Citation
Multi-Scale Analysis of Benthic Biogeochemical Properties and Processing in a Spring-Fed River and Estuary

Material Information

Title:
Multi-Scale Analysis of Benthic Biogeochemical Properties and Processing in a Spring-Fed River and Estuary
Creator:
Saunders, Thomas John
Place of Publication:
[Gainesville, Fla.]
Publisher:
University of Florida
Publication Date:
Language:
english
Physical Description:
1 online resource (163 p.)

Thesis/Dissertation Information

Degree:
Doctorate ( Ph.D.)
Degree Grantor:
University of Florida
Degree Disciplines:
Soil and Water Science
Committee Chair:
Collins, Mary E.
Committee Co-Chair:
Frazer, Tom K.
Committee Members:
Brenner, Mark
Ogram, Andrew V.
Zimmerman, Andrew R.
Hurt, Wade G.
Graduation Date:
12/14/2007

Subjects

Subjects / Keywords:
Soil and Water Science -- Dissertations, Academic -- UF
benthic, biogeochemistry, chamber, chassahowitzka, citrus, diel, dynamics, estuary, florida, flux, high, interannual, nitrate, nutrient, salt, sediment, spring, subaqueous, uptake
Gulf of Mexico ( local )
Nutrients ( jstor )
Soil science ( jstor )
Estuaries ( jstor )
Genre:
Electronic Thesis or Dissertation
born-digital ( sobekcm )
Soil and Water Science thesis, Ph.D.

Notes

Abstract:
Transparent freshwater rivers emerge from coastal spring boils along the karst northeastern shore of the Gulf of Mexico. Nitrate concentrations in spring waters have dramatically increased and many questions remain as to the factors that control downstream nutrient utilization within coastal spring-fed rivers. This research quantified the spatial distribution, physical and chemical properties, and biogeochemical function of distinct subaqueous soil (sediment) and water column environments to identify controls on nutrient uptake. All research was based in the Chassahowitzka River and Estuary. An analysis of existing multiyear data provided an interannual perspective of nutrient processing within the river and estuary. Subaqueous soils were evaluated to understand the physical and chemical properties of the bed substrate throughout the entire system. Finally, a novel new method was devised to quantify benthic nitrate dynamics in situ with high temporal resolution. ( en )
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Bibliography:
Includes bibliographical references.
Source of Description:
Description based on online resource; title from PDF title page.
Source of Description:
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Thesis:
Thesis (Ph.D.)--University of Florida, 2007.
Local:
Adviser: Collins, Mary E.
Local:
Co-adviser: Frazer, Tom K.
Statement of Responsibility:
by Thomas John Saunders.

Record Information

Source Institution:
University of Florida
Holding Location:
University of Florida
Rights Management:
Copyright Saunders, Thomas John. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Resource Identifier:
664030203 ( OCLC )
Classification:
LD1780 2007 ( lcc )

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Full Text





system. Subaqueous soils were mapped throughout the River and Estuary. Soils varied widely

in their content of total carbon (range 1-197 g/kg; median 45 g/kg), total nitrogen (range 0-17

g/kg; median 3 g/kg), and total phosphorus (range 50.5-2481 mg/kg; median 152 mg/kg). Hand

texture (mucks to gravels), soil electrical conductivity (0.97-11.46 dS/m), and molar nutrient

stoichiometric ratios also highlighted the distinct properties of subaqueous soils mapped within

the system. Finally, a novel chamber-based method was designed, constructed, and tested to

quantify in-situ benthic NO3~ flUXeS at a high-temporal resolution. Results from multiple flux

measurements made over a 24-hour deployment period demonstrated the utility of the

methodology and produced detailed information regarding controls on NO3~ prOcessing at the

study site. Diffuse porewater seepage was also calculated and ranged from 46-176 L/m2/day.

Porewater seepage was significantly related to benthic NO3~ flUXeS through two distinct modes of

influence: conservative dilution and non-conservative (biologi cally-mediated) reactions.










LIST OF FIGURES


Figure page

1-1 Overview of the Chassahowitzka Spring shed and its River and Estuary ................... .......20

2-1 Floridan Aquifer Vulnerability classification ................ ...............46........... ...

2-2 Soil permeability, sinkholes, and the Chassahowitzka NO3- gradient ............... .... ...........47

2-3 Land-uses (2005) in the Chassahowitzka Springshed .............. ...............48....

2-4 The RIVERS dataset water quality monitoring stations ................. ............... ...._...49

2-5 The RIVERS sampling transects 1-5 .............. ...............50....

2-6 Interannual variation of precipitation, discharge and salinity at Transect 1 ......................5 1

2-7 Average monthly precipitation and discharge on the Chassahowitzka River. ................... 52

2-8 Mean monthly air temperature and the percentage of potential insolation.. ................... ...53

2-9 Boxplots of interannual timescale variation in nutrients ........._.._... ......._............_.._54

2-10 Regression of total annual precipitation to average annual NO3~ COncentration ...............55

2-11 Regres si on of annual mean di charge to annual mean NO3~ COncentrati on.............._._. ....5 5

2-12 Regres si on of annual mean di charge to soluble reactive phosphorus concentrate ons......5 6

2-13 Interannual variability of precipitation and discharge ................ ................ ........ .57

2-14 Rates of NO3~ losses as summarized by class ................ ...............58........... .

2-15 Rates of soluble reactive phosphorus losses by class .............. ...............58....

2-16 Boxplots ofNO3~ COncentration summarized by class combinations. ............. ................59

2-17 Boxplots of NO3~ COncentration summarized by transect and class combinations ............60

3-1 Aerial photo mosaic of the Chassahowitzka River and Estuary (1995) ................... .........86

3-2 Aerial photographs (1944 and 1999) of the study area ................. .......... ...............87

3-3 Soil reconnaissance site descriptions and typical pedon sampling locations ....................88

3-4 Subaqueous soil map of the Chassahowitzka River and Estuary ................. ................. 89

3-5 Soil pH and related factors............... ...............90











Table B1 continued


Total
SpCond Dissolved
(mS/cm) Solids
(g/L)
5.352 3.479
5.352 3.479
5.35 3.478
5.348 3.476
5.345 3.474
5.343 3.473
5.341 3.472
5.339 3.471
5.338 3.47
5.822 3.784
5.826 3.786
5.827 3.788
5.854 3.805
5.878 3.821
5.896 3.832
5.889 3.828
5.9 3.835
5.919 3.848
5.942 3.861
5.935 3.857
5.831 3.791
5.827 3.787
5.823 3.785
5.819 3.782
5.817 3.78
5.813 3.778
5.808 3.776
5.806 3.773
5.802 3.772
5.798 3.769
5.794 3.766
5.791 3.765
5.787 3.762
5.787 3.761
5.782 3.758
5.777 3.756
5.776 3.754
5.772 3.751
5.77 3.75
5.768 3.749
5.763 3.746
5.761 3.744
5.757 3.742
5.753 3.74
5.751 3.738


Water
Elevation
(cm)
57.0
56.8
56.5
56.3
56.1
55.9
55.7
55.5
55.9
56.2
55.7
55.6
55.5
55.4
55.3
55.1
55.0
54.9
54.7
54.7
54.8
54.6
54.6
54.4
54.4
54.3
54.2
54.1
54.0
53.9
53.8
53.8
53.7
53.7
53.7
53.7
53.6
53.6
53.6
53.7
53.6
53.8
53.8
53.7
53.6


Temperature
(oC)

22.56
22.56
22.54
22.54
22.55
22.53
22.53
22.54
22.53
22.55
22.55
22.55
22.55
22.54
22.53
22.53
22.52
22.53
22.51
22.49
22.44
22.43
22.45
22.43
22.43
22.41
22.41
22.38
22.38
22.38
22.36
22.38
22.40
22.38
22.40
22.40
22.39
22.40
22.38
22.38
22.40
22.39
22.43
22.43
22.42


Salin ity
(ppt)

2.89
2.89
2.89
2.89
2.89
2.88
2.88
2.88
2.88
3.16
3.16
3.16
3.18
3.19
3.2
3.2
3.21
3.22
3.23
3.23
3.17
3.16
3.16
3.16
3.16
3.16
3.15
3.15
3.15
3.15
3.15
3.14
3.14
3.14
3.14
3.14
3.13
3.13
3.13
3.13
3.13
3.13
3.12
3.12
3.12


DO
(p-M)

213.13
211.88
210.00
209.38
207.50
206.25
204.38
203.13
201.88
215.63
214.38
214.38
214.38
215.00
213.75
213.13
211.88
211.88
210.00
210.63
203.75
202.50
200.63
199.38
197.50
196.25
194.38
193.13
191.25
190.00
188.13
186.88
185.63
183.75
182.50
181.25
180.63
178.75
178.13
176.88
175.63
175.00
174.38
173.75
173.13


Date and Time


4/25/07 4:25
4/25/07 4:30
4/25/07 4:35
4/25/07 4:40
4/25/07 4:45
4/25/07 4:50
4/25/07 4:55
4/25/07 5:00
4/25/07 5:05
4/25/07 5:10
4/25/07 5:15
4/25/07 5:20
4/25/07 5:25
4/25/07 5:30
4/25/07 5:35
4/25/07 5:40
4/25/07 5:45
4/25/07 5:50
4/25/07 5:55
4/25/07 6:00
4/25/07 6:05
4/25/07 6:10
4/25/07 6:15
4/25/07 6:20
4/25/07 6:25
4/25/07 6:30
4/25/07 6:35
4/25/07 6:40
4/25/07 6:45
4/25/07 6:50
4/25/07 6:55
4/25/07 7:00
4/25/07 7:05
4/25/07 7:10
4/25/07 7:15
4/25/07 7:20
4/25/07 7:25
4/25/07 7:30
4/25/07 7:35
4/25/07 7:40
4/25/07 7:45
4/25/07 7:50
4/25/07 7:55
4/25/07 8:00
4/25/07 8:05


pH


7.14
7.13
7.13
7.13
7.13
7.13
7.13
7.13
7.13
7.11
7.11
7.11
7.10
7.10
7.10
7.10
7.10
7.10
7.10
7.10
7.10
7.10
7.10
7.10
7.09
7.09
7.09
7.09
7.09
7.09
7.09
7.09
7.09
7.09
7.09
7.09
7.09
7.09
7.09
7.09
7.09
7.09
7.09
7.09
7.09









the sulfide oxidation process during incubation. Contents of OC, TN, and TP were higher than

those in the Blue Crab and the Chass Sands and were similar to those of the Riversides (Figure 3-

6). Molar ratios of OC:TN and OC:TP were also elevated within the Midden Flats. TN:TP ratios

are comparable to other map units and generally remain close to 25, again reflecting a slight

scarcity of P relative to N in soils of the Midden Flats. Salt marsh productivity rates are among

the highest in the world and are comparable to productivity rates reported in tropical rainforests

and coral ecosystems (Valiela, 1995). The resulting OM is eventually released into the estuary

and commonly deposited in areas with low water velocities. The Midden Flats are dominantly

covered by M~yriophyllum spicatum and provide habitat for numerous estuarine species.

The Shell Bottom typical pedon was classified as a Mollic Psammaquent (Table 3-2, Table

3-7). Sandy textures often resulted from the presence of carbonate shells as opposed to the

Riversides map unit where sandy textures resulted from quartz sands. The epipedon of the

Midden Flats typical pedon was characterized by low chroma (0) and value (2), resulting in the

Einal subgroup classification as a Mollic Psammaquent.

Shell Bottom (ShB)

The Shell Bottom (ShB) is likely a relict channel bottom carved in a time of lower sea-

level (paleo-channel), yet maintained by flushing tidal currents which still serve to mobilize

sediments along its bottom. Large tidal ranges can generate significant ebb and flow tidal

currents which in turn scour the channel bottom. This effect is most notable in the largest portion

of the channel, while smaller branches of the channel are likely less influenced by significant

flushing events. Due to the high hydrologic energy and estuarine environment, benthic substrate

is commonly composed of coarse oyster shell fragments and is therefore porous in nature and

mobile. Some low-energy areas of the channel may accrete organic material transported from









Denitrification rates have been shown to vary across distinct aquatic systems in proportion

to NO3~ l0ad and as a function of residence time (Seitzinger et al., 2006). Seitzinger et al. (2006)

estimated that Total N inputs and denitrifieation rates were related by the following linear

equation: denitrifieation rate (mmol N/m2/yr) = 0.256*(N inputs; mmol N/m2/yr) This equation

suggests that, regardless of the system (estuaries, lakes, or continental shelves) approximately

26% of N delivered to aquatic systems is denitrified. On the Chassahowitzka, the percentage of

NO3~ l0ad removed from transect 1 to 5 was consistently ~30%. This value remained essentially

unchanged despite a ~60% increase in NO3~ l0ad between the Low and High loading regimes.

The percentage of N load removed is a valuable estimate of the system-integrated NO3~ TemOVal

potential and can be used to calculate downstream transfer of NO3~ aS a function of loading. This

measure of NO3~ l0ad removal percentage is relevant for understanding the proportional uptake

capacity the upper river.

Although NO3~ TemOVal rates increased in proportion to NO3~ l0ad, so did the Einal mass of

NO3- transported downstream. Therefore, significant increases in NO3~ COncentrations also

occurred in downstream environments on the Chassahowitzka (i.e. Transect 10) in response to

load and season. This study has shown that, during the two-year High loading period, increases

in NO3~ l0ads at the headspring also produced significant NO3~ COncentration increases at the

river-channel/salt-marsh interface; potentially affecting the salt marsh and estuary. Elevated

NO3~ COncentrations appeared to propagate furthest downstream under High loading and during

Dry season conditions (i.e. under High and Dry conditions). During the Wet season or under

Low loading conditions, elevated NO3~ COncentrations appeared to be constrained within the

upper ten transects of the Chassahowitzka River (Figure 2-16). Temporal variability in NO3

loads at both the seasonal and interannual timescale ultimately superseded spatial controls on









CHAPTER 3
THE DISTRIBUTION AND PROPERTIES OF SUB AQUEOUS SOILS OF THE
CHASSAHOWITZKA RIVER AND ESTUARY

Introduction

The land-sea interface is one of the most biologically and biogeochemically active sites on

Earth's surface resulting from the mixing of resources from terrestrial and oceanic systems.

Reactions at the land-sea boundary fuel fisheries production, regional economies, mitigate

terrestrial anthropogenic contamination, provide valuable habitat, and serve as recreational sites

for coastal populations. The benthic environment has been recognized for its many roles in

riverine and estuarine ecosystems (Jickells and Rae, 1997; Wall, 2004). The physical and

chemical composition of benthic substrate influences habitat quality, ecosystem services, and the

storage and cycling of carbon, nitrogen, and phosphorus (Jickells and Rae, 1997; Wall, 2004).

Resulting from activity at the benthic/aquatic interface, benthic substrate affects estuarine

productivity, fisheries production, and the storage, concentration, and processing of

anthropogenic effluents. Given the importance of the benthic environment, many government

agencies, universities, and consulting agencies charged with understanding and managing natural

resources have begun to survey coastal benthic habitats to comprehend how their physical and

chemical properties vary in space and time and influence its role in the ecosystem.

Subaqueous Soils

Over the past 10-15 years, soil scientists have become increasingly involved in studying

the distribution and properties of the subaqueous environment (Bradley and Stolt, 2003; Demas

and Rabenhorst, 1999; Demas and Rabenhorst, 2001; Demas et al., 1996; Ellis, 2006; Fischler,

2006). Soil scientists modified their longstanding terrestrially-based conceptual framework to

suit the dynamics of a subaqueous environment (Demas and Rabenhorst, 2001). Soil scientists

consider each soil individual or "polypedon" in a similar manner that a biologist considers traits











,


I


I


LOADING: LOW


LOADING: LOW


Season: Dry


Season: Wet


- 500



- 200


Z,


LOADING: HIGH


LOADING: HIGH


Season: Dry


Season: Wet


500 -



200 -


l i l l i l l i l l i l l i l l i l l i
1 3 5 7 9 11 13 15 17 19


l i l l i l l i l l i l l i l l i l i l
1 3 5 7 9 11 13 15 17 19


T RAN S ECT
Figure 2-16. Boxplots of NO3~ COncentration summarized by transect and grouped by High and Low classes of loading condition and
Wet and Dry classes of season. Data are from the RIVERS dataset. Outliers are shown for reference purposes. Figure y-
axes extend horizontally through the plots and are the same in every case


~j9~11.









MIULTI-SCALE ANALYSIS OF BENTHIC BIOGEOCHEMICAL PROPERTIES AND
PROCESSING IN A SPRING-FED RIVER AND ESTUARY






















By

THOMAS JOHN SAUNDERS


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

UNIVERSITY OF FLORIDA

2007









Table 4-1. Rates of chae for all paaeter of iterest calculated during eah ofthe si icbtio peiods
Incubation Date/Time Night/Day NO3- DO Water Temp Salinity pH Light Light
(tide) Clmol/m2/hr Cloml/m2/hr elevation oC/hr ppt/hr units/hr intensity intensity
cm/hr (surface) (underwater)
mmol/m2/min Clmol/m2/min
1 4/24/07
1930 Night (high) -165 -5059 4.22 -0.510 -0.010 -0.002 -263.8 -188.8
2 4/24/07
2315 Night (high) -112 -3393 -3.98 -0.606 -0.005 -0.023 -0.6 12.3
3 4/25/07
3:30Night (low) -205 -3164 -3.31 -0.062 -0.014 -0.014 -18.6 -8.7
4 4/25/07
7:30Day (low) -385 -2079 -0.49 0.039 -0.036 -0.002 65.1 3.2
5 4/25/07
1130 Day (low) -286 5332 9.10 0.606 -0.020 0.020 109.6 65.9
6* 4/25/07
1445 Day (high) NA NA 4.41 NA NA NA 90.4 -52.2
Note: Dissolved oxygen (DO), total dissolved solids (TDS); Times represent the mid-point of each incubation period; **Incubation 6
was disturbed by a passing watercraft and therefore rates of change were not calculated for parameters measured within the chamber





y =239.5 -9.5*x + 0.04*X2


ldn I


a) 4


y =-15.5609 -2.8755*x









Excluded point
from Incubation 3


-110


-160


-210


-260


-310


-360


-410


E
O



O



3
On
1-


20 40 60 80

SGD


100 120

(L/m2/day)


140 160 180


-
S-100

-


is
( )-200
Z

- 250


0 -300
Z


y =2.6 -0.71*x


20 40 60 80 100 120
SGD (Lm2/day)


140 160 180


20 40 60 80 100 120 140
SGD (L/m2/day)


160 180


Figure 4-6. Relationships between submarine groundwater discharge (SGD) and a) total NO3
losses, b) conservative NO3~ lOsses, and c) non-conservative NO3~ lOsses. Incubation
6 is excluded due to an accidental chamber opening during the incubation. Incubation
3 is considered an outlier for the equation calculated in Figure a. However,
incubation 3 also had the highest rate of SGD, indicating a potential non-linear
relationship as shown in Figure c. This relationship warrants further investigation in
the future



121









CHAPTER 4
THE SIMULTANEOUS QUANTIFICATION OF SHORT-TERM BENTHIC NITRATE
REACTIONS AND DIFFUSE GROUNDWATER SEEPAGE

Introduction

The benthic environment plays a vital role in estuarine biogeochemical cycling and in

regulating biological productivity (Jickells and Rae, 1997; Wall, 2004). In many coastal

environments, increasing terrestrially-derived NO3- exports have been associated with

environmental problems such as eutrophication and hypoxia, sometimes resulting in significant

economic and ecological damage (Paerl, 2006). Therefore, understanding benthic influences on

the fate and transport ofNO3- entering estuarine environments has become a significant research

priority (see Paerl, 2006). However, methodological challenges have limited the investigation of

two potentially important drivers of benthic NO3- cycling: 1) reactions stimulated by submarine

groundwater discharge and 2) the effects of short-term (tidal/diel) variability of environmental

factors. This study presents an in situ chamber-based method that offers three distinct

improvements over existing approaches for quantifying benthic NO3~ COnSumption and/or

production in dynamic estuarine environments. These improvements include: 1) the capability to

quantify benthic NO3- reaction rates over short (hourly) timescales with unprecedented precision,

2) the ability to simultaneously quantify rates of NO3- reactions and diffuse groundwater seepage

(DGS), and 3) in situ NO3~ analySis and near real-time data availability,. This approach allows

for an detailed analysis of relationships between NO3~ flUXeS and the rate of change of

environmental variables including tide, temperature, insolation, and DGS over short timescales

(hours) .

Short Timescales

Diel variability in estuarine environments integrates the dynamics of tides, changing physical

and chemical water column characteristics (Sakamaki et al. 2006), photosynthetically active









ACKNOWLEDGMENTS

Certain things cannot be completed alone and this dissertation ranks strongly as one of

them. Without the direction, inspiration, and insight of my committee, this work could not have

come to be. My committee chair, Mary Collins was always there with an open ear and sage

advice to manage my energy and keep me on course. I cannot thank her enough for providing

me with a consistent combined dose of direction, freedom, encouragement, and support

throughout my doctoral research experience. She encouraged my exploration of concepts, ideas,

and experiences with a smile and advice when things didn't work out and drive to follow-up

when they did. Tom Frazer challenged me to focus, hone-in on specific questions, collaborate

with peers, and was a boon for open and honest discussion about all things academic; from

dreams to reality. Tom selflessly provided data and resources, encouraged discussion, and was

always a welcoming presence who made me feel that what I was doing was exciting, important

and worthwhile. Wade Hurt was famously Wade Hurt. Wade was amazingly motivated,

dedicated, and selfless with his time and energy in the Hield, onfce, and essentially all the time.

Field days with Wade were some of the brightest highlights of my dissertation experience and I

learned volumes about soil, about myself, and about the world. Mark Brenner was always a

positive influence, asking frank and often necessary questions, offering insight and discussion,

and always encouraging me to keep going. Andy Ogram was available, encouraging, and willing

to share his excitement for the microbial world. Though the maj ority of my dissertation work

was at a large scale, Andy's presence kept me grounded, challenged, and up to date with the

current research into processes occurring at the microbial level. Finally, Andy Zimmermann,

though added as a committee member late in the game, immensely improved my final product

through his detailed reviews, fearless questioning, and thorough discussions.















































OO
















Source Florida Department ofTrarspctation
[FDOT]Surveylngend Mapplrg Offce
2rn Resolutir. Aenal Photos cf the
Chassahowitzka River, Citrus
County, Rlorida. 1995
1:30000
500 0 500 Meters





Figure 3-1. Aerial photo mosaic of the Chassahowitzka River and Estuary (1995). Imagery data provided by the Florida Department

of Transportation (FDOT). Channel forms and depositional flats are evident in the phototones

















160 Ebb Tide








160

50 556 57 58
Wae oum lvtin(m

Fiue47 umrn rudae icag SD srltdt ae ouneeain G
rate ar ihs hntewtr ou neeain r o, ieydet erae
prsueoc h oueo vryn ae a erae




















































TOM1.DSC


insinarnani- 910 fmli Hann


IIIIIIIIIIIIIIIIIII 11111(11


rat appear to be iron-based, rounded minerals from the sample in Figure A-9


Operator:
Dae: wo212aos0
Time: 11:45 AM


-2





Wisw 3eesl cWai1


0 100 200 300
Temperature ("C)


400 500 600


Figure A-14. Differential scanning calorimetry results for clays from the sample in Figure A-9


File Name: ~
IDCDSC Sire. 62s
Desc. 1 :


Univ of Florida














~ij*.
r- :31 *' "' ;

S~i~;~te e




X,11.


I,_ iCc~.
ii
*I~.IC~ P /--.~
Yy r*
EL~
~I
rd~L_~~E~k~:*~U~Z17~? CY~


Figure A-7. Chass Sands augered soil sampled during reconnaissance work











3-6 Soil nutrient data and stoichiometric ratios .............. ...............91....

4-1 Relationship of sampling intervals and the method precision ................. ................ ..116

4-2 Schematic of benthic chamber instrumentation and deployment configuration. .............1 17

4-3 Diel variation in environmental parameters and rates during incubations ...................118

4-4 Regression lines of variables measured during chamber incubations ............................119

4-5 Nitrate losses and their relationship to NO3~ COncentration ................. .. ......_._. .......120

4-6 Relationships between submarine groundwater discharge and NO3~ losses ..........._......121

4-7 Submarine groundwater discharge as related to water column elevation........................122

A-1 Riversides soil core and microscopic images for reference purposes..............................125

A-2 Riversides soil core near on the lateral edge of Crab Creek..........._._. .. ......._._. ......126

A-3 Blue Crab soil core and microscopic images for reference purposes ........._._... .............127

A-4 Blue Crab soil core with a large krotovina .............. ...............128....

A-5 Midden Flats soil core and microscopic images for reference purposes .........................129

A-6 Chass Sands soil core for reference ..........._ .....___ ...............130

A-7 Chass Sands augered soil sampled during reconnaissance work ................. .................1 31

A-8 Chass Sands soil core with a clay-enriched horizon at its base ................. ................. 132

A-9 Subsample from clay enriched horizon............... ...............133

A-10 Microcopic photo of biomineralization site ...._ ......_____ .......___ ............3

A-11 Microscopic photo of biomineralized spherules ................. ..........._._ .......__. .. 13

A-12 Microscopic photo of biomineralized framboidal pyrite ........._..... .... ..___............134

A-13 What appear to be iron-based, rounded minerals............... ...............13

A-14 Differential scanning calorimetry results for clays ................. ................ ......... .135

A-15 X-ray diffraction results from clay and silt fractions ................. ......... ................1 36

A-16 Scanning electron microscope image of minerals ................ ................. ......... ..136

A-17 Scanning electron microscope image of Framboidal pyrite ................. ................. .. 137











Table B2 continued


Surface
Solar
Irradiance
(pIS/cm2/S)
84.6
84.6
84.6
86
86.8
84.5
84.5
84.5
194.8
477.9
588.1
496.3
636.3
929
933
1008
1013
1089
1173
1182
1157
1170
1293
1181
1244
1013
931
815
959
853
1100
1185
1147
1025
1360
1513
922
1516
1404
1485
1193
917
569.1
1425
1765


Subsurface
Solar
Irradiance
pIS/cm2/S)
80.4
80.4
80.4
80.4
80.1
79.96
76.21
72.06
65.63
50.09
39.24
18.88
15.53
393.8
641.1
678.7
722.8
784.9
833
889
824
862
907
884
918
766.3
655
589.3
702.7
658.2
844
899
883
774.2
1003
1112
661.8
1108
1019
1059
842
660
373.2
1014
1260


Panel
Temperature
o"C)
19.34
19.57
19.81
20.05
20.41
20.74
20.92
21.18
21.55
22.42
24.6
28.16
30.15
31.69
34
34.72
35.68
37.23
39.65
41.79
42.01
41.55
41.8
41.64
42.19
41.33
39.85
38.42
37.58
38.28
37.78
38.71
39.47
39.97
41.22
42.83
42.39
41.03
42.79
42.17
42.9
41.25
38.5
36.18
36.53


Red ox
Probe 1


-135.7
-132.5
-136.2
-141.8
-136.4
-133.5
-131.9
-141.2
-115
-106.7
-121.3
-139.9
-121.8
-133
-144.9
-149.7
-153.5
-156.4
-156.6
-155.7
-155.3
-156.6
-158.6
-162.1
-164.2
-166
-166.9
-168.5
-169.8
-170.5
-171.1
-172.8
-173.6
-173.7
-173.4
-173.9
-173.3
-173
-173.6
-173.4
-174.2
-175
-173.6
-172.5
-174.7


Redox
Probe 2

-162.6
-162.2

-160.9
-158.7
-157
-156.2
-155.7
-155.2
-153.2
-154.1
-154.1
-154.3
-153.7
-155.3
-156.2
-156.3
-156.5
-156.7
-156.4
-155.9
-155.3
-154.2
-153.1
-151.9
-150.2
-149.4
-148.8
-147
-146.5
-146.4
-146.2
-147.1
-146.8
-146.5
-146.6
-147.5
-148.1
-148.1
-147.7
-146.6
-145.4
-144.4
-142.2
-136.4
-136


Redox
Probe 3

-120.4
-120.2
-119.5
-119.5
-120.4
-120.4
-120.8

-121.2
-123
-124.2
-122.6
-121.6
-121.4
-126.6
-128.8
-129.7
-128.7
-126.5
-124
-122.1
-121.4
-121.9
-135.1
-132.1
-133.8
-133.5
-133.6
-129.7
-127.4
-126
-125.4
-125.2
-125.1
-124.4
-124.5
-124.5
-123.8
-123.3
-123.6
-123.5
-123.7
-123.6
-121.8
-120.4
-121.9


Redox
Probe 4


-168.5
-167.7
-167.2
-166.1
-165.4
-165.3
-165.6
-165.1
-164
-163.2
-163.2
-163.6
-163.4
-165.5
-164.9
-164.2
-163.6
-163.1
-162.2
-161.1
-159.7
-157.6
-154.9
-152.9
-150.2
-147.5
-145
-142.7
-141
-139.9
-138.1
-137.9
-137.3
-135.4
-134.6
-134.4
-135.3
-137.3
-139.6
-141.3
-143.1
-143.5
-141.2
-139.2
-143


Date and Time


4/25/07 8:15
4/25/07 8:20
4/25/07 8:25
4/25/07 8:30
4/25/07 8:35
4/25/07 8:40
4/25/07 8:45
4/25/07 8:50
4/25/07 8:55
4/25/07 9:00
4/25/07 9:05
4/25/07 9:10
4/25/07 9:15
4/25/07 9:20
4/25/07 9:25
4/25/07 9:30
4/25/07 9:35
4/25/07 9:40
4/25/07 9:45
4/25/07 9:50
4/25/07 9:55
4/25/07 10:00
4/25/07 10:05
4/25/07 10:10
4/25/07 10:15
4/25/07 10:20
4/25/07 10:25
4/25/07 10:30
4/25/07 10:35
4/25/07 10:40
4/25/07 10:45
4/25/07 10:50
4/25/07 10:55
4/25/07 11:00
4/25/07 11:05
4/25/07 11:10
4/25/07 11:15
4/25/07 11:20
4/25/07 11:25
4/25/07 11:30
4/25/07 11:35
4/25/07 11:40
4/25/07 11:45
4/25/07 11:50
4/25/07 11:55










upstream areas when tidal flushing currents are less strong. However, this accretion is likely

temporary as the material will likely be remobilized when higher water velocities return.

Map Unit Names

The Chass Sands map unit was named after the common reference made the

Chassahowitzka River as the "Chass" by locals. This map unit receives the greatest use by locals

for boating and therefore was named after the Chassahowitzka itself. The map unit is dominated

by sandy material, thereby earning the entire name of "Chass Sands". The Riversides map unit

was named such due to the fact that it is the transition between the riparian areas of the river and

the mainstem channel. Much fishing in the area is undertaken on the sides of the river and this is

a common recreational activity on the Chassahowitzka River. The Blue Crab map unit was

named after the blue crabs that are common to the area and play a notable role in the soil

formation within the area. Many locals capture these crabs for recreation and as a food source

and this map unit is a rich area for that activity. The Midden Flats map unit was named due to

the fact that shell middens (kitchen waste from earlier societies) were found in the area of the

map unit. Finally, the Shell Bottom map unit was named after the shell material that was

consistently detected and moving about the bottom of the channel in the salt marsh area.

Typical Pedon Map Unit Representation

Typical pedons were selected based on field observations and multiple soil descriptions.

To evaluate whether typical pedons were representative of other soil descriptions made within a

map unit, typical pedons were directly compared with the reconnaissance soil descriptions from

the same map unit. The surface horizon was chosen for this evaluation as it is the portion of the

soil with closest contact to the overlying water column and may be an important component of

estuarine biogeochemical cycling (see Chapter 4). The Riversides map unit was chosen as an










presence of sulfidic materials resulted in the great group taxonomic classification as a

Sulfaquent. The subgroup of the soil was Typic, as the requirements for Haplic, Histic, and

Thapto-histic subgroups were not met. Two buried horizons were also described indicating that

this area was once covered by emergent vegetation and has since become inundated with water.

The Blue Crab map unit is differentiated from upstream map units based on the elevated

densities of saltwater tolerant estuarine and marine species that begin to dominate the benthos

and the effects of these conditions on the soils. For instance, the increased presence of reduced

sulfides as indicated by the drastic drop of incubation pH is a direct influence of association with

the estuarine environment. With distance downstream, the upstream area contributing OM to the

water column increases, providing OM for settling, mixing, and incorporation into downstream

soils. The Blue Crab map unit remains characterized by sandy textures, but is comparably

enriched in OM compared to the Chass Sands map unit. Krotovina (animal-derived tunnels) were

frequently observed in this map unit, resulting from the burrowing activities of benthic species

such as blue crabs. This burrowing activity also notably increases the content of silt as was

observed in the Hield. An enrichment of silt results in the only loamy textures reported in the

Chassahowitzka River and Estuary. Most textures were sands/fine sands or muck/mucky sand,

which reflect the two extremes of substrates encountered during soil sampling and descriptions.

Midden Flats (MdF)

The large expanses of flats that lay between the vegetated salt marsh and the Shell Bottom

were mapped as the Midden Flats (MdF) and constitute 44.5% of the total area mapped in this

study .

The n values measured in the typical pedon were consistently >0.7 and bulk density ranged

from 0.3-0.8 g/cm. Lower n values resulted from the presence of sand size CaCO3 Shells. Field

and incubation pH were similar, likely as a result of CaCO3-buffering of any pH changes during










LIST OF TABLES


Table page

2-1 Datasets relevant to the Chassahowitzka River and Estuary .............. .....................4

2-2 Transect 1 mean nutrient concentrations summarized by classification...........................4

2-3 Mean annual mass loads over the period of 1998-2006 at Transect 1 ............... ...............42

2-4 Average inorganic concentrations of N and P during the Low loading period .................43

2-5 Average inorganic concentrations of N and P during the High loading period.................43

2-6 Net apparent riverine nutrient loss rates during the Low loading regime..........................44

2-7 Net apparent riverine nutrient loss rates during the High loading regime ................... ......44

2-8 Percentage of inorganic nutrient load lost between RIVERS transects 1 and 5 ................44

2-9 Significant differences in downstream nutrient concentrations ................. ................ ...45

3-1 Subaqueoues soil map units and their charactreristics............... ............8

3-4 Chass Sands (ChS) typical pedon description and taxonomic identification ....................84

3-5 Riversides (RvS) typical pedon description and taxonomic identification........................84

3-6 Blue Crab (BIC) typical pedon description and taxonomic identification. ................... .....85

3-7 Midden Flats (MdF) typical pedon description and taxonomic identification ..................85

4-1 Incubation-based rates of change ........................_. ...............114 ...

4-2 Estimates of submarine groundwater discharge (diffuse porewater seepage) rates ........115

B1 Five minute dataset of chamber and environmental data ................. .......................139

B2 Five minute database of solar irradiance, redox probes, and panel temperature .............146

B3 Thirty minute dataset including raw NO3- data............... ...............153.










uptake capacities of these systems is an important step in directing management strategies,

pollution reduction targets, and total maximum daily loads in the future.


























































Figure A-8. Chass Sands soil core with a clay-enriched horizon at its base






132










Callahan, M.R., J.B. Rose, and J.H. Paul. 2001. A bacteriological and pathogenic water quality
assessment of the upper reaches of the Chassahowitzka River. University of South Florida,
St. Petersburg.

Champion, K.M., and R. Starks. 2001. The hydrology and water quality of select springs in the
Southwest Florida Water Management District. Report to the Southwest Florida Water
Management District.

Dauer, D.M., J.A. Ranasinghe, and S.B. Weisberg. 2000. Relationships between benthic
community condition, water quality, sediment quality, nutrient loads, and land use patterns
in Chesapeake Bay. Estuaries 23:80-96.

Davis, W.P., and A.D. Steinman. 1998. A lightweight, inexpensive benthic core sampler for use
in shallow water. Journal Of Freshwater Ecology 13:475-479.

DeBrabendere, L., Frazer, T.K., Montoya, J. Submitted 2006. Stable nitrogen isotope ratios of
macrophytes and associated periphyton along a nitrate gradient in two subtropical, spring-
fed streams. Freshwater Biology. In Press.

Demas, G.P., M.C. Rabenhorst, and J.C. Stevenson. 1996. Subaqueous soils: A pedological
approach to the study of shallow-water habitats. Estuaries 19:229-237.

Demas, G.P., and M.C. Rabenhorst. 1999. Subaqueous soils: Pedogenesis in a submersed
environment. Soil Science Society of America Journal 63:1250-1257.

Demas, G.P., and M.C. Rabenhorst. 2001. Factors of subaqueous soil formation: a system of
quantitative pedology for submersed environments. Geoderma 102:189-204.

Eisma, D. 1998. Intertidal deposits: River mouths, tidal flats, and coastal lagoons CRC Press,
Boca Raton.

Ellis, L.R. 2006. Subaqueous pedology: Expanding soil science to near-shore subtropical marine
habitats. Ph.D. Dissertation, University of Florida, Gainesville.

ESRI. 2005. ArcGIS 9.1: Release 9.1. Redlands, CA.

FDEP 1997. Florida Department of Environmental Protection Drainage basin data layers.
Accessed online at: http://www.dep.state .fl.us/gis/datadir. asp. March, 2007.

Fischler, K.C. 2006. Observations and characterization of subaqueous soils and seagrasses in a
recently constructed habitat in the Indian River Lagoon, Florida. M.S. Thesis, University
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Fisher, M.M., and K.R. Reddy. 2001. Phosphorus flux from wetland soils affected by long-term
nutrient loading. Journal Of Environmental Quality 30:261-271.

Fisher, D.C., and M. Oppenheimer. 1991. Atmospheric nitrogen deposition and the Chesapeake
Bay estuary. Ambio 20:102-108.










Laursen, A.E., and S.P. Seitzinger. 2004. Diurnal patterns of denitrifieation, oxygen consumption
and nitrous oxide production in rivers measured at the whole-reach scale. Freshwater
Biology 49:1448-1458.

Liu, S.M., J. Zhang, H.T. Chen, and G.S. Zhang. 2005. Factors influencing nutrient dynamics in
the eutrophic Jiaozhou Bay, North China. Progress In Oceanography 66:66-85.

Macreadie, P.I., D.J. Ross, A.R. Longmore, and M.J. Keough. 2006. Denitrifieation
measurements of sediments using cores and chambers. Marine Ecology-Progress Series
326:49-59.

Malecki, L.M., J.R. White, and K.R. Reddy. 2004. Nitrogen and phosphorus flux rates from
sediment in the Lower St. Johns River estuary. Journal of Environmental Quality 33:1545-
1555.

Mallin, M.A., K.E. Williams, E.C. Esham, and R.P. Lowe. 2000. Effect of human development
on bacteriological water quality in coastal watersheds. Ecological Applications 10:1047-
1056.

Martin, J.B., and S.L. Gordon. 1997. Rapid chemical variations in spring discharge; evidence for
surface and ground water mixing and reactions in the Floridan Aquifer; Geological Society
of America, 1997 annual meeting. Salt Lake City, UT, United States.

Martin, J.B., J.E. Cable, J. Jaeger, K. Hartl, and C.G. Smith. 2006. Thermal and chemical
evidence for rapid water exchange across the sediment-water interface by bioirrigation in
the Indian River Lagoon, Florida. Limnology And Oceanography 51:1332-1341.

McGlathery, K.J., P. Berg, and R. Marino. 2001. Using porewater profies to assess nutrient
availability in seagrass-vegetated carbonate sediments. Biogeochemistry 56:239-263.

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Stenberg, R.E. Turner, F. VeraHerrera, and R.G. Wetzel. 1997. Effects of climate change
on freshwater ecosystems of the south-eastemn United States and the Gulf Coast of Mexico.
Hydrological Processes 11:949-970.

NADP. 2006. National Atmospheric Deposition Program precipitation and atmospheric
deposition data. Accessed online at:
http://nadp. sws.uiuc.edu/sites/siteinfo. asp?net=NTN&id=FL05 December, 2006.

Nedwell, D.B., T.D. Jickells, M. Trimmer, and R. Sanders. 1999. Nutrients in estuaries, p. 43-92
Advances in Ecological Research, Vol 29, Vol. 29.

Ni, J.Y., X.Y. Liu, Q.J. Chen, and Y. Lin. 2006. Pore-water distribution and quantifieation of
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Nicholson, G.J., A.R. Longmore, and W.M. Berelson. 1999. Nutrient fluxes measured by two
types of benthic chamber. Marine And Freshwater Research 50:567-572.









(storms/high NO3~ lOading) will likely yield valuable insight into the dynamics and drivers of an

important component of estuarine biogeochemical cycling.



























































Figure 3-2. Aerial photographs taken in 1944 and 1999 suggest that the dominant subaqueous
landforms in the study area are stable (at least over this 55 year period). The aerial
photos do suggest that there may be some infilling of channels with new sedimentary
material


87










of the organic-rich bottom. To estimate the effects of SGD on NO3- additions and losses within

the chamber, it was necessary to calculate the proportion of the total mass NO3- decrease

accounted for by both conservative dilution (i.e. SGD-based dilution) and non-conservative

biogeochemical reactions (i.e. biological assimilation, denitrification, anammox reactions,

dissimilatory NO3- reduction to ammonium, or any other reaction that would alter NO3~

concentrations). The former can be calculated as:

VTSGD 7 0(C/C *VChamber (4-2)

where VTSGD = theoretical volume of SGD required to account for observed changes

concentration (used for NO3- and DO), C, = initial chamber concentration, Cf= final chamber

concentration, and VChamber = final VOlume of the chamber. The latter was calculated as:

Fcp = (VSGD/VTSGD)*100 (4-3)

where Fcp = the percentage of VTSGD accounted for by conservative dilution (of either NO3~ Of

DO). The losses unaccounted for by conservative dilution were assumed to result from non-

conservative biogeochemical reactions.

Fncp = 100-Fcp (4-4)

where Fncp = the percentage of the additions or losses accounted for by non-conservative

biogeochemical reactions. Percentages where then multiplied against actual measurements of

additions and losses to calculate the additions and losses due conservative and non-conservative

processes. It should also be noted that dilution only causes an apparent loss of NO3- and that

total NO3~ maSS is COnSeTVed within the chamber.

Results

Diel Variation

Over the period of study, the average photon flux density ranged from 0-1200

Clmol/m2/min, following the variability expected of a diel cycle (Figure 4-3). Temperature (range









of NO3-. This suggests that chemical reduction in the benthic substrate is key for reducing NO3~

concentrations in two spatially-distinct sites within the river-estuarine system. The first site is at

the base of the highly-reduced subaqueous soil environment. As aquifer groundwater enriched

with anthropogenic NO3- exfiltrates from limestone and passes up into the benthic substrate,

NO3~ is likely lost to microbial uptake and reduction reactions. This mechanism is hypothesized

based on known elevated NO3~ COncentrations in the aquifer, calculated SGD rates, and redox

measurements taken in the Hield that preclude a significant presence of NO3-. The second site of

benthic-mediated NO3- reduction likely occurs at the subaqueous soil/water column interface.

Flows of SGD through the benthic interface likely deliver reduced chemical species towards the

water column that fuel NO3- reduction not only at the benthic/water interface but perhaps in the

water column above. Again, more detailed analyses must be undertaken in the future to test the

above-mentioned hypothetical relationships.

Ultimately, the electron source for NO3- reduction reactions is derived from the microbial

oxidation of organic matter incorporated into the benthic substrate. Given the hypothetical

influence of SGD discussed above, one would expect that substrates with distinct physical and

chemical characteristics, particularly organic matter content, will vary in their interaction with

the SGD moving through them (Ni et al., 2006). Also, the rate of SGD at a given location will

vary with the transmissivity of a given substrate, which in turn varies with the particle size, bulk

density, and organic matter content. Based on these observations, another hypothesis emerges:

Benthic substrate properties significantly influence the chemical properties and rate of SGD.

Given that SGD varies with tide and as a function of bottom type, it is also likely that the

temporal variability of SGD-driven NO3- reactions will also be different between distinct bottom

types.









Table 2-6. Net apparent riverine nutrient loss rates normalized to the area between transects for Wet and Dry seasons during the Low
loading regime (1999-2001). Negative numbers indicate uptake (nutrient losses)
NO3- SRP NH4
LOW Wet Dry Wet Dry Wet Dry
1999-2001 (mg/m2/d) (mg/m2/d) (mg/m2/d) (mg/m2/d) (mg/m2/d) (mg/m2/d)
Tran 1-2 -309.6 -206.4 -14.0 -33.3 -32.2 -32.2
Tran 2-3 -214.8 -241.2 -11.1 -16.0 -7.0 -11.1
Tran 3-4 -231.6 -202.5 -3.9 -1.6 53.0 -15.7
Tran 4-5 -272.1 -221.5 -13.0 -3.4 -22.2 8.9
Note: Soluble reactive phosphorus (SRP), total nitrogen (TN), total phosphorus (TP)

Table 2-7. Net apparent riverine nutrient loss rates normalized to the area between transects for Wet and Dry seasons during the High
loading period (2004-2006). Negative numbers indicate uptake (losses)
NO3- SRP NH4+
HIGH Wet Dry Wet Dry Wet Dry
2004-2006 (mg/m2/d) (mg/m2/d) (mg/m2/d) (mg/m2/d) (mg/m2/d) (mg/m2/d)
Tran 1-2 -773. 0 257.2 -20.9 -15.7 -32.6 -114.4
Tran 2-3 -203.5 -426.0 -14.4 -0.8 0.8 2.0
Tran 3-4 -516.9 -525.0 -1.9 5.7 83.9 50.4
Tran 4-5 -456.7 -216.9 -14.1 -12.5 -47.3 -27.0
Note: Soluble reactive phosphorus (SRP)

Table 2-8. Percentage of incoming inorganic nutrient load lost between RIVERS transects 1 and 5
NO3- SRP NH4
Loading (%) (%) (%)
Low (1999-2001) 31 39 16
High (2004-2006) 31 25 21
Note: Soluble reactive phosphorus (SRP)









Methodological Precision

Despite the potential advantages offered by benthic flux chambers, such as covering a large

benthic surface area and allowing measurements under in situ conditions (Viollier et al., 2003),

many past chamber-based experiments have been limited in temporal resolution by

methodological precision. Methodological precision is a measure of the variability of a given

measurement introduced by the process of sampling, preservation, storage, and analysis of a

given analyte. Increased measurement variability can potentially result in dramatic variation

between actual (in situ) and measured concentrations of an analyte (Viollier et al., 2003). A

significant effort has therefore been made to increase methodological precision by utilizing in

situ analytical techniques, thereby decreasing artifacts introduced by sampling, preservation, and

storage (Viollier et al., 2003).

Chamber-based benthic NO3~ flUXeS are based on the rate calculated from multiple NO3-

concentration measurements over time in a chamber sealed to the benthic substrate. The greater

the number of measurements within a given incubation, the more robust the consumption rate

calculation will be. This makes in situ analysis especially important for short term chamber

experiments because precise measurements are necessary to resolve the slight changes in

concentration that occur within a sealed chamber over short periods of time (Figure 4-1).

However, despite its potential, in situ NO3~ analySis has not previously been coupled with a

chamber-based approach to evaluate short-term dynamics of NO3~ flUXeS. Some previous short-

term chamber experiments have instead relied on a limited number of samples to calculate

nutrient fluxes. For example, Sakamaki et al (2006) calculated nutrient fluxes over a two-hour

period from rates based on only two sample points. Increasing sample resolution within each

short time interval could dramatically increase measurement reliability and would provide a

means to evaluate the quality of short term flux measurements. Increasing methodological









and temperature. Therefore, no formal conclusions regarding the status of nutrient limitation can

be made from these data.

Map Units

Chass Sands (ChS)

Beginning at the main spring boil of the Chassahowitzka River and meandering

approximately 3 km toward the salt marsh, the Chass Sands (ChS) map unit accounts for 4.2% of

the area mapped during this study. The channel generally has a very slight slope (<2%), both

longitudinally and in cross section. The Chass Sands map unit is influenced by higher water

velocities compared to other map units, though velocities throughout the entire study area are

generally low and range from 0-0.5m/s (Frazer et al., 2001). The average water depth observed

in the Chass Sands is approximately 1.0 m and the channel bottom is derived from sand-

dominated parent materials with occasional outcroppings of limestone bedrock. Due to shallow

depths at low tide or when West winds dominate, there is frequent disturbance and mixing within

the landform by outboard motors. Common submerged aquatic vegetation (SAV) species include

Vallisneria amnericana (Tape grass), Najas guadalupensis (Southern Naiad), Hydrilla verticillata

(Hydrilla), and a variety of benthic algal species (Frazer et al., 2001).

Soil pH decreased from over 7 to below 4 following moist incubation in two horizons and

therefore indicating the presence of unbuffered sulfidic materials (Table 3-3, field pH vs.

incubation pH). Within the typical pedon OC, TN, and TP contents varied from 1-9 g/kg, 0.1-0.6

g/kg, and 54-98 mg/kg respectively (Table 3-3).

Subaqueous soils representative of the Chass Sands map unit were classified to the

subgroup level as Haplic Sulfaquents (Table 3-3, Table 3-4). The typical pedon had no

diagnostic horizons (order = Entisol), was permanently saturated (suborder = Aquent), and

contained sulfidic materials within 50cm of the soil surface (as evidenced by pH changes









environments. Low velocity environments included the Midden Flats, Riversides, and within the

Blue Crab map unit where mixing with estuarine OM sources occurs. Sands and Eine-sands were

generally characterized by high color value and dominated the composition of the Chass Sands

and the underlying C horizons of the Riversides map unit. Muck and mucky sand textures were

common throughout the Midden Flats and the upper horizons of the Riversides map units. Soil

conductivity ranged from 0.97-1 1.46 dS/m with a median of 2.6 dS/m. The highest conductivity

values were generally located in organic-rich surface horizons close to or inside the salt marsh

and upland/salt-marsh transition area. Bulk density ranged from 0. 1-1.8g/cm3 and differed

notably between map units (Figure 3-5d). Those pedons sampled from high energy

environments, namely the Chass Sands and Blue Crab, have much higher median bulk densities

than those from lower energy depositional environments. Observed mineral composition varied

from quartz-sand dominated in the upstream areas toward a carbonate/quartz sand mix within the

estuarine and Salt Marsh map units. Gravel-sized particles were not commonly observed in the

system and comprised less than 1% of the total soil contents analyzed.

Chemical properties

Field soil pH varied in response to texture and among map units, though remained within a

relatively narrow range of 6.9 to 8.1 through all sites and horizons sampled (Figure 3-5a).

Results from pH incubations indicated that reduced sulfides were present in many of the

subaqueous soils of the Chassahowitzka River and Estuary (Table 3-3, Figure 3-5b). However, in

the Midden Flats, though reduced sulfides were likely present, their presence was not indicated

by pH incubations. This most likely resulted from buffering by the presence of CaCO3 in the

form of shells. Reduced sulfides appeared to be most prevalent, or least-buffered by CaCO3, in

the Blue Crab map unit which resulted in a post-incubation pH decrease to less than 2. Values of

OC (range 1-209g/kg; median 28 g/kg), TN (range 0-17 g/kg; median 3 g/kg), and TP (range 51-









;. *


r?





.. i


i I
i /
UC!
P`
,i
~ia~ c


| Chassahowitzka River and Estuary


D 50 100 200
Figure 1-1. Overview and location of the Chassahowitzka Springshed and its river and estuary with respect to the state of Florida.
Imagery of the region indicates land-use and anthropogenic disturbance in the springshed and is composed of a mosaic of
true-color digital orthophotos made available by the Southwest Florida Water Management District (SWFWMD, 2007)









loading classes (method described below). Season was classified as either "Wet" or "Dry" based

on average seasonal variation of spring water temperature at Transect 1. Water temperatures are

higher during the wet season in Florida. Temperature ranged from 20.8-25.90C, was statistically

normally distributed, and had a mean value of 23.360C and a median of 23.420C. All samples

with a temperature equal to or greater than 23.40C were considered representative of the Wet

season while the remaining samples were classified as Dry. In almost all cases, the Wet season

included samples collected in the months of April through August, while the remainder of the

year was considered the Dry season.

One-way analysis of variance (ANOVA) was used to test for significant differences in

nutrient concentration between seasonal or loading classes, or for season:10ading class

interactions (Table 2-2). Interannual variability in nutrient concentration at the headspring was

compared with regional and local variations in precipitation and discharge using mean annual

data from both the RIVERS and COAST datasets. Relationships between regional environmental

variables and nutrient concentrations at the headspring were evaluated for significance using

linear regression statistical parameters.

River and Estuary: Calculation of Nutrient Loads

Annual nutrient loads at the headspring (Transect 1) were calculated as the product of

mean annual discharge and mean annual nutrient concentrations at the headspring. A substantial

increase in the load of N (~60% increase) and P (30% increase) was observed during a two year

Low loading period (April 2004-Feb 2006) relative to a two year High loading period (April

1999-Feb 2001) as highlighted in Table 2-3. These two distinct loading regimes provided the

opportunity to analyze a natural nutrient loading experiment where two distinct treatments (Low

and High regimes) of nutrient loading were maintained in the system, each for a period of two

years. The RIVERS data were chosen to analyze trends resulting from these treatments due to the










Quantify basic physical and chemical properties of subaqueous soils associated with each
map unit though the selection, sampling, and analysis of a typical pedon

Evaluate the selection of a typical pedon sampling location in a subaqueous soil
environment based on multiple field-based soil descriptions

Methods

Subaqueous Soil Reconnaissance

A total of 68 soil descriptions were made in the subaqueous and near-shore terrestrial

environment to gain an appreciation for the variability of soils along the Chassahowitzka River

and Estuary (Figure 3-3). During this exploratory phase, sampling tools included a piston corer,

Russian auger, Dutch auger, and vibra-corer to acquire soil samples in various substrates. At

each site a field description was completed that included the following parameters: GPS

coordinates (lat/long), horizon designation, horizon starting and ending depth, native vegetation,

parent material, landform, field texture, and soil color. Soil samples were collected at select sites

and analyzed for physical and chemical properties.

Delineating Subaqueous Soil Map Units

Exploratory and systematic transect-based subaqueous soil descriptions and aerial

photography were combined into a GIS interface to map the subaqueous soils of the

Chassahowitzka River and Estuary System. Following reconnaissance field work and soil

descriptions, subaqueous soil map units were delineated using photo-tone on aerial photographs

and a Im resolution Digital Orthoimagery Quarter Quadrangles (DOQQ) created in 2005 by the

United States Geological Survey (USGS). Subaqueous soil map units (Figure 3-4, Table 3-1)

were compared against bathymetry provided by the Southwest Florida Water Management

District (SWFWMD) to confirm photo-tone interpretations of depth and the overall distribution

of landforms. All landforms delineations took place at a scale of 1:1000 and all landform and

river/estuary channel study area boundaries were hand-digitized using ArcGIS 9.1 (ESRI, 2006).

















































b) y =69.9 -7.6*x












10 12 14 16 18 20 22 24
NOB Concentration (pM)


C~ty =84.5 -15.9*x
excluded outller
Incubation 3










10 12 14 16 18 20 22 24
NO: Concentration (pM)


y =146.1 -22.9*x







Excluded point
from Incubation 3


-100




O
200


v,-250
O

S-300
O
Z
W -350
O

-400


10 12 14 16 18 20 22 24
NO3-Concentration (CIM)


-2100
Z
0

-250


Figure 4-5. a) Conservative and b) non-conservative NO3~ losses and their relationship to NO3~
concentration. Incubation 6 is excluded due to an accidental chamber opening during
the incubation. Incubation 3 is considered an outlier for the equation calculated in
Figure a and c. However, incubation 3 also had the highest rate of SGD, which may
have modified the strong relationship between NO3~ COncentration and its rate of
uptake (or production). This relationship warrants further investigation in the future















LOAD HIGH LOAD HIGH LOAD LOW LOAD LOW
Season dry Season wet Season dry Season wet


200












5 -800


LOAD HIGH LOAD HIGH LOAD LOW LOAD LOW
Season dry Season wet Season dry Season wet















-I


Calculated Flux Rates

Figure 2-14. Rates of NO3~ losses as summarized by High and Low classes of load and Wet and
Dry classes of season


>r
U

E ~10
rs,
E
a
L~ ~20
C~


-30




-40


Calculated Flux Rates

Figure 2-15. Rates of soluble reactive phosphorus (SRP) losses summarized by High and Low
classes of nutrient loading and Wet and Dry classes of season









between the Earth's mineral crust and air or water. The presence of overlying water should not

be considered a boundary between soil and sediment, but a significant driver of the structure and

function of the benthic environment.

Subaqueous soil surveys have been created to map the distribution of soils and their

associated properties in the subaqueous environment. The subaqueous soil survey has emerged

as a useful method for mapping the distribution and properties of various environments in

estuarine and coastal regions. Subaqueous soil surveys have already been completed in diverse

estuarine environments along the coasts of Florida, Rhode Island, and Maryland (Bradley and

Stolt, 2002; Bradley and Stolt, 2003; Demas and Rabenhorst, 2001; Demas et al., 1996; Ellis,

2006; Fischler, 2006). Soil is studied in terms of its equilibrium condition with the environment.

Essentially, a soil map unit relates soil properties to soil forming factors over large areas. This

relationship is guided by the concept that soil forming factors alter parent material in a manner

reflective of the environmental drivers acting upon the soil.

The Chassahowitzka River and Estuary (Figure 3-1) is a stable environment (Figure 3-2)

that provides a number of contrasting soil properties and benthic landforms and is an area where

little is currently known regarding the spatial distribution of subaqueous soil properties. Also,

given recent anthropogenic impacts and the ecosystem management needs (Chapter 2), a

subaqueous soil survey in this area can support management and future research efforts aimed at

understanding biogeochemical cycling within the system. This mapping effort can also add to the

existing base of knowledge regarding the soils of the region (see Pilny et al., 1988).

Objectives

The obj ectives were:

*Map the spatial extent of distinct subaqueous soils and describe their associated
landforms and vegetation in the Chassahowitzka River and Estuary









Water quality monitoring along the Chassahowitzka River and Estuary has been conducted

since the late nineties and many interesting trends in biogeochemical change along the riverine-

estuarine gradient have been elucidated (Frazer et al., 2001). One of the most notable spatial

trends along the Chassahowitzka River is the dramatic decline in NO3~ COncentrations from the

headspring toward the estuary. However, the dominant environmental factors controlling the

decreasing NO3~ COncentrations have not been identified. Therefore, many important questions

regarding biogeochemical cycling still remain, including: "what is the role of subaqueous soils in

the NO3~ CyCling alOng the spring run and in the estuary"; "are subaqueous soils a dominant NO3

sink within the spring run and in the estuary?"; and "if so, which subaqueous soils play the

dominant role in nutrient cycling and what is their spatial distribution?

Obj ectives

The obj ectives of this research were: to quantify the spatial and temporal variability of

nutrient concentrations, loads, and distribution over seasonal and inter-annual timescales

(Chapter 2), to map the distribution and quantify the properties of subaqueous soils along a

freshwater-estuarine gradient (Chapter 3), and to develop and evaluate a novel method for the

high-resolution in-situ measurement of benthic nitrate fluxes and their environmental drivers

(Chapter 4). The overarching obj ective of this research was to characterize the large-scale

variability of nutrient source and cycling and evaluate the properties of subaqueous soils and

their influence on nutrient cycling on the Chassahowitzka River and Estuary.












Delineating Subaqueous Soil Map Units............... ...............64.
Typical Pedons ................... .. ...............65.
Laboratory Analytical Methods............... ...............66
Results and Discussion .............. ...............67....

Subaqueous Soils............... ........ ......... .. ............6
Physical and Chemical Soil Data Between Map Units .............. ....................6
Physical properties .............. ...............68....
Chemical properties............... ...............6
Map Units .................... ...............71.
Chass Sands (ChS) .............. ...............71....
Riversides (RvS) .............. ...............72....
Blue Crab (BIC) .............. ...............74....
M idden Flats (M dF) .............. ...............75....
Shell Bottom (ShB) .............. ...............76....
M ap Unit Name s ................. ............ ...............77. ....
Typical Pedon Map Unit Representation .............. ............. ........ .......7
Soil Taxonomy and Subaqueous Soils of a Riverine-Estuarine System .........................78
Summary ............ ..... .._ ...............79...


4 THE SIMULTANEOUS QUANTIFICATION OF SHORT-TERM BENTHIC
NITRATE REACTIONS AND DIFFUSE GROUNDWATER SEEPAGE ................... .......93


Introducti on ................. ...............93.................
Short Timescales .............. ...............93....
Methodological Precision ................. ...............95.................
Influence of Diffuse Groundwater Seepage ................. ................ ................96
In Situ Nutrient Analyses .............. ... ... .... ........ ............9
Conceptual Introduction to the Method Proposed by this Study ................. .....................98
M materials and Procedures .............. ...............99....
Environmental Data............... ...............100.
Method Assessment ................. ............... ........___..........10
Site Description: Chassahowitzka River ................. ...............101...............
Chamb er Depl oyment ............... .... .... .............. ...............102 ....
Benthic Flux and Biogeochemical Reaction Calculations .............. ..... .................10
Calculating SGD and SGD-Driven Influences on NO3- Additions and Losses ............104
Re sults ................ ...............105................
Diel Variation ................. .... ..... ... ............ ..... ..........10
Benthic Reactions and Environmental Variability ................. .... ......... .................1 06
NO3- Additions and Losses and Their Relationships to Environmental Parameters.....106
Submarine Groundwater Discharge .............. ...............107....
Data Interpretation ................. ...............107._._._.......
Discussion ........._.._.. .. ...... ._ ...............110.....
Comments and Recommendations ........._.._.. ...._... ...............111...


5 SYNTHESIS: BIOGEOCHEMICAL DYNAMICS OF SUBAQUEOUS SOILS IN
THE CHASSAHOWITZKA SPRING-FED RIVER AND ESTUARY ................... ...........123










Flindt, M.R., J.A. Pardal, A.I. Lillebo, I. Martins, and J.C. Marques. 1999. Nutrient cycling and
plant dynamics in estuaries: A brief review. Acta Oecologica-International Journal of
Ecology 20:237-248.

Frazer, T.K. 2000. Coastal nitrate assessment: Nutrient assimilation capacity of five gulf coast
rivers. Second annual proj ect summary. Southwest Florida Water Management District.
Surface Water Improvement and Management Program, Tampa, FL.

Frazer, T.K., M.V. Hoyer, S.K. Notestein, J.A. Hale, and D.E. Canfield. 2001. Physical,
chemical and vegetative characteristics of five gulf coast rivers. University Of Florida,
Gainesville.

Frazer, T.K., E.J. Philips, S.K. Notestein, and C. Jett. 2002. Nutrient limiting status of five gulf
coast rivers and their associated estuaries. Southwest Florida Water Management District.
Surface Water Improvement and Management Program, Tampa, FL.

Frazer, T.K., S.K. Notestein, M.V. Hoyer, J.A. Hale, D.E. Canfield, S.B. Blitch, and C. Bedee.
2003. Water quality characteristics of the nearshore Gulf Coast waters adj acent to Citrus,
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Management District, Tampa.

Galloway, J.N., J.D. Aber, J.W. Erisman, S.P. Seitzinger, R.W. Howarth, E.B. Cowling, and B.J.
Cosby. 2003. The nitrogen cascade. Bioscience 53:341-356.

Garrison, G.H., C.R. Glenn, and G.M. McMurtry. 2003. Measurement of submarine groundwater
discharge in Kahana Bay, O'ahu, Hawai'i. Limnology and Oceanography 48:920-928.

Glibert, P.M., J. Harrison, C. Heil, and S. Seitzinger. 2006. Escalating worldwide use of urea a
global change contributing to coastal eutrophication. Biogeochemistry 77:441-463.

Hanson, P.J., D.W. Evans, D.R. Colby, and V. S. Zdanowicz. 1993. Assessment of elemental
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Harrison, J.A., S.P. Seitzinger, A.F. Bouwman, N.F. Caraco, A.H.W. Beusen, and C.J.
Vorosmarty. 2005. Dissolved inorganic phosphorus export to the coastal zone: Results
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Hubertz, E.D., and L.B. Cahoon. 1999. Short-term variability of water quality parameters in two
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Insightful Corp. 2002. SPlus 6.1. Academic Site Edition. Release 1. Insightful Corp., Seattle,
WA.



















~c

i~.' 'i '
t 'L: C
~f .~rl~


1.1
r..


1.


't'Lr7s
h'


Figure A-2. Riversides soil core near on the lateral edge of Crab Creek









introduced here also allowed for an evaluation of relationships between SGD, tidal elevation,

light, temperature, water column elevation and NO3- additions and losses over multiple chamber

incubations over a diel time period. While previous benthic nutrient flux studies in estuarine

environments have not addressed SGD-driven biogeochemical reactions, in this Hield trial, SGD

was significantly related to conservative and non-conservative NO3~ lOsses. In fact, regardless of

marked diel variation in light, temperature, pH, and DO concentrations, both SGD and water

column NO3~ COncentrations were significantly related to NO3~ lOsses. While benthic NO3~

concentrations have been related to benthic NO3~ losses in a number of studies (Laursen and

Seitzinger, 2004; Seitzinger et al., 2006; Seitzinger, 1987), SGD has not been directly linked to

reactions at the benthic/water interface.

The potential role of SGD in altering observed benthic NO3- additions or losses may be

two-fold: 1) exfiltration of groundwater depleted in both NO3- and DO into the river and estuary

will result in dilution of surface water NO3~ COncentrations (conservative dilution) and 2)

incoming SGD may influence in-stream nutrient concentrations by providing reactants for the

chemical alteration of water column nutrient species via denitrifieation, anammox, or other NO3~

reduction reactions (non-conservative reactions). While NO3- reduction, denitrifieation, and the

influence of reduced compounds have been observed at the benthic/water interface in many

environments (see Bianchi, 2007), no study that I am aware of has evaluated how SGD modifies

these processes. Continued work and a larger study will be needed to test the hypothesis that

SGD acts as a significant driver of benthic NO3- reactions.

Although aquifer groundwater at the research site is known to have appreciable NO3~

concentrations in its limestone-dominated matrix, the sand and OM-dominated benthic substrate

provided a chemically reduced environment, indicating very low to non-existent concentrations































































Figure A-3. Blue Crab soil core and microscopic images for reference purposes










Estuarine areas subj ect to significant rates of SGD require a new approach, such as the one

presented, to quantify nutrient additions and losses at the benthic/water interface. In areas with

appreciable rates of SGD, studies based on assumptions of diffusive transport may dramatically

misrepresent nutrient additions or losses, given that porewater is actively flowing into the water

column. Previous chamber-based methods that did not provide a bladder for the infiltration of

SGD may alter benthic hydrology, and thus could potentially influence their reported flux

measurements. Past benthic flux studies carried out in areas with a high potential for SGD should

be interpreted with caution, given that the role of SGD may not have been accounted for.

The method described above will allow for detailed research into the various factors

affecting net NO3- reactions at the benthic/water interface. The method can be used to study the

role of plants, various substrates, sites with differing rates of SGD, or sites with different tidal

scale variability. Short-term variations resulting from pulse events such as elevated rainfall

events can also be evaluated for their impact on benthic NO3- cycling. Further, manipulative

experiments focused on determining the influence of nutrient additions, distinct light and

temperature regimes, or altered water column characteristics can be also carried out in situ and in

near real-time to experimentally determine their influence on benthic NO3~ COnSumption.

Although this method is specifically designed to quantify net NO3- and DO reactions, as in situ

analytical technology becomes available, other nutrient species, gases, or heavy metals can also

be evaluated over the short term and in response to SGD.

Comments and Recommendations

Although the reported methodology was evaluated in a sand-dominated environment,

chamber deployments in organic matter rich estuarine deposits should be feasible without any

modification. However, the two-source mixing model approach presented here requires two

distinct sources of chemical constituents (SGD porewater and the overlying water column) that










all processes affecting nutrient concentrations in the area between the upstream and downstream

transects.

Results

Seasonal and Interannual Variation

Total annual precipitation ranged from 102-172 cm and total monthly precipitation ranged

from 7-18 cm seasonally (Figures 2-6 and 2-7) during the study period. Air temperature varied

with precipitation within the year while the percentage of potential sunshine arriving at the land

surface was likely modified by cloud formation during the rainy season (Figure 2-8). At the

inter-annual timescale, natural variation resulted in two multi-year periods with distinct

precipitation, discharge, and salinity conditions.

Spring Source: Variation and Interrelationships

At the spring source (Transect 1), TN (P<0.001) and NO3- (P<0.001) concentrations were

significantly higher during under High loading conditions (RIVERS data; Table 2-2,).

Statistically significant interactions of season and load were also detected for NO3

concentrations (RIVERS data; Table 2-2). Concentrations of SRP and TP were not significantly

different between loading classes (RIVERS data; Table 2-2), suggesting a relatively consistent

concentration of P regardless of interannual variability in discharge rates.

Annual mean NO3~ COncentration (RIVERS) was significantly related to precipitation (r2

0.73; P < 0.05; Figure 2-10) and discharge (r2 = 0.60, P < 0.05; Figure 2-11). Total phosphorus

(COAST) and SRP (RIVERS) concentrations (e.g. Figure 2-12) were not significantly related to

either precipitation or discharge at the interannual timescale (r2 = 0.03, P = 0.98). However, total

phosphorus and SRP concentrations were significantly different between seasons (RIVERS data;

Table 2-2). Nitrate concentration at the headspring was not significantly different (P = 0.067) in

response to season.

































































Figure A-5. Midden Flats soil core and microscopic images for reference purposes


Midden Flats









increased from 1.74 to 1.87ppt between transects 1 and 5 while mean NO3~ COncentrations

decreased from 456.5 to 320.6Clg/L. The slight increase in salinity suggested minimal dilution

by high salinity estuarine waters. A two-source mixing model was used to calculate the amount

of dilution occurring between transects 1-5, given the mixing of waters from two different

sources: transect 1 (low salinity) and transect 20 (high salinity). The percentage of water from

transect 20 added between transects 1 and 5, Voo, was calculated as:

Voo = ((CT1 CT5)/( Cry-Creo))*100 (2-1)

where Voo = the percentage of water from transect 20 added between transects 1 and 5, Cr; = the

salinity at transect 1 (1.74ppt), CT5 = the concentration at transect 5 (1.87ppt), Creo =

concentration at transect 20 (15.6ppt). Voo accounted for approximately a 1% dilution of water

from the spring-run with waters from NO3- depleted estuarine waters. Therefore, the role of

dilution with estuarine waters was assumed to be minimal between transects 1-5.

Rates of spatially distributed net nutrient losses (including dilution) for unique combinations of

seasonal and loading classes were calculated as follows:

L=(Cd- 7) zz-,d (2-2)

where L = rate of spatially distributed net nutrient losses (mg/m2/day), Cd= nutrient

concentration of downstream transect (mg/L), C,, = nutrient concentration of upstream transect

(mg/L), D = discharge rate (L/day) and Azz-d = the river surface area (m2) between the upstream

and downstream transects of interest. The average nutrient concentrations and discharge rates for

each given season and load classification are provided in Tables 2-4 and 2-5 and the area

between transects is shown in Figure 2-5. The area between transects was quantified by

digitizing the stream channel between sampling transects and performing an area calculation

using ArcGIS 9. 1 (ESRI, 2005; Figure 2-5). Spatial rates of nutrient losses therefore represented









Given the context of increasing NO3~ COntamination of the Floridan Aquifer, the value of

coastal resources to the state of Florida, and their sensitivity to anthropogenic disturbance (e.g.

Chapter 2), the SGD-related processes reported herein may be quite important at the regional

scale. At this time it is impossible to state that these processes are occurring all along the coast.

However, research in Florida' s coastal environment has shown that SGD is occurring at

appreciable rates (Burnett et al., 2003; Martin et al., 2006; Swarzenski et al., 2007; Swarzenski et

al., 2006). Also, strong decreases in NO3~ COncentrations have been observed from source to sea

in many coastal spring-fed rivers (Frazer et al., 2006; Frazer et al., 2001). As SGD is a common

occurrence globally (Burnett et al., 2003), the interaction of SGD, benthic substrate, and

reactions at the benthic/water interface could have greater significance and is in need of more

detailed study.

Discussion

The method described above addresses the methodological challenges of providing high-

resolution, real-time, in situ measurements ofNO3~ COncentration, SGD, and environmental

parameters via a chamber-based approach. The method was capable of quantifying rates of

change of these variables via multiple incubations within the diel and tidal timescale. The data

provided sufficient resolution for the evaluation of relationships between the rates of change of

all measured variables and increased measurement precision by eliminating variability

introduced by sample preservation and storage. SGD was calculated concomitantly with NO3~

losses under in situ conditions with high temporal resolution for the first time. At the method

evaluation site, it appeared that SGD had the potential to be particularly important in influencing

rates of benthic NO3- reactions. This method has the potential to provide new and valuable

insight into the impact of SGD on benthic biogeochemistry in estuarine environments.










quantify SGD and net NO3~ flUXeS Simultaneously, thereby allowing an evaluation of the effects

of SGD driven mass transport on net NO3~ cycl S.

In Situ Nutrient Analyses

Another impediment to current chamber-based nutrient flux studies is the difficulty of

knowing whether an appropriate sampling interval was used for a given incubation until

analytical results are attained up to weeks following Hieldwork. High spatial and temporal

variability may mean that a sampling interval in one location, or at one time, that accurately

quantified benthic nutrient fluxes, may not be appropriate in another location or under different

environmental conditions. The ability to evaluate near real-time benthic NO3~ flUXeS in situ, can

offer tremendous advantages that would dramatically increase the efficiency of Hield-based

efforts. With near real-time in situ measurements, NO3~ flUXeS can be calculated in the field

between deployments and data integrity and consistency can be verified immediately.

Conceptual Introduction to the Method Proposed by this Study

The high spatial and temporal variability and complex hydrological processes

characteristic of estuarine environments pose unique challenges to those interested in

understanding benthic NO3- cycling. However, this understanding is increasingly important as

more NO3~ is transferred to the world's estuaries each year (Paerl 2006). A new methodological

approach is required to overcome current limitations in sampling frequency, methodological

precision, and the simultaneous quantifieation of SGD and NO3~ flUXeS. The method described in

this study provides a high temporal resolution, near real-time, in situ, chamber-based approach

for the quantifieation of net benthic NO3~ flUXeS and the variability of its environmental drivers.

The method takes advantage of readily available technology including a commercially available

in situ NO3- analyzer, peristaltic pump, sensors, and dataloggers (Figure 4-2) to increase the

resolution at which benthic NO3- cycling can be studied. Sensors to measure dissolved oxygen









hydrologic transport is as rapid as that found in the State of Florida. An understanding of nutrient

cycling is essential to evaluate potential future responses of the coastal environment to a

changing climate and increasing human population.

Based on approximately a decade of detailed monitoring of the concentration and spatial

distribution of nutrients in Florida' s coastal environment, coastal spring-fed rivers demonstrated

distinct trends in the assimilation and/or transport of nutrients (Frazer et al., 2006; Frazer et al.,

2001; Frazer et al., 2003). The upper reaches of some coastal rivers function as transport

conduits, maintaining a relatively constant nutrient concentration along their length until

eventually mixing with estuarine waters (Frazer, 2000; Frazer et al., 2006; Frazer et al., 2001;

Frazer et al., 2003). In contrast, the Chassahowitzka River is characterized by a marked and

consistent decrease in NO3- and SRP concentrations from the headspring to the estuary. Despite

the importance of the functional mechanisms which currently reduce NO3- and SRP loads to

estuarine environments, the capacity, variation, mechanisms, and controls of nutrient export and

processing within the spring-run remain relatively unstudied at a mechanistic level.

Unlike those for SRP and NH4+ N4+ data not shown), net NO3~ l0SSCS (normalized by

area) differed significantly in response to N load along the spring-run in the region of the upper

five transects. Spatially normalized (to a specific area) mean net loss rates measured within the

system were similar to -200 mg/m2/day for NO3-; however, mean NO3~ l0SSCS WeTO

approximately -500 mg/m2/day during High loading and Wet season conditions. These loss (i.e.

uptake) values are relatively rapid compared to benthic fluxes reported for a variety of estuarine

systems (Jickells and Rae, 1997). Elevated NO3~ TemOVal rates may partially result from the fact

that these calculations integrate all NO3~ TemOVal (or apparent removal) processes including

assimilation, denitrification, and any dilution that may potentially be occurring.










site, soil hydraulic conductivity may be lower as compared to the Chass Sands map unit.

Therefore, surface water induced advective exchange with the overlying water column is likely

not present and exchange across the soil/water interface is likely to be more dominated by

diffusion. On many occasions during the course of this research, much of the of the Riversides

map unit was covered almost completely with algal mats, dramatically reducing local water

velocities.

Blue Crab (BIC)

The Blue Crab (BIC) map unit is located within the subtidal freshwater/estuarine mixing

zone and covers 6.7% of the study area. Water column properties (salinity and total dissolved

solids) are most dynamic in response tidal variations in the Blue Crab map unit as it receives

direct inputs from both the estuary and the freshwater-dominated spring. The Blue Crab map unit

is similar to Chass Sands in flow characteristics, but Blue Crab has been additionally influenced

by the presence of increased salinities and the associated marine benthic community. Plant

species frequently encountered in this map unit consist of the salt-tolerant M~yriophyllum

spicatum, Najas guadalupensis, and a number of common algal species including Lyngbia sp.,

Spyrogyra, and Vaucheria sp.

The OC, TN, and TP contents varied from 8-49 g/kg, 0.6-3.9 g/kg, and 70.7-192.2 mg/kg,

respectively.

The typical pedon was classified as a Typic Sulfaquent and responded strongly to moist

incubation. Incubation resulted in pH decreases in two horizons to values less than 2 (Table 3-

3). Changes in soil pH following moist incubation are a strong indicator of the presence of

sulfidic materials. However, the absence of carbonates is also required to detect sulfidic

materials, as their presence will buffer any change in pH during moist incubation. The soil

suborder was Aquent (no diagnostic soil horizons and permanently saturated) and the strong














LOADING: LOW

-0 Precipitation
2.0 -- Discharge
S30



1.5 --1



LOADING: HIGH



O


1 0 v


Ap u u c e e p u u c e e
Figre -13 Ineranua vaiablit ofpreipiatin ad dschrgeplotedove th duatin o th
Lo 19-01 n ih(04206 odn eie.Ecodn regm
consste of tw-yea peiod romApri arc









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

MIULTI-SCALE ANALYSIS OF BENTHIC BIOGEOCHEMICAL PROPERTIES AND
PROCESSING INT SPRING-FED RIVER AND ESTUARY

By

Thomas John Saunders

December 2007

Chair: Mary E. Collins
Cochair: Thomas K. Frazer
Major: Soil and Water Science

Transparent freshwater rivers emerge from coastal spring boils along the karst northeastern

shore of the Gulf of Mexico and drain into the estuaries of Florida's coastal salt marsh. The

resulting physical and chemical gradients in water properties and benthic substrate grade from

freshwater/riverine to brackish/estuarine environments and provide an ideal environment for the

study of subaqueous soils and biogeochemical cycling. Multi-year (1997-2007) monitoring

programs have demonstrated that inorganic nutrients are consistently and rapidly utilized within

the Chassahowitzka River and Estuary, yet many questions remain as to the controls and

thresholds of nutrient attenuation processes. A meta-analysis of seasonal and interannual-scale

nutrient dynamics in the Chassahowitzka River and Estuary demonstrated that NO3~

concentration was significantly related to precipitation and discharge and that NO3-- uptake

within the river was consistently 30% of its load. Soluble reactive phosphorus (SRP), in

contrast, was not significantly related to precipitation or discharge, and its uptake remained

relatively consistent regardless of load, though SRP concentration varied significantly between

seasons. Spatially distributed nutrient flux estimates derived from mass-balance calculations

suggest that the benthic environment provided a strong control on nutrient cycling in this


























A 9 98 1 9 18 246 13

AC1 34 54 0 6 14 281 20

AC2 55 67 1 8 17 289 17
CA 66 66 0 1 14 50 4


Conductivity Texture n value Gravel Porosity D y

dS/m 0.7 % % g/cm3


AC 6 ND ND 12 ND ND ND
2Ab 13 136 2 12 8 234 28

2ACb 24 71 1 11 12 398 33
3Ab 51 192 4 49 14 652 45
3ACb 66 93 1 8 16 223 14


Table 3-3. Horizon designations, depths, and physical and chemical parameters of subaqueous soils of the Chassahowitzka River
and Estuary. OC = Organic Carbon, TN = Total Nitrogen, and TP = Total Phosphorus, ND = Not determined. Stoichiometric
ratios are molar. *C horizons described in Table 3-7. No typical pedon was sampled for the Shell Bottom (ShB) map unit as it


is frequently disturbed and mobile
Horizon Depth TP TN OC OC:TN OC:TP TN:TP Inuato Field pH Domlant OM


cm mg/kg g/kg g/kg Molar Molar Molar


>120 days


(moist) %


ChS: Chass Sands
6.88 7.15 5Y 6/1 2

3.8 7.55 2.5Y 4/1 1


1.205 sand

0.972 sand

1.474 sand
1.277 fine sand



ND muck
10.26 mucky sand
7.08 mucky sand
4.64 mucky sand
1.193 fine sand


<0.7 0.1 ND ND

<0.7 0.3 ND ND


7.47 2.5Y 4/1 2
7.7 2.5Y 6/1 0


<0.7 0.4 ND
<0.7 ND ND


RvS: Riversides
6.93 7.61 N 2/0 42
6.53 7.13 N 2/0 26
4.24 6.94 N 2/0 21
4.18 6.94 N 2/0 17
4.04 6.9 10YR 3/1 1


B/C: Blue Crab
7.44 7.62 10YR 2/1 2
7.4 7.48 10YR 3/1 2

3.1 7.54 10YR 3/4 2
1.95 7.36 10YR 2/2 10
1.98 7.32 10YR 3/1 2


MlldF: Mlidden Flats
7.18 7.19 N 2/0 15
7.55 7.31 N 2/0 9
7.58 7.06 N 2/0 13
7.46 6.86 N 2/0 21


On
Al
A2
SA3
A4


7 1014 17 209
27 2481 10 131
49 520 5 104
64 152 4 85
82 51 0 5


15 531 36
16 136 9
26 518 20
23 1443 62
20 235 12


>0.7 0.1
>0.7 0.1
>0.7 0.2
>0.7 0.5
<0.7 0.7


ND loamy sand
2.44 loamy sand

1.714 loamy sand

4.92 mucky sand
2.75 fine sand




11.46 mucky sand
2.25 mucky sand
7.65 mucky sand
10.24 mucky sand


>0.7 0.2
>0.7 0.5

>0.7 0.3
>0.7 0.2
<0.7 0.3



>0.7 ND
>0.7 ND
>0.7 ND
>0.7 ND


Al
A2
A/C1*
A/C2*


10.5 489 6 77
16.5 450 3 43
61.5 379 4 67
106.5 405 6 106


15 405 26
16 247 16
18 457 25
21 675 32










of coastal and terrestrial spring-fed systems in Florida. Land-use in the springshed (Table 2-1,

Figure 2-3) includes low (1,469 hectares), medium (768 hectares), and high-density (88.6

hectares) residential areas, multiple golf-courses (334 hectares), and pasture and farm lands

(2,337 hectares). Each of these land-uses is known to contribute N and/or P to the terrestrial

landscape via fertilization, animal wastes, and surface water runoff from impervious surfaces

(Jones et al., 1997).

The Chassahowitzka, like many other coastal spring-fed rivers, is currently undergoing an

increase in NO3~ COncentrations as a result of anthropogenic land-use and NO3~ leading (Jones et

al., 1997; Scott et al., 2004). Elevated NO3~ COncentrations in many of Florida's springs result

from a variety of anthropogenically introduced organic and inorganic N sources (Jones et al.,

1997; Katz, 2004; Katz et al., 1999a; Katz et al., 1999b; Katz et al., 2001a; Katz et al., 2001c).

Stable NO3--N isotopic data from Chassahowitzka River spring complex specifically implicated

inorganic N sources likely derived from fertilizers (Jones et al., 1997). The average water

residence time within the aquifer prior to spring discharge has been estimated as 5-35 years

based on geochemical studies and groundwater tracers in a variety of Floridian spring systems

(Jones et al., 1997; Katz et al., 2001c; Toth and Katz, 2006).

Methods

Data Sources

Quarterly and monthly surface water monitoring programs (Frazer et al., 2006; Frazer et

al., 2001; Frazer et al., 2003) were conducted over a ten-year period, providing an opportunity to

evaluate seasonal and interannual variation in the concentration, load, distribution, processing,

and fate of nutrients in the Chassahowitzka River and Estuary. The datasets utilized for both

qualitative mapping and quantitative analyses are listed in Table 2-1. The methods utilized in

creating these datasets are covered in detail by each of the authors or data sources. All spatial









evaluation of their sampling locations for the presence of SGD. As SGD is likely an active

component in many estuarine environments (Burnett et al., 2006) past diffusive flux estimates in

areas where advective SGD exists could dramatically misrepresent actual fluxes by a margin

determined by the rate and reactivity of SGD.

Chamber designs are currently available to quantify either reaction or diffusion-based

benthic nutrient fluxes (Tengberg et al., 2004) or mass hydrologic fluxes transported across the

benthic/water interface by SGD (Burnett et al., 2006; Garrison et al., 2003). However, no

method has been presented to quantify SGD-driven nutrient reactions and net nutrient fluxes (i.e.

SGD-driven mass nutrient fluxes plus/minus nutrient reactions that directly result from SGD

discharge) under in situ conditions. Many SGD-based nutrient flux estimates multiply a benthic

porewater nutrient concentration by an associated SGD rate to quantify mass nutrient fluxes

(Slomp and Van Cappellen, 2004; Swarzenski et al., 2006). Others multiply chamber water

nutrient concentrations by the SGD rate after allowing SGD to completely exchange the

overlying water within the chamber (Garrison et al., 2003), likely altering the chemistry of the

overlying water column and thus its interaction with benthic substrate. Neither method, however,

considers that denitrification or anammox reactions may also be directly driven by SGD,

stimulating a gaseous loss of N from the estuary and decreasing the net delivery of N to the

estuary. Reactions stimulating a net loss of N are likely to occur given the mixing of reduced

porewaters benthicc substrate) and oxidized (water column) surface waters driven by SGD in

estuarine environments. Microbial communities are known to take advantage of the gradient of

electron donors and acceptors to carry out their metabolic processes. SGD driven N losses, if

active, could significantly decrease the net impact of SGD on NH4' Or NO3~ COncentrations in the

estuarine environment. Once modified correctly, a chamber-based design can provide a means to








35 b)


S30
25

1n 0


S500
S400
-r300


I UU
1998 1999 2000 2001 2002 2003 2004 2005 2006


1998 1999 2000 2001 2002 2003 2004 2005 2006
d)


S20

v,12
S10
8)


600


Z 00


200
100


1998 1999 2000 2001 2003 2004 2005 2006


1998 1999 2000 2001 2003 2004 2005


Figure 2-9. Boxplots of interannual timescale variation in a) total nitrogen (COAST), b) total phosphorus (COAST), c) NO3~
(RIVERS), and d) soluble reactive phosphorus (RIVERS). Outliers, indicated by points outside of the boxplots, are shown
for reference to local variability. Data from 2002 were not available for the RIVERS dataset


lilil'i


'II;


113


-Illt


111










NO3- retention. Differences in NO3~ prOcessing rates are likely related to both residence time and

alterations of hydrologic flowpaths as a function of variability in hydrologic inputs and outputs

(Seitzinger et al., 2006). As coastal systems are generally sensitive to increases in NO3~

concentrations, a transfer of NO3- further into nutrient depleted waters could present a significant

management problem in the future.

Downstream transfers (to Transect 10) of significantly elevated SRP concentrations did not

result in response to the High loading period. However, seasonal variation of SRP concentrations

at Transect 10 was significant. These results suggest that seasonally-mediated biological

controls such as primary production, microbial activity, and biomass production, likely varying

with water temperature and insolation, control P uptake on the Chassahowitzka. Notestein et al.

(2003) suggested that periphyton primary productivity was most strongly limited by P in this

system. Phosphorus has also been suggested as a limiting nutrient in other coastal spring-fed

rivers of Florida (Frazer et al., 2002). Therefore, it is likely that increased SRP loads are utilized

over short distances and are in high demand along the Chassahowitzka River, especially during

periods of elevated primary productivity.

Conclusions

This study focused on the source, spatial distribution, and controls on dissolved inorganic

N and P in the Chassahowitzka River and Estuary system. Analysis of seasonal and interannual

timescale nutrient concentration data on the Chassahowitzka River highlight the general

conclusion that temporal variation in source, processing, and fate of nutrients is significant and

should be studied, tested, and integrated into management plans dealing with Florida's coastal

environment. The specific conclusions of this analysis were as follows:

*Nitrate concentrations at the headspring were significantly related to annual precipitation.
It is likely that locally-derived NO3~ WAS transferred to the headspring from the











Table B2 continued


Surface
Solar
Irradiance
(pIS/cm2/S)
1520
1520
1520
1520
1431
1351
1351
1350
1218
1161
1021
1133
1000
834
767.9
867
960
1014
1039
1013
1013
962
929
928
772.1
760


Subsurface
Solar
Irradiance
(pS/cm2/S)
1104
1128
1106
1073
1064
1036
1018
987
928
822
794.8
817
730.2
602.9
518.2
584.4
663.7
760.5
788
789.4
758.1
700.2
650.3
604.9
589
551.6


Panel
Temperature
o"C)
37.5
38
37.33
37.09
37.5
38.08
37.7
37.18
37.05
36.42
36.03
35.68
35.17
34.05
32.92
31.96
32.18
33.35
33.63
33.76
33.71
33.82
34.12
33.55
33.09
32.39


Red ox
Probe 1


-183.4
-184.5
-183.9
-179.7
-183.7
-184.4
-182.8
-183.3
-178.6
-181.7
-173.5
-168.5
-165.6
-163.2
-158.8
-159.5
-30.24
-42.76
-101.5
-130
-143.9
-150.7
-160.7
-162.9
-165.1
-166.5


Redox
Probe 2


-67.88
-68.66
-67.41
-65.34
-67.91
-66.25
-61.34
-58.04
-59.04
-57.5
-62.81
-61.13
-59.98
-55.84
-56.31
-55.09
-117.3
-125.6
-125.4
-125.1
-125
-124.7
-125
-124.1
-121.6
-121.3


Redox
Probe 3

-122
-122.2
-121.9
-121.1
-123.2
-124.2
-1242.7
-122.3

-121.7
-124.9
-127
-123.1
-121.8
-119.9
-119.6
-120.3
-112.9
-127.7
-134.9
-136.6
-136.7
-136.9
-139.2
-137.2
-137.3
-137


Redox
Probe 4


-34.39
-37.05
-37.68
-36.44
-38.96
-40.93
-39.31
-39.54
-40.44
-44.86
-45.23
-41.64
-39.96
-38.1
-39.21
-41.75
-132.7
-143.4
-147.7
-149.2
-149.7
-148.5
-145.9
-142.4
-140
-137.8


Date and Time


4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07


15:45
15:50
15:55
16:00
16:05
16:10
16:15
16:20
16:25
16:30
16:35
16:40
16:45
16:50
16:55
17:00
17:05
17:10
17:15
17:20
17:25
17:30
17:35
17:40
17:45
17:50









CHAPTER 2
SEASONAL AND INTERANNUAL DYNAMICS INT THE SOURCE, CYCLING, AND FATE
OF NUTRIENTS INT A COASTAL SPRING-FED RIVER AND ESTUARY

Introduction

Estuaries are characterized by diverse physical and chemical properties, high rates of

biological productivity, and are increasingly impacted by anthropogenic activities (Flindt et al.,

1999; Paerl, 2006; Wall, 2004). In most estuaries, including those of Florida, nitrogen and

phosphorus (N and P) are often important limiting factors of primary productivity (Bricker et al.,

2003; Frazer et al., 2002; Notestein et al., 2003; Pinckney et al., 2001). Human activity has

increasingly altered N and P inputs to many estuarine systems (Bowen and Valiela, 2001;

Nedwell et al., 1999; Paerl, 2006), increased inputs of trace metals (Hanson et al., 1993; Trimble

et al., 1999), and introduced biological contaminants (Mallin et al., 2000). Given the sensitivity,

productivity, and global importance of estuaries, understanding and managing human alterations

of estuarine resources has become one of the most important natural resource management

priorities (Pinckney et al., 2001).

The amount of N available at the global scale has dramatically increased through industrial

N-fixation, cultivation of leguminous crops, and fossil fuel combustion, thereby altering exports

of dissolved inorganic nitrogen (DIN) to coastal regions (Glibert et al., 2006; Seitzinger et al.,

2006; Seitzinger et al., 2005; Seitzinger et al., 2002). Delivery of dissolved inorganic phosphorus

(DIP) to estuaries have also increased globally due to fertilizer application, dairy wastes, and

wastewater discharges (Harrison et al., 2005). However, terrestrial retention of DIP is often

much greater when compared to that of DIN, and natural weathering sources are often significant

(Harrison et al., 2005; Seitzinger et al., 2005). Excess nutrient loading to estuaries has in many

cases resulted in cultural eutrophication, algal blooms, and associated negative impacts on the

health and ecological function of estuarine environments (Bowen and Valiela, 2001; Nedwell et
























































Figure A-4. Blue Crab soil core with a large krotovina. Krotovina were relatively common in the
Blue Crab map unit




















E
N1200
E

E




4 00

O





Apr 24207-Ap 507


-- Water Column Helght
-# Salinity


80
E
S75


C70


65





S55


3 5


3 4


33 3

32

32 1



30


29







450


400 ~


350


300



2500



150


Apr 24 2007 Apr 25 2007


-0 TemperatureCP 1


H22

7 8 1


70 618

o
74
04

72


7 0 10


Apr 24 2007 -Apr 25 2007


Apr 24 2007 Apr 25 2007


Figure 4-3. Diel variation in a) solar irradiance, b) mean water column height, c) temperature,

and d) NO3~ COncentration averaged by incubation period. An in situ incubation was

conducted during each of these unique combinations of conditions. The x-axis

represents the midpoint of the incubation period, staring at 8PM Eastern Standard

Time, and therefore does not extend across the entire temporal range



























118










All dataloggers were time-synchronized prior to deployment and set to record data at 5-

minute intervals, with the exception of the YSI 9600 NO3~ analyZeT, Which logged at 30 minute

intervals. All sonde probes were calibrated hours prior to deployment with the exception of DO,

which was calibrated just prior to deployment after allowing at least 30 minutes for the DO probe

to become polarized. All chemical reagents in the YSI 9600 were supplied by YSI, with the

exception of the NO3~ Standard, which was purchased from Fisher Scientific. Three separate

subsamples of the final mixed standard reagent were analyzed by a Florida DEP-certified

laboratory (Dawn Lucas, University of Florida) and the mean of three values was determined to

be 0.290mg/L. The standard solution was used to continuously calibrate the YSI 9600 in situ at

two hour intervals using its native automated program throughout the experiment. A standard

YSI pre-deployment check was conducted immediately before deployment and no problems or

issues were detected.

Method Assessment

Site Description: Chassahowitzka River

Florida' s Gulf Coast is tidally influenced, underlain by a large karst aquifer, and covered

with a diverse assemblage of benthic substrates. Multiyear trends of increasing NO3~

concentrations in coastal springs result from elevated terrestrial anthropogenic deposition of N

and its transfer though the karst Floridan Aquifer (Frazer, 2000; Frazer et al., 2001; Frazer et al.,

2003; Jones et al., 1997; Katz et al., 2001b; Scott et al., 2004). Coastal spring-fed rivers draining

the Floridan Aquifer have varying capacities to "mitigate" NO3~ l0ads along the length of their

runs, and therefore contain distinct capacities to reduce N-loading to sensitive coastal ecosystems

(Frazer, 2000; Frazer et al., 2001; Frazer et al., 2003). However, at present, the mechanisms

behind the observed decreases in NO3 COncentrations are not well understood.










analyze NO3~ USing the well known cadmium-reduction method (Strickland et al., 1972). An

accuracy of +5% or 0.01mg/L and a precision of 0.002mg/L NO3--N were reported by YSI when

using its protocols for sample analysis and post-processing. Those protocols were followed

during this study and the accuracy and precision were confirmed under laboratory conditions

prior to deployment. The other end of the flow-through cell was fitted with a rubber stopper

(#11) drilled to accommodate a YSI 6000 series multi-probe sonde. Variables monitored using

the datalogging multiprobe sonde included temperature, conductivity, salinity, pH, and DO.

Fluid flow across all probes was maintained throughout the experiment via the peristaltic pump

which ran throughout the experiment.

Environmental Data

Tidal variation was measured using a datalogging pressure transducer ("Mini-Troll" by In-

Situ Inc; Ft. Collins, CO). The pressure transducer was installed in an acrylic well to reduce any

variability due to water velocity. The well was submerged in the water column (but not into the

benthic substrate) and secured to a rod that had been firmly embedded in the channel bottom.

Photosynthetically active radiation (PAR) measurements were made using two Li-COR Quantum

Sensors (Li-COR; Lincoln, NE), one each for above and below the water surface (LI-190 and LI-

192, respectively). Both light sensors were connected to millivolt adaptors (Li-COR part number

2291 and part number 2290 for surface and subsurface sensors, respectively) and wired to a

CR1000 datalogger (Campbell Scientific; Logan, Utah). Four platinum-tipped redox electrodes

were installed in the chamber so as to contact the upper 1-2 cm of the benthic surface and were

connected to the CR1000 datalogger along with a calomel electrode that was submerged in the

water column. The CR1000 datalogger was programmed to measure sensor voltages once per

second, correct voltages to a standard hydrogen electrode, and calculate and store averages and

standard deviations at 5 and 30 minute intervals.










APPENDIX A
SUPPORTING SOIL PHOTOS AND MINERALOGICAL ANALYSES


Riversides


I .i; .
'P
la4~! iYr.. .

Figure A-i. Riversides soil core and microscopic images for reference purposes


































Leen ,1 '
Chsaoizk ie ndEtayC




< isall ornthrk valw andEsua


SGOILF GCOIRSES
RESICEK LAL HIGH DENSITY
SRESI CE K L MED CE NSITY2->5 DWELOLING U NE 7 --
SGCROLArNDAND~PASTURELANrD 0I 1 2 4 6 8 10
SRESI CE K1AL LOWDENS TY<~2 DWELLING UNITS *s


Figure 2-3. Land-uses (2005) in the Chassahowitzka Springshed that are likely to directly cause elevated NO3~ COncentrations into the
Floridan Aquifer. Data modified from SWFWMD (2006)






































Figure A-17. Scanning electron microscope image of framboidal pyrite taken from the sample in
Figure A-9

















422.5
401.9
393.8
374.4
355.0
346.3
381.3
441.9
451.3
473.8
450.6
452.5
420.0
424.4
420.0
243.1
248.1
246.9
252.5
240.6
230.0
220.6
211.9
203.1
215.0
210.6
196.3
186.9
178.8
173.8
170.6


25.6
25.4
25.6
25.3
25.0
24.8
24.6
24.2
24.1
24.2
24.2
23.8
23.3
23.0
22.8
22.6
22.6
22.7
22.7
22.7
22.6
22.5
22.6
22.5
22.5
22.5
22.4
22.4
22.4
22.4
22.5


Table B3. Thirty minute dataset including raw NOsT data


Total
Water Specific
Temperature Dissolved
el ovation Conductivity


'0"'


Surface Subsurface
Solar Solar
pH
Irradiance Irradiance
(pS/cm Is) (pS/cm Is)
8.0 150.6 -138.7
8.0 90.6 -139.0
8.0 159.1 -135.6
8.0 220.3 -136.8
8.0 238.0 -135.9
8.0 241.5 -142.5
8.0 235.1 -143.2
7.8 80.9 -145.0
7.7 -78.2 -145.2
7.7 98.6 -144.6
7.6 215.5 -145.1
7.6 182.9 -143.9
7.6 151.9 -140.7
7.6 165.4 -149.9
7.6 151.0 -154.8
7.3 118.0 -132.6
7.2 151.1 -106.5
7.2 -79.0 -167.9
7.2 -111.6 -166.8
7.2 -124.3 -165.1
7.1 -122.8 -164.1
7.1 -119.6 -164.9
7.1 -123.9 -166.6
7.1 -108.3 -169.3
7.1 -123.6 -168.1
7.1 -137.8 -166.3
7.1 -133.7 -165.1
7.1 -144.9 -167.9
7.1 -140.3 -170.1
7.1 -125.4 -167.8
7.1 -131.4 -162.1


DO
Salinity
Saturation
(ppt)
(%)
3.6 84.4
3.4 79.9
3.3 78.5
3.3 74.3
3.3 70.0
3.3 68.0
3.3 74.7
2.9 85.7
2.9 87.3
3.0 91.9
3.0 87.4
3.0 87.1
3.0 80.1
3.0 80.5
3.0 79.4
2.9 45.7
2.9 46.7
2.9 46.5
2.9 47.6
2.9 45.3
2.9 43.2
2.9 41.4
2.9 39.8
2.9 38.2
3.2 40.5
3.2 39.7
3.2 36.8
3.1 35.1
3.1 33.6
3.1 32.6
3.1 32.0


Flux Nitrate DO
Class (p M) (pM)


Time and Date


4/24/2007 17:30
4/24/2007 18:00
4/24/2007 18:30
4/24/2007 19:00
4/24/2007 19:30
4/24/2007 20:00
4/24/2007 20:30
4/24/2007 21:00
4/24/2007 21:30
4/24/2007 22:00
4/24/2007 22:30
4/24/2007 23:00
4/24/2007 23:30
4/25/2007 0:00
4/25/2007 0:30
4/25/2007 1:00
4/25/2007 1:30
4/25/2007 2:00
4/25/2007 2:30
4/25/2007 3:00
4/25/2007 3:30
4/25/2007 4:00
4/25/2007 4:30
4/25/2007 5:00
4/25/2007 5:30
4/25/2007 6:00
4/25/2007 6:30
4/25/2007 7:00
4/25/2007 7:30
4/25/2007 8:00
4/25/2007 8:30


(cm)
71.1
71.6
72.9
75.3
77.2
79.4
81.4
83.1
83.9
83.5
82.2
80.4
78.5
76.3
73.6
70.9
68.3
65.8
63.4
61.3
59.3
58.0
56.8
55.5
55.4
54.7
54.3
53.8
53.6
53.7
53.3


E


Solids
(ms/cm)
(g/L)
6.7 4.3
6.3 4.1
6.2 4.0
6.1 4.0
6.1 4.0
6.1 4.0
6.1 4.0
5.3 3.5
5.3 3.5
5.5 3.6
5.5 3.6
5.5 3.6
5.5 3.6
5.5 3.6
5.5 3.6
5.4 3.5
5.4 3.5
5.4 3.5
5.4 3.5
5.4 3.5
5.4 3.5
5.4 3.5
5.4 3.5
5.3 3.5
5.9 3.8
5.9 3.9
5.8 3.8
5.8 3.8
5.8 3.8
5.8 3.7
5.7 3.7


RIVER
RIVER
1
1
1
1
1
RIVER
RIVER
2
2
2
2
2
2
RIVER
RIVER
NA
3
3
3
3
3
RIVER
RIVER
4
4
4
4
4
4


21.1
21.2
15.1
14.4
NA
13.2
13.0
19.9
20.5
12.1
11.4
11.2
NA
10.6
10.2
27.5
30.5
26.5
24.6
23.8
NA
22.8
21.8
21.3
28.3
26.9
26.1
NA
23.9
21.7
21.2










Scott, T.M., G.H. Means, R.P. Meegan, R.C. Means, S.B. Upchurch, R.E. Copeland, J. Jones, T.
Roberts, and A. Willet. 2004. Springs of Florida. Florida Geological survey Bulletin No.
66. Florida Geological Survey, Tallahassee, Florida.

Seitzinger, S., J.A. Harrison, J.K. Bohlke, A.F. Bouwman, R. Lowrance, B. Peterson, C. Tobias,
and G. Van Drecht. 2006. Denitrification across landscapes and waterscapes: A synthesis.
Ecological Applications 16:2064-2090.

Seitzinger, S.P., J.A. Harrison, E. Dumont, A.H.W. Beusen, and A.F. Bouwman. 2005. Sources
and delivery of carbon, nitrogen, and phosphorus to the coastal zone: An overview of
global nutrient export from watersheds (NEWS) models and their application. Global
Biogeochemical Cycles 19.

Seitzinger, S.P., C. Kroeze, A.F. Bouwman, N. Caraco, F. Dentener, and R.V. Styles. 2002.
Global patterns of dissolved inorganic and particulate nitrogen inputs to coastal systems:
Recent conditions and future proj sections. Estuaries 25:640-655.

Seitzinger, S.P. 1987. Nitrogen Biogeochemistry in an Unpolluted Estuary the Importance of
Benthic Denitrification. Marine Ecology-Progress Series 41:177-186.

Slomp, C.P., and P. Van Cappellen. 2004. Nutrient inputs to the coastal ocean through submarine
groundwater discharge: controls and potential impact. Journal of Hydrology 295:64-86.

Strickland, J.D., and T.R. Parsons. 1972. A practical handbook of seawater analysis Bulletin
Fisheries Board of Canada.

Swarzenski, P.W., W.H. Orem, B.F. McPherson, M. Baskaran, and Y. Wan. 2006.
Biogeochemical transport in the Loxahatchee River estuary, Florida: The role of submarine
groundwater discharge. Marine Chemistry 101:248-265.

SWFWMD. 2007. Southwest Florida Water Management District digital orthophotos. Accessed
online: http://ftp.swfwmd. state.fl.us/pub/gisdata/Imagery/2006RGB/. March, 2007.

SWFWMD. 2006. Southwest Florida Water Management District land-use data. Accessed
online at: http://www.swfwmd. state.fl.us/data/gi s/layer_1ibrary/category/physical_dense.
December, 2006.

Tengberg, A., H. Stahl, G. Gust, V. Muller, U. Airing, H. Andersson, and P.O.J. Hall. 2004.
Intercalibration of benthic flux chambers I. Accuracy of flux measurements and influence
of chamber hydrodynamics. Progress in Oceanography 60: 1-28.

Tengberg, A., P.O.J. Hall, U. Andersson, B. Linden, O. Styrenius, G. Boland, F. de Bovee, B.
Carlsson, S. Ceradini, A. Devol, G. Duineveld, J.U. Friemann, R.N. Glud, A. Khripounoff,
J. Leather, P. Linke, L. Lund-Hansen, G. Rowe, P. Santschi, P. de Wilde, and U. Witte.
2005. Intercalibration of benthic flux chambers II. Hydrodynamic characterization and flux
comparisons of 14 different designs. Marine Chemistry 94: 147-173.









































02.5 5 10


I I I ~jlo~mete~s


Chassahowitzka River Spring shed


0 50 100


400


Figure 2-1. Floridan Aquifer Vulnerability classification carried out by the FDEP-FGS (Arthur et
al., 2006). The Chassahowitzka Springshed is just one area in Florida where the
aquifer is particularly vulnerable to terrestrial anthropogenic disturbances


L~eg en d V
Ch assahowitzka S pri ngshed
Floridan Aquifer Vu~lnerabFility
More- Vulnerable
Vulnerable
SLess Vulnerable











Table B2 continued


Surface
Solar
Irradiance
(pIS/cm2/S)
1133
1336
1431
1213
1078
1606
1096
775.8
1112
1222
1571
1468
628.4
1473
1553
1082
1918
2038
2020
2065
2088
2036
1532
1906
1985
1988
1895
1818
1804
1876
1808
1857
1857
1857
1858
1844
1857
1845
1745
1803
1770
1348
1688
1601
1470


Subsurface
Solar
Irradiance
(pS/cm2/S)
805
985
1048
903
747.6
1103
821
517.1
768.5
864
1116
1098
447.9
1024
1040
732.3
1378
1550
1441
1472
1451
1527
1102
1282
1359
1211
1340
1249
1272
1324
1260
1282
1313
1307
1352
1066
503.5
1247
1256
1294
1290
986
1233
1183
1089


Panel
Temperature
o"C)
37.21
36.28
36.3
36.46
35.51
36.43
36.47
35.14
35.53
35.27
37.5
38.4
35.9
34.62
35.8
35.28
35.63
38.83
39.88
40.27
40.83
40.84
40.39
40.01
40.01
40.07
40.61
40.16
38.74
38.78
38.02
37.26
36.89
36.52
36.97
37.36
38.06
38.62
38.93
39.04
39.4
37.72
37.51
37.89
37.62


Red ox
Probe 1

-175.8
-175.5

-173.7
-172.6
-172.1
-172.2
-171.8
-170.5
-168.5
-172.8
-176
-176.9
-173.2
-168.3
-170.6
-170.7
-170.5
-179.4
-178.3
-178.1
-178.2
-178.8
-179.2
-178.9
-179
-180.5
-181.6
-183
-181.7
-183.1
-183.1
-183.4
-183.6
-183.6
-184.9
-184.5
-185.3
-184.8
-185.8
-184.9
-185.4
-184
-185.8
-186.3
-185.2


Redox
Probe 2

-136.5
-136.3
-136.2

-134.3
-133
-131.7
-130
-128.2
-126.2
-123.1
-122.7
-124
-121
-118.2
-119.7
-117.5
-114.8
-115.4
-115.2
-115
-116
-115.7
-113.8
-112.2
-111.1
-111.3
-111.6
-115
-116.4
-119.4
-118.7
-119.2
-118.9
-118.7
-120
-121.2
-122
-119.9
-123.8
-122.2
-121.2
-122.5
-119.9
-113
-66.17


Redox
Probe 3


-123.7
-122.4
-120.1
-118.2
-117.8
-117.9
-117.9
-117.9
-117.6
-118.9
-120.6
-121
-118.8
-117.1
-120.8
-124.6
-123.2
-124.4
-123.3
-122.4
-126.9
-124
-122.2
-122.5
-123.9
-128.4
-127.4
-126.5
-124.8
-125.4
-125.1
-124.8
-124.1
-124
-124.9
-125.7
-126.6
-126.8
-127.5
-127.2
-127.7
-125
-124.3
-124.9
-124.4


Redox
Probe 4


-143.7
-138.7
-138.5
-136.5
-134.3
-133.4
-127.2
-123.7
-122
-120.4
-119.5
-118.6
-114.9
-112.1
-109.5
-106.8
-104.9
-106.7
-104.5
-104.3
-103.1
-102.8
-100.5
-96.9
-94.7
-96.4
-95.3
-99.4
-103.1
-105.8
-107.6
-108.2
-111.8
-114.2
-118.2
-119.2
-123.6
-124.8
-129.7
-128.3
-130.5
-122.3
-134.1
-116.4
-30.99


Date and Time


4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07
4/25/07


12:00
12:05
12:10
12:15
12:20
12:25
12:30
12:35
12:40
12:45
12:50
12:55
13:00
13:05
13:10
13:15
13:20
13:25
13:30
13:35
13:40
13:45
13:50
13:55
14:00
14:05
14:10
14:15
14:20
14:25
14:30
14:35
14:40
14:45
14:50
14:55
15:00
15:05
15:10
15:15
15:20
15:25
15:30
15:35
15:40









rivers to climatic variation should be taken into account when considering issues related to NO3~

management in the terrestrial system.

The concentration of SRP was not significantly different between interannual loading

classes, nor was it significantly correlated to precipitation or discharge. This suggests that SRP

concentration remains relatively constant regardless of environmental variation. Therefore,

variation in the mass load of SRP to the Chassahowitzka is determined by variation in spring

discharge. In other words, as spring discharge increased, SRP concentration remained the same,

while SRP mass load increased in proportion to river discharge. Mass load is the product of

discharge and concentration. Therefore, the mass load of NO3~ inCreaSed multiplicatively due to

the fact that NO3~ COncentrations continued to increase even as discharge volume increased. Both

SRP and NO3- need to be considered individually when evaluating the influences of temporal

climatic variation on nutrient loading to spring-fed coastal rivers.

Spring-Run Nutrient Dynamics

Human-climate interactions have been linked to the productivity, trophic status, and

anoxic/hypoxic events in many estuaries around the world (Jickells, 2005; Mulholland et al.,

1997; Paerl, 2006; Pinckney et al., 2001). An evaluation of the effects of climate change in

Florida and the Gulf of Mexico forecasted increased precipitation rates in the region of Florida' s

Springs Coast (Mulholland et al., 1997), thereby potentially exacerbating the nutrient loading to

Florida' s coastal ecosystems. Interactions between atmospheric N deposition (Fisher and

Oppenheimer, 1991; Paerl et al., 2002; Whitall et al., 2003; Winchester and Fu, 1992;

Winchester et al., 1995), land-use, increasing precipitation, and spring discharge rates can

potentially multiply N loading to coastal Florida as each of those factors relate to an increased N

load. Understanding the present-day response of coastal ecosystems to nutrient loading and their

capacity to "absorb" these loads should be of paramount importance, especially in regions where











APPENDIX B
RAW FLUX MEASUREMENT DATA

Table B l. Five minute dataset of chamber and environmental data. SpCond = specific


conductivity, DO


dissolved oxygen

Temperature SI
(oC) (mr

25.58 6
25.88 6
25.83 6
25.74
25.71 6
25.68 6
25.38 6
25.76 6
25.74 6
25.73
25.69 6
25.60 6
25.57 6
25.46 6
25.44 6
25.43 6
25.41 6
25.37 6
25.33
25.24 6
25.16 6
25.10 6
25.06 6
25.01 6
24.97 6
24.95 6
24.89
24.87 6
24.84 6
24.80 6
24.76 6
24.72 6
24.65 6
24.67 6
24.63 6
24.62 6
24.58 6
24.60 6
24.53 6
24.65 6
24.21


Total
pCond Dissolved
IS/cm) Solids
(g/L)
j.666 4.333
j.444 4.189
j.418 4.172
6.38 4.147
j.334 4.117
j.281 4.083
j.329 4.114
j.233 4.051
j.205 4.033
6.19 4.023
j.173 4.012
j.162 4.006
j.152 3.998
j.142 3.992
j.132 3.986
j.129 3.983
j.136 3.988
j.129 3.984
6.12 3.978
j.122 3.98
j.118 3.977
j.116 3.976
j.114 3.974
j.113 3.973
j.107 3.97
j.103 3.967
6.1 3.965
j.104 3.968
j.103 3.967
j.101 3.966
j.101 3.966
j.103 3.967
j.108 3.97
j.105 3.968
j.104 3.968
j.104 3.967
j.102 3.967
j.101 3.966
j.098 3.963
j.053 3.934
5.35 3.477


Water
Elevation
(cm)
71.1
71.1
71.2
71.4
71.7
71.6
71.6
71.7
71.8
72.1
72.3
73.4
72.9
73.3
73.6
74.1
74.5
74.9
75.3
75.7
75.8
75.9
76.5
76.9
77.2
77.6
77.9
78.3
78.7
79.1
79.4
79.7
80.0
80.3
80.6
81.1
81.4
81.8
81.8
82.3
82.5


Salinity DO
(ppt) (p-M)


Date and Time


4/24/07 17:30
4/24/07 17:35
4/24/07 17:40
4/24/07 17:45
4/24/07 17:50
4/24/07 17:55
4/24/07 18:00
4/24/07 18:05
4/24/07 18:10
4/24/07 18:15
4/24/07 18:20
4/24/07 18:25
4/24/07 18:30
4/24/07 18:35
4/24/07 18:40
4/24/07 18:45
4/24/07 18:50
4/24/07 18:55
4/24/07 19:00
4/24/07 19:05
4/24/07 19:10
4/24/07 19:15
4/24/07 19:20
4/24/07 19:25
4/24/07 19:30
4/24/07 19:35
4/24/07 19:40
4/24/07 19:45
4/24/07 19:50
4/24/07 19:55
4/24/07 20:00
4/24/07 20:05
4/24/07 20:10
4/24/07 20:15
4/24/07 20:20
4/24/07 20:25
4/24/07 20:30
4/24/07 20:35
4/24/07 20:40
4/24/07 20:45
4/24/07 20:50


pH


8.03
8.07
8.09
8.07
8.06
8.04
8.01
8.02
8.02
8.02
8.01
8.01
8.01
8.01
8.01
8.01
8.01
8.01
8.01
8.01
8.01
8.01
8.02
8.02
8.02
8.02
8.02
8.02
8.02
8.02
8.02
8.01
8.01
8.01
8.01
8.01
8.00
8.00
7.99
7.98
7.89


3.64
3.51
3.49
3.47
3.45
3.42
3.44
3.39
3.37
3.36
3.35
3.35
3.34
3.34
3.33
3.33
3.33
3.33
3.32
3.32
3.32
3.32
3.32
3.32
3.32
3.31
3.31
3.32
3.32
3.31
3.31
3.32
3.32
3.32
3.32
3.32
3.32
3.31
3.31
3.29
2.88


422.50
458.75
478.75
433.75
421.88
416.25
401.88
411.25
406.88
405.63
403.13
396.88
393.75
390.63
386.88
382.50
380.00
376.88
374.38
371.88
368.75
365.00
361.25
356.25
355.00
353.13
351.88
350.63
350.00
347.50
346.25
346.25
345.00
345.00
390.63
385.00
381.25
383.13
374.38
407.50
400.63











Table B2 continued


Surface
Solar
Irradiance
(pIS/cm2/S)
-8.17
4.933
0.141
-1.128
-7.752
-16.21
-23.68
-16.07
-32.98
-35.66
-43.13
-39.89
-57.5
9.87
12.26
10.71
14.52
-5.778
-11.56
-29.74
-9.3
-12.12
-12.4
-8.74
-8.03
-10.01
-12.12
-13.53
-19.31
-21.99
-14.8
-21.7
-20.29
-25.65
-26.35
-26.35
-30.44
-37.91
-43.13
-25.37
-22.55
-45.38
-40.59
-43.55
-59.62


Subsurface
Solar
Irradiance
(pS/cm2/S)
74.49
55.47
49.84
62.57
47.43
53.73
44.89
45.56
49.44
23.58
51.18
64.04
63.1
78.11
78.24
76.9
77.84
71.68
73.42
72.75
78.91
78.11
73.42
68.33
76.5
74.62
73.02
78.51
77.71
78.11
75.03
75.29
77.04
77.44
70.61
71.95
74.22
72.48
63.5
54.53
60.29
60.43
55.61
53.86
55.61


Panel
Temperature
o"C)
16.62
16.7
16.8
16.77
16.64
16.62
16.68
16.79
16.95
17.09
17.19
17.28
17.28
17.25
17.33
17.43
17.53
17.61
17.71
17.78
17.83
17.88
17.91
17.89
17.89
17.9
17.91
17.88
17.83
17.72
17.6
17.5
17.42
17.34
17.26
17.22
17.15
17.05
16.97
16.9
16.81
16.74
16.7
16.68
16.66


Red ox
Probe 1


150.3
170.9
31.1
47.33
177.8
180.2
178.8
174.1
175.1
20.49
-43.84
-66.21
-80.1
-88.5
-95
-100.3
-104.3
-108.7
-108.6
-113.3
-115.8
-119
-121.2
-122.9
-124.8
-126.2
-127.6
-123.2
-129
-125.3
-119.8
-129.1
-132.8
-100.7
-102.5
-121.1
-128.2
-132
-109.5
-124.1
-126.4
-126.7
-127.4
-126.6
-125


Redox
Probe 2


-131.5
-106.9
-140.7
-138.5
-91.4
-82.9
-97.9
-96.7
-106.9
-163
-167.6
-168.1
-168.5
-167.8
-167.7
-167.5
-167.3
-167.3
-166.6
-166.7
-166.3
-166.6
-166.8
-165.8
-165.2
-164.8
-164.2
-163.8
-163.9
-163.7
-164.2
-164.3
-164.3
-164.2
-164.7
-164.9
-164.9
-164.9
-164.8
-165.1
-165.5
-165.9
-166.3
-167.1
-167.2


Redox
Probe 3


48.72
140.3
3.354
79.93
233.7
261.5
280
288.6
304.3
25.94
-63.01
-71.62
-81.7
-85
-90.2
-92.6
-121.5
-126.6
-117.3
-114
-112.7
-119.6
-114.6
-113.8
-113.5
-114.2
-114.4
-114.2
-113.4
-114
-114.4
-115.5
-116.5
-116.9
-117.7
-116.5
-117.4
-117.1
-116.9
-116.1
-116
-115.2
-114.7
-114.8
-115.5


Redox
Probe 4


-8.44
-17.33
-119.5
-100.8
-57.59
-44.2
-56.13
-61.85
-52.91
-145.8
-167.5
-168
-169
-168.6
-168.8
-169
-170.3
-171.7
-172
-172
-171.8
-171.7
-171.9
-171.8
-171.5
-171.2
-171
-170.7
-170.8
-170.9
-171
-170.9
-171.1
-171.1
-171.2
-171.3
-171.5
-171.8
-172.3
-172.7
-173.6
-174.8
-176.3
-177.9
-179


Date and Time


4/25/07 0:45
4/25/07 0:50
4/25/07 0:55
4/25/07 1:00
4/25/07 1:05
4/25/07 1:10
4/25/07 1:15
4/25/07 1:20
4/25/07 1:25
4/25/07 1:30
4/25/07 1:35
4/25/07 1:40
4/25/07 1:45
4/25/07 1:50
4/25/07 1:55
4/25/07 2:00
4/25/07 2:05
4/25/07 2:10
4/25/07 2:15
4/25/07 2:20
4/25/07 2:25
4/25/07 2:30
4/25/07 2:35
4/25/07 2:40
4/25/07 2:45
4/25/07 2:50
4/25/07 2:55
4/25/07 3:00
4/25/07 3:05
4/25/07 3:10
4/25/07 3:15
4/25/07 3:20
4/25/07 3:25
4/25/07 3:30
4/25/07 3:35
4/25/07 3:40
4/25/07 3:45
4/25/07 3:50
4/25/07 3:55
4/25/07 4:00
4/25/07 4:05
4/25/07 4:10
4/25/07 4:15
4/25/07 4:20
4/25/07 4:25









CHAPTER 5
SYNTHESIS: BIOGEOCHEMICAL DYNAMICS OF SUBAQUEOUS SOILS IN THE
CHASSAHOWITZKA SPRING-FED RIVER AND ESTUARY

Anthropogenic impacts at the global scale continue to influence the coastal environment.

Florida' s valuable coastal resources are particularly susceptible to anthropogenic impacts,

especially given the karst nature of Florida' s geology. The interconnectivity between

anthropogenic activities on land and rising nutrient concentrations at the springhead was shown

in Chapter 2. Significant positive correlations between annual precipitation and NO3~

concentrations strongly suggest that NO3~ is quickly transported from the surrounding terrestrial

environment and into the river and estuarine system. The analysis in Chapter 2 demonstrated that

receiving water bodies and associated benthic substrate have distinct abilities to ameliorate

excess NO3- and soluble reactive phosphorus (SRP) concentrations. Along the upper transect of

the Chassahowitzka River NO3~ losses increased in proportion to the total NO3~ l0ad while

increases in SRP losses did not change significantly under high SRP loading conditions. Despite

the capacity of the system to uptake additional amounts of NO3-, both NO3- and SRP

concentrations increased significantly at transect 10 in response to elevated nutrient loading

conditions suggesting that the natural buffering capacity of elevated nutrient concentrations

along the upper transects of the study area had been maximized.

Benthic substrate likely plays a dominant role in the biogeochemical cycling of N and P,

especially in along the upper transects of the Chassahowitzka River. Mapping the spatial

distribution of subaqueous soils within the Chassahowitzka River and Estuary and determining

their basic physical and chemical properties was the subj ect of Chapter 3. It is well known that

the nature of benthic substrate (i.e. its physical and chemical properties) will likely influence its

function in the environment. Therefore, understanding large-scale trends in the distribution of

subaqueous soils and their physical and chemical properties is extremely important in the









Table 3-6. Blue Crab (BIC) typical pedon description and taxonomic identification

Typical Pedon Description: Blue Crab
Map Unit: BIC
Location N 280 43' 14.7", W 0820 35' 52.2"
Classifieation: Typic Sulfaquent

Oa 0-1cm; black (N 2/0); muck; pH 7.62; diffuse boundary.

AC 1-6 cm; black (10YR 2/1); loamy sand; pH 7.62.

2Ab 6-13 cm; very dark gray (10YR 3/1); loamy sand; pH 7.48.

2ACb 13-24 cm; dark yellowish brown (10YR 3/4); loamy sand; pH 7.54; wavy
boundary.

3Ab 24-51 cm; very dark brown (10YR 2/2); mucky sand; pH 7.36; distinct boundary.

3ACb 51-66 cm; very dark gray (10YR 3/1); Eine sand; pH 7.32.


Table 3-7. Midden Flats (MdF) typical pedon description and taxonomic identification
Typical Pedon Description: M~idden Flats
Map Unit: MdF
Location N 280 42' 39.5", W 0820 36' 43.9"
Classifieation: Mollic Psammaquent

Al 0-10.5cm; black (N 2/0); mucky sand; few Eine roots; 2% shell fragments; pH
7.19; diffuse boundary.

A2 10.5-16.5 cm; black (N 2/0); mucky sand; many fine roots; 2% shell fragments;
pH 7.31; diffuse boundary.

A/C 1 16.5-61.5cm; A: black (N 2/0); mucky sand. C: very dark gray (10YR 3/1); Eine
sand. Few Eine roots; 2% shell fragments; pH 7.06; diffuse boundary.

A/C2 61.5-106.5cm; A: black (N 2/0); mucky sand. C2: very dark gray (10YR 3/1); Eine
sand. Few Eine roots; 2% shell fragments; pH 6.86.









and characteristics of individual animal species. This classification allows one to relate soil

characteristics to those with similar characteristics. In essence, soil scientists have applied a

taxonomic classification to the Earth's surface. In this conceptual framework, each polypedon

has similarities to soils in its family, subgroup, great group, suborder, and order and its

distinction or similarity from other soils varies as function of taxonomic relationship. A soil

scientist selects a specific typical pedon for taxonomic description based on observations of the

variability of the properties of that soil over its extent, in the same manner that a biologist would

go about a species description of a representative specimen after they observe variability of traits

within a particular species.

A common question that soil scientists working in aquatic environments need to answer is,

"What differentiates soil and sediment?" The dominant conceptual understanding is that the

presence of overlying water is what separates soil and sediment. Post-depositional processes

occurring in a terrestrial environment are referred to as pedogenic processes, while those

occurring in the subaqueous environment are often termed diagenetic processes. One distinction

between pedologists and sedimentologists is that a significant portion of sedimentological work

focuses on the transport, deposition, and post-burial conversion of sediment into rock.

Pedologists on the other hand mainly study the formation, morphology, and equilibrium

condition of the Earth/atmosphere or Earth/water-column interface. It would suffice to say that

pedologists study the genetic processes, controls, properties, and function of the world' s bio-

reactive interface. Pedologists are concerned with how parent material arrived, where it will

eventually go, and are also concerned with the interdependency between substrate properties and

the surrounding environment at the outermost layer of the Earth' s crust. While various

definitions exist, for the purposes of this research, soil is considered as the reactive interface










precipitation was stronger than that between mean annual NO3~ COncentration and annual

discharge. This suggested that fresh high- NO3~ COncentration water derived from recent

precipitation was most important in contributing to variation in NO3~ COncentrations.

Mean NO3~ COncentrations remained consistently elevated during the High loading regime,

regardless of season. This is likely due to abundant amounts of freshly-recharged groundwater

feeding the spring throughout the year and limited dilution as discussed above. In contrast,

during the Low loading regime, NO3~ COncentrations were significantly different between Dry

and Wet seasons (P<0.05). During the Low loading period, the highest NO3~ COncentrations

occurred during the Dry season, concomitant with the arrival of the discharge pulse related to

that season's rainfall at the headspring. This result supports the concept that seasonal increases in

NO3~ COncentrations draining the springs of the Chassahowitzka River result from recent,

precipitation-derived NO3 -

Whereas past authors have concluded that there is little that can be done regarding NO3~

concentrations in springs due to the fact that contamination of the aquifer has already occurred

(Jones et al., 1997), the findings of this research suggest that there is potential for management

actions to decrease NO3~ COncentrations within the same year. The potential for management

impact would likely increase with proximity to the spring-head. Locations closest to the

springhead likely contribute a greater proportion of recently derived rain and stormwater as

opposed to those locations further away (Jones et al., 1997). It is therefore evident that NO3~

concentrations in coastal springs will be particularly sensitive to climatic modification and

hydrologic variability. Florida is subj ect to a number of factors that influence its climate and

hydrology at a variety of timescales including hurricanes, El Nifio events, droughts, and

anthropogenic water-withdrawals. The response of nutrient concentrations in coastal springs and









= 23-260C), DO (range = 140-480ClM), and pH (range = 7.1-8.0) increased markedly in the water

column with photon flux. NO3~ COncentrations ranged from 11-26C1M in the water column and

were highest when salinity was lowest, indicating a freshwater NO3~ Source. Tidally driven

changes in water column elevation roughly co-varied with the diurnal light cycle; low tide

occurred at 7:30AM and the tidal high was at approximately 4PM (Figure 4-3). Generally,

nighttime values were associated with a falling tide while daytime values were associated with a

rising tide. Wind was light throughout the daytime hours of the experiment and almost

completely calm during the night. There was no precipitation and scattered cloud cover

throughout the duration of the field trial.

Benthic Reactions and Environmental Variability

Table 4-1 presents the rates of change for all water and environmental constituents

calculated using slopes of data segments indicated by lines shown in Figure 4-4. Each segment

represents an incubation period, each separated by a period of chamber re-equilibration.

Apparent NO3~ losses ranged from -1 12 to -3 85 Clmol/m2/hr and DO additions and losses ranged

widely from -5059 to 5332 Clmol/m2/hr (Table 4-1; Figure 4-4). DO losses occurred during the

nighttime hours while additions occurred concomitant with the strongest period of insolation

(incubation 5, Figure 4-4). Temperatures decreased at night at a maximum rate of -0.610C/hr and

increased during the day at a maximum rate of 0.610C/hr. Salinity concentrations consistently

decreased during all incubations; however, the rate of salinity decrease varied from -0.007 to -

0.024 ppt/hr (Table 4-1, Figure 4-4), equivalent to an SGD rate of 50.7-175.8 L/m2/day.

NO3- Additions and Losses and Their Relationships to Environmental Parameters

Net NO3~ losses were positively correlated with NO3~ COncentration (r2 = 0.65; P=0.056)

throughout the study period. When the outlying data point from incubation 3 was removed, net

NO3~ losses were significantly related with NO3~ COncentrations (Figure 4-5; r2 = 0.997; P<0.001)












a) -








Chass Sand Riversides Blue Crab Midden Flat


e)








Chass Sand Riversides Blue Crab Midden Flat


f)








Chass Sand Riversides Blue Crab Midden Flat


600 b

S400

O
O200


200_ C


60 d)


I



Chass Sand Riversides Blue Crab Midden Flat


ZC


Chass Sand Riversides Blue Crab Midden Flat


Figure 3-6. a) Total phosphorus (TP), c) organic carbon (OC), e) total nitrogen (TN), and molar
ratios ofb) OC:TP, d) TN:TP, and f) OC:TN plotted by map unit. Box plots indicate
the sample median (line with dark circle inside the shaded box), upper and lower
quartiles (indicated by the shaded area above or below the sample median). Box
whiskers indicate the upper and lower limits (1.5*inter quartile range) of non-outlying
values. Finally, lines with dark circles beyond boxplot whiskers indicate outlying
data points


Chass Sand Riversides Blue Crab Midden Flat


,I
































gure A-11i. Microscopic photo of potentially biomineralized spherules from the sample in
Figure A-9


Figure A-12. Microscopic photo of potentially biomineralized framboidal pyrite from the sample
in Figure A-9
















S75

27




0- 70 -


S22-


L- 65 .0




17 -
S60


-% Possible Sunshine
-[-I Temperature

12 55



Fiur -8 Ma mnhl artepratr n hepretg o oetalislto rahn h
eat srae NA, 07









surrounding terrestrial environment via rapid flowpaths and resulted in elevated NO3~
concentrations on the timescale of months, not decades.

Net NO3~ losses were directly proportional to NO3~ l0ad along the upper reaches of the
Chassahowitzka River. At the reach scale this retention is equal to 30% of the total N
load.

Estuarine areas received the highest loads of both inorganic N and P during periods of
High source loading (flow) and during the Dry (Sept-March) season, suggesting that the
upstream controls did not attenuate increased nutrient loads under all conditions.

At the interannual timescale, mass SRP uptake was relatively constant in the upper
reaches (Transect 1-5) regardless of P load, suggesting a maximum or limited uptake rate
in contrast to that of NO3 -

The interactive effects of increasing precipitation, higher anthropogenic N deposition,
greater sources of atmospheric N deposition, higher discharge rates, and the increased
proportion of recently-derived waters at the spring head have the potential to dramatically
increase NO3~ COncentrations in Florida' s coastal ecosystems.

Management of anthropogenic drivers of nutrient additions, especially within close
proximity to the springhead, has the potential to reduce precipitation-dependent NO3~
concentrations at the headspring over short timescales.

The Chassahowitzka Springshed has entered what has become a familiar series of events in

modern times: anthropogenic activities have led to increasing N inputs at the watershed scale,

stimulated increased N loading to aquatic systems, and potentially threatened the ecological

integrity of associated estuaries. The karst geology and rapid hydrological transport of

terrestrially-derived solutes in Florida results in an accelerated propagation of anthropogenic

effects to coastal ecosystems. Coastal spring-fed rivers, salt marshes, and estuaries have

demonstrated some intrinsic capacity to attenuate increasing nutrient loads, but this capacity

appears to be limited as was shown by downstream transfers of elevated nutrient concentrations

in response to varying load and seasonal conditions. Therefore, the Chassahowitzka River and

Estuary may be approaching the limits of its natural capacity to prevent significant downstream

transfers of nutrients. This was evidenced by downstream propagation of elevated nutrient

concentrations to Transect 10 under high loading conditions. Understanding the threshold










precision would also increase the overall precision of the final flux measurement, which could

potentially reveal relationships between NO3- flux and environmental drivers previously

unnoticed.

Influence of Diffuse Groundwater Seepage

Another factor complicating studies of benthic nutrient cycling in estuaries is DGS

(Billerbeck et al., 2006; Burnett et al., 2003; Burnett et al., 2006). Diffuse groundwater seepage

is also known as submarine groundwater discharge (SGD) in coastal brackish or saline water

bodies and is the advective transport of groundwater from an aquifer, through surface materials,

to the water column. Submarine groundwater discharge has become increasingly recognized as a

process of paramount importance in estuarine biogeochemical cycling (Burnett et al., 2006;

Charette, 2007; Moore et al., 2006; Swarzenski et al., 2006). Although researchers have

estimated SGD-driven mass nutrient export (Paytan et al., 2006; Slomp and Van Cappellen,

2004; Swarzenski et al., 2006) and studied the chemical alteration of SGD within benthic

porewater (Beck et al., 2007), to the best of my knowledge there has not been a direct study of

the role of SGD as a driver of nutrient cycling at the benthic/water interface over short timescales

(hours). Variability in SGD is often controlled by tidal elevation (Burnett et al., 2006).

Therefore, if SGD does influence benthic reaction rates, tidal timescale variability may be an

important regulator of nutrient fluxes.

Common benthic flux measurement methods including microprofilers, peepers, and

porewater sippers calculate nutrient fluxes across the benthic/water interface using Fick' s law of

diffusion and the assumption of diffusion-driven mass transport at the benthic/water interface

(Hou et al., 2006; Liu et al., 2005; Ni et al., 2006). While this approach is appropriate for

diffusion-dominated benthic/water boundaries, the assumption is invalidated by the presence of

advective SGD flowing at even a modest rate. However, many studies do not report an









BIOGRAPHICAL SKETCH

Tom arrived on the scene in Denver, Colorado in February of 1978 and spent the first year

of his life in a dresser drawer (open) in nearby Scottsbluff, Nebraska. From there the Saunders

found their way to San Jose, California. Camping, hiking, and swimming in and around the

mountains and valleys of the coastal foothills and Yosemite National Park instilled a

fundamental interest and enchantment with the world outdoors. Wanderlust and restlessness

took hold of Tom before long, motivating him to leave high school in pursuit of an associates

degree at Colorado Mountain College and focused on outdoor recreational leadership.

Employment and personal time in the outdoors provided an abundance of unforgettable moments

spent scaling granite and sandstone, working search and rescue in Yosemite, guiding whitewater

in Colorado, and truck-camping across climbing locales of the Southwest; all the time gaining a

deeper respect and awe for the power and intricacy of the natural world.

Tom shifted his focus from recreation toward environmental science, obtaining his B.S. in

Environmental Science from Humboldt State University in Northemn Califomnia. A strong

interest in watershed science and travel experiences in Latin America then drew him toward a

masters from Florida Intemnational University that focused on riparian biogeochemistry in

montane rainforests of the Peruvian Amazon. While in Florida he was particularly drawn toward

the unique Florida Spring systems and the anthropogenic activities affecting them. He pursued

an opportunity to integrate soils, estuaries, and spring-fed rivers into his dissertation work. Tom

and his wife Lynn plan to continue working on applied natural resource issues around the world.















































0.04 0.08 0.16 0.24 0.32

Figure 2-5- Delineation and areas of the upstream RIVERS sampling transects 1-5 used for flux calculations. The area, transect
numbers, and designations of the area between transects are indicated. The background image is composed of digital
orthophotos (SWFWMD, 2007)









data was assembled into a geodatabase using ArcGIS 9.1 (ESRI; Redlands, CA, 2005) for

analysis. Data that quantified environmental variables and water quality parameters were

assembled and evaluated to identify trends, relationships, and the statistical distributions of each

parameter of interest. All statistical analyses were carried out using S-Plus 6. 1 (Insightful

Corporation; Seattle, WA, 2002).

Water quality monitoring data from 1998-2006 (missing data in 2002) for the

Chassahowitzka River and Estuary was assembled from two reports: the "Five Rivers" (Frazer et

al., 2006; Frazer et al., 2001) and "Three Rivers" (Frazer et al., 2006) water quality monitoring

programs. This combined dataset used here is referred to as the "RIVERS" data. Data from both

reports were sampled from the same monitoring locations and chemically analyzed in the same

laboratory. The RIVERS data consist of 20 monitoring sites extending from the springhead into

the estuary, the first 15 of which have a three-station transect perpendicular to the main channel

(Figure 2-4). Analytes of interest to this study are listed in Table 2-1. A separate monitoring

program, titled Proj ect COAST (Frazer et al., 2007), produced a monthly dataset from 1997-

2006 with fewer analytes and sample sites (Table 2-1), though covering a larger area. In this

study, COAST data were used in addition to the RIVERS dataset to evaluate temporal dynamics

in spring source nutrient concentrations at Transect 1 (Figure 2-4).

Spring Source: Quantifying Seasonal and Interannual Variation

Transect 1 of the RIVERS and COAST monitoring programs on the Chassahowitzka is

adj acent to the headspring and data was available at monthly and quarterly intervals from 1997-

2006. A United States Geological Survey (USGS) stream discharge gauging station is also

located just below the main headspring providing relatively continuous hydrologic flow data for

the spring source. Based on the discharge and water quality information assembled, multi-year

variability in both NO3~ COncentration and discharge were divided into "Low" and "High"

















ChS


MdF


Legend

*Soil Description Sites

@ Typical Pedon Locations
SIslands




II l lill l
0 0.5 1 2 Kilometers s
Figure 3-3. Soil reconnaissance site descriptions and typical pedon sampling locations on the Chassahowitzka River and Estuary.
Typical pedon sampling locations are indicated as follows: Chass Sands (ChS), Riversides (RvS), Blue Crab (BIC), and
Midden Flats (MdF). Shell Bottom (ShB; not shown) was not sampled for a typical pedon as the map unit dominantly
consisted of mobile sands and gravels











Table B2 continued


Surface
Solar
Irradiance
(pIS/cm2/S)
-8.88
-12.4
-18.17
-20.57
-15.07
-12.82
-15.64
-17.33
-12.82
-22.55
-33.54
-26.07
-43.97
-49.04
-52.57
-47.64
-61.17
-64.97
-56.51
-33.82
-56.51
-149.5
-123.5
-52.43
-54.54
-52.57
-119.2
-182.5
-85.7
-84.4
-83
-84.3
-76.95
-73.29
-64.55
-67.23
-53.41
-4.651
7.47
4.228
-27.62
-33.4
-35.8
-35.37
-23.54


Subsurface
Solar
Irradiance
(pS/cm2/S)
0.804
9.38
19.42
23.04
14.2
14.73
18.89
22.77
25.32
47.42
51.44
35.64
52.92
61.63
67.93
64.31
72.08
67.79
70.07
53.59
67.12
56.94
62.03
69.13
71.68
67.93
69.53
74.09
75.16
72.62
66.18
71.01
78.38
78.11
76.23
75.56
69.53
69
72.88
77.44
79.72
79.58
79.05
76.63
75.83


Panel
Temperature
o"C)
20.34
20.12
19.85
19.6
19.43
19.28
19.26
19.3
19.2
19.05
18.87
18.71
18.59
18.43
18.32
18.18
18.06
17.99
17.87
17.78
17.76
17.69
17.62
17.55
17.47
17.4
17.37
17.32
17.24
17.18
17.14
17.19
17.32
17.41
17.39
17.36
17.33
17.27
17.19
17.07
16.96
16.88
16.81
16.77
16.68


Red ox
Probe 1


-48
-60.68
-69.71
-77.2
-82.7
-87.9
-91.1
-94.3
-33.07
103.7
163.8
216.4
234.9
227.3
222.3
215.9
215
208
204.4
206
196.6
193.8
168.3
167.9
164.6
165.7
159.9
148.6
142.3
131.5
163.3
188.6
166.4
161.7
163.3
160.9
151.8
154
152.7
156.1
143.7
146.6
152.7
156.5
152.1


Redox
Probe 2

-144.1
-145.1

-144.5
-145.3
-145.7
-145.4
-145.3
-146
-147.7
-144.8
-142.8
-142.9
-143.4
-145.5
-145.6
-144.6
-142.9
-145.5
-146.4
-145.9
-144.1
-145.2
-145
-141.3
-141.7
-140.4
-140.7
-142
-141.2
-140
-140.3
-149.8
-149.5
-148.1
-150.1
-149.3
-152.4
-152.6
-155.1
-156.5
-155.3
-155.4
-153.7
-140.9
-136.8


Redox
Probe 3


20.42
11.46
2.596
-3.784
-10.74
-20.58
-36.35
-37.81
-32.99
-33.4
-33.76
-34.22
-10.14
53.14
35.96
44.64
40.53
35.37
37.37
58.59
60.88
41.14
31.88
33.22
22.56
15.88
23.34
28.32
25.65
19.17
20.87
24.59
42.29
35.71
34.46
35.38
46.91
43.47
57.93
65.35
62.65
70.72
62.32
57.33
56.39


Redox
Probe 4


-132.8
-131.6
-124.1
-112.7
-5.717
140.5
109.8
-58.86
-80.8
36.46
-29.5
122.9
7.524
0.22
234.7
137.9
-35.03
108.9
141
249.5
139.6
111.8
224
252
264.7
243.3
22.57
191.1
186.2
6.012
-32.08
-6.055
-20.13
-26.79
-4.093
-8.41
27.96
-5.74
175.3
228.9
106.4
30.99
-26.81
-23.14
-21.54


Date and Time


4/24/07 21:00
4/24/07 21:05
4/24/07 21:10
4/24/07 21:15
4/24/07 21:20
4/24/07 21:25
4/24/07 21:30
4/24/07 21:35
4/24/07 21:40
4/24/07 21:45
4/24/07 21:50
4/24/07 21:55
4/24/07 22:00
4/24/07 22:05
4/24/07 22:10
4/24/07 22:15
4/24/07 22:20
4/24/07 22:25
4/24/07 22:30
4/24/07 22:35
4/24/07 22:40
4/24/07 22:45
4/24/07 22:50
4/24/07 22:55
4/24/07 23:00
4/24/07 23:05
4/24/07 23:10
4/24/07 23:15
4/24/07 23:20
4/24/07 23:25
4/24/07 23:30
4/24/07 23:35
4/24/07 23:40
4/24/07 23:45
4/24/07 23:50
4/24/07 23:55
4/25/07 0:00
4/25/07 0:05
4/25/07 0:10
4/25/07 0:15
4/25/07 0:20
4/25/07 0:25
4/25/07 0:30
4/25/07 0:35
4/25/07 0:40


























4

3-

2-


Chass Sand Riversides Blue Crab Midden Flat











iD3 n


sad fn ad la ysadm cysn uk
Tetr


-


Chass Sand Riversides Blue Crab Midden Flat






NA**














Chass Sand Riversides Blue Crab Midden Flat


-



-


4





3

2







10





015



O00


Figure 3-5. a) Soil pH (field determined) among map units (intentionally presented with the same y-axis as Figure b and c for

comparison), incubation pH (>120 day moist incubation) as grouped by b) map unit and c) soil texture. d) Bulk density is

grouped by map unit. All pH calculations were carried out on raw hydrogen ion concentration data and transformed back to

-log[H+] for data presentation. NA= not available. **Data not available however, as the Chass Sands were the most sand-
dominated soils within the river system, it is likely they also has the highest bulk densities within the study area. Box plots

indicate the sample median (line with dark circle inside the shaded box), upper and lower quartiles (indicated by the shaded

area above or below the sample median). Box whiskers indicate the upper and lower limits (1.5*inter quartile range) of

non-outlying values. Finally, lines with dark circles beyond boxplot whiskers indicate outlying data points



































gure A-9. Subsample from clay enriched horizon from figure above


'+
I~ i;,


~ f" ";



IF,.
iii~i~~41F~
Ii .r




r ;P~


r
"i~;;~-"T~ ~ C X*
C


Figure A-10. Microscopic photo of potential biomineralization site from sample in Figure A-9









settle. Small sticks and leaves from terrestrial plants were commonly encountered in the surface

horizons of Riversides soils. Water velocity in the lateral channel is quite slow, often resulting in

flow rates of 0-0. 1 m/s.

Contents of OC, TN, and TP ranged from 4-209 g/kg, 0.3-16.6 g/kg, and 50.5-2481mg/kg,

respectively (Table 3-3). The highest OC, TN, and TP contents were located in the surface

horizon and decreased consistently with depth.

The typical pedon of the Riversides map unit was classified to the subgroup level as a

Mollic Psammaquent (Table 3-2, Table 3-5). No diagnostic horizons were present in the typical

pedon and the soil remains saturated year round. Therefore, the subgroup taxonomic

classification was Aquent. Soil pH decreased upon incubation, though not below the pH < 4

required for the definition of sulfidic materials. However, sand and sandy-loam lamellae were

common in the soils described in this map unit as well as in the typical pedon. The presence of

these coarse materials resulted in the classification of the typical pedon into the Great Group of

Psammaquents. Finally, the presence of low-value, low-chroma colors in the upper horizons led

to the subgroup classification of Mollic Psammaquents.

The Riversides map unit is longitudinally associated with Chass Sands. However, the

Riversides map unit is characterized by lower water velocities of the channel edges. This

depositional environment has promoted the settling of OM produced in the upper reaches of the

river, riparian areas, and by algal communities growing on the sides of the channel. Chironomids

(non-biting midges) have been observed in a number of soil cores sampled from this area and

may be significant drivers of mixing to form the mucky sand A horizons that characterize this

map unit. Many wading bird species common to the Chassahowitzka National Wildlife Refuge

hunt in this map unit among the emergent vegetation. As OM content is higher in the Riversides









Landform boundaries were used to calculate the areal extent of landform features using ArcGIS

9.1i. Due to the fine scale of the survey, map units smaller than dominant landforms were not

delineated.

Typical Pedons

A pedon is the smallest volume that can be called a soil. A typical pedon is a reference

specimen that illustrates the central concept of a soil in a given soil map unit or series (NRCS,

2005). While no typical pedon sampled in a map unit is likely represent the mean of all soil

properties within a given map unit, the typical pedon should represent the mean of most physical

and chemical properties. Therefore, within each map unit delineated as part of this study, one

site was selected for the sampling of a typical pedon based on the reconnaissance observations

and soil descriptions (Table 3-2, Figure 3-3). The selection procedure was based on the

formation of a conceptual model of soil properties throughout the Chassahowitzka River and

Estuary. The formation of a conceptual model involved observing the variability of soil

properties including texture, color, horizonation, and horizon thickness across reconnaissance

description sites. These observations led to an understanding of the variability of soil properties

and their spatial distribution, limits, and associated vegetation. Finally, based on the conceptual

model, a sampling location was selected that was believed to represent the "norm" for the

mapped area given the multiple previous observations made during reconnaissance work (NRCS,

2005). To evaluate whether the typical pedon was representative of the greater soil map unit,

comparisons were made between the typical pedon soil description and the variability of

reconnaissance soil descriptions within a select map unit.

All typical pedons were sampled using a transparent polycarbonate core-tube and piston

assembly mounted to an aluminum tripod (3 m height) to minimize or eliminate any

displacement of soil materials upon coring. The piston corer was similar in design to that













10-la>


Muck Mucky Sand Sand
Soil Texture


4 8 12
Depth of Surface Horizon (crn)


2
Munsell Soil Value


0
Munsell Soil Chroma


TD


TP


N10YR
Munsell Soil Hue


A B O
Master Horizon Below Surface


Figure 3-7. Histograms of the distribution of a) soil texture, b) depth of the surface horizon
below the soil surface, c) Munsell soil value, d) Munsell soil chroma, e) Munsell soil hue,
and f) the master horizon underlying the surface horizon. 'TP' indicates the value
described in the typical pedon soil description. All data presented in histograms
originates from the Riversides Map unit reconnaissance soil descriptions. All data, with
the exception of Figure f), reflects the surface horizon (epipedon) at the description site










(DO), temperature, salinity, pH, and NO3~ COncentrations are connected to the chamber via a

flow-through cell and water is constantly cycled between the cell and the chamber via a

peristaltic pump. The chamber is fitted with a flexible bladder, allowing the movement of SGD

from below into the chamber. Salinity concentrations are used in combination with a two-source

mixing model to provide SGD estimates. All data are evaluated at the same time interval (every

30 minutes) allowing for an analysis of relationships between NO3~ flUXeS and the factors

influencing those rates including temperature, DO, salinity, pH, and SGD.

Materials and Procedures

The benthic chamber was constructed from 46 cm inside diameter (ID) fiberglass cylinder

(Aquatic Ecosystems; Apopka, FL; Figure 4-2) with a height of 30 cm. The chamber material is

approximately 90% translucent to photosynthetically active radiation (PAR; 400-700-nm

wavelengths). The cylinder was sealed at one end using a 0.635 cm thick acrylic sheet and

silicone aquarium sealant. Four 5 cm holes were machined into the sides of the chamber to

accommodate rubber stoppers. Rubber stoppers (#10; Fisher Scientific; Pittsburgh, PA) were

then drilled to accommodate 1 cm ID PVC tubing while maintaining a watertight seal. A

flexible bladder was attached to the chamber to equilibrate inner and outer water pressure

through the changing tidal cycle and to allow SGD to enter the chamber.

A 1 cm ID flexible PVC tube was connected to a peristaltic pump (Masterfiex E/S Portable

Sampler, Cole-Parmer Instrument Company; Vernon Hills, IL) and the flow rate was calibrated

at 200mL/min. The peristaltic pump drew water from one side of the chamber, through a flow-

through cell constructed of 6 cm ID, 0.635 cm thick, acrylic tubing, and back into the other side

of the chamber. One end of the flow-through cell was sealed with a rubber stopper (#1 1) drilled

to accommodate the filter head for a YSI 9600 in-situ NO3- analyzer (YSI Environmental;

Yellow Springs, OH). The YSI 9600 utilizes flow-inj section and in situ filtering in order to










Janssen, F., P. Faerber, M. Huettel, V. Meyer, and U. Witte. 2005. Pore-water advection and
solute fluxes in permeable marine sediments (I): Calibration and performance of the novel
benthic chamber system Sandy. Limnology And Oceanography 50:768-778.

Jenny, H. 1941. Factors of soil formation: A system of quantitative Pedology. McGraw-Hill,
New York.

Jickells, T.D., and J.E. Rae. 1997. Biogeochemistry of intertidal sediments Cambridge
University Press, Cambridge.

Jickells, T. 2005. External inputs as a contributor to eutrophication problems. Journal of Sea
Research 54:58-69.

Jones, G.W., S.B. Upchurch, K.M. Champion, and D.J. Dewitt. 1997. Water quality and
hydrology of the Homosassa, Chassahowitzka, Weeki Wachee, and Aripeka spring
complexes, Citrus and Hernando Counties, Florida Origin of increasing nitrate
concentrations. Southwest Forida Water Management Program. Ambient Ground-Water
Quality Monitoring Program.

Katz, B.G., J.F. Bohlke, and M.F. Mokray. 1999a. Sources and chronology of nitrate
contamination in spring waters, Suwannee River Basin, Florida, United States. Report:
USGS/WRI-99-4252: Prepared in cooperation with Suwannee River Water Management
District, White Springs, FL.

Katz, B.G., H.D. Hornsby, and J.F. Bohlke. 1999b. Sources of nitrate in water from springs and
the upper Floridan Aquifer, Suwannee River basin, Florida; Proceedings of an international
symposium held during IUGG 99; Impact of land-use change on nutrient loads from
diffuse sources. Birmingham, United Kingdom, July 18-30, 1999. IAHS-AISH Publication
257:117-124.

Katz, B.G., J.K. Boehlke, and H.D. Hornsby. 2001a. Timescales for nitrate contamination of
spring waters, northern Florida, USA. Chemical Geology 179:167-186.

Katz, B.G., J.K. Bohlke, E. Busenberg, and H.D. Hornsby. 2001Ib. Determining sources of nitrate
and residence times of groundwater discharging from springs in a karst system during
variable recharge conditions; Geological Society of America, 2001 annual meeting.
Geological Society of America, 2001 annual meeting, Boston, MA, United States, Nov. 1-
10, 2001. Abstracts with Programs Geological Society of America 33:341.

Katz, B.G. 2004. Sources of nitrate contamination and age of water in large karstic springs of
Florida. Environmental Geology 46:689-706.

Kemp, W.M., and W.R. Boynton. 2004. Productivity, trophic structure, and energy flow in the
steady-state ecosystems of Silver Springs, Florida. Ecological Modelling 178:43-49.

Kennish, M.J. 2002. Environmental threats and environmental future of estuaries. Environmental
Conservation 29:78-107.



































Sampling interval (time between measurements)


Figure 4-1. The theoretical relationship between sampling intervals necessary to calculate nutrient chamber-based additions and
losses vs. the method precision necessary to provide adequate information for the calculation of nutrient addition and loss
rates. As the sampling interval decreases, the precision to resolve slight differences in concentration increases rapidly


I


This
method
Previous methods




Full Text

PAGE 1

1 MULTI-SCALE ANALYSIS OF BENTHI C BIOGEOCHEMICAL PROPERTIES AND PROCESSING IN A SPRINGFED RIVER AND ESTUARY By THOMAS JOHN SAUNDERS A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2007

PAGE 2

2 2007 Thomas John Saunders

PAGE 3

3 To my parents

PAGE 4

4 ACKNOWLEDGMENTS Certain things cannot be completed alone and this dissertation ranks strongly as one of them. Without the direction, inspiration, and insi ght of my committee, this work could not have come to be. My committee chair, Mary Collins was always there with an open ear and sage advice to manage my energy and keep me on course. I cannot thank her enough for providing me with a consistent combined dose of dir ection, freedom, encouragement, and support throughout my doctoral research experience. She encouraged my explora tion of concepts, ideas, and experiences with a smile and advice when things didnÂ’t work out and drive to follow-up when they did. Tom Frazer challenged me to focus, hone-in on specifi c questions, collaborate with peers, and was a boon for open and honest discussion about all things academic; from dreams to reality. Tom selflessly provided data and resources, encour aged discussion, and was always a welcoming presence who made me feel that what I was doing was exciting, important and worthwhile. Wade Hurt was famously Wade Hurt. Wade was amazingly motivated, dedicated, and selfless with his time and energy in the field, office, and essentially all the time. Field days with Wade were some of the bright est highlights of my disse rtation experience and I learned volumes about soil, about myself, and about the world. Mark Brenner was always a positive influence, asking frank and often necessary questions, offering insight and discussion, and always encouraging me to keep going. Andy Ogram was availa ble, encouraging, and willing to share his excitement for the microbial worl d. Though the majority of my dissertation work was at a large scale, AndyÂ’s presence kept me grounded, challenged, and up to date with the current research into processe s occurring at the microbial le vel. Finally, Andy Zimmermann, though added as a committee member late in th e game, immensely improved my final product through his detailed reviews, fearless que stioning, and thorough discussions.

PAGE 5

5 I would also like to thank my lab mates and colleagues: Kelly (Fischler) Crew, Chip Chilton, Rex Ellis, and Victoria Gardner. Thei r constant encouragement offered an amazing sense of camaraderie to our day to day life. Fr om discussions about soil, archaeology, science, life, and beyond to everyoneÂ’s wil lingness to help in the field, la b, or in the office, I could not have asked for a better research group. Beyond our office, there were many students and staff from both the Soil and Water Science Department and the Department of Fisheries and Aquatic Sciences who made this research possible. Willie Harris, Gavin Wilson, Bill Reeve, Lisa Stanley, and Rocky Cao kept me on track in the labs of the Soil and Water Science Department and were hugely helpful and supportive. S ky Notestein, Darlene Sa indon, and Loreto De Brabandere helped immensely with equipment logistics, discussi ons regarding the systems that they were so familiar with, and in the field and lab. Finally, the good folks of the Chassahowitzka campground and community offere d their support, quest ions, insight, and encouragement to continue working on understa nding and improving the water quality of their spring-fed river and estuary. Of course, none of this could have happened without the loving suppor t of my wife, Lynn. Lynn was there throughout my dissertation experi ence, in the field, lab, and all the way through the final formatting of my dissertation; her cont ributions to this work cannot be understated. Most importantly, her love, understanding, and warm words of encouragement were the source of my motivation and were the fu el that kept things in moti on. Finally, I thank my family; moms, dads, brothers, and a sister (some in-laws, some blood relatives) all added spice to the last four years and their encouragement and support were always inspirational.

PAGE 6

6 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................4 LIST OF TABLES................................................................................................................. ..........9 LIST OF FIGURES................................................................................................................ .......10 CHAPTER 1 INTRODUCTION................................................................................................................. .15 The Coast as a Natural and Anthropogenic Interface.............................................................15 Interfaces at Interfaces: the Role of Benthic Biogeochemical Processes in the Coastal System.............................................................................................................16 Subaqueous Soils.............................................................................................................17 The Chassahowitzka River and Estuary.................................................................................18 Objectives..................................................................................................................... ..........19 2 SEASONAL AND INTERANNUAL DYNAMICS IN THE SOURCE, CYCLING, AND FATE OF NUTRIENTS IN A COASTAL SPRING-FED RIVER AND ESTUARY........................................................................................................................ ......21 Introduction................................................................................................................... ..........21 Methods........................................................................................................................ ..........24 Data Sources................................................................................................................... .24 Spring Source: Quantifying Seasona l and Interannual Variation....................................25 River and Estuary: Calculation of Nutrient Loads..........................................................26 Calculation of Spatially Dist ributed Net Nutrient Losses...............................................27 Results........................................................................................................................ .............29 Seasonal and Interannual Variation.................................................................................29 Spring Source: Variation and Interrelationships.............................................................29 River and Estuary: Nutrient Load Processing.................................................................30 Discussion..................................................................................................................... ..........31 Temporal Variability of Spring Source Nutrient Concentrations....................................31 Spring-Run Nutrient Dynamics.......................................................................................34 Conclusions.................................................................................................................... .........37 3 THE DISTRIBUTION AND PROPERTIES OF SUBAQUEOUS SOILS OF THE CHASSAHOWITZKA RIVER AND ESTUARY.................................................................61 Introduction................................................................................................................... ..........61 Subaqueous Soils.............................................................................................................61 Objectives..................................................................................................................... ...63 Methods........................................................................................................................ ..........64 Subaqueous Soil Reconnaissance....................................................................................64

PAGE 7

7 Delineating Subaqueous Soil Map Units.........................................................................64 Typical Pedons................................................................................................................6 5 Laboratory Analytical Methods.......................................................................................66 Results and Discussion......................................................................................................... ..67 Subaqueous Soils.............................................................................................................67 Physical and Chemical Soil Data Between Map Units...................................................68 Physical properties...................................................................................................68 Chemical properties..................................................................................................69 Map Units...................................................................................................................... ..71 Chass Sands (ChS)...................................................................................................71 Riversides (RvS)......................................................................................................72 Blue Crab (BlC).......................................................................................................74 Midden Flats (MdF).................................................................................................75 Shell Bottom (ShB)..................................................................................................76 Map Unit Names..............................................................................................................77 Typical Pedon Map Unit Representation........................................................................77 Soil Taxonomy and Subaqueous Soils of a Riverine-Estuarine System.........................78 Summary........................................................................................................................ .........79 4 THE SIMULTANEOUS QUANTIFICAT ION OF SHORT-TERM BENTHIC NITRATE REACTIONS AND DIFF USE GROUNDWATER SEEPAGE..........................93 Introduction................................................................................................................... ..........93 Short Timescales.............................................................................................................93 Methodological Precision................................................................................................95 Influence of Diffuse Groundwater Seepage....................................................................96 In Situ Nutrient Analyses................................................................................................98 Conceptual Introduction to the Method Proposed by this Study............................................98 Materials and Procedures................................................................................................99 Environmental Data.......................................................................................................100 Method Assessment.............................................................................................................. 101 Site Description: Chassahowitzka River.......................................................................101 Chamber Deployment....................................................................................................102 Benthic Flux and Biogeochemi cal Reaction Calculations............................................103 Calculating SGD and SGD-Dr iven Influences on NO3 Additions and Losses............104 Results........................................................................................................................ ...........105 Diel Variation................................................................................................................1 05 Benthic Reactions and E nvironmental Variability........................................................106 NO3 Additions and Losses and Their Relationships to Environmental Parameters.....106 Submarine Groundwater Discharge..............................................................................107 Data Interpretation............................................................................................................ ....107 Discussion..................................................................................................................... ........110 Comments and Recommendations.......................................................................................111 5 SYNTHESIS: BIOGEOCHEMICAL DYN AMICS OF SUBAQUEOUS SOILS IN THE CHASSAHOWITZKA SPRINGFED RIVER AND ESTUARY..............................123

PAGE 8

8 APPENDIX A SUPPORTING SOIL PHOTOS AND MINERALOGICAL ANALYSES.........................125 Riversides..................................................................................................................... ........125 Blue Crab...................................................................................................................... ........127 Midden Flats................................................................................................................... ......129 Chass Sands.................................................................................................................... ......130 B RAW FLUX MEASUREMENT DATA..............................................................................139 LIST OF REFERENCES............................................................................................................. 155 BIOGRAPHICAL SKETCH.......................................................................................................163

PAGE 9

9 LIST OF TABLES Table page 2-1 Datasets relevant to the Ch assahowitzka River and Estuary.............................................40 2-2 Transect 1 mean nutrient concentr ations summarized by classification............................41 2-3 Mean annual mass loads over the period of 1998-2006 at Transect 1...............................42 2-4 Average inorganic concentrations of N and P during the Low loading period.................43 2-5 Average inorganic concentrations of N and P during the High loading period.................43 2-6 Net apparent riverine nutrient lo ss rates during the Low loading regime..........................44 2-7 Net apparent riverine nutrient lo ss rates during the High loading regime.........................44 2-8 Percentage of inorganic nutrient load lost between RIVERS transects 1 and 5................44 2-9 Significant differences in dow nstream nutrient concentrations.........................................45 3-1 Subaqueoues soil map units and their charactreristics.......................................................81 3-4 Chass Sands (ChS) typical pedon desc ription and taxonomic identification....................84 3-5 Riversides (RvS) typical pedon desc ription and taxonomic identification........................84 3-6 Blue Crab (BlC) typical pedon desc ription and taxonomic identification.........................85 3-7 Midden Flats (MdF) typical pedon desc ription and taxonomic identification..................85 4-1 Incubation-based rates of change.....................................................................................114 4-2 Estimates of submarine groundwater discha rge (diffuse porewater seepage) rates........115 B1 Five minute dataset of ch amber and environmental data.................................................139 B2 Five minute database of solar irradi ance, redox probes, and panel temperature.............146 B3 Thirty minute dataset including raw NO3 data................................................................153

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10 LIST OF FIGURES Figure page 1-1 Overview of the Chassahowitzka Springshed and its River and Estuary..........................20 2-1 Floridan Aquifer Vulnerability classification....................................................................46 2-2 Soil permeability, sinkholes, and the Chassahowitzka NO3 gradient...............................47 2-3 Land-uses (2005) in the Chassahowitzka Springshed.......................................................48 2-4 The RIVERS dataset water quality monitoring stations....................................................49 2-5 The RIVERS sampling transects 1-5.................................................................................50 2-6 Interannual variation of precipitation, discharge and salinity at Transect 1......................51 2-7 Average monthly precipitation and di scharge on the Chassahowitzka River....................52 2-8 Mean monthly air temperature and th e percentage of pot ential insolation........................53 2-9 Boxplots of interannual time scale variation in nutrients...................................................54 2-10 Regression of total annual pr ecipitation to average annual NO3 concentration...............55 2-11 Regression of annual mean discharge to annual mean NO3 concentration.......................55 2-12 Regression of annual mean discharge to soluble reactive phosphorus concentrations......56 2-13 Interannual variability of precipitation and discharge.......................................................57 2-14 Rates of NO3 losses as summarized by class....................................................................58 2-15 Rates of soluble reactiv e phosphorus losses by class........................................................58 2-16 Boxplots of NO3 concentration summarized by class combinations................................59 2-17 Boxplots of NO3 concentration summarized by transect and class combinations............60 3-1 Aerial photo mosaic of the Cha ssahowitzka River and Estuary (1995)............................86 3-2 Aerial photographs (194 4 and 1999) of the study area......................................................87 3-3 Soil reconnaissance site descriptions and typica l pedon sampling locations....................88 3-4 Subaqueous soil map of the Chassahowitzka River and Estuary......................................89 3-5 Soil pH and related factors................................................................................................ .90

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11 3-6 Soil nutrient data and stoichiometric ratios.......................................................................91 4-1 Relationship of sampling inte rvals and the method precision.........................................116 4-2 Schematic of benthic chamber instru mentation and deployment configuration..............117 4-3 Diel variation in environmental pa rameters and rates during incubations......................118 4-4 Regression lines of variables m easured during chamber incubations.............................119 4-5 Nitrate losses and their relationship to NO3 concentration..............................................120 4-6 Relationships between submar ine groundwater discharge and NO3 losses....................121 4-7 Submarine groundwater discharge as related to water column elevation........................122 A-1 Riversides soil core and micros copic images for reference purposes..............................125 A-2 Riversides soil core near on the lateral edge of Crab Creek............................................126 A-3 Blue Crab soil core and micros copic images for reference purposes..............................127 A-4 Blue Crab soil core with a large krotovina......................................................................128 A-5 Midden Flats soil core and micros copic images for reference purposes.........................129 A-6 Chass Sands soil core for reference.................................................................................130 A-7 Chass Sands augered soil sampled during reconnaissance work.....................................131 A-8 Chass Sands soil core with a clay-enriched horizon at its base.......................................132 A-9 Subsample from clay enriched horizon............................................................................133 A-10 Microcopic photo of biomineralization site.....................................................................133 A-11 Microscopic photo of biomineralized spherules..............................................................134 A-12 Microscopic photo of biomin eralized framboidal pyrite.................................................134 A-13 What appear to be iron-based, rounded minerals.............................................................135 A-14 Differential scanning calo rimetry results for clays..........................................................135 A-15 X-ray diffraction results fr om clay and silt fractions.......................................................136 A-16 Scanning electron microscope image of minerals...........................................................136 A-17 Scanning electron microscope image of Framboidal pyrite............................................137

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12 A-18 Augered soil from the densely vegetated channel of Crab Creek....................................138

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13 Abstract of Dissertation Pres ented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy MULTI-SCALE ANALYSIS OF BENTHI C BIOGEOCHEMICAL PROPERTIES AND PROCESSING IN SPRING-FE D RIVER AND ESTUARY By Thomas John Saunders December 2007 Chair: Mary E. Collins Cochair: Thomas K. Frazer Major: Soil and Water Science Transparent freshwater rivers emerge from co astal spring boils along th e karst northeastern shore of the Gulf of Mexico a nd drain into the estuaries of Florida's coastal salt marsh. The resulting physical and chemical gradients in wa ter properties and benthic substrate grade from freshwater/riverine to brackish/e stuarine environments and provide an ideal environment for the study of subaqueous soils and biogeochemical cycling. Multi-year (1997-2007) monitoring programs have demonstrated that inorganic nutrient s are consistently and ra pidly utilized within the Chassahowitzka River and Estuary, yet many questions remain as to the controls and thresholds of nutrient attenuati on processes. A meta-analysis of seasonal and interannual-scale nutrient dynamics in the Chassahowitzka Ri ver and Estuary demonstrated that NO3 concentration was significantly related to precipitation and discharge and that NO3 -uptake within the river was consisten tly 30% of its load. Soluble reactive phosphorus (SRP), in contrast, was not significantly related to precipitation or disc harge, and its uptake remained relatively consistent regardless of load, though SR P concentration varied significantly between seasons. Spatially distributed nutrient flux estim ates derived from massbalance calculations suggest that the benthic envi ronment provided a strong contro l on nutrient cycling in this

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14 system. Subaqueous soils were mapped throughout the River and Estuary. Soils varied widely in their content of total carbon (range 1-197 g/ kg; median 45 g/kg), tota l nitrogen (range 0-17 g/kg; median 3 g/kg), and total phosphorus (r ange 50.5-2481 mg/kg; median 152 mg/kg). Hand texture (mucks to gravels), soil electrical conductivity (0.97-11.46 dS/m ), and molar nutrient stoichiometric ratios also highlighted the distin ct properties of subaqueous soils mapped within the system. Finally, a novel chamber-based me thod was designed, constructed, and tested to quantify in-situ benthic NO3 fluxes at a high-temporal reso lution. Results from multiple flux measurements made over a 24-hour deployment period demonstrated the utility of the methodology and produced detailed info rmation regarding controls on NO3 processing at the study site. Diffuse porewater seepage was al so calculated and ranged from 46-176 L/m2/day. Porewater seepage was significantly related to benthic NO3 fluxes through two distinct modes of influence: conservative dilu tion and non-conservative (biologi cally-mediated) reactions.

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15 CHAPTER 1 INTRODUCTION The Coast as a Natural a nd Anthropogenic Interface The coastal environment stands out as one of the most abrupt interfaces on the planet. The boundary of terrestrial and oceanic ecosystems is a crossroads of distinct biogeochemical endmembers characterized by physical and chemical gradients that exist over relatively short distances. In turn, many organisms and biogeoche mical processes thrive amidst the mixing of resources and energy, making the coastal and associ ated estuarine environm ent one of the most biologically productive regions on th e planet (Jickells and Rae, 1997). As rivers drain the terrestrial system, they carry with them the cumulative biogeochemical signature of their watershed, making the coastal and estuarine environment a “melting pot” where the effluents of terrestrial world meet th e reservoir of the ocean. Home to vast human populations, coastal environments have attracte d human populations since time immemorial and the resulting anthropogenic disturbance of the co astal environment has been widely recognized (Kennish, 2002; Paerl, 2006). Though conditions in some estuaries have been significantly altered by human activity, the natural system has a capacity to “absorb” some degree of anthropogenic impact, providing intrinsic “treatme nt” to human-borne contamination. Given the coast’s role in assimilation and processing of anthropogenic effluents, two important questions asked regarding many coastal and estuarine system s are, “Just how much can a system “absorb” before becoming damaged or dysfunctional?” an d “What in-situ mechanisms control pollution attenuation and/or processing?” Exceeding the assimilative capacity of the coastal riverine and estuarine systems has resulted in heavy metal contamination entering the estuarine food–web, eutrophication, and harmful algal blooms (K ennish, 2002; Paerl, 2006). Many of these

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16 environmental predicaments have significant ne gative feedbacks on local economies, health, and the integrity of the natural system. Interfaces at Interfaces: the Role of Bent hic Biogeochemical Processes in the Coastal System Within the large-scale terrestrial /oceanic interface a myriad of “sub-interfaces” exist, all of which have some potential to catalyze a variet y of biogeochemical reactions. Of those, the benthic/surface-water interface, given its juxtaposition of electron donors and acceptors, stands out as a potential hotspot for biogeochemical activity. Generally, the chemically reduced environment of the benthic environment forms a strong gradient with the oxidized environment of the surface water above. Microbial communitie s exploit that gradient to capture energy in support their life-processes, often resulting in important reactions such as nitrification, denitrification, SO4 2reduction to H2S, and the oxidation of a variety of organic compounds. Porous sands commonly encountered in many coastal benthic environments have low organic matter (OM) contents, generally rema in oxidized, and receiv e advective inputs of dissolved and particulate organic carbon. These sands also provide a surface for the reactive processes of microbial communities, thereby earni ng the title of “biocatalytical filters” from some researchers (Huettel et al., 2003). Due to its heterogeneity and associated biogeochemical reactivity, the benthic substrate in many coastal and estuarine envi ronments has the potential to significantly alter the concentrations and sp eciation of a vast number of natural and anthropogenic chemical compounds. In fact, nut rient release via mineralization processes occurring in benthic environments often supports a large portion of prim ary production occurring in the water column, especially in sha llow estuaries (Niencheski and Jahnke, 2002).

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17 Subaqueous Soils In many environments, the geologic past has shaped the template upon which present-day environmental drivers control the composition of the upper portions of the Earth surface. The transformation of original sedimentary material into “soil” depends on the factors which drive that material toward its equilibrium with the en vironment. In the terrestrial realm, controlling factors have become known as “soil forming fact ors” and include climate, organisms, relief, parent material, and time (Jenny, 1941). Recently, soil scientists have applied this same paradigm to subaqueous environments, adding th e factors of water-column characteristics, bathymetry, and flow (Demas and Rabenhorst, 2001). Regardless of the environment, soil properties reflect the equilibrium condition of a variety of soil forming factors at work over a specific area. Soil properties affect land-use, habitat quality, and th e role each soil has in the environment (i.e. its biogeochemical function). As a scientific understa nding of environmental controls on the physical and chemical charact eristics of subaqueous soil emerges, this information can be applied to understand how al tered exposure regimes of soil forming factors will influence both human utilization and the natu ral role that subaqueous soils play in the environment. In a number of estuaries and nearshore coastal environments soil scien tists have begun to map what has traditionally been referred to as sediment using a soils-based approach (Bradley and Stolt, 2002; Bradley and Stolt, 2003; Demas and Rabenhorst, 2001; Demas et al., 1996; Ellis, 2006; Fischler, 2006). Soil surveys and res ource inventories can be used as a source of information for academic and applied research. Examples of the potential uses for subaqueous soil maps include identifying locations for oyste r production, seagrass ha bitat restoration, and benthic habitat mapping for a variety of aquatic organisms (Bradley and Stolt, 2002; Bradley and Stolt, 2006; Demas and Rabenhor st, 1999; Ellis, 2006; Fischler 2006). Academic researchers

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18 from diverse fields can utilize subaqueous soil maps as a basemap for ecological or environmental research. To date, limited numbers of subaqueous soil survey s exist, despite their potential value in the study and management of coastal resources. The Chassahowitzka River and Estuary The Chassahowitzka River and Estuary (Figure 1-1) along FloridaÂ’s Springs Coast is one area where subaqueous soil may be particularly info rmative, especially for the interpretation and study of anthropogenic impacts and biogeochemical processes operating within the system. This first-magnitude spring-system drains a watershe d that has become increasingly influenced by a growing population (Jones et al., 1997; Sco tt et al., 2004). Anthropogenic impacts in the Chassahowitzka River are dominan tly expressed as increased NO3 concentrations at the headspring which drains to an estuarine environmen t and eventually the Gulf of Mexico (Frazer, 2000; Jones et al., 1997). The domin ant source of this inorganic fo rm of N was attributed to residential and golf course ferti lization (Jones et al., 1997). Concen trations at headsprings were reported to have increased from 0.01mg/L to over 0.5mg/L since the 1960s, a greater than 50 fold augmentation (Frazer, 2000; Jones et al., 199 7). Biological contamina tion indicated by fecal coliforms and pathogens traced to local sewage systems was also repor ted within the spring water and along the upper spring run of the Ch assahowitzka (Callahan et al., 2001). Increased nutrient concentrations have the potential to ca use algal blooms and st imulate the process of eutrophication, which could ultimately damage th e natural resource base and the existing tourism and fishing economies that depend on it (Pinckne y et al., 2001). The Chassahowitzka River and Estuary also provides ecologically important habitat for the West Indian Manatee and migratory bird populations. A large portion of the river an d estuary is protected as the Chassahowitzka National Wildlife Refuge.

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19 Water quality monitoring along the Chassahowit zka River and Estuary has been conducted since the late nineties and many interesting trends in biogeoche mical change along the riverineestuarine gradient have been elucidated (Frazer et al., 2001). One of the most notable spatial trends along the Chassahowitzka River is the dramatic decline in NO3 concentrations from the headspring toward the estuary. However, the do minant environmental factors controlling the decreasing NO3 concentrations have not been identif ied. Therefore, many important questions regarding biogeochemical cycling still remain, incl uding: “what is the role of subaqueous soils in the NO3 cycling along the spring run and in the es tuary”; “are subaqueous soils a dominant NO3 sink within the spring run and in the estuary?”; and “if so, wh ich subaqueous soils play the dominant role in nutrient cycling an d what is their spatial distribution? Objectives The objectives of this research were: to quantify the spatial and temporal variability of nutrient concentrations, loads, and distributi on over seasonal and in ter-annual timescales (Chapter 2), to map the distribution and quan tify the properties of s ubaqueous soils along a freshwater-estuarine gradient (C hapter 3), and to develop and evaluate a novel method for the high-resolution in-situ measuremen t of benthic nitrate fluxes a nd their environmental drivers (Chapter 4). The overarching obj ective of this research was to characterize the large-scale variability of nutrient source and cycling and ev aluate the properties of subaqueous soils and their influence on nutrient cycling on the Chassahowitzka River and Estuary.

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20 Figure 1-1. Overview and location of the Chassahowitzka Springshed and its river a nd estuary with respect to the state of Flori da. Imagery of the region indicates land-use and anthropogenic distur bance in the springshed and is composed of a mosaic of true-color digital orthophotos made available by the Southwest Florida Wate r Management District (SWFWMD, 2007)

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21 CHAPTER 2 SEASONAL AND INTERANNUAL DYNAMICS IN THE SOURCE, CYCLING, AND FATE OF NUTRIENTS IN A COASTAL SPRING-FED RIVER AND ESTUARY Introduction Estuaries are characterized by diverse physical and chemical properties, high rates of biological productivity, and are in creasingly impacted by anthropoge nic activities (Flindt et al., 1999; Paerl, 2006; Wall, 2004). In most estuaries, including those of Florida, nitrogen and phosphorus (N and P) are often important limiting f actors of primary productivity (Bricker et al., 2003; Frazer et al., 2002; Notestein et al., 2003; Pinckney et al., 2001). Human activity has increasingly altered N and P inputs to many estuarine system s (Bowen and Valiela, 2001; Nedwell et al., 1999; Paerl, 2006), in creased inputs of trace metals (Hanson et al., 1993; Trimble et al., 1999), and introduced biolog ical contaminants (Mallin et al., 2000). Given the sensitivity, productivity, and global importance of estuaries, understanding and managing human alterations of estuarine resources has beco me one of the most important natural resource management priorities (Pinckney et al., 2001). The amount of N available at the global scale has dramatically increased through industrial N-fixation, cultivation of leguminous crops, and fo ssil fuel combustion, thereby altering exports of dissolved inorganic nitrogen (DIN) to coastal regions (Glibert et al., 2006; Seitzinger et al., 2006; Seitzinger et al., 2005; Seit zinger et al., 2002). Delivery of dissolved inorganic phosphorus (DIP) to estuaries have also in creased globally due to fertilizer application, dairy wastes, and wastewater discharges (Harris on et al., 2005). However, terrestr ial retention of DIP is often much greater when compared to that of DIN, an d natural weathering sources are often significant (Harrison et al., 2005; Seitzinger et al., 2005). Excess nutrient load ing to estuaries has in many cases resulted in cultural eu trophication, algal blooms, and a ssociated negative impacts on the health and ecological function of estuarine envi ronments (Bowen and Valiela, 2001; Nedwell et

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22 al., 1999; Paerl, 2006; Pinckney et al., 2001). Many es tuaries, including thos e in Florida (Frazer et al., 2006), have some ability to naturally attenuate anthropoge nically increased nutrient loads. Therefore, aside from their historic roles in biological productivity, coas tal shoreline protection, and as habitat for diverse species assemblages, es tuarine systems have also assumed the role of “biological filter” or “contaminant buffer” between anthropogenic effluents and adjoining coastal environments (Dauer et al., 2000; Paerl, 2006). The estuarine role in assimilation, processing, and “treatment” of hu man-derived nutrients is seldom as evident as that measured in th e coastal riveri ne and estuarine ecosystems of Florida’s Gulf Coast. Resulting largely from th e high porosity of the karst formations making up the Floridan Aquifer, groundwater resources are impacted by terrestrial ac tivities (Figure 2-1) through sinkholes, permeable soils (Figure 2-2) and elevated precip itation rates common in subtropical environments (Scott et al., 2004). In contrast to most watersheds, coastal Floridian springsheds are not fed by multiple surficial stream s. Coastal spring-runs are therefore the direct surface-water linkage between estuaries and the incr easingly impacted terrestrial aquifer (Scott et al., 2004). Dissolved chemicals such as NO3 are transported from Florida’s landscape to springheads, perhaps with mini mal reactive processing during tr ansport (Jones et al., 1997). Spring-runs concentrate runoff from their springs hed and are therefore subject to a spatially disproportionate load (total ma ss per unit time) of nutrients an d associated contaminants in comparison to the remainder of the springshed. Florida is currently facing environmental problems resulting from the interaction of a burgeoning human population, an aq uifer susceptible to human impact, and a coastal and estuarine environment closely linked to the terrestria l aquifer. This interaction has led to distinct increases in NO3 concentrations through time in coastal and terrestrial springs across the State

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23 (Champion and Starks, 2001; Frazer et al., 2001; Jones et al., 1997; Katz et al., 2001b; Scott et al., 2004). High NO3 concentrations arriving at headsprings are subsequently diminished as surface waters are transported dow n the spring-run, resulting in a strong spatial concentration gradient from spring-source to estuary in a num ber of coastal spring-fe d rivers (Frazer, 2000; Frazer et al., 2001; Frazer et al., 2003). This upstream-downstream concentration gradient (Figure 2-2) highlights the role of the coasta l spring-fed river and estuary in “mitigating” anthropogenically elevated NO3 concentrations from the Florid an Aquifer and springs. Soluble reactive phosphorus (SRP) concentrations also dramatically decrease along this gradient, possibly indicating a utilization of available P in the system. Despite well-documented decreases in nutrient concentrations along spring-runs, the capacity of spring-runs to process elevated nutrient inputs, the mechanisms controlling thes e processing rates, a nd the spatio-temporal variability in nutrient dynamics are currently poorly understood. Thus, the specific objectives of this study were to: (i) character ize the seasonal and interannual variation of the con centration and load of N and P in spring source waters; (ii) evaluate relationships between spring-source concentra tion and environmental drivers such as precipitation and discharge; (iii ) estimate the proportion of N and P retention and processing along the upper reaches of the sp ring-run during distinct nutrient loading regimes, and (iv) examine the relationship between variation in nut rient load at the head spring and nutrient supply to the river/salt marsh boundary. The Chassahowitzka River flows from a first-magnitude (flow >2.8m3/s) spring system draining a springshed of approximately 23,700 hectares to the Gulf of Mexico (Figure 2-1). The research presented here focuses on the Chassa howitzka Springshed and drainage complex, though many of the issues, character istics, and processes may be relevant to a much larger area

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24 of coastal and terrestrial spring-fed systems in Florida. Land-use in th e springshed (Table 2-1, Figure 2-3) includes low (1,469 hectares), me dium (768 hectares), and high-density (88.6 hectares) residential areas, multiple golf-course s (334 hectares), and pasture and farm lands (2,337 hectares). Each of these land-uses is know n to contribute N and/or P to the terrestrial landscape via fertilization, animal wastes, and surface water runoff from impervious surfaces (Jones et al., 1997). The Chassahowitzka, like many other coastal spri ng-fed rivers, is currently undergoing an increase in NO3 concentrations as a result of anthropogenic land-use and NO3 loading (Jones et al., 1997; Scott et al., 2004). Elevated NO3 concentrations in many of FloridaÂ’s springs result from a variety of anthropogenica lly introduced organic and inor ganic N sources (Jones et al., 1997; Katz, 2004; Katz et al., 1999a; Katz et al., 1999b; Katz et al ., 2001a; Katz et al., 2001c). Stable NO3 --N isotopic data from Chassahowitzka Rive r spring complex specifically implicated inorganic N sources likely de rived from fertilizers (Jones et al., 1997). The average water residence time within the aquifer prior to spri ng discharge has been estimated as 5-35 years based on geochemical studies and groundwater tracer s in a variety of Floridian spring systems (Jones et al., 1997; Katz et al ., 2001c; Toth and Katz, 2006). Methods Data Sources Quarterly and monthly surface water monitori ng programs (Frazer et al., 2006; Frazer et al., 2001; Frazer et al., 2003) were conducted over a ten-year period, providing an opportunity to evaluate seasonal and interannual variation in the concentration, load, distribution, processing, and fate of nutrients in the Ch assahowitzka River and Estuary. The datasets utilized for both qualitative mapping and quantitative analyses ar e listed in Table 2-1. The methods utilized in creating these datasets are covered in detail by each of the author s or data sources. All spatial

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25 data was assembled into a geodatabase usi ng ArcGIS 9.1 (ESRI; Redlands, CA, 2005) for analysis. Data that quantified environmental variables and wa ter quality parameters were assembled and evaluated to identif y trends, relationships, and the st atistical distributions of each parameter of interest. All statistical analyses were carried out using S-Plus 6.1 (Insightful Corporation; Seattle, WA, 2002). Water quality monitoring data from 1998-2006 (missing data in 2002) for the Chassahowitzka River and Estuary was assembled fr om two reports: the “Five Rivers” (Frazer et al., 2006; Frazer et al., 2001) and “Three Rivers” (Frazer et al., 2006) water quality monitoring programs. This combined dataset used here is re ferred to as the “RIVERS” data. Data from both reports were sampled from the same monitoring lo cations and chemically analyzed in the same laboratory. The RIVERS data consist of 20 mon itoring sites extending from the springhead into the estuary, the first 15 of which have a three-stat ion transect perpendicular to the main channel (Figure 2-4). Analytes of intere st to this study are listed in Table 2-1. A separate monitoring program, titled Project COAST (Frazer et al ., 2007), produced a monthly dataset from 19972006 with fewer analytes and sample sites (Table 2-1), though covering a la rger area. In this study, COAST data were used in addition to the RIVERS dataset to evaluate temporal dynamics in spring source nutrient concentrati ons at Transect 1 (Figure 2-4). Spring Source: Quantifying Seasonal and Interannual Variation Transect 1 of the RIVERS and COAST m onitoring programs on the Chassahowitzka is adjacent to the headspring and data was availa ble at monthly and quarterly intervals from 19972006. A United States Geological Survey (USGS) stream discharge gauging station is also located just below the main headspring providing relatively continuous hydrologic flow data for the spring source. Based on the discharge and wa ter quality information assembled, multi-year variability in both NO3 concentration and discharge were divided into “Low” and “High”

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26 loading classes (method described below). Season wa s classified as either “Wet” or “Dry” based on average seasonal variation of sp ring water temperature at Transe ct 1. Water temperatures are higher during the wet season in Florida. Temp erature ranged from 20.8-25.9C, was statistically normally distributed, and had a mean value of 23.36C and a median of 23.42C. All samples with a temperature equal to or greater than 23.4C were considered re presentative of the Wet season while the remaining samples were classified as Dry. In almost all cases, the Wet season included samples collected in th e months of April through August, while the remainder of the year was considered the Dry season. One-way analysis of variance (ANOVA) was used to test fo r significant differences in nutrient concentration between seasonal or loading classes, or for season:loading class interactions (Table 2-2). Intera nnual variability in nut rient concentration at the headspring was compared with regional and loca l variations in precipitation a nd discharge using mean annual data from both the RIVERS and COAST datasets Relationships between regional environmental variables and nutrient concentrations at the h eadspring were evaluated for significance using linear regression statistical parameters. River and Estuary: Calcul ation of Nutrient Loads Annual nutrient loads at the headspring (Trans ect 1) were calculat ed as the product of mean annual discharge and mean annual nutrient concentr ations at the head spring. A substantial increase in the load of N (~60% increase) and P (30% increase) was observed during a two year Low loading period (April 2004-Feb 2006) relative to a two year High lo ading period (April 1999-Feb 2001) as highlighted in Table 2-3. These two distinct loading regimes provided the opportunity to analyze a natural nut rient loading experiment where two distinct treatments (Low and High regimes) of nutrient loading were main tained in the system, each for a period of two years. The RIVERS data were chosen to analyze tr ends resulting from these treatments due to the

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27 higher density of sampling points and multiple sa mples taken at each transect. RIVERS data were therefore classified into High (A pril 1999-Feb 2001) and Low (April 2004-Feb 2006) loading regimes based on observed mass loads presented in Table 2-3. To detect downstream delivery of nutrients fu rther into the estuary, nutrient concentrations were evaluated between each loading regime clas s (High and Low) and season (Wet and Dry) at Transect 10 using the RIVERS dataset (Figure 2-4). Transect 10 is at the boundary of the freshwater-dominated channel and a salt-marsh mixing zone based on the distinct shift to common salt-marsh vegetation. The location of this boundary (Figure 2-4) serves as a useful site to determine whether changes in upstream nut rient loading are transferred downstream. Statistical analyses to test seasonal and load ing differences in nutrient concentrations were applied as described for Transect 1. Spatial differences in nutrient concentrati ons were also evaluated qualitatively using boxplots of concentration distributions as gr ouped by season, loading regime, and sampling transect. Boxplots provide a number of statistical measur es in one convenient and intuitive graph including: the sample median (indicated by line and point with in the box); the data range (indicated by the highest and lowest values); the upper and lower quartile s (the upper and lower edges of the solid box); data sk ewness (indicated by how centered the median is within the box); and suspected outliers (indicated by points beyond the upper and lower bracke ts). Outliers were determined as those data with values 1.5 times greater than th e inter-quartile range. Calculation of Spatially Dist ributed Net Nutrient Losses From the RIVERS dataset, transects 1-5 (Fi gure 2-5) were chosen for an evaluation of spatially distributed net nutrient losses. Transe cts 1-5 are the furthest upstream and therefore subject to minimal dilution with more NO3 depleted, saline waters compared to areas further downstream in the system. For example, over th e study period, mean salinity concentrations

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28 increased from 1.74 to 1.87ppt between transects 1 and 5 while mean NO3 concentrations decreased from 456.5 to 320.6g/L. The slight incr ease in salinity suggested minimal dilution by high salinity estuarine waters. A two-source mi xing model was used to calculate the amount of dilution occurring between transects 1-5, gi ven the mixing of waters from two different sources: transect 1 (low salinity) and transect 20 (high salinity). The percentage of water from transect 20 added between transects 1 and 5, V%, was calculated as: V% = ((CT1 – CT5)/( CT1-CT20))*100 (2-1) where V% = the percentage of water from trans ect 20 added between transects 1 and 5, CT1 = the salinity at transect 1 (1.74ppt), CT5 = the concentration at transect 5 (1.87ppt), CT20 = concentration at transect 20 (15.6ppt). V% accounted for approximately a 1% dilution of water from the spring-run with waters from NO3 depleted estuarine waters. Therefore, the role of dilution with estuarine waters was assume d to be minimal between transects 1-5. Rates of spatially distributed net nutrient losses (including dilution) for unique combinations of seasonal and loading classes were calculated as follows: L=(Cd-Cu)*D/Au-d (2-2) where L = rate of spatially distri buted net nutrien t losses (mg/m2/day), Cd = nutrient concentration of downstream transect (mg/L), Cu = nutrient concentratio n of upstream transect (mg/L), D = discharge rate (L/day) and Au-d = the river surface area (m2) between the upstream and downstream transects of interest. The average nutrient concentrations and discharge rates for each given season and load classification are pr ovided in Tables 2-4 and 2-5 and the area between transects is shown in Figure 2-5. Th e area between transects was quantified by digitizing the stream channel between sampling transects and performing an area calculation using ArcGIS 9.1 (ESRI, 2005; Figure 2-5). Spatial rates of nutrient losse s therefore represented

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29 all processes affecting nutrient concentrations in the area between the upstream and downstream transects. Results Seasonal and Interannual Variation Total annual precipitation range d from 102-172 cm and total m onthly precipitation ranged from 7-18 cm seasonally (Figures 2-6 and 2-7) during the study period. Ai r temperature varied with precipitation within the year while the per centage of potential sunshi ne arriving at the land surface was likely modified by cloud formation during the rainy season (Figure 2-8). At the inter-annual timescale, natural va riation resulted in two multiyear periods with distinct precipitation, discharge, and salinity conditions. Spring Source: Variation and Interrelationships At the spring source (Transect 1), TN (P<0.001) and NO3 (P<0.001) concentrations were significantly higher during under High loading conditions (RIVERS data; Table 2-2,). Statistically significant interactions of s eason and load were also detected for NO3 concentrations (RIVERS data; Ta ble 2-2). Concentrations of SR P and TP were not significantly different between loading classes (RIVERS data; Table 2-2), suggesting a relatively consistent concentration of P regardless of intera nnual variability in discharge rates. Annual mean NO3 concentration (RIVERS) was signi ficantly related to precipitation (r2 = 0.73; P < 0.05; Figure 2-10) and discharge (r2 = 0.60, P < 0.05; Figure 2-11). Total phosphorus (COAST) and SRP (RIVERS) concen trations (e.g. Figure 2-12) were not significantly related to either precipitation or discharg e at the interannual timescale (r2 = 0.03, P = 0.98). However, total phosphorus and SRP concentrations were significan tly different between seasons (RIVERS data; Table 2-2). Nitrate concentration at the headspring was not signi ficantly different (P = 0.067) in response to season.

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30 River and Estuary: Nutrient Load Processing Mean nutrient concentrations tabulated for each season and loading class for each of the upper 5 transects of the RIVERS database are presented in Table 2-4 and Table 2-5. Monthly precipitation and discharge for the Low and High lo ading class periods of study are presented in Figure 2-13. These data constitute the data utilized for the calculation of the between-transect mass consumption rates reported in Table 2-6 and Table 2-7. Median NO3 and SRP losses were most negative during the Wet season of the High loading regime (-486 and -14.2 mg/m2/day, respectively; Figure 2-14, Figure 2-15). Nitrate losses were smallest during the Dry season and Low loading class (-214 mg/m2/day). The smallest SRP c onsumption occurred during High loading and Dry season conditions (-6.7 mg/m2/day). Table 2-8 highlights the percentage of the incoming mass nutrient load utilized between Transects 1 and 5 under Low and High interannual loading conditions. Nitrate loads we re utilized in proportion to the total load (cons istently ~30% of total load removed). In contrast, 39% of the SRP load was removed under Low loading conditions while only 25% was rem oved under High loading conditions. To evaluate whether interannual and seasonal va riability in water quality at the spring source had a significant impact on downstream nutr ient concentrations, Transect 10 (see Figure 2-4) of the RIVERS dataset was selected for statistical analysis. A number of significant differences between season and loading conditio ns were observed at Transect 10 and are summarized in Table 2-9. Briefly, both NO3 and SRP concentrations we re significantly higher during the Dry season as compared to the Dry season. Nitrate concentrations also differed significantly between the Low and High load ing periods, increasing from 120 to 215 g/L, respectively. Total N, SRP, and NO3 concentrations all responded to significant seasonal/loading interactions. Salinity values at Transect 10 were significantly lower during the high loading

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31 period (data not shown); indicati ng increased freshwater discharg e which likely resulted in a decreased hydrologic re sidence time within the upper river reaches. Spatial trends in nutrient concentrations from the source toward the estuary were summarized by transect using boxplots according to season and load (Figures 2-16 and 2-17). Nitrate concentration showed c onsistent generalized trends in spatial distribution between seasons, dramatically decreasing from the headsp ring toward the coast (Figure 2-16). Soluble reactive phosphorus concentrations follow a si milar decreasing pattern to that of NO3 concentrations (Figure 2-17). Discussion Temporal Variability of Spring Source Nutrient Concentrations The Chassahowitzka River and Estuary is su bject to marked interannual and seasonal variability in precipita tion, discharge, and nutrient loadi ng. At the headspring, significant differences in nutrient concentrations were detected at interannual (NO3 and TN) and seasonal (SRP, TP) timescales. FloridaÂ’s karst geology is known to foster relativ ely rapid connections between terrestrial N additions and springhead nutrient concentrations (Katz et al., 2001b). Based on the significant positive relationship between precipitation and NO3 concentration observed in the interannual monitoring data, it appears that groundwaters with elevated NO3 concentrations emerged at the springhead over re latively short timescales (less than one year). Indeed, during synoptic sampling of a variety of FloridaÂ’s springs it has been determined that spring water is a mixture of older waters and younger, more-recently rech arged waters (Toth and Katz, 2006). In select springs of Florida, the resp onse of spring chemistry to storm events also demonstrated rapid connectivity between recent pr ecipitation and the water discharging from the springhead (Martin and Gordon, 1997). In fact, NO3 concentrations in water discharging from springs appeared to be particularly sensitiv e to precipitation events (Martin and Gordon, 1997).

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32 Unfortunately, there has been no thorough assessme nt of the variability of the age of spring source water through varying seasonal discharge conditions or associated with large storm events. However, recently-derived, highNO3 concentration waters have been noted in several spring systems (Jones et al., 1997; Katz et al., 2001c; Toth and Katz, 2006). The relationship between average annual NO3 concentration and annual precipitation is quantified by the line shown in Figure 2-10 where [NO3 -] g/L = 2.36*cmprecip + 196.5. The yintercept suggests that the NO3 concentration at zero precipitati on of waters discharging at the springhead is roughly 19786.5 g/L (meanstandard error). Annua l precipitation appears to increase NO3 concentration by approximately 2.4 g/L for every centimeter of precipitation. This relationship, though coarse, suggests th at although there is a background NO3 concentration in the aquifer, interannual varia tion in precipitation has a str ong influence on the ultimate NO3 concentrations in the Chassahow itzka River and Estuary. The NO3 source related to precipitation is likely some mixture of atmospherically-derived NO3 as well terrestriallydeposited N compounds (i.e. inorganic fertilizers, human and animal waste; Jones et al., 1997). The significant relationship of NO3 to both precipitation and disc harge may have also been influenced by physical mixing processes at the sp ringhead. For example, the interannual salinity variations shown in Figure 2-6 appe ared inversely-related to discha rge. Therefore, as the water table of the aquifer fell, waters discharged at the headspring become increasingly diluted by saline marine water (in the aquifer and in the channel). Physical dilution by saline waters, assuming they have lower NO3 concentrations than fresh Floridan Aquifer waters, may have accounted for some of the temporal variability in NO3 concentrations observed at the headspring. However, as the transects analyzed were of the uppermost reach, dilution was likely not a significant factor. The correlation between mean annual NO3 concentration and annual

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33 precipitation was stronger than that between mean annual NO3 concentration and annual discharge. This suggest ed that fresh highNO3 concentration water derived from recent precipitation was most important in contributing to variation in NO3 concentrations. Mean NO3 concentrations remained consistently elevated during the High loading regime, regardless of season. This is likely due to a bundant amounts of freshly-recharged groundwater feeding the spring throughout the year and lim ited dilution as discussed above. In contrast, during the Low loading regime, NO3 concentrations were signif icantly different between Dry and Wet seasons (P<0.05). During th e Low loading period, the highest NO3 concentrations occurred during the Dry season, c oncomitant with the ar rival of the discharge pulse related to that seasonÂ’s rainfall at the headspring. This resu lt supports the concept that seasonal increases in NO3 concentrations draining the springs of th e Chassahowitzka River result from recent, precipitation-derived NO3 -. Whereas past authors have concluded that th ere is little that can be done regarding NO3 concentrations in springs due to the fact that contamination of the aqui fer has already occurred (Jones et al., 1997), the findings of this research suggest that there is pote ntial for management actions to decrease NO3 concentrations within the same year. The potential for management impact would likely increase with proximity to the spring-head. Loca tions closest to the springhead likely contribute a greater proportion of recently derived rain and stormwater as opposed to those locations furthe r away (Jones et al., 1997). It is therefore evident that NO3 concentrations in coastal springs will be part icularly sensitive to cl imatic modification and hydrologic variability. Florida is subject to a number of factors that influence its climate and hydrology at a variety of timescales including hurricanes, El Nio events, droughts, and anthropogenic water-withdrawals. Th e response of nutrient concentra tions in coastal springs and

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34 rivers to climatic variation should be taken into account when considerin g issues related to NO3 management in the terrestrial system. The concentration of SRP was not significan tly different between interannual loading classes, nor was it significantly correlated to precipita tion or discharge. Th is suggests that SRP concentration remains relatively constant regardless of enviro nmental variation. Therefore, variation in the mass load of SRP to the Chassa howitzka is determined by variation in spring discharge. In other words, as spring discharg e increased, SRP concentration remained the same, while SRP mass load increased in proportion to ri ver discharge. Mass load is the product of discharge and concentration. Therefore, the mass load of NO3 increased multiplicatively due to the fact that NO3 concentrations continued to increase ev en as discharge volume increased. Both SRP and NO3 need to be considered individually wh en evaluating the influences of temporal climatic variation on nutrient load ing to spring-fed coastal rivers. Spring-Run Nutrient Dynamics Human-climate interactions have been li nked to the productivit y, trophic status, and anoxic/hypoxic events in many estuaries around the world (Jic kells, 2005; Mulholland et al., 1997; Paerl, 2006; Pinckney et al., 2001). An eval uation of the effects of climate change in Florida and the Gulf of Mexico forecasted increased precipitation ra tes in the region of Florida’s Springs Coast (Mulholland et al., 1997), thereby pot entially exacerbating th e nutrient loading to Florida’s coastal ecosystems. Interactions between atmospheric N deposition (Fisher and Oppenheimer, 1991; Paerl et al., 2002; Whita ll et al., 2003; Winchester and Fu, 1992; Winchester et al., 1995), landuse, increasing precipitation, and spring discharge rates can potentially multiply N loading to coastal Florida as each of those factors re late to an increased N load. Understanding the present-day response of co astal ecosystems to nutri ent loading and their capacity to “absorb” these loads should be of paramount importan ce, especially in regions where

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35 hydrologic transport is as rapid as that found in th e State of Florida. An understanding of nutrient cycling is essential to evalua te potential future responses of the coastal environment to a changing climate and increasing human population. Based on approximately a decade of detailed monitoring of the concentration and spatial distribution of nutrients in Florid aÂ’s coastal environment, coastal spring-fed rivers demonstrated distinct trends in the assimilation and/or transp ort of nutrients (Frazer et al., 2006; Frazer et al., 2001; Frazer et al., 2003). The upper reaches of some coastal rivers function as transport conduits, maintaining a relatively constant nutrient concentration along their length until eventually mixing with estuarin e waters (Frazer, 2000; Frazer et al., 2006; Frazer et al., 2001; Frazer et al., 2003). In contrast, the Chassahow itzka River is characterized by a marked and consistent decrease in NO3 and SRP concentrations from the headspring to the estuary. Despite the importance of the functional m echanisms which currently reduce NO3 and SRP loads to estuarine environments, the capacity, variation, m echanisms, and controls of nutrient export and processing within the spring-r un remain relatively unstudied at a mechanistic level. Unlike those for SRP and NH4 + (NH4 + data not shown), net NO3 losses (normalized by area) differed significantly in response to N load along the spring-run in the region of the upper five transects. Spatially normalized (to a specific area) mean net loss rate s measured within the system were similar to -200 mg/m2/day for NO3 -; however, mean NO3 losses were approximately -500 mg/m2/day during High loading and Wet season conditions. These loss (i.e. uptake) values are relatively rapid compared to benthic fluxes reported for a variety of estuarine systems (Jickells and Rae, 1997). Elevated NO3 removal rates may partially result from the fact that these calculations integrate all NO3 removal (or apparent re moval) processes including assimilation, denitrification, and any d ilution that may potentially be occurring.

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36 Denitrification rates have been shown to vary across distinct aquatic systems in proportion to NO3 load and as a function of residence time (S eitzinger et al., 2006). Se itzinger et al. (2006) estimated that Total N inputs and denitrification rates were related by the following linear equation: denitrification rate (mmol N/m2/yr) = 0.256*(N inputs; mmol N/m2/yr) This equation suggests that, regardless of the sy stem (estuaries, lakes, or con tinental shelves) approximately 26% of N delivered to aquatic systems is denitr ified. On the Chassahowitzka, the percentage of NO3 load removed from transect 1 to 5 was consis tently ~30%. This value remained essentially unchanged despite a ~60% increase in NO3 load between the Low and High loading regimes. The percentage of N load removed is a va luable estimate of the system-integrated NO3 removal potential and can be used to cal culate downstream transfer of NO3 as a function of loading. This measure of NO3 load removal percentage is relevant for understanding the proportional uptake capacity the upper river. Although NO3 removal rates increased in proportion to NO3 load, so did the final mass of NO3 transported downstream. Therefore, significant increases in NO3 concentrations also occurred in downstream environments on the Cha ssahowitzka (i.e. Transect 10) in response to load and season. This study has shown that, duri ng the two-year High loading period, increases in NO3 loads at the headspring also produced significant NO3 concentration increases at the river-channel/salt-marsh interface; potentially a ffecting the salt marsh and estuary. Elevated NO3 concentrations appeared to propagate fu rthest downstream under High loading and during Dry season conditions (i.e. under High and Dry conditions). During the Wet season or under Low loading conditions, elevated NO3 concentrations appeared to be constrained within the upper ten transects of the Chassahowitzka River (Figure 2-16). Temporal variability in NO3 loads at both the seasonal and interannual time scale ultimately superseded spatial controls on

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37 NO3 retention. Differences in NO3 processing rates are likely re lated to both residence time and alterations of hydrologic flowpaths as a function of variability in hydrol ogic inputs and outputs (Seitzinger et al., 2006). As coastal system s are generally sensitive to increases in NO3 concentrations, a transfer of NO3 further into nutrient depleted wa ters could present a significant management problem in the future. Downstream transfers (to Transect 10) of signi ficantly elevated SRP concentrations did not result in response to the High lo ading period. However, seasonal va riation of SRP concentrations at Transect 10 was significant. These result s suggest that seasonally-mediated biological controls such as primary production, microbial activity, and biomass production, likely varying with water temperature and inso lation, control P uptake on the Cha ssahowitzka. Notestein et al. (2003) suggested that periphyton primary productiv ity was most strongly limited by P in this system. Phosphorus has also been suggested as a limiting nutrient in ot her coastal spring-fed rivers of Florida (Frazer et al., 2002). Therefore, it is likely that increased SRP loads are utilized over short distances and are in high demand along the Chassahowitzka River, especially during periods of elevated primary productivity. Conclusions This study focused on the source, spatial dist ribution, and controls on dissolved inorganic N and P in the Chassahowitzka River and Estuary system. Analysis of seasonal and interannual timescale nutrient concentration data on the Chassahowitzka River hi ghlight the general conclusion that temporal variati on in source, processing, and fate of nutrients is significant and should be studied, tested, and integrated into ma nagement plans dealing with FloridaÂ’s coastal environment. The specific conclusions of this analysis were as follows: Nitrate concentrations at the headspring were significantly re lated to annual precipitation. It is likely that locally-derived NO3 was transferred to the headspring from the

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38 surrounding terrestrial environment via rapi d flowpaths and resulted in elevated NO3 concentrations on the timescale of months, not decades. Net NO3 losses were directly proportional to NO3 load along the upper reaches of the Chassahowitzka River. At the reach scale this retention is equal to 30% of the total N load. Estuarine areas received the hi ghest loads of both inorgani c N and P during periods of High source loading (flow) and during the Dr y (Sept-March) season, suggesting that the upstream controls did not attenuate incr eased nutrient loads under all conditions. At the interannual timescale, mass SRP uptak e was relatively constant in the upper reaches (Transect 1-5) regardless of P loa d, suggesting a maximum or limited uptake rate in contrast to that of NO3 -. The interactive effects of increasing pr ecipitation, higher anth ropogenic N deposition, greater sources of atmospheric N deposition, hi gher discharge rates, and the increased proportion of recently-derived waters at the spri ng head have the potential to dramatically increase NO3 concentrations in FloridaÂ’s coastal ecosystems. Management of anthropogenic drivers of nut rient additions, especially within close proximity to the springhead, has the potential to redu ce precipitation-dependent NO3 concentrations at the headspring over short timescales. The Chassahowitzka Springshed has entered what has become a familiar series of events in modern times: anthropogen ic activities have led to increasi ng N inputs at the watershed scale, stimulated increased N loading to aquatic syst ems, and potentially threatened the ecological integrity of associated estuaries. The kars t geology and rapid hydrological transport of terrestrially-derived solutes in Florida result s in an accelerated propagation of anthropogenic effects to coastal ecosystems. Coastal spring-fe d rivers, salt marshes, and estuaries have demonstrated some intrinsic capacity to attenuate increasing nutrient load s, but this capacity appears to be limited as was shown by downstream transfers of elevated nutrient concentrations in response to varying load and seasonal condi tions. Therefore, the Chassahowitzka River and Estuary may be approaching the limits of its natu ral capacity to prevent significant downstream transfers of nutrients. This was evidenced by downstream propagation of elevated nutrient concentrations to Transect 10 under high load ing conditions. Unders tanding the threshold

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39 uptake capacities of these systems is an importa nt step in directing management strategies, pollution reduction targets, and total maximum daily loads in the future.

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40 Table 2-1. Data types, sources, temporal coverage and citations for datasets relevant to the Chassahowitzka River and Estuary Data type Source agency Parameters utilized Year(s) Notes Citation Land-use SWFWMD Land-use Classification 2004 Spatial (SWFWMD, 2006) Sinkholes FDEP-FGS Presence of sinkholes 2006 Spatial (Arthur et al., 2006) Soil Permeability FDEP-FGS Permeability Estimate 2006 Spatial (Arthur et al., 2006) Drainage Basins FDEP Areas and borders of FDEP determined drainage basins. 1997 Spatial (FDEP, 1997) Floridan Aquifer Vulnerability FDEP-FGS Relative vulnerability of the Floridan Aquifer to terrestrial processes 2006 Spatial (Arthur et al., 2006) Water Quality COAST SWFWMD TN, TP, Temperature, Salinity, Location 1997-2007 Spatial/ Temporal (Frazer et al., 2003) Water Quality, RIVERS SWFWMD TN, TP, NO3 -, NH4 +, SRP, Temperature, Salinity, Location 1998-2001 Spatial/ Temporal (Frazer et al., 2006; Frazer et al., 2001) Water Quality, RIVERS SWFWMD TN, TP, NO3 -, NH4 +, SRP, Temperature, Salinity, Location 2003-2007 Spatial/ Temporal (Frazer et al., 2006) Wet Deposition, Local Precipitation NADP Precipitation (cm) Site FL05 Chassahowitzka National Wildlife Refuge 1996-2006 Temporal (NADP, 2006) Discharge USGS Discharge Site 02310650Chassahowitzka near Homosassa, FL. 1997-2006 Temporal (USGS, 2007) Average Climatic Variables NOAA Average air temperature, % potential sunshine, precipitation Precipitation (1971-2000) Temp (1952-2004) Sunshine (1952-2004) Temporal (NOAA, 2007) Aerial Imagery SWFWMD Digital Orthophotos True Color (RGB) 2006 Spatial (SWFWMD, 2007) Note: Southwest Florida Water Management Di strict (SWFWMD), Florida Department of Environmental Protection (FDEP), Florida Geol ogical Survey (FGS), National Atmospheric Deposition Program (NADP), United States Geol ogical Survey (USGS), National Oceanic and Atmospheric Association (NOAA). Total Nitr ogen (TN), Total Phosphorus (TP), Soluble reactive phosphorus (SRP), Red-Green-Blue (RGB)

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41Table 2-2. Transect 1 mean nutrient concentrations as summarized by distinct discharge (High and Low) and seasonal (Wet and Dry ) classifications. ANOVA results are su mmarized by analytes and classification Transect 1 Discharge Season Parameter ( g/L) High (mean) Low (mean) df F P Wet (mean) Dry (mean) df F P NO3 ***+492.3 390.7120.96<<0.001 467.2425.313.0650.09 NH4 + 13.2 20.511.040.32 17.017.011.0360.32 SRP 15.12 14.410.770.3846 ***13.113.6111.330.0016 TN ***574.2 431.4154.87<<0.001 528.6489.211.9190.17 TP 20.5 20.810.040.8387 ***22.918.6110.050.001 Note: Source data are from the RIVERS dataset. ***Statistically significant difference between cl asses of Discharge or Season (P<0.001). +Statistically significant interactions (P<0.05) between season and load. Soluble reactive phosphorus (SRP). Total nitrogen (TN). Total phosphorus (TP), degrees of freedom (df)

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42 Table 2-3. Mean annual discharge, NO3 and SRP concentrations, and resulting mass loads over the period of 1998-2006 based on the RIVERS dataset at Transect 1 of the Chassahowitzka River Year Discharge (m3/s) Mean NO3 ( g/L) Mean SRP ( g/L) Annual Mass NO3 Load (Mg) Annual Mass SRP Load (Mg) 1998 2.03 535 24.0 34.2 1.53 1999a 1.66 435 18.3 22.8 0.96 2000a 1.48 418.9 22.4 19.5 1.05 2001 1.48 476.7 23.0 22.2 1.07 2002 1.58 ND ND ND ND 2003 1.98 546.7 19.4 34.1 1.21 2004b 1.98 563.3 20.9 35.2 1.31 2005b 1.87 582.5 22.1 34.3 1.30 2006 1.70 547.5 18.3 29.4 ND Note: Discharge data modified from USGS (2007) and nutrient data modified from the RIVERS dataset. aLow loading period. bHigh loading period. ND = no da ta, Soluble reactive phosphorus (SRP)

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43Table 2-4. Average seasonal hydrologic flow rates and nutrient concentrations of inor ganic species of N and P during the Low (1 9992001) two year loading period. n = 12 Flow Days NO3 SRP NH4 + LOW 1999-2001 Transect Wet (m3/s) Dry (m3/s) Wet Dry Wet ( g/L) Dry ( g/L) Wet ( g/L) Dry ( g/L) Wet ( g/L) Dry ( g/L) 1 1.49 1.51153213353.1440.9 12.716.72218.3 2 1.49 1.51153213324.3421.7 11.413.61915.3 3 1.49 1.51153213293.4387.0 9.811.31813.7 4 1.49 1.51153213263.9361.2 9.311.124.811.7 5 1.49 1.51 153 213 224.1 328.8 7.4 10.6 21.513.0 Note: Soluble reactive phosphorus (SRP), total nitrogen (TN), total phosphorus (TP) Table 2-5. Average seasonal hydrologic flow rates and nutrient concentrations of organi c and inorganic species of N and P durin g the High (2004-2006) interannual loading period. n = 12 Flow Days NO3 SRP NH4 + HIGH 2004-2006 Transect Wet (m3/s) Dry (m3/s) Wet Dry Wet ( g/L) Dry ( g/L) Wet ( g/L) Dry ( g/L) Wet ( g/L) Dry ( g/L) 1 1.81 1.93153213497.5487 14.515.812.613.8 2 1.81 1.93153213438.3506.7 12.914.610.15.04 3 1.81 1.93153213414.2456.3 11.214.510.25.28 4 1.81 1.93153213360.0401.2 11.015.119.010.56 5 1.81 1.93 153 213 305 375.1 9.3 13.6 13.37.31 Note: Soluble reactive phosphorus (SRP), total nitrogen (TN), total phosphorus (TP)

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44Table 2-6. Net apparent riverine nutrient loss rates normalized to the area between transects for Wet and Dry seasons during th e Low loading regime (1999-2001). Negative num bers indicate uptake (nutrient losses) NO3 SRP NH4 + LOW 1999-2001 Wet (mg/m2/d) Dry (mg/m2/d) Wet (mg/m2/d) Dry (mg/m2/d) Wet (mg/m2/d) Dry (mg/m2/d) Tran 1-2 -309.6 -206.4-14.0-33.3-32.2-32.2 Tran 2-3 -214.8 -241.2-11.1-16.0-7.0-11.1 Tran 3-4 -231.6 -202.5-3.9-1.653.0-15.7 Tran 4-5 -272.1 -221.5-13.0-3.4-22.28.9 Note: Soluble reactive phosphorus (SRP), total nitrogen (TN), total phosphorus (TP) Table 2-7. Net apparent riverine nutrient loss rates normalized to the area between transects for Wet and Dry seasons during th e High loading period (2004-2006). Negative numbers indicate uptake (losses) NO3 SRP NH4 + HIGH 2004-2006 Wet (mg/m2/d) Dry (mg/m2/d) Wet (mg/m2/d) Dry (mg/m2/d) Wet (mg/m2/d) Dry (mg/m2/d) Tran 1-2 -773.0 257.2-20.9-15.7-32.6-114.4 Tran 2-3 -203.5 -426.0-14.4-0.80.82.0 Tran 3-4 -516.9 -525.0-1.95.783.950.4 Tran 4-5 -456.7 -216.9-14.1-12.5-47.3-27.0 Note: Soluble reactive phosphorus (SRP) Table 2-8. Percentage of incoming inorganic nutrie nt load lost between RIVERS transects 1 and 5 Loading NO3 (%) SRP (%) NH4 + (%) Low (1999-2001) 31 3916 High (2004-2006) 31 2521 Note: Soluble reactive phosphorus (SRP)

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45Table 2-9. Significant differences in downstr eam nutrient concentrations as related to season and load classifications for tran sect 10 (River/Salt Marsh Boundary) Transect 10 Discharge Season Parameter ( g/L) High (mean) Low (mean) dfFPWet (mean) Dry (mean) dfFP NO3 +**234.5 119.8 110.350.003 +*** 86.7 274.7148.41<<0.001 NH4 + 22.0 26.9 10.810.37421.4 24.910.590.447 SRP +6.0 6.3 10.040.836 +***4.8 7.717.200.010 TN +465.0 453.5 10.120.733 +460.9 458.610.010.946 TP *21.5 28.2 16.240.01627.1 21.713.830.057 Note: Source data are from the RIVERS dataset. +Statistically significant (P<0.05) interac tions between season and load. Soluble reactive phosphorus (SRP), total nitrogen (TN), total phosphorus (T P). ***(P<0.001), **(P<0.01), *(P<0.05)

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46 Figure 2-1. Floridan Aquifer Vulnerability classi fication carried out by th e FDEP-FGS (Arthur et al., 2006). The Chassahowitzka Springshed is just one area in Florida where the aquifer is particularly vulnerable to terrestrial anthr opogenic disturbances

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47 Figure 2-2. Relative weighted soil permeab ility (Arthur et al., 2006), sinkhole locatio ns (Arthur et al., 2006), and the mean N O3 gradient of the Chassahowitzka Spring shed (Frazer et al., 2006). Permeable soils and hydrologicall y conductive sinkholes have the potential to rapi dly transfer terrestrial NO3 to the coastal system. Upon en tering the Chassahowitzka River, NO3 concentrations are naturally a ttenuated in a downstream direction. The highes t concentrations, indicated by vertical red bars, begin in the most upstream section ( eastern end) of the Chassahow itzka River at similar to 55 0 g/L and decrease in a downstream direction to approximately 10 g/L at the most downstream (western end) location [NO3 -] 550 g/L [NO3 -] 10 g/L Chassahowitzka River

PAGE 48

48 Figure 2-3. Land-uses (2005) in the Ch assahowitzka Springshed that are likel y to directly cause elevated NO3 concentrations into the Floridan Aquifer. Data m odified from SWFWMD (2006)

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49 Figure 2-4. The RIVERS water quality monitori ng stations within the Cha ssahowitzka River and Estuary. The COAST Transect 1 is located at the RIVERS Transect 1 site i ndicated. The upper 15 transects each consis t of three stations while transects 1520 each have one station. Transect 10, indicated above, marks the boundary between the ri ver channel and salt marsh mixing zone and is the natural boundary between salt marsh and upland terrestrial vegetation

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50 Figure 2-5Delineation and areas of the upstream RIVERS sampling transects 1-5 used for flux calculations. The area, transect numbers, and designations of the area between transects are indicated. The b ackground image is composed of digital orthophotos (SWFWMD, 2007) Area = 18,832 m2 Area = 16,398 m2 Area = 18,521 m2 Area = 11,977 m2

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51 199819992000200120022003200420052006 0 1 2 3 4 5Salinity (ppt) 1.4 1.6 1.8 2.0Discharge (m3/s) 100 120 140 160Precipitation (cm) Salinity (boxplot) Discharge Precipitation Figure 2-6. Interannual timescale va riation of precipitation, discha rge and salinity at Transect 1. n=12 samples per year taken at monthly intervals from 1998 to 2006. Salinity data from the COAST dataset (Frazer et al., 2007), annual mean precipitation from NADP (2007), and discharge from US GS (2007). Outliers are indicated for reference

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52 JANFEBMARAPRMAYJUNJULAUGSEPOCTNOVDECMonth 5 9 13 17Precipitation (cm) 1.4 1.5 1.6 1.7 1.8Discharge (m3/s) Precipitation Discharge Figure 2-7. Average monthly pr ecipitation (NADP, 2007) and discharge on the Chassahowitzka River (USGS, 2007) over the study time period 1998-2006

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53 January February March April May June July August September October November December 12 17 22 27 55 60 65 70 75% Possible Sunshine % Possible Sunshine TemperatureTemperature ( C) Figure 2-8. Mean monthly air temperature and the percentage of potential insolation reaching the earth surface (NOAA, 2007)

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54 Figure 2-9. Boxplots of interannual timescal e variation in a) total nitrogen (C OAST), b) total phosphorus (COAST), c) NO3 (RIVERS), and d) soluble reactive phos phorus (RIVERS). Outliers, indicated by po ints outside of the boxplots, are shown for reference to local variabilit y. Data from 2002 were not av ailable for the RIVERS dataset 199819992000200120022003200420052006 100 200 300 400 500 600Total Nitrogen ( g/L) 199819992000200120022003200420052006 5 10 15 20 25 30 35Total Phosphorus ( g/L) 19981999200020012003200420052006 8 10 12 14 16 18 20Soluble Reactive Phosphorus ( g/L) 19981999200020012003200420052006 100 200 300 400 500 600Nitrate ( g/L) a) b) d) c)

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55 100110120130140150160170Total Annnual Precipitation (cm) 400 450 500 550 600Average Annual Nitrate ( g/L) 1998 1999 2000 2001 2003 2004 2005 Figure 2-10. Linear least-square s regression of total annual pr ecipitation to average annual NO3 concentration (significant at P<0.05). The year of the data overlies its measurement. Data from 2002 were not available for the RIVERS dataset 1.41.51.61.71.81.92.0Annnual Mean Discharge (m3/s) 400 450 500 550Average Annual Nitrate ( g/L) 1998 1999 2000 2001 2003 2004 2005 2006 Figure 2-11. Linear least-squa res regression of annual mean discharge to annual mean NO3 concentration (significant at P < 0.05). Data from 2002 were not available for the RIVERS dataset

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56 1.41.51.61.71.81.92.0Discharge (m3/s) 18 19 20 21 22 23 24SRP ( g/L) 1998 1999 2000 2001 2003 2004 2005 2006 Figure 2-12. Linear least square s regression of annual mean disc harge to annual mean soluble reactive phosphorus (SRP) concentration. Data from 2002 were not available for the RIVERS dataset. This result, though statistica lly insignificant, is instructive in that it demonstrates that SRP does not respond signi ficantly to discharge and is therefore controlled by different factors when compared to the behavior of NO3 .

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57 AprJunAugOctDecFebAprJunAugOctDecFeb 10 30 10 30Precipitation (cm) LOADING: HIGH LOADING: LOW 1.5 2.0 1.5 2.0Discharge (m3/s) Precipitation Discharge Figure 2-13. Interannual variability of precipitation and discharge plotted over the duration of the Low (1999-2001) and High (2004-2006) loadin g regimes. Each loading regime consisted of a two-year period from April – March

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58 Calculated Flux Rates -800 -600 -400 -200 0 200Nitrate (mg/m2/day) Season: dry Season: wet Season: dry Season: wet LOAD: HIGH LOAD: HIGH LOAD: LOW LOAD: LOW Figure 2-14. Rates of NO3 losses as summarized by High and Low classes of load and Wet and Dry classes of season Calculated Flux Rates -40 -30 -20 -10SRP (mg/m2/day) Season: dry Season: wet Season: dry Season: wet LOAD: HIGH LOAD: HIGH LOAD: LOW LOAD: LOW Figure 2-15. Rates of soluble reactive phosphorus (SRP) losses summarized by High and Low classes of nutrient lo ading and Wet and Dry classes of season

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59 135791113151719135791113151719TRANSECT 200 500 200 500Nitrate ( g/L) wet.dry: dry wet.dry: wet wet.dry: dry wet.dry: wet LOADING: HIGH LOADING: HIGH LOADING: LOW LOADING: LOW Figure 2-16. Boxplots of NO3 concentration summarized by transect and grouped by High and Low classes of loading condition and Wet and Dry classes of season. Data are from the RIVERS da taset. Outliers are shown for reference purposes. Figure yaxes extend horizontally through the plot s and are the same in every case Season: Dry Season: Dry Season: Wet Season: Wet

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60 12345678910111213141516171819201234567891011121314151617181920TRANSECT 1 12 1 12SRP ( g/L) wet.dry: dry wet.dry: wet wet.dry: dry wet.dry: wet LOADING: HIGH LOADING: HIGH LOADING: LOW LOADING: LOW Figure 2-17. Boxplots of NO3 concentration summarized by transect and grouped by High and Low classes of loading condition and Wet and Dry classes of season. Data are from the RIVERS da taset. Outliers are shown for reference purposes. Figure yaxes extend horizontally through the plot s and are the same in every case Season: Dr y Season: Dry Season: Wet Season: Wet

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61 CHAPTER 3 THE DISTRIBUTION AND PROPERTIES OF SUBAQUEOUS SOILS OF THE CHASSAHOWITZKA RIVER AND ESTUARY Introduction The land-sea interface is one of the most bi ologically and biogeochemically active sites on Earth’s surface resulting from th e mixing of resources from terrestrial and oceanic systems. Reactions at the land-sea boundary fuel fish eries production, regional economies, mitigate terrestrial anthropogenic contaminat ion, provide valuable habitat, and serve as recreational sites for coastal populations. The be nthic environment has been recognized for its many roles in riverine and estuarine ecosystems (Jickells and Rae, 1997; Wall, 2004). The physical and chemical composition of benthic substrate influen ces habitat quality, ecosystem services, and the storage and cycling of carbon, nitrogen, and phosphorus (Jickells and Rae, 1997; Wall, 2004). Resulting from activity at the be nthic/aquatic interface, benthi c substrate affects estuarine productivity, fisheries production, and the st orage, concentration, and processing of anthropogenic effluents. Given the importance of the benthic environment, many government agencies, universities, and consulting agencies charged with understand ing and managing natural resources have begun to survey coastal benthic habitats to comprehend how their physical and chemical properties vary in space and time and influence its role in the ecosystem. Subaqueous Soils Over the past 10-15 years, soil scientists ha ve become increasingl y involved in studying the distribution and properties of the subaqueous environment (B radley and Stolt, 2003; Demas and Rabenhorst, 1999; Demas and Rabenhorst, 2001; Demas et al., 1996; Ellis, 2006; Fischler, 2006). Soil scientists modified their longstanding terrestrially-based conc eptual framework to suit the dynamics of a subaqueous environment (Demas and Rabenhorst, 2001). Soil scientists consider each soil individual or “polypedon” in a si milar manner that a biologist considers traits

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62 and characteristics of individual animal species. This classification allows one to relate soil characteristics to those with similar characteristics. In essence, soil scientists have applied a taxonomic classification to the Ea rth’s surface. In this concep tual framework, each polypedon has similarities to soils in its family, subgroup, great group, suborder, and order and its distinction or similarity from other soils va ries as function of ta xonomic relationship. A soil scientist selects a specific t ypical pedon for taxonomic descrip tion based on observations of the variability of the properties of that soil over its extent, in the same manner that a biologist would go about a species description of a representative specimen after they observe variabili ty of traits within a particular species. A common question that soil scient ists working in aquatic environments need to answer is, “What differentiates soil and sediment?” The do minant conceptual understanding is that the presence of overlying water is what separates soil and sediment. Post-depositional processes occurring in a terrestrial environment are refe rred to as pedogenic processes, while those occurring in the subaqueous environment are often termed diagenetic processes. One distinction between pedologists and sediment ologists is that a significant portion of sedimentological work focuses on the transport, deposition, and postburial conversion of sediment into rock. Pedologists on the other hand mainly study the formation, morphology, and equilibrium condition of the Earth/atmosphere or Earth/water-column interface. It would suffice to say that pedologists study the genetic processes, controls properties, and function of the world’s bioreactive interface. Pedologists are concerned with how parent ma terial arrived, where it will eventually go, and are also concerned with the interdependency between substrate properties and the surrounding environment at the outermost layer of the Earth’s crust. While various definitions exist, for the purposes of this rese arch, soil is considered as the reactive interface

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63 between the EarthÂ’s mineral crus t and air or water. The presen ce of overlying water should not be considered a boundary between soil and sediment but a significant driver of the structure and function of the benthic environment. Subaqueous soil surveys have been created to map the distribution of soils and their associated properties in the subaqueous envir onment. The subaqueous soil survey has emerged as a useful method for mapping the distribution and properties of various environments in estuarine and coastal regions. Subaqueous soil su rveys have already been completed in diverse estuarine environments along the coasts of Florida, Rhode Is land, and Maryland (Bradley and Stolt, 2002; Bradley and Stolt, 2003; Demas and Rabenhorst, 2001; Demas et al., 1996; Ellis, 2006; Fischler, 2006). Soil is studied in terms of its equilibrium condition with the environment. Essentially, a soil map unit relates soil properties to soil forming factors over large areas. This relationship is guided by the con cept that soil forming factors alter parent material in a manner reflective of the environmental drivers acting upon the soil. The Chassahowitzka River and Estuary (Figure 31) is a stable environment (Figure 3-2) that provides a number of contra sting soil properties a nd benthic landforms and is an area where little is currently known regardi ng the spatial distribution of su baqueous soil properties. Also, given recent anthropogenic impacts and the eco system management needs (Chapter 2), a subaqueous soil survey in this area can support mana gement and future research efforts aimed at understanding biogeochemical cycli ng within the system. This mapping effort can also add to the existing base of knowledge regarding the so ils of the region (see Pilny et al., 1988). Objectives The objectives were: Map the spatial extent of distinct subaque ous soils and describe their associated landforms and vegetation in the Chassahowitzka River and Estuary

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64 Quantify basic physical and chemical properties of subaqueous soils associated with each map unit though the selection, sampling, and analysis of a typical pedon Evaluate the selection of a typical pe don sampling location in a subaqueous soil environment based on multiple field-based soil descriptions Methods Subaqueous Soil Reconnaissance A total of 68 soil descriptions were made in the subaqueous and n ear-shore terrestrial environment to gain an appreciation for the va riability of soils along the Chassahowitzka River and Estuary (Figure 3-3). During this exploratory phase, sampling tools included a piston corer, Russian auger, Dutch auger, and vibra-corer to acquire soil samples in various substrates. At each site a field description was completed that included the following parameters: GPS coordinates (lat/long), horizon designation, horizon starting and ending depth, native vegetation, parent material, landform, field te xture, and soil color. Soil sample s were collected at select sites and analyzed for physical and chemical properties. Delineating Subaqueous Soil Map Units Exploratory and systematic transect-based subaqueous soil descriptions and aerial photography were combined into a GIS inte rface to map the subaqueous soils of the Chassahowitzka River and Estuary System. Fo llowing reconnaissance field work and soil descriptions, subaqueous soil map units were de lineated using photo-tone on aerial photographs and a 1m resolution Digital Orthoimagery Quar ter Quadrangles (DOQQ) created in 2005 by the United States Geological Survey (USGS). Suba queous soil map units (Figure 3-4, Table 3-1) were compared against bathymetry provided by the Southwest Florida Water Management District (SWFWMD) to confirm photo-tone interpretations of de pth and the overall distribution of landforms. All landforms delineations took place at a scale of 1:1000 and all landform and river/estuary channel study area boundaries were hand-digitized using ArcGIS 9.1 (ESRI, 2006).

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65 Landform boundaries were used to calculate the areal extent of landform features using ArcGIS 9.1. Due to the fine scale of the survey, map un its smaller than dominant landforms were not delineated. Typical Pedons A pedon is the smallest volume that can be ca lled a soil. A typical pedon is a reference specimen that illustrates the centr al concept of a soil in a give n soil map unit or series (NRCS, 2005). While no typical pedon sampled in a map un it is likely represent the mean of all soil properties within a given map unit, the typical pe don should represent the mean of most physical and chemical properties. Therefore, within ea ch map unit delineated as part of this study, one site was selected for the sampling of a typica l pedon based on the rec onnaissance observations and soil descriptions (Table 3-2, Figure 3-3) The selection procedure was based on the formation of a conceptual model of soil prop erties throughout the Chassahowitzka River and Estuary. The formation of a conceptual m odel involved observing the variability of soil properties including texture, co lor, horizonation, and horizon thickness across reconnaissance description sites. These observati ons led to an understa nding of the variabili ty of soil properties and their spatial distribution, limits and associated vegetation. Finally, based on the conceptual model, a sampling location was se lected that was believed to represent the “norm” for the mapped area given the multiple previous observations made during reconnaissance work (NRCS, 2005). To evaluate whether the typical pedon was representative of the greater soil map unit, comparisons were made between the typical pe don soil description a nd the variability of reconnaissance soil descriptions within a select map unit. All typical pedons were sampled using a tr ansparent polycarbonate core-tube and piston assembly mounted to an aluminum tripod (3 m height) to minimize or eliminate any displacement of soil materials upon coring. The pi ston corer was similar in design to that

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66 reported by Davis and Steinman (1998). After the co re tube was driven to its final depth, soil displacement was measured as the difference betw een soil depth outside and inside the soil core tube. Cores were hand-pulled or extracted using a pulley system once the piston was secured and were immediately extruded in the field. Soil horizons were measured in the transparent core tube and were verified and describe d in greater de tail upon extrusion. Field soil descriptions in cluded horizon designation, depth, soil color, so il texture, boundary description, structure, and n value estimation using the hand squeeze test and were recorded according to the methods of the National Soil Survey Handbook (NRCS, 2005). Soil horizon subsamples of known volume were extrud ed for the measurement of bulk density and porosity according to method 3B6a (NRCS, 2004). Soil pH was analyzed in the field using a handheld temperature-corrected electrode placed directly in contact with water-saturated subaqueous soil as modified fr om method 4C1a1a2 (NRCS, 2004). Laboratory Analytical Methods Horizons from sampled typical pedons were subsampled within 24 hours and placed in an incubation chamber to determine moist incuba tion oxidized pH (Method 4C1a1a3) using the conventions of the Soil Survey Laboratory Me thods Manual (SSLM) (NRCS, 2004). Incubations were conducted at room temperat ure on field moist soil in a hu midified constantly-circulating chamber. Soil incubation samples were periodica lly mixed to ensure complete aeration and the final pH reading was taken following a minimu m of 120 days. A subsample was air-dried and particles greater than 2mm were sieved, weighed, and reported as percen t gravel (or shells). Subsamples were taken from the <2mm fractio n for both physical and chemical analyses. Soil subsamples <2mm in size were ball-milled and analyzed for total nitrogen (TN) content via dry combustion using a Flash EA N analyzer. Total phosphorus (TP) content was quantified on the ball-milled subsamples via dry combustion, digestion in HCl, and colorimetric

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67 analysis as described by Anderson (1976). So il conductivity was meas ured on intact <2mm subsamples in the supernatant of a 2:1 dilution of deionized water to air-dry soil that was left to equilibrate overnight. Organic matter (OM) co ntent was determined on intact subsamples via loss on ignition (LOI) in a muffle furnace set at 550C for 5 hours. OM content was multiplied by an organic carbon (OC):OM ratio of 0.5 (Nelson and Sommers, 1996) to estimate the organic carbon (OC) content of the soil. Molar stoichiome tric ratios were calcula ted using the ratio of moles of OC, TN, and TP per kilogram. All da ta analysis and graph plotting was completed using SPLUS 6.1 (Insightful Corp., 2002). Results and Discussion Subaqueous Soils The benthic environment of the Chassahowitzka River and Estuary is diverse and grades from narrow sand-dominated channels to broad sh allow estuarine flats dominated by organic and shell materials common in estu arine environments. Reconnaissa nce soil descriptions also indicated a substantial am ount of variability within map units (Table 3-2). For example, surface horizon depths varied from 1-14 cm in the Blue Crab map unit compared to 1-18 cm across the whole study area (Table 3-2). Si milarly, in the Chass Sands ma p unit the surface horizon color value ranged from 0-5 while the va riability across the entire site was from 0-6 (Table 3-2). However, some map units, such as the Midden Flat s displayed very low variability in color value (all values = 2; Table 3-2). To further divide and understand the differences between soil from distinct map units, more detailed physical and chemical data are required. These data are presented for the typical pe dons samples during this study. Subaqueous soils differed markedly in color, texture, bulk density, and incubation pH across typical pedons sampled from the study area (Table 3-3). These differences resulted in taxonomic divisions occurring at the level of grea t group (Table 3-2). Based on information from

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68 typical pedons and reconnaissance soil descrip tions (Figure 3-3), a strong relationship was observed between benthic map units, associated vegetation, and soil physical and chemical properties. The heterogeneity of the subaqueous landscape was delineated into the following soil map units: Chass Sands, Riversides, Blue Crab, Midden Flats, and Shell bottom (Figure 3-4). These map units represent the dominant unique co mbinations of soil forming factors and their resultant soils at the scale of interest in this research (1: 1000). The Shell Bottom map unit was not analyzed in detail du ring this study due to its frequent disturbance and sediment mobility. Physical and Chemical Soil Data Between Map Units The benthic environment of the Chassahowitzka River and Estuary is comprised of an array of soils with distinct phys ical and chemical properties (Tab le 3-3). Local-scale (within map unit) variability was not directly quantified a nd analytical resources were directed toward evaluating differences between typical pedons repres entative of distinct map units. Physical and chemical properties were grouped by typica l pedon and were presented using boxplots to facilitate parameter comparisons between dist inct map units. Information provided by a boxplot includes the range, median, proportion of the data in the upper and lower quartiles, potential outliers (values that are greater than 1.5 times the in ter-quartile range), and the highest and lowest non-outlying values. Based on a boxplot, one can deduce the gene ral variation of the parameter within a given typical pedon and make comparisons with the variability measured in other pedons. Physical properties Soil texture and color (Table 3-3) were strongl y influenced by the parent materials (Table 3-1) in which the subaqueous soils formed. Soil textures in the Ch assahowitzka River and Estuary ranged from muck to sand (soil text ure, Table 3-2, Table 3-3). Typical pedon color values ranged from 2-6 and the lowest values we re associated with lo w-velocity depositional

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69 environments. Low velocity environments include d the Midden Flats, Riversides, and within the Blue Crab map unit where mixing with estuarine OM sources occurs. Sands and fine-sands were generally characterized by high color value and dominated the composition of the Chass Sands and the underlying C horizons of th e Riversides map unit. Muck and mucky sand textures were common throughout the Midden Flats and the upper horizons of the Riversides map units. Soil conductivity ranged from 0.97-11.46 dS /m with a median of 2.6 dS /m. The highest conductivity values were generally located in organic-rich surface horizons close to or inside the salt marsh and upland/salt-marsh transition area Bulk density ranged from 0.1-1.8g/cm3 and differed notably between map units (Figure 3-5d) Those pedons sampled from high energy environments, namely the Chass Sands and Blue Crab, have much higher median bulk densities than those from lower energy depositional enviro nments. Observed mineral composition varied from quartz-sand dominated in the upstream areas toward a carbonate/quartz sand mix within the estuarine and Salt Marsh map units. Gravel-sized particles were not commonly observed in the system and comprised less than 1% of the total soil contents analyzed. Chemical properties Field soil pH varied in res ponse to texture and among map un its, though remained within a relatively narrow range of 6.9 to 8.1 through all sites and horizons sampled (Figure 3-5a). Results from pH incubations i ndicated that reduced sulfides were present in many of the subaqueous soils of the Chassahow itzka River and Estuary (Table 3-3, Figure 3-5b). However, in the Midden Flats, though reduced sulfides were likely present, their pr esence was not indicated by pH incubations. This most likely resu lted from buffering by the presence of CaCO3 in the form of shells. Reduced sulfides appeared to be most prevalent, or least-buffered by CaCO3, in the Blue Crab map unit which resulted in a post-inc ubation pH decrease to less than 2. Values of OC (range 1-209g/kg; median 28 g/kg), TN (range 0-17 g/kg; median 3 g/kg), and TP (range 51-

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70 2481 mg/kg; median 152 mg/kg) vari ed strongly between map units (Figure 3-6 a,c,e). The highconcentrations of OC, TN, and TP (Figure 3-6 a,c,e) observed in the Riversides map unit all originated in the organic (Oa) soil horizon described for that map unit. Molar stoichiometric ratios relate the conten ts of OC, TN, and TP within a given sample. Generally, soils with elevated OC:TN and OC:T P ratios contain recalcitrant OM while those with lower OC:TN and OC:TP ratios are composed of relatively labile, nutrient-rich organic materials (Jickells and Rae, 1997). The relative am ount of TN vs. TP is also an indicator of which nutrient may be limiting decomposition pr ocesses. The highest OC:TN (range 8-26; median 16) ratios were observed in the Midden Flats and Riversides, while the lowest values were located in the Chass Sands and in the Blue Crab map units (Table 3-3). Molar ratios of OC:TN less than 30 are generally considered to be labile materials whose decomposition is not N limited (Jickells and Rae, 1997). Across all sample s, OC:TP values ranged from 50-1443 with an overall median of 289. These values crossed the generalized threshold of 116, above which P may be considered as a factor potentially lim iting the decomposition of OM (Jickells and Rae, 1997). The median TN:TP ratio was 20 and TN:T P ranged from 4-62. Generally, TN:TP values greater than 16 also suggest th at P is the limiting factor of decomposition. In many cases it is important to note that variation of molar ratios of OC, TN, and TP with in typical pedons was often as striking as the variati on between pedons. This demonstrat es that indivi dual horizons are also characterized by distinct physical and chemical properties. In most cases, molar stoichiometric ratios suggest that P is likely the nutrient limiting decomposition within the benthic substrate of the Chassa howitzka River and Estuary. Howeve r, nutrient limitation is often complex and dependent on many other factors in cluding the presence/absence of micronutrients

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71 and temperature. Therefore, no formal conclusion s regarding the status of nutrient limitation can be made from these data. Map Units Chass Sands (ChS) Beginning at the main spring boil of the Chassahowitzka River and meandering approximately 3 km toward the salt marsh, the Chass Sands (ChS) map unit accounts for 4.2% of the area mapped during this study. The channel ge nerally has a very slight slope (<2%), both longitudinally and in cross section. The Chass Sands map unit is influenced by higher water velocities compared to other map units, t hough velocities throughout th e entire study area are generally low and range from 0-0.5m/s (Frazer et al., 2001). The average water depth observed in the Chass Sands is approximately 1.0 m and the channel bottom is derived from sanddominated parent materials with occasional out croppings of limestone bedrock. Due to shallow depths at low tide or when West winds dominate, there is frequent disturbance and mixing within the landform by outboard motors. Common submerge d aquatic vegetation (SAV) species include Vallisneria americana (Tapegrass), Najas guadalupensis (Southern Naiad), Hydrilla verticillata (Hydrilla), and a variety of benthic algal specie s (Frazer et al., 2001). Soil pH decreased from over 7 to below 4 fo llowing moist incubation in two horizons and therefore indicating the presence of unbuffered sulfidic materi als (Table 3-3, field pH vs. incubation pH). Within the typical pedon OC, TN and TP contents varied from 1-9 g/kg, 0.1-0.6 g/kg, and 54-98 mg/kg respect ively (Table 3-3). Subaqueous soils representative of the Cha ss Sands map unit were classified to the subgroup level as Haplic Sulfaquents (Table 3-3, Table 3-4). Th e typical pedon had no diagnostic horizons (order = Entisol), was pe rmanently saturated (suborder = Aquent), and contained sulfidic materials within 50cm of the soil surface (as evidenced by pH changes

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72 following incubation; Great group = Sulfaque nt). The typical pedon also had an n value of less than 0.7 at a depth of 20-50 cm below the soil su rface and therefore the sub-group was classified taxonomically as Haplic. Based on the temperat ure of the overlying water column (throughout the Chassahowitzka River and Estuary), the so il temperature regime is likely hyperthermic, though temperatures were not measured at the co ntrol depth for a sufficient period of time to confirm this hypothesis. The Chass Sands map unit is subject to the hi ghest water velocities and have sands that were likely been derived from the surroundi ng terrestrial environm ent. Blue crabs ( Calinectes sapidus ) are common in the benthos of this map un it and often burrow into the soil, thereby working OM to lower depths. Also, boat traffic in the area has often been observed “plowing” the soil surface with outboard motors as the wate r depth is generally less than a meter deep and can drop quickly in response to tides and wind. Aquatic plants have fine root systems that anchor the surface soil and inject carbon into the soil surf ace. The above drivers interact to maintain a sand-dominated soil, enriched with OM in the surface layers forming a distinct A horizon. Due to the high porosity and sandy textures, this site likely has the highest hydraulic conductivity of all map units in the study area and is most likel y influenced by advective exchange with the overlying water column. The main channel is the dominant habitat of SAV growing in the area and is therefore significant habi tat for a variety of aquatic organisms including the West Indian Manatee, blue crabs, and as shelter for a num ber of species during their early life stages. Riversides (RvS) The Riversides (RvS) map unit is located on the shallow (<0.5 m) lateral edges of the Chass Sands and covers 8.6% of the study area. This map unit contains similar species of aquatic vegetation as the Chass Sands, but also receiv es greater inputs of sedimentary material, especially riparian-derived orga nic debris and algae that accumulate at the channel edges and

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73 settle. Small sticks and leaves from terrestrial plants were commonly encountered in the surface horizons of Riversides soils. Water velocity in the lateral channel is quite slow, often resulting in flow rates of 0-0.1 m/s. Contents of OC, TN, and TP ranged from 4-209 g/kg, 0.3-16.6 g/kg, and 50.5-2481mg/kg, respectively (Table 3-3). The highest OC, TN, and TP contents were located in the surface horizon and decreased cons istently with depth. The typical pedon of the Rivers ides map unit was classified to the subgroup level as a Mollic Psammaquent (Table 3-2, Table 3-5). No di agnostic horizons were present in the typical pedon and the soil remains saturated year round. Therefore, the subgroup taxonomic classification was Aquent. So il pH decreased upon incubati on, though not below the pH < 4 required for the definition of sulf idic materials. However, sa nd and sandy-loam lamellae were common in the soils described in this map unit as well as in the typical pedon. The presence of these coarse materials resulted in the classificat ion of the typical pedon into the Great Group of Psammaquents. Finally, the pres ence of low-value, low-chroma colors in the upper horizons led to the subgroup classification of Mollic Psammaquents. The Riversides map unit is longitudinally a ssociated with Chass Sands. However, the Riversides map unit is characterized by lower water velocities of the channel edges. This depositional environment has promoted the settlin g of OM produced in the upper reaches of the river, riparian areas, and by algal communities gr owing on the sides of the channel. Chironomids (non-biting midges) have been observed in a numb er of soil cores sampled from this area and may be significant drivers of mixing to form th e mucky sand A horizons that characterize this map unit. Many wading bird species common to the Chassahowitzka National Wildlife Refuge hunt in this map unit among the emergent vegetati on. As OM content is higher in the Riversides

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74 site, soil hydraulic condu ctivity may be lower as compared to the Chass Sands map unit. Therefore, surface water induced advective excha nge with the overlying water column is likely not present and exchange across the soil/water interface is likely to be more dominated by diffusion. On many occasions during the course of th is research, much of the of the Riversides map unit was covered almost completely with algal mats, dramatically reducing local water velocities. Blue Crab (BlC) The Blue Crab (BlC) map unit is located with in the subtidal freshwater/estuarine mixing zone and covers 6.7% of the study area. Water co lumn properties (salinity and total dissolved solids) are most dynamic in res ponse tidal variations in the Bl ue Crab map unit as it receives direct inputs from both the estuary and the fres hwater-dominated spring. The Blue Crab map unit is similar to Chass Sands in flow characteristics, but Blue Crab has been additionally influenced by the presence of increased salinities and th e associated marine be nthic community. Plant species frequently encountered in this map unit consist of the salt-tolerant Myriophyllum spicatum Najas guadalupensis and a number of common algal species including Lyngbia sp., Spyrogyra, and Vaucheria sp The OC, TN, and TP contents varied from 8-49 g/kg, 0.6-3.9 g/kg, and 70.7-192.2 mg/kg, respectively. The typical pedon was classified as a Typic Sulfaquent and responded strongly to moist incubation. Incubation resulted in pH decreases in two horizons to values less than 2 (Table 33). Changes in soil pH following moist incubation are a strong indicator of the presence of sulfidic materials. However, the absence of carbonates is also require d to detect sulfidic materials, as their presence will buffer any ch ange in pH during moist incubation. The soil suborder was Aquent (no diagnostic soil horizon s and permanently saturated) and the strong

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75 presence of sulfidic materials resulted in the great group taxonomic classification as a Sulfaquent. The subgroup of th e soil was Typic, as the requirements for Haplic, Histic, and Thapto-histic subgroups were not met. Two buried horizons were also desc ribed indicating that this area was once covered by emergent vegetati on and has since become inundated with water. The Blue Crab map unit is differentiated from upstream map units based on the elevated densities of saltwater tolerant estuarine and mari ne species that begin to dominate the benthos and the effects of these conditions on the soils. For instance, the increased presence of reduced sulfides as indicated by the drasti c drop of incubation pH is a direct influence of association with the estuarine environment. With distance downstr eam, the upstream area contributing OM to the water column increases, providing OM for sett ling, mixing, and incorpora tion into downstream soils. The Blue Crab map unit remains charac terized by sandy textures, but is comparably enriched in OM compared to the Chass Sands ma p unit. Krotovina (anima l-derived tunnels) were frequently observed in this map unit, resulti ng from the burrowing activities of benthic species such as blue crabs. This burrowing activity also notably increases the content of silt as was observed in the field. An enrichment of silt results in the only loamy textures reported in the Chassahowitzka River and Estuary. Most textur es were sands/fine sands or muck/mucky sand, which reflect the two extremes of substrates encountered during soil sa mpling and descriptions. Midden Flats (MdF) The large expanses of flats that lay between the vegetated salt marsh and the Shell Bottom were mapped as the Midden Flats (MdF) and constitute 44.5% of the total area mapped in this study. The n values measured in the typical pedon were consistently >0.7 and bulk density ranged from 0.3-0.8 g/cm. Lower n values resulted from the presence of sand size CaCO3 shells. Field and incubation pH were simila r, likely as a result of CaCO3-buffering of any pH changes during

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76 the sulfide oxidation process during incubation. C ontents of OC, TN, and TP were higher than those in the Blue Crab and the Ch ass Sands and were similar to t hose of the Riversides (Figure 36). Molar ratios of OC:TN and OC:TP were also elevated within the Midden Flats. TN:TP ratios are comparable to other map units and generally remain close to 25, again reflecting a slight scarcity of P relative to N in soils of the Midden Flats. Salt marsh productivity rates are among the highest in the world and are comparable to pr oductivity rates reported in tropical rainforests and coral ecosystems (Valiela, 1995) The resulting OM is eventual ly released into the estuary and commonly deposited in areas with low wate r velocities. The Midden Flats are dominantly covered by Myriophyllum spicatum and provide habitat for nu merous estuarine species. The Shell Bottom typical pedon was classified as a Mollic Psammaquent (Table 3-2, Table 3-7). Sandy textures often resulted from the presence of carbonate shells as opposed to the Riversides map unit where sandy textures resulted from quartz sands. The epipedon of the Midden Flats typical pedon was ch aracterized by low chroma (0) a nd value (2), resulting in the final subgroup classificati on as a Mollic Psammaquent. Shell Bottom (ShB) The Shell Bottom (ShB) is likely a relict channel bottom carved in a time of lower sealevel (paleo-channel), yet maintained by flushing tidal currents which still serve to mobilize sediments along its bottom. Larg e tidal ranges can generate significant ebb and flow tidal currents which in turn scour the ch annel bottom. This effect is mo st notable in the largest portion of the channel, while smaller br anches of the channel are likel y less influenced by significant flushing events. Due to the high hydrologic energy and estuarine environment, benthic substrate is commonly composed of coarse oyster shell fragments and is th erefore porous in nature and mobile. Some low-energy areas of the channel may accrete organic material transported from

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77 upstream areas when tidal flushing currents are less strong. However, this accretion is likely temporary as the material will likely be rem obilized when higher water velocities return. Map Unit Names The Chass Sands map unit was named after the common reference made the Chassahowitzka River as the “Chass” by locals. This map unit recei ves the greatest use by locals for boating and therefore was name d after the Chassahowitzka itself. The map unit is dominated by sandy material, thereby earning th e entire name of “Chass Sands ”. The Riversides map unit was named such due to the fact that it is the tr ansition between the riparian areas of the river and the mainstem channel. Much fishing in the area is undertaken on the sides of the river and this is a common recreational activity on the Chassahow itzka River. The Blue Crab map unit was named after the blue crabs that are common to the area and play a notable role in the soil formation within the area. Many locals capture these crabs for recreation and as a food source and this map unit is a rich area for that activ ity. The Midden Flats map unit was named due to the fact that shell middens (kit chen waste from earlier societie s) were found in the area of the map unit. Finally, the Shell Bottom map unit was named after the shell material that was consistently detected and moving about the bo ttom of the channel in the salt marsh area. Typical Pedon Map Unit Representation Typical pedons were selected based on field observations and multiple soil descriptions. To evaluate whether typical pedons were representative of other so il descriptions made within a map unit, typical pedons were directly compared with the reconnaissance soil descriptions from the same map unit. The surface horizon was chosen for this evaluation as it is the portion of the soil with closest contact to th e overlying water column and may be an important component of estuarine biogeochemical cycling (see Chapter 4). The Riversides map unit was chosen as an

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78 example for evaluation as the greatest number of soil descriptions were made within its boundaries (n = 22; Table 3-2). The surface soil texture, depth of the epipedon, soil hue, value, chroma and the dominant horizon directly underlying the surf ace soil horizon for the all rec onnaissance descri ptions in the Riversides map unit are summarized in Figure 3-7. Although the epipedon properties varied appreciably within the map unit, the typical pedon values fell on or near the center of each distribution. All values of soil color (hue, value, and chroma) and the master horizon below the surface horizon of the typical pedon re presented the majority of othe r soil descriptions. In the case of surface horizon texture, the typical pedo n was described as ‘muck’ even though the dominant soil texture was ‘mucky sand’. The surf ace horizon depth of the typical pedon (7 cm) was fairly close to the mean of 4 cm, given the variation of surface horizon depths (1-14 cm) within the map unit. Overall, the typical pedon appears to have provided a viable representation of the variability of soils described within the Riversides map unit. Soil Taxonomy and Subaqueous Soils of a Riverine-Estuarine System Soil Taxonomy has been developed to help scientists communicat e and understand the relationships among and between so ils and to understand the factor s that contribute to their character (NRCS, 2005). However, the USDA-Soil Taxonomy has largely been developed in the terrestrial environment and only recently have soil scientists be gun to study subaqueous environments. Therefore, the subaqueous envi ronment poses unique chal lenges for the future development of Soil Taxonomy. Do the taxonom ic distinctions desi gned to describe the terrestrial environment accomplish the same task equally well in a subaqueous setting? The soils described during this study traverse d a freshwater-dominated springhead to an estuary and crossed a gradient of soil forming factors including: wate r column properties (see Chapter 2), vegetation, and parent material. Desp ite the variability in soil forming factors, no

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79 taxonomic distinctions were made above the great group level. In a coastal subaqueous environment, properties such as reduced sulfid e content and soil conducti vity vary distinctly across freshwater-estuarine gradie nts. Although sulfidic materi als are used to make taxonomic divisions at the great group le vel, their presence is obscured when using standard tests in environments that contain calcium carbonate. This is especially important in Florida, as the foundation of the state is a massive carbonate platform. Soil conductivity provides an indication of th e environments exposure to saline, high ioncontent waters. No taxonomic di stinction is currently made to distinguish soils from fresh, brackish, or salt waters. Soil conductivity measur ements could potentially serve as a valuable indicator soil exposure to and re tention of dissolved ions from overlying water columns. This measure in turn, could potentially be used as the basis for a taxonomic di vision at the great group level to better differentiate the origin of the a quatic environments to wh ich the soil was exposed. Future, potentially long-term, research will be re quired to evaluate the potential utility of soil conductivity as a robust measure of a soilÂ’s place along freshw ater-estuarine gradients. Summary The main objectives of this study were to map the spatial distribution of distinct subaqueous soils, characterize subaqueous soil physical and chemical properties through the description and analysis of typical pedons, and to confir m that the typical pedon chosen following multiple field observations was represen tative of its greater map unit. During the reconnaissance phase of this research, a conceptual model of the variation of soil properties in relation to parent material, bathymetric landscap e, spatial location, and vegetation was attained following multiple soil descriptions. Soil/landscape relationships have also been documented in previous subaqueous soil work in the Northeaste rn US (Bradley and Stolt, 2003; Bradley and Stolt, 2006) and along the Florid a coastline (Ellis, 2006; Fischl er, 2006), though they had never

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80 been documented within a rive r channel. Briefly, hydrology is paramount in influencing the fluvial geomorphic distribution of parent materi als, and therefore the template, from which subaqueous soils develop. Post-depositional processes interact with parent material to drive the ultimate expression of soil morphology. Overall, there is a notable range in soil properties and soil forming factors along the freshwater-estuarine trans ition in the Chassahowitzka Ri ver and Estuary. The benthic environment is a significant co mponent of coastal ecosystems and needs to be considered, studied, and understood for the sake of science and resource management. Subaqueous soil and resource inventories are emerging as a rele vant component of studying and understanding shallow coastal benthic environments and thei r overall ecosystem significance. The subaqueous soil survey carried out du ring this research demonstrated so il/landscape relationships within a freshwater/brackish spring-run and its receiving estuary. Thes e findings extend the subaqueous soil paradigm for the first time to relatively low-energy freshwater-dominated environments and demonstrate the utility of the mapping exercise The resulting soil map will provide a useful basemap for future investigators and resource managers who work in the Chassahowitzka Riverine and Estuarine system.

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81Table 3-1. Subaqueous soil map units, areal coverage, average wate r depth, dominant parent materi al, soil taxonomic classificat ion, and the percent coverage of the map unit within the Chassahowitzka Rive r and Estuary. OM = organic matter Soil Map Unit Subaqueous Soil Map Unit Name Study Area Coverage Study Area Coverage Water Depth Parent Material Soil Classification of Map Unit Typical Pedon (hectares) (%) Range (m) ChS Chass Sands 10.8 4.2 0-3 Holocene sands Haplic Sulfaquent RvS Riversides 22.2 8.6 0-1.5 Fluvial OM, bank erosion deposition Mollic Psammaquent BlC Blue Crab 17.3 6.7 0-2.5 Holocene sands and estuarine OM Typic Sulfaquent MdF Midden Flats 115.2 44.5 0-2.5 Estuarine OM deposits and fine shell gravels Mollic Psammaquent ShB Shell Bottom 90.1 34.8 0-4 Fluvial marine shells coarse materials Entisol Total 258.9 100

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82Table 3-2. Summary of reconnaissance soil descriptions for the surface horizon of all map units delineated within the Chassahowitzka River and Estuary. *Shell Bott om (ShB) was frequently not described as it most often consisted of mobile coarse sands and gravels. Surface horizon depth, value, and chroma are listed as: range (mean) Soil Map Unit Soil Map Unit Name Number of Descriptions Dominant Vegetation Surface Horizon Designation Surface Horizon Depth (cm) Surface Horizon Texture Surface Horizon Hue Surface Horizon Value Surface Horizon Chroma Horizon Below Surface ChS Chass Sands 8 Multiple Algal Species, Najas Guadalupensis A, Oa, A/C, C/A 1-11 (5.6) muck-sand N-10YR 0-5 (1.9) 0-3 (0.9) A, A/C RvS Riversides 22 Multiple Algal Species A, Oa, A/C, C/A 1-14 (4) muck-sand N-10YR 0-2 (1.6) 0-1 (0.4) A, A/C, Oa, Bw BlC Blue Crab 6 Multiple Algal Species Oa, A, A/C 1-8 (3.7) muckmucky sand N-10YR 0-6 (4) 0-1 (0.3) A, Oa Ab MdF Midden Flats 10 Myriophyllum Spicatum Oa, A 2-18 (7.6) muckmucky sand N-10YR 2 (2) 0-1 (0.4) A, Oa, CR ShB* Shell Bottom 2 None/Algae A/C 4-6 (5) sand/shell fragments 2.5Y10YR 2-4 (3) 1-2 (1.5) C

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83Table 3-3. Horizon designati ons, depths, and physical and chemical parameters of subaqueous soils of the Chassahowitzka River and Estuary. OC = Organic Ca rbon, TN = Total Nitrogen, and TP = Total Phosphorus, ND = Not determined. Stoichiometric ratios are molar. *C horizons described in Table 3-7. No ty pical pedon was sampled for the Shell Bottom (ShB) map unit as it is frequently disturbed and mobile Horizon Depth TP TN OC OC:TN OC:TP TN:TP Incubation pH Field pH Dominant Color OM Conductivity Texture n value Gravel Porosity Bulk Density cm mg/kg g/kg g/kg Molar Molar Molar >120 days (moist) % dS/m 0.7 % % g/cm3 A 9 98 1 9 18 246 13 6.88 7.15 5Y 6/1 2 1.205 sand < 0.7 0.1 ND ND AC1 34 54 0 6 14 281 20 3.8 7.55 2.5Y 4/1 1 0.972 sand < 0.7 0.3 ND ND AC2 55 67 1 8 17 289 17 2.48 7.47 2.5Y 4/1 2 1.474 sand < 0.7 0.4 ND ND CA 66 66 0 1 14 50 4 6.05 7.7 2.5Y 6/1 0 1.277 fine sand < 0.7 ND ND ND Oa 7 1014 17 209 15 531 36 6.93 7.61 N 2/0 42 ND muck >0.7 0.1 95 0.1 A1 27 2481 10 131 16 136 9 6.53 7.13 N 2/0 26 10.26 mucky sand >0.7 0.1 91 0.2 A2 49 520 5 104 26 518 20 4.24 6.94 N 2/0 21 7.08 mucky sand >0.7 0.2 99 0.5 A3 64 152 4 85 23 1443 62 4.18 6.94 N 2/0 17 4.64 mucky sand >0.7 0.5 70 0.6 A4 82 51 0 5 20 235 12 4.04 6.9 10YR 3/1 1 1.193 fine sand < 0.7 0.7 36 1.8 AC 6 ND ND 12 ND ND ND 7.44 7.62 10YR 2/1 2 ND loamy sand >0.7 0.2 65 1.3 2Ab 13 136 2 12 8 234 28 7.4 7.48 10YR 3/1 2 2.44 loamy sand >0.7 0.5 74 1.0 2ACb 24 71 1 11 12 398 33 3.1 7.54 10YR 3/4 2 1.714 loamy sand >0.7 0.3 64 1.3 3Ab 51 192 4 49 14 652 45 1.95 7.36 10YR 2/2 10 4.92 mucky sand >0.7 0.2 78 0.6 3ACb 66 93 1 8 16 223 14 1.98 7.32 10YR 3/1 2 2.75 fine sand < 0.7 0.3 47 1.3 A1 10.5 489 6 77 15 405 26 7.18 7.19 N 2/0 15 11.46 mucky sand >0.7 ND 85 0.3 A2 16.5 450 3 43 16 247 16 7.55 7.31 N 2/0 9 2.25 mucky sand >0.7 ND 99 0.8 A/C1* 61.5 379 4 67 18 457 25 7.58 7.06 N 2/0 13 7.65 mucky sand >0.7 ND 49 0.4 A/C2* 106.5 405 6 106 21 675 32 7.46 6.86 N 2/0 21 10.24 mucky sand >0.7 ND 85 0.4 ________________________________________________________ ChS: Chass Sand s _______________________________________________________________ _________________________________________________________ RvS: Riversides _________________________________________________________________ _________________________________________________________ BlC: Blue Crab __________________________________________________________________ _________________________________________________________ MdF: Midden Flats ______________________________________________________________

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84 Table 3-4. Chass Sands (ChS) typical pedon description and taxonomic identification Typical Pedon Description: Chass Sands Map Unit: ChS Location N 28 42’ 59.5”, W 082 35’ 17.2” Classification: Haplic Sulfaquent A 0-9 cm; 40% gray (5Y 6/1), 30% olive gray (5Y 5/2), 15% black (N 0/0), 10% very dark gray, (10YR 3/1), 5% light olive brown (2.5Y 5/4); sand; many fine roots; pH 7.15; diffuse boundary. AC1 9-34 cm; 40% dark gray (2.5Y 4/1), 30% dark gray (10YR 4/1), 10% black (N 2/0), 10% black (10YR 2/1), 10% gray ( 10YR 6/1); sand; many fine roots; pH 7.55; diffuse boundary. AC2 34-55 cm; 50% dark gray (2.5Y 4/1), 30% gray (10YR 6/1), 10% black (N 2/0), 10% very dark gray (10YR 3/1); sand ; many fine roots; pH 7.47; diffuse boundary. CA 55-66 cm; 60% (2.5Y 6/1), 20% (10YR 2/1), 10% (10YR 4/1), 10% (2.5Y 6/2); fine sand; pH 7.70. ______________________________________________________________________________ Table 3-5. Riversides (RvS) typical pedon description and tax onomic identification Typical Pedon Description: Riversides Map Unit: RvS Location N 28 43’ 10.2”, W 082 35’ 58.4” Classification: Mollic Psammaquent Oa 0-7 cm; black (N 2/0); muck; pH 7.61; diffuse boundary. A1 7-27 cm; black (N 2/0); mu cky sand; pH 7.13; diffuse boundary. A2 27-49 cm; black (N 2/0); mucky sand; pH 6.94; diffuse boundary. A3 49-64 cm; black (N 2/0); mucky sand; pH 6.94; wavy boundary. A4 64-82 cm; black (10YR 3/1); fine sand; pH 6.90.

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85 Table 3-6. Blue Crab (BlC) typical pedon description and tax onomic identification Typical Pedon Description: Blue Crab Map Unit: BlC Location N 28 43’ 14.7”, W 082 35’ 52.2” Classification: Typic Sulfaquent Oa 0-1cm; black (N 2/0); muck; pH 7.62; diffuse boundary. AC 1-6 cm; black (10YR 2/1); loamy sand; pH 7.62. 2Ab 6-13 cm; very dark gray (10YR 3/1); loamy sand; pH 7.48. 2ACb 13-24 cm; dark yellowish brown (10YR 3/4); loamy sand; pH 7.54; wavy boundary. 3Ab 24-51 cm; very dark brown (10YR 2/2) ; mucky sand; pH 7.36; distinct boundary. 3ACb 51-66 cm; very dark gray (10YR 3/1); fine sand; pH 7.32. _____________________________________________________________________________ Table 3-7. Midden Flats (MdF) typical pedon description and taxonomic identification Typical Pedon Description: Midden Flats Map Unit: MdF Location N 28 42’ 39.5”, W 082 36’ 43.9” Classification: Mollic Psammaquent A1 0-10.5cm; black (N 2/0); mucky sand; fe w fine roots; 2% sh ell fragments; pH 7.19; diffuse boundary. A2 10.5-16.5 cm; black (N 2/0); mucky sand; many fine roots; 2% shell fragments; pH 7.31; diffuse boundary. A/C1 16.5-61.5cm; A: black (N 2/0); mucky sa nd. C: very dark gray (10YR 3/1); fine sand. Few fine roots; 2% shell frag ments; pH 7.06; diffuse boundary. A/C2 61.5-106.5cm; A: black (N 2/0); mucky sa nd. C2: very dark gray (10YR 3/1); fine sand. Few fine roots; 2% shell fragments; pH 6.86. _____________________________________________________________________________

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86 Figure 3-1. Aerial photo mosaic of the Cha ssahowitzka River and Estuary (1995). Imager y data provided by the Florida Departmen t of Transportation (FDOT). Channel forms and de positional flats are evid ent in the phototones

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87 Figure 3-2. Aerial photographs taken in 1944 and 1999 suggest th at the dominant subaqueous landforms in the study area are stable (at least ove r this 55 year period). The aerial photos do suggest that there may be some infilling of channels with new sedimentary material 1999 1944 F F L L A A T T S S F F L L A A T T S S C C H H A A N N N N E E L L C C H H A A N N N N E E L L

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88 Figure 3-3. Soil reconnaissance site descri ptions and typical pedon sampling locations on the Chassahowitzka River and Estuary. Typical pedon sampling locations are indicated as follows: Cha ss Sands (ChS), Riversides (RvS), Blue Crab (BlC), and Midden Flats (MdF). Shell Bottom (ShB; not shown) was not sampled for a typical pedon as the map unit dominantly consisted of mobile sands and gravels

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89 Figure 3-4. Subaqueous soil map of the Cha ssahowitzka River and Estuary. Map units indicated include: Chass Sands (ChS), Riversides (RvS), Blue Crab (BlC), Midden Flats (MdF) and Shell Bottom (ShB). Map units do not include terrestrial islands, mainland, or a dredged channel that exists upstream of the main headspring

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90 Figure 3-5. a) Soil pH (field determined) among map units (intenti onally presented with the same y-axis as Figure b and c for comparison), incubation pH (>120 day moist incubation) as grouped by b) map unit and c) soil te xture. d) Bulk density is grouped by map unit. All pH calculations we re carried out on raw hydroge n ion concentration data and transformed back to –log[H+] for data presen tation. NA= not available. **Data not available however, as the Chass Sands were the most sanddominated soils within the river system, it is likely they also has the highest bulk densities within the study area. Box plot s indicate the sample median (l ine with dark circle inside the shaded box), upper and lower quartiles (indicated by the shaded area above or below the sample median). Box whiskers indicate the upper and lo wer limits (1.5*inter quartile range) of non-outlying values. Finally, lines w ith dark circles beyond boxplot whiske rs indicate outlying data points Chass SandRiversidesBlue CrabMidden Flat 0.0 0.5 1.0 1.5Bulk density (g/cm3) sandfine sandloamy sandmucky sandmuckTexture 1 3 5 7Incubation pH Chass SandRiversidesBlue CrabMidden Flat 1 2 3 4 5 6 7Incubation pH Chass SandRiversidesBlue CrabMidden Flat 1 2 3 4 5 6 7pH NA**

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91 Figure 3-6. a) Total phosphorus (TP), c) organi c carbon (OC), e) total n itrogen (TN), and molar ratios of b) OC:TP, d) TN:TP, and f) OC :TN plotted by map unit. Box plots indicate the sample median (line with dark circle inside the shaded box), upper and lower quartiles (indicated by the shaded area above or below the sample median). Box whiskers indicate the upper and lower limits (1.5*inter quartile range) of non-outlying values. Finally, lines with dark circle s beyond boxplot whiskers indicate outlying data points Chass SandRiversidesBlue CrabMidden Flat 0 50 100 150 200Organic Carbon (g/kg) Chass SandRiversidesBlue CrabMidden Flat 0 5 10 15Total Nitrogen (g/kg) Chass SandRiversidesBlue CrabMidden Flat 0 200 400 600OC:TP (molar) Chass SandRiversidesBlue CrabMidden Flat 0 20 40 60TN:TP (molar) Chass SandRiversidesBlue CrabMidden Flat 0 500 1000 1500 2000 2500Total Phosphorus (mg/kg) Chass SandRiversidesBlue CrabMidden Flat 5 10 15 20 25OC:TN (molar) f) e) d) c) b) a)

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92 Figure 3-7. Histograms of the distribution of a) soil texture, b) depth of the surface horizon below the soil surface, c) Munsell soil value, d) Munsell soil chroma, e) Munsell soil hue, and f) the master horizon underlying the surface horizon. ‘TP’ indicates the value described in the typical pedon soil descrip tion. All data presented in histograms originates from the Riversides Map unit reconna issance soil descriptions. All data, with the exception of Figure f), reflects the surface horizon (epipedon) at the description site Munsell Soil Value 0 5 10 15 20 Number of Occurences2 0481216Depth of Surface Horizon (cm) 0 4 8 12 Number of Occurrences MuckMucky SandSandSoil Texture 0 2 4 6 8 10 Number of Occurences 01Munsell Soil Chroma 0 4 8 12 Number of OccurencesTP TP TP TP ABOMaster Horizon Below Surface 0 5 10 15 20 Number of Occurences N10YR2.5YMunsell Soil Hue 0 4 8 12 Number of OccurencesTP TP a) b) c) d) e) f)

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93 CHAPTER 4 THE SIMULTANEOUS QUANTIFICATION OF SHORT-TERM BENTHIC NITRATE REACTIONS AND DIFFUSE GROUNDWATER SEEPAGE Introduction The benthic environment plays a vital role in estuarine biogeochemical cycling and in regulating biological productiv ity (Jickells and Rae, 1997; Wall, 2004). In many coastal environments, increasing terrestrially-derived NO3 exports have been associated with environmental problems such as eutrophication and hypoxia, sometimes resulting in significant economic and ecological damage (Paerl, 2006). Ther efore, understanding benthic influences on the fate and transport of NO3 entering estuarine environments has become a significant research priority (see Paerl, 2006). However, methodological challenges have limited the investigation of two potentially important drivers of benthic NO3 cycling: 1) reactions stimulated by submarine groundwater discharge and 2) the effects of shortterm (tidal/diel) variability of environmental factors. This study presents an in situ chamber-based method that offers three distinct improvements over existing appro aches for quantifying benthic NO3 consumption and/or production in dynamic estuarine environments. These improvements include: 1) the capability to quantify benthic NO3 reaction rates over short (hourly) times cales with unprec edented precision, 2) the ability to simultaneously quantify rates of NO3 reactions and diffuse groundwater seepage (DGS), and 3) in situ NO3 analysis and near real-time data av ailability,. This approach allows for an detailed analysis of relationships between NO3 fluxes and the rate of change of environmental variables including tide, temperat ure, insolation, and DGS over short timescales (hours). Short Timescales Diel variability in estuarine environments inte grates the dynamics of tides, changing physical and chemical water column characteristics (Sakamaki et al. 2006), photosynthetically active

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94 radiation (PAR) (An and Joye, 2001) and related biological proce sses (Cabrita and Brotas, 2000; Qu et al., 2003; Sundback et al., 2004). All of th ese variables have some potential to influence NO3 cycling processes and rates at the benthic/wate r interface. In fact, r ecent measures of tidal timescale influences on benthic nutrient fluxes ha ve shown that short-term variation (hours) resulted in greater temporal variability in nutri ent fluxes than that previously attributed to seasonal or spatial variability (Sakamaki et al. 2006). These findings suggest that multiple shortterm measurements are necessary to accurately quantify the variability, drivers, and ultimately the average nutrient fluxes at a given site through time. However, multiple short-term analyses of benthic nutrient fluxes have seldom been repo rted (Sakamaki et al., 2006) due to methodological challenges discussed below. An ideal in situ method for measuring benthic nutr ient fluxes over short time periods would fulfill four main criteria: 1) provide mu ltiple high-resolution (sub-hour) measurements to discern temporal variability in nutrient fluxes, 2) represent spatial heterogeneity, 3) provide limited alteration of in situ hydrologic or biogeochemical cond itions, and 4) function well in a range of bottom substrate types (from muck to sa nd). Methods currently in-use for quantifying benthic nutrient fluxes include equilibrium porewater profilers (e.g.Weston et al., 2006;Viollier et al 2003), lab-based core incubation techni ques (Fisher and Reddy, 2001; Liu et al., 2005; Malecki et al., 2004), porewater sippers (McGlathery et al., 2001; Wigand et al., 2001), porewater profiles derived from core porewater extraction (Cook et al., 2004) and deployable benthic flux chambers (Janssen et al., 2005b; Tengberg et al., 2004; Tengberg et al., 2005). Of these methods, only a chamber-based approach is capable of quantifying short-term in situ variability of nutrient fluxes in a single location.

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95 Methodological Precision Despite the potential advantages offered by be nthic flux chambers, such as covering a large benthic surface area and allowing measurements under in situ conditions (Viollier et al., 2003), many past chamber-based experiments have been limited in te mporal resolution by methodological precision. Methodologi cal precision is a measure of the variability of a given measurement introduced by the process of sampli ng, preservation, storage, and analysis of a given analyte. Increased measurement variabilit y can potentially result in dramatic variation between actual ( in situ ) and measured concentrations of an analyte (Viollier et al., 2003). A significant effort has therefore been made to increase methodological precision by utilizing in situ analytical techniques, ther eby decreasing artifacts introdu ced by sampling, preservation, and storage (Viollier et al., 2003). Chamber-based benthic NO3 fluxes are based on the rate calculated from multiple NO3concentration measurements over ti me in a chamber sealed to the benthic substrate. The greater the number of measurements within a given in cubation, the more robust the consumption rate calculation will be. This makes in situ analysis especially important for short term chamber experiments because precise measurements are necessary to resolve the slight changes in concentration that occur within a sealed chamber over short periods of time (Figure 4-1). However, despite its potential, in situ NO3 analysis has not previously been coupled with a chamber-based approach to eval uate short-term dynamics of NO3 fluxes. Some previous shortterm chamber experiments have instead relied on a limited number of samples to calculate nutrient fluxes. For example, Sakamaki et al (2006) calculated nutrien t fluxes over a two-hour period from rates based on only two sample points. Increasing sample resolution within each short time interval could dramatically increa se measurement reliability and would provide a means to evaluate the quality of short term flux measurements. Incr easing methodological

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96 precision would also increase the overall precisi on of the final flux measurement, which could potentially reveal relationships between NO3 flux and environmenta l drivers previously unnoticed. Influence of Diffuse Groundwater Seepage Another factor complicating studies of bent hic nutrient cycling in estuaries is DGS (Billerbeck et al., 2006; Burnett et al., 2003; Burnett et al., 2006) Diffuse groundwater seepage is also known as submarine groundwater discharg e (SGD) in coastal brackish or saline water bodies and is the advective transport of groundwat er from an aquifer, through surface materials, to the water column. Submarine groundwater discha rge has become increasingly recognized as a process of paramount importance in estuarin e biogeochemical cycling (Burnett et al., 2006; Charette, 2007; Moore et al., 2006; Swarzen ski et al., 2006). Alt hough researchers have estimated SGD-driven mass nutrient export (P aytan et al., 2006; Slomp and Van Cappellen, 2004; Swarzenski et al., 2006) and studied the chemical alteration of SGD within benthic porewater (Beck et al., 2007), to the best of my knowledge there has not been a direct study of the role of SGD as a driver of nutrient cycling at the benthic/wa ter interface over short timescales (hours). Variability in SGD is often controlled by tidal elev ation (Burnett et al., 2006). Therefore, if SGD does influence benthic reactio n rates, tidal timescale variability may be an important regulator of nutrient fluxes. Common benthic flux measurement methods including microprofilers, peepers, and porewater sippers calculate nutrien t fluxes across the benthic/water interface using FickÂ’s law of diffusion and the assumption of diffusion-driven mass transport at the benthic/water interface (Hou et al., 2006; Liu et al., 2005; Ni et al., 2006 ). While this approach is appropriate for diffusion-dominated benthic/water boundaries, the assumption is i nvalidated by the presence of advective SGD flowing at even a modest ra te. However, many studies do not report an

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97 evaluation of their sampling locations for the presence of SGD. As SGD is likely an active component in many estuarine enviro nments (Burnett et al., 2006) past diffusive flux estimates in areas where advective SGD exists could dramat ically misrepresent actual fluxes by a margin determined by the rate and reactivity of SGD. Chamber designs are currently available to quantify either reacti on or diffusion-based benthic nutrient fluxes (Tengberg et al., 2004) or mass hydrologic fluxes transported across the benthic/water interface by SGD (Burnett et al ., 2006; Garrison et al., 2003). However, no method has been presented to quantify SGD-driven nutrient reactions and net nutrient fluxes (i.e. SGD-driven mass nutrient fluxes plus/minus nutrien t reactions that directly result from SGD discharge) under in situ conditions. Many SGD-based nutrient flux estimates multiply a benthic porewater nutrient concentration by an associ ated SGD rate to quantify mass nutrient fluxes (Slomp and Van Cappellen, 2004; Swarzenski et al., 2006). Others multiply chamber water nutrient concentrations by the SGD rate afte r allowing SGD to completely exchange the overlying water within the chamber (Garrison et al., 2003), likely altering the chemistry of the overlying water column and thus its interaction with benthic substrate. Neither method, however, considers that denitrification or anammox reactions may also be directly driven by SGD, stimulating a gaseous loss of N from the estuary and decreasing the net delivery of N to the estuary. Reactions stimulating a net loss of N are likely to occur given the mixing of reduced porewaters (benthic substrate) and oxidized (water column) su rface waters driven by SGD in estuarine environments. Microbial communities are known to take advantage of the gradient of electron donors and acceptors to carry out their metabolic processes. SGD driven N losses, if active, could significantly decrea se the net impact of SGD on NH4 + or NO3 concentrations in the estuarine environment. Once modified correctly, a chamber-based design can provide a means to

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98 quantify SGD and net NO3 fluxes simultaneously, thereby allo wing an evaluation of the effects of SGD driven mass transport on net NO3 cycling. In Situ Nutrient Analyses Another impediment to current chamber-based nutrient flux studies is the difficulty of knowing whether an appropriate sampling interv al was used for a given incubation until analytical results are attained up to weeks following fieldwork. High spatial and temporal variability may mean that a samp ling interval in one location, or at one time, that accurately quantified benthic nutrient fluxes, may not be ap propriate in another loca tion or under different environmental conditions. The ability to evaluate near real-time benthic NO3 fluxes in situ can offer tremendous advantages that would dramatic ally increase the effi ciency of field-based efforts. With near real-time in situ measurements, NO3 fluxes can be calculated in the field between deployments and data integrity and consistency can be ve rified immediately. Conceptual Introduction to the Method Proposed by this Study The high spatial and temporal variabili ty and complex hydrological processes characteristic of estuarine environments pos e unique challenges to those interested in understanding benthic NO3 cycling. However, this understa nding is increasingly important as more NO3 is transferred to the worldÂ’s estuarie s each year (Paerl 2006). A new methodological approach is required to overcome current limitations in sampling frequency, methodological precision, and the simultaneous quantification of SGD and NO3 fluxes. The method described in this study provides a high temporal resolution, near real-time, in situ chamber-based approach for the quantification of net benthic NO3 fluxes and the variability of its environmental drivers. The method takes advantage of readily availabl e technology including a co mmercially available in situ NO3 analyzer, peristaltic pump, sensors, and da taloggers (Figure 4-2) to increase the resolution at which benthic NO3 cycling can be studied. Sensors to measure dissolved oxygen

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99 (DO), temperature, salinity, pH, and NO3 concentrations are connected to the chamber via a flow-through cell and water is constantly cycled between th e cell and the chamber via a peristaltic pump. The chamber is fitted with a flexible bladder, allowing the movement of SGD from below into the chamber. Salinity concentrati ons are used in combination with a two-source mixing model to provide SGD estimates. All data are evaluated at the same time interval (every 30 minutes) allowing for an analys is of relationships between NO3 fluxes and the factors influencing those rates including temp erature, DO, salinity, pH, and SGD. Materials and Procedures The benthic chamber was constructed from 46 cm inside diameter (ID) fiberglass cylinder (Aquatic Ecosystems; Apopka, FL; Figure 4-2) with a height of 30 cm. The chamber material is approximately 90% translucent to photosynt hetically active radi ation (PAR; 400-700-nm wavelengths). The cylinder was sealed at one end using a 0.635 cm thick acrylic sheet and silicone aquarium sealant. Four 5 cm holes we re machined into the sides of the chamber to accommodate rubber stoppers. Rubber stoppers (#10; Fisher Scientific; Pittsburgh, PA) were then drilled to accommodate 1 cm ID PVC tubi ng while maintaining a watertight seal. A flexible bladder was attached to the chamber to equilibrate inner and outer water pressure through the changing tidal cycle and to allow SGD to enter the chamber. A 1 cm ID flexible PVC tube was connected to a peristaltic pump (Masterflex E/S Portable Sampler, Cole-Parmer Instrument Company; Ver non Hills, IL) and the flow rate was calibrated at 200mL/min. The peristaltic pump drew water from one side of the chamber, through a flowthrough cell constructed of 6 cm ID, 0.635 cm thick, acrylic tubing, a nd back into the other side of the chamber. One end of the flow-through cell was sealed with a rubber stopper (#11) drilled to accommodate the filter head for a YSI 9600 in-situ NO3 analyzer (YSI Environmental; Yellow Springs, OH). The YSI 9600 utilizes flow-injection and in situ filtering in order to

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100 analyze NO3 using the well known cadmium-reduction me thod (Strickland et al., 1972). An accuracy of 5% or 0.01mg/L and a precision of 0.002mg/L NO3 --N were reported by YSI when using its protocols for sample analysis and post-processing. Those protocols were followed during this study and the accuracy and precisi on were confirmed under laboratory conditions prior to deployment. The other end of the fl ow-through cell was fitted with a rubber stopper (#11) drilled to accommodate a YSI 6000 series multi-probe sonde. Variables monitored using the datalogging multiprobe sonde included temperature, conductivity, salinity, pH, and DO. Fluid flow across all probes was maintained th roughout the experiment vi a the peristaltic pump which ran throughout the experiment. Environmental Data Tidal variation was measured using a dataloggin g pressure transducer (“Mini-Troll” by InSitu Inc; Ft. Collins, CO). The pressure transducer was installed in an acrylic well to reduce any variability due to water velocity. The well was su bmerged in the water column (but not into the benthic substrate) and secured to a rod that had been firmly embedded in the channel bottom. Photosynthetically active radia tion (PAR) measurements were made using two Li-COR Quantum Sensors (Li-COR; Lincoln, NE), one each for ab ove and below the water surface (LI-190 and LI192, respectively). Both light sensors were conne cted to millivolt adaptors (Li-COR part number 2291 and part number 2290 for surface and subsurface sensors, respectively) and wired to a CR1000 datalogger (Campbell Scientif ic; Logan, Utah). Four pla tinum-tipped redox electrodes were installed in the chamber so as to contac t the upper 1-2 cm of the benthic surface and were connected to the CR1000 datalogger along with a calomel electrode that was submerged in the water column. The CR1000 datalogger was progra mmed to measure sensor voltages once per second, correct voltages to a standard hydrogen el ectrode, and calculate and store averages and standard deviations at 5 and 30 minute intervals.

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101 All dataloggers were time-synchr onized prior to deployment a nd set to record data at 5minute intervals, with th e exception of the YSI 9600 NO3 analyzer, which l ogged at 30 minute intervals. All sonde probes were calibrated hours prior to depl oyment with the exception of DO, which was calibrated just prior to deployment after allowing at least 30 minutes for the DO probe to become polarized. All chemical reagents in the YSI 9600 were supplied by YSI, with the exception of the NO3 standard, which was purchased from Fisher Scientific. Three separate subsamples of the final mixed standard reag ent were analyzed by a Florida DEP-certified laboratory (Dawn Lucas, University of Florida) and the mean of three values was determined to be 0.290mg/L. The standard solution was us ed to continuously calibrate the YSI 9600 in situ at two hour intervals using its native automated program throughout the experiment. A standard YSI pre-deployment check was conducted immedi ately before deployment and no problems or issues were detected. Method Assessment Site Description: Chassahowitzka River Florida’s Gulf Coast is tidally influenced, underlain by a large karst aquifer, and covered with a diverse assemblage of benthic substrates. Multiyear trends of increasing NO3 concentrations in coastal spri ngs result from elevated terrest rial anthropogenic deposition of N and its transfer though the karst Floridan Aquifer (Frazer, 2000; Frazer et al., 2001; Frazer et al., 2003; Jones et al., 1997; Katz et al ., 2001b; Scott et al., 2004). Co astal spring-fed rivers draining the Floridan Aquifer have varying capacities to “mitigate” NO3 loads along the length of their runs, and therefore contain distin ct capacities to reduce N-loading to sensitive coastal ecosystems (Frazer, 2000; Frazer et al., 2001; Frazer et al., 2003). However, at present, the mechanisms behind the observed decreases in NO3 -concentrations are not well understood.

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102 The upper sections of the Chassahowitzka Rive r on FloridaÂ’s Gulf Co ast are characterized by a distinct spatial gradient of NO3 concentrations, decreasing from the brackish springhead into the coastal estuary and signaling a hi gh potential for the bent hic regulation of NO3 uptake (Chapter 2). The method evaluation site was located within a tidall y-influenced reach less than 1 km from the spring source and is considered the low salinity (~2.6 ppt ) end-member of the estuarine gradient. Brackish SGD in the area is likely a combinati on of terrestrial freshwater and brackish waters mixed within the subterran ean estuary. Based on large scale mass balance calculations, the most significant downstream decreases in NO3 concentrations also occur in this area (Chapter 2, Transect 2). In areas similar to the site, bottom textures ranged from mucky sand to sand and organic matter (OM) content ranged from 1-46% through the soil, with the highest OM values measured at the surface (Chapter 3) Dark colors and odor indicated the presence sulfides just below the benthic surface at the study site. Chamber Deployment The chamber was slowly and carefully embedde d in the benthic substrate such that the chamber wall was submerged 15 cm below the benthi c surface. The chamber was left with ports open to equilibrate for over an hour. Following the equilibration period, all dataloggers were engaged and the chamber was sealed using th e rubber stoppers and fl ow-through circuit. Six chamber incubations were conducted over a tw enty-four hour period. The chamber was opened for a minimum of one hour betw een incubations. During this tim e, one end of the flow-through circuit was placed in the water column, pu mping surface water from the surrounding water column into the chamber. This was done to re -equilibrate the chamber with the overlying water column, which was constantly altered in res ponse to tidal and diel variability. Chamber incubations and monitoring began at 6:30PM Eastern Standard Time on April 24, 2007 and ended at 6:00PM on April 25, 2007.

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103 Benthic Flux and Biogeochemi cal Reaction Calculations Data were assembled into a database that included 30 minute averages of environmental and chamber variables and NO3 concentration data. Data from equilibration periods were removed and the rate of change of all variab les was calculated for each incubation using the least-squares fit of the slope of time (hours) versus concen tration data for the parameter of interest. Chamber volumes were calculated by measuring the average height of the chamber above the benthic substrate, measured on four sides of the chamber, and multiplying by the chamber cross-sectional area. Th e volume of the flow-through ce ll and bladder was measured by filling the entire extent of the cell and conduit with water and m easuring the resulting volume in a graduated cylinder. Changes in NO3 and DO concentrations expressed on the basis of mass/area/time were considered to be net additions or losses across or in response to reactions occurring at the benthic/water in terface. Linear regression was utilized to evaluate significant relationships between NO3 and DO addition and losses and the rates of change of the environmental variables measured. All data anal ysis was completed using Splus 6.1 (Insightful Corp., 2002; Seattle, WA). The technical definition of the term “flux” refe rs to the mass transfer of a given material across a boundary of known area in a specific amount of time. However, much of the literature measuring reactions at the benthic/water inte rface over time actually re fer to mass transfers across or in response to the benthic/water interface; meaning that although some reactions occur at the benthic water interface, the mass movement of the chemi cal species across the interface may never occur. In keeping with the tech nical definition, results quantifying changes in concentration across or in response to the bent hic/water interface will be referred to here as additions or losses. It shoul d be noted however, that the general approach to making and calculating the chamber measurements for measuri ng fluxes or additions and losses is the same.

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104 Therefore, what have commonly been termed as “f luxes” are comparable with what is described here as an addition or loss. The one exception is SGD-driven dilution wh ich causes an apparent loss of concentration and is discussed below. Calculating SGD and SGD-Dr iven Influences on NO3 Additions and Losses Consistent decreases in salinity concentra tions within the chamber during all chamber incubations were assumed to be caused by SGD. Freshwater discha rging from the aquifer at the springhead had a salinity concentration of appr oximately 2.6 ppt. Surface waters that had mixed with more saline waters, were characterized by el evated salinity concentra tions that ranged from 2.9-3.5 ppt in the water column during the course of this experiment. Therefore, when aquifer water (SGD) (2.6 ppt) was mixed with surface wa ter (2.9-3.5 ppt), dilution of the overlying water column with SGD produced a consistent decrease in salinity. Dilution consistently occurred within the chamber rega rdless of outside salinity con centration, suggesting that SGD occurred at some rate throughout the entire period of study. To estimate the volume of water associated with SGD, a two-source mixi ng model was utilized. The volume of SGD ( VSGD) was calculated as follows: VSGD = ((Ci – Cf)/( Ci-CSGD))*VChamber (4-1) where Ci = initial chamber salinity, Cf = final chamber salinity, CSGD = assumed SGD salinity (2.6 ppt), and VChamber = final volume of the chamber. VSGD was normalized to the surface area of the chamber in contact with the benthic substrat e to produce discharge rates normalized to units of L/m2/day. The benthic substrate was measured for re dox potential at four lo cations and values averaged well below -100mV which suggested that no NO3 was present beneath the benthic surface under these highly reduced conditions. Gi ven this information, it was assumed that NO3 was not present within the SGD that was transported through the chemically reduced conditions

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105 of the organic-rich bottom. To estimate the effects of SGD on NO3 additions and losses within the chamber, it was necessary to calculate the proportion of the total mass NO3 decrease accounted for by both conservative dilution (i.e SGD-based dilution) and non-conservative biogeochemical reactions (i.e. biological a ssimilation, denitrificat ion, anammox reactions, dissimilatory NO3 reduction to ammonium, or any other reaction that would alter NO3 concentrations). The former can be calculated as: VTSGD = (1-(Cf/ Ci))*VChamber (4-2) where VTSGD = theoretical volume of SGD require d to account for observed changes concentration (used for NO3 and DO), Ci = initial chamber concentration, Cf = final chamber concentration, and VChamber = final volume of the chamber. The latter was calculated as: Fcp = (VSGD/VTSGD)*100 (4-3) where Fcp = the percentage of VTSGD accounted for by conservativ e dilution (of either NO3 or DO). The losses unaccounted for by conservative dilution were assumed to result from nonconservative biogeochemical reactions. Fncp = 100-Fcp (4-4) where Fncp = the percentage of the additions or losses accounted for by non-conservative biogeochemical reactions. Percentages where th en multiplied against actual measurements of additions and losses to calculat e the additions and losses due c onservative and non-conservative processes. It should also be noted that dilution only causes an apparent loss of NO3 and that total NO3 mass is conserved within the chamber. Results Diel Variation Over the period of study, the average photon flux density ranged from 0-1200 mol/m2/min, following the variability expected of a diel cycle (Figure 4-3). Temperature (range

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106 = 23-26C), DO (range = 140-480 M), and pH (range = 7.1-8.0) incr eased markedly in the water column with photon flux. NO3 concentrations ranged from 11-26 M in the water column and were highest when salinity was lo west, indicating a freshwater NO3 source. Tidally driven changes in water column elevation roughly co-v aried with the diurnal light cycle; low tide occurred at 7:30AM and the tidal high was at approximately 4PM (Figure 4-3). Generally, nighttime values were associated with a falling tide while daytime values were associated with a rising tide. Wind was light th roughout the daytime hours of the experiment and almost completely calm during the night. There wa s no precipitation and scattered cloud cover throughout the duration of the field trial. Benthic Reactions and Environmental Variability Table 4-1 presents the rates of change for all water and environmental constituents calculated using slopes of data segments indicated by lines show n in Figure 4-4. Each segment represents an incubation period, each sepa rated by a period of ch amber re-equilibration. Apparent NO3 losses ranged from -112 to -385 mol/m2/hr and DO additions and losses ranged widely from -5059 to 5332 mol/m2/hr (Table 4-1; Figure 4-4). DO losses occurred during the nighttime hours while additions occurred concom itant with the strongest period of insolation (incubation 5, Figure 4-4). Temperatur es decreased at night at a ma ximum rate of -0.61C/hr and increased during the day at a maximum rate of 0.61C/hr. Salinity concentrations consistently decreased during all incuba tions; however, the rate of salinity decrease varied from -0.007 to 0.024 ppt/hr (Table 4-1, Figure 4-4), equiva lent to an SGD rate of 50.7-175.8 L/m2/day. NO3 Additions and Losses and Their Relati onships to Environmental Parameters Net NO3 losses were positively correlated with NO3 concentration (r2 = 0.65; P=0.056) throughout the study period. When the outlying da ta point from incubation 3 was removed, net NO3 losses were significantly related with NO3 concentrations (Figure 4-5; r2 = 0.997; P<0.001)

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107 and SGD rate (r2 = 0.94, P<0.01; Figure 4-6). Finally, SGD was related to water column elevation (Figure 4-7; r2 = 0.69, P = 0.08), though SGD appeared to vary during ebb and flood tides (Figure 4-7). It should be not ed here that salinity dilution (i .e. SGD) occurred regardless of the relative salinity outside the chamber or tida l elevation. Even when salinities outside the chamber were elevated in comparison to waters inside the chamber, the chamber salinity concentrations would continue to decrease. The one exception, left in Figure 4-4 as an example (but not included in calculati ons), occurred during the final chamber incubation (Incubation 6, Figure 4-4). In that case, a r ubber stopper was dislodged as the result of a wake of a passing watercraft, causing an immediate increase in sali nity concentrations. Thes e results demonstrate a reliable seal between the chamber and the underl ying benthic substrate an d show that SGD was continually flowing from the bent hic substrate into the chamber. Submarine Groundwater Discharge Two distinct modes (“conservative” and “ non-conservative”) of SGD influence were evaluated for their significance in altering NO3 concentrations. The conservative mode accounted for dilution of NO3 concentrations that resulted from mixing SGD waters depleted in NO3 with surface waters rich in NO3 -. On average, conservative S GD-derived dilution accounted for 28% (range = 17-54%; Table 4-2) of the observed changes in NO3 concentration. Other factors (non-conservative) on average accounted for the remaining 72% (range 46-83%) of NO3 losses observed within the chamber system. Data Interpretation In accordance with the findings of Sakamaki et al. (2006), strong variability was observed for in situ water column physical and chemi cal parameters and resulting NO3 additions and losses at the benthic/water interface in response to tidal and diel temporal variation. However, the temporal resolution, preci sion, and capacity to measure SGD provided by the methodology

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108 introduced here also allowed for an evaluation of relationships between SGD, tidal elevation, light, temperature, water column elevation and NO3 additions and losses over multiple chamber incubations over a diel time period. While previous benthic nutrient flux studies in estuarine environments have not addressed SGD-driven bioge ochemical reactions, in this field trial, SGD was significantly related to c onservative and non-conservative NO3 losses. In fact, regardless of marked diel variation in light, temperature, pH, and DO concentrations, both SGD and water column NO3 concentrations were significantly related to NO3 losses. While benthic NO3 concentrations have been related to benthic NO3 losses in a number of studies (Laursen and Seitzinger, 2004; Seitzinger et al., 2006; Seitzinger, 1987), SGD ha s not been directly linked to reactions at the bent hic/water interface. The potential role of SGD in altering observed benthic NO3 additions or losses may be two-fold: 1) exfiltration of groundwater depleted in both NO3 and DO into the river and estuary will result in dilution of surface water NO3 concentrations (conservative dilution) and 2) incoming SGD may influence in-stream nutrient concentrations by providing reactants for the chemical alteration of water column nutrient sp ecies via denitrificati on, anammox, or other NO3 reduction reactions (non-conservati ve reactions). While NO3 reduction, denitrification, and the influence of reduced compounds have been obs erved at the benthic/water interface in many environments (see Bianchi, 2007), no study that I am aware of has evaluated how SGD modifies these processes. Continued work and a larger study will be needed to test the hypothesis that SGD acts as a significant driver of benthic NO3 reactions. Although aquifer groundwater at the research site is known to have appreciable NO3 concentrations in its limestone-dominated matr ix, the sand and OM-dominated benthic substrate provided a chemically reduced environment, indi cating very low to non-existent concentrations

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109 of NO3 -. This suggests that chemical reduction in the benthic substrate is key for reducing NO3 concentrations in two spatially-distinct sites within the river-estuarine system. The first site is at the base of the highly-reduced subaqueous soil environment. As aquifer groundwater enriched with anthropogenic NO3 exfiltrates from limestone and passes up into the benthic substrate, NO3 is likely lost to microbial uptake and reduc tion reactions. This mechanism is hypothesized based on known elevated NO3 concentrations in the aquifer, calculated SGD rates, and redox measurements taken in the field that preclude a significant presence of NO3 -. The second site of benthic-mediated NO3 reduction likely occurs at the subaque ous soil/water column interface. Flows of SGD through the benthic interface likely deliver reduced chemical species towards the water column that fuel NO3 reduction not only at the benthic/wa ter interface but perhaps in the water column above. Again, more detailed analyses must be undertaken in the future to test the above-mentioned hypothetical relationships. Ultimately, the electron source for NO3 reduction reactions is de rived from the microbial oxidation of organic matter incorporated into the benthic substrate. Given the hypothetical influence of SGD discussed above, one would expect that substrates with distinct physical and chemical characteristics, particularly organic matt er content, will vary in their interaction with the SGD moving through them (Ni et al., 2006). Al so, the rate of SGD at a given location will vary with the transmissivity of a given substrate, which in turn vari es with the particle size, bulk density, and organic matter content. Based on these observations, anot her hypothesis emerges: Benthic substrate properties signi ficantly influence the chemical properties and rate of SGD. Given that SGD varies with tide and as a func tion of bottom type, it is also likely that the temporal variability of SGD-driven NO3 reactions will also be different between distinct bottom types.

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110 Given the context of increasing NO3 contamination of the Florid an Aquifer, the value of coastal resources to the state of Florida, and their sensitiv ity to anthropogenic disturbance (e.g. Chapter 2), the SGD-related proc esses reported herein may be qu ite important at the regional scale. At this time it is impossibl e to state that these processes are occurri ng all along the coast. However, research in FloridaÂ’s coastal envi ronment has shown that SGD is occurring at appreciable rates (Burnett et al., 2003; Martin et al., 2006; Swarzen ski et al., 2007; Swarzenski et al., 2006). Also, strong decreases in NO3 concentrations have been observed from source to sea in many coastal spring-fed rivers (Frazer et al ., 2006; Frazer et al., 2001). As SGD is a common occurrence globally (Burnett et al., 2003), the interaction of SGD, benthic substrate, and reactions at the benthic/water inte rface could have greater signifi cance and is in need of more detailed study. Discussion The method described above addresses the me thodological challenges of providing highresolution, real-time, in situ measurements of NO3 concentration, SGD, and environmental parameters via a chamber-based approach. Th e method was capable of quantifying rates of change of these variables via multiple incubations within the diel and tidal timescale. The data provided sufficient resolution for the evaluation of relationships be tween the rates of change of all measured variables and increased measurement precision by eliminating variability introduced by sample preservation and storage. SGD was calculated concomitantly with NO3 losses under in situ conditions with high temporal resolu tion for the first time. At the method evaluation site, it appeared that SGD had the poten tial to be particularly important in influencing rates of benthic NO3 reactions. This method has the pot ential to provide new and valuable insight into the impact of SGD on benthic biogeochemistry in estuarine environments.

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111 Estuarine areas subject to significant rates of SGD require a new approach, such as the one presented, to quantify nutrient additions and losses at the benthic/water interface. In areas with appreciable rates of SGD, studies based on assumptions of diffusive transport may dramatically misrepresent nutrient additions or losses, given that porewater is actively flowing into the water column. Previous chamber-based methods that di d not provide a bladder for the infiltration of SGD may alter benthic hydrology, and thus coul d potentially influence their reported flux measurements. Past benthic flux studies carried ou t in areas with a high potential for SGD should be interpreted with caution, give n that the role of SGD may not have been accounted for. The method described above will allow for de tailed research into the various factors affecting net NO3 reactions at the benthic/water interface. The method can be used to study the role of plants, various substrates sites with differing rates of SGD, or sites with different tidal scale variability. Short-term va riations resulting from pulse ev ents such as elevated rainfall events can also be evaluated for their impact on benthic NO3 cycling. Further, manipulative experiments focused on determining the influenc e of nutrient additions distinct light and temperature regimes, or altered water column characteristics can be also carried out in situ and in near real-time to experimentally de termine their influence on benthic NO3 consumption. Although this method is specifica lly designed to quantify net NO3 and DO reactions, as in situ analytical technology becomes available, other nutrie nt species, gases, or heavy metals can also be evaluated over the short te rm and in response to SGD. Comments and Recommendations Although the reported methodology was evaluate d in a sand-dominated environment, chamber deployments in organic matter rich estu arine deposits should be feasible without any modification. However, the two-source mixing model approach presented here requires two distinct sources of chemical constituents (SGD porewater and the overlying water column) that

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112 have contrasting salinity concentr ations. This should not presen t a problem in most cases, as SGD is generally more dominated by freshwater in many estuarine enviro nments, However, this may present a problem where there is very little to no difference between salinities in porewater and the overlying water column. In those cases, it may be possible to introduce a conservative tracer into the chamber to quan tify SGD rates, though this was not evaluated as a component of this study. It may also be possible to couple this chamber-based approach with those designed to measure SGD at fine temporal intervals. For example, Swarzenski et al. (2006) utilized an electromagnetic seepage meter to measure rates of SGD. If integrated into the chamber described in this study, the seepage meter could eliminate the need for the two-source mixing model. The initial deployment of this method was carried out in an area with slow-moving water column velocities of generally <0.01 m/s. However, recent research has show n that at sites with elevated water velocities, advection-driven exch ange across the benthic/wa ter interface can also dramatically influence measuremen ts of benthic nutrient cycling. Janssen et al. (2005) developed a method to simulate advective conditions with in a chamber using a horizontal paddle and motor-driven mixing approach. The method presented here could also be modified to incorporate an advective stirring component and thus quantif y both advective-driven exchange (Janssen et al., 2005a; Janssen et al., 2005b) and SGD-driven influences on net benthic NO3 reactions. This in situ high temporal resolution, multi-parameter approach to quantifying benthic NO3 additions and losses should greatly incr ease our understanding of the variability, mechanisms, and drivers influencing NO3 cycling in many coastal and estuarine environments. Future work comparing various substrate t ypes, the influence of macrophyte and algal communities, and focused over longer time periods (weeks) or during distinct time periods

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113 (storms/high NO3 loading) will likely yield valuable insight into the dynamics and drivers of an important component of estu arine biogeochemical cycling.

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114Table 4-1. Rates of change for all parameters of intere st calculated during each of the six incubation periods Incubation Date/Time* Night/Day (tide) NO3 mol/m2/hr DO oml/m2/hr Water elevation cm/hr Temp C/hr Salinity ppt/hr pH units/hr Light intensity (surface) mmol/m2/min Light intensity (underwater) mol/m2/min 1 4/24/07 19:30 Night (high) -165-50594.22-0.510-0.010-0.002-263.8-188.8 2 4/24/07 23:15 Night (high) -112-3393-3.98-0.606-0.005-0.023-0.612.3 3 4/25/07 3:30 Night (low) -205-3164-3.31-0.062-0.014-0.014-18.6-8.7 4 4/25/07 7:30 Day (low) -385-2079-0.490.039-0.036-0.00265.13.2 5 4/25/07 11:30 Day (low) -28653329.100.606-0.0200.020109.665.9 6** 4/25/07 14:45 Day (high) NANA4.41NANANA90.4-52.2 Note: Dissolved oxygen (DO), total dissolved solids (TDS); *Times represent the mid-point of ea ch incubation period; **Incubation 6 was disturbed by a passing watercraft and ther efore rates of change were not calculated for parameters measured within the cham ber

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115Table 4-2. Estimates of submarine groundwater discharge (diffuse porewater seepage) rates and the conservative and non-conserva tive additions and losses of NO3 and dissolved oxygen Volume of SGD hypothetically required to produce observed changes in concentration (Liters) NO3 losses accounted for by conservative and non-conservative processes (%) DO additions and losses accounted for by conservative and nonconservative processes (%) SGD Rates (L/m2/day) Incubation Date/ Time* NO3 Salinity DO Conservative NonConservative Conservative NonConservative Salinity-based SGD estimation 1 4/24/07 19:30 3.6 0.70.82377 98250.7 2 4/24/07 23:15 4.1 0.72.92080 287241.7 3 4/25/07 3:30 2.9 2.44.25446 3862175.8 4 4/25/07 7:30 7.0 2.85.02971 4159133.9 5 4/25/07 11:30 4.6 1.1-5.21783 -15ND81.5 Mean 4.4 1.61.62872 386296.7 Note: Dissolved oxygen (DO), total dissolv ed solids (TDS), submarine groundwater discharge (SGD), not determined (ND); *Times represent the mid-point of each incubation period. Incubation 6 is not presented as the measurement was disturbed by a passing watercraft

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116 Figure 4-1. The theoretical relationship be tween sampling intervals necessary to calc ulate nutrient chamber-based additions an d losses vs. the method precision necessary to provide adequate information for the calculation of nutrient addition and loss rates. As the sampling interval decreas es, the precision to resolve slight differe nces in concentration increases rapidly Sampling interval (time between measurements) Method p recision necessar y Previous methods This method

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117 Figure 4-2. Schematic of benthic chamber in strumentation and deployment configuration. Not pictured is a flexible bladder conne cted to the side of the chamber via a rubb er stopper which allows the exchange of SGD. Note: Figure not to scale Redox p robe Campbell datalogger YSI datalogger Pressure transducer Light meter Light meter Mini-troll datalogger Subaqueous soil 42 cm 46 cm 15 cm 30 cm Wate r co l u mn YSI 9600 Nitrate Analyzer Peristaltic pump

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118 Figure 4-3. Diel variation in a) solar irradiance, b) mean water column height, c) temperature, and d) NO3 concentration averaged by incubation period. An in situ incubation was conducted during each of these unique combinations of conditions. The x-axis represents the midpoint of the incubation period, staring at 8PM Eastern Standard Time, and therefore does not extend across the entire temporal range 8:00 9:00 10:00 11:00 12:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 1:00 2:00Apr 24 2007 Apr 25 2007 22 23 24 25 26Temperature ( C) 7.0 7.2 7.4 7.6 7.8 8.0pH Temperature pH 8:00 9:00 10:00 11:00 12:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00 12:00 1:00 2:00Apr 24 2007 Apr 25 2007 0 400 800 1200Average Photon Flux Density ( mol/m2/min) 8:00 9:00 10:00 11:00 12:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00Apr 24 2007 Apr 25 2007 10 14 18 22Mean NO3 Concentration ( M) 150 200 250 300 350 400 450Mean DO Concentration ( M) NO3DO 8:00 9:00 10:00 11:00 12:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00 11:00Apr 24 2007 Apr 25 2007 50 55 60 65 70 75 80Mean Water Column Height (cm) 2.9 3.0 3.1 3.2 3.3 3.4 3.5Mean salinity (ppt) Water Column Height Salinitya) d) c) b)

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119 Figure 4-4. Regression lines used to calculate the rate of change for a) Water column elevation, b) dissolved oxygen, c) temperatur e, d) nitrate, e) salinity, f) pH, g) light (i.e. solar irradiance). The x-axis in graphs a-g is hours from the beginning of the experiment and began at 6:30PM Eastern Standard Time 1256910131517182122Hours 50 60 70 80 90Water Column Elevation (cm) Incubation: 1 Incubation: 2 Incubation: 3 Incubation: 4 Incubation: 5 Incubation: 6 1256910131517182122Hours 22 23 24 25 26Temperature ( C) Incubation: 1 Incubation: 2 Incubation: 3 Incubation: 4 Incubation: 5 Incubation: 6 1256910131517182122Hours 100 200 300 400 500Dissolved Oxygen () Incubation: 1 Incubation: 2 Incubation: 3 Incubation: 4 Incubation: 5 Incubation: 6 1256910131517182122Hours 10 15 20 25Nitrate ( ) Incubation: 1 Incubation: 2 Incubation: 3 Incubation: 4 Incubation: 5 Incubation: 6 1256910141517182122Hours 2.8 3.0 3.2 3.4Salinity (ppt) Incubation: 1 Incubation: 2 Incubation: 3 Incubation: 4 Incubation: 5 Incubation: 6 1256910131517182122Hours 7.0 7.2 7.4 7.6 7.8 8.0pH Incubation: 1 Incubation: 2 Incubation: 3 Incubation: 4 Incubation: 5 Incubation: 6 1256910131517182122Hours -200 300 800 1300 1800Light ( mol/m2/s) Incubation: 1 Incubation: 2 Incubation: 3 Incubation: 4 Incubation: 5 Incubation: 6d) c) e) f) g) b) a)

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120 1012141618202224NO3 -Concentration ( M) -400 -350 -300 -250 -200 -150 -100Total NO3 Losses ( mol/m2/hr) Excluded point from Incubation 3 y =146.1 22.9*x 1012141618202224NO3 Concentration ( M) -120 -100 -80 -60 -40 -20Conservative NO3 Losses ( mol/m2/hr) y = 69.9 7.6*x 1012141618202224NO3 Concentration ( M) -300 -250 -200 -150 -100Non-conservative NO3 Losses ( mol/m2/hr) excluded outlier Incubation 3y = 84.5 15.9*x Figure 4-5. a) Conservative and b) non-conservative NO3 losses and their relationship to NO3 concentration. Incubation 6 is excluded due to an accidental chamber opening during the incubation. Incubation 3 is considered an outlier for the e quation calculated in Figure a and c. However, incubation 3 also had the highest rate of SGD, which may have modified the strong relationship between NO3 concentration and its rate of uptake (or production). This relationship warra nts further investigation in the future a) b) c)

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121 20406080100120140160180SGD (L/m2/day) -410 -360 -310 -260 -210 -160 -110Total NO3 Losses ( mol/m2/hr) Excluded point from Incubation 3 y = -15.5609 2.8755*x Figure 4-6. Relationships between submarine gr oundwater discharge (S GD) and a) total NO3 losses, b) conservative NO3 losses, and c) non-conservative NO3 losses. Incubation 6 is excluded due to an accidental chambe r opening during the incubation. Incubation 3 is considered an outlier for the equa tion calculated in Figure a. However, incubation 3 also had the hi ghest rate of SGD, indi cating a potential non-linear relationship as shown in Figure c. This re lationship warrants further investigation in the future 20406080100120140160180SGD ( L/m2/da y) -300 -250 -200 -150 -100Non-conservative NO3 Losses ( mol/m2/hr) y = 239.5 9.5*x + 0.04*x2 20406080100120140160180SGD ( L/m2/da y) -140 -120 -100 -80 -60 -40 -20Conservative NO3 Losses ( mol/m2/hr) y = 2.6 0.71*xa) b) c)

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122 50556065707580Water Column Elevation (cm) 10 60 110 160SGD (L/m2/day) Ebb Tide Flood Tide Figure 4-7. Submarine groundwater di scharge (SGD) as related to water column elevation. SGD rates are highest when the water column elev ations are low, likely due to a decreased pressure once the volume of overlying water was decreased

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123 CHAPTER 5 SYNTHESIS: BIOGEOCHEMICAL DYNAMIC S OF SUBAQUEOUS SOILS IN THE CHASSAHOWITZKA SPRING-FE D RIVER AND ESTUARY Anthropogenic impacts at the global scale contin ue to influence the coastal environment. FloridaÂ’s valuable coastal resources are particularly susceptible to anthropogenic impacts, especially given the karst nature of Fl oridaÂ’s geology. The interconnectivity between anthropogenic activities on land and rising nutrient con centrations at the springhead was shown in Chapter 2. Significant positive correlations between annual precipitation and NO3 concentrations strong ly suggest that NO3 is quickly transported fr om the surrounding terrestrial environment and into the river and estuarine system The analysis in Chapter 2 demonstrated that receiving water bodies and associat ed benthic substrate have dis tinct abilities to ameliorate excess NO3 and soluble reactive phosphorus (SRP) con centrations. Along th e upper transect of the Chassahowitzka River NO3 losses increased in proportion to the total NO3 load while increases in SRP losses did not change significantly under high SRP loading conditions. Despite the capacity of the system to uptake additional amounts of NO3 -, both NO3 and SRP concentrations increased significantly at transect 10 in response to elevated nutrient loading conditions suggesting that the na tural buffering capacity of elev ated nutrient concentrations along the upper transects of the study area had been maximized. Benthic substrate likely plays a dominant role in the biogeochemical cycling of N and P, especially in along the upper transects of the Chassahowitzka River. Mapping the spatial distribution of subaqueous soils within the Ch assahowitzka River and Estuary and determining their basic physical and chemical properties was the subject of Ch apter 3. It is well known that the nature of benthic substrate (i.e. its physical and chemical properties) will likely influence its function in the environment. Therefore, understa nding large-scale trends in the distribution of subaqueous soils and their physical and chemical properties is extremely important in the

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124 determination of the location of nutrient cycli ng hotspots. Chapter 3 al so provided a pedological perspective on the factors that c ontrol the properties of benthic s ubstrate within each map unit. Soil properties are an integrated manifestati on of the climate, organisms, bathymetry, parent material, hydrology, and disturbance regime of their surrounding environments as discussed in Chapter 3. Environmental drivers and soil forming factors therefore create an equilibrium condition in the struct ure of subaqueous soil, which in-t urn influences its function in the environment. Chapter 4 provided a focuse d on evaluating a new method to quantify the variability, drivers, and net func tion of a particular soil in NO3 cycling. This method was evaluated in the Chassahowitzka River and Estu ary and provided valuable new insight into NO3 cycling at the benthic-surface water interface. The subaqueous soil chosen for study was located in the upper transects most of ten exposed to elevated NO3 concentrations. Findings from Chapter 4 demonstrated strong diel an d tidally-dependent variability in NO3 flux rates. New insights into the complex inte ractions between subaqueous so il properties, regional hydrology and submarine groundwater discharge, and NO3 concentration and loss rates were gained from this research. This new and novel method has opened significant doors for future hypothesisdriven research. Synthesized, the research presen ted in this dissertation has reshaped the current conceptual understanding of how the Cha ssahowitzka River and Estuar y processes nutrients and characterized the systemÂ’s vulnera bility to anthropogenic activities. New insight s into the role of submarine groundwater discharge, tidal variability, nutrient flux ra tes, seasonal and decadal scale nutrient distributions and proces sing, and the distribution and properties of subaqueous soils have provided information valuable for both mange rs of local water resources as well as for future investigations.

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125 APPENDIX A SUPPORTING SOIL PHOTOS AND MINERALOGICAL ANALYSES Riversides Figure A-1. Riversides soil core and micr oscopic images for reference purposes

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126 Figure A-2. Riversides soil core near on the lateral edge of Crab Creek

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127 Blue Crab Figure A-3. Blue Crab soil core and micr oscopic images for reference purposes

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128 Figure A-4. Blue Crab soil core w ith a large krotovina. Krotovina were relatively common in the Blue Crab map unit

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129 Midden Flats Figure A-5. Midden Flats soil core and micr oscopic images for reference purposes

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130 Chass Sands Figure A-6. Chass Sands soil core for reference

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131 Figure A-7. Chass Sands augered soil sampled during reconnaissance work

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132 Figure A-8. Chass Sands soil core with a clay-enriched horizon at its base

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133 Figure A-9. Subsample from clay enriched horizon from figure above Figure A-10. Microscopic photo of potential biomineralization site from sample in Figure A-9

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134 Figure A-11. Microscopic photo of potentially bi omineralized spherules from the sample in Figure A-9 Figure A-12. Microscopic photo of potentially biomineralized framboidal pyrite from the sample in Figure A-9

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135 Figure A-13. What appear to be iron-based, r ounded minerals from the sample in Figure A-9 Figure A-14. Differential scanni ng calorimetry results for clays from the sample in Figure A-9

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136 Figure A-15. X-ray diffraction resu lts from clay and silt fractions taken from the sample in Figure A-9 Figure A-16. Scanning electron microscope im age of minerals sampled from Figure A-9

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137 Figure A-17. Scanning electron microscope image of framboidal pyrite taken from the sample in Figure A-9

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138 Figure A-18. Augered soil from the a densely vegetate d site in the Chass Sands map unit of Crab Creek

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139 APPENDIX B RAW FLUX MEASUREMENT DATA Table B1. Five minute dataset of chamber and environmental data. SpCond = specific conductivity, DO = dissolved oxygen Date and Time Water Elevation (cm) Temperature (C) SpCond (mS/cm) Total Dissolved Solids (g/L) Salinity (ppt) DO (M) pH 4/24/07 17:30 71.1 25.58 6. 666 4.333 3.64 422.50 8.03 4/24/07 17:35 71.1 25.88 6. 444 4.189 3.51 458.75 8.07 4/24/07 17:40 71.2 25.83 6. 418 4.172 3.49 478.75 8.09 4/24/07 17:45 71.4 25.74 6. 38 4.147 3.47 433.75 8.07 4/24/07 17:50 71.7 25.71 6. 334 4.117 3.45 421.88 8.06 4/24/07 17:55 71.6 25.68 6. 281 4.083 3.42 416.25 8.04 4/24/07 18:00 71.6 25.38 6. 329 4.114 3.44 401.88 8.01 4/24/07 18:05 71.7 25.76 6. 233 4.051 3.39 411.25 8.02 4/24/07 18:10 71.8 25.74 6. 205 4.033 3.37 406.88 8.02 4/24/07 18:15 72.1 25.73 6. 19 4.023 3.36 405.63 8.02 4/24/07 18:20 72.3 25.69 6. 173 4.012 3.35 403.13 8.01 4/24/07 18:25 73.4 25.60 6. 162 4.006 3.35 396.88 8.01 4/24/07 18:30 72.9 25.57 6. 152 3.998 3.34 393.75 8.01 4/24/07 18:35 73.3 25.46 6. 142 3.992 3.34 390.63 8.01 4/24/07 18:40 73.6 25.44 6. 132 3.986 3.33 386.88 8.01 4/24/07 18:45 74.1 25.43 6. 129 3.983 3.33 382.50 8.01 4/24/07 18:50 74.5 25.41 6. 136 3.988 3.33 380.00 8.01 4/24/07 18:55 74.9 25.37 6. 129 3.984 3.33 376.88 8.01 4/24/07 19:00 75.3 25.33 6. 12 3.978 3.32 374.38 8.01 4/24/07 19:05 75.7 25.24 6. 122 3.98 3.32 371.88 8.01 4/24/07 19:10 75.8 25.16 6. 118 3.977 3.32 368.75 8.01 4/24/07 19:15 75.9 25.10 6. 116 3.976 3.32 365.00 8.01 4/24/07 19:20 76.5 25.06 6. 114 3.974 3.32 361.25 8.02 4/24/07 19:25 76.9 25.01 6. 113 3.973 3.32 356.25 8.02 4/24/07 19:30 77.2 24.97 6. 107 3.97 3.32 355.00 8.02 4/24/07 19:35 77.6 24.95 6. 103 3.967 3.31 353.13 8.02 4/24/07 19:40 77.9 24.89 6. 1 3.965 3.31 351.88 8.02 4/24/07 19:45 78.3 24.87 6. 104 3.968 3.32 350.63 8.02 4/24/07 19:50 78.7 24.84 6. 103 3.967 3.32 350.00 8.02 4/24/07 19:55 79.1 24.80 6. 101 3.966 3.31 347.50 8.02 4/24/07 20:00 79.4 24.76 6. 101 3.966 3.31 346.25 8.02 4/24/07 20:05 79.7 24.72 6. 103 3.967 3.32 346.25 8.01 4/24/07 20:10 80.0 24.65 6. 108 3.97 3.32 345.00 8.01 4/24/07 20:15 80.3 24.67 6. 105 3.968 3.32 345.00 8.01 4/24/07 20:20 80.6 24.63 6. 104 3.968 3.32 390.63 8.01 4/24/07 20:25 81.1 24.62 6. 104 3.967 3.32 385.00 8.01 4/24/07 20:30 81.4 24.58 6. 102 3.967 3.32 381.25 8.00 4/24/07 20:35 81.8 24.60 6. 101 3.966 3.31 383.13 8.00 4/24/07 20:40 81.8 24.53 6. 098 3.963 3.31 374.38 7.99 4/24/07 20:45 82.3 24.65 6. 053 3.934 3.29 407.50 7.98 4/24/07 20:50 82.5 24.21 5. 35 3.477 2.88 400.63 7.89

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140 Table B1 continued Date and Time Water Elevation (cm) Temperature (C) SpCond (mS/cm) Total Dissolved Solids (g/L) Salinity (ppt) DO (M) pH 4/24/07 20:55 82.9 24.20 5. 333 3.466 2.87 438.13 7.85 4/24/07 21:00 83.1 24.17 5. 324 3.461 2.87 441.88 7.82 4/24/07 21:05 83.4 24.16 5. 327 3.462 2.87 441.88 7.80 4/24/07 21:10 83.5 24.16 5. 328 3.464 2.87 442.50 7.78 4/24/07 21:15 83.6 24.13 5. 327 3.462 2.87 447.50 7.77 4/24/07 21:20 83.8 24.13 5. 341 3.471 2.88 448.75 7.76 4/24/07 21:25 83.8 24.10 5. 338 3.469 2.88 453.75 7.75 4/24/07 21:30 83.9 24.08 5. 341 3.472 2.88 451.25 7.74 4/24/07 21:35 83.9 24.28 5. 508 3.58 2.97 442.50 7.70 4/24/07 21:40 83.9 24.29 5. 503 3.577 2.97 451.25 7.69 4/24/07 21:45 83.8 24.26 5. 497 3.573 2.97 457.50 7.68 4/24/07 21:50 83.8 24.22 5. 492 3.57 2.96 463.13 7.67 4/24/07 21:55 83.6 24.21 5. 489 3.568 2.96 467.50 7.66 4/24/07 22:00 83.5 24.18 5. 489 3.568 2.96 473.75 7.65 4/24/07 22:05 83.4 24.20 5. 488 3.567 2.96 477.50 7.65 4/24/07 22:10 83.2 24.20 5. 486 3.566 2.96 480.00 7.64 4/24/07 22:15 83.0 24.20 5. 487 3.566 2.96 439.38 7.64 4/24/07 22:20 82.8 24.20 5. 485 3.565 2.96 445.00 7.64 4/24/07 22:25 82.5 24.16 5. 485 3.565 2.96 450.00 7.63 4/24/07 22:30 82.2 24.15 5. 484 3.564 2.96 450.63 7.63 4/24/07 22:35 82.0 24.18 5. 483 3.564 2.96 453.75 7.63 4/24/07 22:40 81.7 24.17 5. 483 3.564 2.96 454.38 7.63 4/24/07 22:45 81.4 24.12 5. 482 3.564 2.96 455.00 7.62 4/24/07 22:50 81.1 24.02 5. 482 3.563 2.96 455.63 7.62 4/24/07 22:55 80.8 23.92 5. 482 3.563 2.96 456.25 7.62 4/24/07 23:00 80.4 23.82 5. 479 3.562 2.96 452.50 7.62 4/24/07 23:05 80.2 23.69 5. 479 3.561 2.96 451.88 7.61 4/24/07 23:10 79.8 23.59 5. 48 3.561 2.96 449.38 7.61 4/24/07 23:15 79.3 23.50 5. 478 3.56 2.96 449.38 7.61 4/24/07 23:20 79.0 23.45 5. 477 3.56 2.96 423.13 7.61 4/24/07 23:25 78.7 23.35 5. 477 3.559 2.96 420.63 7.61 4/24/07 23:30 78.5 23.27 5. 475 3.559 2.96 420.00 7.60 4/24/07 23:35 78.4 23.14 5. 471 3.557 2.96 421.25 7.60 4/24/07 23:40 78.0 23.07 5. 472 3.557 2.96 423.13 7.60 4/24/07 23:45 77.6 23.12 5. 471 3.556 2.96 425.00 7.60 4/24/07 23:50 77.1 23.09 5. 471 3.556 2.96 425.00 7.60 4/24/07 23:55 76.7 23.06 5. 47 3.555 2.96 425.63 7.60 4/25/07 0:00 76.3 23.03 5. 468 3.554 2.95 424.38 7.60 4/25/07 0:05 75.8 22.98 5. 467 3.554 2.95 429.38 7.60 4/25/07 0:10 75.3 22.93 5. 466 3.553 2.95 426.88 7.59 4/25/07 0:15 74.9 22.92 5. 465 3.552 2.95 425.00 7.59 4/25/07 0:20 74.5 22.89 5. 463 3.551 2.95 422.50 7.59 4/25/07 0:25 74.1 22.87 5. 463 3.551 2.95 420.63 7.59 4/25/07 0:30 73.6 22.84 5. 46 3.55 2.95 420.00 7.59 4/25/07 0:35 72.8 22.80 5. 461 3.55 2.95 418.13 7.58

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141 Table B1 continued Date and Time Water Elevation (cm) Temperature (C) SpCond (mS/cm) Total Dissolved Solids (g/L) Salinity (ppt) DO (M) pH 4/25/07 0:40 72.8 22.79 5. 46 3.549 2.95 417.50 7.58 4/25/07 0:45 72.3 22.78 5. 43 3.529 2.93 378.13 7.56 4/25/07 0:50 71.7 22.78 5. 429 3.529 2.93 332.50 7.41 4/25/07 0:55 71.4 22.79 5. 408 3.516 2.92 331.25 7.36 4/25/07 1:00 70.9 22.58 5. 383 3.499 2.91 243.13 7.31 4/25/07 1:05 70.4 22.62 5. 38 3.497 2.91 236.25 7.23 4/25/07 1:10 70.0 22.83 5. 405 3.513 2.92 380.63 7.27 4/25/07 1:15 69.5 22.62 5. 391 3.504 2.91 237.50 7.21 4/25/07 1:20 69.1 22.62 5. 395 3.507 2.91 236.88 7.19 4/25/07 1:25 68.9 22.64 5. 394 3.507 2.91 244.38 7.17 4/25/07 1:30 68.3 22.61 5. 41 3.516 2.92 248.13 7.17 4/25/07 1:35 68.0 22.64 5. 413 3.518 2.92 245.63 7.16 4/25/07 1:40 67.6 22.65 5. 42 3.523 2.93 246.25 7.15 4/25/07 1:45 67.1 22.66 5. 43 3.53 2.93 248.13 7.15 4/25/07 1:50 66.7 22.66 5. 422 3.524 2.93 246.88 7.15 4/25/07 1:55 66.4 22.67 5. 431 3.53 2.93 248.13 7.15 4/25/07 2:00 65.8 22.68 5. 431 3.53 2.93 246.88 7.15 4/25/07 2:05 65.4 22.70 5. 413 3.519 2.92 253.13 7.15 4/25/07 2:10 65.0 22.63 5. 408 3.515 2.92 265.63 7.16 4/25/07 2:15 64.6 22.64 5. 405 3.513 2.92 260.00 7.16 4/25/07 2:20 64.2 22.66 5. 404 3.513 2.92 257.50 7.16 4/25/07 2:25 63.8 22.66 5. 401 3.511 2.92 255.63 7.16 4/25/07 2:30 63.4 22.66 5. 399 3.51 2.92 252.50 7.16 4/25/07 2:35 63.0 22.65 5. 398 3.509 2.92 250.00 7.16 4/25/07 2:40 62.6 22.66 5. 394 3.507 2.91 248.13 7.15 4/25/07 2:45 62.2 22.65 5. 394 3.506 2.91 246.88 7.15 4/25/07 2:50 61.9 22.65 5. 391 3.504 2.91 244.38 7.15 4/25/07 2:55 61.7 22.65 5. 39 3.504 2.91 242.50 7.15 4/25/07 3:00 61.3 22.65 5. 387 3.502 2.91 240.63 7.15 4/25/07 3:05 61.0 22.63 5. 387 3.502 2.91 238.75 7.15 4/25/07 3:10 60.6 22.63 5. 385 3.499 2.91 236.25 7.15 4/25/07 3:15 60.2 22.63 5. 383 3.498 2.91 235.00 7.15 4/25/07 3:20 59.9 22.63 5. 38 3.497 2.91 233.13 7.15 4/25/07 3:25 59.6 22.62 5. 378 3.496 2.9 231.25 7.15 4/25/07 3:30 59.3 22.59 5. 376 3.495 2.9 230.00 7.14 4/25/07 3:35 59.1 22.61 5. 373 3.493 2.9 228.13 7.14 4/25/07 3:40 58.8 22.59 5. 372 3.492 2.9 226.88 7.14 4/25/07 3:45 58.6 22.58 5. 37 3.491 2.9 225.00 7.14 4/25/07 3:50 58.3 22.58 5. 368 3.489 2.9 223.75 7.14 4/25/07 3:55 58.1 22.57 5. 366 3.488 2.9 221.25 7.14 4/25/07 4:00 58.0 22.54 5. 364 3.486 2.9 220.63 7.14 4/25/07 4:05 57.8 22.52 5. 363 3.486 2.9 218.75 7.14 4/25/07 4:10 57.6 22.54 5. 36 3.484 2.89 217.50 7.14 4/25/07 4:15 57.4 22.55 5. 358 3.482 2.89 216.25 7.14 4/25/07 4:20 57.2 22.56 5. 356 3.481 2.89 215.00 7.14

PAGE 142

142 Table B1 continued Date and Time Water Elevation (cm) Temperature (C) SpCond (mS/cm) Total Dissolved Solids (g/L) Salinity (ppt) DO (M) pH 4/25/07 4:25 57.0 22.56 5. 352 3.479 2.89 213.13 7.14 4/25/07 4:30 56.8 22.56 5. 352 3.479 2.89 211.88 7.13 4/25/07 4:35 56.5 22.54 5. 35 3.478 2.89 210.00 7.13 4/25/07 4:40 56.3 22.54 5. 348 3.476 2.89 209.38 7.13 4/25/07 4:45 56.1 22.55 5. 345 3.474 2.89 207.50 7.13 4/25/07 4:50 55.9 22.53 5. 343 3.473 2.88 206.25 7.13 4/25/07 4:55 55.7 22.53 5. 341 3.472 2.88 204.38 7.13 4/25/07 5:00 55.5 22.54 5. 339 3.471 2.88 203.13 7.13 4/25/07 5:05 55.9 22.53 5. 338 3.47 2.88 201.88 7.13 4/25/07 5:10 56.2 22.55 5. 822 3.784 3.16 215.63 7.11 4/25/07 5:15 55.7 22.55 5. 826 3.786 3.16 214.38 7.11 4/25/07 5:20 55.6 22.55 5. 827 3.788 3.16 214.38 7.11 4/25/07 5:25 55.5 22.55 5. 854 3.805 3.18 214.38 7.10 4/25/07 5:30 55.4 22.54 5. 878 3.821 3.19 215.00 7.10 4/25/07 5:35 55.3 22.53 5. 896 3.832 3.2 213.75 7.10 4/25/07 5:40 55.1 22.53 5. 889 3.828 3.2 213.13 7.10 4/25/07 5:45 55.0 22.52 5. 9 3.835 3.21 211.88 7.10 4/25/07 5:50 54.9 22.53 5. 919 3.848 3.22 211.88 7.10 4/25/07 5:55 54.7 22.51 5. 942 3.861 3.23 210.00 7.10 4/25/07 6:00 54.7 22.49 5. 935 3.857 3.23 210.63 7.10 4/25/07 6:05 54.8 22.44 5. 831 3.791 3.17 203.75 7.10 4/25/07 6:10 54.6 22.43 5. 827 3.787 3.16 202.50 7.10 4/25/07 6:15 54.6 22.45 5. 823 3.785 3.16 200.63 7.10 4/25/07 6:20 54.4 22.43 5. 819 3.782 3.16 199.38 7.10 4/25/07 6:25 54.4 22.43 5. 817 3.78 3.16 197.50 7.09 4/25/07 6:30 54.3 22.41 5. 813 3.778 3.16 196.25 7.09 4/25/07 6:35 54.2 22.41 5. 808 3.776 3.15 194.38 7.09 4/25/07 6:40 54.1 22.38 5. 806 3.773 3.15 193.13 7.09 4/25/07 6:45 54.0 22.38 5. 802 3.772 3.15 191.25 7.09 4/25/07 6:50 53.9 22.38 5. 798 3.769 3.15 190.00 7.09 4/25/07 6:55 53.8 22.36 5. 794 3.766 3.15 188.13 7.09 4/25/07 7:00 53.8 22.38 5. 791 3.765 3.14 186.88 7.09 4/25/07 7:05 53.7 22.40 5. 787 3.762 3.14 185.63 7.09 4/25/07 7:10 53.7 22.38 5. 787 3.761 3.14 183.75 7.09 4/25/07 7:15 53.7 22.40 5. 782 3.758 3.14 182.50 7.09 4/25/07 7:20 53.7 22.40 5. 777 3.756 3.14 181.25 7.09 4/25/07 7:25 53.6 22.39 5. 776 3.754 3.13 180.63 7.09 4/25/07 7:30 53.6 22.40 5. 772 3.751 3.13 178.75 7.09 4/25/07 7:35 53.6 22.38 5. 77 3.75 3.13 178.13 7.09 4/25/07 7:40 53.7 22.38 5. 768 3.749 3.13 176.88 7.09 4/25/07 7:45 53.6 22.40 5. 763 3.746 3.13 175.63 7.09 4/25/07 7:50 53.8 22.39 5. 761 3.744 3.13 175.00 7.09 4/25/07 7:55 53.8 22.43 5. 757 3.742 3.12 174.38 7.09 4/25/07 8:00 53.7 22.43 5. 753 3.74 3.12 173.75 7.09 4/25/07 8:05 53.6 22.42 5. 751 3.738 3.12 173.13 7.09

PAGE 143

143 Table B1 continued Date and Time Water Elevation (cm) Temperature (C) SpCond (mS/cm) Total Dissolved Solids (g/L) Salinity (ppt) DO (M) pH 4/25/07 8:10 53.6 22.41 5. 747 3.736 3.12 173.13 7.09 4/25/07 8:15 53.5 22.44 5. 745 3.734 3.12 171.88 7.09 4/25/07 8:20 53.5 22.45 5. 742 3.732 3.11 171.25 7.09 4/25/07 8:25 53.4 22.48 5. 736 3.729 3.11 171.25 7.09 4/25/07 8:30 53.3 22.48 5. 735 3.728 3.11 170.63 7.09 4/25/07 8:35 53.2 22.50 5. 732 3.726 3.11 170.63 7.09 4/25/07 8:40 53.3 22.50 5. 73 3.724 3.11 170.00 7.09 4/25/07 8:45 53.2 22.52 5. 726 3.722 3.11 170.00 7.09 4/25/07 8:50 53.2 22.55 5. 724 3.72 3.1 169.38 7.09 4/25/07 8:55 53.0 22.58 5. 72 3.718 3.1 170.00 7.09 4/25/07 9:00 53.1 22.61 5. 719 3.717 3.1 170.00 7.09 4/25/07 9:05 53.0 22.67 5. 716 3.716 3.1 170.00 7.09 4/25/07 9:10 53.0 22.69 5. 712 3.713 3.1 170.00 7.09 4/25/07 9:15 53.6 22.71 6. 515 4.234 3.56 233.13 7.07 4/25/07 9:20 52.8 22.76 6. 599 4.29 3.61 280.00 7.13 4/25/07 9:25 52.8 22.77 6. 617 4.301 3.62 285.63 7.15 4/25/07 9:30 52.9 22.82 6. 601 4.29 3.61 295.63 7.17 4/25/07 9:35 53.0 22.85 6. 608 4.295 3.62 305.00 7.18 4/25/07 9:40 52.9 22.93 6. 61 4.297 3.62 315.63 7.20 4/25/07 9:45 52.9 22.98 6. 623 4.305 3.63 327.50 7.21 4/25/07 9:50 52.9 23.03 6. 621 4.304 3.62 340.00 7.23 4/25/07 9:55 53.0 23.08 6. 62 4.302 3.62 355.00 7.25 4/25/07 10:00 53.1 23.15 6. 615 4.3 3.62 372.50 7.27 4/25/07 10:05 53.2 23.36 6. 466 4.203 3.53 325.63 7.23 4/25/07 10:10 53.4 23.43 6. 46 4.199 3.53 330.00 7.22 4/25/07 10:15 53.4 23.49 6. 457 4.197 3.53 333.13 7.21 4/25/07 10:20 53.6 23.53 6. 453 4.195 3.52 336.25 7.21 4/25/07 10:25 53.8 23.55 6. 451 4.193 3.52 339.38 7.21 4/25/07 10:30 54.1 23.58 6. 448 4.191 3.52 342.50 7.21 4/25/07 10:35 54.3 23.63 6. 444 4.189 3.52 345.00 7.21 4/25/07 10:40 54.6 23.66 6. 44 4.186 3.52 348.13 7.21 4/25/07 10:45 54.8 23.73 6. 437 4.184 3.51 350.63 7.21 4/25/07 10:50 55.3 23.79 6. 434 4.182 3.51 355.00 7.21 4/25/07 10:55 55.7 23.83 6. 432 4.181 3.51 357.50 7.21 4/25/07 11:00 56.1 23.88 6. 43 4.179 3.51 360.63 7.21 4/25/07 11:05 56.8 23.96 6. 428 4.178 3.51 364.38 7.21 4/25/07 11:10 57.5 24.04 6. 425 4.176 3.51 367.50 7.21 4/25/07 11:15 58.2 24.05 6. 424 4.175 3.5 370.00 7.21 4/25/07 11:20 59.0 24.17 6. 421 4.174 3.5 374.38 7.21 4/25/07 11:25 60.1 24.20 6. 419 4.172 3.5 376.88 7.21 4/25/07 11:30 60.8 24.33 6. 416 4.17 3.5 383.75 7.22 4/25/07 11:35 61.7 24.39 6. 416 4.17 3.5 384.38 7.22 4/25/07 11:40 62.5 24.36 6. 412 4.168 3.5 383.75 7.22 4/25/07 11:45 63.4 24.37 6. 41 4.166 3.5 386.25 7.23 4/25/07 11:50 64.4 24.50 6. 409 4.166 3.49 390.00 7.22

PAGE 144

144 Table B1 continued Date and Time Water Elevation (cm) Temperature (C) SpCond (mS/cm) Total Dissolved Solids (g/L) Salinity (ppt) DO (M) pH 4/25/07 11:55 65.3 24.58 6. 407 4.164 3.49 391.88 7.23 4/25/07 12:00 66.3 24.61 6. 405 4.163 3.49 395.00 7.23 4/25/07 12:05 67.3 24.67 6. 402 4.162 3.49 398.75 7.23 4/25/07 12:10 68.2 24.63 6. 401 4.161 3.49 400.00 7.23 4/25/07 12:15 69.0 24.64 6. 4 4.16 3.49 402.50 7.24 4/25/07 12:20 70.0 24.70 6. 399 4.159 3.49 406.25 7.24 4/25/07 12:25 70.9 24.71 6. 396 4.158 3.49 408.13 7.25 4/25/07 12:30 71.7 24.73 6. 393 4.156 3.48 410.63 7.25 4/25/07 12:35 72.7 24.77 6. 393 4.155 3.48 413.13 7.25 4/25/07 12:40 73.5 24.79 6. 392 4.155 3.48 414.38 7.26 4/25/07 12:45 74.4 24.83 6. 391 4.154 3.48 417.50 7.26 4/25/07 12:50 75.2 24.87 6. 389 4.153 3.48 420.00 7.26 4/25/07 12:55 76.2 24.90 6. 384 4.15 3.48 422.50 7.27 4/25/07 13:00 77.0 24.88 6. 384 4.149 3.48 424.38 7.27 4/25/07 13:05 77.8 24.94 6. 38 4.147 3.48 427.50 7.28 4/25/07 13:10 78.7 24.80 5. 187 3.372 2.79 593.75 7.72 4/25/07 13:15 79.5 24.82 5. 173 3.362 2.78 565.63 7.83 4/25/07 13:20 80.3 24.94 5. 263 3.421 2.83 546.88 7.87 4/25/07 13:25 81.0 24.99 5. 468 3.554 2.95 537.50 7.90 4/25/07 13:30 81.9 25.06 5. 297 3.443 2.85 524.38 7.94 4/25/07 13:35 82.9 25.16 5. 203 3.382 2.8 510.00 7.96 4/25/07 13:40 83.4 25.23 5. 181 3.368 2.78 506.88 7.98 4/25/07 13:45 83.9 25.28 5. 249 3.412 2.82 497.50 7.99 4/25/07 13:50 84.6 25.19 5. 269 3.425 2.83 482.50 7.98 4/25/07 13:55 85.3 25.20 5. 198 3.379 2.79 475.63 7.98 4/25/07 14:00 85.7 25.24 5. 416 3.521 2.92 470.63 7.97 4/25/07 14:05 86.2 25.60 5. 375 3.494 2.89 457.50 7.92 4/25/07 14:10 86.4 25.64 5. 364 3.487 2.89 460.00 7.91 4/25/07 14:15 87.1 25.69 5. 356 3.482 2.88 460.63 7.91 4/25/07 14:20 87.4 25.75 5. 346 3.475 2.88 460.63 7.92 4/25/07 14:25 87.8 25.79 5. 337 3.469 2.87 459.38 7.92 4/25/07 14:30 88.0 25.81 5. 327 3.462 2.86 458.75 7.92 4/25/07 14:35 88.4 25.86 5. 331 3.465 2.87 456.88 7.93 4/25/07 14:40 88.4 25.91 5. 317 3.456 2.86 455.63 7.94 4/25/07 14:45 88.6 25.96 5. 311 3.452 2.85 453.75 7.94 4/25/07 14:50 88.5 26.01 5. 308 3.45 2.85 453.13 7.94 4/25/07 14:55 88.6 26.04 5. 295 3.441 2.84 451.25 7.95 4/25/07 15:00 88.5 26.08 5. 286 3.435 2.84 449.38 7.95 4/25/07 15:05 88.6 26.13 5. 281 3.433 2.84 448.13 7.95 4/25/07 15:10 88.5 26.15 5. 269 3.425 2.83 447.50 7.96 4/25/07 15:15 88.4 26.24 5. 259 3.419 2.82 447.50 7.96 4/25/07 15:20 88.4 26.22 5. 249 3.412 2.82 445.00 7.96 4/25/07 15:25 88.1 26.24 5. 279 3.431 2.83 445.00 7.97 4/25/07 15:30 88.0 26.27 5. 306 3.449 2.85 446.25 7.97 4/25/07 15:35 87.9 26.20 5. 36 3.484 2.88 463.13 7.99

PAGE 145

145 Table B1 continued Date and Time Water Elevation (cm) Temperature (C) SpCond (mS/cm) Total Dissolved Solids (g/L) Salinity (ppt) DO (M) pH 4/25/07 15:40 87.5 26.17 5. 389 3.502 2.9 444.38 8.01 4/25/07 15:45 87.3 26.17 5. 413 3.519 2.91 443.75 8.02 4/25/07 15:50 87.1 26.17 5. 409 3.516 2.91 442.50 8.03 4/25/07 15:55 86.8 26.17 5. 407 3.515 2.91 494.38 8.04 4/25/07 16:00 86.5 26.14 5. 398 3.509 2.9 439.38 8.05 4/25/07 16:05 86.2 26.18 5. 396 3.508 2.9 438.13 8.06 4/25/07 16:10 85.8 26.16 5. 394 3.506 2.9 436.25 8.07 4/25/07 16:15 85.4 26.16 5. 387 3.501 2.9 431.25 8.08 4/25/07 16:20 85.0 26.18 5. 381 3.498 2.89 446.88 8.08 4/25/07 16:25 84.7 26.15 5. 42 3.523 2.92 471.88 8.09 4/25/07 16:30 84.2 26.14 5. 441 3.537 2.93 468.75 8.10 4/25/07 16:35 84.0 26.12 5. 428 3.528 2.92 461.25 8.11 4/25/07 16:40 83.7 26.12 5. 43 3.529 2.92 452.50 8.11 4/25/07 16:45 83.4 26.10 5. 435 3.533 2.92 443.75 8.12 4/25/07 16:50 83.1 26.05 5. 429 3.529 2.92 436.88 8.12 4/25/07 16:55 82.7 26.01 5. 419 3.523 2.92 430.00 8.12 4/25/07 17:00 82.3 25.97 5. 429 3.529 2.92 423.75 8.13 4/25/07 17:05 81.8 25.99 5. 419 3.522 2.92 443.13 8.13 4/25/07 17:10 81.4 26.01 5. 397 3.508 2.9 440.63 8.13 4/25/07 17:15 81.1 26.00 5. 378 3.496 2.89 438.13 8.14 4/25/07 17:20 80.7 26.00 5. 385 3.5 2.9 516.25 8.12 4/25/07 17:25 80.2 26.01 5. 364 3.487 2.88 461.88 8.14 4/25/07 17:30 80.3 25.99 5. 347 3.476 2.87 351.88 8.15 4/25/07 17:35 79.5 25.94 5. 332 3.466 2.87 356.25 8.15 4/25/07 17:40 79.1 25.91 5. 324 3.461 2.86 356.88 8.15 4/25/07 17:45 78.8 25.86 5. 304 3.447 2.85 356.88 8.16 4/25/07 17:50 78.4 25.81 5. 288 3.437 2.84 356.88 8.16

PAGE 146

146 Table B2.Five minute database of solar irradi ance, redox probes at 2cm depth, and datalogger panel temperature Date and Time Panel Temperature (C) Surface Solar Irradiance (S/cm2/s) Subsurface Solar Irradiance (S/cm2/s) Redox Probe 1 (mv) Redox Probe 2 (mv) Redox Probe 3 (mv) Redox Probe 4 (mv) 4/24/07 17:30 33.92 929 682.2 217.4 -140 190.1 -160.4 4/24/07 17:35 33.08 929 539.3 228.2 -137.8 199.7 -158.9 4/24/07 17:40 32.55 908 526.5 163.2 -141.5 116.6 -159.2 4/24/07 17:45 32.74 760 549.6 48.36 -139.7 57.95 -158.8 4/24/07 17:50 32.64 760 598.2 -4 .33 -138.6 23.62 -156.6 4/24/07 17:55 32.79 760 548.2 37.91 -140 -2.189 -154.5 4/24/07 18:00 32.68 755.7 509.2 145.8 -136.6 96.9 -154.5 4/24/07 18:05 32.1 616.2 482.9 28.83 -138.6 7.012 -154.1 4/24/07 18:10 31.19 591.1 423. 1 107 -138.8 25.42 -154.3 4/24/07 18:15 30.32 591.2 404.3 193.8 -139.4 174.7 -154.2 4/24/07 18:20 29.73 591.3 392.5 202.3 -134.4 219.1 -152.6 4/24/07 18:25 29.54 484.2 374. 1 211.1 -131.4 212 -150.5 4/24/07 18:30 29.41 422.4 347. 2 211.7 -131.1 220.1 -148 4/24/07 18:35 29.16 422.4 302.7 209.9 -134.9 218.8 -145.9 4/24/07 18:40 28.76 422.4 268. 6 217 -134.6 210.9 -143.8 4/24/07 18:45 28.4 410.1 248.9 220.6 -137.1 208.8 -143.8 4/24/07 18:50 28.05 274.7 242 226.6 -138.1 198.4 -143 4/24/07 18:55 27.76 253.4 238. 4 226 -138.1 212.6 -140.8 4/24/07 19:00 27.44 253.4 196.9 221.7 -138.2 215.8 -137.9 4/24/07 19:05 27.13 247.2 104.1 228.1 -135.8 212.6 -128.5 4/24/07 19:10 26.81 84.5 80. 3 231.4 -137.1 212.3 196.8 4/24/07 19:15 26.28 84.5 80. 3 233.5 -136.4 208.5 235.1 4/24/07 19:20 25.87 84.5 80. 3 244.1 -132.1 206.9 232.6 4/24/07 19:25 25.47 84.5 80. 3 244.9 -134.7 204.9 239.5 4/24/07 19:30 25.1 84.5 80. 3 246.2 -139.5 209.1 165.6 4/24/07 19:35 24.75 84.5 80. 3 244.1 -141.1 210.5 62.78 4/24/07 19:40 24.41 84.5 80. 3 242.6 -141.1 216.7 187.8 4/24/07 19:45 24.11 84.5 80. 3 242.8 -142.9 204.1 272.1 4/24/07 19:50 23.82 84.5 80. 3 241.2 -142.9 200.9 272 4/24/07 19:55 23.53 84.5 79. 8 240 -143.3 204.6 280.4 4/24/07 20:00 23.24 82.8 76. 18 238.1 -143.7 206.9 272.4 4/24/07 20:05 22.97 67.74 52. 62 237.3 -142.5 201.8 264.4 4/24/07 20:10 22.67 37.89 30. 79 237.4 -143.2 205.3 318.2 4/24/07 20:15 22.32 6.479 9. 77 236.6 -142.2 202.7 275.4 4/24/07 20:20 22.06 6.479 2. 276 234.8 -143.7 202.1 300.4 4/24/07 20:25 21.83 -2.958 4.419 232.6 -144.2 201.7 258 4/24/07 20:30 21.61 -10.71 2. 143 231.9 -143.8 202.8 309.7 4/24/07 20:35 21.33 -7.748 -1 .339 234.5 -144.6 201.6 328.7 4/24/07 20:40 21.15 -1.268 0.67 232.5 -140.2 207 223.4 4/24/07 20:45 20.91 -4.367 3. 482 95.2 -150.3 104.7 -71.03 4/24/07 20:50 20.67 -5.354 0. 536 0.964 -146.9 44.34 -116.2 4/24/07 20:55 20.46 -9.02 6. 831 -29.86 -143.9 29.8 46.31

PAGE 147

147 Table B2 continued Date and Time Panel Temperature (C) Surface Solar Irradiance (S/cm2/s) Subsurface Solar Irradiance (S/cm2/s) Redox Probe 1 (mv) Redox Probe 2 (mv) Redox Probe 3 (mv) Redox Probe 4 (mv) 4/24/07 21:00 20.34 -8.88 0. 804 -48 -144.1 20.42 -132.8 4/24/07 21:05 20.12 -12.4 9.38 -60.68 -145.1 11.46 -131.6 4/24/07 21:10 19.85 -18.17 19.42 -69.71 -144.5 2.596 -124.1 4/24/07 21:15 19.6 -20.57 23.04 -77.2 -145.3 -3.784 -112.7 4/24/07 21:20 19.43 -15.07 14.2 -82.7 -145.7 -10.74 -5.717 4/24/07 21:25 19.28 -12.82 14.73 -87.9 -145.4 -20.58 140.5 4/24/07 21:30 19.26 -15.64 18.89 -91.1 -145.3 -36.35 109.8 4/24/07 21:35 19.3 -17.33 22.77 -94.3 -146 -37.81 -58.86 4/24/07 21:40 19.2 -12.82 25.32 -33.07 -147.7 -32.99 -80.8 4/24/07 21:45 19.05 -22.55 47. 42 103.7 -144.8 -33.4 36.46 4/24/07 21:50 18.87 -33.54 51.44 163.8 -142.8 -33.76 -29.5 4/24/07 21:55 18.71 -26.07 35. 64 216.4 -142.9 -34.22 122.9 4/24/07 22:00 18.59 -43.97 52. 92 234.9 -143.4 -10.14 7.524 4/24/07 22:05 18.43 -49.04 61. 63 227.3 -145.5 53.14 0.22 4/24/07 22:10 18.32 -52.57 67. 93 222.3 -145.6 35.96 234.7 4/24/07 22:15 18.18 -47.64 64. 31 215.9 -144.6 44.64 137.9 4/24/07 22:20 18.06 -61.17 72. 08 215 -142.9 40.53 -35.03 4/24/07 22:25 17.99 -64.97 67.79 208 -145.5 35.37 108.9 4/24/07 22:30 17.87 -56.51 70.07 204.4 -146.4 37.37 141 4/24/07 22:35 17.78 -33.82 53.59 206 -145.9 58.59 249.5 4/24/07 22:40 17.76 -56.51 67. 12 196.6 -144.1 60.88 139.6 4/24/07 22:45 17.69 -149.5 56. 94 193.8 -145.2 41.14 111.8 4/24/07 22:50 17.62 -123.5 62.03 168.3 -145 31.88 224 4/24/07 22:55 17.55 -52.43 69.13 167.9 -141.3 33.22 252 4/24/07 23:00 17.47 -54.54 71. 68 164.6 -141.7 22.56 264.7 4/24/07 23:05 17.4 -52.57 67. 93 165.7 -140.4 15.88 243.3 4/24/07 23:10 17.37 -119.2 69. 53 159.9 -140.7 23.34 22.57 4/24/07 23:15 17.32 -182.5 74.09 148.6 -142 28.32 191.1 4/24/07 23:20 17.24 -85.7 75. 16 142.3 -141.2 25.65 186.2 4/24/07 23:25 17.18 -84.4 72.62 131.5 -140 19.17 6.012 4/24/07 23:30 17.14 -83 66.18 163.3 -140.3 20.87 -32.08 4/24/07 23:35 17.19 -84.3 71. 01 188.6 -149.8 24.59 -6.055 4/24/07 23:40 17.32 -76.95 78. 38 166.4 -149.5 42.29 -20.13 4/24/07 23:45 17.41 -73.29 78. 11 161.7 -148.1 35.71 -26.79 4/24/07 23:50 17.39 -64.55 76. 23 163.3 -150.1 34.46 -4.093 4/24/07 23:55 17.36 -67.23 75. 56 160.9 -149.3 35.38 -8.41 4/25/07 0:00 17.33 -53.41 69. 53 151.8 -152.4 46.91 27.96 4/25/07 0:05 17.27 -4.651 69 154 -152.6 43.47 -5.74 4/25/07 0:10 17.19 7.47 72. 88 152.7 -155.1 57.93 175.3 4/25/07 0:15 17.07 4.228 77. 44 156.1 -156.5 65.35 228.9 4/25/07 0:20 16.96 -27.62 79. 72 143.7 -155.3 62.65 106.4 4/25/07 0:25 16.88 -33.4 79. 58 146.6 -155.4 70.72 30.99 4/25/07 0:30 16.81 -35.8 79. 05 152.7 -153.7 62.32 -26.81 4/25/07 0:35 16.77 -35.37 76. 63 156.5 -140.9 57.33 -23.14 4/25/07 0:40 16.68 -23.54 75. 83 152.1 -136.8 56.39 -21.54

PAGE 148

148 Table B2 continued Date and Time Panel Temperature (C) Surface Solar Irradiance (S/cm2/s) Subsurface Solar Irradiance (S/cm2/s) Redox Probe 1 (mv) Redox Probe 2 (mv) Redox Probe 3 (mv) Redox Probe 4 (mv) 4/25/07 0:45 16.62 -8.17 74. 49 150.3 -131.5 48.72 -8.44 4/25/07 0:50 16.7 4.933 55.47 170.9 -106.9 140.3 -17.33 4/25/07 0:55 16.8 0.141 49.84 31.1 -140.7 3.354 -119.5 4/25/07 1:00 16.77 -1.128 62. 57 47.33 -138.5 79.93 -100.8 4/25/07 1:05 16.64 -7.752 47. 43 177.8 -91.4 233.7 -57.59 4/25/07 1:10 16.62 -16.21 53. 73 180.2 -82.9 261.5 -44.2 4/25/07 1:15 16.68 -23.68 44. 89 178.8 -97.9 280 -56.13 4/25/07 1:20 16.79 -16.07 45. 56 174.1 -96.7 288.6 -61.85 4/25/07 1:25 16.95 -32.98 49. 44 175.1 -106.9 304.3 -52.91 4/25/07 1:30 17.09 -35.66 23. 58 20.49 -163 25.94 -145.8 4/25/07 1:35 17.19 -43.13 51.18 -43.84 -167.6 -63.01 -167.5 4/25/07 1:40 17.28 -39.89 64.04 -66.21 -168.1 -71.62 -168 4/25/07 1:45 17.28 -57.5 63.1 -80.1 -168.5 -81.7 -169 4/25/07 1:50 17.25 9.87 78.11 -88.5 -167.8 -85 -168.6 4/25/07 1:55 17.33 12.26 78.24 -95 -167.7 -90.2 -168.8 4/25/07 2:00 17.43 10.71 76.9 -100.3 -167.5 -92.6 -169 4/25/07 2:05 17.53 14.52 77.84 104.3 -167.3 -121.5 -170.3 4/25/07 2:10 17.61 -5.778 71.68 -108.7 -167.3 -126.6 -171.7 4/25/07 2:15 17.71 -11.56 73.42 -108.6 -166.6 -117.3 -172 4/25/07 2:20 17.78 -29.74 72. 75 -113.3 -166.7 -114 -172 4/25/07 2:25 17.83 -9.3 78.91 -115.8 -166.3 -112.7 -171.8 4/25/07 2:30 17.88 -12.12 78.11 -119 -166.6 -119.6 -171.7 4/25/07 2:35 17.91 -12.4 73.42 -121.2 -166.8 -114.6 -171.9 4/25/07 2:40 17.89 -8.74 68.33 -122.9 -165.8 -113.8 -171.8 4/25/07 2:45 17.89 -8.03 76.5 -124.8 -165.2 -113.5 -171.5 4/25/07 2:50 17.9 -10.01 74.62 -126.2 -164.8 -114.2 -171.2 4/25/07 2:55 17.91 -12.12 73.02 -127.6 -164.2 -114.4 -171 4/25/07 3:00 17.88 -13.53 78.51 -123.2 -163.8 -114.2 -170.7 4/25/07 3:05 17.83 -19.31 77.71 -129 -163.9 -113.4 -170.8 4/25/07 3:10 17.72 -21.99 78.11 -125.3 -163.7 -114 -170.9 4/25/07 3:15 17.6 -14.8 75.03 -119.8 -164.2 -114.4 -171 4/25/07 3:20 17.5 -21.7 75.29 -129.1 -164.3 -115.5 -170.9 4/25/07 3:25 17.42 -20.29 77.04 -132.8 -164.3 -116.5 -171.1 4/25/07 3:30 17.34 -25.65 77.44 -100.7 -164.2 -116.9 -171.1 4/25/07 3:35 17.26 -26.35 70.61 -102.5 -164.7 -117.7 -171.2 4/25/07 3:40 17.22 -26.35 71.95 -121.1 -164.9 -116.5 -171.3 4/25/07 3:45 17.15 -30.44 74.22 -128.2 -164.9 -117.4 -171.5 4/25/07 3:50 17.05 -37.91 72.48 -132 -164.9 -117.1 -171.8 4/25/07 3:55 16.97 -43.13 63.5 -109.5 -164.8 -116.9 -172.3 4/25/07 4:00 16.9 -25.37 54.53 -124.1 -165.1 -116.1 -172.7 4/25/07 4:05 16.81 -22.55 60.29 -126.4 -165.5 -116 -173.6 4/25/07 4:10 16.74 -45.38 60.43 -126.7 -165.9 -115.2 -174.8 4/25/07 4:15 16.7 -40.59 55.61 -127.4 -166.3 -114.7 -176.3 4/25/07 4:20 16.68 -43.55 53.86 -126.6 -167.1 -114.8 -177.9 4/25/07 4:25 16.66 -59.62 55. 61 -125 -167.2 -115.5 -179

PAGE 149

149 Table B2 continued Date and Time Panel Temperature (C) Surface Solar Irradiance (S/cm2/s) Subsurface Solar Irradiance S/cm2/s) Redox Probe 1 (mv) Redox Probe 2 (mv) Redox Probe 3 (mv) Redox Probe 4 (mv) 4/25/07 4:30 16.69 -59.06 54. 94 -111 -167.7 -116.5 -180 4/25/07 4:35 16.71 -55.25 51.45 -114.1 -168.3 -117.1 -180.2 4/25/07 4:40 16.71 -54.97 51.32 -122.7 -168.8 -117.4 -180.4 4/25/07 4:45 16.71 -49.33 55.47 -104.1 -169.3 -120.2 -180.7 4/25/07 4:50 16.72 -55.96 56.41 -102.5 -169.7 -120 -180.7 4/25/07 4:55 16.72 -61.03 60.43 -101.2 -169.7 -119.3 -180.9 4/25/07 5:00 16.72 -57.65 59. 63 -105 -169.8 -120 -181.2 4/25/07 5:05 16.72 -53.56 57.08 -101.1 -170.3 -121.8 -181.5 4/25/07 5:10 16.76 -28.75 73.56 -113.1 -169.3 -120.3 -179.6 4/25/07 5:15 16.8 -14.38 78.25 -127 -167.7 -122.6 -169.5 4/25/07 5:20 16.81 -13.53 73.83 -133.6 -167 -125.4 -166.3 4/25/07 5:25 16.8 -7.47 59.09 -131.2 -167.2 -125.7 -167.5 4/25/07 5:30 16.78 -16.63 60.43 -135.6 -167.2 -127.8 -170.1 4/25/07 5:35 16.78 -18.32 58.28 -137.2 -166.9 -130.4 -173 4/25/07 5:40 16.78 -12.54 56.14 -134.6 -166.7 -126.1 -174 4/25/07 5:45 16.77 -9.58 59.09 -137.6 -166.1 -123.3 -175.1 4/25/07 5:50 16.76 -15.65 61.24 -140.7 -166.1 -124.5 -176.7 4/25/07 5:55 16.76 -14.52 62. 04 -138 -166 -122.8 -177.3 4/25/07 6:00 16.76 -21.28 64.85 -138.5 -165.7 -123.3 -177.6 4/25/07 6:05 16.8 -25.65 62.71 -137.1 -164.3 -128.1 -174.6 4/25/07 6:10 16.86 -43.41 73.02 -142.9 -164.1 -130.8 -168.4 4/25/07 6:15 16.86 -39.18 74.36 -124.8 -164.3 -126.2 -165.1 4/25/07 6:20 16.94 -49.75 76.77 -131.8 -165.4 -123.9 -163.9 4/25/07 6:25 16.97 -55.81 78.51 -136 -165.9 -122.5 -163.7 4/25/07 6:30 17 -59.48 79.05 129.7 -166.2 -122.6 -164.7 4/25/07 6:35 17.06 -61.31 79. 85 -133.2 -166.9 -122 -165 4/25/07 6:40 17.19 -65.39 80.3 -146.8 -167.8 -122.8 -166 4/25/07 6:45 17.3 -33.97 79.18 -146.5 -168.6 -122.7 -167.2 4/25/07 6:50 17.37 -20.58 80.4 -148.6 -169 -122.3 -168.4 4/25/07 6:55 17.4 24.1 80.4 147.8 -168.3 -120.8 -168.1 4/25/07 7:00 17.44 74.55 80.4 -146.8 -167 -119.9 -166.9 4/25/07 7:05 17.5 75.96 80.4 -151.3 -169 -120.6 -169.4 4/25/07 7:10 17.58 84.6 80.4 -130 -170.4 -121.1 -171.6 4/25/07 7:15 17.66 84.6 80.4 132.5 -170.6 -122.1 -172.4 4/25/07 7:20 17.76 84.6 80.4 142.8 -170.4 -121.2 -172.8 4/25/07 7:25 17.85 84.6 80.4 -141.7 -170.4 -120.7 -173 4/25/07 7:30 17.91 84.6 80.4 143.8 -170.1 -120.8 -173.5 4/25/07 7:35 18.01 84.6 80.4 141.1 -169.3 -120.7 -172.9 4/25/07 7:40 18.13 84.6 80.4 131.1 -169.2 -120.8 -172.7 4/25/07 7:45 18.23 84.6 80.4 -118.1 -168 -120.7 -172.3 4/25/07 7:50 18.37 84.6 80.4 127.1 -167.7 -121.1 -172.6 4/25/07 7:55 18.52 84.6 80.4 119.5 -167.4 -121.2 -172.6 4/25/07 8:00 18.67 84.6 80.4 115.3 -165.4 -119.5 -170.6 4/25/07 8:05 18.89 84.6 80.4 -122.2 -165.1 -118.9 -170 4/25/07 8:10 19.12 84.6 80.4 119.7 -162.9 -118.8 -168.3

PAGE 150

150 Table B2 continued Date and Time Panel Temperature (C) Surface Solar Irradiance (S/cm2/s) Subsurface Solar Irradiance S/cm2/s) Redox Probe 1 (mv) Redox Probe 2 (mv) Redox Probe 3 (mv) Redox Probe 4 (mv) 4/25/07 8:15 19.34 84.6 80.4 135.7 -162.6 -120.4 -168.5 4/25/07 8:20 19.57 84.6 80.4 132.5 -162.2 -120.2 -167.7 4/25/07 8:25 19.81 84.6 80.4 136.2 -160.9 -119.5 -167.2 4/25/07 8:30 20.05 86 80.4 141.8 -158.7 -119.5 -166.1 4/25/07 8:35 20.41 86.8 80.1 -136.4 -157 -120.4 -165.4 4/25/07 8:40 20.74 84.5 79.96 133.5 -156.2 -120.4 -165.3 4/25/07 8:45 20.92 84.5 76.21 131.9 -155.7 -120.8 -165.6 4/25/07 8:50 21.18 84.5 72.06 141.2 -155.2 -121.2 -165.1 4/25/07 8:55 21.55 194.8 65.63 -115 -153.2 -123 -164 4/25/07 9:00 22.42 477.9 50.09 106.7 -154.1 -124.2 -163.2 4/25/07 9:05 24.6 588.1 39.24 121.3 -154.1 -122.6 -163.2 4/25/07 9:10 28.16 496.3 18.88 139.9 -154.3 -121.6 -163.6 4/25/07 9:15 30.15 636.3 15.53 121.8 -153.7 -121.4 -163.4 4/25/07 9:20 31.69 929 393.8 133 -155.3 -126.6 -165.5 4/25/07 9:25 34 933 641.1 -144. 9 -156.2 -128.8 -164.9 4/25/07 9:30 34.72 1008 678.7 149.7 -156.3 -129.7 -164.2 4/25/07 9:35 35.68 1013 722.8 153.5 -156.5 -128.7 -163.6 4/25/07 9:40 37.23 1089 784.9 156.4 -156.7 -126.5 -163.1 4/25/07 9:45 39.65 1173 833 -156.6 -156.4 -124 -162.2 4/25/07 9:50 41.79 1182 889 -155. 7 -155.9 -122.1 -161.1 4/25/07 9:55 42.01 1157 824 -155. 3 -155.3 -121.4 -159.7 4/25/07 10:00 41.55 1170 862 -156. 6 -154.2 -121.9 -157.6 4/25/07 10:05 41.8 1293 907 -158. 6 -153.1 -135.1 -154.9 4/25/07 10:10 41.64 1181 884 -162. 1 -151.9 -132.1 -152.9 4/25/07 10:15 42.19 1244 918 -164. 2 -150.2 -133.8 -150.2 4/25/07 10:20 41.33 1013 766.3 166 -149.4 -133.5 -147.5 4/25/07 10:25 39.85 931 655 -166.9 -148.8 -133.6 -145 4/25/07 10:30 38.42 815 589.3 168.5 -147 -129.7 -142.7 4/25/07 10:35 37.58 959 702.7 169.8 -146.5 -127.4 -141 4/25/07 10:40 38.28 853 658.2 170.5 -146.4 -126 -139.9 4/25/07 10:45 37.78 1100 844 -171. 1 -146.2 -125.4 -138.1 4/25/07 10:50 38.71 1185 899 -172. 8 -147.1 -125.2 -137.9 4/25/07 10:55 39.47 1147 883 -173. 6 -146.8 -125.1 -137.3 4/25/07 11:00 39.97 1025 774.2 173.7 -146.5 -124.4 -135.4 4/25/07 11:05 41.22 1360 1003 -173. 4 -146.6 -124.5 -134.6 4/25/07 11:10 42.83 1513 1112 -173. 9 -147.5 -124.5 -134.4 4/25/07 11:15 42.39 922 661.8 173.3 -148.1 -123.8 -135.3 4/25/07 11:20 41.03 1516 1108 -173 -148.1 -123.3 -137.3 4/25/07 11:25 42.79 1404 1019 -173. 6 -147.7 -123.6 -139.6 4/25/07 11:30 42.17 1485 1059 -173. 4 -146.6 -123.5 -141.3 4/25/07 11:35 42.9 1193 842 -174. 2 -145.4 -123.7 -143.1 4/25/07 11:40 41.25 917 660 -175 -144.4 -123.6 -143.5 4/25/07 11:45 38.5 569.1 373.2 173.6 -142.2 -121.8 -141.2 4/25/07 11:50 36.18 1425 1014 -172. 5 -136.4 -120.4 -139.2 4/25/07 11:55 36.53 1765 1260 -174.7 -136 -121.9 -143

PAGE 151

151 Table B2 continued Date and Time Panel Temperature (C) Surface Solar Irradiance (S/cm2/s) Subsurface Solar Irradiance (S/cm2/s) Redox Probe 1 (mv) Redox Probe 2 (mv) Redox Probe 3 (mv) Redox Probe 4 (mv) 4/25/07 12:00 37.21 1133 805 -175. 8 -136.5 -123.7 -143.7 4/25/07 12:05 36.28 1336 985 -175. 5 -136.3 -122.4 -138.7 4/25/07 12:10 36.3 1431 1048 -173. 7 -136.2 -120.1 -138.5 4/25/07 12:15 36.46 1213 903 -172. 6 -134.3 -118.2 -136.5 4/25/07 12:20 35.51 1078 747.6 172.1 -133 -117.8 -134.3 4/25/07 12:25 36.43 1606 1103 -172. 2 -131.7 -117.9 -133.4 4/25/07 12:30 36.47 1096 821 -171.8 -130 -117.9 -127.2 4/25/07 12:35 35.14 775.8 517.1 170.5 -128.2 -117.9 -123.7 4/25/07 12:40 35.53 1112 768.5 168.5 -126.2 -117.6 -122 4/25/07 12:45 35.27 1222 864 -172. 8 -123.1 -118.9 -120.4 4/25/07 12:50 37.5 1571 1116 -176 -122.7 -120.6 -119.5 4/25/07 12:55 38.4 1468 1098 -176.9 -124 -121 -118.6 4/25/07 13:00 35.9 628.4 447.9 -173.2 -121 -118.8 -114.9 4/25/07 13:05 34.62 1473 1024 -168. 3 -118.2 -117.1 -112.1 4/25/07 13:10 35.8 1553 1040 -170. 6 -119.7 -120.8 -109.5 4/25/07 13:15 35.28 1082 732.3 170.7 -117.5 -124.6 -106.8 4/25/07 13:20 35.63 1918 1378 -170. 5 -114.8 -123.2 -104.9 4/25/07 13:25 38.83 2038 1550 -179. 4 -115.4 -124.4 -106.7 4/25/07 13:30 39.88 2020 1441 -178. 3 -115.2 -123.3 -104.5 4/25/07 13:35 40.27 2065 1472 -178.1 -115 -122.4 -104.3 4/25/07 13:40 40.83 2088 1451 -178.2 -116 -126.9 -103.1 4/25/07 13:45 40.84 2036 1527 -178.8 -115.7 -124 -102.8 4/25/07 13:50 40.39 1532 1102 -179. 2 -113.8 -122.2 -100.5 4/25/07 13:55 40.01 1906 1282 -178. 9 -112.2 -122.5 -96.9 4/25/07 14:00 40.01 1985 1359 -179 -111.1 -123.9 -94.7 4/25/07 14:05 40.07 1988 1211 -180. 5 -111.3 -128.4 -96.4 4/25/07 14:10 40.61 1895 1340 -181. 6 -111.6 -127.4 -95.3 4/25/07 14:15 40.16 1818 1249 -183 -115 -126.5 -99.4 4/25/07 14:20 38.74 1804 1272 -181. 7 -116.4 -124.8 -103.1 4/25/07 14:25 38.78 1876 1324 -183. 1 -119.4 -125.4 -105.8 4/25/07 14:30 38.02 1808 1260 -183. 1 -118.7 -125.1 -107.6 4/25/07 14:35 37.26 1857 1282 -183. 4 -119.2 -124.8 -108.2 4/25/07 14:40 36.89 1857 1313 -183. 6 -118.9 -124.1 -111.8 4/25/07 14:45 36.52 1857 1307 -183.6 -118.7 -124 -114.2 4/25/07 14:50 36.97 1858 1352 -184.9 -120 -124.9 -118.2 4/25/07 14:55 37.36 1844 1066 -184. 5 -121.2 -125.7 -119.2 4/25/07 15:00 38.06 1857 503.5 185.3 -122 -126.6 -123.6 4/25/07 15:05 38.62 1845 1247 -184. 8 -119.9 -126.8 -124.8 4/25/07 15:10 38.93 1745 1256 -185. 8 -123.8 -127.5 -129.7 4/25/07 15:15 39.04 1803 1294 -184. 9 -122.2 -127.2 -128.3 4/25/07 15:20 39.4 1770 1290 -185. 4 -121.2 -127.7 -130.5 4/25/07 15:25 37.72 1348 986 -184 -122.5 -125 -122.3 4/25/07 15:30 37.51 1688 1233 -185. 8 -119.9 -124.3 -134.1 4/25/07 15:35 37.89 1601 1183 -186.3 -113 -124.9 -116.4 4/25/07 15:40 37.62 1470 1089 -185. 2 -66.17 -124.4 -30.99

PAGE 152

152 Table B2 continued Date and Time Panel Temperature (C) Surface Solar Irradiance (S/cm2/s) Subsurface Solar Irradiance (S/cm2/s) Redox Probe 1 (mv) Redox Probe 2 (mv) Redox Probe 3 (mv) Redox Probe 4 (mv) 4/25/07 15:45 37.5 1520 1104 -183.4 -67.88 -122 -34.39 4/25/07 15:50 38 1520 1128 -184.5 -68.66 -122.2 -37.05 4/25/07 15:55 37.33 1520 1106 -183. 9 -67.41 -121.9 -37.68 4/25/07 16:00 37.09 1520 1073 -179. 7 -65.34 -121.1 -36.44 4/25/07 16:05 37.5 1431 1064 -183. 7 -67.91 -123.2 -38.96 4/25/07 16:10 38.08 1351 1036 -184. 4 -66.25 -124.2 -40.93 4/25/07 16:15 37.7 1351 1018 -182. 8 -61.34 -122.7 -39.31 4/25/07 16:20 37.18 1350 987 -183. 3 -58.04 -122.3 -39.54 4/25/07 16:25 37.05 1218 928 -178. 6 -59.04 -121.7 -40.44 4/25/07 16:30 36.42 1161 822 -181. 7 -57.5 -124.9 -44.86 4/25/07 16:35 36.03 1021 794.8 173.5 -62.81 -127 -45.23 4/25/07 16:40 35.68 1133 817 -168. 5 -61.13 -123.1 -41.64 4/25/07 16:45 35.17 1000 730.2 165.6 -59.98 -121.8 -39.96 4/25/07 16:50 34.05 834 602.9 163.2 -55.84 -119.9 -38.1 4/25/07 16:55 32.92 767.9 518.2 158.8 -56.31 -119.6 -39.21 4/25/07 17:00 31.96 867 584.4 159.5 -55.09 -120.3 -41.75 4/25/07 17:05 32.18 960 663.7 30.24 -117.3 -112.9 -132.7 4/25/07 17:10 33.35 1014 760.5 42.76 -125.6 -127.7 -143.4 4/25/07 17:15 33.63 1039 788 -101. 5 -125.4 -134.9 -147.7 4/25/07 17:20 33.76 1013 789.4 130 -125.1 -136.6 -149.2 4/25/07 17:25 33.71 1013 758.1 143.9 -125 -136.7 -149.7 4/25/07 17:30 33.82 962 700.2 150.7 -124.7 -136.9 -148.5 4/25/07 17:35 34.12 929 650.3 160.7 -125 -139.2 -145.9 4/25/07 17:40 33.55 928 604.9 162.9 -124.1 -137.2 -142.4 4/25/07 17:45 33.09 772.1 589 165.1 -121.6 -137.3 -140 4/25/07 17:50 32.39 760 551.6 166.5 -121.3 -137 -137.8

PAGE 153

153Table B3. Thirty minute dataset including raw NO3 data Time and Date Flux Class Nitrate (M) DO (M) Water Elevation (cm) Temperature (C) Specific Conductivity (ms/cm) Total Dissolved Solids (g/L) Salinity (ppt) DO Saturation (%) pH Surface Solar Irradiance (S/cm2/s) Subsurface Solar Irradiance (S/cm2/s) 4/24/2007 17:30 RIVER 21.1 422.571.1 25. 6 6.7 4.3 3.6 84.4 8.0150.6 -138.7 4/24/2007 18:00 RIVER 21.2 401.971.6 25. 4 6.3 4.1 3.4 79.9 8.090.6 -139.0 4/24/2007 18:30 1 15.1 393.872.9 25.6 6.2 4.0 3.3 78.5 8.0159.1 -135.6 4/24/2007 19:00 1 14.4 374.475.3 25.3 6.1 4.0 3.3 74.3 8.0220.3 -136.8 4/24/2007 19:30 1 NA 355.077.2 25.0 6.1 4.0 3.3 70.0 8.0238.0 -135.9 4/24/2007 20:00 1 13.2 346.379.4 24.8 6.1 4.0 3.3 68.0 8.0241.5 -142.5 4/24/2007 20:30 1 13.0 381.381.4 24.6 6.1 4.0 3.3 74.7 8.0235.1 -143.2 4/24/2007 21:00 RIVER 19.9 441.983.1 24. 2 5.3 3.5 2.9 85.7 7.880.9 -145.0 4/24/2007 21:30 RIVER 20.5 451.383.9 24. 1 5.3 3.5 2.9 87.3 7.7-78.2 -145.2 4/24/2007 22:00 2 12.1 473.883.5 24.2 5.5 3.6 3.0 91.9 7.798.6 -144.6 4/24/2007 22:30 2 11.4 450.682.2 24.2 5.5 3.6 3.0 87.4 7.6215.5 -145.1 4/24/2007 23:00 2 11.2 452.580.4 23.8 5.5 3.6 3.0 87.1 7.6182.9 -143.9 4/24/2007 23:30 2 NA 420.078.5 23.3 5.5 3.6 3.0 80.1 7.6151.9 -140.7 4/25/2007 0:00 2 10.6 424.476.3 23.0 5.5 3.6 3.0 80.5 7.6165.4 -149.9 4/25/2007 0:30 2 10.2 420.073.6 22.8 5.5 3.6 3.0 79.4 7.6151.0 -154.8 4/25/2007 1:00 RIVER 27.5 243.170.9 22. 6 5.4 3.5 2.9 45.7 7.3118.0 -132.6 4/25/2007 1:30 RIVER 30.5 248.168.3 22. 6 5.4 3.5 2.9 46.7 7.2151.1 -106.5 4/25/2007 2:00 NA 26.5 246.965.8 22. 7 5.4 3.5 2.9 46.5 7.2-79.0 -167.9 4/25/2007 2:30 3 24.6 252.563.4 22.7 5.4 3.5 2.9 47.6 7.2-111.6 -166.8 4/25/2007 3:00 3 23.8 240.661.3 22.7 5.4 3.5 2.9 45.3 7.2-124.3 -165.1 4/25/2007 3:30 3 NA 230.059.3 22.6 5.4 3.5 2.9 43.2 7.1-122.8 -164.1 4/25/2007 4:00 3 22.8 220.658.0 22.5 5.4 3.5 2.9 41.4 7.1-119.6 -164.9 4/25/2007 4:30 3 21.8 211.956.8 22.6 5.4 3.5 2.9 39.8 7.1-123.9 -166.6 4/25/2007 5:00 RIVER 21.3 203.155.5 22. 5 5.3 3.5 2.9 38.2 7.1-108.3 -169.3 4/25/2007 5:30 RIVER 28.3 215.055.4 22. 5 5.9 3.8 3.2 40.5 7.1-123.6 -168.1 4/25/2007 6:00 4 26.9 210.654.7 22.5 5.9 3.9 3.2 39.7 7.1-137.8 -166.3 4/25/2007 6:30 4 26.1 196.354.3 22.4 5.8 3.8 3.2 36.8 7.1-133.7 -165.1 4/25/2007 7:00 4 NA 186.953.8 22.4 5.8 3.8 3.1 35.1 7.1-144.9 -167.9 4/25/2007 7:30 4 23.9 178.853.6 22.4 5.8 3.8 3.1 33.6 7.1-140.3 -170.1 4/25/2007 8:00 4 21.7 173.853.7 22.4 5.8 3.7 3.1 32.6 7.1-125.4 -167.8 4/25/2007 8:30 4 21.2 170.653.3 22.5 5.7 3.7 3.1 32.0 7.1-131.4 -162.1

PAGE 154

154Table B3 continued Time and Date Flux Class Nitrate (M) DO (M) Water Elevation (cm) Temperature (C) Specific Conductivity (ms/cm) Total Dissolved Solids (g/L) Salinity (ppt) DO Saturation (%) pH Surface Solar Irradiance (S/cm2/s) Subsurface Solar Irradiance (S/cm2/s) 4/25/2007 9:00 4 19.7 170.053.1 22.6 5.7 3.7 3.1 32.0 7.1-127.4 -155.2 4/25/2007 9:30 RIVER 23.8 295.652.9 22. 8 6.6 4.3 3.6 56.2 7.2-135.1 -155.0 4/25/2007 10:00 RIVER 21.3 372.553.1 23. 2 6.6 4.3 3.6 71.2 7.3-155.7 -155.8 4/25/2007 10:30 5 20.6 342.554.1 23.6 6.4 4.2 3.5 65.9 7.2-164.4 -150.1 4/25/2007 11:00 5 19.3 360.656.1 23.9 6.4 4.2 3.5 69.8 7.2-171.9 -146.6 4/25/2007 11:30 5 18.5 383.860.8 24.3 6.4 4.2 3.5 74.9 7.2-173.4 -147.4 4/25/2007 12:00 5 17.4 395.066.3 24.6 6.4 4.2 3.5 77.4 7.2-174.3 -140.1 4/25/2007 12:30 5 16.9 410.671.7 24.7 6.4 4.2 3.5 80.6 7.3-173.0 -133.6 4/25/2007 13:00 RIVER 16.1 424.477.0 24. 9 6.4 4.1 3.5 83.7 7.3-173.0 -124.2 4/25/2007 13:30 6 16.6 524.481.9 25.1 5.3 3.4 2.9 103.3 7.9-173.0 -116.8 4/25/2007 14:00 6 16.1 470.685.7 25.2 5.4 3.5 2.9 93.0 8.0-178.7 -114.0 4/25/2007 14:30 6 15.3 458.888.0 25.8 5.3 3.5 2.9 91.6 7.9-182.2 -115.4 4/25/2007 15:00 6 14.6 449.488.5 26.1 5.3 3.4 2.8 90.1 8.0-184.2 -120.0 4/25/2007 15:30 6 13.6 446.388.0 26.3 5.3 3.4 2.9 89.8 8.0-185.1 -121.6 4/25/2007 16:00 6 NA 439.486.5 26.1 5.4 3.5 2.9 88.2 8.1-183.8 -74.7 4/25/2007 16:30 NA 11.9 468.884.2 26.1 5.4 3.5 2.9 94.2 8.1-182.4 -61.7 4/25/2007 17:00 NA 56.0 423.882.3 26.0 5.4 3.5 2.9 84.9 8.1-164.9 -58.5 4/25/2007 17:30 SPIKE1 57.8 351.980.3 26. 0 5.3 3.5 2.9 70.5 8.2-99.9 -123.8 4/25/2007 18:00 SPIKE1 57.6 77.8 -164.3 -122.0 4/25/2007 18:30 SPIKE1 56.3 75.7 -160.1 -118.0

PAGE 155

155 LIST OF REFERENCES Alvarez-Gongora, C., and J.A. Herrera-Silveir a. 2006. Variations of phytoplankton community structure related to water quality trends in a tropical karstic coastal zone. Marine Pollution Bulletin 52:48-60. An, S., and S.B. Joye. 2001. Enhancement of coupl ed nitrification-deni trification by benthic photosynthesis in shallow estuarine sedi ments. Limnology and Oceanography 46:62-74. Andersen, J.M. 1976. Ignition method for determination of total phosphorus in lake sediments. Water Research 10:329-331. Arthur, J.D., A.E. Baker, J.R. Cichon, A. R. Wood, and A. Rudin. 2006. Florida aquifer vulnerability assessment. Florida Geological Survey Bulletin 67:150 p. Bianchi, T.S. Biogeochemistry of estuaries. 2007. Oxford University Press. New York, New York. 706 pp. Billerbeck, M., U. Werner, K. Bosselmann, E. Walpersdorf, and M. Huettel. 2006. Nutrient release from an exposed inte rtidal sand flat. Marine Ec ology-Progress Series 316:35-51. Bowen, J.L., and I. Valiela. 2001. The ecological e ffects of urbanization of coastal watersheds: historical increases in nitrogen loads a nd eutrophication of Wa quoit Bay estuaries. Canadian Journal of Fisherie s and Aquatic Sciences 58:1489-1500. Bradley, M.P., and M.H. Stolt. 2002. Evaluating methods to create a base map for a subaqueous soil inventory. Soil Science 167:222-228. Bradley, M.P., and M.H. Stolt. 2003. Subaqueous soil-landscape relationshi ps in a Rhode Island estuary. Soil Science Society of America Journal 67:1487-1495. Bradley, M.P., and M.H. Stolt. 2006. Landscape-le vel seagrass-sediment relations in a coastal lagoon. Aquatic Botany 84:121. Burnett, W.C., H. Bokuniewicz, M. Huettel, W.S. Moore, and M. Taniguchi. 2003. Groundwater and pore water inputs to the coas tal zone. Biogeochemistry 66:3-33. Burnett, W.C., P.K. Aggarwal, A. Aureli, H. Bokuni ewicz, J.E. Cable, M.A. Charette, E. Kontar, S. Krupa, K.M. Kulkarni, A. Loveless, W.S. Moore, J.A. Oberdorfer, J. Oliveira, N. Ozyurt, P. Povinec, A.M.G. Privitera, R. Rajar, R.T. Ramassur, J. Scholten, T. Stieglitz, M. Taniguchi, and J.V. Turner. 2006. Quantif ying submarine groundwater discharge in the coastal zone via multiple methods. Scie nce Of The Total Environment 367:498-543. Cable, J.E., J.B. Martin, and J. Jaeger. 2006. Exonerating Bernoulli? On evaluating the physical and biological processes a ffecting marine seepage mete r measurements. Limnology And Oceanography-Methods 4:172-183.

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156 Callahan, M.R., J.B. Rose, and J.H. Paul. 2001. A bacteriological and pathogenic water quality assessment of the upper reaches of the Chassahow itzka River. University of South Florida, St. Petersburg. Champion, K.M., and R. Starks. 2001. The hydrology a nd water quality of se lect springs in the Southwest Florida Water Management Distri ct. Report to the Southwest Florida Water Management District. Dauer, D.M., J.A. Ranasinghe, and S.B. We isberg. 2000. Relationships between benthic community condition, water quality, sediment qua lity, nutrient loads, and land use patterns in Chesapeake Bay. Estuaries 23:80-96. Davis, W.P., and A.D. Steinman. 1998. A lightwei ght, inexpensive benthic core sampler for use in shallow water. Journal Of Freshwater Ecology 13:475-479. DeBrabendere, L., Frazer, T.K., Montoya, J. Su bmitted 2006. Stable nitrogen isotope ratios of macrophytes and associated periphyton along a nitr ate gradient in two subtropical, springfed streams. Freshwat er Biology. In Press. Demas, G.P., M.C. Rabenhorst, and J.C. St evenson. 1996. Subaqueous soils: A pedological approach to the study of shallowwater habitats. Estuaries 19:229-237. Demas, G.P., and M.C. Rabenhorst. 1999. Suba queous soils: Pedogenesis in a submersed environment. Soil Science Societ y of America Journal 63:1250-1257. Demas, G.P., and M.C. Rabenhorst. 2001. Factors of subaqueous soil formation: a system of quantitative pedology for submersed environments. Geoderma 102:189-204. Eisma, D. 1998. Intertidal depos its: River mouths, tidal flats, and coastal lagoons CRC Press, Boca Raton. Ellis, L.R. 2006. Subaqueous pedology: Expanding so il science to near-shore subtropical marine habitats. Ph.D. Dissertation, Univer sity of Florida, Gainesville. ESRI. 2005. ArcGIS 9.1: Release 9.1. Redlands, CA. FDEP 1997. Florida Department of Environmen tal Protection Drainage basin data layers. Accessed online at: http://www.dep.state.fl.us/gis/datadir.asp March, 2007. Fischler, K.C. 2006. Observations and characteri zation of subaqueous soils and seagrasses in a recently constructed habitat in the Indian River Lagoon, Florida. M.S. Thesis, University of Florida, Gainesville. Fisher, M.M., and K.R. Reddy. 2001. Phosphorus fl ux from wetland soils affected by long-term nutrient loading. Journal Of Environmental Quality 30:261-271. Fisher, D.C., and M. Oppenheimer. 1991. Atmosphe ric nitrogen deposition and the Chesapeake Bay estuary. Ambio 20:102-108.

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163 BIOGRAPHICAL SKETCH Tom arrived on the scene in Denver, Colorado in February of 1978 and spent the first year of his life in a dresser drawer (open) in nearby Scottsbluff, Ne braska. From there the Saunders found their way to San Jose, California. Ca mping, hiking, and swimming in and around the mountains and valleys of the coastal footh ills and Yosemite National Park instilled a fundamental interest and enchantment with th e world outdoors. Wande rlust and restlessness took hold of Tom before long, motivating him to l eave high school in pursuit of an associates degree at Colorado Mountain College and fo cused on outdoor recreational leadership. Employment and personal time in the outdoors provided an abundance of unforgettable moments spent scaling granite and sandstone, working sear ch and rescue in Yose mite, guiding whitewater in Colorado, and truck-camping across climbing lo cales of the Southwest; all the time gaining a deeper respect and awe for the power and intricacy of the natural world. Tom shifted his focus from recreation toward e nvironmental science, obtaining his B.S. in Environmental Science from Humb oldt State University in Northern California. A strong interest in watershed science and travel experi ences in Latin America then drew him toward a masters from Florida International University that focused on riparian biogeochemistry in montane rainforests of the Peruvian Amazon. While in Florida he was particularly drawn toward the unique Florida Spring systems and the anthro pogenic activities affecting them. He pursued an opportunity to integrate soils, estuaries, and spring-fed rivers into his dissertation work. Tom and his wife Lynn plan to continue working on applied natural resource issues around the world.