Project ID: 14-0380
Everglades Ecosystem Assessment
Phase IV
Miami, FL
Project Date: September 3-21, 2014
Project Leader: Peter I. Kalla, Ph.D.
Ecology Section
Field Services Branch
Science & Ecosystem Support Division
USEPA - Region 4
980 College Station Road
Athens, Georgia 30605-2720
The activities depicted in this report are accredited under the US EPA Region 4 Science
and Ecosystem Support Division ISO/1 EC 17025 accreditation issued by the ANSI-ASQ
National Accreditation Board. Referto certificate and scope of accreditation AT-1644.
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Requestor:
Douglas Mundrick, Deputy Director
Water Protection Division
61 Forsyth St. SW
Atlanta, Georgia 30303-8960
Analytical Support:
Florida International University
Southeastern Environmental
Research Center
11200 S.W. 8th Street
Miami, Florida 33199
Analytical Services Branch
Science and Ecosystem Support Division
USEPA - Region 4
980 College Station Road
Athens, Georgia 30605-2720
Approvals:
SESD Project Leader:
"Petei "KcMa
Peter Kalla
Ecology Section
Field Services Branch
June 8, 2017
Date
Approving Official:
Stacey %>ax
Stacey Box, Chief
Ecology Section
Field Services Branch
June 8, 2017
Date
This report should be cited as:
Kalla, P.I., and D.J. Scheidt. 2017. Everglades ecosystem assessment - Phase IV, 2014: Data
reduction and initial synthesis. U.S. EPA, Science and Ecosystem Support Division, Athens, GA.
SESD 14-0380. 58 pp.
SESD Project ID Number: 14-0380
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Introduction
In September 2014, the U.S. Environmental Protection Agency, Region 4 Science and
Ecosystem Support Division (EPA SESD), in cooperation with Florida International
University (FIU) and the EPA Region 4 Water Protection Division, conducted a
comprehensive survey of the Florida Everglades as part of a recurring Everglades
Ecosystem Assessment described in the next section. This report presents the findings of
the survey for three key pollutants and one important measure of ecosystem integrity.
Summary and bivariate statistics on mercury, phosphorus, sulfur, and soil depth are
presented in this initial report. Only physical and biogeochemical results are included
here. Plant community mapping information was collected by other Principal
Investigators at FIU. They will present those findings in a separate report.
Planning and study design for the Everglades Ecosystem Assessment began in 1992. This
Program has focused on mercury because of its potency as a neurotoxin in wildlife and
concerns about human health risks associated with consumption of mercury-laden
gamefish. Phosphorus has been assessed because of its potential to eliminate the native
periphyton community, favor replacement of the native marsh with invasive cattail, and
aid in conversion of the natural ridge-and-slough microtopography to a flatter landscape
supporting only monospecific stands of unnaturally tall, dense sawgrass. Sulfur is of
concern due to its role in conversion of elemental mercury to its bioavailable form. A
review of the historical literature on these pollutants is available in Scheidt and Kalla
(2007).
Background
Phases I - III: Since 1993, EPA has been conducting a landscape-level assessment of the
Everglades ecosystem in association with many partners, including Everglades National
Park (ENP). The Program uses EPA's Environmental Monitoring and Assessment
Program (EMAP) statistical survey design (reviewed in Diaz-Ramos et al. 1996) to
sample all of the Marl Prairie/Rocky Glades and the Everglades Ridge and Slough
physiographic regions. The Everglades Ecosystem Assessment [EEA, also known as
Everglades Regional EMAP (REMAP)] is the only comprehensive probabilistic
monitoring and assessment program that preceded the development of the Comprehensive
Everglades Restoration Program (CERP), which subsequently defined several monitoring
and assessment objectives to include: documenting status and trends, determining
baseline variability, detecting responses to management actions, and improving the
understanding of cause and effect relationships. The EEA has provided this information
system-wide for the entirety of the freshwater Everglades. In Phases I (1993-1996) and II
(1999) EPA provided pre-2000 baseline conditions for a broad array of indicators against
which future changes can be measured. In Phase III (2005) changes were detected in
mosquitofish (Gambit si a holbrooki), mercury burdens and soil phosphorus
concentrations. EEA Program data have been featured in approximately 30 peer-
reviewed publications or agency reports which have been cited over 800 times. Data
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have been used by the National Academies of Sciences and about 30 federal or state
agencies, Indian Tribes, environmental groups, agricultural interests, or universities.
The overarching objectives of the EEA are to measure the condition of ecological
resources in the Marl Prairie/Rocky Glades and the Everglades Ridge and Slough
physiographic regions; and to document ecosystem responses as CERP restoration
efforts change the quality, quantity, timing and distribution of water, and as State
agencies implement control strategies for pollutants such as phosphorus, sulfur, and
mercury. EEA employs an integrated, holistic approach in a consistent manner at the
landscape level - the only effort to do so throughout the entire freshwater Everglades
ecosystem.
EEA has provided data relevant to 23 CERP performance measures for the Everglades
Ridge and Slough and the Marl Prairie/Rocky Glades physiographic regions - seven for
the Greater Everglades, one for the Miccosukee Reservation, three for Everglades
National Park, one for soil performance, one for animal performance, five for plant
performance and five for hydrological performance. Among these 23 are nine water
quality measures.
This monitoring and assessment project has been guided from the outset by the
following seven policy-relevant questions which are equally applicable to the four major
issues affecting the Everglades ecosystem (hydropattern modification, eutrophication,
habitat alteration and mercury contamination): What is the magnitude of the problem?
What is the extent of the problem? Has it changed over time? What are the associations
with the problem? What are the sources of the problem? What is the risk to ecological
resources? What are the solutions?
In Phase IV (2013-2014) of the Program, EPA continued change detection and/or
assessments of:
• concentrations of drivers, including nitrogen, phosphorus, carbon, and
sulfur, in water and soil over time and space;
• hydropattern modifications in the system and responses during the wet season;
• soil thickness;
• habitat alterations associated with nutrient loading and hydropattern
changes;
• methylmercury contamination;
• mechanisms controlling mercury methylation;
• bioaccumulation of methylmercury;
• interacting stressors through structural equation modeling; and
• management implications of these issues.
The information will be critical as baseline data for the Central Everglades Planning
Project, a new component of CERP that features restoration of the central flow-way.
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Methods
Design: The probability design EPA uses to sample the Everglades marsh was developed
from the EMAP base grid, a Generalized Random-Tessellation Stratified approach
(Stevens and Olsen 2004), in order to ensure spatial coverage. The design includes
stratification by the four major subareas of the system, the Water Conservation Areas
[WCA1 (also known as Arthur R. Marshal Loxahatchee National Wildlife Refuge -
LOX), WCA2, and WCA3] and the Park (ENP), to ensure that coverage of smaller
subareas is adequate for obtaining variance estimates. A consistent sample size of
approximately 125 random points per seasonal survey ensures acceptable confidence
intervals around estimated environmental parameters. This design criterion is compatible
with logistical considerations allowing helicopter-supported crews to complete all
sampling in about 15 days, which also matches throughput capacities of cooperating
analytical laboratories.
In Phase IV, EPA utilized an improved design that features a 50-50 mix of new random
points and points from the previous Phase (III, 2005). EPA's Office of Research and
Development (ORD), Western Ecology Division, National Health and Environmental
Effects Research Laboratory, provided the statistical design and sample draw. The 2014
statistical design is a probability survey design that consists of two parts: a) 50% of the
sites are a probability subsample of the prior survey design (2005) and b) 50% of the
sites are a new probability sample. Since the two designs are completed independently,
the combined survey design is also a probability survey design. The combined design
has two objectives. The first objective is to estimate the current status across space as
has been done in the past. The second objective is to estimate change between the two
time periods (2005 and 2014). The power of detecting a change is increased by visiting
some sites in both time periods (Breidt and Fuller 1999, USEPA 2015). Simulation
studies of alternative designs for estimating change favor survey designs where
approximately 50% of the sites are visited in both time periods. The 2014 change
estimation is based not only on the panel of 50% revisits, but also on the panel of sites
from the previous time period (2005) not revisited, and on the panel of new sites from
the current time period (2014).
In September 2013, the EPA SESD initiated Phase IV sampling at 125 target stations,
and successfully collected biogechemical data at 51 stations within ENP and WCA3.
Due to a federal government shutdown during the sampling period, the project was not
completed as planned. However, analysis was completed for the samples obtained prior
to the shutdown. Summary statistics are presented in USEPA (2014a).
EPA's synoptic, probabilistic approach is the only multi-media Program in the
Everglades that produces quantitative statements with known confidence about
environmental conditions across an entire resource over space and time. For example,
the proportion of the Everglades marsh having a total phosphorus concentration greater
than 400 milligrams per kilogram (mg/kg) (the CERP goal) in soil was 49.3 ± 7.1 % in
2005, and this proportion was statistically significantly greater than the 33.7 ± 5.4 %
measured in 1995-1996.
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Tasks: EPA conducted a probabilistic, multimedia, synoptic survey of the entire
freshwater flow-way of the greater Everglades ecosystem, an area of 2098 square
miles, during September of 2014. This survey focused on the biogeochemistry of key
pollutants in the marsh, namely mercury, phosphorus, and sulfur. Media sampled were
surface water, bottom water, periphyton, soil, flocculent detrital matter (floe),
macrophytic vegetation, and mosquitofish.
There was no dry season survey in Phase IV. Soil pore water, sampled in Phases II and
III, was replaced by bottom water. Aquatic community sampling by throw-trap,
conducted in Phase III, was omitted. These changes were made to match the Phase IV
effort to available funding.
Field Protocols: Crews obtained samples of water, floe, soil, periphyton, and
mosquitofish at each station. EPA Region 4 Field Branch Standard Operating
Procedures, which can be found at http://www.epa.gov/region4/sesd/fbqstp/index.html
were followed as applicable. At half of the stations, sawgrass leaf clippings were also
collected. At these stations plant communities present were classified at the 2-meter
scale, with a total of up to four GPS locations obtained at sub-meter accuracy in the
communities. Whole sawgrass plants were also collected at a quarter of the stations.
Sediment, benthic periphyton, and floe were collected in core tubes. A vacuum chamber
was used to collect a clean sample of surface water for trace-level mercury analysis.
Periphyton in the water column was collected by direct dipping. Mosquitofish were
collected with an MA"-frame dip-net or a large aquarium net for analysis of whole-body
total mercury. Mosquitofish are used in the Program because they are an excellent
indicator of mercury bioaccumulation due to their varied diet, small home range, great
abundance, ubiquity and short life cycle. They are also common forage for many other
fish.
A number of procedures have been developed specifically for the Program over the
years. These techniques and equipment, including a new procedure developed for
collection of bottom water for sulfide analysis, are described in the Quality Assurance
Project Plan (USEPA 2014b).
Data Analysis
The spatial survey statistics used for this report are described in Scheidt and Kalla
(2007). Since its inception, the Program has featured techniques to examine
probabilistic survey data. Complementary descriptive methods included here are box-
and-whisker plots and kriged mapping, to show the distribution of the data over the
range of the variable and over actual space, respectively. The cumulative distribution
function (CDF) is used here to estimate the magnitude and extent of key pollutants and
other parameters. CDF curves are tested (Wald F test) against each other to infer a
change, or lack thereof, in these variables between surveys. In this report, conclusions
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about change are based on the Wald F test results. This report includes correlation
analysis as an initial exploration of relationships among the data.
Outcome
The survey took place from September 4th through the 20th, 2014. All stations were in the
greater Everglades freshwater flow-way (Figure 1). Approximately 6,000 continuous
data values were generated.
All but six of the 125 stations in the base design were sampled. Two stations in ENP
were not sampled because they were non-target. One was a tree island and the other was
a forested upland. Another station in the Park was not attempted because of the potential
to disturb an endangered species of butterfly. The remaining three stations were not
sampled because of safety concerns about landing on site, due to the presence of tall
woody vegetation.
Throughout this report the results from the 2014 survey are compared to those from
previous surveys. The years chosen for comparison are 1995, which was the first
assessment of the marsh, and 2005, which was the midpoint in three decades of
successive effort. Because of three successive hurricanes in September and October, the
2005 survey was not conducted until November.
The 2014 survey was conducted during a period of lower water levels than in 2005,
which had levels lower than in 1995 (Figure 2). Water depths in the REMAP study area
are determined by precipitation and water management in the greater Everglades
watershed. The watershed begins in the Kissimmee River basin, which drains into Lake
Okeechobee, which is drained by canals. Some canals move water to the Atlantic or Gulf
coasts, while others flow south through the Everglades Agricultural Area (EAA). These
southern canals then pass through the marsh on their way to outlets along the east coast
(Figure 1). Some water in these canals eventually goes into the marsh, either by direct
pumping, by overbank flow, or by seepage through levees. In the EAA, the canals are
used for irrigation and drainage, depending on the season and on local rainfall. In drier
years, less water is discharged from the EAA downstream into the marsh. There was far
less discharge in the wet season of 2014 than in the wet season of 2005 (Figure 3).
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WCA2
WCA3AN
Legend
Everglades Design Sites
Symbol
A Fall 2005
Q Fall 2011
K WCA3AS >
Everglsces
Canal VfcKi
m
Everglades Phase IV Sampling Locations
September 2014
yv * ^
tox
%
WCA3B
Figure 1. REMAP station draw for the September 2014 survey. Subareas shown are
Everglades National Park (ENP); Water Conservation Areas 3A North (WCA3AN), 3A
South (WCA3AS), 3B (WCA3B), and 2 (WCA2); and Loxahatchee National Wildlife
Refuge (LOX). The triangles are re-visits of 2005 wet season stations and the circles are
new visits. The thin blue lines are drainage canals.
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WATER DEPTH
WET SEASON
SEPTEMBER 1995
WATER DEPTH
WET SEASON
SEPTEMBER 2014
WATER DEPTH
WET SEASON
NOVEMBER 2005
3.0
— 2.0
— 1.0
— O.O
5.0
4.0
Figure 2. Wet season water depths during the 1995, 2005, and 2014 Everglades
Ecosystem Assessments. The black dots are biogeochemical sampling station locations.
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Water Flow at Selected Everglades Structures
300000
250000
200000
150000
100000
50000
S-8
S-12C+D
I
1
Figure 3. Cumulative discharge, in cubic feet per second (cfs), in the summer months of
2005 and 2014 at water control structures discharging from the EAA into WCA3 (S-8,
solid bars) and from WCA3 into ENP (S-12 C + S-12 D, crosshatched bars). Blue bars
are June through October 2005, green bars are August through October 2005, and red
bars are June through August 2014. The 2005 sampling occurred during November and
the 2014 sampling occurred during September. Blue bars represent the entirety of the
wet season prior to sampling; red and green bars represent the three months prior to
sampling. Data from DBHydro (https://www.sfwmd.gov accessed 4/17/2015).
Results and Discussion
This section is focused on the three contaminants of concern discussed in the Introduction
- mercury, phosphorus, and sulfur. We also include new information on soil thickness,
since historical soil loss in the northern Everglades is still a matter of ecological concern
to be addressed by the Central Everglades Planning Project, which is a part of CERP.
The section concludes with a brief summary of all analyses, observations, and
measurements conducted for the survey. Except where noted, all findings refer to the
study area as a whole.
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Mercury
Mercury burdens in mosquitofish have declined sharply over the history of Everglades
REMAP (Figure 4). EPA recognizes a predator protection threshold of 77 nanograms per
gram (ng/g) (USEPA 1997). In 2014, for the first time, both the median and even the
entire interquartile range were below this threshold. However, as Figure 5 shows, there
were still places in the system where that level was exceeded, as was the U.S. Fish and
Wildlife Service's threshold (Eisler 1987) of 100 ng/g for protection of piscivorous birds
and mammals. In fact, mercury in largemouth bass still exceeded the 300 ng/g criterion
for protection of human health throughout the system (Julian et al. 2016), and a gamefish
consumption advisory is still in effect system-wide (Florida Department of Health 2017).
Total Mercury (ng/g) in Mosquitofish in the Wet Season
600
500
400
300
200
100
Predator Protection
Level is 77 ng/g
~ Median
~ 25%-75%
£ Non-Outlier Range
-100
1995
2005
2014
Figure 4. Box-and-whisker plots of total mercury in mosquitofish, by survey year. The
non-outlier range includes 99, 95, and 93 % of the data for 1995, 2005, and 2014,
respectively.
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MOSQUITOFISH MERCURY
WET SEASON
SEPTEMBER 1995
MOSQUITOFISH MERCURY
Figure 5. Krigs of total mercury in mosquitofish, in micrograms per kilogram (ug/kg),
over the history of REMAP surveys.
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Consistent with the other analyses, the CDF curves have also shifted considerably (Figure
6). The solid black vertical line in the figure is at 77 ng/g (or 77 ug/kg). The dashed
green horizontal lines are the corresponding y-intercepts, showing the proportion of the
system below that level. In 2014 the intercept was at 87%, thus only 13 % of the marsh
was above 77 ng/g. The 95% confidence interval about this estimate is + 6 %, well
within the data quality objective for the Program of + 10 %. The apparent differences
among the curves are statistically significant (Wald F, P < 0.05). Analysis of variance
indicated that the lower concentrations observed in 2014 compared to 2005 cannot be
explained by fish length or weight.
Figure 6. Cumulative distribution function (CDF) curves of total mercury in
mosquitofish in the wet season, showing changes over the course of REMAP.
The changes described here for the whole study area also apply to all four major subareas
(ENP and the three WCAs). The CDFs (not shown here) for those places in 2014 are all
different than in 2005 and in 1995 (Wald F, P < 0.04).
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There was less mercury in mosquitofish because there was less methyl mercury in the
system (Figures 7 and 8). Methyl mercury is the form of mercury that is bio-accumulated
via the food web. The pattern of change in methyl mercury concentrations in surface
water (Figure 7) resembles the pattern for total mercury concentrations in mosquitofish
(Figure 4). There have been consistent declines in the median, the interquartile range,
and the non-outlier range for both analytes over the course of the REMAP surveys. The
apparent differences among the CDF curves in Figure 8 are statistically significant (Wald
F, P < 0.05).
Methyl Mercury (ng/L) in Surface Water in the Wet Season
1.0
0.8
0.6
0.4
0.2
0.0
~ Median
~ 25%-75%
£ Non-Outlier Range
-0.2
1995
2005
2014
Figure 7. Box-and-whisker plots of methyl mercury [nanograms per liter (ng/L)] in
surface water, by survey year. The non-outlier range includes 91, 94, and 90 % of the
data for 1995, 2005, and 2014, respectively.
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Methyl Mercury in Surface Water (ng/L)
Figure 8. CDF curves of methyl mercury in surface water in the wet season, showing
changes over the course of REMAP.
The changes described here for the whole study area also apply to the three WCAs for
2014 compared to 2005, and for 2014 compared to 1995. The CDFs (not shown here) for
those three places in 2014 are all different than in 2005 (Wald F, P < 0.02); and 2014 is
also different than in 1995 (Wald F, P < 0.01).
There was also less total mercury in surface water at the time of the survey in 2014
(Figure 9). As compared to 1995, the curves show a slight increase in the 2005 survey
and a noticeable decrease in 2014. Both differences are significant (Wald F, P < 0.05).
As the units on the x-axes of Figures 8 and 9 show, methylated mercury is present in
concentrations that are about an order of magnitude less than total mercury.
The bulk of total mercury in surface water consists of inorganic mercury atoms that are
deposited from the atmosphere (reviewed in Liu et al. 2008). Atmospheric deposition of
mercury is influenced by precipitation, by local sources, and by global sources and air
circulation patterns. Though there has been a decline in global atmospheric mercury
emission in recent years (Zhang et al. 2016), wet deposition by summertime
thunderstorms in the study area was unchanged in 2014 compared to 2005 (Julian et al.
2016). For example, Table 1 shows data from the monitoring station at Everglades
National Park that is part of the Mercury Deposition Network of the National
Atmospheric Deposition Program (MDN-NADP). There was no difference in mercury
loading between 2005 and 2014. A hypothetical reason for finding less total mercury in
the water column in 2014 is that the residence time of that water was longer than in
previous surveys, because discharge into the system, and therefore possible outflow from
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it, was so much lower. Longer residence time provides a greater opportunity for removal
of mercury from the water column by a variety of mechanisms, and elemental mercury
has less affinity for water than for other ecosystem compartments, notably soil (Liu et al.
2008).
Total Mercury (ng/L) in Surface Water
Figure 9. CDF curves of total mercury in surface water in the wet season, showing
changes over the course of REMAP.
The change described here for the whole study area comparing 2014 to 2005 also applies
to all four of the major subareas. The CDFs (not shown here) for those places in 2014 are
all different than in 2005 (Wald F, P < 0.01). The CDFs are different for 2014 compared
to 1995 for the Park and WCA1 subareas (Wald F, P < 0.01).
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Table 1. Weekly measurements of wet deposition of atmospheric total mercury from
June through September at Everglades National Park in 2005 (Phase III) and 2014 (Phase
IV), in ng/m2 2005 sampling was completed during November, while 2014 sampling
was completed during September. The two years are not different (t-test, P = 0.42). Data
from MDN-NADP (http://nadp.sws.uiuc.edu/mdn/ accessed 11/4/16).
Phase III Phase IV
187.15 637.36
2079.07 765.63
1864.39 1596.65
349.76 883.83
428.5 91.34
850.65 480.69
89.38 2217.73
302.59 1382.86
1234.8 1853.69
593.14 768.74
579.12 830.2
511.25 379.29
572.14 120.4
1422.04 478.23
135.89 525.33
1388.44 101.57
90.57 300.3
1523.39 24.74
789.015 746.5878 mean
14202.27 13438.58 sum
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Phosphorus
Successive surveys have shown consistently less total phosphorus in surface water
(Figure 10). Both the Miccosukee Tribe of Indians and the State of Florida have adopted
a 10 micrograms per liter (ug/L) water quality criterion for total phosphorus for the parts
of the Everglades within their jurisdiction. The CDF curves reveal that the proportion of
the marsh above the water quality criterion has been cut in half twice. The differences
are statistically significant (Wald F, P < 0.05). The State of Florida has been building
stormwater treatment areas (STAs) in the Everglades Agricultural Area to remove
phosphorus from water flowing into the native marsh. As of 2012 there were 57,000
acres of STAs. In Water Year 2016 (which included September 2014), over 80 % of the
total phosphorus leaving EAA farms was removed by STAs before it got to the public
Everglades (SFWMD 2016).
Figure 10. CDF curves of total phosphorus in surface water in the wet season, showing
changes over the course of REMAP. The 10 ug/L water quality standard is circled on the
x-axis.
The Park and WCA3 had less total phosphorus in surface water in 2014 than in 1995. The
CDFs (not shown here) for both places are different between years (Wald F, P < 0.01).
For 2014 only the WCA1 subarea had less phosphorus in surface water than in 2005
(Wald F,P< 0.01).
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Though phosphorus enters the public Everglades in surface water, it exerts an impact in
the soil. Despite a remarkable decrease in total phosphorus loading via inflowing water
over the course of REMAP, there was no change in its concentration in the soil system-
wide from 2005 to 2014 (Figure 11; Wald F, P = 0.82). For all four subareas there was
no change in soil phosphorus in 2014 as compared to 2005. There was an increase in
2005 from the mid-1990s (Wald F, P < 0.05). System-wide, the median concentration
went from 343 mg/kg in the mid-1990s to 390 mg/kg in 2005 and 2014. The Refuge and
WCA3 had more total phosphorus in soil in 2014 than in 1995. The CDFs (not shown
here) for both places are different between years (Wald F, P < 0.05). These findings
indicate the effect of continued, though diminished, loading of phosphorus above
background levels, which are less than 4 ug/L (Figure 10). Forty-six percent of the marsh
is still above the CERP goal of 400 mg/kg (Figure 11).
100
go
8o
70
6o
50
40
30
20
10
0
Above CERP goal
Below CERP goal
2005
¦Estimate of Marsh Area 2005
-Lower 95% Confidence Limit 2005
-Upper 95% Confidence Limit 2005
¦Estimate of Marsh Area 2014
- Lower 95% Confidence Limit 2014
- Upper 95% Confidence Limit 2014
300 400 500 600 700 800 900 1000
Total Phosphorus in Soil (mg/kg)
100 200
Figure 11. CDF curves of total phosphorus in soil in the wet season, showing no change
between 2014 and 2005.
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Sulfur
The pattern of change in methyl mercury (Figure 7) resembles the pattern for sulfate
(Figure 12). There have been consistent declines in the median, interquartile range, and
non-outlier range for sulfate over the course of the REMAP surveys. The analytical
method detection limit (MDL) improved by two orders of magnitude between 1995 and
2005, so the apparent differences between those surveys in Figure 12 are probably
exaggerated. The 2014 median was below the CERP goal of 1 mg/L, and very close to
background level which is near 0.
26
24
22
20
18
16
14
12
10
8
6
4
2
0
-2
Sulfate (mg/l) in S urface Water in the Wet Season
MDL = 2 —~
~ Median
~ 25%-75%
£ Non-Outlier Range
CERP goal is 1 mg/l
MDL = 0.02
1995
2005
2014
Figure 12. Box-and-whisker plots of sulfate in surface water, in milligrams per liter
(mg/l), by survey year. The non-outlier range includes 86, 85, and 88 % of the data for
1995, 2005, and 2014, respectively.
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Elevated sulfate levels in 2014 followed the same landscape pattern as in previous years
(Figure 13), though the influence of canal overflows into the marsh in the wet season was
more apparent in 2005. There was some spatial correspondence between moderately
elevated sulfate in water and moderately elevated mercury in mosquitofish (Figure 5).
The highest sulfate concentrations originate within the Everglades Agricultural Area
(Scheidt and Kalla 2007). Sources include legacy deposits in the soil in the EAA, where
sulfate was, and continues to be, used as a soil amendment (Julian et al. 2016).
SULFATE
WET SEASON
SEPTEMBER 1996
SULFATE
WET SEASON
NOVEMBER 2005
SULFATE
WET SEASON
SEPTEMBER 2014
Figure 13. Krigs of sulfate in surface water in the wet season over the history of REMAP
surveys. Some of the heavy black lines in and around the study area are levees and
canals.
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The data for the CDF curves for all years in Figure 14 were truncated at the 1995 MDL of
2 mg/L. Despite this censorship and considerable overlap of confidence intervals, the
curves are all different (Wald F, P < 0.05). The same temporal pattern observed in most
other analytes also held for sulfate. The STAs do little to remove sulfate from water that
will enter the public Everglades. As with other pollutants, concentrations in surface
water are influenced by precipitation in the EAA and the marsh, and by local water
management practices.
2005
^^Estimate of Marsh Area 2014
Lower 95% Confidence Limit 2014
Upper 95% Confidence Limit 2014
^Estimate of Marsh Area 2005
— Lower 95% Confidence Limit 2005
— Upper 95% Confidence Limit 2005
^^Estimate of Marsh Area 1995
Lower 95% Confidence Limit 1995
Upper 95% Confidence Limit 1995
o -i 1 1 1 1 1 1 1 1
o 5 io 15 20 25 30 35 40
Surface Water Sulfate (mg/L)
1995
Figure 14. CDF curves of sulfate in surface water in the wet season, showing changes
over the course of REMAP.
The Park, the Refuge, and WCA3 had less sulfate in surface water in 2014 than in 2005
(Wald F,P< 0.02).
Conclusion and Synthesis on Mercury. Sulfur, and Phosphorus
Comparing the 2014 REMAP survey to prior surveys, antecedent discharge from the
EAA at S-8 appeared to be down, sulfate in surface water was down, methyl mercury in
surface water was down, and total mercury in mosquitofish was down. Program data
over two decades of REMAP show that mercury in mosquitofish was strongly associated
with other constituents including moderate levels of sulfate in surface water (Pollman
2012). There was some spatial correspondence between moderately elevated sulfate in
SESD Project ID Number: 14-0380
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water and moderately elevated mercury in mosquitofish. This association was spatially
explicit, most obviously in Phase III (Scheidt and Kalla 2007). Any inorganic mercury
present in surface water can be methylated by sulfur-reducing bacteria (SRB) if sulfate
concentration is above background. Methylated mercury can be efficiently
bioaccumulated by mosquitofish where phosphorus in soil is not so high that the habitat
has become poor (Poilman 2014), resulting in a depauperate food web (Abbey-Lee et al.
2013), and where sulfate is not so high that toxic levels of sulfide are also present.
Soil Thickness
There has been no change in soil thickness over the study area as a whole during the
course of REMAP. Figure 15 shows the pooled data. In previous decades, peat loss due
to drainage, oxidation, and subsidence was severe in northern WCA3 A and the
northeastern corner of ENP (reviewed in Scheidt and Kalla 2007). Current sample sizes
are too small in these sub-areas to detect recent changes in either direction, but future
surveys may provide enough data to do so.
SESD Project ID Number: 14-0380
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Figure 15. Krig of soil thickness (feet) based on REMAP data. The inset figure from the
1940s (Davis 1946) has a similar scale.
Project Analvtes by Media
Much other physical and biogeochemical data was generated during the course of the
project that is not discussed in this report. All data were collected to describe, diagnose,
and predict the ecological health of the Everglades. Subsequent reports and publications
SESD Project ID Number: 14-0380
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by various Principal Investigators will include this information. The following is a
complete listing of all measurements taken and observations made, many of which are
potential explanatory variables that could be used to model mercury in mosquitofish.
These data were obtained at every station where the given medium was present to
sample, measure, or observe. The letters in parentheses are measurement, media, and
analyte codes used in the variable names in Table 2 and in the correlation matrix that
comprises the Appendix.
Field Data on Surface Water, Soil, Floe, Periphyton, and Vegetation:
TEMPERATURE (TEMP)
CONDUCTIVITY (COND)
PH
TURBIDITY (TURB)
DISSOLVED OXYGEN (DO)
OXIDATION-REDUCTION POTENTIAL (ORP)
WATER DEPTH (WATDEPAV)
SOIL THICKNESS (SOILTHAV)
FLOC THICKNESS (FLOCTHAV)
BENTHIC PERIPHYTON THICKNESS (PBTHAV)
SOIL TYPE
PERIPHYTON % COVER (PERICOV)
PERIPHYTON GROWTH FORMS PRESENT
WATER COLUMN PERIPHYTON BIOVOLUME (PERIVOL)
VEGETATIVE COMMUNITY TYPE
DOMINANT MACROPHYTE
CATTAIL PRESENCE
Laboratory Analytical Data:
Surface Water (SW)
CHLORIDE (CL)
SULFATE (S04)
DISSOLVED ORGANIC CARBON (DOC)
TOTAL ORGANIC CARBON (TOC)
TOTAL PHOSPHORUS (TP)
SOLUBLE REACTIVE PHOSPHORUS (SRP)
FILTERED NITRATE+NITRITE (FNN)
FILTERED NITRATE (FN03)
FILTERED NITRITE (FN02)
FILTERED AMMONIA (FNH4)
TOTAL NITROGEN (TN)
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CHLOROPHYLL A (CHLA)
TOTAL MECURY (THG)
METHYL MERCURY (MEHG)
Bottom Water (BW)
SULFIDE (H2S)
Floe (FC)
pH
WATER CONTENT (H20)
ASH-FREE DRY WEIGHT (ASH)
BULK DENSITY (BD)
TOTAL CARBON (TC)
TOTAL NITROGEN (TN)
TOTAL PHOSPHORUS (TP)
CHLOROPHYLL A (CHLA)
TOTAL MERCURY (THG)
METHYL MERCURY (MEHG)
Soil (SD)
PH
WATER CONTENT (H20)
ASH-FREE DRY WEIGHT (ASH)
ORGANIC MATTER (OM)
BULK DENSITY (BD)
TOTAL CARBON (TC)
TOTAL NITROGEN (TN)
TOTAL PHOSPHORUS (TP)
TOTAL MERCURY (THG)
METHYL MERCURY (MEHG)
Sciwgi'ciss Leaf Clippings (VCj)
TOTAL CARBON (TC)
TOTAL NITROGEN (TN)
TOTAL PHOSPHORUS (TP)
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Whole Saw grass Plants, Above-ground Parts (SGA)
TOTAL MERCURY (THG)
METHYL MERCURY (MEHG)
Whole Sawgrass Plants, Below-ground Parts (SGB)
TOTAL MERCURY (THG)
METHYL MERCURY (MEHG)
Benthic Periphyton (PB) and Water Column Periphyton (PC)
pH
WATER CONTENT (H20)
ASH-FREE DRY WEIGHT (ASH)
BULK DENSITY (BD)
TOTAL CARBON (TC)
TOTAL NITROGEN (TN)
TOTAL PHOSPHORUS (TP)
CHLOROPHYLL A (CHLA)
TOTAL MERCURY (THG)
METHYL MERCURY (MEHG)
Mosquitofish (FS)
TOTAL MERCURY (THG)
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Summary statistics for all continuous variables are presented in Table 2. The order of the
variables matches the order in the correlation matrix. The last two letters in each name of
a measurement are laboratory codes. Five different laboratories were used in the project,
the FIU mercury lab (FC), FIU nutrient lab (FB), FIU soil lab (FS), EPA field lab (EE),
and EPA Regional lab at SESD (EA). As an example of the codes given above and on
the preceding pages, the first measurement in Table 2 is THGFSFC, which is total
mercury in mosquitofish analyzed at the FIU mercury lab.
Table 2. Minimum, 25th percentile, median, 75th percentile, maximum, and sample size
for all continuous data generated for the 2014 REMAP survey.
measurement
unit
min
25th %-ile
median
75th %-ile
max
n
THGFSFC
ng/g
4.9
22
33.5
54
270
104
THGSWFC
ng/L
0.63
1.2
1.6
2.08
3.5
116
MEHGSWFC
ng/L
0.02
0.064
0.1
0.18
0.69
116
CHLAFCFB
mg/g
0.014
0.173
0.34
0.683
2.4
64
THGFCFC
ng/g
5.9
81.25
120
160
290
96
MEHGFCFC
ng/g
0.04
1.13
2.55
5.68
32
96
THGSDFC
ng/g
19
94
150
200
290
117
MEHGSDFC
ng/g
0.04
0.36
0.77
1.85
7.9
117
CHLAPBFB
mg/g
0.008
0.068
0.14
0.29
1
31
THGPBFC
ng/g
3.6
11.5
24
46
160
42
MEHGPBFC
ng/g
0.065
0.255
0.505
1.125
8.5
42
CHLAPCFB
mg/g
0.052
0.29
0.6
0.95
2.8
71
THGPCFC
ng/g
5.9
13
19
33
130
71
MEHGPCFC
ng/g
0.077
0.66
1.8
3
16
71
FLOCTHAV
cm
0
0.9
2.7
6.1
18.7
117
PBTHAV
cm
0
0
0
0.8
5.7
117
PERICOV
%
0
0
20
80
100
117
PERIVOL
mL
0
0
50
285
2500
117
THGSGAFC
ng/g
4.3
5.7
6.2
7.4
9.8
27
THGSGBFC
ng/g
3.7
6.4
9.4
13
25
27
MEHGSGAFC
ng/g
0.12
0.15
0.18
0.26
0.44
27
MEHGSGBFC
ng/g
0.24
0.38
0.52
0.77
3.2
27
CLSWEA
mg/L
7
21
36
61
100
116
S04SWEA
mg/L
0.022
0.033
0.39
4.225
48
116
DOCSWEA
mg/L
8.7
15
18
21
32
116
TOCSWEA
mg/L
9.4
15
18
21
32
116
TPSWFB
ug/L
3.4
5.3
6.6
8.6
34
116
SRPSWFB
ug/L
0.9
0.9
1
1.6
19
116
FNNSWFB
mg/L
0.0008
0.0016
0.0023
0.0048
0.042
116
FN03SWFB
mg/L
0.0001
0.0006
0.00135
0.0049
0.041
116
FN02SWFB
mg/L
0.0004
0.001
0.0012
0.0014
0.0026
116
FNH4SWFB
mg/L
0.004
0.0095
0.013
0.02
0.21
116
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TNSWFB
mg/L
0.36
0.54
0.66
0.85
1.2
116
CHLASWFB
ug/L
0.3
1.6
3.0
5.8
58
116
H2SBWEE
mg/L
0.007
0.009
0.012
0.033
0.6
116
pHFCFS
std units
6.23
7.19
7.54
7.69
8.2
64
H20FCFS
%
66
96
98
98
99
64
ASHFCFS
%
5.8
10.1
14.5
32.8
84
64
BDFCFS
g/cc
0.01
0.01
0.02
0.04
0.36
64
TCFCFS
mg/g
170
350
410
450
490
64
TNFCFS
mg/g
7.3
27.3
32
38
44
64
TPFCFB
mg/g
0.100
0.405
0.530
0.668
1.200
64
pHSDFS
std units
6.37
7.25
7.54
7.76
8.7
117
H20SDFS
%
43
80
88
91
99
117
ASHSDFS
%
3.3
12
20
67.5
93
117
OMSDFS
%
7
32.5
80
88
96.7
117
BDSDFS
g/cc
0.04
0.08
0.11
0.19
0.6
117
TCSDFS
mg/g
75
210
430
460
530
117
TNSDFS
mg/g
4.4
15
29
33
46
117
TPSDFB
mg/g
0.100
0.270
0.390
0.490
1.700
117
TCVGFS
mg/g
98
460
470
470
500
60
TNVGFS
mg/g
6
8.5
9.4
11
16
60
TPVGFB
mg/g
0.210
0.243
0.280
0.310
0.550
60
pHPBFS
std units
7.42
7.69
7.91
8.07
8.54
31
H20PBFS
%
55
81
84
93
97
31
ASHPBFS
%
8.4
40
66
76
79
31
BDPBFS
g/cc
0.01
0.08
0.15
0.23
0.44
31
TCPBFS
mg/g
180
200
220
280
440
31
TNPBFS
mg/g
7.3
9.4
12
19
37
31
TPPBFB
mg/g
0.064
0.093
0.130
0.220
0.550
31
pHPCFS
std units
6.71
7.68
7.84
8.05
8.39
71
H20PCFS
%
80
91
95
96
98
71
ASHPCFS
%
7
23
49
62
80
71
BDPCFS
g/cc
0.02
0.04
0.06
0.09
0.26
71
TCPCFS
mg/g
190
230
270
360
460
71
TNPCFS
mg/g
5.3
10
15
20
42
71
TPPCFB
mg/g
0.049
0.091
0.150
0.280
2.100
71
TEMP
C
24
27.61
28.92
30.31
34.3
116
COND
umhos/cm
48
315
386
489
780
116
PH
std units
5.84
7.08
7.26
7.56
8.25
116
TURB
NTU
0.0
0.3
0.7
1.7
12.6
116
DO
mg/L
0.65
2.33
4.00
6.37
10.64
116
ORP
mV
-189.6
-11.8
23.7
127.2
196.7
115
WATDEPAV
feet
0.00
0.99
1.52
2.10
3.83
118
SOILTHAV
feet
0.07
1.27
2.28
3.97
12.07
118
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In addition to the critical analytes and media discussed earlier in this report, specific uses
of other measurements and media will be as follows. As requested by the EPA Region 4
Water Protection Division, most of the mercury, nutrient, and carbon data, as well as
physical and chemical measurements of periphyton, floe, and soil, will be used in mass
balance calculations for the study area by Principal Investigators at FIU. Chlorophyll-a is
a measure of the palatability of periphyton (Sargeant et al. 2011) and food value (carbon
quality) of floe (Neto et al. 2006, Pisani et al. 2015), which can be used in mercury
modeling by other members of the South Florida scientific community. Elevated
chloride levels occur in connate seawater that appears in canals that drain the EAA, and
thus could be used by the community to trace the sheet-flow of canal water through the
marsh.
Correlation Analysis
The correlation matrix in the Appendix presents Spearman rank order correlations. This
approach is non-parametric, which does not assume that the data distribution is normal.
The Shapiro-Wilk test for normality indicted that most data were not normally
distributed.
The Spearman results show that no single variable was found to have a statistically robust
association [coefficient (rho) > 0.7 and p < .001] with mercury in mosquitofish. The
palatability, nutritional status, and methyl mercury content of benthic periphyton were
moderately correlated with mosquitofish mercury (chlorophyll-a Spearman rho = 0.512,
total carbon rho = 0.466, total nitrogen rho = 0.433, ash content rho = - 0.549, water
content rho = 0.435, methyl mercury rho = 0.370, all .001
-------
Total phosphorus (TP) in soil was moderately inversely correlated with benthic
periphyton thickness (rho = - 0.401 ,P< .001), water column periphyton volume
(rho = - 0.426, p < .001), and total periphyton cover (rho = -0.534, p < . 001). These
relationships indicate the negative effect of elevated soil phosphorus on the native ridge
and slough community. This diverse community is dominated by periphyton in the
sloughs and sawgrass on the ridges. Where excessive phosphorus has accumulated in the
soil, the native community can be replaced by invasive cattail (Scheidt and Kalla 2007).
Sawgrass size responds positively to soil phosphorus (Stober et al. 2001). Sawgrass can
be twice as tall (~2 m) and twice as dense (above 50 culms/m2) in high phosphorus
locations (Richards and Kalla, unpublished data from 2005 REMAP survey). Such
habitats have periphyton largely excluded and have less aquatic food web diversity and
shorter food chain length (King and Richardson 2007, Wang et al. 2014).
Sulfate was moderately to strongly correlated with other constituents of agricultural
drainage water - organic carbon (TOC rho = 0.661), phosphorus (TP rho = 0.427), and
chloride (rho = 0.735) (all p < .001). Sulfide in bottom water was moderately associated
with sulfate and organic carbon in surface water (sulfate rho = 0.362, DOC rho = 0.378,
both p < .001) and with water depth (rho = 0.546, p < .001), and strongly inversely
correlated with oxidation-reduction potential measured at the bottom of the water column
(rho = - 0.605, p < .001). Field studies subsequent to the 2014 survey (Kalla et al. 2017)
showed that sulfide in bottom water was an acceptable predictor of sulfide in pore water
in the Everglades.
Path analysis uses a correlation matrix as input. Such an analysis of the REMAP data can
produce structural equation models relating multiple variables to each other and, directly
or indirectly, to mosquitofish mercury (Poilman 2014).
Quality Assurance
Laboratory Audits
Prior to the survey, an independent Project Quality Assurance Officer (QAO), assisted by
other staff from the Quality Assurance Section (QAS) at SESD, audited all participating
laboratories at FIU and SESD, including the portable lab of the in-house contractor field
chemist. A small number of corrective actions were identified and implemented. There
were no findings that compromised use of any data to fulfill the Project's data quality
objectives as defined in the Quality Assurance Project Plan (QAPP).
Pre-survev Blanks
At SESD, rinse blanks are run on equipment and supplies before they are used in the
field. This precaution falls within the SESD Quality Management Plan and is overseen by
QAOs. For REMAP, 29 blanks were run on sample bottles and gloves, by lot, and on all
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vacuum chambers, for trace-level mercury. Another 57 blanks were run for bottles,
gloves, and filtration syringes and filters, as applicable, for total phosphorus, sulfate,
dissolved organic carbon, and the nitrogen series.
Mercury
Three sequential blanks were run on each of the four chambers. During this process, all
of them were cleaned so that the second and third blanks were non-detect for every
chamber.
Other Analytes
Total nitrogen (TN) and sulfate were detected in glove blanks. These blanks were made
by submersing a glove in a beaker of water. This method was inapplicable to the
Program since the vacuum chambers were used to draw all surface water samples. No
glove ever touched the water during sampling. All other blanks for TN and sulfate, as
well as all blanks for all other analytes, were non-detects.
Summary
Results from the pre-survey blanks demonstrated that there was no contamination of the
sampling equipment and supplies that could have compromised the data for critical
analytes in surface water from the Everglades. The solid media did not need to be
blanked, since only water has low analyte levels that could be affected by contamination.
Field Procedures
Training overseen by the Program Leader on field procedures was provided to all
biogeochemical sampling crew members before the start of the survey in order to assure
consistency and adherence to the methods described in the QAPP. Training consisted of
classroom presentations, field simulations conducted in the Athens, GA area, and
demonstrations given on-site in the Everglades. During the field simulations, emphasis
was placed on avoiding cross-contamination between stations. Discussion during the on-
site demonstrations focused on safety, accuracy, and efficiency.
All media were sampled in accordance with the QAPP. Field laboratory operations were
also conducted in accordance with the QAPP. The QAPP references SESD's applicable
Standard Operating Procedures, as well as the Quality Management Plans of all
participating laboratories.
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Field Blanks
Trip blanks, air deposition blanks, and vacuum chamber blanks for trace-level mercury in
water were collected daily during the survey. Trip blanks and vacuum chamber blanks
were also collected daily for sulfate. A total of 264 blanks was produced.
Mercury
All blanks were non-detect.
Sulfate
All blanks were below the Method Reporting Limit (MRL) of 0.10 mg/L. Eight were
very slightly above the MDL of 0.022 mg/L, ranging up to 0.058 mg/L. These low-level
findings did not affect the environmental data, aside from presenting a small potential for
extremely slight upward bias in the very bottom of the data distribution, which is of no
scientific or management interest. For comparison, the field samples included 21 non-
detects and 18 values between the MDL and MRL, while ranging up to as much as 48
mg/L.
Field Duplicates and Laboratory Splits
Eight stations were duplicated for surface water for all analytes except chlorophyll-a.
Two stations were duplicated for sediment, and another four sediment samples were split
after homogenization at the field operations base. One station was duplicated twice for
chlorophyll-c/. In order to obtain sufficient sample volume for laboratory analytical
requirements and meet QA requirements, all stations were duplicated for DOC and seven
stations were quadruplicated for DOC. A total of 536 data values were generated from
the duplicate and split samples.
Methyl Mercury
The Relative Percent Difference (RPD) threshold of 30 % specified in the QAPP was
exceeded twice for methyl mercury in split sediment samples and once for a duplicate
sediment sample. It was also exceeded in four surface water duplicates.
The surface water duplicates are potentially of greater concern because methyl mercury
in surface water is an important variable in models of mercury bioaccumulation in
mosquitofish. However, all values of duplicate pairs were at or near the MRL (0.060
ng/L), where analytical variation is greatest. And, assuming that the true concentration is
better approximated by more than one measurement, the averages of the pairs are all at or
below the minimum associated with threshold mercury levels in mosquitofish as shown
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by past Program data (approximately 0.2 ng/L). Therefore, these exceedances likely do
not indicate that the data are not reliable for Program purposes.
Of the two sediment splits that exceeded 30 % RPD, one yielded values that were both
near the MRL of 0.12 ng/g. The other was just over the limit, at 37 %. While this split
could suggest that homogenization of the sample was insufficient, no other analytes from
this sediment sample split exceeded the threshold.
A duplicate sediment sample exceeded the 30% RPD threshold. The concentrations in the
sample and the duplicate were 0.39 and 0.23 ng/g respectively (41% RPD). The range
of methyl mercury in sediment system-wide was 0.04 to 7.9 ng/g (n=l 17, Table 2). The
difference between the sample and the duplicate was only 2% of the range. These results
indicate the minor heterogeneity present in sediment at the plot scale.
Nitrogen Series
There were eight exceedances for duplicates of filtered nitrogen compounds in surface
water. All associated values were very small, with measured concentrations of ammonia,
nitrate+nitrite, and nitrite falling between the MDL and the MRL (generally in the
10,000ths to lOOOths of a milligram per liter). Nitrate was calculated by subtracting
nitrite from nitrate+nitrite. All values were considered estimates due to the lessened
certainty of results below the MRL.
Other Analytes
Duplicates of soluble reactive phosphorus (SRP) and sulfate in surface water exceeded 30
% RPD at one station each, out of 8 stations. The sulfate values were both below the
MRL of 0.10 mg/L. The SRP values were also very small, one a non-detect (assigned a
result equal to the MDL) and the other below the MRL.
One duplicate, at station 27, for total phosphorus (TP) in surface water had an RPD of 47
%. The seven other duplicates ranged from 0-27 %. The exceedance pair included a
value of 17 ug/L, whereas all other values ranged from 1.4 to 12 ug/L. Samples in
containers for TP were also analyzed for total nitrogen (TN). At station 27 the RPD for
TN was 3 %. Filtered water was analyzed for SRP and the nitrogen series, all from the
same container. The RPD for SRP from station 27 was 0 %, while those for the nitrogen
series ranged from 18-27 %. These results, in the aggregate, suggest that there was no
failure of sampling or analytical technique that led to the 47 % RPD for TP at station 27.
One laboratory split for TN in sediment yielded an RPD of 34 %, slightly above the 30%
threshold. While this split could suggest that homogenization of the sample was
insufficient, no other analytes from this sample split exceeded the threshold.
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Both duplicates from station 262 for chlorophyll-a in surface water resulted in
exceedances. Except for methyl mercury discussed above, no other duplicate from
surface water at that station exceeded the threshold. The chlorophyll-a results were more
likely to have been caused by fine-scale variation in the contagious distribution of
phytoplankton in the water column.
No RPD exceedances occurred for any other duplicated or split analytes. All standard
deviations of quadruplicate DOC values were less than 7 % of any DOC measurement.
Summary
No field duplicates or laboratory splits indicated that survey data were compromised.
This finding applies particularly to the elements critical to the Program - mercury,
phosphorus, and sulfur. It is noteworthy that there were no RPD exceedances for total
mercury in surface water and sediment, and none for total phosphorus in sediment.
Field logbooks
Logbooks were audited by the Project Leader, Associate Project Leader, or Field Quality
Assurance Officer on site at the end of each day of sampling. Implausible field data and
other deficiencies in record-keeping were noted and corrected where possible by the field
sampling crew, before leaving the field operations base. At each sampling site, 12
photographs were taken to document habitat and soils. Photographic records of sampling
activities were reviewed daily by the Project Leader, Associate Project Leader, or Field
Quality Assurance Officer to assure that field measurements and descriptions were
consistent with photographic evidence. Appropriate corrective actions were taken with
the sampling crews before their next day in the field.
Data Review
All laboratory analytical data values were subjected to a quality assurance process that
exceeded EPA standards. The process was applied to 100 % of the data for all analytes
except the nitrogen series and SRP, which were done at 10 %. The process consisted of
formal data review by the independent QAO and other QAS staff and in-house
contractors, verification of data transcription by staff from the SESD Ecology Section,
and validation by the Project Leader and Associate Project Leader. None of the
approximately 5000 laboratory analytical data values were rejected.
Field data were also subjected to 100 % verification and validation. This process was
iterative, as internal review of the calculations in an intermediate draft of this report
revealed a small number of values (9 out of about 1000) that required final editing.
SESD Project ID Number: 14-0380
Page 35 of 58
-------
References
Abbey-Lee, Robin N., Evelyn N. Gaiser and Joel C. Trexler. 2013. Relative roles of
dispersal dynamics and competition in determining the isotopic niche breadth of a
wetland fish. Freshwater Biology 58:780-792 doi: 10. Ill 1/fwb. 12084.
Breidt, F.J., and W.A. Fuller. 1999. Design of supplemented panel surveys with
application to the national resources inventory. Journal of Agricultural, Biological, and
Environmental Statistics 4(4):391-403.
Davis, John H., Jr. 1946. The Peat Deposits of Florida: Their Occurrence, Development
and Uses. Geological Bulletin No. 30. Florida Geological Survey. Tallahassee, Florida.
247 pp.
Diaz-Ramos, S., D.L. Stevens, Jr., and A.R. Olsen. 1996. EMAP statistical methods
manual. U.S. EPA, Corvallis, OR. EPA/620/R-96/002.
Eisler, R. 1987. Mercury hazards to fish, wildlife, and invertebrates: A synoptic review.
U.S. Fish and Wildlife Service Biological Report 85 (1.10). 90 pp.
Florida Department of Health. 2017. Your guide to eating fish caught in Florida.
http://www.floridahealth.gov/programs-and-services/prevention/healthy-
weight/nutrition/seafood-consumption/ documents/advisory-brochure.pdf. 41 pp.
Julian, Paul II, Binhe Gu, Garth Redfield and Ken Weaver, editors. 2016. South Florida
environmental report: Volume I, Chapter 3B: Mercury and sulfur environmental
assessment for the Everglades. South Florida Water Management District.
http://apps.sfwmd.gov/sfwmd/SFER/2016 sfer final/vl/chapters/vl ch3b.pdf. 47 pp.
Kalla, P.I., M. Parsons, and J. Ackerman. 2017. Operating procedure for bottom water
sampling for sulfide, SESDPROC-515-RO. USEPA Region 4, SESD, Athens, Georgia.
King, R.S., and C.J. Richardson. 2007. Subsidy-stress response of macroinvertebrate
community biomass to a phosphorus gradient in an oligotrophic wetland ecosystem.
Journal of the North American Benthological Society 26(3):491-508.
doi: http ://dx. doi. org/10.1899/06-002R. 1
Liu, G., Y. Cai, P. Kalla, D. Scheidt, J. Richards, L. J. Scinto, E. Gaiser, and C. Appleby.
2008. Mercury Mass Budget Estimates and Cycling Seasonality in the Florida
Everglades. Environmental Science and Technology 42:1954-1960.
Liu, G., Yong Cai, Yuxiang Mao, Daniel Scheidt, Peter Kalla, Jennifer Richards, Leonard
Scinto, Georgio Tachiev, David Roelant and Charlie Appleby. 2009. Spatial Variability
in Mercury Cycling and Relevant Biogeochemical Controls in the Florida Everglades.
Environmental Science and Technology 43 (12):4361-4366. DOI: 10.1021/es803665c
SESD Project ID Number: 14-0380
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Neto, Renato R., Ralph N. Mead, J. William Louda and Rudolf Jaffe. 2006. Organic
biogeochemistry of detrital flocculent material (floe) in a subtropical, coastal wetland.
Biogeochemistry 77:283-304.
Pisani, Olivia, Leonard J. Scinto, Jay W. Munyon and Rudolf Jaffe. 2015. The respiration
of flocculent detrital organic matter (floe) is driven by phosphorus limitation and
substrate quality in a subtropical wetland. Geoderma 241-2:272-282.
Pollman, C.D. 2012. Modeling sulfate and gambusia mercury relationships in the
Everglades (Technical No. SP696). Florida Department of Environmental Protection,
Tallahassee, FL.
Pollman, C. D. 2014. Mercury cycling in aquatic ecosystems and trophic-state related
variables—implications from structural equation modeling. Science of the Total
Environment 499:62-73.
Sargeant, Brooke L., Evelyn E. Gaiser, and Joel C. Trexler. 2011. Indirect and direct
controls of macroinvertebrates and small fish by abiotic factors and trophic interactions in
the Florida Everglades. Journal of Freshwater Biology DOI: 10.1111/j. 1365-
2427.2011.02663.x
Scheidt, D. J., and P.I. Kalla. 2007. Everglades ecosystem assessment: water
management and quality, eutrophication, mercury contamination, soils, and habitat:
monitoring for adaptive management: a REMAP status report. U.S. EPA Region 4,
Athens, GA. EPA 904-R-07-001. https://www.epa.gov/everglades/everglades-
ecosvstem-assessment-water-management-and-qualitv-eutrophication-mercury. 98 pp.
South Florida Water Management District. 2016. South Florida environmental report:
Highlights.
https://www.sfwmd.gov/sites/default/files/documents/2016 sfer highlights.pdf
Stevens, D.L., Jr. and A.R. Olsen. 2004. Spatially-balanced sampling of natural
resources. Journal of the American Statistical Association 99(465):262-278. DOI:
10.1198/016214504000000250
Stober, Q.J., K. Thornton, R. Jones, J. Richards, C. Ivey, R. Welch, M. Madden, J.
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assessment: Phase I/II (technical report) - Everglades stressor interactions:
Hydropatterns, eutrophi cation, habitat alteration, and mercury contamination. EPA 904-
R-01-003.
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SESD Project ID Number: 14-0380
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USEPA. 2015. National rivers and streams assessment 2013-14: Quality assurance
project plan. EPA-841-B-12-007. U.S. Environmental Protection Agency, Office of
Water, Washington, DC.
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September 23-29, 2013. SESD Project Identification Number: 13-0513. U. S. EPA
Region 4, Athens, GA. 22 pp.
USEPA. 2014b. Everglades ecosystem assessment phase IV quality assurance project
plan. U.S. EPA Region 4, Athens, GA. 135 pp.
Wang, Y., Gu, B., Lee, M. K., Jiang, S. J., Xu, Y. F. 2014. Isotopic evidence for
anthropogenic impacts on aquatic food web dynamics and mercury cycling in a
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564.
Zhang, Y, D.J. Jacob, H.M. Horowitz, L. Chen, H.M. Amos, D.P. Krabbenhoft, F. Slemr,
V.L. St. Louis, and E. Sunderland. 2016. Observed decrease in atmospheric mercury
explained by global decline in anthropogenic emissions. Proc. National Academy of
Sciences 113(3):526-531. doi: 10.1073/pnas.l516312113.
Acknowledgements
Collaborative support makes this Program possible. Extramural funding for REMAP IV
was provided by the South Florida Ecosystem Office of the National Park Service under
Interagency Agreement # P13PG7. EPA funding was from the Region 4 Water
Protection Division's South Florida Geographic Initiative and from the Office of Water.
The Department of Interior and the Park provided helicopter operations support.
Sampling permits or access permission were received from the Miccosukee Tribe of
Indians of Florida, the Arthur R. Marshall Loxahatchee National Wildlife Refuge, and
Everglades National Park.
The following individuals contributed significantly to REMAP IV:
Field Operations Base
Don Fortson, Field Support Team Leader
Kevin Simmons, Sample Manager
Louie Pounds, Field Chemist
Samplers
Jerry Ackerman*
Chris Decker*
Sue Dye*
SESD Project ID Number: 14-0380
Page 38 of 58
-------
Morris Flexner*
Hunter Johnson
Derek Little*
Jon McMahan*
Michael Roberts
John Ruiz*
Tim Simpson
Brian Striggow
Greg White*
(Note: Samplers with an asterisk were SESD Ecology Section members who also
contributed to method development, sample booking, the QAPP, inventory and
preparation of supplies, mapping, management of personal protective equipment, and
data verification.)
Base Support Personnel
Lonnie Dorn
Cornell Gayle
Linda George
TaraHouda
Nathan Mangle
Eric Somerville
Laboratory Quality Assurance Officers
Ray Terhune, Jeff Hendel
Field Quality Assurance Officers
Landon Pruitt, Art Masters
SESD Chemists
Pam Betts
Tony Campbell
Yvette Walcott
Danny Adams
SESD Quality Assurance Section
Denise Goddard
Sandra Aker
John Thomason
Jeff Wilmoth
EPA Region 4
Jennifer Shadle, Robyn Polinsky
HMC Helicopters. Inc.
Gary Freeman, Carlos Luque, Jorge Gomes
SESD Project ID Number: 14-0380
Page 39 of 58
-------
ENP Aviation Support
Clayton Camblin, Andrew Gill, Gary Carnall
DPI Office of Aircraft Safety
Margaret Gallagher
FIU On-site Logistical Support
Len Scinto
Mark Kershaw
Jenny Richards
Daniel Gann
FIU Laboratories
Pedro Lorenzo
Ruth Justiniano
Guangliang Liu
Diana Johnson
Yong Cai
ENP Science and Administration
Heather Walker
Kim Gomez
Carol Mitchell
Donatto Surratt
Joffre Castro
PJ Walker
Nick Aumen
Rick Anderson
USFWS
Marcie Kapsch, Rebekah Gibble
Miccosukee Tribe of Indians of Florida
James Erskine
EPA ORD
Tony Olsen, Tom Kincaid
Alion. Inc.
Ray Popovic, Sue Jones, Michael Keller
SESD Project ID Number: 14-0380
Page 40 of 58
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APPENDIX
Spearman Rank Order Correlations
for Variables from the 2014 Everglades REMAP Survey.
Notes:
See pages 25 - 28 for analyte, media, and laboratory codes.
Coefficients in red font are considered statistically significant. The 0.001 alpha level was
selected for this matrix due to the large size of the matrix.
Coefficients in bold font are considered to be of environmental interest, as discussed in
the text. Only coefficients with p-values less than 0.05 are bolded. Such coefficients for
variables correlated with mercury in mosquitofish are also in blue font.
Trivial, weak, spurious, and auto-correlations are not excluded.
SESD Project ID Number: 14-0380
Page 41 of 58
-------
THGFSFC
THGSWFC
MEHGSWFC
CHLAFCFB
THGFCFC
MEHGFCFC
THGSDFC
THGFSFC
1.000000
THGSWFC
0.041713
1.000000
MEHGSWFC
-0.094374
0.074471
1.000000
CHLAFCFB
-0.165615
0.145357
-0.087765
1.000000
THGFCFC
-0.107326
0.270337
0.061545
-0.005715
1.000000
MEHGFCFC
0.229732
0.134497
0.060718
0.001237
0.224166
1.000000
THGSDFC
-0.010123
0.378659
0.026337
0,307527
0.45 9078
-0.064447
1.000000
MEHGSDFC
0.082661
0.293900
0.101887
0.256155
0.109628
0.238180
0.396940
CHLAPBFB
0.511723
0.490553
0.132868
0.587879
0.205072
-0.022051
0,686245
THGPBFC
-0.003414
0.253065
-0.120247
0.516248
0.425430
0.426580
0.464187
MEHGPBFC
0.369927
0.074374
0.139466
0.532843
0.433551
0.498583
0.394571
CHLAPCFB
-0.010445
0.226637
-0.202569
0.370292
0.348022
0.131771
0.382174
THGPCFC
-0.019245
0.276116
-0.067924
0.311200
0.279618
0.068040
0.562154
MEHGPCFC
0.051430
0.303498
0.145187
0.118923
0.295002
0.297496
0.422 728
FLOCTHAV
-0.083398
0.128502
0.152138
0.262420
0.154784
-0.138875
0.418647
PBTHAV
0.019998
-0.334473
-0.130005
-0.374662
-0.350745
-0.111005
-0.442481
PERICOV
-0.006747
-0.396927
-0.053525
-0.317562
-0.369594
-0.253686
-0.342 448
PERIVOL
-0.043444
-0.272054
0.018537
-0.313093
-0.407955
-0.263319
-0.205080
THGSGAFC
-0.022740
-0.286348
0.009337
0.314212
0.190827
-0,180842
-0.288297
THGSGBFC
0.162074
0.115884
-0.067963
0.064083
-0.137677
-0.263500
0.151195
MEHGSGAFC
0.153757
0.543924
-0.182656
0.127913
0.155417
0.196434
0.507373
MEHGSGBFC
0.370763
0.444071
0.046206
-0.242769
0.018115
0.284746
0.425204
CLSWEA
0.178469
-0.121928
0.188235
-0.379002
-0.068728
-0,198216
-0.034571
S04SWEA
0.148702
0.215014
0.219239
-0.102713
-0.008699
-0.104241
0.151068
DOCSWEA
0.193870
0.200300
0.288334
-0.250095
0.049533
-0.088122
0.272726
TOCSWEA
0.206557
0.266243
0.232499
-0.294212
0.107986
-0.097404
0.302415
TPSWFB
-0.136217
0.351162
0.080901
0.048048
0.154938
0.095580
0.132469
SRPSWFB
0.256595
0.040139
-0.198869
-0.352355
-0,018841
-0.102786
-0.055541
FNNSWFB
0.027409
-0.156 459
0.078562
-0.080176
-0.089353
0.168376
-0.264798
FN 03SWFB
-0.122036
-0.277285
0.091500
0.042867
-0.022398
0.078204
-0.205562
FN02SWFB
0.253729
0.332941
0.071316
0.128742
0.158522
0.099254
0.298335
FNH4SWFB
-0.102822
-0.159385
0.147185
-0.182366
-0.072014
-0.090190
-0.057770
TNSWFB
0.025410
0.057759
0.299712
-0.291986
0.054959
-0.168852
0.217382
CHLASWFB
-0.221231
0.373906
0.234278
0.237027
0.248767
0.217081
0.166232
H2SBWEE
-0.079946
0.193672
0.103859
0.380109
-0.035093
-0.162967
0.200953
pH FCFS
0.177456
-0.283662
-0.227226
-0.196038
-0.475315
-0.182779
-0.212526
H20FCFS
-0.141399
0.181379
-0.142027
0.730689
0.089659
0.089383
0.357008
ASHFCFS
0.151988
-0.330354
0.042582
-0,526418
-0.446476
-0.307647
-0.437231
BDFCFS
0.089489
-0.167745
0.161633
-0.725594
-0.128681
-0.111689
-0.375 077
TCFCFS
-0.1 49595
0.435258
-0.089933
0.469094
0.476217
0.227144
0.458468
TNFCFS
-0.247438
0.203174
-0.062983
0.571020
0.396458
0.218351
0.368508
TPFCFB
-0.341989
0.314090
0.123086
0,230704
0.595347
0.202736
0.214324
pHSDFS
-0.042343
-0.335882
-0.117885
-0.279575
-0.406911
-0.227682
-0.447332
SESD Project ID Number:
14-0380
Page 42 of 5 8
-------
THGFSFC
THGSWFC
MEHGSWFC
CHLAFCFB
THGFCFC
MEHGFCFC
THGSDFC
H20SDFS
0.014433
0.471112
0.033202
0.474336
0.315589
-0.014129
0.635782
ASHSDFS
0.020221
-0.450275
-0.053274
-0.403098
-0.408176
-0.044840
-0.688112
OMSDFS
-0.020221
0.450275
0.053274
0.403098
0.408176
0.044840
0.688112
BDSDFS
-0.042878
-0.478874
-0.048055
-0.471291
-0.267021
-0.074784
-0.607304
TCSDFS
0.062011
0.462201
-0.009108
0.371554
0.399661
0.049568
0.642196
TNSDFS
-0.041339
0.353619
-0,057205
0.548970
0.258784
-0.024987
0.747952
TPSDFB
0.009298
0.297436
0.089828
0.182493
0.203832
0.233547
0.463799
TCVGFS
0.165154
0.359845
-0.294705
0.045269
0.209730
0.256467
0.149938
TNVGFS
-0.029872
-0.109480
0.247750
0.141036
-0.299606
-0.127638
0.003740
TPVGFB
0.1 97419
0.079165
0.064801
0.171283
-0.047952
0.213864
0.058637
pHPBFS
-0.337840
-0.025286
0.080787
-0.656538
-0.316079
-0 473568
-0.062582
H20PBFS
0.434702
0.490301
0.006054
0.871 967
0.153253
0.082690
0.604532
ASHPBFS
-0.548785
-0.429711
-0.124337
-0.869305
-0.484581
-0.425110
-0.809370
BDF'BFS
-0.342990
-0.364402
-0.077507
-0.887542
-0.203744
-0.031 938
-0.629282
TCPBFS
0.465837
0.280639
0.092041
0.818558
0.698016
0.500005
0.713684
TNPBFS
0.433271
0.326988
0.028840
0.717329
0.614113
0.549063
0.706174
TPPBFB
0.283856
0.211665
-0.015047
0.437692
0.485683
0.568282
0.453958
pHPCFS
-0.007616
-0.019351
0.024992
-0.264942
-0.297360
-0.186240
-0.289646
H20PCFS
-0.1 330S2
0.199333
-0.090008
0.351528
0.266179
0.076540
0.455093
ASHPCFS
-0.046863
-0.223907
0.044733
-0.320823
-0.531996
-0.306139
-0.546380
BDPCFS
0.066886
-0.136631
0.109371
-0.415346
-0.265064
-0.021326
-0.419531
TCPCFS
0.090621
0.249255
-0.004858
0.240991
0.477409
0.285093
0.511876
TNPCFS
-0.035442
0.202306
-0.030206
0.332589
0.374895
0.138459
0.493994
TPPCFB
-0.006989
0.241946
-0.007742
0.458115
0.320490
0.164258
0.483639
TEMP
0.043794
-0.156172
-0.086707
-0.233305
-0.155615
-0.179582
-0.040273
COND
0.183100
-0.195744
0.175707
-0.382399
-0.079180
-0.241780
-0.048757
pH
0.1 36896
-0.331 085
-0.105307
-0.440672
-0.306765
-0.242497
-0.281052
TURB
0.012739
0.057798
0.140517
0.190748
0.013294
0.136865
0.006645
DO
0.1 03216
-0.189288
-0.139290
-0.244250
-0.222888
-0.163821
-0.204261
ORP
0.051559
-0.018847
0.085508
-0.092907
0.164270
0.078941
-0.046671
WAT DE PAY
0.094644
0.239223
0.017190
0.341647
0.112882
-0.304280
0.499603
SOILTHAV
0.042802
0.341920
0.154205
0.282252
0.315822
-0.178218
0.552 458
SESD Project ID Number: 14-0380
Page 43 of 58
-------
THGFSFC
THGSWFC
MEHGSWFC
CHLAFCFB
THGFCFC
MEHGFCFC
THGSDFC
MEHGSDFC
CHLAPBFB
THGPBFC
MEHGPBFC
CHLAFCFB
THGFCFC
MEHGPCFC
FLOCTHAV
PBTHAV
PERICOV
PERIVOL
THGSGAFC
THGSGBFC
MEHGSGAFC
MEHGSGBFC
CLSWEA
S04SWEA
DOCSWEA
TOCSWEA
TPSWFB
SFtPSWFB
FNNSWFB
FN03SWFB
FN02SWFB
FNH4SWFB
TNSWFB
CHLASWFB
H2SBWEE
pHFCFS
H20FCFS
ASHFCFS
BDFCFS
TCFCFS
TNFCFS
TPFCFB
pHSDFS
MEHGSDFC CHLAPBFB THGPBFC MEHGPBFC CHLAPCFB THGPCFC MEHGPCFC
1.000000
0.418948
1.000000
0.505175
0.147644
1.000000
0.384459
0.349077
0.365605
1.000000
0.292778
0.410193
0.432405
0.204864
1.000000
0.413128
0.762129
0.326269
0.316273
0.658104
1.000000
0.452486
0.653970
0.293857
0.581130
0.447089
0.660195
1.000000
0.191323
0.475168
0.246506
0.254600
0.371204
0.442940
0.374126
¦0.402206
-0.261133
-0.486098
-0.262506
-0.563857
-0.551329
-0.476321
0.464962
-0.323469
-0.481869
-0.056869
-0.512937
-0.547975
-0.425825
0.392266
0.003574
-0.427908
-0.091168
-0.518769
-0.438571
-0.311029
¦0.086365
-0.360375
0.100844
-0.050422
0.156854
-0.269248
-0.236819
0.067411
0.563730
0.378165
0.285724
0.218366
0.017158
-0.286907
0.239731
0.860753
0.570342
0.859769
0.239724
0.537654
0.392315
0.280672
0.486506
0.368204
0.343099
-0.027668
-0.014512
-0.047870
¦0.120668
0.090099
-0.273385
0.164021
-0.289518
-0.180577
0.044382
0.047224
0.284076
0.028072
0.148546
-0.080182
0.061609
0.252057
0.147003
0.609780
0.054324
0.296356
0.114117
0.205694
0.382681
0.148053
0.604832
0.081092
0.287866
0.157724
0.229992
0.405779
0.293010
-0.104009
0.143343
-0.153668
0.085951
0.232955
0.368627
0.053478
0.302522
-0.016494
0.084201
0.104344
0.065113
0.074785
¦0.157348
-0.450690
-0.234061
-0.133377
-0.381268
-0.370654
-0.136384
¦0.150181
-0.534016
-0.257104
-0.173077
-0.334654
-0.261718
-0.145993
0.143855
0.319496
0.147462
0.329076
0.204879
0.246939
0.399352
¦0.198148
0.295189
-0.294437
-0.077515
0.022480
0.014785
0.071660
-0.017540
0.467491
0.049686
0.269362
0.061236
0.157253
0.326066
0.308244
0.274602
0.213691
-0.033547
0.169847
0.237032
0.391319
0.129651
0.249521
0.264629
0.105393
0.440618
0.385549
0.247708
¦0.340201
-0.121581
-0.230770
-0.648183
-0.351632
-0.475640
-0.339646
0.438294
0.603670
0.498474
0.590224
0.335006
0.363164
0.293618
-0.415482
-0.407297
-0.618405
-0.590910
-0.520769
-0.611779
-0.428027
¦0.428676
-0.565352
-0.525972
-0.568699
-0.336577
-0.362354
-0.249737
0.340245
0.463423
0.607628
0.499385
0 52108(1
0.591719
0.408604
0.298145
0.309091
0.579239
0.557196
0.517376
0.616257
0.385781
0.345702
0.322190
0.481573
0.327798
0.347777
0.358285
0.297638
¦0.458286
-0.351428
-0.358631
-0.578538
-0.447009
-0.484998
-0.444018
SESD Project ID Number: 14-0380
Page 44 of 58
-------
MEHGSDFC
CHLAPBFB
THGPBFC
MEHGPBFC
CHLAPCFB
THGPCFC
MEHGPCFC
H20SDFS
0.523396
0.823417
0.407573
0.500081
0.492836
0.596804
0.454516
ASHSDFS
-0.470200
-0.771631
-0.487327
-0.431643
-0.582023
-0.635736
-0.515352
OMSDFS
0.470200
0.771631
0.487327
0.431643
0.582023
0.635736
0.515352
BDSDFS
-0.549173
-0.830962
-0.451122
-0.483153
-0.411446
-0.576778
-0.489088
TCSDFS
0.422879
0.773089
0.394454
0.423121
0.535817
0.585575
0.479879
TNSDFS
0.422759
0.689022
0.508037
0.422463
0.576269
0.663730
0.461749
TPSDFB
0.470656
0,575844
0 472335
0.324839
0.285106
0.427181
0453838
TCVGFS
0.107692
-0.149244
0.502569
0.278903
0.095026
0.200816
0.001941
TNVGFS
-0.166377
-0.177901
-0.130326
0.152691
-0.363710
-0.161743
-0.060926
TPVG FB
0.205420
0.262122
0.060606
0.121292
-0.047205
0.151328
0.065168
pHPBFS
-0.306294
-0.103027
-0.429898
-0.513778
-0.054689
-0.168111
-0.257298
H20PBFS
0.351048
0.782307
0.207849
0.419137
0.507202
0.744414
0.755526
ASHPBFS
-0.450081
-0.648128
-0.597738
-0.449616
-0.535051
-0.693928
-0.731798
BDPBFS
-0.311659
-0.764243
-0.240174
-0.276448
-0.456485
-0.712975
-0.703521
TCPBFS
0.442316
0.600351
0.674041
0.488598
0.519596
0.61 9682
0.762618
TNPBFS
0.511073
0.502425
0.785390
0.554512
0.579534
0.584036
0.741888
TPPBFB
0.3761 12
0.157464
0.899536
0.42821 1
0.571287
0.281327
0.416481
pHPCFS
-0.526725
-0.174753
-0.306061
-0.504901
-0.351189
-0.458453
-0.355667
H20PCFS
0.357815
0.6061 87
0.321174
0.327274
0.774197
0.719691
0.497539
ASHPCFS
-0.572671
-0.637645
-0.543143
-0.457097
-0.709171
-0.782078
-0.595029
BDPCFS
-0.280691
-0.672474
-0.374713
-0.321004
-0.776947
-0.713473
-0.444158
TCPCFS
0.555017
0.756670
0.498742
0.529369
0.670051
0.769633
0.606068
TNPCFS
0.550064
0.672086
0.352229
0.627420
0.731801
0.833893
0.607638
TPPCFB
0.547150
0.696979
0.369989
0.460303
0.742446
0.823677
0.607683
TEMP
-0.284521
0.078344
0.073766
0.256855
-0.348027
-0.252435
-0.088822
COND
-0.131112
-0.054653
-0.396471
0.012992
-0.306047
-0.218240
0.005409
pH
-0.428671
-0.052432
-0.241654
-0.065100
-0.489655
-0.502940
-0.283485
TURB
0.064874
-0.206545
-0.188595
-0.036583
0.004863
0.101945
0.127149
DO
-0.299096
-0.176274
-0.096367
0.077500
-0.467435
-0.443023
-0.249199
ORP
-0.094096
-0 089473
-0 233085
-0.216381
-0.407664
-0 25 4255
-0.104990
WAT D E PAV
0.170507
0.798849
0.298137
0.364969
0.434205
0.464700
0.231317
SOILTHAV
0.308485
0.779403
0.182360
0.402765
0.357749
0.381105
0.347584
SESD Project ID Number: 14-0380
Page 45 of 58
-------
FLOCTHAV PBTHAV PERICOV PERIVOL THGSGAFC THGSGBFC MEHGSGAFC
THGFSFC
THGSWFC
MEHGSWFC
CHLAFCFB
THGFCFC
MEHGFCFC
THGSDFC
MEHGSDFC
CHLAPBFB
THGPBFC
MEHGPBFC
CHLAPCFB
THGPCFC
MEHGPCFC
FLOCTHAV 1.000000
PBTHAV
-0.515382
1.000000
PERICOV
-0.185943
0.582822
1.000000
PERIVOL
0.031007
0.35831 8
0.7981 04
1.000000
THGSGAFC
0.162214
0.097939
0.1 10688
0.095014
1.000000
THGSGBFC
-0.114901
-0.242298
-0.3051 66
-0.188617
0.005046
1.000000
MEHGSGAFC
0.310229
-0.1 48409
-0.335308
-0.304854
0.066084
0.140755
1.000000
MEHGSGBFC
-0.295874
-0.069872
-0.313988
-0,233039
-0.214122
0.277396
0.239541
CLSWEA
-0.155914
0.045488
0.248175
0.298342
-0.335474
-0.264067
-0.227232
S04SWEA
-0.14483G
-0.166158
-0.0621 60
0.003830
-0.478807
-0.109986
0.028189
DOCSWEA
0.151974
-0.300936
-0.009374
0.114326
-0.248125
-0.107761
0.043438
TOCSWEA
0.127526
-0.302975
-0.048475
0.077650
-0.216113
-0.059427
0.119183
TPSWFB
-0.036918
-0.395269
-0.408532
-0.328596
-0.306669
-0.210921
0.1 18099
SRPSWFB
-0.203693
0.071836
0.064227
0.039141
-0.465396
0.047355
-0.105561
FNNSWFB
-0.532789
0.423200
0.273122
0.150780
-0.208748
-0.073559
0.003680
FN 03 SWFB
-0.381737
0.329483
0.212972
0.073376
-0.132486
-0.110584
-0.1 16726
FN02SWFB
0.015966
-0.304586
-0.212459
-0.202715
-0.274270
0.021074
0.455193
FNH4SWFB
-0.020007
0.075500
0.272 476
0.290504
-0.172303
-0.246366
-0.130121
TNSWFB
0.125977
-0.1 46799
0.129721
0.253543
-0.074006
-0.066514
0.042012
CHLASWFB
0.447489
-0.490790
-0.505183
-0.406013
0.024771
-0.240673
0.314322
H2SBWEE
0.396102
-0.520284
-0.179582
-0.063768
-0.084362
0.149018
0.163941
pH FCFS
-0.489400
0.530863
0.472839
0.457563
-0.444215
-0.027893
-0.342652
H20FCFS
0.344140
-0 5114556
-0.461512
-0.421631
0.309884
-0.096280
0.107551
ASHFCFS
-0.362086
0.466418
0.701322
0.687266
-0.356477
-0.087565
-0.512461
BDFCFS
-0.362055
0.501416
0.473599
0.445116
-0.337737
0.091252
-0.132432
TCFCFS
0.308271
-0 480680
-0.759380
-0.714317
0.269291
0.054894
0.480540
TNFCFS
0.399693
-0.521560
-0.457627
-0.435574
0.169783
-0.096574
0.354319
TPFCFB
0.084158
-0.459599
-0.671245
-0.687978
0.064666
-0.281428
-0.1 17678
pHSDFS
-0.461981
0.496460
0.495673
0 410538
0.018032
-0.305776
-0.359027
SESD Project ID Number: 14-0380
Page 46 of 58
-------
FLOCTHAV
PBTHAV
PERICOV
PERIVOL
THGSGAFC
THGSGBFC
MEHGSGAFC
H20SDFS
0.42 044G
-0.571476
-0.567978
-0.400928
0.076805
0.305535
0.462414
ASHSDFS
-0.483600
0.548181
0.577312
0.415892
-0.064526
-0.269725
-0.563940
OMSDFS
0.483600
-0.548181
-0.577312
-0.415892
0.064526
0.269725
0.563940
BDSDFS
-0.387971
0.539055
0.587011
0.411023
-0.041597
-0.197085
-0.489765
TCSDFS
0.496138
-0.520879
-0.520706
-0.352508
0.040557
0.278849
0.55 7245
TNSDFS
0.431097
-0.505374
-0.363929
-0.243549
0.102525
0.159296
0.620225
TPSDFB
0.050316
-0.400848
-O.S34491
-0.426328
-0.324924
-0.018502
0.293623
TCVGFS
-0.016491
-0.245877
-0.303236
-0.226302
-0.105812
0.249958
0.344999
TNVGFS
0.254036
0.153129
0.207682
0.243558
0.093559
-0.166565
-0.048139
TPVGFB
0.195554
-0.331468
-0.379884
-0.295498
-0.149272
0.057495
0.107754
pHPBFS
-0.223799
0.1 18675
0.146467
0.202301
0.181818
0.064223
-0.396509
H20PBFS
0.637823
-0.117195
-0.136889
0.130058
-0.055048
0.185185
0.971825
ASHPBFS
-0.540881
0.616993
0.520054
0.340676
0.576600
-0.254588
-0.804617
BDPBFS
-0.668361
0.253968
0.155753
-0.045387
0.155970
-0.194444
-0.743161
TCPBFS
0.460444
-0.577665
-0.4458 46
-0.339428
-0.162169
0.363696
0.767193
TNPBFS
0.396154
-0.642503
-0.456667
-0.352468
0.234244
0.418251
0.804617
TPPBFB
0.25 0754
-0.588705
-0.406123
-0.409526
0.252262
0.436436
0.580073
pHPCFS
-0.281985
0.368590
0.368835
0.405391
0.120053
0.093228
-0.407269
H20PCFS
0.476015
-0.531669
-0.485404
-0.464310
-0.114041
0.022274
0.422430
ASHPCFS
-0.351310
0.580328
0.647196
0.613289
0.059341
0.058022
-0.420807
BDPCFS
-0.468425
0.561723
0.490949
0.456812
0.186453
-0.186010
-0.311190
TCPCFS
0.338603
-0.548431
-0.658633
-0.611769
-0.111454
-0.079295
0.455438
TNPCFS
0.391612
-0.538652
-0.539434
-0.543293
-0.057658
-0.003961
0.671256
TPPCFB
0.486697
-0.652254
-0.577003
-0.525128
-0.035683
-0.029956
0.489585
TEMP
-0.097431
0.304700
0.330520
0.281 733
-0.047052
-0.005805
0.1 14890
COND
-0.160422
0.052034
0.240919
0.269956
-0.363789
-0.357983
-0.333386
pH
-0.426107
0.545497
0.620370
0.529261
-0.138121
0.053018
-0.300753
TURB
0.322350
-0.237820
-0.196749
-0.137140
0.106119
-0.102132
0.179763
DO
-0.321678
0.475671
0.438542
0.332519
0.061717
0.192179
0.09681 4
ORP
-0.226254
0.341848
0.015846
-0.097766
0.092270
-0.048274
-0.075675
WAT D E PAV
0.459586
-0.460700
-0.270058
-0.069757
-0.095951
0.273644
0.305809
SOILTHAV
0.570239
-0.498927
-0.448392
-0.280361
0.190374
0.088465
0.400340
SESD Project ID Number: 14-0380
Page 47 of 58
-------
MEHGSGBFC CLSWEA S04SWEA DOCSWEA TOCSWEA TPSWFB SRPSWFB
THGFSFC
THGSWFC
MEHGSWFC
CHLAFCFEI
THGFCFC
MEHGFCFC
THGSDFC
MEHGSDFC
CHLAPBFB
THGPBFC
MEHGPBFC
CHLAPCFB
THGPCFC
MEHGPCFC
FLOCTHAV
PBTHAV
PERICOV
PERIVOL
THGSGAFC
THGSGBFC
MEHGSGAFC
MEHGSGBFC
1,000000
CLSWEA
0.034235
1.000000
S04SWEA
0.233382
0.734885
1.000000
DOCSWEA
0.21251G
0.709599
0.655359
1 .000000
TOCSWEA
0.266841
0.698024
0.661165
0.973921
1.000000
TPSWFB
0.424094
0.153527
0.427089
0.268571
0.296468
1.000000
SRPSWFB
0.338213
0.183353
0.120794
0.180906
0.174090
-0.032600
1.000000
FNNSWFB
0.033629
0.290095
0.204865
0.018517
0.009487
-0.053015
0.042480
FN 03 SWFB
-0.090478
0.138566
0.055196
-0.044015
-0.046766
-0.048101
-0.09 4245
FN02SWFB
0.424671
0.277427
0.450595
0.561035
0.571748
0.363291
0.106460
FNH4SWFB
-0.382380
0.276083
0.043353
0.258517
0.232145
-0.068699
0.059307
TNSWFB
-0.036375
0.673231
0.508831
0.847124
0.830665
0.144698
0.013349
CHLASWFB
0.098273
-0.202304
-0.051066
0.0561 77
0.058788
0.386195
-0.125936
H2SBWEE
-0.2 33427
0.220126
0.361904
0.377697
0.377112
0.212118
-0.000806
pHFCFS
-0.0 0722 8
0.411912
0.345115
0.142361
0.141896
-0.1 10331
0.017935
H20FCFS
-0.069412
-0.384232
-0.172907
-0.199296
-0.244803
0.108512
-0.236876
ASHFCFS
-0.09321 6
0.651776
0.413481
0.354968
0.362083
0.024494
0.153749
BDFCFS
0.011532
0.430208
0.226896
0.254082
0.301325
-0.058325
0.196488
TCFCFS
0.02381 0
-0.565015
-0.248247
-0.2791 99
-0.26 7295
0.094572
-0.096318
TNFCFS
-0.1 33369
-0.472908
-0.315058
-0.256284
-0.296713
0.048602
-0.148389
TPFCFB
-0.388315
-0.255590
0.003741
-0.127881
-0.133195
0.283681
-0.078930
pHSDFS
-0.225600
0.298418
0.182831
-0.108944
-0.100231
-0.128016
-0.135228
SESD Project ID Number: 14-0380
Page 48 of 58
-------
MEHGSGBFC
CLSWEA
S04SWEA
DOCSWEA
TOCSWEA
TPSWFB
SRPSWFB
H20SDFS
0.401320
-0.173538
0.050153
0.248156
0.25 8455
0.206712
0.073388
ASHSDFS
-0.372459
0.271620
0.033237
-0.189277
-0.202379
-0.18531 9
-0.029620
OMSDFS
0.372459
-0.271620
-0.033237
0.189277
0.202379
0.18531 9
0.029620
BDSDFS
-0.4398G3
0.161176
-0.082130
-0.237762
-0.245933
-0.253057
-0.040433
TCSDFS
0.354444
-0.238265
0.01454 6
0.183567
0.194961
0.135307
0.146004
TNSDFS
0.3014G 9
-0.203998
0.052934
0.202498
0.204056
0.200087
-0.022523
TPSDFB
0.G 30750
0.061553
0.382347
0.276824
0.285492
0.491425
-0.035542
TCVGFS
0.138855
-0.073062
0.1 14932
0.1752 48
0.187617
0.246488
0.133484
TNVGFS
-0.151158
-0.075610
-0.1 83096
-0.145527
-0.133775
-0.261060
-0.403952
TPVGFB
0.165184
-0.151538
0.1 88293
-0.058349
-0.085575
0.22753 7
0.041563
pHPBFS
0.045455
-0.0601 47
-0.154360
0.004912
0.049291
0.07751 4
-0.208750
H20PBFS
0.105145
0.020878
0.220027
0.503637
0.508515
-0.370954
0.210156
ASHPBFS
-0.30631 9
-0.004123
-0.246574
-0.542552
-0.569275
-0.093593
-0.195354
BDPBFS
0.082572
0.000669
-0.29371 1
-0.517828
-0.517683
0.132806
-0.113140
TCPBFS
0.054056
-0.018693
0.222386
0.448509
0.467483
0.1 18636
0.133423
TNPBFS
0.108112
-0.079625
0.205732
0.387840
0.408238
0.097012
0.160043
TPPBFB
0.486506
-0.040562
0.1 30474
0.131785
0.150174
0.109972
0.067099
pHPCFS
0.036923
0.177740
0.059526
-0.054348
-0.063095
-0.174694
-0.298691
H20PCFS
-0.244902
-0.234994
-0.1 03462
0.114962
0.1 12631
0.061118
0.097813
ASHPCFS
-0,158172
0.241434
-0.014030
-0,183271
-0.205728
-0.22531 1
-0.224407
BDPCFS
0.375398
0.229765
0.090234
-0.108754
-0.091902
-0.037157
-0.055988
TCPCFS
0.180538
-0.198353
0.059364
0.229639
0.253985
0.273759
0.264988
TNPCFS
0.0321 16
-0.255078
-0.051745
0.164847
0.187033
0.220972
0.176942
TPPCFB
-0.082783
-0.2301 68
-0.002208
0.200853
0.216968
0.313484
0.109368
TEMP
-0.007940
0.125801
0.016941
-0.067292
-0.071369
-0.18371 4
-0.186210
COND
0.015119
0.952331
0.710199
0.649657
0.638016
0.13701 7
0.215158
pH
-0.035431
0.413014
0.169180
0.047080
0.038899
-0.295119
0.109192
TURB
-0.233141
-0.254002
-0.312860
-0.149954
-0.184283
-0.034031
-0.13681 1
DO
0.092228
0.074931
-0.095479
-0.184079
-0.170920
-0.291702
-0.038744
ORP
0.395175
-0.185536
-0.263761
-0.213477
-0.198858
-0.093031
-0.11 3977
WATDEPAV
0.001222
0.128200
0.319265
0.347434
0.352823
0.047179
0.058532
SOILTHAV
0.131185
-0.091460
0.021880
0.242556
0.260599
0.092642
0.019511
SESD Project ID Number: 14-0380
Page 49 of 58
-------
FN NSW FB
FN 03 SW FB
FN02SWFB
FNH4SWFB
TNSWFB
CHLASWFB
H2SBWEE
THGFSFC
THGSWFC
MEHGSWFC
CHLAFCFB
THGFCFC
MEHGFCFC
THGSDFC
MEHGSDFC
CHLAPBFB
THGPBFC
MEHGPBFC
CHLAPCFB
THGPCFC
MEHGPCFC
FLOCTHAV
PBTHAV
PERICOV
PERIVOL
THGSGAFC
THGSGBFC
MEHGSGAFC
MEHGSGBFC
CLSWEA
S04SWEA
DOCSWEA
TOCSWEA
TPSWFB
SRPSWFB
FN N SW FB
1.000000
FN 03 SWFB
0.035070
1.000000
FN02SWFB
0.218738
0.022410
1.000000
FNH4SWFB
0.3471 35
0.170415
0.145020
1.000000
TNSWFB
0.128351
0.075722
0.438120
0.398744
1.000000
CHLASWFB
-0.2491 89
-0.208590
0.120445
0.008500
-0.028932
1.000000
H2SBWEE
-0.210327
-0.1 00022
0.229739
0.020324
0.250204
0.107801
pH FCFS
0.127242
-0.025021
-0.157515
0.005229
0.088099
-0.491994
H20FCFS
-0.184299
-0.043103
0.180122
-0.179313
-0.283923
0.332840
ASHFCFS
0.179215
0.038995
-0.184709
0.372752
0.427242
-0.404555
BDFCFS
0.213932
0.070140
-0.137992
0.255177
0.342399
-0.345797
TCFCFS
-0.088024
-0.010850
0.310272
-0.372154
-0.308881
0.304523
TNFCFS
-0.194381
0.010727
0.148133
-0.184093
-0.238184
0.288140
TPFCFB
-0.004020
-0.043102
0.109301
-0.177103
-0.285041
0.415520
pHSDFS
0.300094
0.153840
-0.294353
0.210311
-0.015071
-0.409882
1.000000
-0.078928
0.31G736
-0.0G1389
-0.316019
0.059071
0.204001
0.1 49470
-0.149540
SESD Project ID Number: 14-0380
Page 50 of 58
-------
FN NSW FB
FN 03 SW FB
FN02SWFB
FNH4SWFB
TNSWFB
CHLASWFB
H2SBWEE
H20SDFS
-0.320802
-0.287758
0.422162
-0.187421
0.072191
0.331620
0.338852
ASHSDFS
0.317283
0.1 91972
-0.410084
0.163782
-0.049989
-0.356440
-0.259946
OMSDFS
-0.317283
-0.191972
0.410084
-0.163782
0.049989
0.356440
0.259946
BDSDFS
0.310510
0.303792
-0.423497
0.213070
-0.041885
-0.305583
-0.291809
TCSDFS
-0.3401 87
-0.242179
0.405177
-0.200375
0.023659
0.328895
0.255242
TNSDFS
-0.352035
-0.171008
0.349448
-0.117175
0.122765
0.170540
0.272071
TPSDFB
-0.105723
-0.082807
0.354317
-0.204179
0.067051
0.234759
0.114472
TCVGFS
-0.198828
-0.028780
0.212104
-0.175158
0.031685
0.071200
0.1 0881 9
TNVGFS
-0.019171
0.147948
-n 051288
-0.021201
0.055759
0.057520
-0.173054
TPVGFB
-0.139913
-0.151195
0.104543
-0.253003
-ij 296262
0.195079
-0.053795
pHPBFS
0.010798
0.038530
-0.404957
0.232806
-0.060350
-0.151800
0.058239
H20PBFS
-0.454304
-0.500978
0.258978
0.083156
0.406251
0.000473
0.252542
ASHPBFS
0.423544
0.479012
-0.397388
-0.109585
-0.423861
-0.330732
-0.202824
BDPBFS
0.540144
0.592151
-0.288189
-0.094578
-0.432219
-0.278704
-0.214341
TCPBFS
-0.355801
-0.400503
0.385488
0.097621
0.387943
0.215840
0.240871
TNPBFS
-0.384084
-0.430372
0.308303
0.023477
0.355519
0.228540
0.201540
TPPBFB
-0.235438
-0.202144
0 232694
-0.191354
0.163306
0.183705
0.191023
pHPCFS
0.123383
0.1 10080
-0.219451
0.118705
0.045061
-0.188702
0.027351
H20PCFS
-0.398355
-0.317984
0.057991
0.144262
ij 127863
0.355442
0.448458
ASHPCFS
0.373437
0.282899
-0.266901
0.152765
-0.088826
-0.251450
-0.287374
BDPCFS
0.379598
0.331157
-0.080464
-0.169331
-0.111540
-0.309040
-0.404728
TCPCFS
-0.331300
-0.201717
0.346283
-0.144486
0.089754
0.250469
0.212237
TNPCFS
-0.339218
-0.270551
0.273509
-0.003574
0.115005
0.234033
0.207502
TPPCFB
-0.405200
-0.353218
n 277886
-0.056489
0.090444
0.344073
0.308045
TEMP
0.041002
0.075732
-0.106753
-0.063195
0.128688
-0.223228
-0 226635
COND
0.291734
0.1 30804
0.228431
0.299875
0.572381
-0.213870
0.203433
pH
0.340591
0.210029
-0.189683
0.185561
0.175619
-0.509709
-0.249575
TURB
-0.170790
-0.107027
-0.078528
0.087666
-0.165282
0.302830
0.090796
DO
0.190810
0.195328
-0.225292
-0.123097
-0.023985
-0.299827
-0.293259
ORP
0.137380
0.074057
-0.054752
-0.222368
-0.153109
0.025905
-0.604955
WAT D E PAV
-0.280050
-0.203038
0.319941
-0.058935
0.244805
0.0801 65
0.546028
SOILTHAV
-0.337200
-11204626
0.404872
-0 150228
0.158986
0.337643
0.255233
SESD Project ID Number:
14-0380
Page 51 of 58
-------
pHFCFS H20FCFS ASHFCFS BDFCFS TCFCFS TNFCFS TPFCFB pHSDFS
THGFSFC
THGSWFC
MEHGSWFC
CHLAFCFB
THGFCFC
MEHGFCFC
THGSDFC
MEHGSDFC
CHLAPBFB
THGPBFC
MEHGPBFC
CHLAPCFB
THGPCFC
MEHGPCFC
FLOCTHAV
PBTHAV
PERICOV
PERIVOL
THGSGAFC
THGSGBFC
MEHGSGAFC
MEHGSGBFC
CLSWEA
S04SWEA
DOCSWEA
TOCSWEA
TPSWFB
SRPSWFB
FNNSWFB
FN 03SWFB
FN02SWFB
FNH4SWFB
TNSWFB
CHLASWFB
H2SBWEE
pHFCFS 1.000000
H20FCFS -0.365866
ASHFCFS 0.650601
BDFCFS 0.383122
TCFCFS -0.608455
TNFCFS -0.601228
TPFCFB -0.382090
pHSDFS 0.788060
1.000000
-0.699341
-0.970228
0.585557
0.730606
0.405296
-0.520774
1.000000
0.717492
-0.913081
-0.79 6 422
-0.553320
0.337214
1.000000
-0.593050
-0.75 4037
-0.391976
0.546570
1.000000
0.723464
0.588696
-0.780867
1 .000000
0.445 6 68
-0.647955
1.000000
-0.478916
1.000000
SESD Project ID Number: 14-0380
Page 52 of 58
-------
pHFCFS
H20FCFS
ASHFCFS
BDFCFS
TCFCFS
TNFCFS
TPFCFB
pHSDFS
H20SDFS
-0.514078
0.607376
-0.770291
-0.618715
0.761748
0.484587
0.461427
-0.662914
ASHSDFS
0.542881
-0.583931
0.808869
0.574256
-0.793690
-0.552471
-0.407438
0.734561
OMSDFS
-0 542881
0.583931
-0 808869
-0 574256
0 793690
0.552471
0 407438
-0 734561
BDSDFS
0.481928
-0.579421
0.741959
0.585465
-0.75 72 1 7
-0.461786
-0.427927
0.634742
TCSDFS
-0.544178
0.477036
-0.787476
-0.519331
0 799862
0.525473
0.361250
-0.731512
TNSDFS
-0.448969
0.604728
-0.646098
-0.625273
0 590291
0.650802
0.132337
-0.568044
TPSDFB
0.038690
0.308436
-0.342 440
-0.266667
0 383389
0.155161
0.553022
-0.286167
TCVGFS
-0.207977
0.077464
-0.203 729
-0.129824
0.248259
0.269240
0.148331
-0.287624
TNVGFS
-0.168636
0.198959
-0.017741
-0.146315
-0.016558
0.1045 79
-0.210446
0.070954
TPVGFB
-0.275936
0.179716
-0.206982
-0.194317
0.254774
0.072073
0.178801
-0.149376
pHPBFS
0.7 3 4756
-0.639147
0.789634
0.670732
-0.715600
-0.844989
-0.640244
0.766980
H20PBFS
-0 645263
0 877301
-0 703367
-0.856273
0 736196
0.640256
0 385323
-0.41 6019
ASHPBFS
0.823171
-0.856273
0.835366
0.865854
-0.819576
-0.826752
-0.567073
0.403190
BDPBFS
0.503049
-0.886854
0.689024
0.868902
-0.776762
-0.601826
-0.42 9 8 78
0.366502
TCPBFS
-0.487691
0.798796
-0.978470
-0.814877
0.931929
0.972423
0.858090
-0.37 9 426
TNPBFS
-0.487805
0.706425
-0.893293
-0.731707
0 807343
0.930095
0.713415
-0.361350
TPPBFB
-0.45 42 6 8
0.418962
-0.625000
-0.457317
0.495415
0.699091
0.445122
-0.407329
pHPCFS
0.787875
-0.354873
0.609161
0.375380
-0.618476
-0.559427
-0.455 302
0.75 7253
H20PCFS
-0.546616
0.373487
-0.594610
-0.349317
0.490180
0.582359
0.374879
-0.510144
ASHPCFS
0.644620
-0.488294
0.865779
0.523404
-0.767489
-0.785949
-0.663743
0.675519
BDPCFS
0 475117
-0.372862
0540005
0 371591
-0 447686
-0 573075
-0 396272
0443480
TCPCFS
-0.624780
0.397239
-0.806370
-0.430762
0.731305
0.715201
0.594066
-0.640654
TNPCFS
-0.760934
0.388409
-0.733949
-0.379538
0 658492
0.716748
0.496461
-0.614739
TPPCFB
-0.71731 1
0.510258
-0.737336
-0.519689
0630944
0.705558
0.469389
-0.598009
TEMP
0.361366
-0.318310
0.42 8 2 80
0.278670
-0.409765
-0.268028
-0.419283
0.359591
COND
0.437107
-0.387793
0.679973
0.43 7454
-0.576931
-0.509289
-0.229841
0.344735
pH
0.654048
-0.558525
0.787594
0.571944
-0.768107
-0.615158
-0.600048
0.644332
TURB
-0.479788
0.247946
-0.308034
-0.263714
0.2 0 455 9
0.267439
0.131834
-0.327617
DO
0.401967
-0.339656
0.436632
0.301696
-0.466890
-0.328086
-0.473 755
0.408620
ORP
-0 101159
0.002882
-0 178486
-0.039342
0 194673
0.0751 02
0.101075
0048022
WAT D E PAV
-0.101816
0.302553
-0.295439
-0.318825
0.302101
0.272471
0.140777
-0.293047
SOILTHAV
-0.603158
0.256499
-0.589565
-0.301535
0.617167
0.338902
0.232734
-0.607042
SESD Project ID Number:
14-0380
Page 53 of 58
-------
H20SDFS
ASHSDFS
OMSDFS
BDSDFS
TCSDFS
TNSDFS
TPSDFB
TCVG FS
H20SDFS
1.000000
ASHSDFS
-0.383922
1.00000
OMSDFS
0.893922
-1.00000
1.00000
BDSDFS
-0.958789
0.83082
-0.83082
1.000000
TCSDFS
0.840829
-0.91805
0.91805
-0.795805
1.000000
TNSDFS
0.726816
-0.82264
0.82264
-0.671222
0.805213
1.000000
TPSDFB
0.495397
-0.50347
0.50347
-0.521047
0.453685
0.45 6 066
1.000000
TCVGFS
0.241219
-0.27000
0.27000
-0.320295
0.381202
0.225922
0.154684
1 000000
TNVGFS
-0.123581
0.10299
-0.10299
0.123268
-0.196110
-0.094664
-0.249408
-0.379718
TPVG FB
0.179177
-0.08996
0.08996
-0.181462
0.118241
0.038649
0.33021 0
-0.049717
pHPBFS
-0.396585
0.18065
-0.18065
0.371757
-0.271108
-0.228306
-0.112828
-0 208578
H20PBFS
0.824846
-0.70272
0.70272
-0.804189
0.832253
0.662618
0.437956
0 0 675 5 4
ASHPBFS
-0.679301
0.83909
-0.83909
0.762924
-0.599419
-0.852769
-0.638780
-0 040608
BDPBFS
-0.768180
0.73284
-0.73284
0.804183
-0.808661
-0.71 7969
-0.500202
-0 124340
TCPBFS
0.650871
-0.73213
0.73213
-0.735889
0.571443
0.766113
0.620946
0 211182
TNPBFS
0.612724
-0 72951
0.72951
-0 709003
0.554951
0 777328
0 625379
0 332873
TPPBFB
0.389125
-0.46859
0.46859
-0.461531
0.308539
0.545473
0.407396
0 356244
pHPCFS
-0.446527
0.472 9 4
-U. 472 9 4
0.449641
-0.465301
-0.401670
-0.246209
-0 185235
H20PCFS
0,495894
-0.55329
0.55329
-0 433470
0 465774
0548471
0 263885
0 182310
ASHPCFS
-0.617561
0.70466
-0.70466
0.581588
-0.653195
-0.657039
-0.501726
-0.185379
BDPCFS
-0.496235
0.53404
-0.53404
0.425137
-0.45 0 2 0 7
-0.535577
-0.265587
-0 171881
TCPCFS
0.598140
-0.69322
0.69322
-0.555609
0.641 874
0.63 5 751
0.499176
0 093016
TNPCFS
0.600460
-0.65504
0.65504
-0.551746
0.587567
0.673207
0.41 75 6 5
0.068481
TPPCFB
0.619037
-0.67672
0.67672
-0.561554
0.612826
0.686295
0.468963
0 0 45 9 9 4
TEMP
-0.344679
0.32793
-0.32793
0.336636
-0.307413
-0.117755
-0.191848
-0 006333
COND
-0.198894
0.30447
-0.30447
0.180068
-0.265467
-0.246965
0.067140
-0 158657
pH
-0.599743
0.62402
-0.62402
0.575700
-0.567864
-0.41 7326
-0.3 5 9 458
-0 1 375 39
TURB
0.174783
-0.22748
0.22748
-0.150309
0.177564
0.104623
-0.078863
-0 0 42 0 5 7
DO
-0.468121
0.46673
-0.46673
0.443559
-0.434012
-0.307406
-0.355715
-0.028275
ORP
-0.160594
0.11400
-0.11400
0.105585
-0.138555
-0.178448
-0.038448
-0.186241
WATDEPAV
0.548342
-0.57408
0.57408
-0.473240
0.597780
0.5 75 720
0.22901 9
0 212737
SOILTHAV
0.714353
-0.73556
0.73556
-0.678998
0.748314
0.559368
0.286492
0.119785
SESD Project ID Number:
14-0380
Page 54 of 58
-------
TNVGFS
TPVGFB
H20SDFS
ASHSDFS
OMSDFS
BDSDFS
TCSDFS
TNSDFS
TPSDFB
TCVGFS
pHPBFS
H20PBFS
ASHPBFS
BDPBFS
TCPBFS
TNPBFS
TNVGFS
1.000000
TPVG FB
0.09S153
1 .000000
pHPBFS
-0.082809
-0.4541 40
1.000000
H20PBFS
-0.2 5 7221
0.153291
-0.212076
1.000000
ASHPBFS
-0.08911 0
-0.437053
0.308329
-0.590896
1.000000
BDPBFS
0.141177
-0.444847
0.208224
-0.861612
0.646084
1.000000
TCPBFS
-0.077687
0.342 0 5 8
-0.348848
0.544496
-0.8 9 7280
-0.641063
1 .000000
TNPBFS
0.051280
0.346814
-0.393211
0.489674
-0.880041
-0 565837
0.940842
1.000000
TPPBFB
0.1 8381 8
0.275 1 82
-0.505199
0.228225
-0.681277
-0.2645 7 8
0.709975
0.835169
pHPCFS
0.186189
-0.53861 1
0.799703
-0.200944
0.252788
0.087323
-0.271782
-0.288299
H20PCFS
-0.191901
0.166609
-0.223361
0.682492
-0.674736
-0.655196
0.582079
0.644487
ASHPCFS
0.284415
-0.198571
0.260267
-0.662947
0.672115
0.683690
-0.793541
-0.821898
BDPCFS
0.281893
-0.219180
0.273182
-0.732669
0.712869
0.715818
-0.691059
-0.724494
TCPCFS
-0.209292
0.349252
-0.370521
0.81 7227
-0.899078
-0.763139
0.866922
0.853054
TNPCFS
-0.1 40267
0.264725
-0.294624
0.735190
-0.787691
-0.686324
0.798744
0.801363
TPPCFB
-0.144749
0.354545
-0.313012
0.772253
-0.81 0965
-0.755401
0.718225
0.72 1588
TEMP
0.270103
-0.241018
-0.202782
0.085676
-0.214453
-0.116113
0.249640
0.287440
COND
-0.0 745 0 4
-0.125419
-0.023044
-0.213681
0.040650
0.186023
-0.117129
-0.176772
pH
0.023809
-0.324590
0.123135
0.067069
0.169860
0.032438
-0.163909
-0.112474
TUF1B
0.008825
-0.052535
0.1 17063
-0.381431
0.250704
0.234076
-0.237420
-0.346908
DO
0.222129
-0.414292
-0.010907
-0 155958
0.189066
0.229775
-0.209152
-0.129931
ORP
0.289938
-0.023605
0.179855
-0.21 0398
0.253869
0.154892
-0.329051
-0.337865
WAT D E PAV
-0.042008
0.096098
-0.140431
0.82 45 37
-0.633799
-0.775023
0.611661
0.571197
SOILTHAV
0.127064
0.268907
-0.269370
0.706533
-0.574730
-0.670067
0.553918
0.477682
SESD Project ID Number: 14-0380
Page 55 of 58
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TPPBFB
H20SDFS
ASHSDFS
OMSDFS
BDSDFS
TCSDFS
TNSDFS
TPSDFB
TCVGFS
TNVGFS
TPVG FB
pHPBFS
H20PBFS
ASHPBFS
BDPBFS
TCPBFS
TNPBFS
pHPCFS
H20PCFS
ASHPCFS
BDPCFS
TCPCFS
TNPCFS
TPPCFB
TPPBFB
1.000000
pHPCFS
-0.452G99
1.000000
H20PCFS
0.S73S59
-0.4222 9 8
1.000000
ASHPCFS
-0.G10245
0.000400
-0.711899
1.000000
BDPCFS
-0.002940
0.410080
-0.943792
0.876439
1.000000
TCPCFS
0.032503
-0.015999
0.670200
-0.957326
-0.041910
1.000000
TNPCFS
0.515340
-0.023204
0.779220
-0.905016
-0.740952
0.909301
1.000000
TPPCFB
0.552802
-0.034182
0.748804
-0.851962
-0.709010
0.800580
0.912075
1.000000
TEMP
0.217349
0.442 3 2 3
-0.273831
0.378086
0.275080
-0.390782
-0.345618
-0.419323
COND
-0.130193
0.158047
-0.204702
0.274310
0.245925
-0.235143
-0.297980
-0.254192
pH
-0.152484
0.014715
-0.453821
0.602487
0.452003
-0.075358
-0.645896
-0 698709
TUF1B
-0.454450
-0.014140
0.132614
-0.021056
-0.142813
-0.007342
0.0772 1 5
0.11 7272
DO
-0.008307
0.504230
-0.432732
0.550775
0.403488
-0.002903
-0.558394
-0 031170
ORP
-0.285937
0.153310
-0.430263
0.143695
0.431307
-0.095207
-0.217697
-0285008
WAT D E PAV
0.322917
-0.177758
0.400358
-0.439070
-0.529879
0.417830
0.415291
0.476935
SOILTHAV
0.129270
-0.385430
0.379013
-0.481989
-0.371807
0.517824
0.484325
0.473872
SESD Project ID Number: 14-0380
Page 56 of 58
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TEMP COND pH TURB DO ORP WAT DEPAV SOILTHAV
H20SDFS
ASHSDFS
OMSDFS
BDSDFS
TCSDFS
TNSDFS
TPSDFE!
TCVGFS
TNVGFS
TPVG FB
pHPBFS
H20PBFS
ASHPBFS
BDPBFS
TCPBFS
TNPBFS
TPPBFB
pHPCFS
H20PCFS
ASHPCFS
BDPCFS
TCPCFS
TNPCFS
TPPCFB
TEMP 1.000000
COND 0.065171 1.000000
pH 0.653027 0 403074 1 000000
TURB -0.1 69703 -0 242450 -0.350068 1.000000
DO 0.799474 0 035334 0 765344 -0.197141 1.000000
ORP 0.122894 -0 196519 0 051344 -0.045979 0.274479 1.000000
WAT DEPAV -0.066067 0.085949 -0 207535 -0.000605 -0.265777 -0.428876 1.000000
SOILTHAV -0.248882 -0 120626 -051 1665 0.240057 -0.388811 -0.042487 0.544976 1.000000
SESD Project ID Number: 14-0380
Page 57 of 58
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END OF REPORT
SESD Project ID Number: 14-0380 Page 58 of 58
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