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Environmental Dredging to Remove Fine-Grained, Organic-Rich Sediments and Reduce Inputs of Nitrogen and Phosphorus to a Subtropical Estuary

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Environmental dredging of fine-grained, organic-rich sediments, locally referred to as Indian River Lagoon (IRL) muck, have been promoted as an integral part of restoring the IRL, Florida, to a healthy ecosystem. In Turkey Creek, a tributary to the IRL, ~300 metric tons of N and ~70 metric tons of P were removed with 160,000m ³ of wet muck and sand via environmental dredging during 2016 and 2017. Within the established dredged area, muck removal efficiency was ~63%; some areas were not dredged deep enough to remove all the muck. An additional 24,000 m ³ of muck located outside the dredged area were not removed due to the presence of docks and seawalls. Prior to dredging, benthic fluxes of dissolved N (as ammonium) and P (as phosphate) from sediments to the overlying water, adjusted to 25°C, averaged 11 mg N/m ² /h and 2.5 mg P/m ² /h, respectively. Where IRL muck was removed to expose the underlying sand or mixed sand and muck, benthic fluxes of N and P were 20- to 30-fold lower after dredging. Subsequent disturbances, including Hurricane Matthew in October 2016, redistributed residual muck, leaving the dredged area 26%muck-free.Wheremuck was incompletely dredged or reintroduced by slumping, fluxes returned to predredging values within 6 months as equilibrium was reestablished between sediments and interstitial water. Dredging produced a 50% increase in water depth and basin volume with positive increases in salinity and the total inventory of dissolved oxygen. This deeper basin also serves as a sediment trap that will sequester future inputs of muck and mitigate future benthic fluxes of N and P by reducing the transport of muck into the IRL.
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PAPER
Environmental Dredging to Remove
Fine-Grained, Organic-Rich Sediments
and Reduce Inputs of Nitrogen and
Phosphorus to a Subtropical Estuary
AUTHORS
Austin L. Fox
John H. Trefry
Department of Ocean Engineering
and Marine Sciences, Florida
Institute of Technology
ABSTRACT
Environmental dredging of ne-grained, organic-rich sediments, locally
referred to as Indian River Lagoon (IRL) muck, has been promoted as an integral
part of restoring the IRL, Florida, to a healthy ecosystem. In Turkey Creek, a
tributary to the IRL, ~300 metric tons of N and ~70 metric tons of P were removed
with 160,000 m
3
of wet muck and sand via environmental dredging during 2016
and 2017. Within the established dredged area, muck removal efciency was
~63%; some areas were not dredged deep enough to remove all the muck. An
additional 24,000 m
3
of muck located outside the dredged area were not removed
due to the presence of docks and seawalls. Prior to dredging, benthic uxes of
dissolved N (as ammonium) and P (as phosphate) from sediments to the overlying
water, adjusted to 25°C, averaged 11 mg N/m
2
/h and 2.5 mg P/m
2
/h, respectively.
Where IRL muck was removed to expose the underlying sand or mixed sand and
muck, benthic uxes of N and P were 20- to 30-fold lower after dredging.
Subsequent disturbances, including Hurricane Matthew in October 2016,
redistributed residual muck, leaving the dredged area 26% muck-free. Where muck
was incompletely dredged or reintroduced by slumping, uxes returned to
predredging values within 6 months as equilibrium was reestab-lished between
sediments and interstitial water. Dredging produced a 50% increase in water depth
and basin volume with positive increases in salinity and the total inventory of
dissolved oxygen. This deeper basin also serves as a sediment trap that will
sequester future inputs of muck and mitigate future benthic uxes of N and P by
reducing the transport of muck into the IRL.
Introduction
Fine-grained, organic-rich sedi-
ments are well recognized as primary
repositories for toxic metals, organic
substances, and excess nutrients in
coastal estuaries in the United States
and globally (e.g., National Research
Council, 1997; Salomons & Brils,
2004). One such repository, the
Indian River Lagoon (IRL), is a bar-
built estuary that extends for 250 km
along the central east coast of Florida.
Within a 140-km section of the
IRL that has no inlets to the ocean
(between Ponce de Leon and Sebastian
Inlets), >4 million m
3
(~5.2 × 10
6
yd
3
)
of ne-grained, nutrient-rich sediment
have accumulated in numerous areas
where sand and shell once covered
the bottom. Locally called IRL muck,
this sediment contains 10%30%
organic matter (OM) and >60% silt
and clay with a high water content
(75% water by weight; porosity > 0.9).
IRL muck (1) is easily resuspended to
block light from seagrass, (2) consumes
oxygen, (3) is characterized by a dearth
of biota, and (4) continually releases
dissolved N and P that contribute to
eutrophication in the IRL.
Management of IRL muck requires
a multifaceted approach that addresses
both control of upland inputs of N, P,
and suspended sediments plus removal
of muck that has already accumulated.
Muck removal is an integral part of the
ongoing restoration process for the IRL
(Tetra Tech & Close Waters, 2016).
Although dredging is an effective
method for removing large reservoirs
of N and P associated with ne-grained
sediment, numerous challenges and
limited data constrain present-day
assessments of environmental dredging
in the IRL. A postdredging evaluation
of muck removal in Crane Creek,
another tributary to the IRL, identied
~82,000 m
3
of muck in 2002, even
though the creek had been dredged
four years earlier (Trefry et al., 2004).
42 Marine Technology Society Journal
Keywords: environmental dredging, eutrophication, nitrogen, phosphorus
This observation emphasized issues
with incomplete dredging near docks
and seawalls, as well as postdredging
redistribution of undredged muck.
Despite challenges to dredging in re-
stricted basins with docks and seawalls,
the present study of muck removal
from Turkey Creek, a tributary to the
IRL, provided an opportunity to
evaluate the effectiveness of environ-
mental dredging.
The U.S. Army Corps of Engineers
and others have developed approaches
to establish and evaluate objectives for
environmental dredging for a variety of
purposes (e.g., Palermo et al., 2008).
Environmental dredging of Turkey
Creek was initiated with the following
objectives: (1) remove N- and P-rich
sediment from the creek so that it
would be less likely to be resuspended
and transported into the IRL and
(2) decrease uxes of dissolved N and
P from creek sediments to the overlying
water column. The success of environ-
mental dredging is evaluated here
based on the following considerations:
(1) metric tons of N and P removed,
(2) fraction of muck removed, and
(3) decrease in benthic ux of N and
P to the water column.
Methods
Muck Survey, Sediment,
and Water Collection
Dredging in Turkey Creek began
on February 20, 2016, followed by a
planned temporary shutdown on
April 22, 2016, for manatee season.
Dredging resumed on September 6,
2016, and was completed on January
11, 2017. Muck surveys were carried
out before and after dredging using a
4-cm diameter, capped polyvinyl chlo-
ride pole with 4-mm diameter holes at
half-meter intervals along its length to
maintain neutral buoyancy. The pole,
marked in centimeter graduations, was
lowered into the water column until
the surface layer of sediment was
encountered; this depth was recorded
as the water depth. The pole was
then pushed into the sediment until a
rm bottom was struck and the total
depth minus the water depth was
recorded as the thickness of the muck
layer. Water depths were validated at
5% of the sites by lowering a 20-cm
diameter weighted plastic disk attached
to a calibrated rope until it settled onto
bottom sediments. The thickness of
the muck layer was veried with sedi-
ment cores at four sites during each
survey. Data from each survey were
tabulated, and elevations were adjusted
to a reference datum established
during the initial survey and traceable
to the North American Vertical
Datum of 1988 (NAVD88). Contour
maps for water depths, muck distribu-
tion, muck thicknesses, and changes in
waters depth and muck thicknesses
were prepared using ArcGIS (Version
10.2.2.3552, Esri, Redlands, CA).
Surface sediment samples for chem-
ical analysis were collected before,
during, and after dredging using a
0.1-m
2
Ekman grab. Sediment from
the top ~2 cm was placed in double
Ziploc bags for grain size analysis and
in polycarbonate vials (~70 ml) for
other chemical analyses. Sediment
cores were collected before and after
dredging by divers using 60-cm-long,
7-cm-diameter cellulose acetate buty-
rate tubing. These cores were subsec-
tioned upon return to the laboratory
into 2-cm intervals for chemical analy-
sis. Interstitial water was obtained
from 16 sections along 30-cm cores
using whole-core squeezers ( Jahnke,
1988).
Additional samples of interstitial
water were obtained using minipiston
corers made from modied 30-ml
syringes (Eleftheriou, 2013). Sediment
in the minicores was cut to a length of
3 cm, extruded into nitrogen-purged
tubes, and centrifuged at 3,000 RPM
for 10 min to obtain the supernatant
interstitial water (Khalil & Rifaat,
2013). All extracted interstitial water
was ltered through 0.45-μMpore-
size polypropylene lters and analyzed
immediately for sulde following
Standard Methods 4500-S2
-
D(Rice
et al., 2012).
Vertical proles for salinity, tem-
perature, pH, and dissolved oxygen
(DO) were obtained monthly or
bimonthlyduringdredging,from
April 2015 to April 2017, using inter-
calibrated YSI 6600 V2 or YSI ProDSS
probes (Yellow Springs Instruments).
Thesondeswerecalibratedatthe
beginning of each day following the
manufacturers specications. Discrete
samples were collected at nominal
depths of 0.5, 1.0, and 2.0 m and dee-
per as appropriate through depth-
calibrated Tygon tubing attached
at the surface to a peristaltic pump.
Samples were placed in acid-washed
low-density polyethylene bottles and
stored in coolers until returned to the
Marine & Environmental Chemistry
Laboratories at Florida Institute of
Technology. Samples were then
ltered within 23h.
Laboratory Analyses: Sediments
All sediment samples, except sub-
samples for grain size, were freeze-
dried to a constant weight (>72 h)
using a Labconco FreeZone 6 system
andthenpowderedusingaSPEX
Model 8000 Mixer/Mill. Water con-
tent was determined based on the loss
of water by freeze drying [(weight
wet
weight
dry
/ weight
wet
) × 100]. In prep-
aration for analysis for Al, Fe, Si, and P,
1020 mg of freeze-dried, homog-
enized and desiccated sediment or
July/August 2018 Volume 52 Number 4 43
certied reference material (CRM)
sediment MESS-3, from the National
Research Council of Canada, were
totally digested in sealed Teon tubes
using concentrated, high-purity HF
and HNO
3
following methods
of Trefry and Trocine (1991). Com-
plete digestion of the sediment was
chosen because it accounts for the
entire amount of each element in the
sample.
Sediment trace metal concentra-
tions were determined by dissolving
samples using high-purity HF,
HNO
3
, and HClO
4
. Analysis for Cr,
Cu, and Zn was carried out using a
Perkin-Elmer Model 4000 atomic
absorption spectrometer (AAS) and
for As, Cd, Ni, Pb, and Sn using a
Varian Model 820-MS inductively
coupled mass spectrometer (U.S.
EPA, 1991; Trefry & Trocine, 2011).
Total Hg concentrations were deter-
mined by cold vapor AAS for samples
digested in high-purity HNO
3
and
H
2
SO
4
(Trefry & Trocine, 2011).
All results for the CRM MESS-3
were within the 95% condence limits
for certied values. Analytical preci-
sion (as relative standard deviation,
RSD = [SD/mean] × 100%) deter-
mined from analysis of replicate sam-
ples ranged from 1% (Al, Cu, and Fe)
to 3% (Sn). Procedural blanks and
matrix spikes were also included in
our laboratory procedures (Trefry &
Trocine, 2011).
Grain size analyses were carried out
using the classic method of Folk
(1974) that includes a combination
of wet sieving and pipette techniques.
Loss on ignition (LOI) at 550°C was
determined using freeze-dried and
desiccated samples following the
method of Heiri et al. (2001). Values
for LOI estimate the fraction of OM
in the sample and were used in conjunc-
tion with concentrations of organic C,
total N, and total P to help characterize
sediment composition. Concentra-
tions of CaCO
3
were determined by
heating the sediment that had been
treated for LOI at 550°C to 950°C
following the method of Heiri et al.
(2001).
Concentrations of total organic
carbon (TOC) were determined using
freeze-dried sediment that was treated
with 10% (v/v) hydrochloric acid to
remove any inorganic carbon, then
washed with carbon-free, high purity
water (HPLC grade) and dried.
Approximately 200800 mg of pre-
treated sediment were weighed into
ceramic boats and combusted with
pure oxygen at 950°C using a LECO
Corporation (St. Joseph, MI) TruMac
C/N/Ssystemwithquantication of
the CO
2
produced using an infrared
detection cell and following the manu-
facturers specications. Sediment total
N concentrations were determined
using separate samples that were un-
treated prior to analysis to avoid losses
of N during acidication. Nitrogen
analyses of sediments were also carried
out using the LECO system at 950°C
with quantication of the N
2
gas pro-
duced via a thermal conductivity
detector. Concentrations of C and N
in the sediment CRM (MESS-3) and
LECO reference sample 502-309
were within the 95% condence inter-
vals for certied values. Analytical
precisions (RSD) were 1.5% for TOC
and 2% for total N based on analysis of
5% of the samples in replicate.
Laboratory Analyses: Water
Water samples for dissolved nutri-
ent analysis were vacuum-ltered
through polycarbonate lters (Poretics,
47-mm diameter, 0.4-μmporesize)
in a laminar ow hood. Ammonium
concentrations were quantied using a
SEAL (Mequon, WI) AA3 HR Contin-
uous Segmented Flow AutoAnalyzer
following standard methods (#4500-
NH
3
; Rice et al., 2012). The U.S.
National Institute of Standards and
Technology (NIST) traceable SPEX
CertiPrep Cation Standard was ana-
lyzedwitheachbatchofsamples;all
values were within the 95% condence
interval. Analytical precision (RSD) for
lab duplicates was <3%.
Concentrations of nitrate + nitrite
were determined using a SEAL
(Mequon, WI) AA3 HR Continuous
Segmented Flow AutoAnalyzer follow-
ing manufacturers method G-172-96.
The NIST-traceable Dionex 5-Anion
Standard was analyzed as a reference
standard with each batch of samples
to ensure accuracy; all values were
within 10% of the known concentra-
tion. Analytical precision (RSD) for
lab duplicates was 6% ± 5%.
Concentrations of orthophosphate
were determined using a SEAL AA3
HR Continuous Segmented Flow
AutoAnalyzer following manufac-
turers method G-297-03. The NIST-
traceable Dionex 5-Anion Standard
wasanalyzedasareferencestandard
with each batch of samples to ensure
accuracy; all values were within 95%
condence interval for this standard.
Analytical precision (RSD) for lab
duplicates averaged 1%.
Flux Calculations
Diffusive uxes (F)ofNandP
were calculated from gradients of
solute concentrations in interstitial
water (e.g., Berner, 1974; Boudreau
& Scott, 1978) using Ficksrst law
of diffusion (Equation 1). Diffusion
coefcients (D
s
) from Li and Gregory
(1974) were corrected for variations
in temperature, salinity, and sediment
porosity. Concentration gradients (dc
dx)
for N and P were (1) obtained from
discrete samples obtained using
44 Marine Technology Society Journal
whole core squeezers and (2) calculated
from integrated concentrations in the
top3cmofminicoresplusvalues
from the overlying water (Khalil &
Rifaat, 2013). Precision from whole
core squeezers (% RSD) for ux values
was determined from replicate cores.
Precision for minipiston cores (i.e.,
integrated surface sediment samples)
was determined using eld replicates
and direct comparison with values
obtained using whole core squeezers.
F¼Ds
dc
dxð1Þ
Bacterially mediated uxes of N
and P have been shown to vary with
sediment temperature; therefore, tem-
perature coefcients (Q
10
)couldbe
calculated using Equation 2 (Bailey,
2005). Equation 2 was rearranged to
solve for ux (F
2
) at a specied differ-
ent temperature (T
2
in Equation 3).
Fluxes at in situ sediment temperatures
(F
1
and T
1
) were normalized to a con-
stant sediment temperature of 25°C
using Q
10
temperature coefcients
and data from the literature (Bailey,
2005; Trefry et al., 2015).
Q10 ¼ðF2
F1Þ10
T2T1
ðÞ ð2Þ
F2¼10
log Q10
10
T2T1
!
þlog F1
ð3Þ
Results and Discussion
Effectiveness of Muck Removal
Water depths and the presence and
thickness of muck deposits were deter-
mined with ~30-m spatial resolution
in Turkey Creek before dredging in
February 2015 and after dredging in
March 2017 (Figure 1). Additional
measurements were made with ~150-m
resolution in the adjacent IRL. Our
detailed surveys spanned Turkey
Creek from the Florida East Coast
(FEC) Railroad Bridge to Palm Bay
at the mouth of the creek (Figure 1).
Dredging was limited by design to
~60% of the 160,000 m
2
of total area
in the creek due to obstructions from
docks and seawalls plus the presence
of known sand deposits that did not
require dredging (Figure 2).
Water depths of >4 m were found
at <1% (n= 1) of the 111 sites surveyed
prior to dredging (Table 1; Figure 3).
After dredging, 59% of the same 111
sites (n=66)hadwaterdepthsof
>4 m when elevations were adjusted
to the reference datum (Table 1;
Figure 3). The average water depth
for pre- versus postdredging increased
from 2.1 to 3.8 m in the dredged
FIGURE 1
Contour maps of muck thicknesses in Turkey Creek from the FEC Railroad Bridge to the adjacent
IRL (a) before dredging in February 2015 and (b) ~2 months after dredging in March 2017.
Contour maps of (c) increases in water depths and (d) decreases in muck thicknesses (i.e., amount
of muck removed) after dredging. Dots show probing locations.
July/August 2018 Volume 52 Number 4 45
area; maximum water depth increased
from 4.4 to 6.0 m in the dredged area
(Table 1; Figure 3). Increased water
depths in dredged areas can modify
water ow, increase bottom water res-
idence time, and inuence water
chemistry as discussed below in more
detail.
Results from our pre- and post-
dredge muck surveys showed that little
or no muck was present in the adjacent
IRL near the mouth of Turkey Creek
(Figures 1a and 1b). This observation
suggests that any muck carried to the
mouth of the creek at the IRL was
advected away from the immediate
area. Likewise, little or no muck was
found in shallow water (depth < 1 m)
at the northern reaches of Palm Bay,
just west of the mouth of the creek
(Figures 1a and 1b). In contrast, muck
layers as thick as 3 m were found in 2-
to 4-m deep water in the southern
portion of Palm Bay before dredging
(Figure 1a; Table 2).
Data for muck thicknesses from
our predredge survey (for all wet
muck in Turkey Creek from the FEC
Railroad Bridge to the mouth of the
creek, n= 195) were used to calculate
FIGURE 2
Contour map of muck thicknesses in Turkey
Creek before dredging in February 2015 with
overlying dredge cuts (yellow lines) and sta-
tion locations for TC3TC6 (blue circles).
Image credit for dredge cuts: Brevard County
Natural Resources Management Department.
TABLE 1
Groupings of water depths adjusted to the reference datum for Turkey Creek before (February
2015) and after dredging (March 2017) for the dredged area (n= 111).
Predredging (February 2015) Postdredging (March 2017)
Water Depth (m)
No. of Locations
Water Depth (m)
No. of Locations
Dredged Area Dredged Area
01.0 11 01.0 2
>1.01.5 27 >1.01.5 3
>1.52.0 9 >1.52.0 20
>2.02.5 19 >2.02.5 3
>2.53.0 33 >2.53.0 3
>3.03.5 9 >3.03.5 8
>3.54.0 2 >3.54.0 6
>4.04.5 1 >4.04.5 24
>4.55.0 0 >4.55.0 21
>5.05.5 0 >5.05.5 15
>5.56.0 0 >5.56.0 6
FIGURE 3
Water depth adjusted to the reference datum versus thickness of the muck layer for Turkey Creek
(a) before dredging (February 2015) and (b) after dredging (March 2017). Dredged and not
dredged sites include 111 and 84 data points, respectively. Vertical solid lines at 1 m (muck thick-
ness) and horizontal lines at 4 m (water depth) were added to help cross reference the graphs.
46 Marine Technology Society Journal
a total muck volume of 107,000 m
3
for
all of Turkey Creek, including the area
to be dredged (Table 3), in reasonably
good agreement with 114,000 m
3
identied before dredging by contrac-
tors for Brevard County (McGarry
2017). Using our high-resolution
data [1latitude (~30 m) and 1lon-
gitude (~27.5 m) spacing] to extend
contours to the shoreline, we identied
muck adjacent to seawalls in the creek
(Figure 2) and we calculated that
~24,000 m
3
of muck were initially
present outside the area to be dredged
with ~83,000 m
3
located within the
dredge area.
After dredging, muck thicknesses
in the dredged area (as dened on Fig-
ure 2) were >1 m in only 5% (6/111)
of the 111 survey sites relative to 28%
(31/111) of the sites before dredging
(Table 2; Figure 3). Contour maps
showing the increase in water depth
and decrease in thickness of the muck
layer (Figures 1c and 1d) are relatively
well matched with the dredge cuts
(Figure 2). Based on our postdredge
survey (March 2017), 52,000 m
3
of
muck (63% of the original volume of
83,000 m
3
) were removed from the
dredge area (Table 3). The 31,000 m
3
of muck that remained in the dredged
area (Table 3) were mostly due to not
dredging deep enough to remove all
the muck because only ~1,000 m
3
of
much were calculated to have slumped
in from outside the dredged area
(Table 3).
After dredging, 23% (25/111) of
the sites located within the dredged
area contained muck at water depths
shallower than (i.e., above) the bottom
of the preexisting muck layer, suggest-
ing incomplete removal. Muck at
these sites accounted for ~16,000 m
3
or ~50% of the 31,000 m
3
of the
muck that remained in the dredged
area (Table 3). At least 63% (71/111)
of the sites were dredged to an average
depth of ~1m below the bottom of the
muck layer (based on our pre-dredge
survey); ~100,000 m
3
of material were
dredged from below muck deposits
(determined by probing). A total of
9,000 m
3
of muck was identied at
50% of the 71 locations that were
dredged deeper than the bottom of
preexisting muck layers identied dur-
ing our predredge survey; this muck
most likely slumped in from surround-
ing areas to cover freshly exposed sand.
Overall, dredging and redistribution
of residual muck resulted in a 70%
decrease in the mean thickness of
muck (0.90.3 m) in the dredged area
(Table 2). The original surface area
of muck coverage decreased from
76,000 m
2
(92sites×27.5m×30m)
before dredging to 68,000 m
2
(82 sites ×
27.5 m × 30 m) after dredging.
TABLE 2
Groupings of observed muck thicknesses for Turkey Creek before (February 2015) and after
dredging (March 2017) for the dredged area (n= 111). Mean muck thicknesses were 0.9 ± 1.0 m
(predredging) and 0.3 ± 0.4 m (postdredging).
Predredging (February 2015) Postdredging (March 2017)
Muck Thickness (m)
No. of Locations
Muck Thickness (m)
No. of Locations
Dredged Area Dredged Area
019029
>00.10 16 >00.10 11
>0.100.25 5 >0.100.25 21
>0.250.50 19 >0.250.50 22
>0.500.75 12 >0.500.75 15
>0.751.0 9 >0.751.0 7
>1.01.5 4 >1.01.5 3
>1.52.0 5 >1.52.0 1
>2.02.5 8 >2.02.5 2
>2.53.1 14 >2.53.1 0
TABLE 3
Volume of muck in all of Turkey Creek (from the FEC Railroad Bridge to the mouth of the creek) and in the dredged and non-dredged areas of the creek.
Location Volume (m
3
)
a
Before Volume (m
3
)
a
After Volume (m
3
)
a
Removed % Change
Turkey Creek (n= 195) 107,000 54,000 53,000 50%
Dredged area (n= 111) 83,000 31,000 52,000 63%
Nondredged area (n= 84) 24,000 23,000 1,000 4%
a
1yd
3
= 1.308 m
3
.
July/August 2018 Volume 52 Number 4 47
Based on our data and a total of
160,000 m
3
of material reported to
be dredged from Turkey Creek
(McGarry 2017, personal communi-
cation), ~32% of the dredged material
was muck (identied by probing) and
68% was lower water content sedi-
ment (e.g., sand or mixed sand and
muck) dredged from deeper than the
muck deposits. About 30% of sites
(21/71) that were dredged below the
bottom of the muck deposit retained
a sandy bottom for ~3 months after
dredging. Net migration of muck
toward deeper water is shown graphi-
cally by the increase from one site
containing muck with a water depth
of >4 m before dredging (Figure 3a)
to 56 sites after dredging (Figure 3b
and Table 1).
Sediment Composition
Sediment composition and OM
content have long been shown to be
important factors in explaining the
abundance and diversity of benthic
biota (e.g., Dubois et al., 2012;
Kumar & Khan, 2013; Tagliarolo &
Scharler, 2018). In Turkey Creek,
Beckett (2016) and Johnson and
Shenker (2016) found that muck is
essentially uninhabitable, most likely
because of very high concentrations
of H
2
S. In contrast, mixed sand and
muck can have signicantly greater
species abundance and diversity (Cox
et al., 2018). Therefore, sediment
composition and benthic community
structure have been monitored to iden-
tify changes (Cox et al., 2018; this
study).
The water content and chemical
composition of surface sediments in
Turkey Creek are highly variable as a
function of the relative amounts of
sand, silt, and clay in the sample
(Table 4). For example, the water con-
tent of surface sediments in Turkey
Creek throughout the study ranged
from ~46% (by volume) in sandy sed-
iments to ~96% in muck. Sediment
OM also varied widely from 1.6% in
sandy sediments to 22% in muck.
Using a denition of IRL muck with
>75% water by weight (90% by
volume), >60% silt + clay, and >10%
OM (Trefry & Trocine, 2011), 12
of the samples collected in Turkey
Creek before and after dredging t
the parameters listed above for IRL
muck (Table 4). No signicant differ-
ences (i.e., p< 0.05, Studentsttest,
two-tailed assuming equal variance)
were found in the composition of
muck collected before versus after
dredging.
Sediments collected from Turkey
Creek showed a continuum of compo-
sition for TOC, total phosphorus (TP)
and total nitrogen (TN) in response to
the relative amounts of muck and sand.
Very strong correlations (r> 0.9) were
found between (1) TOC and LOI,
(2) TP and TOC, (3) TN and TOC,
and (4) TP and TN (Figure 4). When
data from mid- and postdredging
surveys were plotted, essentially all
data t within the 95% prediction
intervals derived from the predredge
muck samples (Figure 4).
TheslopeofthelineforTOC
versus LOI was 0.35 for the predredge
data; this slope suggests that the OM
collected in Turkey Creek averages
~35% C. Muck samples had an average
C/P molar ratio of 120, close to the Red-
eldratioof106(publishedC/N/P
atomic [molar] ratio of 106/16/1 in
phytoplankton and in deep seawater
by Redeld, 1934; Figure 4b). The
average molar ratio of 10.6 for N/P
in IRL muck was ~35% lower than
the Redeld ratio of 16 (Figure 4d).
This result supports excess N release
from sediment and possible removal
of inorganic P during formation
TABLE 4
Averages ± standard deviations for parameters in muck sediment from Turkey Creek (n= 12) and in representative sediments prior to dredging (n= 9). (LOI = Loss on Ignition at 550 °C, TOC = TOC)
Gravel Sand Silt + Clay LOI CaCO
3
Al Fe Si TOC H
2
OH
2
ON P
(%) (%) (%) (%) (%) (%) (%) (%) (%) (wt. %) (vol. %) (%) (%)
TC Muck 0.5 ± 0.9 13.9 ± 10.8 85.5 ± 10.6 18.9 ± 2.4 13.6 ± 3.9 4.0 ± 0.7 3.7 ± 0.7 18.6 ± 2.2 6.7 ± 0.8 84.5 ± 3.7 93.6 ± 1.6 0.70 ± 0.17 0.14 ± 0.02
TC Sed. 0.6 ± 0.9 59.7 ± 38.0 39.8 ± 38.5 10.1 ± 8.2 6.6 ± 4.7 2.3 ± 1.7 1.9 ± 1.4 29.0 ± 8.6 3.3 ± 2.9 61.1 ± 24.5 80.9 ± 46.7 0.36 ± 0.32 0.08 ± 0.06
48 Marine Technology Society Journal
of Ca- or Fe- minerals (Seitzinger
1991). The TOC and TN values
are for organic C and organic N in
sediments, whereas TP values include
both organic and inorganic P; inorganic
P may be associated with weathered
phosphorite rock or phosphorus sorbed
to inorganic particles and could lead
to N/P ratios lower than the Redeld
ratio.
The 160,000 m
3
of wet sediment
(80.9% water by volume) removed
from Turkey Creek had a total dry mass
of ~83,000 metric tons (160,000 m
3
×
(1 0.809) × 2.7 tons/m
3
). The average
composition of sediments from Turkey
Creek (including muck plus sand and
shell) was 0.36 ± 0.32% N and 0.08
± 0.06% P (Table 4). Therefore, calcu-
lated masses of ~300 metric tons of N
and ~70 metric tons of P (1-signicant
gure) were removed from Turkey
Creek.
Data from sediment cores collected
at four separate locations before and
after dredging showed changes in
chemical composition as a function
of whether (1) muck was dredged to
sand, (2) muck was not completely
dredged, or (3) sand was dredged and
then covered by muck. Two cores
(stations TC5 and TC6) contained
muck (high water content) before
dredging (Figures 5a and 5b). After
dredging, both stations contained a
thinlayer(~2cm)ofmuck,above
~510cmofmixedsandandmuck,
and then sand (low water content)
deeperinthecore(Figures5aand
5b). At station TC4, cores from before
and after dredging contained muck
because this site near the boundary
of the dredged area was not dredged
(Figure 5c). The fourth site (station
TC3, original water depth = 1.1 m)
contained sand before dredging; how-
ever, after dredging to a water depth of
3.8 m and after Hurricane Matthew,
the newly formed basin accumulated
~30 cm of muck (Figure 5d). Concen-
trations of TOC, TN, TP, and Al in
each core increased directly with
increased muck content as discussed
above (Figure 4). Down core trends
in water content are controlled by
increased pressure from sediment
accumulation that promotes upward
advection of water and a decrease in
water content. This loss in water
content is accompanied by essentially
FIGURE 4
(a) Sediment total organic carbon (TOC) versus sediment LOI at 550°C, (b) sediment TP versus
sediment TOC, (c) sediment TN versus TOC, and (d) sediment TP versus TN. Muck samples plot
within the ovals on (a)(d). The molar ratio for the muck samples, where appropriate, is listed next
to each oval. Solid lines and equations on each graph are from linear regression analysis of
predredge data (n= 9), dashed lines show 95% prediction intervals, ris the correlation coefcient,
and pis the pstatistic.
FIGURE 5
Vertical proles for sediment water content, before (pre-) and after (post-) dredging in sediment
cores from stations TC5, TC6, TC4, and TC3. Locations in Figure 2.
July/August 2018 Volume 52 Number 4 49
no changes in concentrations of Al,
TOC, and other sediment chemicals
on a dry weight basis.
Interstitial Water Composition
Decomposition of organic-rich
muck leads to high concentrations of
dissolvedNandPintheabundant
interstitial water (Figures 6a6h).
Before dredging, concentrations of
dissolved N, virtually all as ammonium,
were very high in muck (relative to
sand) with maximum values of
~2,0006,000 μM(2884 mg N/L;
Figures 6a6d). Ammonium concen-
trations in sandy sediments were
<200 μM (2.8 mg N/L). After dredg-
ing, concentrations of ammonium
followed patterns for water content
with >80% lower ammonium values
at stations TC5 and TC6 because
dredging removed muck and left
mostly sand with a surface layer of
mixed sand and muck (Figures 5
and 6). Lower interstitial water
concentrations of ammonium after
dredging in Turkey Creek were consis-
tent with vertical proles obtained
before and after dredging in the Bay
of Cadiz (Forja et al., 1994). At station
TC4, where muck was not dredged,
ammonium values in interstitial water
were ~50% lower after dredging
in March 2017 (T= 21.5°C) than
before dredging in October 2016
(T=29.4°C)(Figure5c).This
observation follows reported seasonal
trends where large amounts of ammo-
nium produced during the summer
were still present in the interstitial
water in October (Trefry et al., 2015).
Then, cooler winter temperatures
decrease ammonium production from
December to March when the cycle
begins again. Highest ammonium
and phosphate values were found
in muck that slumped in over the
original sandy bottom at station TC3
(Figures 6d and 6h), possibly because a
more coherent mass of N- and P-rich
sediment from an originally deeper
muck layer from more shallow water
slumped in over the sand (Figures 6d
and 6h).
Vertical proles of interstitial water
phosphate before and after dredging
followed the same trends observed for
ammonium with much higher values
in muck than sand or mixtures of sand
and muck (Figures 6e6h). Thus,
interstitial phosphate concentrations
were (1) much lower at stations TC5
and TC6 after dredging due to removal
of muck, (2) only slightly changed
at station TC4, and (3) higher in
the new muck at station TC3 (Fig-
ures 6e6h).
Oxygen was essentially absent
from all muck cores before and after
dredging. Thus, concentrations of
FIGURE 6
Vertical proles for interstitial water (ad) ammonium, (eh) phosphate, and (il) sulde before
(pre-) and after (post-) dredging in sediment cores from stations TC5, TC6, TC4, and TC3. Loca-
tions in Figure 2.
50 Marine Technology Society Journal
nitrate + nitrite were below detection
limits (0.2 μM) in all representative
samples analyzed. A postdredging
shift in the sediment redox environ-
ment was observed at all four stations
as characterized by data for interstitial
H
2
S(Figures6i6l). Maximum con-
centrations of H
2
Safterdredging
were (1) lower at stations TC5 and
TC6 due to muck removal and much
lower OM content, (2) lower at station
TC4 due to a decrease in temperature
from 29.4°C to 21.5°C (Table 5), and
(3) higher at station TC3 due to a shift
from sand to organic-rich muck
(Figures 6i6l).
Benthic Fluxes of Nitrogen
and Phosphorus
One goal of environmental dredg-
ing in Turkey Creek was to decrease
benthic uxes of N and P from sedi-
ments to the overlying water through
muck removal. As described above,
complete muck removal from Turkey
Creek was not possible. Direct com-
parison of benthic uxes from before
versus after dredging was complicated
because some of the remaining muck
was redistributed by resuspension or
slumping following dredging, especial-
ly during Hurricane Matthew in Octo-
ber 2016. Such redistribution of muck
can change N and P concentrations in
interstitial water and sediments as
discussed below.
TABLE 5
Pre- and postdredging uxes of N and P determined from interstitial water proles and from surface sediments along with supporting information and
uxes normalized to 25°C.
Predredge
Flux (mg/m
2
/h)
a
Ammonium-N Phosphate-P
Station Sediment Type Date Temp. (°C)
Interstitial
Water Prole
Surface
Sediment
Interstitial
Water Prole
Surface
Sediment
TC3 Sand Oct 2015 29.4 0.1 ± 0.1 0.1 ± 0.0 0.01 ± 0.02 0.01
25.0 0.1 ± 0.1
b
0.1 ± 0.0
b
0.01 ± 0.02
b
0.01
b
TC4 Muck Oct 2015 29.4 8.6 ± 6.3 5.6 ± 0.0 1.0 ± 0.9 0.77
25.0 5.5 ± 4.0
b
3.6 ± 0.0
b
0.6 ± 0.9
b
0.57
b
TC5 Muck Feb 2016 17.7 8.6 ± 7.8 ND
c
1.4 ± 1.8 ND
c
25.0 18.2 ± 16.5
b
3.1 ± 4.6
b
TC6 Muck Feb 2016 17.7 5.0 ± 3.5 ND
c
1.7 ± 2.4 ND
c
25.0 10.6 ± 7.4
b
3.8 ± 6.2
b
Postdredge
Flux (mg/m
2
/h)
a
Ammonium-N Phosphate-P
Station Sediment Type Date Temp. (°C)
Interstitial
Water Prole
Surface
Sediment
Interstitial
Water Prole
Surface
Sediment
TC3 Muck Mar 2017 21.5 1.5 ± 2.5 3.1 ± 1.6 0.09 ± 0.06 0.03
25.0 2.2 ± 3.6
b
4.4 ± 2.3
b
0.13 ± 0.10
b
0.04
b
TC4 Muck Mar 2017 21.5 3.8 ± 3.2 4.4 ± 0.9 0.84 ± 0.12 0.63 ± 0.03
25.0 5.4 ± 4.6
b
6.3 ± 1.3
b
1.23 ± 0.16
b
0.93 ± 0.04
b
TC5 Sand and muck Apr 2017 21.9 0.4 ± 0.4 1.1 ± 0.3 0.09 ± 0.03 0.08 ± 0.0
25.0 0.6 ± 0.6
b
1.5 ± 0.4
b
0.13 ± 0.03
b
0.11 ± 0.0
b
TC6 Sand and muck Apr 2017 21.9 0.4 ± 0.4 0.7 ± 0.0 0.10 ± 0.00 0.06 ± 0.0
25.0 0.6 ± 0.6
b
1.0 ± 0.1
b
0.14 ± 0.00
b
0.08 ± 0.0
b
a
Tons/km
2
/year = 8.8 × mg/m
2
/h.
b
Adjusted to 25°C using Equation 3.
c
Not determined.
July/August 2018 Volume 52 Number 4 51
In addition to muck redistribu-
tion, sediment temperatures were dif-
ferent during pre- and postdredging
determinations of benthic uxes
(Table 5). Previous studies have
shown that temperature-related varia-
tions in benthic uxes of N and P are
linked to changes in microbial activity
(e.g., Klump & Martens, 1989). A
review of 48 estuaries around the
world identied temperature-related
variations in benthic uxes using
temperature coefcients (Q
10
)of2.9
and 3.0 for N and P, respectively
(Bailey, 2005). Similar Q
10
values of
2.8 (N) and 3.0 (P) were calculated
(Equation 2) for this paper using
data from Trefry et al. (2015); these
Q
10
values correspond to ~11%
increases in benthic N and P uxes
per 1°C increase in sediment tempera-
ture. Moreover, ammonium uxes
were reported to be underestimated
during spring and overestimated
during fall due to seasonal lags for
increases (spring to summer) and
decreases (fall to winter) in production
of ammonium within the sediments
(Brady et al., 2013). To address this
lag effect, Q
10
values of 2.9 (N) and
3.0 (P) were used to calculate uxes
at average sediment temperatures for
the month prior to sample collection.
All uxes are shown at in situ temper-
atures and adjusted to 25°C using
Equations 2 and 3 (Table 5).
The effects of incomplete dredging
and muck redistribution also compli-
cated ux calculations for samples col-
lected before and 3 months after
dredging in Turkey Creek. Fluxes of
both N and P at Stations TC5 and
TC6 (adjusted to 25°C) were 20- to
30-fold lower after dredging because
muck removal exposed sandy sediment
(Table 5). At station TC3 where
sand was dredged and ~30 cm of
muck was accumulated, benthic uxes
of N and P increased by 10- to 20-fold
after dredging (adjusted to 25°C;
Table 5).
Collectively, predredging uxes
of N (ammonia) and P (phosphate)
(adjusted to 25°C) from muck in
Turkey Creek (Stations TC4, TC5,
andTC6)averaged11.5.6mg
N/m
2
/hand2.5±1.4mgP/m
2
/h,
respectively. These values twell
within the wide range of uxes for
ne-grained organic-rich sediments
from estuaries around the world
(Bailey, 2005). When applied to the
76,000 m
2
surface area of muck in the
area dredged (92 sites × 27.5 m × 30 m),
predredging uxes were 0.84 kg N/h
(7.4 tons N/year) and 0.19 kg P/h
(1.7 tons P/year). Much lower uxes
(0.1 mg N/m
2
/hand0.01mgP/m
2
/h)
were identied for the 16,000 m
2
(19sites×27.5m×30m)ofsandy
sediments within the dredge area,
before dredging. Sandy sediments con-
tributed only 0.01 kg N/year and
0.001 kg/P/year to Turkey Creek.
After dredging, muck in the dredged
area covered 68,000 m
2
(8,000 m
2
less with 10 fewer muck sites ×
27.5 m × 30 m). Based on the ~10%
reduction in surface area of muck and
lower uxes identied for sandy sedi-
ments, calculated load reductions
were 0.76 tons N/year (~10%) and
0.17 tons P/year (~10%).
Lower uxes (normalized to 25°C)
were also identied for muck remain-
ing in Turkey Creek at 3 months
after the completion of dredging
(~5 months after Hurricane Matthew,
Table 5). This decrease was likely
associated with redistribution of sedi-
ments and mixing as identied for
surface sediments at Station TC3 (Fig-
ure 5d). This recovery period lasted
several months and is consistent with
results from previous studies where
sediment interstitial water proles
were investigated or simulated before
and after dredging (Cornwell &
Owens, 2011; Forja et al., 1994;
Klump and Martens, 1989). By
6 months postdredging, uxes of N
and P from muck at station TC3
(adjusted to 25°C) increased to
11.7 mg N/m
2
/h and 1.5 mg P/m
2
/h
in July 2017. These uxes are in good
agreement with predredging values
and support reestablishment of an
equilibrium between sediments and
interstitial water.
Water Quality
Environmental dredging is de-
signed to remove impaired bottom
sediment and thereby enhance both
sediment and water quality. In con-
trast with typical navigational dredging
of channels, a larger area is typically
included in broadscale environmental
dredging. In Turkey Creek, dredging
increased the average depth and total
volume of the whole basin by ~1 m
(from ~1.9 to ~2.9 m) and ~50%
(300,000460,000 m
3
), respectively.
Here, we consider the impact of envi-
ronmental dredging on the water qual-
ity parameters of salinity, DO, and
nutrients in Turkey Creek.
Large freshwater diversions into
Turkey Creek during the 1920s to
1940s stressed the estuarine ecosystem
in the lower creek and at its boundary
with the IRL (Knowles, 1995). West-
ward rediversion of freshwater to the
St. Johns River is presently underway
(SJRWMD, 2017). Dredging in
lower Turkey Creek and Palm Bay
augmented the rediversion effort by
increasingthevolumeofthedown-
stream receiving basin to previous
levels. At Station TC3 in Palm Bay,
for example, dredging increased water
depths by about threefold (1.23.6 m)
and allowed higher salinity water
from the IRL to move into Palm Bay
52 Marine Technology Society Journal
(Figure 7). Annual and monthly differ-
ences in water ow from Turkey Creek
are sizeable as suggested by the salinity
proles in Figure 7. The increased
volume of saline water in Palm Bay
that resulted from muck dredg-
ingservesasabufferagainsttheim-
pacts of large seasonal freshwater
inputs on shes, benthic infauna,
and seagrass; it also lengthened the
residence time for water in Palm
Bayby~50%duetocorresponding
increase in volume.
The total inventory of DO in Palm
Bay also increased with the increased
volume of water. For example, a
postdredging inventory of DO at
station TC3 on April 4, 2016, was
~22 g O
2
/m
2
, 2.3 times greater than
the predredging value of 9.6 g/m
2
on
April 4, 2016 (Figure 8). Garcia
(1998) reported a similar observation
after dredging in nearby Crane
Creek, except lower DO values were
common in deeper basins (>3 m).
Even though the inventory of oxygen
in Turkey Creek has increased, bottom
water can become hypoxic or anoxic
during the summer as long as organic-
rich sediments are present (Figure 8).
Throughout this study, we obtained
vertical proles for ammonium in
Palm Bay that showed low concentra-
tions for incoming fresher water at the
top of the water column (typically
0.050.1 mg N/L; Figure 9) and
often high values (>0.5 mg N/L;
Figure 9) in saline water at >2.5 m,
especially during summer when sedi-
ment temperatures approached 30°C.
Concentrations of ammonium were
low (<0.07 mg N/L) in the water
column at station TC3 before dredg-
ing (Figure 9a) because the sediment
in the area was sand with low OM con-
tent (i.e., TOC < 1% in sand relative
to >5% in IRL muck). As previously
discussed, muck was deposited at
station TC3 after dredging (Figures 5
and 6). Concentrations of ammonium
in the bottom water at station TC3
during September 2016 were very
high at 0.6 mg N/L (Figure 9b). Sedi-
ment ammonium uxes at station
TC3 were 18.6 mg N/m
2
/h in Sep-
tember 2016 (sediment T= 30°C);
the water column inventory for am-
monium was 670 mg N/m
2
. This in-
ventory could be produced in bottom
sediments via bacterial ammonication
in ~36 h [(670 mg N/m
2
)/(18.6 mg N/
m
2
/h)] in the absence of any signicant
mixing or advection. Ammonium con-
centrations in bottom water during
FIGURE 7
Vertical proles for salinity at station TC3 during April (4), May (5), July (7), and September (9) for
(a) 2015, predredging, (b) 2016, postdredging at station TC3, and (c) 2017, postdredging.
FIGURE 8
Vertical proles for (a) salinity and (b) % DO saturation at station TC3 in Turkey Creek on February
8, 2016 (predredging), and April 4, 2016 (postdredging). Vertical boxes on (b) show the integrated
amount of DO for each date in a water column of 1 m
2
and varying depths. The DO concentration
on February 8 was relatively uniform at 8 mg/L (=8 g/m
3
) over a total water depth of 1.2 m (Inte-
grated DO = 1.2 m × 8 g/m
3
= of 9.6 g/m
2
). On April 4, the integrated O
2
was 22 g/m
2
(based on
using 10-cm-thick layers and the average DO value in each layer; DO was 6.6 g/m
3
at 1 m and 3.5 g/m
3
at 3.0 m).
July/August 2018 Volume 52 Number 4 53
winter are typically 10 times lower than
in summer. In the absence of muck sed-
iments, ammonium uxes from sand
are <0.2 mg N/m
2
/h as discussed
above.
Similar trends were found for phos-
phate. Surface water typically con-
tained <0.03 mg P/L; however, peak
values of >0.15 mg P/L were found
in bottom water during the hot sum-
mer months (Figure 9). Similar to am-
monium, a benthic ux in summer of
4mgP/m
2
/h could produce a phos-
phate inventory of 190 mg P/m
2
in
~48 h.
Sediment Quality
Mean concentrations of potentially
toxic trace metals (total As, Cd, Cr,
Cu, Hg, Ni, Pb, Sn, and Zn) in eight
representative samples of dredged
muck sediment from Turkey Creek
were not signicantly different (ttest,
two-tailed, α= 0.05,p> 0.05) from
results for sediments from the IRL
(Table 6). Sediment quality guidelines
have been used to determine whether
sediments have metal concentrations
that may cause adverse biological
effects. Long et al. (1995) introduced
an Effects Range Low (ERL) and an
Effects Range Median (ERM) that
were set at the 10th and 50th percen-
tile, respectively, from an ordered list
of concentrations of metals in sedi-
ments with an associated biological
effect. None of the sediment metals
in our study exceeded realistic values
for the ERM or ERL as dened by
Long et al. (1995) and further rened
by OConnor (2004) (Table 6). Several
authors state that sediment quality
guidelines should be used cautiously.
For example, OConnor (2004)
noted that the ERL is a concentration
at the low end of a continuum that
links metal values with toxicity and
that these criteria call attention to a
specicsitewhereadditionalstudy,
such as determining benthic com-
munity structure, may be warranted.
None of the Turkey Creek sam-
ples contained metal concentrations
above the ERL and therefore should
be considered unlikely to harm ben-
thic biota.
Previous studies of IRL sediments,
including samples from Turkey Creek,
have shown similar results for organic
substances as shown for metals (Trefry
et al., 2008). They found concentra-
tions of total polycyclic aromatic
hydrocarbons (TPAH) throughout
the IRL were <4 μg/g. All TPAH
values in the IRL are below the Appar-
ent Effects Threshold of 22 μg/g (Long
& Morgan, 1990); therefore, risks
would be low from these contami-
nants. Bis(2-ethylhexyl) phthalate,
the most universally distributed of all
phthalate esters, was the only phthalate
ester detected in sediments from the
IRL and at only the following two
locations: (1) near Cocoa (0.12 μg/g)
and (2) in Eau Gallie Harbor
(0.20 μg/g) (Trefry et al., 2008).
None of the concentrations for chlori-
nated hydrocarbon pesticides in
sediments from the IRL were above
FIGURE 9
Vertical proles in the water column for ammonium at station TC3 during selected months in
(a) 2015, predredging, (b) 2016, postdredging, and (c) 2017, postdredging. Vertical proles in
the water column for phosphate at station TC3 during selected months in (d) 2015, predredging,
(e) 2016, postdredging, and (f) 2017, postdredging.
54 Marine Technology Society Journal
reporting limits for sediments. Analy-
sis for polybrominated diphenhyl
ethers in sediments showed that 3 of
11 congeners studied were above
reporting limits only in Eau Gallie
Harbor (Trefry et al., 2008). Contam-
inant concentrations above sediment
quality criteria are uncommon to
date, most likely due to limited indus-
trial activity or discharges from waste-
water treatment facilities.
Conclusions
About 300 and 70 metric tons of N
and P, respectively, were removed
from Turkey Creek by environmental
dredging of sediments during 2016
and 2017. Within the dredged area,
muck removal efciency was ~63%.
Incomplete removal of muck resulted
mainly from underdredging and not
dredging near docks and seawalls.
Following dredging, water depth
increasedby~1m,andthevolume
of the basin increased by ~50%
(160,000 m
3
). The greater depth and
larger volume increased salinity and
the total inventory of DO in the
water column. These changes will
help buffer the ecosystem from the im-
pacts of freshwater runoff and hypoxia.
Residual muck within and sur-
rounding the dredged area was redis-
tributed during Hurricane Matthew
in October 2016. Some of this muck
covered sand that had been recently ex-
posed; the net result was that ~26% of
the dredged area was muck-free. Prior
to dredging, uxes of N and P from
muck in Turkey Creek averaged 11
mg N/m
2
/h and 2.5 mg P/m
2
/h (ad-
justed to 25°C). In areas where muck
was dredged to expose the underlying
sand, benthic uxesofNandP
decreased by 20- to 30-fold. In areas
where muck remained or was reintro-
duced by slumping, uxes returned to
predredging rates within 6 months as
equilibrium between sediments and
interstitial water was regained. Inputs
of N and P from sediments in Turkey
Creek continue to be directly linked to
the surface area of muck and sediment
temperature.
Other noteworthy results from this
study include the following: (1) a sed-
iment trap was created by dredging
that can capture future particle inputs
from upstream and (2) chemical
analysis of potential contaminants in
dredged muck (e.g., mercury, lead,
TPAH) showed that all values were
below minimum sediment quality cri-
teria. Contaminants in both dredged
and residual sediments are unlikely to
cause adverse impacts to benthic biota.
Dredged sediments are being used as
soil amendments for agricultural and
other uses.
Acknowledgments
We thank Virginia Barker, Mike
McGarry, Matt Culver, and Walker
Dawson from the Brevard County
Natural Resources Management
Department for their support during
this project and for assistance with
logistics and obtaining background
information. We thank John Windsor
of Florida Institute of Technology
for his role as Project Manager. We
appreciate all the other investigators
for their collaboration and scientic
discussions. Field and laboratory
efforts from Bob Trocine, Stacey Fox,
TABLE 6
Concentrations of total metals, organic carbon (TOC), plus TN and phosphorus for samples of dredged muck from Turkey Creek (n=8),plus
sediments from the IRL (n= 23) and values for the sediment quality criteria identied as ERL and ERM.
Al (%) As (ppm) Cd (μg/g) Cr (μg/g) Cu μg/g) Fe (%) Hg (μg/g)
Dredged muck 4.1 ± 1.3 6.2 ± 2.1 0.29 ± 0.09 59 ± 20 27 ± 14 3.1 ± 1.1 0.09 ± 0.03
IRL
a
4.4 ± 1.4 6.9 ± 3.5 0.28 ± 0.15 58 ± 20 44 ± 34 2.6 ± 1.3 0.10 ± 0.09
ERL
b
8.2 1.2 81 70
c
0.15
ERM
b
70 9.6 370 270 0.71
Ni (ppm) Pb (ppm) Zn (ppm) Sn (ppm) TOC (%) TN (%) TP (%)
Dredged muck 14.0 ± 4.3 25 ± 8 91 ± 29 2.0 ± 0.06 4.8 ± 1.5 0.46 ± 0.16 0.11 ± 0.03
IRL 15 ± 6 33 ± 16 95 ± 50 2.4 ± 1.1 5.0 ± 2.3 ––
ERL 20.9 46.7 150 ––––
ERM 51.6 218 410 ––––
a
Trefry and Trocine (2011).
b
Long et al. (1995).
c
OConnor (2004).
July/August 2018 Volume 52 Number 4 55
Kate Beckett, and Jessica Voelker of
Florida Institute of Technology were
outstanding. We also thank Tetra
Tech, Inc., for their helpful reviews
and comments. Support, guidance,
and valuable discussions with Charles
Jacoby of St. Johns River Water
Management District are greatly
appreciated. Funding for this project
was provided by the Florida Legisla-
ture as part of the DEP Grant Agree-
ment No. S0714-Brevard County
Muck Dredging. Support was also
provided by St. Johns River Water
Management District as part of the
Indian River Lagoon Algal Blooms
Investigation Project (Contract
27815).
Corresponding Author:
Austin Fox
Florida Institute of Technology
Melbourne, FL
Email: afox@t.edu
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July/August 2018 Volume 52 Number 4 57
... Our study focused on organic-rich sediments in the Indian River Lagoon (IRL), a barrier island lagoon in Florida. Organicrich sediments in the IRL typically contain >60% silt + clay, >75% water by weight, >10% OM, and >100 µM dissolved H 2 S (Trefry and Trocine, 2011;Fox and Trefry, 2018). These sediments release dissolved nutrients that fuel algal blooms (Fox and Trefry, 2018). ...
... Organicrich sediments in the IRL typically contain >60% silt + clay, >75% water by weight, >10% OM, and >100 µM dissolved H 2 S (Trefry and Trocine, 2011;Fox and Trefry, 2018). These sediments release dissolved nutrients that fuel algal blooms (Fox and Trefry, 2018). Along with increased algal blooms, the IRL has experienced reductions in seagrass, decreased water quality and fish kills (Phlips et al., 2015). ...
... The average water depth for areas with muddy sediments was 2.5 ± 1.0 m with a range of 0.9-4.9 m. These muddy sediments cover an area of <10% of the lagoon; however, they were estimated to be the source of >25% of total dissolved inorganic N and P fluxes to the lagoon (Trefry and Trocine, 2011;Fox and Trefry, 2018;Tetra Tech Inc and Closewaters LLC, 2021). ...
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... Muck is fine-grained sediment characterized by having high organic nutrients and high water content [9][10][11][12]. The nutrient load that is constantly fluxing up into the water from the muck can be higher than the nutrients flowing into the water body from the runoff [13]. This legacy loading of nutrients is an additional cause of eutrophication. ...
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... Field research has linked the potential sources of nutrient pollution causing brown tides to agricultural fertilizer runoff (Zhang et al., 2007), leeching of N from onsite sewage disposal systems (OSDSs, Barile, 2018;Lapointe et al., 2015Lapointe et al., , 2017, and the accumulation of legacy nutrients resuspended by natural and humaninduced actions (Dunne et al., 2011;Fox & Trefry, 2018;Reddy et al., 2011;Yang et al., 2013). Some research suggests that the limiting nutrient for brown tide is organic nitrogen derived from OSDS, which is ultimately reduced to ammonium or urea (Gobler & Sañudo-Wilhelmy, 2001;Gobler & Sunda, 2012;Kang et al., 2015;Lapointe et al., 2017). ...
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... Other external sources of dissolved nutrients to the IRL include agricultural and urban stormwater runoff and atmospheric deposition (Sigua and Tweedale, 2003;Lapointe et al., 2015). Internal nutrient sources include natural N 2 fixation (Patriquin and Knowles, 1972;Capone and Taylor, 1980;Peterson and Fry, 1987) and sediment flux from IRL ''muck" (Fox and Trefry, 2018). ...
Article
Historically, extensive seagrass meadows were common throughout the Indian River Lagoon (IRL) in east-central Florida, USA. Between 2011 and 2017, widespread catastrophic seagrass losses (~95%) occurred in the IRL following unprecedented harmful algal blooms (HABs), including persistent brown tides (Aureoumbra lagunensis). Little is known about how dissolved nutrients and chlorophyll a are related to light limitation or how biochemical factors, such as the elemental composition (C:N:P) and stable isotope signatures (δ13C, δ15N), of seagrasses within the IRL relate to coverage. Accordingly, we conducted a survey from 2013 to 2015 at 20 sites to better understand these relationships. Results showed a negative correlation between DIN and salinity, indicating freshwater inputs as a DIN source. Seawater N:P ratios and chlorophyll a concentrations were higher in the urbanized, poorly-flushed northern IRL segments. Kd values were higher in the wet season and often exceeded seagrass light requirements (0.8 m-1) for restoration, demonstrating light limitation. Species distribution varied by location. Halodule wrightii was ubiquitous, whereas Syringodium filiforme was not found in the northernmost segments. Thalassia testudinum was only present in the two southernmost segments that had the lowest TDN and highest light availability (Kd). Blade %N and %P also frequently exceeded critical values of 1.8% and 0.2%, respectively, especially in the northern segments. Further, δ15N was positively correlated with ammonium, suggesting wastewater as a major N source. The δ13C values indicated a trend of increasing light limitation from south to north, which helps explain the recent catastrophic loss of seagrasses in the northern IRL. Overall, elemental composition reflected high N-availability and seagrass species distributions were relatable to spatial trends in N and light limitation. For effective restoration, resource managers must reduce N-loading to the IRL to diminish HABs and increase light availability. Regular biochemical monitoring of seagrass tissue should also be implemented during restoration efforts.
... Sediments matching or exceeding these content thresholds are a potential source of nutrients and environmental degradation (MRC, 2012). Nutrients fluxing into the water column from organic sediments can contribute to harmful algal blooms (Fox & Trefry, 2018), which in turn can shade seagrasses or cause fish kills. Dying seagrasses, dead fish, and decaying algae further contribute to organic sediments and perpetuate this cycle. ...
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Species distribution, abundance and diversity of mangrove benthic macroinvertebrate fauna and the relationships to environmental conditions are important parts of understanding the structure and function of mangrove ecosystems. In this study seasonal variation in the distribution of macrobenthos and related environmental parameters were explored at four mangrove stations along the Pondicherry coast of India, from September 2008 to July 2010. Multivariate statistical analyses, including cluster analysis, principal component analysis and non-multidimensional scales plot were employed to help define trophic status, water quality and benthic characteristic at the four monitoring stations. Among the 528 samples collected over 168 ha of mangrove forest 76 species of benthic macroinvertebrate fauna were identified. Macrofauna were mainly composed of deposit feeders, dominated numerically by molluscs and crustaceans. Statistical analyses yielded the following descriptors of benthic macroinvertebrate fauna species distribution: densities between 140--1113 ind. m-2, dominance 0.17-0.50, diversity 1.80-2.83 bits ind-1, richness 0.47-0.74 and evenness 0.45-0.72, equitability 0.38-0.77, berger parker 0.31-0.77 and fisher alpha 2.46-5.70. Increases of species diversity and abundance were recorded during the post monsoon season at station 1 and the lowest diversity was recorded at station 2 during the monsoon season. The pollution indicator organisms Cassidula nucleus, Melampus ceylonicus, Sphaerassiminea minuta were found only at the two most polluted regions, i.e. stations 3 and 4. Benthic macroinvertebrate fauna abundances were inversely related to salinity at the four stations, Based on Bray-Curtis similarity through hierarchical clustering implemented in PAST, it was possible to define three distinct benthic assemblages at the stations. From a different multivariate statistical analysis of the different environmental parameters regarding species diversity and abundance of benthic macroinvertebrate fauna, it was found that benthic communities are highly affected by all the environmental parameters governing the distribution and diversity variation of the macrofaunal community in Pondicherry mangroves. Salinity, dissolved oxygen levels, organic matter content, sulphide concentration were the most significant parameters.
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Executive summary 5 Sediments originate in river basins mainly through land and channel erosion processes and are transported in river systems in the direction of the coast, with the oceans being the final sink. Thus land use, climate, hydrology, geology and topography determine sediment supply and transport in rivers. In the river system, temporary deposition can take place. Important in this respect are floodplains, reservoirs and lakes. In many regulated rivers, sediments are trapped behind dams and reduce the sediment supply downstream. Important impacted areas downstream include wetlands, deltas and harbours. Hence, sediments, like water, are a highly dynamic part of river systems: it is not tied to a particular area and is transported through countries in the same river basin. Besides quantity, quality of sediment affects downstream areas. In particular, the presence of contaminants, such as heavy metals, nutrients pesticides and other organic micro-pollutants, threatens the good ecological status of waterways, wetlands and estuarine systems, which is the focal point of the European Water Framework Directive. In addition, the removal of contaminated sediments from waterways and harbours, to ensure their navigability, imposes high costs for the regulatory and responsible authorities at the local level. The European Sediment Research Network – SedNet* – is commissioned by EC DG-Research in order to (main objective) set up a thematic network, initially aimed at the assessment of fate and impact of contaminants in sediment and dredged material and aimed at sustainable solutions for their management and treatment. Hence, between 2002 and 2005 scientific, policy and regulatory aspects of contaminated sediments and dredged material were addressed in 17 workshops and 3 conferences organised by SedNet. Europe’s leading scientists and major sediment managers contributed to these SedNet activities. The results are summarised in this booklet, in the annexes on the enclosed CD-ROM and at the SedNet website (www.SedNet.org). The comprehensive results will be published in 2005 by Elsevier as a series of four books. This booklet gives a short, state-of-the-art overview of the main scientific, policy and regulatory issues on contaminated sediments, based on the results of the SedNet network activities. In particular, this booklet describes the main sources, transport processes and impacts of contaminated sediment and describes the main methods used to evaluate (including chemical analysis, bioassays and impact assessment) and manage (such as treatment, disposal and beneficial uses) contaminated sediment in river basins. The booklet also presents the main policies and regulations that relate to contaminated sediment (including the EU Water Framework Directive) and describes recent developments in sediment management, such as * Project acronym: SedNet; EC contract No. EVK1-CT-2001-20002; EC 5th RTD Framework Programme; keyaction: 1.4.1 ‘Abatement of water pollution from contaminated land, landfills and sediments’. 6 the move towards the basin-scale approach, the use of risk-based management and the need for stakeholder participation in the decision-making process. As a result of the activities of SedNet, and especially the workshops and conferences, SedNet has developed the following main recommendations: • Towards European policy development: Further develop and eventually integrate sustainable sediment management into the European Water Framework Directive and related policy and legislation • Towards sediment management: Find management solutions that carefully balance social, economic and environmental values and are set within the context of the whole river system • Towards research: Improve our understanding of the relation between sediment contamination (hazard) and its actual impact to the functioning of ecosystems (ecological status) and develop strategies to assess and manage the risks involved More specific recommendations are given in Chapter 6.
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Estuarine carbon fluxes constitute a significant component of coastal CO2 emissions and nutrients recycling, but high uncertainty is still present due to the heterogeneity of these areas. Although South Africa has nearly 300 estuaries, very little is known about their contribution to carbon emissions or sequestration. This study aims to provide a first estimation of the carbon emissions and nutrient fluxes of South African sub-tropical estuaries through a direct quantification of respiration, primary production and nutrient regeneration of benthic and planktonic communities. In order to account for the extreme variability in subtropical estuarine areas, due to seasonality in rainfall, two estuaries with opposite characteristics were studied; the temporarily open/closed Mdloti Estuary subjected to strong anthropic pressure, and the permanently open Mlalazi Estuary located in a natural reserve. Field deployment of benthic chambers and clear/dark bottles assessed oxygen, ammonia and phosphate fluxes of both benthic and planktonic communities. An inverse pattern between benthic and pelagic primary production was found in both estuaries. Different drivers related to mouth status and sediment characteristics were identified in the two estuaries. The annual average carbon emission indicates that the two systems are heterotrophic over the year releasing substantial CO2 emissions into the atmosphere. Results show that carbon fluxes in subtropical estuaries are extremely variable in space and time. Future up-scaling carbon estimations need to account for those small scale and regional dynamics.
Book
Completely revised and updated to include many new methods and technologies, this Fourth Edition of Methods for the Study of Marine Benthos provides comprehensive coverage on the tools and techniques available to those working in the area. Commencing with an overview of the design and analysis of benthic surveys, the book continues with chapters covering the sedimentary environment, imaging and diving techniques, macro- and meiofauna techniques, deep sea sampling, energy flow and production. An additional new chapter provided in this edition covers phytobenthos techniques. Written by many of the world’s leading authorities in marine sampling techniques and use, and edited by Professor Anastasios Eleftheriou, this comprehensive Fourth Edition is an essential tool for all marine and environmental scientists, ecologists, fisheries workers and oceanographers. Chapter 1 Design and Analysis in Benthic Surveys in Environmental Sampling ( A.J. Underwood and M.G. Chapman) Chapter 2 Characterising the Physical Properties of Seabed Habitats (A.J. Kenny and I. Sotheran) Chapter 3 Imaging Techniques (C.J.Smith and H.Rumohr) Chapter 4 Diving (C.Munro) Chapter 5 Macrofauna Techniques (A.Eleftheriou and D.C. Moore) Chapter 6: Meiofauna Techniques (P. J. Somerfield and R. M. Warwick) Chapter 7 Deep-Sea Benthic Sampling (A. J. Jamieson, B. Boorman and D. O. B. Jones) Chapter 8 Measuring the Flow of Energy and Matter in Marine Benthic Animal Populations (J. van der Meer, T. Brey, C. H. R. Heip, P. M. J. Herman, T. Moens and D. van Oevelen) Chapter 9 Phytobenthos Techniques (H.Kautsky)
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Because this technique does not require the sediments to be sectioned into sampling intervals before pore-water extraction, it is rapid and eliminates the need for walk-in cold vans, specialized equipment such as sediment squeezers, high-speed centrifuges and gimbals, and glove bags (for sampling anoxic sediments). -from Author