentheses. (> or < is
statistically significant, P<0.05)
North of
Alligator Alley
Alligator Alley to
Tamiami Trail
South of
Tamiami Trail
Canal
Wet
101 (56)
> 18 (35)
10 (8)
Dry
62 (57)
> 36 (28)
> 19 (10)
Marsh
Wet
15 (84)
> 8 (81)
8 (77)
Dry
25 (62)
> 20 (76)
16 (61)
Summaries of TN concentrations in marsh water are shown on Table 7.5 and Figures 7.22
and 7.23. The pattern of TN concentrations is very similar to that for TP in water with higher
concentrations occurring in WCA2 and concentrations decreasing in WCA3, ENP, and BCNP.
Dry season concentrations were higher than wet season concentrations. The box and whisker
plots indicate that TN concentrations in WCA2 are consistently significantly (P<0.05) greater
than those in WCA3 and ENP. TN concentrations in WCA2 are also significantly (P<0.05)
different from those in BCNP. It is uncertain wether or not the higher TN concentrations
measured in BCNP during the dry season are representative, because there were only five
measurements during this sampling cycle.
Table 7.5 Geometric mean TN (mg/L) in water in the Marsh. Number in parenthesis is sample
size for both sampling cycles.
Total Nitrogen (mg/L)
Subarea
Geometric Mean (#i)
LNWR
1.6 (22)
WCA2
1.8 (18)
WCA3
1.4 (86)
BCNP
1.2 (17)
ENP
1.2 (62)
7-9
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TP concentrations in marsh soils showed similar patterns as TP concentrations in water.
Highest soil TP concentrations were found above Alligator Alley (Figures 7.24 and 7.25).
Generally, median TP concentrations in marsh soil were significantly higher in WCA2 and
WCA3 than in LNWR or ENP and BCNP except during the wet seasons (Figure 7.26).
Maximum TP concentrations in marsh soils (i.e., marsh soils hot spots), were located in WCA2,
WCA3, and the ENP. Strong correlation between TP hot spots in marsh soils and marsh water
was observed (Figure 7.27).
7.2.4 Vegetation and Periphyton Relationships
A comparison of TP concentrations in marsh soils with presence of cattails (Typha
domingiensis) throughout the marsh (Figure 7.28) showed a strong correlation between TP
concentrations in soils and presence of cattails. A weak relationship was observed between TP in
water and the presence of cattails. Similar analyses of TP in water and presence of floating
periphyton mats suggest that as TP concentrations in water increased, the presence of floating
periphyton mats in the marsh decreased.
7.3 Synthesis
Consistent patterns exist in TP concentrations in water and soil in the Everglades
ecosystem to describe the spatial distribution of TP within the Everglades and allow inferences
on the sources and potential ecosystem changes associated with TP enrichment. Data collected
for other indicators of nutrient enrichment (i.e., APA and chlorophyll a) further support the
patterns in TP observed and the following conclusions.
The canal and the marsh water quality data collected during this assessment support the
hypotheses in the original 1993 conceptual model (Stober et al. 1993) that the EAA is the
primary source of phosphorus enrichment in the Everglades, and that the canals are the major
mechanism for transport of TP from the EAA to the marsh ecosystem. Identifiable gradients in
TP concentrations in marsh water and soils were observed, with highest concentrations
consistently found above Alligator Alley. Canal data collected over two very different years with
respect to precipitation, consistently showed highest concentrations of TP in the EAA and
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decreasing TP concentrations in water with increasing distance from the EAA. Transect data
showed an increase in TP in soils and water in the marsh at locations closest to the canals,
thereby, indicating that the canals are likely to be a major source of TP in the marsh.
The data show that certain localized areas within the Everglades marsh, particularly in
WCA2 and WCA3 and in the ENP, have TP concentrations in water and soil that are higher than
background concentrations found in the marsh at similar latitudes or within each of the subareas.
Maximum concentrations or TP hot spots in water in ENP, where TP concentrations typically are
lowest, were observed in locations near or at the end of the major canals in ENP. TP
concentrations in the ENP during the dry season likely represented the transport of TP to ENP via
the L67 canal. These data combined, with the canal and the transect data, support the hypothesis
that the canals are a major transport mechanism for TP to the marsh.
Evaluation of seasonal patterns of TP concentrations in marsh water showed that seasonal
differences in TP concentrations were more pronounced south of Alligator Alley than north of
Alligator Alley adjacent to the EAA. These data suggest that there is more continuous input of
TP to LNWR, WCA2, and the northern portion of WCA3 during both dry and wet seasons. The
higher TP concentrations observed were south of Alligator Alley during the dry season expected
as a result of evapoconcentration in this precipitation driven marsh system.
TP concentrations in the WCAs and the ENP also appeared to correlate well with plant
community composition and the presence of floating periphyton mats. The data showed a high
correlation between the presence of cattails and increased TP concentrations in marsh soils. This
association between high elevated soil phosphorus and cattail presence was also independently
observed by Doren et al. (1996) in LNWR, WCA2A, WCA3A and ENP, and in WCA2A by
DeBusk et al. (1994) and Urban et al. (1993). North of Alligator Alley the plant community was
largely sawgrass (Cladium jamaicense) dominated, but both the presence of cattails within this
community and the frequency of cattail dominated plant communities was higher north of
Alligator Alley where TP concentrations were highest in water and soil. Although high TP
concentrations in water and soil were not likely the sole factor for the presence of cattails or the
higher frequency of cattail dominated communities north of Alligator Alley, it is likely that the
shift in plant community composition and increased cattail dominated communities as described
7-11
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in Chapter 5.0 was a response to high TP concentrations in the soils and water in the marsh north
of Alligator Alley. Preliminary field observations of increased height and density of marsh
vegetation (i.e., sawgrass and cattails) in northern WCA3A near the EAA and at locations along
the canal compared to similar vegetation throughout the marsh also support this conclusion.
Studies by Urban et al. (1993) and Davis (1991) indicate that cattails effectively outcompeted
other plant species, thereby reducing plant community diversity when soil TP concentrations
increased above background concentrations. The periphyton data from this study also support
this conclusion. In those areas in the northern portion of Alligator Alley where sawgrass was the
dominant plant community, where the presence of cattails was the highest, and where the
frequency of cattail dominated communities was highest, the presence of periphyton mats were
lowest. As documented by McCormick et al. (1998), the presence of floating periphyton mats
was well correlated with the presence of wet prairie or slough dominated communities.
Consequently, as shifts in the dominant plant communities occurred and plant biomass increased
as a response to increased TP concentrations in the marsh, periphyton productivity and the ability
of the habitats to support higher trophic levels (i.e., fish) decreased.
The nutrient data collected in this study also provides a baseline for evaluating proposed
ecosystem restoration measures in the Florida Everglades. As part of the Everglades restoration
project, approximately 43,000 acres (175 km2) of constructed wetlands are to be built to reduce
TP concentrations discharged from the EAA into the Everglades ecosystem. The STAs are
designed to reduce TP concentrations in water to 50 /Ug/L. The 1993 through 1996 Everglades
marsh and canal phosphorus conditions described by the present study represent the phase-in
period for the EAA BMP program and implementation of about 10% of the Phase I STA
program treatment area. This assessment indicates that from 1993 to 1995 75% of canal miles
had TP concentrations in water greater than 50 ,ug/L north of Alligator Alley while less than 15%
had TP greater than 50 //g/L south of Alligator Alley. Approximately 4% of the marsh area
sampled from 1995 to 1996 had TP concentrations in water greater than 50 /^g/L. If the Phase I
TP target became the criterion, the marsh would continue to eutrophy. In fact, 55 to 62% of the
marsh already has concentrations less than 10 /Ug/L.
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100 -
00
3
V
w
ctf
£
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Sampling Cycle
Figure 7.1 TP concentrations in surface water in the Everglades marsh were lower in 1996 than 1995 and during the wet season.
-------
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-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 7.2 TP concentrations in canals are highest in canals north of Alligator Alley.
7-14
-------
Cana! Total Phosphorus in Water
North of Alligator Alley
100
80
.c
ei
5 60
J
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a 40
(J HU
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0 100 200 300 400 500
Total Phosphorus (ug/L)
Canal Total Phosphorus in Water
Alligator Alley to Tamiami Trail
' Measured Value
95% Confidence
100 200 300 400
Total Phosphorus (ug/L)
500
Canal Total Phosphorus in Water
South of Tamiami Trail
Measured Value
95% Confidence
100 200 300
Total Phosphorus (ug/L)
400
500
Figure 7.3
Cumulative distributions of canal TP in subareas. % canal length refers to the
population estimate, where each sample represents a specific portion of the
population. 7.15
-------
Canal Data
0> 75*/. ~ 3 MID RANGE
* > 75% ~ I 5 MIDRANGE
T 75% ~ I 5 MIDRANGE
J 75%
MEDIAN
> MIDRANGE
25%
1 25% - I 5 MIDRANGE
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WCA
BCNP
ENP
EAA WCA BCNP ENP
Figure 7.4 Notched box and whisker plots of canal TP in each of the subareas.
7-16
-------
Canal Data
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400
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Figure 7.5 Plot of selected constituents showing latitudinal gradients in canals.
7-17
-------
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Figure 7.6 APA in canals is highest in areas where TP concentrations are lowest.
7-18
-------
Canal Data
eo
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~ 8000
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- 4000
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Wet Seasons
EAA
WCA
ENP BCNP
Figure 7.7 TP concentrations in canal sediments by geographic subarea show no spatial patterns.
7-19
-------
0> 75% • 3 MIDRANGE
* > 75V. ~ I 5 MIDRANGE
75V, ~ I 5 MIDRANGE
75%
Canal Data
95% f
CONFIDENCE <
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10000
6000
4000 -
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Figure 7.8 TP concentrations in canal sediments by latitudinal subarea show no spatial patterns.
7-20
-------
10000
8000
6000
4000 -
2000
1 2
Sampling Cycle
Figure 7.9 TP concentrations in canal sediments by cycle show no temporal patterns.
10000
3 8000
\
60
3
~ 6000
t>
E
« 4000
C/3
a
^ 2000
0
-81.5 -81.0 -80.5 -80.0
Longitude
Figure 7.10 TP concentrations in canal sediment by longitude for all cycles combined.
7-21
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Figure 7.11 Location of four April 1994 marsh transects and canal water control structures
sampled on a biweekly basis.
7-22
-------
100
^ 80
to
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S 60
cd
£
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0 4000 8000 12000 16000 20000
Distance from Canal, m
Figure 7.12 TP in water along transects decreases with distance from the canals.
Distance from Canal, m
Figure 7.13 TP in soil along transects decreases with distance from the canals.
7-23
-------
26.
26,
26.
26.
25.
25.
25.
26.
26.
26.
26.
25.
25,
25,
14
TOTAL PHOSPHORUS IN WATER
DRY SEASON
APRIL 1995
T 1 r
-81.0 -80.8 -80.6 -80.4
1— "I T
-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Kriged surfaces showing TP in the marsh for each sampling cycle based on
sampling data.
7-24
-------
cd
0>
J3
c/5
U
C3
2 40
Marsh Total Phosphorus in Water
Cycle 1 : September 1995
Measured Value
95% Confidence
200 300
Total Phosphorus (ug/L)
500
Marsh Total Phosphorus in Water
Cycle 2 : May 1996
Total Phosphorus (ug/L)
Figure 7.15 Cumulative distributions of TP concentrations in the marsh for selected cycles.
7-25
-------
Marsh Total Phosphorus in Water
North of Alligator Alley
Total Phosphorus (ug/L)
Marsh Total Phosphorus in Water
Alligator Alley to Tamiami Trail
Total Phosphorus (ug/L)
Marsh Total Phosphorus in Water
South of Tamiami Trail
80
r
I i
60
I
I !
I
40
I j
20
Measured Value
O
95% Confidence
0 100 200 300 400 500
Total Phosphorus (ug/L)
Figure 7.16 Cumulative distributions of TP concentrations in the marsh subareas.
7-26
-------
26.6-
TOTAL PHOSPHORUS IN WATER
DRY SEASONS
25.4-
-81.0
-80.8
-80.6
-80.4 -81.0 -80.8
LONGITUDE, decimal degrees
-80.6
-80.4
Figure 7.17 Kriged surfaces showing TP concentrations in the marsh using dry and wet season data.
-------
Marsh Data
1000
100
10
O > w.. 3 midrange
• > 75V. . I s midrange
75*/. • I 5 MIDRANGE
75%
MEDIAN ) MIDRANGE
25V. 1 SMIDRANGC
All Data
* <
> *
1 '! " *
>
* *
. A ^
i
i
I
LNWR WCA2 WCA3
ENP
BCNP
LNWR WCA2 WCA3 ENP BCNP
1000
100
10
1
Notched box and whisker plots comparing marsh TP in subareas during dry and
wet seasons.
LNWR WCA2 WCA3 ENP BCNP
7-28
-------
Marsh Data
40
30
.j
\
eo
3
cl, 20
(2
10
All £)ata
I i i
^——1
i i i
LNWR WCA2 WCA3 ENP BCNP
Dry Season's
LNWR WCA2 WCA3 ENP BCNP
40
30
J
eo
2
cu 20
13
+*
o
H
10
0
Figure 7.19 Plots of the medians of marsh TP measurements in each of the subareas with a
vertical line indicating the 95% confidence interval about each median.
7-29
Wet Seasons
i i i i i
LNWR WCA2 WCA3 ENP BCNP
-------
26.6-
26.4-
TOTAL PHOSPHORUS
IN WATER
ALL CYCLES, 1995 & 1996
-81.0
-80.8
-80.6
-80.4
-81.0
-80.8
-80.6
-80.4
LONGITUDE, decimal degrees
Figure 7.20 Kriged surfaces showing patterns of TP and APA in the marsh.
-------
ALKALINE PHOSPHATASE ACTIVITY
IN WATER
26.6-
i 1 — i r
-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 7.21 Kriged surfaces showing APA in the marsh for each sampling cycle.
7-31
-------
O > 75V. ~ 3 MID RANGE
* > 75% + I 5 MIDKANGE
75% ~ I 5 MID RANGE
,,,
Marsh Data
LNWR WCA2 WCA3 ENP BCNP
LNWR WCA2 WCA3 ENP BCNP
J
\
(2
Wet Seasons
1
I
1
*
T
*
1 1
1
l
*
I
1
*
1
*
T
a.
1
LNWR WCA2 WCA3 ENP
BCNP
Figure 7.22 Notched box and whisker plots comparing marsh TN in subareas during dry and
wet seasons.
7-32
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26.6-
-80.8
-80.4 -81.0 -80.8
LONGITUDE, decimal degrees
-80.6
-80.4
Figure 7.23 Kriged surface showing marsh TN concentrations in water during the May and September 1996 cycles.
-------
TOTAL PHOSPHORUS
IN SOIL
ALL CYCLES, 1995 & 1996
-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 7.24 Kriged surface showing marsh soil TP concentrations over the study period.
7-34
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O > 75% 4 \ M1DRANGE
* > 75V. ~ I 5 MIDRANGE
r 75V. ~ 1 5 MIDRANGE
1 75V.
Marsh Data
95*/.
CONFIDENCE
ON MEDIAN
MEDIAN ) MIDRANGE
2000
1500
1000
500
25V.
2SV. • I S MIDRANGE
All Data
I
r- H
AA-N
AA-TT
TT-S
2000
1500
1000
500
Dry Seasons
o
o
0
1
c
1
i<
r i
-
-
1—
AA-N
AA-TT
TT-S
2000
1500
1000
500
Wet Seasons
§
e
0
1
, T , T
1 ^
AA-N
AA-TT
TT-S
Notched box and whisker plots comparing marsh soil TP in latitudinal subareas
during dry and wet seasons.
7-35
-------
Marsh Data
95%
CONFIDENCE
ON MEDIAN I
\
W)
3
O
CO
c
cu
2000
1500
1000
£ 500
0> 75% ~ 3 MIDRANGC
• > 75% ~ I 5 MIDRANGE
75% ~ I 5 MIDRANGE
75%
All data
WCA1
¥
¥
B
WCA2 WCA3
ENP
25 V.
ii% ¦ I 5 MIDRANGE
BICY
2000
WCA1
WCA2
WCA3
ENP
BICY
2000
1500
" 1000
o 500
Wet S
easons
i
"
8
0
o
•
0
t
1
*
T
X
1
- ^
i
i
£
WCA1
WCA2
WCA3
ENP
BICY
Figure 7.26 Notched box and whisker plots comparing marsh soil TP in geographic subareas
during dry and wet seasons.
7-36
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-J
26.6-
TOTAL PHOSPHORUS
IN WATER
TOTAL PHOSPHORUS
IN SOIL
LONGITUDE, decimal degrees
Figure 7.27 Kriged surfaces showing TP concentrations in marsh water and soil during study period.
-------
25.6-
25.4-
X= CATTAILS PRESE
-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 7.28 Kriged surface of TP in marsh soils with sampling stations where cattails were
present.
7-38
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8.0 MERCURY
8.1 Introduction
Since the initial detection of elevated levels of Hg in freshwater fish in 1989 (Ware et al.
1990), it has become increasingly apparent that South Florida has an extensive Hg contamination
problem. The state of Florida has issued human health fish consumption advisories due to Hg
contamination that either ban or restrict the consumption of largemouth bass and other freshwater
species from over 7,600 km2 (2 million acres) encompassing the Everglades and BCNP. The
maximum concentrations found in largemouth bass (4.4 mg/kg) and bowfin (over 7 mg/kg)
collected from the Everglades are the highest concentrations found in Florida to date. Hg
contamination has also been found at levels of concern in largemouth bass throughout Florida's
surface waters (Lange et al. 1993). Hg accumulation through the food web may reduce the
breeding success of wading birds (Frederick and Spalding 1994) and the survival of the
endangered Florida panther (Roelke et al. 1991).
Prior to the initiation of this and other studies (e.g., USGS, EPA ORD, FDEP, SFWMD,
EPRI) in the mid-1990s, the sources, distribution, magnitude, transport, transformations, and
pathways of Hg through the Everglades ecosystem were poorly known. Among the possible Hg
sources in South Florida are natural mineral and peat deposits (Rood et al. 1995) and atmospheric
deposition from global, regional and local sources (e.g., fossil-fuel fired electrical generating
plants, municipal waste incinerators, medical waste incinerators, paint operations, and
agricultural operations). Although there are multiple interactions among these sources and
several possible pathways for Hg transport and bioaccumulation through the Everglades
ecosystem, none of these individual sources appear to adequately explain the vast area apparently
contaminated by Hg.
The issues of Hg contamination of Everglades biota are extremely complex. Various
hypotheses have been put forward to account for the apparent susceptibility of the Everglades to
Hg impacts (SFMSP 1996), including (1) high historical accumulations of readily methylatable
Hg in the downstream sediment attributable to the historical oxidation of peat in the EAA; (2) a
high mobilization rate of readily methylatable Hg from the sediment associated with the dry-wet
8-1
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cycles in the EAA and some locations in the WCAs; (3) a high atmospheric deposition flux of
methylatable Hg from local, regional, and global sources; (4) a high rate of net methylation of Hg
associated with high concentrations of conducive factors in water and sediment pore water; (5)
change in flow path from overland flow to infiltration and subsurface flow following drainage;
(6) a high bioavailable fraction of MeHg; (7) the absence of a freeze-thaw cycle and high average
annual temperatures that accelerate aquatic metabolic processes; (8) high bioaccumulation and
biomagnification factors resulting from the complex aquatic and terrestrial food webs; or (9)
combinations of the above (EPA 1993). The importance of wetlands as sites of abiotic and biotic
Hg methylation was recognized in the review by Zillioux et al. (1993). The large surface to
volume ratio of wetlands makes them sensitive to atmospheric inputs and sentinel indicator
ecosystems for this global contamination problem.
For fish Hg contamination to reach concentrations that have ecological or human health
consequences, five conditions must exist: (1) presence of Hg in locations, forms, and
concentrations available to aquatic bacteria; (2) combination of environmental factors favorable
to a high rate of net MeHg production and bioavailability; (3) bioaccumulation and
biomagnification through the food chain; (4) significant rate of exposure by consumption of
contaminated food; and (5) one or more species of wildlife sensitive to consuming Hg
contaminated food at rates that result in the accumulation of MeHg to toxic levels. This chapter
discusses: (1) the external loadings or sources of Hg to the South Florida Everglades ecosystem;
(2) the spatial patterns, water quality gradients, and constituent interactions in the canal and
marsh ecosystems; and (3) the general attributes and response of the biological indicator, the
Eastern mosquitofish (Gambusia holbrooki).
8.2 Initial Conceptual Mercury Cycling Model
A conceptual model of Hg cycling in the Everglades was initially developed in 1992.
Several testable hypotheses were developed from this initial model (Table 8.1). This section
presents the initial conceptual model that formed the basis of data collection activities in the
Everglades from 1993 through 1996.
8-2
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Table 8.1 Initial Hg hypotheses developed in the Interagency Scope of Study (Stober et al.
1992).
• Hg contamination is significantly increased by anthropogenic (global, regional and local)
releases to the air and subsequent wet/dry deposition to the Everglades ecosystem.
• Water discharged from the EAA is loading the downstream WCA and ENP with Hg
and/or MeHg.
• Eutrophication of the Everglades is resulting in conditions conductive for the methylation
of Hg of geologic origin in peat soils. Specific hypotheses include:
- Phosphorus loading to the Everglades ecosystem is stimulating primary production
leading to increased organic matter, which leads to increased oxygen demand and
development of anaerobic conditions that favor the methylation of Hg.
- The addition of nutrients to wetland soils results in proliferation of excess biomass
and microbial consumption of organic matter leading to reducing conditions and
Hg methylation.
- The sedimentation of autochthonous and allochthonous organic matter in canals
and waterways results in the development of anaerobic conditions near the
sediment-water interface, which contributes to an increase in the rate of
methylation and solubilization of naturally occurring Hg. Because these canals are
often the source of (or directly associated with) Hg contaminated fish, anaerobic
sediments are a likely contributor of MeHg for bioaccumulation by fish.
Agricultural practices lead to increased soil oxidation and compaction and cause
Hg concentration increases (mg/kg) in cultivated fields. Subsequently increases in
bulk density of these soils allows less oxygen to diffuse into the soil matrix. Thus,
intermittent repeated flooding occurring naturally or used in nematode control,
causes an increase in the rate of methylation and solubilization of naturally
occurring Hg followed by transport from the fields into the Everglades.
For Hg to be methylated, a specific set of conditions must occur — anaerobiosis,
specific range of Eh, presence of sulfate and organic matter — which have limited
geographic distribution in South Florida, but are not foreign to the Everglades.
The distribution of THg and MeHg concentrations in soils, sediments, surface
waters and selected biota is the same throughout the Everglades study area.
- There is no relationship between MeHg concentrations in soils and indicators of
eutrophic effects (e.g., TP) in soils and surface waters of the Everglades ecosystem.
Irrigation and drainage water from the EAA is loading the downstream Everglades
ecosystem with Hg.
8-3
-------
Significant quantities of Hg cycle through air, water, and solid phases of the global
environment. Hg cycling through the atmosphere is estimated at 6 billion grams/year (Fitzgerald
1986, 1989; Porcella et al. 1992), and additional research indicates that this amount has increased
at about 1.5% per year over the North Atlantic Ocean since 1970 (Slemr and Langer 1992).
Deposition of atmospheric Hg has increased since 1850 in lake sediments taken in
midcontinental North America (Swain et al. 1992). The rate closely parallels that documented for
greenhouse gases. Within this global background, regional areas exist that may exhibit higher
atmospheric background concentrations due to the proximity of urban or industrial activity. The
entire southeast coast of Florida is an urban area inhabited by about 5 million people. The
operation of solid waste incinerators and fossil fuel power plants has increased significantly since
1940 (Newman 1992), presenting the prospect that regional atmospheric Hg might have
increased similarly over this time period (Figure 8.1). The predominant wind directions are from
the east to southeast, which causes an air mass to be transported from above the Atlantic Ocean,
westward over the urban area and across the Everglades. There are a variety of Hg emission
sources in the urban areas along the east coast. Hg is emitted into the atmosphere as a mixture of
gases and particulates. As the Hg from individual sources mixes together, the mass of air
containing the Hg is transported over the Everglades where it is then potentially deposited
through a variety of mechanisms. The most likely mechanism is through wet deposition, with the
Hg being washed out by rainfall. The other mechanism is dry deposition with particulates
dropping into the Everglades and gaseous Hg coming into contact with the water. The fate and
transport of point source atmospheric discharges and speciation of atmospheric Hg from regional
incinerators and power plants must be evaluated to determine the depositional contributions to
the Everglades ecosystem. Regional (far-field) atmospheric Hg flux was monitored by the Florida
Atmospheric Mercury Study (FAMS). Local (near-field) source apportionment and fate and
transport studies of Hg are being investigated by EPA and the University of Michigan.
Two common factors in Hg contamination in temperate regions are low pH of receiving
waters and acid rain (Winfrey and Rudd 1990). Both lead to conditions that contribute directly to
the enhanced solubilization of inorganic Hg. Once inorganic Hg enters the water, it becomes
more available to the methylation processes. Although acid rain and acidic conditions in other
8-4
-------
ecosystems could be responsible for Hg contamination, it is unlikely that these factors contribute
significantly in the subtropical Everglades because the Everglades are generally circumneutral or
alkaline in pH and underlying limestone strata provide a high buffering capacity.
Figure 8.1. Schematic figure depicting atmospheric deposition of Hg.
Organic soils and sediments, such as those found throughout Everglades wetlands, would
be expected under appropriate conditions to contain and retain Hg. The natural processes by
which this occurs, however, have been altered by water management and other anthropogenic
activities in South Florida and, perhaps, by large-scale global Hg inputs (Slemr and Langer
1992). To understand the biogeochemical cycling of Hg in the Everglades ecosystem, it is
necessary to understand the processes and factors influencing the flux of Hg through this system.
An important step in this process is identifying the sources of Hg and quantifying the relative
contribution of these sources to the Everglades ecosystem (Figure 8.2).
The soils and sediments (Figure 8.2) of the Everglades ecosystem represent the largest
deposits of circumneutral peat in the world. However, the abundant organic matter in wetlands
sequesters Hg (Lodenius et al. 1987, Schuster 1991), and Everglades soils and sediments can
contain a substantial Hg pool even without continuing atmospheric deposition. When this study
was initiated in 1992, the Hg pool was not yet quantified. Preliminary results of Hg sediment and
8-5
-------
soil accumulation rates in the Everglades suggested that the rate may have increased at some
locations since 1980 (Delfino 1992). Therefore, these soils and sediments were a candidate
source of the Hg that may ultimately contaminate the tissues of fishes found in associated waters
(Stoberetal. 1992).
A unique feature of these organic soils is that peat and muck are subject to subsidence
and lose surface elevation when drained because of (1) shrinkage due to desiccation;
(2) consolidation by loss of the buoyant force of groundwater; (3) compaction by tillage; (4) wind
erosion; (5) burning; and (6) biochemical oxidation (Stephens 1984). The subsidence of the
organic soils in the EAA in recent decades may have resulted in the concentration of Hg in the
remaining soil, thereby facilitating the methylation and/or transport of Hg downstream via forced
drainage. Considering the surface area under cultivation and drainage and the fact that over
70% of the EAA peat volume has been lost to subsidence since farming began at the turn of the
century (Stephens 1984), a significant mass of Hg may have been transported downstream to the
Everglades by drainage canals over the years.
Inorganic Hg is converted to MeHg primarily through the actions of microorganisms.
Sulfate-reducing bacteria, which are obligate anaerobes, have been implicated in Hg methylation
(Gilmour et al. 1992). The methylation process vastly increases the toxicity and likelihood for Hg
to bioaccumulate (Gilmour et al. 1992). Methylation of Hg not only increases the bioavailability
of this metal, it also increases the mobility of Hg in the environment by decreasing the formation
of relatively insoluble salts and oxides (Grieb et al. 1990). The interactions of the sulfur cycle
and sulfate-reducing bacteria with the chemistry of Hg present numerous questions for
understanding the processes affecting Hg contamination in the Everglades. Zillioux et al. (1993)
in a review of Hg cycling and effects in freshwater wetland ecosystems state that both abiotic and
biotic methylation processes are likely to occur in wetlands.
One of the most noticeable changes in the Everglades ecosystem in recent years is
eutrophication (Figure 8.2). Pristine Everglades wetland soils are not highly reduced (anaerobic),
even when flooded (Bachoon and Jones 1992). Primary production and microbial respiration in
the Everglades are apparently limited by TP, with average TN to TP ratios (TN:TP) as high as
170:1 reported in Everglades waters (Scheidt et al. 1989, SFWMD 1992). Typically, TP limits
primary production when TN:TP ratios exceed 20:1 to 30:1 (Redfield 1958). However, TN
8-6
-------
includes organic N contributions and the bioavailability of organic N to microbial assemblages in
the Everglades is not well known. Effective N:P ratios, therefore, might be lower than 170, based
on TN:TP. Phosphate enrichments in Everglades soils and sediments have accelerated production
of organic matter, resulting in a change from oligotrophic to eutrophic ecosystems in some areas,
an increased water column and sediment oxygen demand, and the establishment of anaerobic
conditions. Under anoxic conditions, inorganic Hg is converted to MeHg by sulfur bacteria and
bioaccumulated in the food chain. Methylation of inorganic Hg in Everglades soil samples has
been shown in laboratory tests to increase with increased nutrient concentrations (Barkay 1992).
However, highly eutrophic soils showed a decline in methylation or an increase in demethylation
(Barkay 1992). The methylation/ demethylation (M/D) ratios in soil, sediment, and water and the
influence of nutrients (TN and TP) on these processes can result in both increased methylation
and demethylation of Hg (Figure 8.2). This relationship has yet to be elucidated in the
Everglades. Surface flow of water (Figure 8.2) may be an important transport mechanism that
moves sediment, TP, inorganic Hg, and organic Hg off the EAA via canals to the downstream
WCAs and ENP. An average of 204 metric tons (225 tons) of TP flow from the 3,000 km2
(700,000 acres) of the EAA into downstream habitats from 1980 to 1996 (SFWMD 1997c)
resulting in changes in wetland plant communities (Nearhoof 1992).
Evasion or soil degassing of Hg is an important component of the biogeochemical model
describing the Hg cycle (Figure 8.2). Evasion from seepage lakes has been measured on northern
temperate lakes (Fitzgerald et al. in press), but wetlands in the Everglades have higher ambient
temperatures than temperate seepage lakes, so evasion rates are likely different. Evasion
estimates also are likely to be confounded because of highly managed hydroperiods. Evasion
estimates from wetland habitats, other land uses, and open waters are important components of
the model that must be defined.
A definition of the aquatic and terrestrial bioaccumulation pathways (Figure 8.2) also
must be determined. Critical path analyses should be made for the top terrestrial predators (e.g.,
fish, birds, reptiles, and mammals) in several habitat types in the Everglades ecosystem with
particular attention to endangered or threatened species.
Development and operation of the C&SF canal system for flood control has greatly
modified the hydrology of the Everglades over the last 40 years. The result is that parts of the
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study area presently have shorter hydroperiods while other areas have longer hydroperiods than
occurred historically. The process of flooding soils by itself, however, does not appear to lead to
anaerobic conditions and the methylation of Hg in the pristine Everglades system. It is the
development of reducing conditions that leads to methylation. In addition, reducing conditions
can occur in microhabitats within the peat. Anaerobic zones can be contiguous to oxic zones in
these microhabitats. However, the interaction of hydroperiod (duration of inundation) with the
methylation process may result in generation of MeHg under some conditions (e.g., alligator
holes are naturally nutrient enriched, maintain reducing conditions, and contain some fish). Thus,
despite the presence of flooded soils, Hg methylation may be expected to be limited in the
absence of eutrophic conditions. Recycling from the soil and water surfaces, however, might be
an important loss from the system under water management conditions.
An ecological risk assessment must evaluate the impacts of Hg on the entire ecosystem,
as well as selected rare and endangered species. The identification of these components will
determine the factors and processes to be incorporated into mathematical models of the
biogeochemical cycling of Hg in the Everglades ecosystem. An a priori Hg model for the South
Florida Everglades ecosystem was developed to help guide the study.
8.3 Results
8.3.1 Mercury Loading
Hg loading to the Everglades was estimated from bi-weekly monitoring of water samples
that were collected at S-5A, S-6, S-7, and S-8 during 1994,1995, and 1996. Sampling at these
four structures was used to estimate the mass transport of Hg through the canal system from the
EAA to the downstream Everglades. Total discharge was measured at each of these structures by
SFWMD. The total biweekly discharge was multiplied times the biweekly Hg concentration to
obtain the Hg mass for the biweekly period. These masses were summed to obtain seasonal and
annual estimates. The loading of THg in the water flowing south through the structures was
estimated at 0.5 to 0.6 kg during the dry season and 1.3 to 2.7 kg during the wet season. Annual
estimates of THg loadings from the EAA ranged from 1.8 to 3.3 kg/yr. Estimates of the loading
of MeHg flowing through the structures was 0.1 to 0.2 kg during the dry season and 0.2 to 0.4 kg
during the wet season. Annual estimates of MeHg loading from the EAA ranged from 0.3 to
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0.6 kg/yr. Atmospheric loading of THg from wet deposition to the system was estimated at
between 40 and 50 kg/yr, clearly indicating that most of the Hg entering the system comes from
atmospheric deposition.
8.3.2 Water Quality Patterns
The methylation of inorganic Hg to its bioaccumulated form (i.e., MeHg) occurs under a
favorable set of environmental conditions. These conditions include anoxia (Matilianen 1995),
moderate TS04 concentrations (Gilmour et al. 1992), moderate TOC concentrations (Driscoll et
al. 1994), low pH and/or alkalinity concentrations (Rudd 1995). In general, oligotrophic, rather
than eutrophic, aquatic ecosystems have Hg contamination problems. Wetlands are particularly
conducive to Hg methylation (Zillioux et al. 1993). In general, southern and southeastern aquatic
ecosystems under fish consumption advisories have these water quality characteristics (Southern
States Mercury Task Force 1997). Based on these patterns observed in other wetland systems,
and the conceptual model developed for the Everglades ecosystem, analyses were performed to
evaluate these observations and associations in the South Florida ecosystems.
The following sections present the spatial patterns, gradients, and associations among
water quality constituents in South Florida canal and marsh ecosystems.
8.3.2.1 Canal Water Quality by Subarea
Exploratory analyses (i.e., cluster, factor, and principal components analyses) were used
to investigate possible relationships among THgF, MeHg concentrations in water, and the water
quality constituents discussed above. Principal components analyses indicated TOC, TS04, and
TP grouped as one principal component and MeHg as a second component in describing variance
in THgF. Analyses subsequently focused on the spatial patterns and gradients in these five
constituents.
Distinct gradients by subarea in canal water quality occurred with each of these
parameters. TOC showed a strong gradient from the EAA canals through the WCA canals
declining to significantly lower concentrations in the ENP canals (Figure 8.3). If the 95%
confidence intervals around the median (the notch) in the box and whisker plots are
nonoverlapping, the medians are significantly different at the 5% level (P<0.05). Seasonally the
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gradient was most pronounced during the wet season with significant declines from the north to
the south (Figure 8.3). TOC concentrations in BCNP were similar to ENP. TOC concentrations
during the dry season remained higher in the EAA and WCA with a significant decline in ENP
and BCNP (Figure 8.3). TS04 demonstrated a similarly strong north to south gradient
(Figures 8.4 and 8.5) with higher concentrations occurring during the wet season (Figure 8.5).
Significant declines in TS04 occurred between the EAA and WCA canals during both wet and
dry (Figure 8.5) seasons; TS04 concentration in the WCA and ENP canals were not significantly
different (P<0.05) during either season. A well defined north to south gradient also occurred with
TP significantly declining along this latitudinal gradient. A significant gradient in TP persisted in
the subarea canals through both wet and dry seasons, but TP concentrations were higher in the
EAA during the wet season (Figure 8.6 and 8.7).
The source of the highest concentrations for each of these variables was the EAA. The
high TOC concentrations in water were most likely enhanced by the runoff of agricultural
stormwater, which increased during the wet season. The TS04 emanating from the EAA may
result from both fertilizer applications and the entrainment of connate seawater in groundwater
during pumping in the wet season (Miller 1988). High TP concentrations in the EAA result from
fertilizer application, soil subsidence, and water management (Izuno et al. 1991, Coale et al.
1994, Stone and Legg 1992).
The THg concentrations in water among the subarea canals for all cycles combined did
not show a significant north to south gradient as observed in the other constituents (Figures 8.8
and 8.9). However, a comparison of the wet and dry (Figures 8.8 and 8.9) season samples by
subarea indicated higher THg concentrations in water occurred during the wet season when a
significant decline was evident from north to south. THg concentrations in canal water could be
dominated by the runoff of atmospheric wet deposition and particulate loading from the EAA
during the wet season. A comparison of the canal data for all cycles combined indicates MeHg
concentrations were similar in the EAA and WCA subareas and decline significantly (P<0.05)
downstream in ENP and BCNP (Figure 8.10). A significant MeHg gradient declining from the
EAA through the WCA to ENP occurred during the wet season (Figure 8.10). However, during
the dry season (Figure 8.10), MeHg concentration in the WCA showed significantly higher
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concentrations than in the EAA or ENP. The MeHg concentrations in the ENP were significantly
lower statistically than in the EAA and WCA during both seasons.
Overall, the wholebody mosquitofish THgF concentrations were found to be lowest in the
EAA while significantly higher concentrations were found in mosquitofish from the WCA, ENP,
and BCNP regardless of season (Figures 8.11 and 8.12). The highest concentrations occurred in
mosquitofish from the WCA canals, but these concentrations were not statistically different from
the THgF concentrations in mosquitofish from the ENP and BCNP canals. When THg
concentrations in water and THgF concentrations in mosquitofish are evaluated, THg
concentrations in water do not provide a good indication of THgF concentrations in
mosquitofish; however, water concentrations might provide information on atmospheric
deposition and source.
8.3.2.2 Canal Water Quality by Latitude
Scatter plots of combined canal data for all four cycles are presented by latitude in
Figure 8.13. These plots show the gradients from north to south in TOC, TS04, and TP, a
gradient for MeHg in water was less apparent. The THgF concentrations indicated a cluster of
high values between Alligator Alley and Tamiami Trail bounding the southern two-thirds of
WCA3. This indicated that Alligator Alley and Tamiami Trail were reasonable latitudinal
demarcation points on which to parse the data for this analysis.
An ANOVA was conducted on constituent concentrations north of Alligator Alley,
between Alligator Alley and Tamiami Trail, and south of Tamiami Trail (Table 8.2). These
latitudinal subregions showed significant (P<0.05) differences in the geometric mean
concentrations between subregions in TP and TOC. TS04 showed a significant (P<0.05)
concentration decline from north of Alligator Alley to between Alligator Alley and Tamiami
Trail with no significant difference in TS04 concentrations between Alligator Alley and Tamiami
Trail and the area south of Tamiami Trail. MeHg concentrations in the areas north and south of
Alligator Alley were equal, but a significant (P<0.05) decline occurred in ENP. In contrast, THgF
in mosquitofish was significantly (P<0.05) higher between Alligator Alley and Tamiami Trail
than in either the north or the south sectors.
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Table 8.2 Comparison of canal constituent geometric means concentrations in water by
latitude. Sample size in parenthesis. (> or < is statistically significant, P<0.05)
Latitude
Constituent0
North of
Alligator Alley
Alligator Alley -
Tamiami Trail
South of
Tamiami Trail
TP (Mg/L)
79(114)
>
24 (64)
>
14(21)
TOC (mg/L)
26(114)
>
18(64)
>
11(21)
TSO4 (mg/L)
27(114)
>
7(64)
8(21)
MeHg (ng/L)
0.2(114)
0.2 (64)
>
0.1 (21)
THg Fish (/ig/kg)
33(114)
<
83 (64)
>
37(21)
THg (ng/L)
1.6(114)
1.2(64)
>
0.8 (21)
An ANOVA on a seasonal comparison of the canal data of the two wet and two dry
seasons combined (Table 8.3) showed a more pronounced gradient in TP concentrations from
north to south during the wet season when compared to the dry season, which had a
concentration gradient (P<0.05) through all three subareas. A significant (P<0.05) gradient in
TOC occurred during the wet season. During the dry season, the decline in the canal water TOC
concentration was significant only south of Tamiami Trail in ENP. The north to south gradient in
TS04 only occurred between the northern two subregions and was twice as high during the wet
season when compared to the dry season. The lower concentrations of TS04 south of Alligator
Alley may not be significant because the MDLs vary from 5 to 2 mg/L for these analyses. MeHg
in water showed a significant (P<0.05) gradient during the wet season. The gradient was less
pronounced during the dry season and only occurred south of Tamiami Trail.
THgF in mosquitofish was significantly higher (P<0.05) during both wet and dry seasons
between Alligator Alley and Tamiami Trail with the highest THgF concentrations in the dry
season.
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Table 8.3 Comparison of canal constituent geometric mean concentration, by latitude and by
season. Sample size in parenthesis. (> or < is significant, P<0.05)
Latitude
Constituent
North of
Alligator Alley
Alligator Alley -
Tamiami Trail
South of
Tamiami Trail
TP (MgfL)
Wet
101 (56)
>
18(35)
= 10(8)
Dry
62 (58)
>
36 (27)
>
19(10)
TOC (mg/L)
Wet
31 (56)
>
16(35)
>
10(8)
Dry
22 (58)
21(27)
>
11(10)
TS04 (mg/L)
Wet
40 (56)
>
7(35)
= 10(8)
Dry
19(58)
>
6(29)
6(13)
MeHg (ng/L)
Wet
0.4 (56)
>
0.2(35)
>
0.1 (8)
Dry
0.2 (58)
0.2 (29)
>
0.1 (13)
THgF Oug/kg)
Wet
30 (50)
<
69 (34)
>
27 (8)
Dry
36 (58)
<
103(29)
>
45(13)
THg (ng/L)
Wet
2.3 (56)
>
1.3 (35)
0.8(13)
Dry
1.1 ("58)
1.2(29)
0.9(13)
8.3.3 Transect Gradients
8.3.3.1 Water
Four transects were selected that had been previously studied by others (Doren
et al. 1996) to investigate the differential effects of TP on the eutrophication of the marsh.
Because this historical information was available and the differences in nutrient impacts on each
transect were known, the interrelationships of TP and other constituents along the same transects
were investigated. The transects were oriented 90° to a canal and extended various distances into
the marshes (Figure 8.14). The transect in LNWR was oriented perpendicular to the flow. The
WCA3 transect was oriented upstream or opposite the flow, while the transects in WCA2 and
ENP were oriented downstream or with the flow.
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TP concentrations in water on each transect are shown in Figure 8.15. A sharp decline in
TP was apparent within the first 1,000 m (3,281 feet) in LNWR indicating the influence of
agricultural stormwater runoff in the canals surrounding LNWR. Stormwater does not penetrate
the center of LNWR because the interior is a rain driven marsh system. The transect in WCA2
showed the highest TP concentrations in water, which had a sharp decline from about 90 Aig/L
near the canal to about 40 /ig/L 2,000 m (6,562 feet) from the canal, declining further to about
10 //g/L 8,000 m (26,246 feet) into the marsh. The lowest transect TP concentration (~10/Ug/L)
was measured along the WCA3 transect. TP delivery through S12C into ENP tended to increase
water concentrations to about 15 //g/L across most of this transect. TOC in water declined from
25 to 20 mg/L about 2,000 m (6,562 feet) from the canal along the LNWR transect. TOC
concentrations also decreased from 32 to 24 mg/L about 2,000 m (6,562 feet) from the canal
along the WCA2 transect, but then increased again to about 32 mg/L and remained relatively
constant about 8,000 m (26,246 feet) from the canal on into the marsh. TOC also decreased after
about 2,000 m (6,562 feet) along the WCA3 and ENP transects (Figure 8.16). There were few
differences among the transects or apparent gradients in TOC concentrations in water. TS04
concentrations in water declined from about 15 to 5 mg/L within 3,000 m (9,842 feet) of the
canal in LNWR and remained at those concentrations along the remainder of the transect
(Figure 8.17). TS04 concentrations were highest in WCA2 ranging from 25 to 50 mg/L with no
apparent trend along the length of the transect. TS04 in WCA3 was consistently at the MDL of 2
mg/L; however, ENP showed a decline in TS04 from 23 mg/L near the canal to baseline
concentrations of 2 mg/L 5,000 m (16,404 feet) along the transect. Higher TS04 concentrations
near the canal along the ENP transect indicate that stormwater is transported through the canal
system from upstream and discharged into ENP.
THg concentrations in water along the transect in (Figure 8.18) LNWR initially increased
from the canal toward the center. THg concentrations along the WCA2 transect showed a sharp
increase about 500 m (1,640 feet) from the canal with declining concentrations from the canal
along the remainder of the transect until the end when THg concentrations increased again.
WCA3 shows a consistent background THg concentration of about 1 ng/L. MeHg concentrations
in water on transects in LNWR and ENP show increased concentrations beyond about 3,000 m
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(9,842 feet) from the canal, while MeHg concentration along the WCA2 transect decline rapidly
near the canal with an increase between 8,000 to 9,000 m down the transect (Figure 8.19). No
trend was seen along the WCA3 transect.
The ratio of MeHg to THg is plotted in Figure 8.20. Increasing trends down the WCA2
and ENP transects are apparently reaching a maximum of 45% on each. A MeHg response
reaching 60% in LNWR near the interface of marsh and stormwater was also evident. No trend in
the percent MeHg in water was apparent on the transect in WCA3.
THg in wholebody mosquitofish in LNWR showed increased concentrations down the
transect (Figure 8.21). A similar pattern also was apparent along the ENP transect. An increase of
THg in fish begins beyond 8,000 m (26,246 feet) along the WCA2 transect. The THg
concentrations in fish along the WCA3 transect are highest near the canal and declined into the
marsh.
8.3.3.2 Soil Parameters
Sulfide in soil expressed as bulk density (i.e., mg/cc) indicated a maximum concentration
of 0.03 mg/cc within 1,500 m (4,921 feet) of the canal, which declined toward the center of
LNWR (Figure 8.22). A similar relationship occurred on the ENP transect. The concentrations
remained somewhat higher in WCA2 throughout the length of the transect. The lowest soil
sulfide concentrations were found along the entire length of the transect in WCA3.
TP expressed as /^g/cc indicated an exponential decline within the initial 4,000 m
(13,123 feet) of the LNWR transect (Figure 8.23). A linear decline occurred in WCA2, which
remained generally higher throughout the transect length. The transect in the ENP showed an
initial rapid decline near the canal; however, TP concentrations then increased and paralleled the
linear decline in TP observed along the WCA2 transect. The concentrations in WCA3 were
nearly constant at 0.06 /^g/cc except for immediately adjacent the canal.
THg in soil expressed by bulk density indicated a relatively consistent pattern on all
transects (Figure 8.24). MeHg concentrations were found to be higher on transects in LNWR,
WCA2, and WCA3 and lowest in ENP (Figure 8.25). Highest concentrations tended to occur
either near the canal (WCA3) or within about 4,000 m (13,123 feet) of the canal, LNWR and
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WCA2, but MeHg concentrations were highly variable. In general, BAFs in mosquitofish were
highest near the canal and decreased toward the marsh interior (Figure 8.26). BAFs in the ENP
initially declined away from the canal and then slowly increased toward the interior.
8.3.4 Marsh Characteristics
8.3.4.1 Marsh Water Quality by Subarea
Box plots were used to analyze the water variables identified by principal components
analysis as influencing the distribution and speciation of Hg. These variables were initially
analyzed by geographic subarea to identify the existing water quality relationships and possible
gradients in the system. The combined marsh data (all four sampling cycles) showed a significant
north to south gradient in median TOC concentrations from WCA2 to ENP (Figure 8.27). The
median concentration in LNWR was 22.6 mg/L. TOC concentrations usually increase during the
dry season; however, because the April 1995 dry season was exceptionally wet, only the May
1996 dry sample was significantly higher (P<0.05) than either wet season sample. Significantly
higher TS04 concentrations (P<0.05) occurred in WCA2 with a median concentration of 34 mg/L
(Figures 8.28 and 29). The median TS04 concentrations in WCA3 and ENP were 3.3 mg/L and
2.0 mg/L, respectively. With only a small peripheral area of the LNWR marsh affected by
stormwater runoff, the central marsh in LNWR was near the minimum TS04 detection limit of
2.0 mg/L.
The concentrations of TP in the marsh system were much lower than those found in the
canal system indicating the canals load the marsh at numerous overflow points. A clear gradient
decreasing downstream occurred with TP concentrations in the canal system; the TP
concentration gradient in the marsh was much less, ranging from a median TP concentration of
17.8 Mg/L in WCA2 to 14.8 /ug/L in WCA3 and 10 /ug/L in ENP. Dry season concentrations were
approximately twice the wet season concentrations. The high TP concentrations indicated in
Figures 8.30 and 8.31 occurred in random samples near overflowing canals where canal water
high in TP directly influenced the marsh.
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TN was sampled in the marsh water only during the wet and dry seasons in 1996. A TN
gradient was apparent from WCA2 through ENP (Figure 8.32). A similar gradient was present in
both seasons; however, concentrations were higher during the dry season.
There were no apparent trends by marsh subarea for THg concentrations in water
(Figures 8.33 and 8.34). LNWR exhibited the highest median THg concentration of 3.4 ng/L.
The wet season concentrations were somewhat higher than the dry season, which may be due to
increased wet deposition. When distribution of MeHg in marsh water by subarea was examined,
MeHg in marsh water was slightly higher in LNWR than the other subareas (Figures 8.35 and
8.36). There was no significant difference (P<0.05) in MeHg in water concentrations downstream
through WCA3. A significant (P<0.05) decline in MeHg concentrations occurred in the ENP and
BCNP. The variance in MeHg concentrations was greater in the dry season than in the wet
season.
THgF concentrations in wholebody mosquitofish were significantly higher in WCA3 with
a median of 185 ywg/kg and ENP with a median of 176 ,ug/kg than the subareas to the north
(Figure 8.37), which all had medians less than 115 /ig/kg. This was apparent during both wet and
dry seasons. The bioaccumulation factor (BAF) was consistently low in LNWR, WCA2, and
ROT-EAA at less than 180,000 (Figure 8.38). The median BAF increased to 354,000 in WCA3
and continued to increase in ENP to 729,000, which was similar to the BAF in BCNP. The
increased BAF downstream in WCA3, ENP, and BCNP was significantly higher (P<0.05) than
LNWR, WCA2, and ROT-EAA.
Box plots of the combined THg in floating periphyton by subarea indicate that the highest
concentrations occurred in LNWR, WCA2, and WCA3, with significant declines in ENP and
BCNP (Figures 8.39 and 8.40). Seasonally the wet season periphyton samples showed
consistently higher concentrations across all subareas with an apparent decline from northern to
southern subareas. MeHg in floating periphyton was highest in LNWR with a linear decline
downstream through all areas (Figure 8.41). The consistency in this MeHg gradient in periphyton
indicates methylation occurs throughout the system, with higher concentrations occurring in the
north. The incidence of floating periphyton was most consistent in WCA3 and ENP.
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THg in soil periphyton did not show a consistent pattern in the data (Figure 8.42). MeHg
in soil periphyton indicated the highest concentrations occurred in LNWR declining to ENP
(Figure 8.43); however, the incidence of soil periphyton, which formed a distinct layer on the
surface of the soil which could be excised from the top of the soil core, was most prevalent in
WCA3 and ENP. The high concentrations of MeHg in periphyton in LNWR indicate that
methylation is also very active in this subarea.
The median soil THg expressed by bulk density was significantly lower in LNWR than
found over the remainder of the study area (Figure 8.44) with increasing concentrations from
WCA2 to WCA3 and ENP. The soil MeHg expressed by bulk density was significantly higher
(P<0.05) in LNWR than in WCA2, a pattern opposite that for soil THg (Figure 8.45). Soil MeHg
concentrations also were higher in WCA3, ENP, and BCNP during both the wet and dry seasons.
8.3.4.2 Marsh Water Quality by Latitude
Scatter plots of combined marsh data for all four cycles are presented by latitude in
Figure 8.46. These plots show the gradients in TOC and TS04 declining from north to south.
Although there is a smaller TP gradient in the marsh than canals there are high values in the
northern part of the system, which occurred in overflow areas near canals that carried water high
in TP. There was also an apparent decline in TP concentrations about midway through ENP,
which may indicate the southern extent of canal water influence on the marsh. MeHg
concentrations in water were high in LNWR and WCA3 and low in ENP. THg concentrations in
mosquitofish were highest in WCA3 extending into northern ENP. Latitudinal analysis of these
data using Alligator Alley and Tamiami Trail as demarcation points was made to achieve a
comparison with the canal data.
An ANOVA was conducted on three latitudinal subsets of the data (north of Alligator
Alley, between Alligator Alley and Tamiami Trail, and south of Tamiami Trail) with all cycles
combined (Table 8.4). Analysis of the data in these latitudinal subregions showed significant
differences (P<0.05) in the geometric means for TOC, which declined from north to south
through the system. A significant difference in the data was found for TS04 between the northern
two sectors. Data from the southern sites were typically near the MDLs of 2 and 0.5 mg/L. TP in
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water showed a significant decline from north of Alligator Alley to the area between Alligator
Alley and Tamiami Trail. MeHg in water declined significantly from north to south. The
concentration of THgF in wholebody mosquitofish was significantly lower (P<0.05) north of
Alligator Alley and increased to comparable concentrations in the two southern subareas.
Table 8.4 Comparison of geometric means of marsh constituents by latitude. Sample size is
in parenthesis. (< or > is statistically significant, P <0.05)
Constituent
Latitude
North of
Alligator Alley
Alligator Alley -
Tamiami Trail
South of
Tamiami Trail
TOC (mg/L)
27 (146)
> 19 (157)
> 16 (138)
TS04 (mg/L)
7 (146)
> 3 (157)
2 (138)
TP (Mg/L)
18 (146)
> 12 (157)
10 (138)
MeHg (ng/L)
0.5 (145)
> 0.4 (156)
> 0.2 (138)
THgF Gug/kg)
88 (129)
< 1550 (145)
151 (120)
THg (ng/L)
2.3 (146)
> 1.8 (157)
1.8 (137)
An ANOVA also was conducted on the three latitudinal subareas by season (Table 8.5).
There were significant declining gradients of TOC during the wet and dry seasons from north of
Alligator Alley to between Alligator Alley and Tamiami Trail. The TS04 gradient was the same
for both seasons with a significant decline from north of Alligator Alley to between Alligator
Alley and Tamiami Trail with higher dry season concentrations. A complete assessment of this
parameter was limited by high detection levels. TP concentrations in water showed a gradient
from north of Alligator Alley to south of Tamiami Trail for the wet and dry seasons, respectively.
The TP concentrations were nearly twice as high during the dry season. MeHg in water showed a
significant decline downstream in all three areas during the wet season and a significant decline
between the southern two areas (i.e., Alligator Alley - Tamiami Trail to south of Tamiami Trail)
in the dry season. The concentrations in the dry season were approximately twice as high as those
of the wet season. The THgF concentrations in wholebody mosquitofish were consistently lower
north of Alligator Alley during both seasons. The THgF concentrations in mosquitofish were
higher in the dry season south of Alligator Alley.
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Table 8.5 Comparison of marsh geometric mean constituents by latitude and season. Sample
size in parenthesis. (> or < is statistically significant, P<0.05)
Latitude
Constituent
North of Alligator
Alley
Alligator Alley -
Tamiami Trail
South of Tamiami
Trail
TOC (mg/L)
Wet
7(84)
>
3(81)
2 (77)
Dry
8(62)
>
3(76)
= 2 (61)
TS04 (mg/L)
Wet
15 (84)
>
8(81)
8 (77)
Dry
25(62)
>
20 (76)
= 16(61)
TP (Aig/L)
Wet
24 (84)
>
15(81)
> 12 (77)
Dry
32 (62)
>
25 (76)
> 23 (61)
MeHg (ng/L)
Wet
0.4 (84)
>
0.2(81)
> 0.1 (77)
Dry
0.7(61)
0.6 (75)
> 0.4(61)
THgF (Aig/kg)
Wet
94* (76)
<
124 (77)
= 130 (73)
Dry
81* (53)
<
199 (68)
= 195 (47)
THg (ng/L)
Wet
2.6* (84)
>
2.0 (81)
1.7 (77)
Dry
2.0 (62)
1.7(76)
1 .9(60)
8.3.4.3 Marsh Spatial Analysis
A spatial analysis of the TOC data by cycle is shown in Figure 8.47. The maps of the wet
season show high TOC water concentrations primarily occur in WCA2 and northern WCA3 and
flow across the marsh in a downstream direction. The highest water conditions and flow rates
occurred during the September 1995 sample event, which showed a clear gradient in TOC
flowing across the marsh system. Water concentrations of TOC decrease downstream across the
system. The April 1995 and May 1996 dry seasons and the September 1996 wet season indicate
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areas of higher TOC concentrations in ENP Shark Slough flowway, which may result from water
brought in via the canal system. The dry season in May 1996 was the driest sample period in the
study, and it is evident that with the reduced water volume and decreased flow across the marsh
the TOC concentrations generally increased throughout the system.
Maps of water TS04 concentrations in the system (Figure 8.48) show gradients similar to
those observed with TOC. The concentrations are consistently highest in WCA2 due to the
overflow of canal water, which generally spreads downstream across northeastern WCA3. The
reduction of TS04 appears to occur rapidly across the system. There is also an indication of
transport of water with higher TS04 concentrations to the northern ENP via L67 extension.
Future monitoring by USGS should further resolve the TS04 gradient with an MDL below
0.5 mg/L.
Spatial maps of TP (Figure 8.49) in marsh system water are leveraged by the relatively
few high concentrations which were found in random samples taken near canals where high TP
water was flowing into the marsh. The transport of high TP concentrations downstream via the
canal system to ENP is also evident. TP concentrations in excess of 50 /^g/L affect an area of less
than 5% of the marsh that occurs, primarily near canals. A very well defined gradient in TP can
be seen in the wet season September 1996 sample showing most of the marsh at less than
10 /xg/L with concentrations between 10 and 50 /ugfL limited to the extreme northern WCA3,
WCA2, and the perimeter of LNWR. During the dry season in May 1996, higher TP
concentrations appear to occur in the zone between the dry and wet areas where the shallowest
water occurs.
Spatial analysis of MeHg in water (Figure 8.50) shows an area in excess of 0.5 ng/L in
northern WCA3 during the high flow wet season in September 1995. A similar area was found
below Alligator Alley in WCA3 during the dry season in April 1995. Similar concentrations were
apparent below Alligator Alley in 1996. High MeHg concentrations occurred in LNWR and
WCA2; but there was no consistent pattern.
A spatial map of the combined MeHg concentrations in floating periphyton for all four
cycles (Figure 8.51) shows high concentrations in WCA3 south of Alligator Alley. Floating
periphyton, however, were not consistently found across the entire marsh system as indicated by
8-21
-------
the sample points where it occurred. The most consistent distribution of floating periphyton was
south of Alligator Alley extending into the area of Shark Slough. While soil periphyton had even
a more discontinuous coverage; the combined data indicates a periphyton Hg hot spot in WCA3
south of Alligator Alley (Figure 8.52). MeHg in soil, however, (Figure 8.53) did not show a
distribution similar to the periphyton. Soil MeHg concentrations were higher across the northern
extreme of WCA3 and in LNWR. A homogenate of the top 10 cm of soil did not indicate a hot
spot in soil MeHg south of Alligator Alley.
Spatial maps of the THgF concentrations in wholebody mosquitofish (Figure 8.54)
showed a consistent hot spot in WCA3 south of Alligator Alley during each synoptic sample.
This THgF in mosquitofish hot spot tended to continue to the south into ENP reaching
approximately halfway down Shark River Slough. Areas with THgF concentrations in
mosquitofish greater than 200 //g/kg were rare north of Alligator Alley. Due to the consistency of
the areas of high THgF in mosquitofish between cycles all the data were combined (Figure 8.55 )
along with the rookery locations with Hg concentrations from Great Egret chick feathers
(Frederick et al. 1997). The highest concentrations in feathers occurred in the THgF hot spot for
mosquitofish with lower Hg concentrations in chick feathers at successive rookery locations to
the south and east of the hot spot. The similar spatial distribution of MeHg in water, periphyton,
and fish, indicates a consistency in the location of enhanced bioaccumulation in the food chain
south of Alligator Alley.
8.3.5 Eastern Mosquitofish
A predator protection criteria of 0.1 mg/kg THg for prey species has been proposed by the
USFWS (Eisner et al. 1987). The eastern mosquitofish, Gambusia holbrooki, wholebody THgF
concentrations were presented in the proceeding section. About 15% of the canal miles and
almost 70% of the marsh area have mosquitofish with THgF concentrations exceeding the
predator protection criteria of 0.1 mg/kg. Because the mosquitofish is a prey species for
piscivorous fish and birds and is an excellent indicator of Hg bioaccumulation, additional
analyses were conducted on the mosquitofish populations in the canals and marsh. The purpose
of these analyses were to determine if differences in population attributes or feeding habits
8-22
-------
among subareas or among latitudes might contribute to Hg bioaccumulation. The results are
presented in Appendix D.
8.4 Synthesis
Hg loading to the South Florida Everglades ecosystem was dominated by atmospheric
deposition, rather than loading from theEAA. Deposition was relatively uniform spatially over
South Florida, but there were definite seasonal patterns with the greatest Hg loading occurring
during the wet seasons. Even though the spatial deposition of Hg was relatively uniform, there
were distinct north to south gradients in Hg in water, periphyton, and mosquitofish and other
water quality constituents in both the canal and marsh systems. In contrast to Hurley et al. 1998,
the highest MeHg concentrations in water were measured in the north while the highest Hg
concentrations in mosquitofish occurred in the central area of the marsh and canal, between
Alligator Alley and Tamiami Trail. The hot spot in mosquitofish Hg concentrations also
coincided with peak Hg concentrations in periphyton and Great Egret chick feathers. There were
complex relationships among water depth and TOC, sulfate and TP concentrations and MeHg
concentrations in periphyton, and Hg in mosquitofish. The canals appeared to play a major role
in the transport of TP from the canal to the marsh, while the marsh was the primary site for the
methylation of Hg and might contribute to the higher fish Hg concentrations in the canals.
Numerous preliminary studies related to the processes of mercury cycling in the Everglades
ecosystem (Hurley et al. 1998, Krabbenhoft et al. 1998, and Cleckner et al. 1998) have been
reported by the USGS ACME effort. Additional process oriented reports are under development
from this group, however, a revised conceptual model for the marsh ecosystem is discussed in
greater detail in Chapter 10.0, Synthesis and Integration.
8-23
-------
4. Evasion
Hg*
1. Global and Regional
Atmospheric
Input
Hg*, Hg**, MeHg
N &c. P
2. Peat Soils
Hg**, MeHg
Methylation/Demethylation^
Deposition
Water
9. Critical Path Analysis
(Birds and Mammals, etc.)
Hg** — MeHg — Uptake
^ (fish)
Sulfide Reducing
Bacteria
;'Meth)
-------
Canal Data
0> 75% ¦» 3 MID RANGE
* > 75% + I 5 MIDRANGE
75V. ~ I 5MLDRANGE
75%
MEDIAN > MID RANGE
1 25%
1 25%- I 5 MIDRANGE
100
80
\ 60
U
O 40
H
20
All Data
*
1
1
" I
J
*
T
-
r
1
T
1
w
T
i
_L
l
EAA
WCA
ENP
BCNP
EAA
WCA
ENP
BCNP
100
80
J
\ 60
U
O 40
20
Wet Seasons
1
1
£ £
i i
¦£? "
i
EAA
WCA
ENP
BCNP
Figure 8.3 Notched box and whisker plots comparing canal TOC in subareas during dry and
wet seasons.
8-25
-------
26 A
26.6-
26.4-
_ 26.2-
26.0-
25.8-
25.6-
25.4-
SULFATE IN
WATER
©—x o X—e-
-X—X-
^6
-**-
-X-
X
XX ikj
ikAd —H*
ug/L
o
1.0 to 4.9
X
5.0 to 9.9
~
10.0 to 29.9
II
30.0 to 59.9
•
60.0 to 180.1
-81.0
9 fli_
-80.8
-80.6
-80.4
LONGITUDE, decimal degrees
Figure 8.4 TS04 concentrations in canals during the study period.
8-26
-------
Canal Data
95%
CONFIDENCE
ON MEDIAN
200
150 -
60
8
O 100 -
3
C/5
50
0> ?5% ~ 3 MtDRANGC
* > 75V, + I 5 MIDRANGE
75V. ~ I 5 MIDRANGE
MEDIAN ) MIDRANGE
25% ¦ I 5 MIDRANGE
EA A
WCA
ENP
BCNP
_>
\
a
200
150
100
50
EAA
WCA
ENP
BCNP
200
-J
\
M
E
3
Ui
150
100
50
EAA
WCA
ENP
BCNP
Figure 8.5 Notched box and whisker plots comparing canal TS04 in subareas during dry
and wet seasons.
8-27
-------
Canal Data
600
500
^ 400
M
3
Oh 300
100
0
O > 75% * J MIDRANGE
• > 75% ~ I 5 MIDRANGE
7S% * 1 5 MID RANGE
75V.
25%
25% - 1 5 MID RANGE
All Data
*
*
1
1
1
- M
I
f .
4-
*
o
o
*
T
EAA
WCA
ENP
BCNP
600
500
^ 400
u>
3
bu" 300
(2 200
100
0
Dry Seasons
i
*
T
*
T
1
-------
Canal Data
200
150 -
J
so
a
ft." 100
o
H
50
EAA
WCA
ENP BCNP
200
150 -
¦J
00
a
e.- 100 -
o
H
50
EAA
WCA
ENP
BCNP
200
EAA
WCA
ENP
BCNP
Figure 8.7 Plots of median canal TP for subareas with vertical lines indicating 95% confidence
interval of each median.
8-29
-------
J
\
00
c
eo
£
60
SC
£
0> 75% - 3 MID RANGE
* > 75% ~ | SM1DRANGE
75% ~ I 5 MIDRANGE
75%
Canal Data
16
12
8 -
EAA
WCA
ENP
BCNP
Dry Seasons
i
i
0
4= 4=
t T
i
* -
T
i
EAA WCA ENP BCNP
16
12 -
CQ
*
(2
EAA
WCA
ENP
BCNP
Figure 8.8 Notched box and whisker plots comparing canal THg in water by subareas during
dry and wet seasons.
8-30
-------
Canal Data
\
bo
£
~
BO
X
(2
3 -
1 -
EAA
WCA
ENP
BCNP
_)
\
BO
C
£
a
BO
X
(2
EAA
WCA
ENP
BCNP
EAA
WCA
ENP
BCNP
Figure 8.9 Plots of median canal THg in water for subareas with vertical lines indicating the
95% confidence interval for each median.
8-31
-------
0> 75% ~ 3 MIDRANGE
• > 75V. ~ I S MIDRANGE
75% ~ I 5 MIDRANGC
75%
Canal Data
« i
oc
E
>.
c,
EAA
WCA
ENP
BCNP
EAA
WCA
ENP
BCNP
EAA
WCA
ENP
BCNP
Figure 8.10 Notched box and whisker plots comparing canal MeHg in water for subareas during
dry and wet seasons.
8-32
-------
Canal Data
800
700 -
60
3
b.
500
400 -
J* 300
« 200 -
o
H
100
EAA
CONFIDENCE
ON MEDIAN
WCA
O > 75V. • 3 MID RANGE
• > 75V. • I 5 MIDRANGE
75*/. ~ I 5 MID RANGE
75V.
, 2S%
1 25V. - I 5 MID RANGE
ENP
BCNP
800
700
Wet
Seasons
1
i
i
00
\
00
3
600
-
-
.13
500
-
-
b.
c
400
-
o
-
no
X
300
-
o
-
a
200
-
0
*
£
100
_
o
T
T
0
+ ^
4- ^
i
EAA
WCA
ENP
BCNP
Figure 8.11 Box and whisker plots comparing canal THg in mosquitofish by subareas during dry
and wet seasons.
8-33
-------
Canal Data
•c
US
E
00
X
o
I-
160
120
80 -
a 40 -
EAA
WCA
ENP
BCNP
M
3
au
X
f2
160
120
80
a 40
EAA
WCA
ENP
BCNP
tm
3
JS
i/i
iZ
c
M
X
(2
160
120
80 -
« 40
EAA
WCA
ENP
BCNP
Figure 8.12 Medians of THg in mosquitofish in canals for subareas with vertical lines indicating
the 95% confidence interval for each median.
8-34
-------
80
60
40
20
0
1.5
1.2
0.9
0.6
0.3
00
.0
Canal Data
/ • • v •
• "I./•• ••• ». ^ •
F%f
/ • \ £
/ • •* • v J
/ • . \ <
/ * * N.
• " V:
W * .Tfc. . ^
* V*%
^ tc
/ 2 =!
* • • \ <
<
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*' ** ,/\ ¦
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/ B .• .\
/. •*. A
/ S • • I
0 26.5 26.0 25 5 25
Latitude
lot of selected constituents showing latitudinal gradients in i
8-35
-------
Figure 8.14 Location of four marsh transects sampled in April 1994 and canal water control
structures sampled on a biweekly basis from February 1994 through February 1997.
8-36
-------
Distance from Canal, m
Figure 8.15 Measurements of TP in water along marsh transects.
Figure 8.16 TOC concentrations along marsh transects.
8-37
-------
Distance from Canal, m
Figure 8.17 TS04 concentrations along marsh transects.
Distance from Canal, m
Figure 8.18 Measurements of THg in water along marsh transects.
8-38
-------
4000 8000 12000
Distance from Canal, m
16000
20000
Figure 8.19 MeHg concentrations along marsh transects.
1 ! 1
1 o
LNWR
A
WCA2
~
WCA3
/ / \\ y\ /
X
ENP
l IA / p~ 0
i i I
1
-
4000 8000 12000
Distance from Canal, m
16000
20000
Figure 8.20 Ratio of MeHg to THg in water along marsh transects.
8-39
-------
500
BO
^ 400
60
a
4 300
b
c
bo 200
5
§ 100
H
0
0 4000 8000 12000 16000 20000
Distance from Canal, m
1 1
1 ' O
LNWR
a
WCA2
-
~
WCA3 -
/ \ /Xx
—" *
ENP
i i
I I
-
Figure 8.21 THg in mosquitofish collected along marsh transects.
Distance from Canal, m
Figure 8 22 Sulfide in soils along marsh transects
8-40
-------
Distance from Canal, m
Figure 8.23 TP in soils along marsh transects.
1 1
1 o
LNWR
A
WCA2
-
~
WCA3 "
~h
X
X
ENP
i i
1 l
-
4000 8000 12000
Distance from Canal, m
16000
20000
Figure 8.24 THg in soils along marsh transects.
8-41
-------
0.10
0.00
O LNWR
a WCA2
° WCA3
x ENP
4000 8000 12000
Distance from Canal, m
16000
20000
Figure 8.25 Methyl Hg in soils along marsh transects.
8000 12000
Distance from Canal, m
16000
20000
Figure 8.26 Bioaccumulation along marsh transects.
8-42
-------
Marsh Data
95%
CONFIDENCE ¦;
ON MEDIAN 1
0> 75V. * 3 MIDRANGE
• > 75V. ~ I 5 MIDRANGE
75V. * I 5 MIDRANGE
75V.
MEDIAN
1 . 25V.
L 25V. ¦ I 5 MIDRANGE
LNWR
WCA2
WCA3
ENP
BCNP
LNWR
WCA2
WCA3
ENP
BCNP
LNWR WCA2
WCA3
ENP
BCNP
Figure 8.27 Notched box and whisker plots comparing marsh TOC in subareas during dry and
wet seasons.
8-43
-------
Marsh Data
93%
CONFIDENCE
ON MEDIAN
J
\
60
E
3
1/5
1000
100
10
O > 75'/. ~ 3 MID RANGE
* >7SV. ~ I 5 MIDRANGE
75% ~ I 5 MID RANGE
75%
MEDIAN / MIDRANGE
25%
25%- I 5 MIDRANGE
All bata
1 !
" : * l
(
0 O
1 T
^ E
r 1 ^
J 1
1
1 1
X TT
1 1
LNWR WCA2 WCA3 ENP BCNP
Dry Season's
1 1
-
t
<=?
0 o
r
i
*
i
i t
r>"
ps
1
i
~
L * o
i i
LNWR WCA2 WCA3 ENP BCNP
Wet Seasons
!
i
" ' x i
' T d
h ;
$
i i
p A
r t
^ -
i
LNWR WCA2 WCA3 ENP BCNP
Figure 8.28 Notched box and whisker plots comparing marsh TS04 in subareas during dry
and wet seasons.
8-44
-------
Marsh Data
Figure 8.29 Median marsh TS04 values for subareas with a vertical line indicating the 95%
confidence interval for each median.
8-45
-------
O > 75V. • ) MlDRANGE
* > 75% • I 5 MIDRANCE
y 75% « I 5 MIDRANCC
Marsh Data
\
M
3
A,'
«
f2
1000
100
10
J
M
3
(2
1000
100 -
10
J
\
CO
3
a.
(2
1000
100
10
MIDRANGE
LNWR WCA2 WCA3 ENP BCNP
LNWR WCA2 WCA3 ENP BCNP
Wet Seasons
i
i
*
I
o
;
- J
*
T
l^
- r
i ^ 2=3 ¦
[
I
*
~
1
LNWR WCA2 WCA3 ENP BCNP
Figure 8.30 Notched box and whisker plots comparing marsh TP in subareas during dry and wet
seasons.
8-46
-------
Marsh Data
40
30
\
tc
3
a." 20
eg
10
0
LNWR WCA2 WCA3 ENP BCNP
40
30
_}
x
GO
3
eu 20
a
10
0
LNWR WCA2 WCA3 ENP BCNP
40
30
J
\
00
3
ft." 20
00
10
0
Figure 8.31 Median marsh TP values for subareas with vertical line indicating 95% confidence
interval for each median.
Wet Seasons
—i— 1 _j i i
LNWR WCA2 WCA3 ENP BCNP
8-47
-------
Marsh Data
V5%
CONFIDENCE
ON MEDIAN
0> 75% ~ I MID RANGE
* > 75% ~ I 5 MIDRANGE
75% ~ I 5 MIDRANGC
75%
MEDIAN > MIDRANGE
J
I 25% ISM1DHANGE
LNWR WCA2 WCA3 ENP BCNP
LNWR WCA2 WCA3 ENP BCNP
Wet Season's
1
1
1
*
•
T
*
£
*
1
1
*
"
*
T ^
j.
"
LNWR WCA2 WCA3 ENP BCNP
Figure 8.32 Notched box and whisker plots of marsh comparing TN in water during diy and wet
seasons.
8-48
-------
Marsh Data«™r
100
O > 75% ~ 3 MIDRANGE
* > 75% ~ I 5 MIDRANGE
75% ~ I 5 MIDRANGE
MEDIAN ) MIDRANGE
25%
1 25% - I 5 MIDRANGE
LNWR WCA2 WCA3
ENP
BCNP
100
-J
\
00
c
H 10 -
CO
X 1
£
LNWR WCA2 WCA3 ENP BCNP
LNWR WCA2 WCA3
ENP
BCNP
Figure 8.33 Notched box and whisker plots comparing marsh THg in subareas during dry and
wet seasons.
8-49
-------
Marsh Data
\ 4
u
e
u
w "3
m J
£
c
2 -
CO
~ 1
o 1
(-
LNWR
WCA2
WCA3
ENP
BCNP
LNWR
WCA2
WCA3
ENP
BCNP
\ 4
M
C
£
c
» 2
5C
*eo
O 1
f-
LNWR
WCA2
WCA3
ENP
BCNP
Figure 8.34 Median values of marsh THg for subareas with a vertical line indicating the 95%
confidence interval for each median.
8-50
-------
0> 75% ~ 3 MID RANGE
* > 75V, ~ 1 5 MIDRANGE
75%+ I 5 MIDRANGE
75%
Marsh Data
LNWR WCA2 WCA3
ENP
BCNP
10.0
J
\
cc
a
s l.o
es
*
G
00
* 0.1
o.o
Dry Season's
!
6 A J
1
*
6
i
-
r
f-
LNWR WCA2 WCA3
ENP
BCNP
100
LNWR WCA2 WCA3
ENP
BCNP
Figure 8.35 Notched box and whisker plots comparing marsh MeHg in subareas during dry and
wet seasons.
8-51
-------
Marsh Data
LNWR WCA2 WCA3
ENP
BCNP
LNWR WCA2 WCA3
ENP
BCNP
-J
ac
CQ
£
2.0
1 5 -
1.0
X
1 0.5
w
O
2
0.0
LNWR WCA2 WCA3
ENP
BCNP
Figure 8.36 Median values of marsh MeHg for subareas with vertical lines indicating the 95%
confidence interval for each median.
8-52
-------
Marsh Data
95% f
CONFIDENCE <
ON MEDIAN I
0> 75% . ) MIDRANGC
* > 75% ~ I 5 MIDRANGE
i 75% ~ I 5 MIDRANGE
75 V.
MEDIAN / MIDRANGE
1 25%
1 25% - J 5 MIDRANGE
\
3
U-
c
00
X
(2
1000
800
600
400
200
All t)2LtSL o
O
~
i
I
*
£ i E
s
H k
A T -
+
LNWR WCA2 WCA3
ENP
BCNP
\
CO
3
¦C
v>
iZ
at
X
£
1000
800
600
400
200
Dry Season's
0
i
-
*
*
11 ^
t
- A r
r
J
P 'vb "
i i
-/
i
LNWR
WCA2
WCA3
ENP
BCNP
\
00
3
U.
c
CO
I
o
f-
1000
800
600
400
200
LNWR
WCA2
WCA3
ENP
BCNP
Figure 8.37 Notched box and whisker plots comparing THg in fish in marsh in subareas during
dry and wet seasons.
8-53
-------
Marsh Data
CONFIDENCE <»
ON MEDIAN
O > 75V. 4 3 MID RANGE
* >75% ~ I 5MIDRANGE
75% + 1 5 MIDRANGE
75%
25% —^
25%- I 5MIDRANGE
(
O
* 3
<4
U-
3
£
3
LNWR
WCA2
WCA3
ENP
BCNP
Dry Season's
i i
-
*
8 t
-
_
• T
*
t
i
rs
LNWR WCA2 WCA3 ENP BCNP
SO
<
o
a
U.
c
o
9
6
3
O
o
«
o
5
Wet Season's
1
i
*
(
k
i
J -
t |—
h >:
^ w
< i , i
i ¦—i i
»
LNWR
WCA2
WCA3
ENP
BCNP
Figure 8.38 Notched box and whisker plots comparing marsh BAF factor in subareas during dry
and wet seasons.
8-54
-------
0>75V. • 3 MIDRANGE
* > 75V. ~ I 5 MIORANCE
75% ~ I 5 Mff) RANGE
75V.
Marsh Data
00
c M
co \
O 00
00 >>
X -5
£ o
O fix
H
1000
800
600 -
400
200 -
LNWR
WCA2
WCA3
ENP BCNP
1000
LNWR
WCA2
WCA3
ENP
BCNP
1000
800
c CO
'Z M
eo \
O
£ 3
DO >*
- t
eo
Z o
O CLi
H
600 -
400 -
200
LNWR
WCA2
WCA3
ENP
Figure 8.39 Notched box and whisker plots comparing THg in floating periphyton in subareas
during dry and wet seasons.
8-55
-------
Marsh Data
00
C CO
.M
(d \
O OA
E 3
.5 |
60 >»
K ^
fi
W U
[2 ^
>100
LNWR
WCA2
WCA3
ENP
BCNP
00
c eo
¦*
co \
o 00
E 3
•- I
•c
a
M
SG
(2 °"
LNWR
WCA2
WCA3
ENP
BCNP
LNWR
WCA2
WCA3
ENP
Figure 8.40 Median values of THg in floating periphyton for subareas with a vertical
indicating the 95% confidence interval for each median.
8-56
-------
Marsh Data
MS%
CONFIDENCE
ON MEDIAN
o > 75% ~ 3 MID RANGE
* > 75% ~ I 5 MIDRANGE
75% ~ i 5 MrDRANGE
75%
25%
25%
I S MIDRANGE
30
«o
c
•- bO
S *
o
X to
P- p
20
.5 c
o
00 —
® £
£ 10
All I^ata
o
0
i i
I A
0
1
M
§
i ^
LNWR
WCA2
WCA3
ENP
BCNP
30
M
C
CO
a ^
O ^ 20
U. 3
.5 c"
o
DC ~
X £
>. C 10
•5 u
u ^
s
0
LNWR WCA2 WCA3 ENP BCNP
30
bo
C
•- CO
03 ^
£ w 20
U. 3
.5 c
o
bo —
X
* Z 10
f: «
o ^
s
0
Figure 8.41 Notched box and whisker plots comparing MeHg in floating periphyton in subareas
during dry and wet seasons.
Dry Seasons
o
LNWR
WCA2
WCA3
ENP
BCNP
8-57
-------
0> 75% ~ 3 MID RANGE
* > 75% ~ I 5 MIDRANGE
75% ~ I 5 MIDRANGE
75%
Marsh Data
to
o \
M 60
a 3
bC o
— j;
a o.
1500
1000 -
o "C 500 -
,o i-
H *
cu
LNWR
WCA3
BCNP
1500
LNWR
WCA2
WCA3
ENP BCNP
1500
WCA2
WCA3
ENP
BCNP
Figure 8.42 Notched box and whisker plots comparing THg in soil periphyton in subareas
during dry and wet seasons.
8-58
-------
0> 75% ~ ) MIDRANGE
* > 75% ~ I 5 MIDRANGC
75% + I 5 MIDRANGE
75%
Marsh Data
20
.*z
o ^
LO v
GO
.E 3
co a
x 2
— >»
>> J3
J.Z Q.
4J ^
« V
2 Cm
15
10 -
LNWR
WCA2
WCA3
ENP
BCNP
20
.-60 15
° ^
M \
60
C 3
00 c
X £ 10
>,
>, £
JC Q,
2 cu
Dry Season's
o
1
*
1 1
7*
-
- ¥
\ /
*
' VJ
1 1
i s
LNWR
WCA2
WCA3
ENP
BCNP
WCA2
WCA3
ENP
BCNP
Figure 8.43 Notched box and whisker plots comparing MeHg in soil periphyton in subareas
during dry and wet seasons.
8-59
-------
0> 75V. • J MIDFLANGE
* > 75V, ~ I 5 MIDRANGE
T 75% ~ I 5 MIDRANGE
J 1 75%
Marsh Data
95% I
CONFIDENCE <
ON MEDIAN 1
MEDIAN } MIDRANGE
2S% - I S MIDRANGC
O
o
\
00
3
60
X
£
80
70
60 -
50 -
40
30 -
o 20
C/5
10
LNWR
WCA2
WCA3
ENP
BCNP
70
u
« 60
bO
3 50
00
X
_ 40
*3
1 30
i 20
10
0
LNWR WCA2 WCA3 ENP BCNP
80
70
u
^ 60
M
3 50
eo
- 40
CO
° 30
i 20
v>
10
0
Figure 8.44 Notched box and whisker plots comparing marsh soil THg in subareas during dry
and wet seasons.
LNWR WCA2
WCA3
ENP
BCNP
8-60
-------
0> 75% ~ 3 MIDRANGE
* > 75% ~ I 5 MIDRANGE
75V. ~ I 5 MIDRANGE
75%
_L
!M3.rsh. Dcitci cqnf'dence/
w "• ON MEDIAN I
> MIDRANGE
2SV. ¦ I 5 MIDRANGE
LNWR
WCA2
WCA3
ENP
BCNP
LNWR
WCA2
WCA3
ENP
BCNP
1.0
S 08
N
60
3
- 0.6
>>
% 0.4
s
I 02
0.0
Figure 8.45 Notched box and whisker plots comparing marsh soil MeHg in subareas during dry
and wet seasons.
Wet Seasons
LNWR
WCA2
WCA3
ENP
BCNP
8-61
-------
Marsh Data
><
w
_j
j
<
<
*
H
j* ^
••;/ ••. s-
/\-v<
•«
1 o
H
<
O ¦
3
j :
v< *
¦ • V
\
*!»¦* • «\
5
<
i
<
H
? r . .v
" * ^ l •
A
•X •
¦ \ > ^ ••.
• • •*•••
• • " / I •' "¦ **
27 0
25 0
Figure 8.46 Selected marsh parameters shown by latitude.
8-62
-------
TOTAL ORGANIC CARBON IN WATER
I I I I i I II
~i r
-81.0 -80.8 -80.6 -80.4
1 T
-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 8.47 Kriged surfaces indicating marsh TOC concentrations during each sampling cycle.
8-63
-------
SULFATE IN WATER
J I I I I L
26.6-
26.4-
V
a
u
WD
U
~a
73
£
'C
a>
•a
w
c
p
H
H
<
-
-i 1 r
-81.0 -80.8 -80.6 -80.4
i 1 r
-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 8.48 Kriged surfaces indicating marsh TSO„ concentrations during each sampling
cycle.
8-64
-------
TOTAL PHOSPHORUS IN WATER
i i i i i i i i
26.6-
26.4-
26.2-
26.0-
25.8-
25.6-
T 1 1 1 1 1 1 r
-81.0 -80.8 -80.6 -80.4 -81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 8.49 Kriged surfaces showing TP in the marsh for each sampling cycle based on
sampling data.
8-65
-------
METHYLMERCURY IN WATER
J 1 I I I I L
t 1 r r
-81.0 -80.8 -80.6 -«0.4
T 1 1 T
-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 8.50 Kriged surfaces indicating marsh MeHg concentrations during each of the sampling
cycles.
8-66
-------
26.6-
26.4-
26.2-
8
V
u
ec
o
¦o
"es
E
E 26.0-
u
V
"O
w
o
H
H
<
J
25.8-
25.6-
25.4-
-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 8.51 Locations of floating periphyton samples with kriged surfaces indicating
concentrations of MeHg in floating periphyton.
8-67
-------
26.6-
26.4-
26.2-
8
&
¦o
"«
M 26.0-
u
O)
T3
fcd
Q
H
< 25.8H
•J
25.6-
25.4-
METHYLMERCURY
IN SOIL PERIPHYTON
ALL CYCLES, 1995 & 1996
• . 'G"'
-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 8.52 Locations of soil periphyton samples with kriged surface indicating concentrations
of MeHg in soil periphyton.
8-68
-------
26.6-
METHVLMERCURY IN SOIL
ALL CYCLES, 1995 & 1996
26.4-
26.2-
v
0)
u
W)
U
"O
"ee
E
5 26.0-
w
v
13
r*
td
Q
H
P
<
J
25.8-
25.6-
25.4-
-81.0
-80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 8.53 Kriged surfaces indicating concentrations of MeHg in marsh soils during study
period.
8-69
-------
TOTAL MERCURY IN GAMBUSIA
J 1 L
i 1 1 r
-81.0 -80.8 -80.6 -80.4
1 T
-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 8.54 Kriged surfaces indicating concentrations of THg in mosquitofish collected in the
marsh during each sampling cycle.
8-70
-------
26.6-
-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 8.55 Hg concentrations in Great Egret chick feathers and mosquitofish indicate spatial
distribution of Hg bioaccumulation.
8-71
-------
9.0 MERCURY MASS ESTIMATES
Mass estimates of THg and MeHg in water, soil, floating periphyton, soil periphyton, and
mosquitofish were calculated for each synoptic sample. Note: This is not a mass balance or
budget, but mass estimates to provide a relative perspective of instantaneous masses among
constituents. The models used to calculate Hg mass estimates are shown in Table 9.1.
Table 9.1 Mercury mass estimate models.
Water:
Massw =
* • a ¦ e z,'d'
n 1
2^ 1=1
k ¦ A • E
Soil:
Masss =
ri 1
2^ 1=1
V- n Z, • M,
Periphyton:
Massp -
k ' A ¦ e -—1
n 1
Z, i=i —
Fish:
Massf =
k-A-E.I, Z,'N'
n 1
^ 1 = 1 V
A =
area of study region, km2
s
soil bulk density at a sample site, g/cc
Z =
concentration Hg at a sample site
0.1 =
soil depth, m
d =
water depth at a sample site, m
M =
density of periphyton, g/m2
TI
sampling design inclusion probability
(Trexler personal communication)
k =
constant used to convert to appropriate
N =
fish/m2*Average fish weight for fish, g/fish
units
(Trexler personal communication)
9-1
-------
Periphyton densities were assumed to range from 171 g/m2 dry weight in the ENP to 452 g/m2
dry weight in WCA-3; based on ash free dry weight measurements collected by J. Trexler
(personal communication). The density of fish was assumed to be 3.5 fish/m2 during dry seasons
and 14.5 fish/m2 during wet seasons based on data gathered by J. Trexler (personal
communication).
Mass estimates of THg in precipitation were also calculated for the wet and dry seasons
corresponding to the sampling cycles. The mass estimate was calculated by multiplying total
precipitation for the season by the average of THg in precipitation measurements for the season.
The wet season was assumed to be June through October, and the dry season was assumed to be
November through May. The precipitation data used for this calculation came from 5 National
Oceanic and Atmospheric Administration (NOAA) weather stations located in the study area;
Belle Glade Experiment Station, Devils Garden, Homestead Experiment Station, Royal Palm
Ranger Station, and Tamiami Trail. Measurements of THg in precipitation were available for the
4 stations monitored for FAMS.
The mass estimates for THg by media and cycle are compiled in Table 9.2. The
systemwide estimates for water range from 4.0 to 4.3 kg during the dry cycles and from 6.8 to
10.1 kg in the wet cycles. Higher loading during the wet season is consistent with the pattern of
atmospheric deposition. Wet deposition of Hg during the wet season accounts for 80% of the
annual total atmospheric deposition of Hg in the Everglades system.
Table 9.2 South Florida THg mass estimates (kg).
Cycle 0
(Dry)
Cycle 1
(Wet)
Cycle 2
(Dry)
Cycle 3
(Wet)
Input
Precipitation
53
163
52
112
Sinks
Water
4.3
10.1
4.0
6.8
Soil
14,135.0
14,888.0
15,330.0
13,962.0
Floating Periphyton
222.0
—
132.0
341.0
Soil Periphyton
835.0
—
473.0
345.0
Mosquitofish
0.68
0.80
0.66
0.64
TOTAL
15.197
H, m
15.939
14.656
9-2
-------
Systemwide estimates of soil THg were relatively consistent in all four cycles ranging
from 13,962 to 15,330 kg. The soil represents the largest Hg sink in the system. Soil loads would
not be expected to change significantly during this period of study. The consistency of these mass
estimates also shows the utility of the randomized design in providing consistent estimates of a
relatively constant indicator.
THg mass estimates for periphyton were able to be calculated for only one wet cycle.
Floating periphyton dry cycle THg mass estimates ranged from 132 to 222 kg, while the single
wet cycle was estimated at 341 kg. The higher wet season estimate was coincident with high wet
season atmospheric deposition of Hg. Soil periphyton THg mass estimates were higher than
those for the floating periphyton ranging from 473 to 835 kg during the dry cycles and 345 kg for
the single wet cycle.
THg mass estimates in mosquitofish were extremely low ranging from 0.66 to 0.68 kg
during the dry cycles and 0.64 to 0.80 kg during the wet cycles. These estimates are remarkably
consistent among cycles. The low estimates obtained may be partly due to low biomass estimates
used to represent the standing stock.
Systemwide mass estimates of MeHg for water, soil, floating periphyton, and soil
periphyton by cycle are presented in Table 9.3. MeHg mass estimates in water ranged from 1.3 to
2.0 kg during the dry cycles to 1.0 to 1.9 kg during the wet cycles. The consistency in these
estimates indicates that the amount of MeHg is likely controlled by internal processes in the
marsh rather than outside influences external to the marsh (e.g., atmospheric deposition).
Table 9.3 South Florida MeHg mass estimates (kg).
Sinks
Cycle 0
Cycle 1
Cycle 2
Cycle 3
(Dry)
(Wet)
(Dry)
(Wet)
Water
2.0
1.9
1.3
1
Soil
88.4
76.4
92.4
89.9
Float Periphyton
9.2
6.1
7.1
4.5
Soil Periphyton
9.5
2.9
4.8
2.1
Mosquitofish
0.68
0.80
0.66
0.64
TOTAL
108.9
87.1
105.4
97.3
9-3
-------
Systemwide mass estimates of MeHg in soil ranged from 88 to 92 kg during the dry
cycles and 76 to 90 kg during the wet cycles. Even though these estimates are higher than the
water estimates, as expected, the consistency among the cycles further indicates internal
processes control MeHg production.
Mass estimates of MeHg across the system for floating periphyton ranged from 7.1 to
9.2 kg during the dry cycles and 4.5 to 6.1 kg during the wet cycles. Comparable estimates for
soil periphyton found the dry cycles ranged from 4.8 to 9.5 kg and the wet cycles ranged from 2.1
to 2.9 kg. Both parameters appear to be higher in the 1995 cycles and lower in the 1996 cycles. In
contrast to THg mass, which was higher in soil periphyton, MeHg mass was higher in floating
periphyton.
Areal mass estimates were also calculated for subareas of the Everglades for each cycle.
The subareas were LNWR, WCA2, WCA3-n (north of Alligator Alley), WCA3-S (south of
Alligator Alley), ENP, and BCNP. Figures 9.1 and 9.2 are plots of areal mass estimates of THg
and MeHg in water and soil.
As expected, areal THg mass estimates of THg in water tended to be higher during the
wet cycles. During the wet cycles the greatest THg mass occurred in WCA3-s. During the dry
cycles, THg masses in the ENP were very similar to those in WCA3-S.
As expected, areal mass estimates of THg in soil were consistent between cycles, with no
seasonal pattern apparent. For the soil, there was a strong north to south gradient with greater
loads in the southern subareas. This pattern corresponded to the general pattern of water flow in
the system.
Areal mass estimates of MeHg in water and soil were fairly consistent between cycles.
MeHg in water tended to decrease from north to south. MeHg mass estimates in water were also
more variable in LNWR and the WCAs than in the ENP and BCNP. MeHg mass estimates in
soil were highest in LNWR and WCA3-n. Areal masses of MeHg in soil were very similar for all
cycles in WCA2 and WCA3-S.
9-4
-------
Marsh Data
Cycle 0 Cycle 1 Cycle 2 -X- Cycle 3
Marsh Data
Cycle 0 Cycle 1 Cycle 2 -H- Cycle 3
Figure 9.1 Marsh data THg in water (top) and soil (bottom).
-------
Marsh Data
Cycle 0 Cycle 1 Cycle 2 -x- Cycle 3
Marsh Data
Cycle 0 Cycle 1 Cycle 2 -x- Cycle 3
Figure 9.2 Marsh data MeHg in water (top) and soil (bottom).
9-6
-------
10.0 SYNTHESIS AND INTEGRATION
10.1 Critical Factors
Three factors are critical for Hg contamination to reach concentrations that can have
adverse ecological and human health effects: (1) Hg source(s); (2) critical combination of
environmental conditions; and (3) bioaccumulation and concentration through the food chain to
top predator species. The biota, in fact, provide the integration of these three conditions.
Therefore, this chapter begins with a discussion of the latter two factors: bioaccumulation of Hg
through the food web; and the environmental conditions that contribute to bioaccumulation.
Previous chapters discuss the conceptual model for Hg that has been revised based on the
information presented in this report and supported by other scientific studies, and identifies a
number of hypotheses that emerge from this discussion that can be tested in the Everglades
ecosystem.
10.2 Mercury Bioaccumulation and Environmental Conditions
Differential bioaccumulation of MeHg in the Everglades ecosystem food web with
latitude was evident both in periphyton and in mosquitofish. Though limited to WCA2 and
WCA3, similar spatial differences in MeHg concentrations in biota were found by Cleckner et al.
(1998). The generally low concentrations of MeHg in wholebody mosquitofish in the northern
subareas and high concentrations in wholebody mosquitofish in the central and southern subareas
requires further analyses to achieve a better understanding of the interactions of environmental
factors contributing to bioaccumulation in this species. Differential Hg uptake in mosquitofish
tissue existed even though high MeHg concentrations occurred in the canal and marsh waters in
the northern areas, which might be expected to result in equally high concentrations in the biota.
To further elucidate this relationship the database was parsed by latitude into seven subgroups
running from north to south. Parsing the data by latitude unified the large scale gradient effects in
water quality moving through the flowway of the ecosystem. The same biological responses (e.g.,
plant growth and distribution responses) occur on a broad scale across the entire system, and
latitudinal parsing combines like effects into subunits with significantly large sample sizes
10-1
-------
providing a statistically powerful analytical tool. It is instructive to treat this system as a very
wide shallow river rather than quiescent marsh; therefore, this analysis is limited to the central
flowway omitting the samples from BCNP. Differences in water and soil quality and the
differences in mosquitofish food habits indicated the BCNP subarea was different from the
central Everglades and justified omission from this analysis.
10.2.1 Vegetation Responses
The randomized canal and marsh data sets were parsed into compartments for each
habitat (Figures 10.1 and 10.2, Table 10.1). North EAA describes the northern EAA canal
system. South EAA and LNWR describe the southern EAA canal system including points
surrounding LNWR in the canal database and the LNWR marsh, which exhibits minimal change
in marsh plant response. The north Alligator Alley subarea consolidates the major plant
responses to TP in this system including the invasion of cattails and the growth and density
responses in sawgrass, which were observed during the sampling. Sawgrass exhibited increased
density and growth (increased height, Turner et al. 1995) in this subarea, which can impose a
shading effect on underlying periphyton (Grimshaw et al. 1997). High TP concentrations are also
known to alter the periphyton community to favor bluegreen and filamentous green algae
(Browder 1994, Swift and Nicholas 1987). The central portion of WCA3 focuses on the hot spot
for Hg in mosquitofish and other organisms, which was separated from the southern portion of
WCA3 where Hg concentrations in mosquitofish are somewhat lower. The northern portion of
ENP is exposed to higher nutrient concentrations than the southern portion of ENP, which
appears least impacted by nutrients and is the reason for the demarcation of the marsh in ENP.
The incidence of floating periphyton is most prevalent in central WCA3, which persists to a
lesser degree downstream through the southern portion of ENP. Since there are fewer canals in
the ENP, all canal data south of Tamiami Trail was consolidated into one canal subarea in order
to maintain comparable sample sizes within each subarea. Water quality, periphyton, and fish
tissue Hg concentrations were evaluated along this latitudinal gradient.
10-2
-------
Table 10.1 Latitudinal divisions used to characterize canal and marsh constituent gradients.
Latitude
Canal
Marsh
>26.68
North EAA
26.679 to 26.36
South EAA
LNWR
26.359 to 26.159
WCA-N
AA-N
26.1589 to 25.95
WCA3-C
WCA3-C
25.949 to 25.76
WCA3-S
WCA3-S
25.759 to 25.56
ENP
ENP-N
25.559 to 25.24
ENP-S
10.2.2 Water Quality
The canal median water quality values for the six latitudinal subareas with 95%
distribution free confidence limits for TP, TOC, TS04, MeHg in water, THg in mosquitofish, and
the BAF are presented in Table 10.2. The median values for each subarea are plotted for these
parameters in (Figure 10.3). This plot shows an inverse relationship between TP in water and
THg in mosquitofish progressing from north to south. High median TP concentrations for the
canals were 94.7 ^g/L in northern EAA and 103.1 tu.g/L in southern EAA declining to 49.3 //g/L
north of Alligator Alley, 30.3 ^g/L in central WCA3, 20.2 [u.g/L in southern WCA3, and
13.9 pig/L in ENP. In contrast, THg concentrations in mosquitofish were minimal at 27.9 jug/kg
in the northern EAA and 24.6 /Ug/kg in the southern EAA followed downstream by rapidly
increasing concentrations of 53.0 ^g/kg north of Alligator Alley, 66.8 ^g/kg in central WCA3,
and 82.1 ij.g/kg in southern WCA3. However, the fish tissue Hg concentration declined to
42.2 /ug/kg in ENP canals, where TP reached the lowest median canal value. The BAF was about
100,000 in the northern EAA and southern EAA and increased steadily downstream to its highest
level of 820,000 in the ENP canals.
The canal median TS04 concentration was 35.5 mg/L in northern EAA, increased to
54.0 mg/L in southern EAA, then declined rapidly to 15 mg/L north Alligator Alley and reached
background concentrations (MDL = 5 mg/L) in cental WCA3 and southern WCA3. A small
10-3
-------
increase in TS04 to 9.1 mg/L occurred in ENP. A maximum TOC value of 29.9 mg/L occurred in
the southern EAA, which declined throughout the system to a minimum of 10.0 mg/L in ENP.
Median MeHg concentrations in water ranged from 0.3 to 0.2 ng/L through the northern four
subareas declining to 0.153 and 0.059 ng/L in southern WCA3 and ENP canals, respectively.
Table 10.2 Latitudinal gradients for canal constituent medians, and confidence intervals from
north to south.
Parameter
EAA-N
EAA-S
AA-N
WCA3-C
WCA3-S
ENP
BAF
1.2 x 10s
(n=18)
(0.5-1.7 x 10s)
1.0 x 105
(n=5I)
(0.7-1.2 x 105)
1.9 x 10s
(n=39)
(1.4-2.4 x 105)
3.1 x 10s
(n=26)
(2.4-3.9 x 105)
5.1 x 10s
(n=37)
(3.7-6.5 x 10s)
8.2 x 10s
(n=21)
(4.7-11.6 x 105;
TP, Mg/L
94.7
(n=20)
(43.7-145.8)
103.1
(n=53)
(83.9-122.3)
49.3
(n=41)
(33.9-64.7)
30.3
(n=26)
(23.7-36.9)
20.2
(n=36)
(14.5-25.8)
13.9
(n=18)
(10.6-17.2)
TOC, mg/L
23.0
(n=20)
(16.9-29.0)
29.9
(n=53)
(25.7-34.1)
22.9
(n=41)
(20.1-25.7)
22.9
(n=26)
(19.6-26.3)
18.1
(n=36)
(15.0-21.2)
10.0
(n=18)
(7.7-12.3)
TS04, mg/L
35.5
(n=20)
(19.2-51.8)
54.0
(n=53)
(39.7-68.3)
15.0
(n=41)
(7.6-22.4)
5.2
(n=27)
(2.3-8.1)
5.0
(n=37)
(3.8-6.2)
9.1
(n=21)
(5.7-12.5)
MeHg, ng/L
0.300
(n=20)
(0.165-0.435)
0.205
(n=53)
(0.148-0.262)
0.272
(n=41)
(0.217-0.326)
0.262
(n=27)
(0.174-0.350)
0.153
(n=37)
(0.119-0.189)
0.059
(n=21)
(0.031-0.087)
THgF, ^g/kg
27.9
(n=10)
(20.8-35.0)*
24.6
(n=51)
(21.4-27.7)
53.0
(n=39)
(36.4-69.5)
66.8
(n=26)
(31.5-102.0
82.1
(n=37)
(53.1-111.1)
42.2
(n=21)
(26.2-58.2)
* 95% confidence interval about the median.
The marsh median water quality values with the 95% confidence intervals for six
latitudinal subareas are presented for TP, TOC, TS04, MeHg in water, THg in mosquitofish,
MeHg in floating and soil periphyton, and the BAF in Table 10.3. A plot (Figure 10.4) of these
medians shows an inverse relationship of TP in water to mosquitofish THg in the upstream
portion of the marsh (e.g., LNWR, north of Alligator Alley), but then shows a direct relationship
with TP in the downstream portions of the marsh. Median TP concentrations were 16.7 //g/L in
LNWR and 16.4 /ug/L north of Alligator Alley. TP concentrations declined to
10-4
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Table 10.3 Latitudinal gradients for marsh constituent medians, and confidence intervals
from north to south.
Parameter
LNWR
AA-N
WCA3-C
WCA3-S
ENP-N
ENP-S
BAF
0.6 x 105
(n=57)
(0.02-1.2 x 10s)*
2.2 x 105
(n=72)
(1.7-2.7 x 105)
3.0 x !05
(n=73)
(2.1-3.9 x 10')
5.6 x 105
(n=72)
(4.8-6.4 x 105)
6.9 x 10s
(n=69)
(5.9-7.9 x 105)
8.5 x 105
(n=51)
(6.6-10.3 x 105)
TP, pigfL
16.7
(n=60)
(13.1-20.2)
16.4
(n=86)
(13.7-19.0)
12.1
(n=84)
(9.1-15.2)
10.7
(n=73)
(7.6-13.8)
12.3
(n=71)
(9.0-15.6)
8.6
(n=67)
(6.9-10.3)
TOC, mg/L
24.8
(n=60)
(21.4-28.1)
27.0
(n=86)
(24.6-29.3)
22.0
(n=84)
(20.0-23.9)
17.9
(n=73)
(15.7-20.0)
19.3
(n=71)
(17.2-21.4)
12.4
(n=67)
(10.5-14.4)
TS04j mg/L
2.0
(n=60)
(1.2-2.8)
15.0
(n=86)
(10.0-20.0)
2.4
(n=84)
(1.0-3.7)
2.0
(ii=73)
(1.6-2.4)
2.0
(n=71)
(1.6-2.4)
2.0
(n=67)
(1.8-2.2)
MeHg, ng/L
0.538
(n=60)
(0.392-0.684)
0.426
(n=85)
(0.370-0.525)
0.502
(n=84)
(0.370-0.634)
0.351
(n=72)
(0.267-0.435)
0.274
(n=71)
(0.220-0.328)
0.151
(n=67)
(0.114-0.187)
THgF, ^g/kg
96.5
(n=57)
(68.6-124.4)
114.7
(n-72)
(96.6-132.7)
208.5
(n=73)
(165.1-252.0)
178.0
(n=72)
(148.1-207.9)
189.3
(n=69)
(156.7-221.9)
155.7
(n=51)
(117.6-193.7)
Floating
Periphyton
MeHg, tigfkg
4.3
(n=14)
(1.9-6.6)
2.4
(n=27)
(1.5-3.3)
3.3
(n=52)
(2.2-4.5)
2.0
(n=52)
(1.5-2.4)
1.7
(n=52)
(1.3-2.2)
1.8
(n=32)
(1.3-2.3)
Soil
Periphyton
MeHg, /^g/kg
5.0
(11=6)
(3.2-6.9)
1.5
(n=7)
(1.1-2.0)
1.2
(n=18)
(-0.1-2.5)
2.1
(n=22)
(1.6-2.7)
0.8
(n=21)
(0.5-1.1)
0.5
(n=40)
(0.3-0.6)
* 95% confidence interval about the median.
12.1 ^g/L in central WCA3 remaining at 10.7 ng/L through the southern WCA3 and 12.3 //g/L
in the northern ENP declining to 8.6 yUg/L in the southern ENP. In contrast, the median THg in
mosquitofish was 96.5 and 114.7 /^g/kg in LNWR and north Alligator Alley. However, with the
decline of TP to 12.1 /ig/L in central WCA3, THg in mosquitofish doubled to a median value of
208.5 ^g/kg. The THg concentrations in fish remained high at 178.0 and 189.3 /ig/kg in the
southern WCA3 and the northern ENP, respectively, followed by a decline to 155.7 /Ug/kg in the
southern ENP coinciding with a decline in median TP to 8.6 pig/L. This plot also indicates higher
MeHg concentrations in water occurred in the northern three subareas with medians ranging from
10-5
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0.43 to 0.54 ng/L, which declined to 0.151 ng/L in the southern ENP. MeHg in floating
periphyton in the northern three subunits was higher than in the southern three subunits.
Maximum MeHg in soil periphyton occurred in LNWR, but remained at low concentrations
throughout the remainder of the system. Maximum MeHg bioaccumulation in mosquitofish
occurred in central WCA3 and successive downstream subunits into the northern ENP followed
by a decline in fish in southern ENP. The decline of nearly all parameters in the southern ENP
suggests this subarea might be the only remaining part of the Everglades marsh system that has
TP concentrations near background levels. The minimum concentrations of TP and MeHg in
water and THg in mosquitofish all occur in the southern ENP. A latitudinal comparison of the
BAFs for floating and soil periphyton found higher values for the former in all areas (Figure
10.5). The BAF for mosquitofish increased from north to south, indicating increased uptake
efficiency which might be due to recovery of the food chain with declining concentrations of TP.
A sharp increase in marsh TS04 north of Alligator Alley to 15 mg/L was followed by a
sharp decline to background concentrations in central WCA3 and all downstream areas. The
concentrations of TOC indicate a decline from a median of 23 mg/L north of Alligator Alley to
10.0 mg/L in the southern ENP, which indicates there were relatively high concentrations of
TOC throughout the entire system.
The natural Everglades is an oligotrophic food limited system. TP creates a series of plant
responses from north to south in single celled algae to emergent macrophytes, which can alter
periphyton communities downstream through the system. One of the most obvious plant
responses to increased TP in this system is the proliferation of plant biomass. The increase in
cattail presence and sawgrass density and height was evident in north of Alligator Alley and the
northern part of central WCA3 with greatest occurrence in WCA3 north of Alligator Alley.
Median TP concentrations in water above 16 //g/L were associated with low mosquitofish THg
concentrations. When TP concentrations declined from 16 to 12 iig/L, there was a doubling in
MeHg bioaccumulation in mosquitofish, which might indicate a change in the structure of the
food chain. However, the highest concentrations of MeHg in water and periphyton were in the
three northern subareas receiving the highest TP concentrations. TP could directly or indirectly
have a stimulatory effect on the methylating microbes in the system. The methylation process is
very likely enhanced by the anaerobic conditions evident in the soil in WCA2. This stimulatory
10-6
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effect could result in high concentrations of MeHg in the water, which declines downstream
reaching minimum levels in the southern ENP, where TP is the lowest and the fertilizer effect on
the microbes may decline to background. It might also indicate there is a threshold TP
concentration where significant system responses begin to occur, which could have important
management implications. Where TP concentrations are between 10 and 12 /ug/L in central
WCA3 and downstream, the presence of floating and soil periphyton appears to be greater. The
presence of large amounts of thick floating and soil periphyton may provide a convenient
substrate in which inorganic Hg can be methylated (Gilmour, personal communication).
Comparison of the canal and marsh datasets indicates most of the MeHg is generated in
the marsh system, where abundant periphyton occurs and not in the canals. The marshes are the
primary areas of Hg contamination, both in area and in magnitude.
10.2.3 Food Habits
The oligotrophic, food limited nature of the Everglades also is indicated by the small
maximum sizes obtained by the mosquitofish in this system. In comparative studies with other
systems, Trexler (personal communication) and Lofitus (personal communication) have found
Everglades mosquitofish to be smaller than those found in other parts of their natural range. A
food habits analysis of mosquitofish from the September 1996 marsh cycle (Appendix E)
showed periphyton composed 36% of the diet of mosquitofish based on biomass in gut contents,
with insect, crustacean, arachnid, and piscine prey accounting for the remaining 64%. Adult
midges gleaned from the water surface accounted for 33.5% of the biomass of the diet, and
midge larvae, probably taken from floating, epiphytic, and benthic periphyton mats, accounted
for an additional 9.6%. Only two fish and an assortment of spiders, ants, and beetles were found
accounting for 15% of the diet by biomass. About 50% of the individual fish had plant matter
present in their guts, and about 45% had adult midges. Chironomid larvae and "other" prey were
both found in about 10% of the fish, while mites were present in around 8% and cladocerans in
only 3% of the fish examined. Very few empty stomachs were found.
When these food habits data were parsed into the six subareas the percentage of plant
food was generally consistent at 31.5% except for the northern ENP, which showed a mean of
50.3%. The intake of midges was over 20% in LNWR and north of Alligator Alley when
10-7
-------
compared to all areas downstream that were less than 6.6%. The "other" prey items were lowest
in LNWR with 6.7% and highest in central WCA3 and southern WCA3 with over 20.8% and
declined in the two downstream areas. The analysis showed that the mosquitofish diet changed
with fish size, even though the fish in this sample were very small. Both factors may confound
the attempt to understand the uptake of Hg by this species and argue for additional future
sampling. Another complicating factor is the likely changes in the structure of the food chain
from north to south through the Everglades ecosystem as a result of the eutrophy in the north and
the oligotrophy in the south and the marked changes in Hg bioaccumulation through these food
chains.
The primary mechanisms controlling the accumulation of MeHg and inorganic Hg in
aquatic food chains are not sufficiently understood; however, uptake most likely occurs through
the food web and not directly from the water. Gaining an understanding of bioaccumulation and
biomagnification is made exceedingly more difficult by the complex food chains in the
Everglades, which are affected by nutrient gradients from north to south through the system.
Mason et al. (1996) hypothesized that phytoplankton cell size may be an important controlling
factor in the uptake of Hg and subsequent concentrations in fish with greater bioaccumulation
associated with the smaller cell sizes in lakes. Proving a similar relationship exists in the
Everglades periphyton communities would be much more complicated. In addition, both detrital
and primary production-based food webs are important. There is probably nowhere else in the
world, however, that such a nutrient gradient ranging from eutrophy to oligotrophy exists on
which to test this hypothesis in a marsh environment. If periphyton cell sizes were found to be
smaller and more efficient Hg bioaccumulators in the oligotrophic portion of the Everglades
ecosystem, a corresponding relationship may be found with that observed in oligotrophic lakes
(Lindquist et al. 1991).
10.3 Conceptual Models
Three new conceptual models have been formulated to describe the processes accounting
for the methylation and bioaccumulation of Hg in the South Florida Everglades ecosystem based
on this assessment. These conceptual models have been developed to correspond to the three
geographic areas: (1) north of Alligator Alley, (2) between the Alley and Tamiami Trail, and
10-8
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(3) below Tamiami Trail in ENP. These conceptual models are based primarily on the results of
this study, but are supported by other on-going Everglades studies and additional studies
documented in the scientific literature.
10.3.1 North of Alligator Alley
Water quality constituent concentrations (e.g., TP, TOC, TS04) are high north of
Alligator Alley. Elevated nutrient concentrations have resulted in a shift in the historical plant
community from calcareous bluegreen algae and periphyton to filamentous algae, cattails, and
dense sawgrass that shade the periphyton community and reduce the periphyton biomass. These
nutrient concentrations are sufficiently high that the assimilative capacity of the natural system
has been greatly exceeded, resulting in a shift in the natural community to a pollution tolerant
community. MeHg concentrations in water and floating and soil periphyton are high, but
concentrations in the mosquitofish are low. There are several factors contributing to low
mosquitofish Hg concentrations. TOC concentrations in LNWR could complex with the MeHg
and make it less biologically available for bioaccumulation. High TS04 concentrations in WCA2
and anoxic conditions also increase the sulfide concentrations, which may complex with
inorganic Hg and reduce its availability for methylation; however, these processes are competing.
In the canal system, hypoxic and anoxic conditions might result in more pollution tolerant
species and an incomplete food chain. This incomplete food chain, consisting primarily of
grazers and filter feeders, results in fewer links in the food chain and lower biomagnification
rates. A detritus-based food web probably dominates in this area.
10.3.2 Alligator Alley to Tamiami Trail
Between Alligator Alley and Tamiami Trail, TS04 concentrations have declined
precipitously. TOC and TP concentrations have decreased to moderate levels. In the marsh, TP
concentrations are between 10 to 20 ^gfL. It is our hypothesis that these concentrations might
alter the periphyton community to pollution tolerant species, and these concentrations might
result in the stimulation of production of the native periphyton. Although TP concentrations are
currently lower, the potential for future system change is not precluded. Complexation of Hg
with TOC or sulfide is reduced, and MeHg is available for bioaccumulation. Increased
10-9
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periphyton production, particularly floating and epiphytic periphyton, provides additional sites
for increased methylation during the nocturnal period. This also results in increased
bioaccumulation of MeHg within the periphyton community. More complete food webs,
including both detrital and primary productivity-based pathways, provide additional links for the
biomagnification of Hg through the food chain. Total system production, however, is less
because of reduced nutrient concentrations, so biodilution does not decrease biotic Hg
concentrations. Hg concentrations throughout the food chain, from periphyton to wading birds,
are highest in this area because this long hydropattern, sustained water depth provides a sustained
aquatic habitat for aquatic organisms and wading birds.
10.3.3 South of Tamiami Trail
TP concentrations have decreased below 10 //g/L to near historical background levels so
periphyton community production is less and is nutrient limited, as indicated by elevated APA
levels. TOC and sulfide concentrations Eire low, so complexation with inorganic or organic Hg is
limited. Both periphyton production and methylation rates have decreased. However, because the
system is ultra oligotrophia food webs are complex, with multiple pathways. Even though
productivity is lower than areas north of Tamiami Trail, Hg bioaccumulation and
biomagnification continues to occur because of the increased complexity of the food webs,
including both detrital and productivity-based pathways. However, THg concentrations in
mosquitofish are decreasing in the southern portion of the Everglades because methylation rates
and MeHg concentrations have decreased.
10.4 Testable Hypotheses
The conceptual model has been developed to provide a framework both for explaining
current study results and for formulating hypotheses that can be tested in the field. Several of
these testable hypotheses are listed in Table 10.4. While there might be agreement or
disagreement on the conceptual models, the constructs can be tested in the field to support or
refute the hypothesized relationships. However, it is important that comparable long-term
monitoring occurs to assess the multiple interactions observed across the system because it is
10-10
-------
doubtful that the scale, magnitude, and complexity of experimental studies needed to define the
interacting variables can be conducted as this dynamic system changes.
10-11
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Table 10.4 Testable Hypotheses.
Ho: North of Alligator Alley
1) TOC and sulfide bind with THg in water, chelate MeHg so less is available to biota.
2) TP concentrations increase microbial activity, which results in both greater demethylation
and methylation.
3) TP increases cattail and sawgrass production, which shades and reduces periphyton
production and methylation.
4) TP concentrations stimulate eutrophication and significant changes in the plant
community (species and density).
6) TP stimulates increased microbial peat decomposition, which increases MeHg production.
7) High TP concentrations promote high productivity, which produces biodilution of Hg in
biota.
8) Impacted food web with pollution tolerant organisms, ergo minimal top predators to
biomagnify Hg.
9) Elevated TP concentrations alter periphyton community composition favoring species that
have low transfer efficiency of MeHg biouptake.
Ho: Alligator Alley to Tamiami Trail
1) Periphyton production stimulated by TP concentrations between 10 to 15 yUg/L, which
results in greater periphyton biomass.
2) Greater periphyton biomass results in anoxic interior zones in the plankton mats and
significant methylation in these interior zones.
3) Elevated THgF is a function of water quality and bioavailability of MeHg.
4) Complete food chain with both detritus and primary producer base, resulting in
biomagnification of THg in bass, wading birds, other top predators.
5) Moderate APA indicates TP-periphyton stimulation.
6) Water depth optimal for wading birds in dry season feeding on high THg fish.
7) BAFs are higher because of complete food chain and addition of primary producer base.
8) Drawdown (hydropattern modification) results in flushing porewater MeHg into overlying
water and uptake through food chain in longer hydropattern area.
9) Chloride and pH affect MeHg uptake by algae consequently affecting periphyton BCF and
fish BAF.
Ho: South of Tamiami Trail
1) Periphyton production stimulated by TP concentrations from canal extension into ENP
resulting in increased methylation in localized areas.
2) TP concentrations below 10 /ig/L significantly reduce productivity, biomass, and
methylation, hence, bioavailability of MeHg.
3) Hydropattern has altered the habitat for fish and wading birds.
4) Fluctuating water level draws pore water MeHg into Shark River Slough and uptake by
primary producers and other biota.
5) Complex food webs result in relatively high fish THg concentrations even through MeHg
concentrations decreased.
10-12
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CANAL LATITUDINAL DIVISIONS
J I k— L
EAA-N
.EAA-S
WCA-N
WCA3-C
WCA3-S
ENP
LONGITUDE, decimal degrees
Figure 10.1 Six canal compartments with locations of sampling points contained in each.
10-13
-------
MARSH LATITUDINAL DIVISIONS
J I |___ L
LNWR
AA-N
WCA3-C
WCA3-S
ENP-N
ENP-S
-81.0 -80.8 -80.6 -80.4
LONGITUDE, decimal degrees
Figure 10.2 Six marsh compartments with locations of sampling points contained in each.
10-14
-------
p
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EAA-N EAA-S AA-N WCA3-C WCA3-S ENP
a Total P
x Sulfate
O Fish THg
v TOC
~ Methyl Hg
Figure 10.3 Median values of selected parameters in canal subareas.
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Figure 10.4 Median values of selected parameters in marsh subareas.
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• Soil Periphyton BAF * Fish BAF
A Floating Periphyton BAF ¦ Total P
Figure 10.5 Median marsh TP and BAFs in subareas.
-------
11.0 MANAGEMENT IMPLICATIONS
11.1 Policy-Relevant Questions
The South Florida Everglades Ecosystem Assessment project has been guided by seven
policy-relevant questions:
1) Magnitude - What is the magnitude of the problem(s) in the Everglades?
2) Extent - What is the extent of the problem(s)?
3) Trend - Is the problem(s) getting better, worse, or staying the same?
4) Cause - What factors are associated with or causing the problem(s)?
5) Source - What are the sources contributing to the causes and what is the
importance of different sources to the problem(s)?
6) Risk - What are the risks to different ecological systems and species from the
stressors or factors causing the problem(s)?
7) Solutions - What management alternatives are available to ameliorate or eliminate
the problem(s)?
This section will provide preliminary answers to these seven questions based on the data
collected in this assessment study. The first four questions can be answered with greater certainty
that the last three questions. The seven questions listed are equally applicable to each issue
impacting the Everglades ecosystem such as hydropattern modification, Hg contamination,
eutrophication, habitat alteration, and endangered and exotic species.
11.1.1 Magnitude - What is the magnitude of the problem(s) in the Everglades?
Mercury
Biota
1) Significant numbers of sportfish species including largemouth bass exceed
the Florida fish consumption advisory of 0.5 ppm. (FGFWFC)
2) Less than 20% of the mosquitofish in the South Florida canals exceed the
proposed predator protection level of 100 ppb for Hg.
11-1
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3) Almost 70% of the mosquitofish in the South Florida marsh exceed the
USFWS proposed predator protection level of 100 ppb for Hg.
Air
1) Atmospheric Hg concentrations in South Florida are as high as that found
near industrial sources in the midwest. (FDEP)
2) Annual average Hg emissions to air for South Florida (0.48 kg/m2/yr) are
3 times higher than the state average. (FDEP)
Water
1) 100% of the marsh and canals have THg concentrations less than the
Florida 12 ng/L water quality criterion for protection of designated uses:
recreation and propagation and maintenance of a well-balanced population
of fish and wildlife.
2) Concentrations of water MeHg are two to three times higher in the marsh
(0.2 to 0.6 ng/L) than in the canals (0.1 to 0.2 ng/1).
3) Water MeHg to THg ratios (MeHg/THg) were consistently higher in the
marsh during the dry season (up to 36% in WCA2).
Soil
1) There are no apparent patterns of THg in soils that would indicate a
specific source of Hg.
2) MeHg in surface soil is generally <10 Mg/kg or <1 Mg/cc with no spatial
pattern. MeHg in soil is less than MeHg in soil periphyton.
Total Phosphorus
Water
1) 95% of the marsh currently has TP concentrations less than the 50 ^:g/L
Phase I target TP concentration.
2) 45% of the marsh has TP concentrations equal to or less than 10 ^g/L.
3) 55% of canal miles have TP concentrations less than 50 ,ug/L.
4) The EAA canals are loading the marsh with P.
5) There is an observable gradient in TP concentrations in the marsh with the
highest concentrations found north of Alligator Alley and the lowest
concentrations in the ENP.
11-2
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Soil
1) TP in surface soil is highest in WCA2 and northern WCA3, with lower
concentrations in central WCA3 and ENP. Lowest concentrations tend to
occur in the marl soils.
11.1.2 Extent - What is the extent of the problem(s)?
Mercury
1) All of Florida Bay and the freshwater Everglades and BCNP are under a
human health fish consumption advisory because of Hg contamination of
certain gamefish species (FDHRS, FGFWFC, FDEP).
2) About 5,100 km2 (2,000 mi2), which is almost 70% of the South Florida
marsh area has prey fish (mosquitofish) Hg concentrations that exceed the
100 ppb USFWS proposed guideline for protection of predators. In
contrast only 20% or 210 km (130 mi) of the canal length exceed this
guideline.
3) There is a Hg hot spot south of Alligator Alley in WCA3A extending into
ENP where Hg concentrations are highest in water, algae, mosquitofish,
gamefish, wading birds, alligators, and the Florida panther.
Phosphorus and Other Nutrients
1) Ninety-five percent (95%) of the marsh was sampled and
7,358 km2 had TP concentrations less than the Phase I TP target
concentration of 50 ^g/L. Forty-seven percent (47%) or 3,654 km2
of the marsh had TP concentrations less than 10 Mg/L.
2) Fifty-five percent (55%) or 678 km (421 miles) canal had TP
concentrations less than the Phase I TP target of 50 /ig/L.
3) The canal system draining the EAA transports water with elevated
concentrations of TP, TOC, and TS04 into the Everglades and
contributes to water quality gradients from north to south across
the marsh changing in extent with wet and dry seasons.
4) The APA, an indicator of microbial P limitation, shows clear
gradients within the Everglades marsh system from north (little P
limitation) to south (highly P limited).
11-3
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11.1.3 Trend - Is the problem(s) getting better, worse, or staying the same?
Mercury
1) No data are available to determine whether Everglades biota were
contaminated with Hg prior to 1989.
2) Monitoring of Hg in Everglades soil, water, algae, and mosquitofish has
not been in place long enough to determine presence or absence of trends
over time.
3) A 2-year baseline has been established with two wet and two dry seasons
per year in the marsh grid. However, a record wet year occurred during
one of these years.
4) Annual largemouth bass monitoring in Everglades canals since 1989
indicate that a significant number of bass exceed the Florida fish limited
consumption advisory level of 0.5 ppm. There has been no significant
decrease in bass Hg concentrations since 1989. (FGFWFC)
5) It is not possible to determine whether there is a trend over time in
Everglades wading bird Hg contamination because monitoring has not
been conducted on a consistent basis. (FDEP)
6) Everglades soil core dating indicates that there has been an increase in Hg
deposition over the last 40 years. (FDEP)
Habitat
1) From 1946 to 1995 soil thickness across northeastern WCA3 has
decreased from 0.9 to 1.5 m (3 to 5 feet) thick to only 0.3 to 0.6 m (1 to
2 feet) thick.
2) Approximately 50% of the historical freshwater marsh has been lost in the
Everglades since the early 1900s. (SFWMD)
3) Preliminary data are available that indicate that cattails are becoming more
abundant and dominant in more areas of the Everglades marsh.
11.1.4 Cause - What factors are associated with or causing the problem(s)?
1) It is the interaction of hydroperiod, TP, TOC, and TS04 concentrations
with the biota that results in the methylation and bioaccumulation of Hg in
the ecosystem, not a single factor.
2) It is thought that TP plays an important role in effecting plant and floating
periphyton communities distributions and structure of food webs, thereby
affecting Hg methylation and bioaccumulation.
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3) Hg methylation is occurring not only in marsh soils, but also in periphyton
mats. Therefore, there are multiple entry points for MeHg into the system.
11.1.5 Source - What are the sources contributing to the causes and what is the
importance of different sources to the problem(s)?
Mercury
1) No single Hg point source has been identified that can be linked to the
remote areas of marsh affected.
2) Atmospheric Hg loading is from 35 to 70 times greater in the Everglades
than Hg loading in canal water from the EAA.
3) The EPA ORD South Florida Atmospheric Mercury Monitoring Study
(SoFAMMS) study indicated urban municipal and medical waste
incineration emissions had higher Hg concentrations than emissions from
a coal-fired cement kiln and that these emissions might be transported over
the marsh.
Total Phosphorus
1) The EAA is contributing TP to the canals in the north and this TP is being
transported as far south as ENP, which is contributing to eutrophication of
the Everglades ecosystem.
2) Eutrophication of the marsh and canals is caused by P being discharged
from the EAA and transported downstream.
11.1.6 Risk - What are the risks to different ecological systems and species from the
stressors or factors causing the problem(s)?
Mercury Trends
1) Hg toxicity is thought to have contributed to the death of a Florida panther
in 1989. (FDHRS)
2) Hg concentrations in Everglades WCA3 great white herons are higher than
those shown to cause adverse effects in common loons. (FDEP)
3) No evidence of adverse human health effects contributed to ingestion of
Hg contaminated biota have been found to date. Sampled concentrations
of Hg in human blood or hair from human populations at potential
increased risk were normal. (FDHRS)
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4) Juvenile wading birds are able to move Hg from their blood into feathers,
thereby decreasing their risk to Hg contamination, however, this does not
preclude possible effects on survival when on a contaminated diet. (FDEP)
5) The critical concentrations of Hg in Everglades wildlife such as wading
birds and the Florida panther above which adverse chronic or acute effects
occur are unknown. (FDEP)
6) Water THg concentrations average 2.5 ng/L. Since the THg 12 ng/L water
quality criterion for protection of fish and wildlife has not been exceeded,
the criterion is inadequate for preventing Hg bioaccumulation.
Total Phosphorus
1) Ninety-five percent (95%) of the marsh has TP concentrations less than the
Phase 1 target TP concentration of 50 A^g/L. The marsh is at risk if TP
concentrations remain at the Phase I target.
2) The effectiveness of the STA's is unknown, but the ENR demonstration
project has reduced inflowing TP concentrations by about 80%. (SFWMD)
Greatest Risk
1) The greatest risk to the Everglades is to assume the problems can be
addressed independently.
11.1.7 Solutions - What management alternatives are available to ameliorate or
eliminate the problem(s)?
1) Atmospheric Hg loading to the Everglades is much greater than Hg
loading from EAA stormwater.
2) In its first year of operation, the ENR project removed over 50% of the
THg, 75% of the MeHg, and 80% of TP in stormwater runoff from EAA.
(SFWMD)
3) Various threats to the long-term viability of the Everglades, such as Hg
contamination, nutrient enrichment, and water management, are
interrelated.
11.2 Potential Considerations
The management implications from this baseline assessment and preliminary answers to
the policy relevant questions are:
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1) Revised THg water quality criterion lower than 12 ng/L are needed to protect
predator species in the food web.
2) MeHg rather than THg criterion should be developed because MeHg, not THg, is
bioaccumulated and biomagnified. There is no statistical relationship between
THg and MeHg concentrations.
3) Hg emission controls should be considered to reduce atmospheric Hg
concentrations and deposition over the Everglades ecosystem.
4) Waste disposal is a multi-media problem. Controlling Hg emissions might create
other problems such as disposal of solid waste, including not only the waste, but
also the Hg removed from the emissions.
5) Wildlife in the marsh aquatic food web appear to be at greater risk from Hg
biomagnification than wildlife in the canal food web. Management actions
directed at reducing wildlife risks from Hg contamination should be directed at
the marsh system.
6) In contrast, Hg concentrations in gamefish such as bass are highest in the canals.
People fish predominantly in the canals. Management actions directed at human
health concerns or environmental concerns for the alligator should be directed at
the canal system.
7) Nutrient gradients appear to influence methylation by stimulating floating and soil
periphyton mat production, which function as sites for methylation. Reducing
nutrient inputs also should affect Hg contamination.
8) Because Hg is a naturally occurring element, cycling of Hg through the marsh
ecosystem likely will continue for decades, even if inputs were reduced today.
Rapid changes in the system should not be expected after reducing Hg inputs.
9) There is no "magic bullet" that can be easily implemented to control one factor
and thereby alleviate Hg contamination. Hg contamination is affected by
hydropattem, TP, TOC, and TS04 concentrations and biotic interactions.
10) The environmental conditions and Hg bioaccumulation processes in the hot spot
need to be identified and compared to those in other portions of the Everglades
with less Hg bioaccumulation to determine the factors controlling Hg
contamination. Once identified, it may be possible to manage these factors.
11) TP criterion must be significantly lower than 50 ^g/L to protect the Everglades
from eutrophication.
12) Cattail presence and abundance is associated with soil TP concentrations. Unlike
water TP concentrations, higher soil TP concentrations might take decades to
centuries to decrease. Management actions should focus on preventing additional
TP loading to marsh soils.
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13) Hydroperiod modifications have contributed to peat loss in northern WCA3.
14) This study was conducted during an abnormally wet period. If the spatial patterns
change significantly by season or by year, management practices could be
implemented at the wrong locations and be ineffective.
15) Continued monitoring over time is required both to determine trends in TP and Hg
contamination and, as part of Government Performance and Review Act (GPRA),
to determine the effectiveness of water and other management actions. Monitoring
is an integral component of the adaptive management process.
16) Management actions in the Everglades ecosystem must be coordinated and
integrated. The greatest risk to the Everglades ecosystem is to assume the
problems are independent.
11.3 Relevance
This study permits a synoptic look at the ecological condition of the entire freshwater
canal and marsh system in South Florida from Lake Okeechobee to the Florida mangrove
systems. This large-scale perspective is needed to understand the impacts of different factors,
such as TP, Hg, habitat alteration, or hydropattem modification, on the entire system rather than
a small piece or area. Looking only at isolated pieces in any given area and extrapolating to South
Florida would provide a distorted perspective. The statistical sampling approach permits
quantitative estimates, with known confidence, about population characteristics, such as acres of
marsh in cattails, percent of the marsh with fish Hg concentrations greater than the proposed
predator protection level of 100 ppb, or percent of the canal miles with TP concentrations greater
than the Phase I control target level of 50 Mg/L. Study information is aiding decision makers with
its significant findings related to the major issues facing ecosystem restoration in South Florida.
In addition to providing answers to policy-relevant questions, the project also is
contributing to a better scientific understanding of the Everglades ecosystem. A holistic picture
of soil thickness, percent organic matter, and water quality is not only scientifically important but
also provides insight into areas with peat subsidence, areas of organic soils that might bind P or
metals or indicate water quality gradients in the system. This study, while contributing to the
development of adaptive management practices, also provides the information needed to evaluate
the effectiveness of these management practices. For example, once the Phase I P control
program is in place, TP concentrations throughout the canal and marsh system can be reassessed
11-8
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to evaluate the effectiveness of the control program. With the passage of GPRA, monitoring and
assessment programs such as this have taken on even greater importance.
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12.0 FUTURE DIRECTION
12.1 Introduction
The interim assessment (Stober et al. 1996) and the results of the final technical
assessment for Phase I (this report) indicate the importance of hydropattern, nutrient, habitat,
vegetation, and food web information for ecosystem management and restoration efforts.
Continued monitoring of water, soil/sediment, periphyton, and fish is critical both for better
understanding of Hg cycling in the ecosystem and to evaluate the effectiveness of ecosystem
restoration activities and natural hydropattern changes that are occurring over time. This research
and monitoring, which is consistent with the South Florida Mercury Science Program (SFMSP),
and the Everglades restoration activities will be extended. The studies in Phase II in 1999 will be
designed to fill existing data gaps in the ecological baseline assessment (habitat assessment),
initiate trend monitoring, provide additional input for models of Hg cycling, landscape, and water
management and to determine systemwide responses to management actions. It is important that
comparable long-term monitoring occurs to assess the multiple interactions observed across this
dynamic system because it is doubtful that the scale, magnitude, and complexity of experimental
studies needed to define the interacting variables can adequately predict future changes.
12.2 Objectives
The USEPA South Florida ecosystem assessment project is an innovative, large-scale,
multimedia, monitoring and assessment program designed to measure the current and changing
conditions of ecological resources in South Florida using an integrated, holistic approach. The
ultimate goal of this program is to provide decision makers with sound ecological data to
improve environmental management decisions on multiple environmental issues and restoration
efforts in the Everglades. The South Florida ecosystem assessment project provides a foundation
for addressing the multiple issues that are critical to the restoration of the Everglades ecosystem
and contributing to the Interagency Task Force on Ecosystem Restoration efforts. The South
Florida ecosystem assessment project uses the EPA ecological risk assessment framework
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(USEPA 1992) as a foundation for providing decision makers with critical information. The
program is guided by seven policy relevant assessment questions:
1) Magnitude - What is the magnitude of the problem(s) in the Everglades?
2) Extent - What is the extent of the problem(s)?
3) Trend - Is the problem(s) getting better, worse, or staying the same?
4) Cause - What factors are associated with or causing the problem(s)?
5) Source - What are the sources contributing to the causes and what is the
importance of different sources to the problem(s)?
6) Risk - What are the risks to different ecological systems and species from the
stressors of factors causing the problem(s)?
7) Solutions - What management alternatives are available to ameliorate or eliminate
the problem(s)?
The seven questions listed are equally applicable to each issue impacting the Everglades
ecosystem, such as, hydropattern modification, Hg contamination, eutrophication, habitat
alteration, and endangered and exotic species.
The USEPA South Florida ecosystem assessment project is a long-term research,
monitoring and assessment program. Initial conceptual models and testable hypotheses have been
developed. A number of studies will be required to test all of the hypotheses and to refine the
conceptual models and complete the ecological risk assessment in the Everglades. Initially, the
South Florida ecosystem assessment project has focused on a subset of hypotheses that are
directly related to the first four policy-relevant assessment questions identified above. Additional
coordinated studies directed at addressing other high priority elements of the interagency
program will be conducted and merged with this program as additional resources are made
available.
12.3 Approach
12.3.1 Revised Monitoring Design
Following the analyses conducted and presented in the South Florida Ecosystem
Assessment Interim Report (Stober et al. 1996), the baseline monitoring design was revisited to
consider reducing the cost while improving the efficiency of monitoring. The importance of
hydropattern modifications, nutrient and Hg cycling, and habitat alteration for marsh restoration
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indicated monitoring should emphasize the marsh ecosystem reducing emphasis on canals and
structures. Compliance monitoring of nutrient and Hg discharge from the future STAs was also
considered. Design scenarios considered included nesting compliance monitoring stations and/or
fixed long-term sites within the probability monitoring matrix. A similar compliance status and
trends network was successfully implemented in the Southern California Bight area (Stevens
1997). The location of the compliance monitoring stations would require a cluster of sites below
the STA discharge areas in WCA2 and the northern area of WCA3. Fixed long-term stations
representing locations that have previously been monitored by the USGS, NPS, or SFWMD
and/or at which process studies have been conducted or are likely to be conducted in the future
were considered. Some of the design scenarios considered are shown in Figure 12.1.
A maximum design constraint of no more than 125 stations can be sampled during any
cycle. Therefore, 119 probability samples with six long-term monitoring and process study sites
can be included without significantly reducing the design-based estimate. Tradeoffs associated
with the revised probability design include the power for trend detection, minimization of within
site variance compared to among site variance, pattern recognition, and cost. The monitoring
design selected satisfies the SFMSP Phase II objectives, provides information to assess the
effectiveness of restoration efforts in support of the Everglades Forever Act and the GPRA.
The initial Phase II design includes six long-term monitoring sites located in each of the
six latitudinal zones identified in the Phase I analysis. These sites are Lox 8 (center of
Loxahatchee), U3 (center of WCA2), WCA3-11 (2.5 mi south of Alligator Alley), WCA3-15 (
Hg hot spot), P33 (west of L67 extension) and P37 (southern ENP). Site selections were made on
the basis of existing water level, rainfall or water quality information or the presence of past or
future Hg cycling process studies. Compliance monitoring was not considered in the final fixed
site selection because many of these sites have already been identified in permit requirements and
will be monitored under permit schedules. BCNP will not be included in the 1999 random
sample. The selection of a minimum of six long-term sites also has the least effect on data
analysis and design-based estimates allowing ease of comparison with the Phase I data.
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12.3.2 Aerial Photo Vegetation Assessment
A Phase I probability assessment of vegetation was accomplished by visually determining
the major habitat types at each sampling location and documenting the sites with 35 mm
photographs. These measures permitted qualitative estimates of presence and dominance of
selected emergent plant species and floating periphyton at each site. However, quantitative
estimates are needed to provide plant biomass and Hg concentrations for input to Everglades Hg
cycling models. Estimates of plant biomass along the system are also needed to document
baseline responses to the nutrient gradient by key indicator species and for input to Everglades
landscape models. The Center for Remote Sensing and Mapping Science (CRMS) at the
University of Georgia is developing vegetation maps and digital databases for ENP using aerial
photo interpretation techniques. These techniques will be applied in this study, however, they
will be adapted to the USEPA probability sampling design used for assessment and monitoring
of the Everglades ecosystem. CRMS has the necessary experience and tools to accomplish this
task in a minimum time frame while ensuring systemwide data comparability.
• CRMS will obtain USGS National Aerial Photography Program (NAPP) color
infrared aerial photo transparencies for the study area (WCA1, WCA2, WCA3,
ENP, and Rotenberger). USEPA will provide CRMS with the Universal
Transverse Mercator (UTM) map coordinates North Atlantic Datum (NAD 83) for
the approximately 260 random sample points to be used in the survey. Map
interpretation will be conducted in the following order to facilitate the pilot study
scheduled for January 1999, dry season survey (April 1999) and the wet season
survey (September 1999). Six geographically distributed points will be sampled in
the pilot study, followed by 125 points in each dry and wet season survey. The
pilot study and each survey will have a unique set of randomized spatially
distributed sampling points which will be identified with a unique numbering
system. The survey points will be ordered by latitude from north to south. The
aerial photo interpretation will provide the detailed information for each site on
which the field sampling will be based; therefore, completion of the digitized
vegetation maps will precede the field sampling by at least 2 months.
• The CRMS will plot the sample site locations on the NAPP color infrared aerial
photographs and interpret the vegetation type and density. While particular
attention will be focused on sawgrass, cattails, and periphyton at each location
with subsequent biomass sampling by USEPA, interpretation of the photos to
evaluate all plant species/communities that can be consistently identified in the
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photos for changes in presence or absence and abundance and/or density will
maximize the information generated. Interpretation will focus on 1 km2 plots
centered at the GPS coordinates for each sample point. A vegetation map in
digital format will be prepared for each 1 km2 plot.
In an effort to try to expedite vegetation sampling the pilot study digital vegetation maps
will be provided to ORD EMAP (Corvallis) for development of an algorithm to weight (near the
center point) the selection of random sampling points for plant species biomass determination.
This will be tested on the six pilot study stations. Following development of the algorithm it will
be tested on the dry season survey points to evaluate the logistical requirements of the
systemwide sampling efforts. With development of the final working algorithm it will be
provided to CRMS for point location on the remaining digital vegetation maps.
The USEPA Region 4 field sampling team will load each site map with associated
vegetation type polygons into Field Notes on a GPS linked laptop and the field sampling crew
will ground truth the plant type communities. CRMS experts will assist EPA vegetation
assessment teams making field observations most appropriate to aerial photo interpretation and
accompany the vegetation assessment team during the pilot study. Various programs will be used
to interpolate these point data across the system to establish general spatial variations or trends in
plant distributions to provide a basis for future systemwide comparisons.
12.3.3 Plant Biomass Estimation
Responses of the macrophyte and periphyton communities to nutrient inputs has
important implications not only for Hg cycling and bioaccumulation, but also for ecosystem
restoration. High Hg methylation rates in periphyton and the higher MeHg mass estimates in
floating periphyton suggest a key interaction between atmospheric Hg deposition, nutrient
concentrations, and Hg methylation. In addition, increased density in cattail and sawgrass
habitats due to nutrient stimulation may inhibit periphyton growth through shading in parts of the
system. Quantitative studies of plant biomass will be conducted on key emergent species and the
periphyton community in Phase II of the program.
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This project proposes to develop a rapid biomass estimation method during the pilot
study, which is compatible with the study design and which can be implemented by the USEPA
Region 4 field sampling team. Clip plots ranging in areas of 0.25, 0.5, and 1.0 m2 will be tested
during the pilot study on the random sampling points for each indicator plant species (e.g.,
sawgrass, cattails). Above ground live leaf number, leaf length, culm diameter at base and culm
number, and wet weight will be determined in the field followed by transport of the samples to
the laboratory where they will be tagged and dried at 70° C to a constant dry weight and
reweighed. A ratio will be developed between the wet and dry weights for each plant species
sampled in an effort to eliminate transport of macrophyte biomass from the field via helicopter
and airboat. During the pilot study each plant species will be sampled in triplicate at each site.
The logistical requirements of vegetation sampling needed for the systemwide surveys
will be assessed from the aerial photo interpretations. Replicate samples will be taken from a
spatially distributed 10% the dry and wet season stations. All replicate samples will be weighed
wet and dried to determine seasonal changes in the wet to dry ratio.
Phase I floating and soil periphyton samples were collected at each station when present;
however, biomass was not measured. Phase II monitoring proposes to include quantitative
biomass estimates of soil and epiphytic and floating periphyton. A 1 m2 throw trap will be used to
collect floating and epiphytic periphyton. Each type of periphyton will be removed by hand and
transferred to a perforated plastic 1000 ml volumetric cylinder. The volumetric to dry weight
ratios will be determined for the pilot study and each systemwide survey and compared to similar
ratios developed by J. Trexler and B. Loftus (personal communication). The quantity of soil
periphyton will be determined during the soil core sampling from which the soil periphyton can
be removed as a complete sample. Following the pilot study, standard macrophyte and
periphyton sampling protocols will be reported in the results of the pilot study and submitted for
peer review.
12.3.4 Food Habits Analysis
A strong north to south gradient in the BAF calculated for Hg uptake in mosquitofish was
found during Phase I research and monitoring of the Everglades ecosystem. This discovery has
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led to the hypothesis that a series of important interactions are occurring in the system primarily
affected by phosphorus loading from the north, which impacts the food chain dynamics in the
system. One means of assessing these impacts is to analyze the food habits of the omnivorous
mosquitofish across the system. This was done once during the September 1996 marsh survey
and will be repeated again in the pilot study, and both dry and wet sampling cycles in 1999.
Twelve to fifteen individual fish will be analyzed at each site for stomach contents. These data
will be used in a comparative study with the 1996 food habits analysis to develop an
understanding of how changes in the food chain may affect the habits and uptake of this
ubiquitous fish species across the system.
12.4 Monitoring & Assessment Indicators
The three laboratories utilized in Phase I (FIU-SERP, Battelle MSL, and USEPA-SESD)
will analyze the comprehensive array of samples of water, soil, and tissue (plants and fish) and
conduct the routine QA/QC requirements in Phase II. FIU-SERP will continue as the primary
analytical laboratory for this project and provide the facility from which the USEPA field
sampling team will stage field activities. The methods previously developed by FIU-SERP for
Phase I will be utilized in Phase II to maintain continuity of results. FIU-SERP will assist
USEPA in the testing and development of new field sampling and analytical methods during the
pilot study in January 1999. New methods for Phase II include development of pore water
sampling, dissolved nutrients and selected anions, sulfate/sulfide ratios, methane and C02 in soil,
diatom species composition, periphyton pigment analyses and macrophyte Hg analyses.
All sampling and analyses to be carried out during the next cycles of the study will be
tested and proven during the pilot study. The pilot study analytes will include THg, MeHg, TP,
TN, dissolved nutrients (NH4, N02, N03, PO„), TOC, sulfate, and sulfide in surface water; TP,
TN, dissolved nutrients, selected anions (Br, CI, F, N02, N03, O-p, TS04), and sulfide in pore
water; THg, MeHg, sulfate, sulfide, TP, CH4, and C02 in soil; THg, MeHg, and EtHg in floating
and soil, periphyton; THg, MeHg, and EtHg in sawgrass and cattails; and THg in mosquitofish.
Selected media collected during the pilot study will be composited and split with equal
amounts of water, soil or tissue going to each laboratory. The mosquitofish will be analyzed as
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individual fish (7 per sample) as well as a homogenate for QAJQC purposes. For certain
parameters, each laboratory will analyze three replicates of each sample for each station to
provide a statistically valid data set on which to conduct an analysis of the interlaboratory
calibration. USEPA SESD Ecological Assessment Branch (EAB) field sampling team will be
responsible for "clean" sample collection, splits will be conducted in the FIU-SERP laboratory
and the EPA/Environmental Services Assistance Team (ESAT) field team will be responsible for
ensuring chain-of-custody, sample tracking, and shipping of blind, split, duplicate and replicate
samples to each laboratory. The data will be returned to FTN Associates, Ltd. (FTN) of Little
Rock, Arkansas, who will be responsible for statistical analysis of the data and report preparation
and presentation to EPA Region 4 SESD Office of Quality Assurance (OQA) for final review to
ensure the QA/QC requirements have been fulfilled. Following protocol testing in the pilot study
the same methods will be applied in the systemwide surveys.
A list of the pilot study (interlaboratory calibration) samples indicating the analyte,
subarea, analyzing laboratory and the number of samples to be analyzed by each laboratory is
presented in Table 12.1. A complete list of the analytical parameters by laboratory, MDL, and
number of samples to be analyzed per survey cycle are listed in Table 12.2. Ten percent of the
samples in each analyte will be replicated for QA/QC purposes.
12.5 Statistical Analyses
Numerous opportunities exist to develop both design-based and model-based statistical
analyses of the data requiring the development of new statistical methods. Design-based analyses
require methods for assessing the uncertainty of statistical summaries such as provided by cdfs.
In addition, methods are required for evaluating the current sampling designs to ensure that
adequate power is achieved to answer the objectives of the respective monitoring initiatives.
Model-based analyses require the development of models that mimic the complex processes that
occur in nature. Environmental processes are complex, involving interactions of numerous biotic
and abiotic factors over different spatial and temporal scales. Spatio-temporal models will be
developed for these data that take into consideration processes occurring at all spatial and
temporal scales including habitat, Hg, and water quality indicators. Methods for combining data
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Table 12.1 Everglades Jan '99 Pilot Study and Laboratory Intercalibration (triplicate analysis).
Sites
Parameter
LOX
AA-N
WCA3-C
WCA3-S
ENP-N
ENP-S
Surf-Water
Turbidity
1,3
1,3
1,3
1,3
1,3
1,3
APA
1
1
1
1
1
1
Chlorophyll a
1
1
1
1
1
1
THg
1,2
1,2
1,2
1,2
1,2
1,2
MeHg
1,2,
1,2
1,2
1,2
1,2
1,2
TP
1,3
1,3
1,3
1,3
1,3
1,3
TN
1,3
1,3
1,3
1,3
1,3
1,3
Diss. Nut-NH4,N02,N03, P04
1,3
1,3
1,3
1,3
1,3
1,3
TOC
1,3
1,3
1,3
1,3
1,3
1,3
tso4
1,3
1,3
1,3
1,3
1,3
1,3
h2s
1,3
1,3
1,3
1,3
1,3
1,3
Porewater
TP
1,3
1,3
1,3
1,3
1,3
1,3
TN
1,3
1,3
1,3
1,3
1,3
1,3
Diss. Nut-NH4,N02,N03,P04
1,3
1,3
1,3
1,3
1,3
1,3
Selected Anions
1,3
1,3
1,3
1,3
1,3
1,
tso4
1,3
1,3
1,3
1,3
1,3
1,3
h2s
1,3
1,3
1,3
1,3
1,3
1,3
Soil
THg
1,2,3
1,2,3
1,2,3
1,2,3
1,2,3
1,2,3
EtHg
1
1
1
1
1
1
MeHg
1,2
1,2
1,2
1,2
1,2
1,2
tso4
1,3
1,3
1,3
1,3
1,3
1,3
h2s
1,3
1,3
1,3
1,3
1,3
1,3
APA
1
1
1
1
1
1
AFDW
1
1
1
1
1
1
Bulk Den.
1
1
1
1
1
1
Min. Cone.
1
1
1
1
1
1
TP
1,3
1,3
1,3
1,3
1,3
1,3
ch4&co2
1,3
1,3
1,3
1,3
1,3
1,3
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Table 12.1 (Continued)
Sites
Parameter
LOX
AA-N !
WCA3-C
WCA3-S
ENP-N
ENP-S
Peri-F
THg
1,2,3
1,2,3
1,2,3
1,2,3
1,2,3
1,2,3
MeHg
1,2
1,2
1,2
1,2
1,2
1,2
EtHg
1
1
1
1
1
1
Diatom comp.
1
1
1
1
1
1
Pigment
1,3
1,3
1,3
1,3
1,3
1,3
Peri-S
THg
1,2,3
1,2,3
1,2,3
1,2,3
1,2,3
1,2,3
MeHg
1,2
1,2
1,2
1,2
1,2
1,2
EtHg
1
1
1
1
1
1
Diatom Comp.
1
1
1
1
1
1
Pigment
1
1
1
1
1
1
Sawgrass
THg
1,2,3
1,2,3
1,2,3
1,2,3
1,2,3
1,2,3
MeHg
1,2
1,2
1,2
1,2
1,2
1,2
EtHg
1
1
1
1
I
1
Cattails
THg
1,2,3
1,2,3
1,2,3
1,2,3
1,2,3
1,2,3
MeHg
1,2
1,2
1,2
1,2
1,2
1,2
EtHg
1
1
1
1
1
1
Fish
THg-indiv.
1,2,3
1,2,3
1,2,3
1,2,3
1,2,3
1,2,3
THg-homo
1,2,3
1,2,3
1,2,3
1,2,3
1,2,3
1,2,3
1 - FIU-SERP
2 - BATTELLE
3 - EPA-SESD
12-10
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Table 12.2 REMAP Parameters by cycle.
Parameter
Primary
Lab
Primary j Secondary
OA/QC qa/QC
Kite No.
Per
Cycle
Samp
ifa.
SURFACE WATER
DO
SESD
SESD-SOP
0.2 mg/L
129
129
PH
SESD
SESD-SOP
0.1 s.u.
129
129
Temp
SESD
SESD-SOP
0.15 C
129
129
Conductance
SESD
SESD-SOP
1.0 uS
129
129
Redox
SESD
SESD-SOP
1 mV
129
129
Depth
SESD
SESD-SOP
1 cm
129
129
Turbidity
FIU
SESD
0.1 NTU
129
155
Total Phosphorus
FIU
SESD
0.6 ug/L
129
155
Total Nitrogen
FIU
SESD
0.03 mg/L
129
155
Dissolved Nutrients
*(NH4,NOj,NO„ P04)
FIU
SESD
NO3-0.4ug/L
NO2-0.1ug/L
NH4-0.7ug/L
SRP-0.3ug/L
129
155
Total Organic Carbon
FIU
SESD
0.12 ug/L
129
155
Sulfate
SESD
SESD
0.01 mg/L
129
155
Sulfide*
SESD
SESD
0.01 ug/L
129
155
Alk_Phos
FIU
FIU
O.OluM/h
129
155
Chlorophyll a
FIU
FIU
0.1 ug/L
30
33
Total Mercury
FIU
Battelle
SESD
0.3 ng/L
129
187
Methyl Mercury
Battelle
FIU
0.02 ng/L
129
187
PORE WATER
Total Phosphorus*
FIU
SESD
0.6 ug/L
129
171
Total Nitrogen*
FIU
SESD
0.03 mg/L
129
155
Dissolved Nutrients
* (NR., NO* NOj, P04)
FIU
SESD
NO3-0.4ug/L
NO2-0.1ug/L
NH4-0.7ug/L
SRP-0.3ug/L
129
155
Anions
* (Br,Cl,Fl,N0I>N0J,0-p,S04)
FIU
SESD
ion chrom.
129
155
Sulfate
SESD
0.01 mg/L
129
171
Sulfide*
SESD
SESD
0.01 ug/L
129
171
SOIL/SEDIMENT
Type
SESD
129
129
Thickness
SESD
1 cm
129
129
PH
SESD
129
129
Redox (in situ)
SESD
1 mV
129
129
12-11
-------
Table 12.2 (Continued)
Parameter
jPtlraary
Lab
Primary
QA/QC |
sec
-------
Table 12.2 (Continued)
Parameter
jPrinjary
Lab
Primary
QA/QC
Secondary
QA/QC
MDL
SiteNo.
Per
Cycle
samp
No,
CATTAILS
Total Mercury*
FIU
SESD
Battelle
3 ug/kg
40
44
Methyl Mercury*
FIU
Battelle
0.2 ug/kg
40
44
Ethyl Mercury*
FIU
0.2 ug/kg
40
44
Biomass*
SESD
10 g
40
44
Surface Area* (% cover)
UGA
40
Habitat Evaluation
* (% cover, pres/absence)
UGA
129
129
Mosquito-Fish
Total Mercury
FIU
SESD
Battelle
1 ug/kg
129
1043
Length
FIU
0.1 mm
129
993
Weight
FIU
0.05 g
129
993
Sex
FIU
129
993
Stable Isotope Analysis
USGS
129
993
Food Habits Analysis
FIU
129
993
• = new parameter
** = minimum reportable quantities
HgT in water = 129 sites, 16 field blanks, 13 duplicates, 16 equip, blanks, 13 splits = 187
Porewater (nutrients/anions) = 129 sites, 13 dups, 16 equip blanks, 13 splits = 171
HgT in soil = 129 sites, 13 dups, 13 splits = 155
HgT in fish = 129 sites @ 7 fish/site = 903, 90 dups, 50 stand, tissue = 1,043
12-13
-------
collected at different spatial and temporal scales and trophic levels will be tested as will methods
required for analyzing spatially and temporally correlated data when some observations are left-
censored by the detection limits of instruments used to measure contaminants. This support will
be provided by EMAP contract support and the University of Georgia, Statistics Department.
12.6 QA/QC Requirements
12.6.1 Data Quality Requirements and Validation
In all data collection activities, data quality requirements will be specified in seven areas:
(1) accuracy and bias, (2) precision, (3) comparability, (4) completeness, (5) representativeness,
(6) tolerable background levels, and (7) DQOs (Stanley and Verner 1985, Smith et al. 1988).
Method detection limits have been specified based on the Phase 1 REMAP monitoring and some
have been lowered where lower detection levels are needed. The validation process will consider
each of the following components using a statistically appropriate method.
• Accuracy and Bias - Accuracy is the degree to which a measured value or
property agrees with an accepted "true" value (Taylor 1988). Accuracy is
estimated by measuring a sample with a known reference value. Bias is the
systematic error inherent in a method or caused by some artifact or idiosyncrasy of
the measurement system. One-way bias is estimated by interlaboratory
comparison of performance evaluation samples among laboratories.
• Precision - Precision is a measure of the scatter among independent repeated
observations or measures of the same property made under prescribed conditions
(Taylor 1988). Precision can be estimated at several points in the data collection
process in order to estimate the effects of different sources of error. Precision can
be partitioned into analytical and measurement system precision. Analytical
precision refers to precision of the analysis performed by analytical instruments; it
is estimated by laboratory replication, including replicates of performance audit
samples. Measurement system precision refers to the precision of the sampling
process, including sample collection, storage, transport, preparation, and analysis.
Collocated field duplicates are used to estimate precision of the entire
measurement system, and laboratory splits are used to estimate the precision of
sample processing after the sample has been received at the laboratory.
• Comparability - Comparability is defined as "the confidence with which one data
set can be compared to another" (Stanley and Verner 1985, Smith et al. 1988).
Comparability studies will be conducted with cooperating laboratories and
12-14
-------
agencies through round robin analyses. Identical field collection and laboratory
procedures will be used when possible.
• Completeness - Completeness requirements for this monitoring effort will be that
90% of all proposed samples are collected and analyzed.
• Representativeness - Representativeness is defined as "the degree to which the
data accurately and precisely represent a characteristic of a population parameter,
a variation of a property, a process characteristic, or an operation condition"
(Stanley and Verner 1985, Smith et al., 1988). The statistical survey, sampling
periods and sample locations were selected to ensure representative samples.
• Tolerable Background Levels - Background is operationally defined as the
amount of contamination due to collection, handling, processing, and
measurement. It is particularly relevant to the measurement of trace
concentrations of Hg species. Background levels will not be tolerated due to the
use of "clean sampling and analytical techniques" and if detected the source will
be isolated and eliminated. Field and laboratory blank samples will be added to
each day's samples and used to control and eliminate background contamination.
• Data Quality Objectives - The assessment of DQOs will follow the guidance
provided in EPA QA/G-4 (EPA 1994) or a revision intended for research projects
that is currently under development. This assessment of the data will be compared
after the pilot study and each cycle of spatial sampling for conformance to the
Phase I results. Deviations with Phase I results will be investigated and the most
probable explanation developed. The overall goal of maintaining consistency in
the database between Phase I and Phase II is most important to provide the most
accurate basis for trend assessments.
Precision and bias are estimates of random and systematic error in a measurement process
(Kirchner 1983, Hunt and Wilson 1986). Collectively, they provide an estimate of the total error
or uncertainty associated with an individual measurement, or set of measurements. Estimates of
the various error components will be determined primarily by replicate sampling. The statistical
design and sampling plan will minimize systematic errors in all components except measurement
error by using documented methodologies and standardized procedures. If new more sensitive
methods must be developed or analytical modifications made documentation will be provided as
the process moves toward standardization. In addition, standard samples will be included in the
field and subjected to the entire collection and measurement process. Variance components of the
collection and measurement process (e.g., among analytical laboratories) will be estimated after
12-15
-------
the pilot study and at the completion of each cycle so the QA efforts can be allocated to control
major sources of error.
12.6.2 Specific Data Package Requirements
The specific requirements for laboratories that submit results and data packages to the
USEPA Region 4, SESD for validation are contained in the document entitled Laboratory
Documentation and Quality Control Requirements for Data Validation, August 1998. These
requirements must be addressed in the laboratory's QA plan, which must be approved by the
SESD OQA prior to the initiation of sample analysis. All data reported from each analytical
laboratory for Phase II will be transmitted in electronic format (variable by numeric station ID
indicating analytical batch order and all other required QA information) in either Excel, Quattro
Pro, or dBase IV. Any additional format requirements will be specified by EPA prior to initiation
of the data collection. FTN will be the initial repository for the data who will compile the
database and conduct the initial QA/QC review of the data.
12.8 Mercury Modeling
A Hg screening model has been developed by EPA ORD NERL-Athens for the South
Florida Everglades ecosystem (Ambrose et al. 1998). The model encapsulates the current
understanding of processes contributing to Hg cycling within the marsh ecosystem and permits
preliminary evaluations of selected management strategies for ecosystem restoration. This
screening model also provides output that is used as input for the BASS model (Barber 1998).
BASS is a bioenergetics model that describes the bioaccumulation, depuration, and
biomagnification of Hg through the food chain to piscivorous fish. The data developed in this
project will allow additional simulations with the Hg screening and BASS models to evaluate
selected hypotheses and alternative pathways for Hg bioaccumulation. These data will support
the USEPA ORD NERL-Athens Everglades Mercury Cycling model currently under
development.
12-16
-------
12.9 Comparative Ecological Risk Assessment
The EPA Ecological Risk Assessment Framework (EPA 1992,1998) has served as the
guidance for the monitoring and research studies conducted under this program. A Visual Basic
model, known as VB-EcoRisk, has been developed to serve as an organizing structure for
conducting the comparative ecological risk assessment (Thornton et al. 1995). Information from
this program, the SFMSP, and other sources will be analyzed and integrated into the VB-EcoRisk
model by EPA Region 4 as a part of this project. A relative, comparative ecological risk
assessment is critical for the Everglades because of the multiple, interacting issues, in addition to
Hg, associated with ecological restoration of the Everglades. A relative ranking approach will be
used to assess risk so that disparate effects from different stressors (e.g., hydropattern
modification, nutrient loading, etc.) can be compared. An interim ecological risk assessment by
FTN is scheduled for completion in 1999.
12.10 Ecosystem Restoration Modeling and Assessment
In addition to providing information critical for a better understanding of mercury
contamination in the Everglades ecosystem, Phase II of this project will simultaneously provide
information useful for a variety of ongoing ecosystem restoration modeling and assessment
efforts. For example, the systemwide phosphorus condition information for marsh water and soil
will be useful for tracking the ongoing effectiveness of Phase I phosphorus control efforts and for
bettering models used to predict vegetation response to soil phosphorus. Dry season and wet
season water depth information will be useful for verification of hydrologic models, such as the
South Florida Water management Model, that are being used to select Everglades restoration
alternatives. Systemwide nutrient, macrophyte biomass, and periphyton biomass data can be used
as model input for the Everglades Landscape Model, a regional scale ecological model designed
to predict landscape response to different water management scenarios. Phase II of the project
will be the first scientific effort to provide this wide variety of information on a systemwide
basis. This collective monitoring is vital for providing baseline information for evaluating the
effectiveness of USACE Restudy Everglades ecosystem restoration project.
12-17
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-81.0 -80.8 -80.6 -80.4 -81.0 -80.8
LONGITUDE, decimal degrees
-80.6 -80.4
Figure 12.1 Potential monitoring network configurations combining probability, compliance
and fixed sites.
12-18
-------
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