Long Term Accretion of Phosphorus in Wetlands

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Title:
Long Term Accretion of Phosphorus in Wetlands The Everglades Stormwater Treatment Areas as a Case Example
Physical Description:
1 online resource (287 p.)
Language:
english
Creator:
Bhomia, Rupesh K
Publisher:
University of Florida
Place of Publication:
Gainesville, Fla.
Publication Date:

Thesis/Dissertation Information

Degree:
Doctorate ( Ph.D.)
Degree Grantor:
University of Florida
Degree Disciplines:
Soil and Water Science
Committee Chair:
Reddy, Konda R
Committee Members:
Wright, Alan Lee
Inglett, Patrick W
Brenner, Mark
Chimney, Michael J

Subjects

Subjects / Keywords:
accretion -- biogeochemistry -- phosphorus -- soil -- treatment -- wetlands
Soil and Water Science -- Dissertations, Academic -- UF
Genre:
Soil and Water Science thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract:
The presence of excess nutrients in an environment can negativelyaffect the ecological integrity of natural systems and lead to loss ofecosystem functions. Aquatic ecosystems experience impairment of naturalstructure and functions due to high nutrient inputs. Constructed treatment wetlandsare often utilized to transform, modify or store excess nutrients and protectdownstream ecosystems. This study was conducted to enhance our understanding ofselect biogeochemical processes that control treatment performance, efficiencyand long-term sustainability of such constructed wetlands. Large constructedwetlands in south Florida, the Everglades Stormwater Treatment Areas (STAs),were selected as the experimental sites for this research. These STAs werebuilt to treat surface runoff originating in the Everglades Agricultural Area(EAA) by removing excess phosphorus (P) from the water before it flows into theEverglades. The overarching goal of this dissertation research was to understandkey processes that control and regulate transformation of P from the reactive(potentially bio-available) fraction into the non-reactive (stable) fractions. Associatedpathways for this transformation were also investigated to determine treatmentwetlands (STAs) capability to provide long-term sustainable storage of thesequestered P. This task was carried out by analyzing long-term soil P dataobtained from various STAs and conducting experiments to quantify andcharacterize soil P storage pools and functional chemical P forms within the STAsthat have been in operation for 10-16 years. Spatio-temporal variation in floc, recently accreted soil(RAS) and pre-STA (antecedent) soil P storage pools was calculated by utilizingexisting information from soils monitoring. Stratigraphic properties of soilprofiles were utilized to determine the boundary between RAS and pre-STA soil,which were then used to calculate accretion rates in the STAs. An inverserelationship was found between accretion rates and operational age of the STAs,suggesting that the rate of new soil formation decreased over time. Using soilP pools, and P retained from the water column, P mass balances for the STAs weredeveloped. Phosphorus mass balance calculations indicated that a large portionof P in RAS sections was probably mined from deeper soil sections. The quality and quantity of sequestered P has profoundimplications for the interaction and fate of P in the STAs, hence chemicalcharacterization of accreted P was done by using operationally defined Pfractionation schemes. Effects of STA age and dominant vegetation on chemicalpartitioning of accreted P were investigated. Fractionation analysis showedthat about 70% of P in the RAS section was in reactive form, i.e., potentiallyvulnerable to mobilization. The relative proportion of reactive and non-reactiveP pools within emergent and submerged aquatic vegetation cells were similar acrossthe studied STAs. Greater proportions of reactive P pools were observed in flocand RAS sections of SAV cells in comparison to EAV cells. In other words, flocand RAS sections of SAV cells contain larger proportion of reactive P than infloc and RAS of EAV cells. Strong positive correlation between TP and calcium(Ca) in floc and RAS layers suggested Ca-P co-precipitation as the dominantmechanism of P removal in SAV cells. Among reactive P pools, the Pi pool washigher in SAV cells while Po pool was greater in EAV cells. Long-term effectiveness and sustainability of treatment wetlands is important to meet treatment targets and protect downstream targets. This dissertation research was designed to advance our understanding of the extent and quality of P pools in treatment wetlands to allow for better planning and management under conditions of environmental uncertainty. Normal 0 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable{mso-style-name:"Table Normal";mso-tstyle-rowband-size:0;mso-tstyle-colband-size:0;mso-style-noshow:yes;mso-style-priority:99;mso-style-parent:"";mso-padding-alt:0in 5.4pt 0in 5.4pt;mso-para-margin:0in;mso-para-margin-bottom:.0001pt;mso-pagination:widow-orphan;font-size:10.0pt;font-family:"Times New Roman","serif";}
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Bibliography:
Includes bibliographical references.
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Description based on online resource; title from PDF title page.
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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.
Statement of Responsibility:
by Rupesh K Bhomia.
Thesis:
Thesis (Ph.D.)--University of Florida, 2013.
Local:
Adviser: Reddy, Konda R.
Electronic Access:
RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2014-05-31

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Source Institution:
UFRGP
Rights Management:
Applicable rights reserved.
Classification:
lcc - LD1780 2013
System ID:
UFE0045022:00001


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1 LONG TERM ACCRETION OF PHOSPHORUS IN WETLANDS: THE EVERGLADES STORMWATER TREATMENT AREAS AS A CASE EXAMPLE By RUPESH KUMAR BHOMIA A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULF ILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 201 3

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2 201 3 Rupesh K umar Bhomia

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3 To my par ents, Suresh and Santosh Bhomia

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4 ACKNOWLEDGEMENTS No words can describe my debt to my parents, who have encoura ged and motivated me t his academic endeavor, one of those adventures, would not have been successful w ithout their profound love and support. Equally important was my advisor Dr. Reddy guidance and encouragemen t that provided the necessary fuel for my progress. I am highly grateful for his patience and persistent belief in my capabilities. I am also thankful to the members of my supervisory committee Dr. Mark Brenner, Dr. Patrick Inglett and Dr. Alan Wright wh o guided me during my research efforts. I thank Dr. Michael Chimney, external committee member, for fulfill ing the role of a critical reviewer and suggesting ideas that reinforced the importance of my work. The import ance of m y research for meeting Evergla des restoration goals was recognized by two premier organizations themselves dedicated to the protection of the Everglades ecosystem. I am thankful to both the South Florida Water Management District and the Everglades Foundatio n for provid ing partial fund ing and technical support for conducting my research I would like to acknowledge s pecifically Ms. Delia Ivano ff, Mr. Manuel Zamorano, Mr. Michael Korvela and Dr Hongjun Chen from the District for extending technical help and field assistance for soil sa mple collection and research. I thank my swamp buddies Michael Jerauld, Alex Cheesman and John Linhoss who accompanied me during my multiple sorties to collect soil cores from the Stormwater Treatment Areas in s outh Florida. I thank Michael Jerauld, Rohi t Kanungo and Christine VanZomeren for assistance in sample processing. Ms. Yu Wang and Mr. Gavin Wilson methodically trained me on every laboratory procedure or equipment

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5 operation that was carried out at the UF Wetland Biogeochemistry L ab oratory. For ini tial training and for elaborate discussions on lab instruments, analytical techniques and generated data, I thank them greatly The staff at the Soil and Water Science Department Mr. Michael Sisk, Ms. Cheryl Combs, Ms. Linda Cowart, Ms. Lacey Givens and Ms. An Nguyen were remarkable in taking care of all kinds of admi nistrative tasks. I acknowledge their eagerness to help and thank them fondly for their day to day assistance. I recognize all the friendly folks my fellow lab members and students for ind ulging me into their world in many unique ways and for generously offering me the benefits of their lively companionship. It is impossible to acknowledge all of them here, but I warmly remember Mike Jerauld, Luke Gommerman, Justin V ogel John Linhoss, Case y Schmidt, Louis Philor, Pasicha Chaikaew, Dakshina Murthy, Daniel Irick, Jing Hu, Christine VanZomeren, Rosalyn Johnson, Philip Alderman and Hugo Sindelar (RJ), for interesting conversations and delightful discussions over cups of coffee or tasty meals. T ime spent in the company of these smiling faces was a truly rewarding experience. I owe special thanks to Michael Jerauld and his parents for sharing a bond of friendship that only grew stronger with time. I would like to thank Dr. Arun Jain Ms. Smita Jai n and Ms. Janice Garry, friends outside of the UF network who had a positive impact on me and were helpful in many ways. I am h ighly indebted to Dr. Paromita C hakraborty for her true friendship and care during the final stages of my dissertation research and writing. F inally, to my little heroes Milli and Joy (niece and nephew), whose sweet presence in my life mak e s everything delightful and meaningful; I shall always remain grateful to them

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6 TABLE OF CONTENTS page ACKNOWLEDGEMENTS ................................ ................................ ............................... 4 LIST OF TABLES ................................ ................................ ................................ ............ 9 LIST OF FIGURES ................................ ................................ ................................ ........ 13 ABSTRACT ................................ ................................ ................................ ................... 20 CHAPTER 1 INTRODUCTIO N ................................ ................................ ................................ .... 23 Treatment Wetlands ................................ ................................ ................................ 24 Biogeochemical Processes ................................ ................................ .............. 26 Phosphoru s Removal Mechanisms ................................ ................................ .. 29 Site Description ................................ ................................ ................................ ....... 33 Dissertation Overview ................................ ................................ ............................. 33 Dissertation Objectives and Hypotheses ................................ .......................... 34 Dissertation Layout ................................ ................................ ........................... 35 2 SPATIO TEMPORAL CHANGES IN SOIL NUTRIENT STORAGE IN THE EVERGLADES STORMWATER TREATMENT AREAS: IMPACT ON PHOSPHORUS REMOVAL PERFORMANCE ................................ ....................... 41 Background ................................ ................................ ................................ ............. 41 Objectives and Hypotheses ................................ ................................ .................... 45 Methods ................................ ................................ ................................ .................. 46 Site Description ................................ ................................ ................................ 46 Data Sources ................................ ................................ ................................ .... 47 Soil Nutrient Mass Storages ................................ ................................ ............. 48 Phosphorus Mass Balance ................................ ................................ ............... 48 Data Analysis ................................ ................................ ................................ ... 50 Results ................................ ................................ ................................ .................... 51 Physico Chemical Properties ................................ ................................ ........... 51 Phosphorus ................................ ................................ ................................ ...... 51 Nitrogen ................................ ................................ ................................ ............ 52 Carbon ................................ ................................ ................................ .............. 53 Mass Balance ................................ ................................ ................................ ... 53 Discussion ................................ ................................ ................................ .............. 54 Phosphorus Retention ................................ ................................ ...................... 55 Phosphorus Mass Balance ................................ ................................ ............... 57 Impact of STA Age on Phosphorus Retention ................................ .................. 58 Summary ................................ ................................ ................................ ................ 60

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7 3 CHANGE POINT TECHNIQUE FOR MEASUREMENT OF SOIL ACCRETION RATES IN CONSTRUCTED WETLANDS ................................ .............................. 78 Background ................................ ................................ ................................ ............. 78 Methods ................................ ................................ ................................ .................. 80 Site Description ................................ ................................ ................................ 80 Soil Sampling and Processing ................................ ................................ .......... 82 Chemical and Isotopic Analysis ................................ ................................ ........ 82 Change point Analysis ................................ ................................ ..................... 83 Results ................................ ................................ ................................ .................... 85 Discussion ................................ ................................ ................................ .............. 86 4 SOIL AND NUTRIENT ACCRETION RATES IN TREATMENT WETLANDS OF THE EVERGLADES BASIN ................................ ................................ ............ 100 Background ................................ ................................ ................................ ........... 100 Objectives and Hypotheses ................................ ................................ .................. 103 Methods ................................ ................................ ................................ ................ 104 Site Description ................................ ................................ .............................. 104 S oil Sampling and Processing ................................ ................................ ........ 105 Data Analysis ................................ ................................ ................................ 106 Mass Balances ................................ ................................ ............................... 107 Results ................................ ................................ ................................ .................. 108 Soil and Phosphorus Accretion Rates ................................ ............................ 109 Phosphorus Mass Balance ................................ ................................ ............. 110 Discussion ................................ ................................ ................................ ............ 110 Soil Physico Chemical Properties ................................ ................................ .. 111 Soil and Phosphorus Accretion Rates ................................ ............................ 112 Phosphorus Mass Balance ................................ ................................ ............. 114 Summary ................................ ................................ ................................ .............. 115 5 STABILITY OF PHOSPHORUS IN RECENTLY AC CRETED SOILS: ASSOCIATED VEGETATION EFFECTS ................................ ............................. 127 Background ................................ ................................ ................................ ........... 127 Objectives and Hypotheses ................................ ................................ .................. 129 Methods ................................ ................................ ................................ ................ 129 Site Description ................................ ................................ .............................. 129 Soil and Chemical Analysis ................................ ................................ ............ 130 Soil Phosphorus Fractionation ................................ ................................ ........ 131 Data Analysis ................................ ................................ ................................ 132 Results ................................ ................................ ................................ .................. 133 Total Nitrogen ................................ ................................ ................................ 134 Total Carbon ................................ ................................ ................................ ... 134 Metals ................................ ................................ ................................ ............. 134 Phosphorus Fractions ................................ ................................ .................... 135 Vegetation Effects ................................ ................................ .......................... 136

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8 Correlations Among Soil Properties ................................ ............................... 137 Discussion ................................ ................................ ................................ ............ 138 Summary ................................ ................................ ................................ .............. 141 6 CONCLUSIONS ................................ ................................ ................................ ... 164 Objective 1: Spatio Temporal Changes in Soil Nutrient Storages ......................... 167 Objective 2: Soil Accretion in Treatment Wetlands ................................ ............... 168 Objective 3: Soil Accretion and Operational Age of Treatment Wetlands ............. 168 Objective 4: Stability of Phosphorus in Recently Accreted Soil ............................. 169 Synthesis ................................ ................................ ................................ .............. 1 70 Future Outlook and Sustainability of STAs ................................ ........................... 172 APPENDiX A ADDITIONAL DATA AND INFORMATION PER TAINING TO CHAPTER 1 ......... 177 B ADDITIONAL DATA AND INFORMATION PERTAINING TO CHAPTER 2 ......... 179 C ADDITIONAL DATA AND INFORMATION PERTAIN ING TO CHAPTER 3 ......... 186 D ADDITIONAL DATA AND INFORMATION PERTAINING TO CHAPTER 4 ......... 191 E ADDITIONAL DATA AND INFORMATION PERTAINING TO CHAPTER 5 ......... 248 LIST OF REFERENCES ................................ ................................ ............................. 266 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 287

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9 LIST OF TABLES Table page 2 1 Bulk density for floc and soil samples from the STAs ................................ ........ 62 2 2 Mean floc depth acros s the STAs for sampling years. ................................ ........ 63 2 3 Total phosphorus concentration in floc and soils in the STAs ........................... 63 2 4 Total phosphorus areal storage in floc and soils in t he STAs ............................. 64 2 5 Comparison of total phosphorus removed from the water column and floc phosphorus storage and soil phosphorus storage. ................................ ............. 64 2 6 Total nitrogen areal storage in floc and soils in the STAs ................................ ... 65 2 7 Total carbon areal storage in floc and soils in the STAs ................................ ..... 66 2 8 Variation in areal and total nutrient storages in the STAs with different ages. Nutrient masses represent entire floc depth and top 10 cm of surface soil. ...... 66 3 1 Soil accre tion measurement methods and published accretion rates from wetland studies. ................................ ................................ ................................ .. 91 4 1 Soil and phosphorus accretion rates in STA 1W, STA 2 and STA 3/4 ............. 117 5 1 Summary statistics for bulk density of soil sections in EAV and SAV cells of STA 1W and STA 2 .. ................................ ................................ ....................... 142 5 2 Summary statistics for loss on ignition of soil sections in EAV and SAV cells of STA 1W and STA 2 ...................................................................................... 142 5 3 Summary statistics for total phosphorus content of soi l sections in EAV and SAV cells of STA 1W and STA 2 .. ................................ ................................ ... 143 5 4 Summary statistics for total phosphorus storage pools for each soil fraction in EAV and SAV cells of STA 1W and STA 2... ................................ .................... 143 5 5 Summary statistics for total nitrogen content of soil sections in EAV and SAV cells of STA 1W and STA 2. ................................ ................................ ............. 144 5 6 Summary stat istics for total nitrogen storage pools for each soil fraction in EAV and SAV cells of STA 1W and STA 2. ................................ ...................... 144 5 7 Summary statistics for total carbon content of soil sections in EAV and SAV ce lls of STA 1W and STA 2 ................................ ................................ .............. 145

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10 5 8 Summary statistics for total carbon storage pools for each soil fraction in EAV and SAV cells of STA 1W and STA 2. ................................ .............................. 145 5 9 Summary statistics for calcium content of soil sections in EAV and SAV cells of STA 1W and STA 2. ................................ ................................ ..................... 146 5 10 Summary statistics for magnesium content of soil section s in EAV and SAV cells of STA 1W and STA 2. ............................................................................. ................................ ............ 146 5 11 Summary statistics for iron content of soil sections in EAV and SAV cells of STA 1W and STA 2 ................................ ................................ ........................ 147 5 12 Summary statistics for aluminum content of soil sections in EAV and SAV cells of STA 1W and STA 2 .. ................................ ................................ ........... 147 5 13 Summary statistics for phosphorus content in P fractions in floc, RAS and pre STA soil from EAV and SAV cells in STA 1W and STA 2 .......................... 148 5 14 Summary statistics for phosphorus content in P fractions in floc, RAS and pre STA soil from EAV and SAV cells in STA 1W ................................ ............ 149 5 15 Summary statistics for phosphorus content in P fractions in floc, RAS and pre STA so il for EAV and SAV cells in STA 2 ................................ .................. 149 5 16 Pearson correlation coefficients for select parameters measured in all soil fractions in both STA 1W and STA 2 .. ................................ ............................. 150 5 17 Pearson correlation coefficients for select parameters measured in all soil fractions in EAV cells from both STA 1W and STA 2 ................................ ....... 151 5 18 Pearson correlat ion coefficients for select parameters measured in all soil fractions in SAV cells from both STA 1W and STA 2 ................................ ...... 152 5 19 Pearson correlation coefficients for select parameters measured in all soil fractions from STA 1W ................................ ................................ ................... 153 5 20 Pearson correlation coefficients for select parameters measured in soil fractions from STA 2. ................................ ................................ ........................ 154 A 1 Treatment Wetland Technology conferences ................................ ................... 177 B 1 Mean total nitrogen concentration in floc and soils in STAs ............................ 182 B 2 Mean total carbon concentration in floc and soils in STAs ............................... 183 B 3 STA performance for WY2011 and the period of record. ................................ .. 184

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11 C 1 Number of 2 cm sections produced by sectioning soil cores collected from STA 1W. ................................ ................................ ................................ ........... 186 C 2 Number of 2 cm sections produced by sectioning soil cores collected from STA 2. ................................ ................................ ................................ .............. 186 C 3 Number of 2 cm sections produced by sectioning soil cores collected from STA 3/4. ................................ ................................ ................................ ........... 187 D 1 STA 1W soil core collection sites by vegetat ion type and cell. ......................... 194 D 2 STA 2 soil core collection sites by vegetation type and cell. ............................ 194 D 3 STA 3/4 soil core collection sites by vegetation type and cell..... ...................... 195 D 4 Summary statistics for change point depths calculated with SegReg in soil cores collected from STA 1W, STA 2 and ST A 3/4. ................................ ......... 196 D 5 Bulk density profiles in soil cores collected from each cell of STA 1W ............. 197 D 6 Total phosphorus profiles in soil cores collected from each cell of STA 1W ..... 198 D 7 Bulk density and total phosphorus profiles in soil cores collected from each cell of STA 2. ................................ ................................ ................................ .... 199 D 8 Bulk density and total phosphorus profiles in soil cores collected from each cell of STA 3/4 ................................ ................................ ................................ .. 200 E 1 STA 1W and STA 2 soil core collection sites by vegetation type and cell ........ 248 E 2 Mean depth of RAS at STA 1W sampling sites used for separating RAS from pre STA soil. ................................ ................................ ................................ ..... 249 E 3 Mean depth of RAS at STA 2 sampling sites used for separating RAS from pre STA soil. ................................ ................................ ................................ .... 249 E 4 Depth of soil fraction, bulk density, total phosphorus concentration and TP storage for each soil fraction at sampl ing sites in STA 1W. .............................. 250 E 5 Depth of soil fraction, bulk density, total phosphorus concentration and TP storage for each soil fraction at sampling sites in STA 2. ........................... ...... 251 E 6 Depth of soil fraction, bulk density, total nitrogen concentration and TN storage for each soil fraction at sampling sites in STA 1W. .............................. 253 E 7 Depth of soil fraction, bulk density, total nitrogen concentration and TN storage for each soil fraction at sampling sites in STA 2. ................................ 254

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12 E 8 Depth of soil fract ion. bulk density, total carbon concentration and TC storage for each soil fraction at sampling sites in STA 1W ................................ ........... 256 E 9 Depth of soil fraction, bulk density, total carbon concentration and T C storage for each soil fraction at sampling sites in STA 2 ................................ .............. 257 E 10 Average total phosphorus concentration and TP storage for each soil fraction over all sampling sites in EAV and SAV cells of STA 1W ................................ 259 E 11 Average total phosphorus concentration and TP storage for each soil fraction over all sampling sites in EAV and SAV cells of STA 2 ................................ .... 259 E 12 Average total nitrogen concentration and TN storage for each soil fraction over all sampling sites in EAV and SAV cells of STA 1W ................................ 260 E 13 Total nitrogen con centration and TN storage for each soil fraction over all sampling sites in EAV and SAV cells of STA 2. ................................ ................ 260 E 14 Total carbon concentration and TC storage for each soil fraction over all samp ling sites in EAV and SAV cells of STA 1W. ................................ ............ 261 E 15 Total carbon concentration TC and storage for each soil fraction over all sampling sites in EAV and SAV cells of STA 2. ................................ ............... 261 E 16 Pearson correlation coefficients for select parameters measured in soil cores from EAV cells of STA 1W ................................ ................................ ............... 262 E 17 Pearson correlat ion coefficients for select parameters measured in soil cores from SAV cells of STA 1W ................................ ................................ ............... 262 E 18 Pearson correlation coefficients for select parameters measured in soil cores from EAV cells of STA 2. ................................ ................................ .................. 263 E 19 Pearson correlation coefficients for select parameters measured in soil cores from SAV cells of STA 2 ................................ ................................ ................... 263

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13 LIST OF FIGURES Figure page 1 1 Cross section view of emergent and submerged aquatic vegetation in free water surface wetlands.. ................................ ................................ ..................... 37 1 2 Common bioge ochemical processes with regard to phosphorus cycling in typical free water surface wetland ................................ ................................ ...... 38 1 3 Map showing the locations of the original six Stormwater Treatment Areas, the Everglades Agr icultural Area and the Everglades Protection Area in South Florida ................................ ................................ ................................ ..... 39 1 4 Configuration of the treatment cells within each Stormwater Treatment Area .... 40 2 1 Phosphorus mass balance calculations for soil P storage with respect to net P retained from the water column. ................................ ................................ ...... 67 2 2 Relationship between STA age and fraction o f total phosphorus storage in floc and soil derived from the water column ................................ ....................... 68 2 3 Relationship between total P retained from the water column through WY2007 and total P storage in floc and soi l ................................ ....................... 69 2 4 Relationship between total P retained from the water column and total P storage in floc and soil.. ................................ ................................ ..................... 70 2 5 Relationsh ip between total P retained from water column and total P storage in floc and soil.. ................................ ................................ ................................ ... 71 2 6 Relationship between floc total P concentration and inflow total P flow weighted mean concentration ................................ ................................ ............ 72 2 7 Relationship between floc P storage and inflow total P flow weighted mean concentration ................................ ................................ ................................ ..... 73 2 8 Relationship between soil carbon storage and soil P storage in WY2007. ......... 74 2 9 Phosphorus mass balance calculations for soil P storage with respect to net P retained from the water column.. ................................ ................................ ..... 75 2 10 Relationship between mean floc P storage per year and STA age.. .. ............... 76 2 11 Relationship between mean surface soil P storage per year and STA age.. ...... 77 3 1 Location of the STA 1W, STA 2 and STA 3/4 and the number of soil cores collected from each STA ................................ ................................ ................... 94

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14 3 2 A cross s ection view of a typical free water surface treatment wetland and schematic depiction of a boundary between recently accreted soil and pre STA soil ................................ ................................ ................................ .............. 95 3 3 SegReg output using bulk density, to tal phosphorus content, and stable isotopic ratios of C and N in a representative soil profile from STA 2. ................ 96 3 4 Depth of RAS for STA 1W, STA 2, and STA 3/4 as determined by SegReg change po ints using bulk density, total phosphorus, isotope ratio of C and N.. ................................ ................................ ................................ ...................... 97 3 5 Variation in RAS depth between two dominant vegetation types Emergent Aquatic Vegetation and submerged aquatic vegetation for four parameters bulk density, total phosphorus, stable isotope ratio of C and N. ........................ 98 3 6 Comparison of RAS depth obtained by using SegReg program and 137Cs peaks from Evergla des Water Conservation Area 2. ................................ ......... 99 4 1 Location of the STA 1W, STA 2 and STA 3/4 and the number of soil cores collected from each STA. ................................ ................................ ................. 118 4 2 Phosphorus mass balance calculations for soil P storage with respect to net P retained from the water column.. ................................ ................................ ... 11 9 4 3 Differences in soil profile bulk density and total phosph orus content between two vegetation communities, in STA 1W, STA 2 and STA 3/4. .... ................... 120 4 4 15 13 communities, EAV and SAV, in STA 1W, STA 2 and STA 3/4. ..................... 121 4 5 Differences in soil profile C:N ratio and N:P ratio between two vegetation communities, EAV and SAV, in STA 1W, STA 2 and STA 3/4. ........................ 122 4 6 RAS depth as determined using change point analyses for different cells of STA 1W, STA 2, STA 3/4 and for entire STA. ................................ ............... 123 4 7 Soil acc retion rate as a function of STA age for STA 1W, STA 2 and STA 3/4. ................................ ................................ ................................ ................... 124 4 8 Phosphorus accretion rate as a function of STA age for STA 1W, STA 2 and STA 3/4.. ................................ ................................ ................................ .......... 125 4 9 Phosphorus mass balance calculations for soil P storage with respect to net P retained from the water column ................................ ................................ ... 126 5 1 Location of soil sampling sites in the STAs. Field triplicate sites are shown ..... 155 5 2 Phosphorus fractionation scheme used to characterize P forms in STA soils 156

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15 5 3 Phosphorus content and relative proportion of P fractions (organic, inorganic and residual P) in floc, RAS and pre STA soil of STA 1W. ............................... 157 5 4 Phosphorus content and relative prop ortion of P fractions (organic, inorganic and residual P) in floc, RAS and pre STA soil of STA 2. ................................ 158 5 5 Inorganic P content plotted against TP for all soil sections in EAV and SAV cells fr om STA 1W and STA 2. ................................ ................................ ......... 159 5 6 Organic P content plotted against TP in EAV and SAV cells from STA 1W and STA 2 ................................ ................................ ................................ ........ 159 5 7 Percent c omposition of stable and reactive phosphorus pools in the floc, RAS and pre STA soil of EAV and SAV cells for STA 1W and STA 2 ...................... 160 5 8 Non reactive phosphorus as a fraction of total phosphoru s in floc, RAS and pre STA soil of STA 1W and STA 2. ................................ ................................ 161 5 9 Relationship between phosphorus and calcium in EAV and SAV cells of STA 1W. ................................ ................................ ................................ ................. 162 5 10 Relationship between phosphorus and calcium in EAV and SAV cells of STA 2. ................................ ................................ ................................ ...................... 163 6 1 Summary of total phosphorus loading rates, TP accretion rates and distribution of reac tive and non reactive TP pools of STA 2. ............................ 176 C 1 Soil core sampling locations in each cell of STA 1W ................................ ........ 188 C 2 Soil core samplin g locations in each cell of STA 2 ................................ ........... 189 C 3 Soil core sampling locations in each cell of STA 3/4. ................................ ...... 190 D 1 Soil depth p rofiles f rom STA 1W. ................................ ................................ ..... 201 D 2 Soil depth profiles from from STA 2. ................................ ................................ 202 D 3 Soil depth profiles from STA 3/4. ................................ ................................ ...... 203 D 4 Bulk density profile in each soil core collected from STA 1W. .......................... 204 D 5 Total phosphorus profile in each soil core collected from STA 1W ................... 211 D 6 Bulk density profile in each soil core collected from STA 2. ............................. 218 D 7 Total phosphorus profile in each soil core collected from STA 2. .................... 223 D 8 Bulk density profile in each soil core collected from STA 3/4. ......................... 228

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16 D 9 Total phosphorus profile in each soi l core collected from STA 3/4 .................. 238 E 1 Relation of TP with Po and Pi and LOI with Po in floc, RAS and pre STA soil from EAV and SAV cells of STA 1W. ................................ .............................. 264 E 2 Relation of TP with Po and Pi and LOI with Po in floc, RAS and pre STA soil from EAV and SAV cells of STA 2. ................................ ................................ ... 265

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17 LIST OF ABBREVIATION S ADW Agricultural Drainage Water AFDW Ash Free Dry Weig ht Al Aluminum BD Bulk Density BMP Best Management Practices C Carbon Ca Calcium CAB Cellulose Acetyl Butyrate CPT Change point Technique EAA Everglades Agricultural Area EAV Emergent Aquatic Vegetation ECP Everglades Construction Project ENRP Everglades N utrient Removal Project EPA Everglades Protection Area FAV Floating Aquatic Vegetation Fe Iron FEFA Florida Everglades Forever Act FL Florida FCS Floc Carbon Storage FNS Floc Nitrogen Storage FPS Floc Phosphorus Storage FWMC Flow Weighted Mean Concentratio ns FWS Free Water Surface HCl Hydro c hloric Acid

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18 HSSF Horizontal Subsurface Flow LOI Loss on Ignition Mg Magnesium N Nitrogen NaOH Sodium Hydroxide NMR Neutron Magnetic Resonance NPDES National Pollution Discharge Elimination System NP P Net Primary Producti vity P Phosphorus PS Phosphorus Storage PAR Phosphorus Accretion Rate POR Period of Record RAS Recently Accreted Soils REE Rare Earth Elements RPM Revolution p er Minute SAR Soil Accretion Rate SAV Submerged Aquatic Vegetation SD Standard Deviation SET Sedi ment Elevation Table SFER South Florida Environment Report SFWMD South Florida Water Management District SCS Soil Carbon Storage SNS Soil Nitrogen Storage SPS Soil Phosphorus Storage SRP Soluble Reactive Phosphorus

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19 STA Stormwater Treatment Area TC Total Ca rbon TN Total Nitrogen TP Total Phosphorus USACE United States Army Corps of Engineers USEPA United States Environmental Protection Agency VF Vertical Flow WCA Water Conservation Areas XANES X ray Absorption Near Edge Structure

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20 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 LONG TERM ACCRETION OF PHOSPHORUS IN WETLANDS: THE EVERGLADES STORMWATER TREATMENT AREAS AS A C ASE EXAMPLE By Rupesh Kumar Bhomia May 2013 Chair: K. Ramesh Reddy M ajor: Soil and Water Science The p resence of e xcess nutrients in an environment can negatively affect the ecological integrity of natural systems and lead to loss of ecosystem functi ons. Aquatic ecosystems experience impairment of natural structure and functions due to high nutrient inputs C onstructed treatment wetlands are often utilized to transform, modify or store excess nutrients and protect downstream ecosystems Th is study was conducted to enhance our understanding o f select biogeochemical processes that control treatment performance, efficiency and long term sustainability of such constructed wetlands Large constructed wetlands in s outh Florida, the Everglades Stormwater Trea tment Areas (STAs) were selected as the experimental site s for this research. The se STAs were built to treat surface runoff originating in the Everglades Agricultural Area (EAA) by removing excess phosphorus (P) from the water before it flow s into the Eve rglades The o vera rching goal of t his dissertation research was to understand key processes that control and regulate transformation of P from the reactive (potentially bio available) fraction into the non reactive (stable) fractions Associated pathways for this transformation were also investigated to determine treatment wetlands ( STAs )

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21 capability to provide long term sustainable storage of the sequestered P. This task was carried out by analyzing long term soil P data obtained from various STAs and cond ucting experiments to quantify and characterize soil P storage pools and functional chemical P forms within the STAs that have been in operation for 10 16 years Spatio temporal variation in floc, recently accreted soil (RAS) and pre STA (antecedent) soil P storage pools was calculated by utilizing existing information from soils monitoring. Stratigraphic properties of soil profile s were utilized to determine the boundary between RAS and pre STA soil which were then used to calculate accretion rates in the STAs An i nverse relationship was found between accretion rate s and operational age of the STAs suggesting that the rate of new soil formation decreased over time Using soil P pools, and P retained from the water column, P mass balance s for the STAs wer e developed. Phosphorus mass balance calculations indicated that a large portion of P in RAS sections was probably mined from deeper soil sections. The quality and quantity of sequestered P has profound implications for the interaction and fate of P i n th e STAs, hence chemical characterization of accreted P was done by using operationally defined P fractionation schemes. Effects of STA age and dominant vegetation on chemical partitioning of accreted P were investigated. Fractionation analysis showed that a bout 70% of P in the RAS section was in reactive form i.e. potentially vulnerable to mobilization. The r elative proportion of reactive and non reactive P pools within emergent and submerged aquatic vegetation cells were similar across the studied STAs G reater proportions of reactive P pools were observed in floc and RAS sections of SAV cells in comparison to EAV cells. In other words, floc and RAS sections of SAV cells contain larger proportion of reactive P than in floc and

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22 RAS of EAV cells. Strong posi tive correlation between TP and calcium (Ca) in floc and RAS layers suggested Ca P co precipitation as the dominant mechanism of P removal in SAV cells. Among reactive P pools, the Pi pool was higher in SAV cells while Po pool was greater in EAV cells. Lon g term effectiveness and sustainability of treatment wetlands is important to meet treatment targets and protect downstream targets. T his dissertation research was designed to advance our understanding of the extent and quality of P pools in treatment wetl ands to allow for better planning and management under conditions of environmental uncertain ty

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23 CHAPTER 1 INTRODUCTION Wetlands are dynamic ecosystems characterized by unique hydrology, soils, vegetation and high net primary productivity (NPP ) ( Keefe, 1972 ; Westlake, 1963 ) As a transitional ecotone s between terrestrial and aquatic ecosystems w etlands fulfi ll a vital role in the landscape continuum ( Sheaves, 2009 ) These productive ecosystem s are a source of many direct and indirect benefits ( Blackwell and Pilgrim, 2 011 ; Costanza and others, 1997 ) and more recently wetlands have been a major catalyst in transforming perspective on the value of ecosystem services offered by other natural ecosyste ms ( Maltby and Acreman, 2011 ) As natural systems, wetlands are increasingly c onsidered valuable capital assets 1 ( Barbier, 2011 ; Daily and others, 2000 ) that provide important services in cluding water quality improvement ( Gilliam, 1994 ; Kadlec and others, 1979 ; Moshiri, 1993 ; Van der Valk and Jolly, 1992 ; Verhoeven and others, 2006 ) flood abatement ( Potte r, 1994 ) ground water discharge recharge ( Acharya, 2000 ) biodiversity enhancement ( Erwin, 1990 ; Mitsch and others, 2009 ) and a variety of recr eational ( Bergstrom and others, 1990 ) and educational opportunities ( Sukhontapatipak and Srikosamatara, 2012 ) T hese services are a net outcome of several biophysical process es that take place within a wetland These complex processes are often bundled to gether in a single term wetland functions which is used frequently in discussions pertaining to valuation of nature ( De Groot, 1992 ) The ability of natural wetlands to improve water quality is one such function that depends on e xisting biogeochemical and physical conditions uniquely present in a wetland environment. Recognition of a to treat polluted 1 Asset can be defined as an economic resource that can produce a flow of beneficial goods and services over time

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24 waters resulted in efforts to create artificial wetlands for abating unwanted contaminants in water. Early research in this direction began in 1952 when Dr. K the Seidel, Max Planck Institute started experimenti ng with m acrophytes to treat wastewater ( Bastian and Hammer, 1993 ) Currently thousands of function ing constructed wetlands are located globally across multiple geographic regions in both developed and developing nations. Treatment Wetland s Constructed wetlands are used for reduction of nutrient loads in surface runoff to protect downstream ecosystems Impacts from excess nutrient availability are known to degrade the natural balance of aquatic ecosystems ( Belanger and others, 198 9 ; Smith, 2003 ; Verhoeven and others, 2006 ) hence constructed wetlands are specifically designed and strategically positioned on the landscape to transform and assimilate excess nutrients by utiliz ing natural biogeochemical processes ( Brix, 1993 ; Solano and others, 2004 ; USEPA, 2000 ; Vymazal, 2005 ) Given c onstructed wetlands specifically created for water quality e nhancement purposes are referred t Constructed treatment wetlands are usually managed to function as buffers to retain or transform excess nutrients and harmful contaminants ( Kadlec and Wallace, 2009 ; Shutes, 2001 ) Surface waters that do not meet water quality standards because of point or nonpoint sources of pollution can be treated by these wetlands ( Babatunde and others, 2008 ; Day and others, 2004 ) In the past two decades, t reatment wet land s ha ve gained considerable popularity as an effective low cost alternative to conventional wastewater treatment approaches ( Table A 1, Appendix A ). Treatment w etlands are mechanically simple, require low energy inputs, and generally have low operation al and

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25 management costs except where cost of land is high since treatment wetlands are often land intensive ( Iovanna and others, 2008 ) Additionally, t reatment wetlands can be designed across a broad realm of operational scale s ranging in size from smaller units capable of treating wastewaters from only a f ew households to large systems covering many hectares and treating high volumes of agricultural or stormwater runoff ( Chen, 2011 ) Treatment wetland s often are design ed based on outflow nutrient (pollutant) target concentration s and operating condition (local climatic conditions ) Various configurations are available to meet desired performance goals efficiency, biotic community and preferred level of intervention ( Brix, 1993 ) T hree major categories of treatment wetlands based on hydraulic flow are: Free water surface (FWS) wetlands: Water flows on the surface and contains areas of open water, just like natural marshes. These w etlands support emergent aquatic vegetation (EAV) and submerged or floating aquatic vegetation (SAV or FAV ; Figure 1 1 ) Horizontal subsurface flow (HSSF) wetlands: Water flows horizontally within the substrate from the inlet to the outlet. The substrate i s usually coarse gravel planted with wetland vegetation. Vertical Flow (VF) wetlands: Water flow is predominantly vertical from the substrate to the overlying water column and the site of treatment is mostly the plant root zone. T his dissertation research is focused on FWS treatment wetlands which are widely popular because of their resilience to adverse climatic factors, and ability to cope with pulse flows and changing water levels ( Kadlec and Wallace, 2009 ) FWS wetla nds resemble natural marshes, with submerged and emergent vegetation communit ies interspersed with patches of open water. These wetlands are commonly used to treat

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26 urban, agricultural and industrial runoff ; however, their use in treating mine waters, leach ate and polluted ground water has also been successfully demonstrated. Biogeochemical Processes W ater quality i mprovement by treatment wetlands is achieved by modification, transformation and storage of excess nutrients and pollutants ( Kadlec and Wallace, 2009 ; Shutes, 2001 ) The main process es that remove contaminants from water include sedimentation, mechan ical filtration, oxidation, reduction, adsorption absorption, precipitation, microbial immobilization, transformation and vegetative uptake. This is possible primarily as a consequence of air soil wate r vegetation the vegetation and mic robial communit ies interact and participate in various biogeochemical processes ( Reddy and DeLaune, 2008 ) The relative rates of these coupled biogeochemical processes vary across time and space, with incidences of intermittent fast reactions 2 and the presence of active action sites ( McClain and others, 2003 ) Wetland s are therefore well suited to transform influent chemicals into pro ducts that could be internally assimilated or exported from the system. Gaseous products (N 2 CH 4 CO 2 H 2 S, NH 3 and N 2 O) are often lost to the atmosphere whereas dissolved forms (NH 4 + PO 4 NO 3 etc.) are immobilized by the microbial or vegetative comm unities ( Reddy and DeLaune, 2008 ; Vymazal, 2007 ) Particulate forms can be exported from the system as a re sult of high hydraulic flow s or can remain trapped in low flow conditions The p hysical settling of suspended organic and inorganic particulates and deposition of plant litter result in the formation of new 2 Biogeochemical hot spots are patches that exhibit disproportionately high reaction rates relative t o the surrounding matrix, whereas hot moments are defined as short periods of time that exhibit disproportionately high reaction rates relative to longer intervening periods.

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27 material at the soil water interface ( DeBusk and Reddy, 1998 ) This newly a ccumulat e d organic layer is composed of both allochthonous and autocthonous m aterial and may represent various stages in the as labile constituents are slowly lost while recalcitrant fractions accumulate over time ( Melillo and others, 1989 ) The res idence time of recalcitrant constituents in accreted soils is often high, and due to this long term storage capability, wetlands are often characterized as nutrient sinks ( Nichols, 1983 ; Reddy and Gale, 1994 ) At the elemental level, c arbon (C) is the primary driver of all the biogeochemical processes in wetlands ( Prairie and Cole, 2009 ; Reddy and DeLaune, 2008 ) and phosphorus ( P ) nitrogen ( N ) and sulphur ( S ) cycling is tightly coupled with organic matter turnover in wetlands ( Reddy and others, 1999a ; Wetzel, 1992 ) Numerous studies have been conducted to understand the scope, scale and associ ated pathways for macro elemental processing in natural and treatment wetlands Some noteworthy examples include carbon ( Alvarez Cobelas and others, 2012 ; Battin and others, 2009 ; Boon and Mitchell, 1995 ) nitrogen ( Bachand and Horne, 2000 ; Lund and others, 2000 ; Spieles and Mitsch, 2000 ) phosphorus ( Fennessy and others, 2008 ; Lund and others, 2001 ; Nairn and Mitsch, 2000 ; Pant and others, 2002 ; Reddy and others, 1999b ; Wang and Mitsch, 2000 ) and sulphur ( Mandernack and others, 2000 ; Morgan and Mandernack, 1996 ; Rudd and others, 1986 ; Spratt and Morgan, 1990 ) These studies have advanced our knowledge to refine design criteria for meeting performance targets in treatment wetlands. Although more than a thousand treatment wetlands are currently operation al throughout the world ( Kadlec and Wallace, 2009 ) active research efforts to optimize performance have been undertaken only on a small proportion of them ( Reddy

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28 and others, 2006 ) This dissertation presents one such effort aimed towards a detailed understanding of the complex processes controlling pollutant removal mechanisms in treatment wetlands. By studying selective wetlands constructed for trapping excess P fr om runoff originating on farms in the Everglades Agricultural Area ( EAA ) an attempt is made to understand key regulators of treatment performance over time, and assess the long term sustainability outlook of those treatment wetlands. T he Everglades histo rically an oligotrophic eco system, experienced an unprecedented input of P as a byproduct of agricultural and urban development during the mid twentieth century ( Richardson, 2010 ) The impacts due to excessive P influx has been widely documented for the greater Everglades ecosystem ( Noe and ot hers, 2001 ; Reddy and others, 2011 ) These impacts include reduced productivity of submerged plants and benthic periphyton, depletion of dissolved oxygen in the water, and changes in invertebrate and v ertebrate community structure ( Crozier and Gawlik, 2002 ; Smith and others, 2009 ) The m ost conspicuous chang e in the Everglades has been the expansion of monotypic stands of cattail ( Typha spp. ) that displac ed the indigenous sawgrass community ( Cladium jamaicense Crantz ) ( Daoust and Childers, 2004 ; Sklar and others, 2005 ; Vaithiyanathan and Richardson, 1999 ) Phosphorus is included in fertilizers and feed s upplements to meet the requirement of agricultural crops and livestock and enable continued higher yields, however unutilized P is susceptible to loss from the agricultural fields or livestock feed lots. Because P in all its various forms i s non volatile, it follows hydrologic pathways and often gets concentrated in wetlands and inland water bodies after being introduced in the environment ( Reddy and others, 1999a ) In the past two decades m uch eff ort has

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29 gone into restoring the Everglades to its original hydrologic flow and ecological condition ( Chimney and Goforth, 2006 ) As a potential remedy, thousands of hectares of artificial treatment wetlands, Stormwater Treatment Areas (STAs), were created to remove excess P from surface runoff before this water reaches the Everglades STAs are actively managed to maintain optimum operational status and meet performance goals mandated by the Everglades Forever Act (EFA) The National Pollutant Discharge Elimination System (NPDES) operating perm its are administered Phosphorus Removal Mechanisms In wetland soils, P predominantly forms complexes within organic matter in peat lands ( Cheesman and others, 20 10 ; Fisher and Reddy, 2010 ) or inorganic sediments in minera l soil wetlands ( Walbridge, 1991 ) Phosphorus occurs as soluble or insoluble organic or inorganic complexes. The relative proportion of each form depends on soil, vegetation and land use characteristics of the drainage basin. The particulate and soluble organic fractions can be further separated into labile and refractory components. Physico chemical tr ansformations convert o rganic and particulate P into biologically available in organic forms which is utilized by micro organisms and vegetation The bioavailable P fraction triggers growth response s in flora and fauna and can caus e a shift from oligotrophic to eutrophic state when P concentrations are sufficiently high It is essent ial that the STAs operate to maximize production and storage of refractory components while minimizing loss of bioavailable P fractions to meet Everglades restoration goals. The relative rates of coupled biogeochemical processes in the STAs regulate long term accretion of P. In general t wo classes of processes biotic and abiotic

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30 mediate these transformations ( Wi thers and Jarvie, 2008 ) Biotic processes include assimilation by vegetation, plankton, periphyton and microorganisms. Abiotic processes includ e sedimentation, adsorption by soils, precipitation, and exchange processes between sediment and the overlying water column. These abiotic and biotic proc esses are detailed in Figure 1 2 with a cross section view of a typical FWS wetland The STAs are representative examples of FWS wetland s In general f our main processes co ntribute to P retention in the STAs so rption to soil solids, sedimentation, co precipitation and biological uptake. M ovements of P on to and off of sites on the surface of soil solids are called adsorption and desorption, respectively. A dsorption/desorption equilibria are reached shortly after there is a change occur in pore water P concentration (e.g. in response to external P inputs) ( Froelich, 1988 ) S olid state diffusion of adsorbed phosphate from the surface into the interior of particles occurs over a longer duration ( Froelich, 1988 ) The s oil water interface controls nutrient concentrations ( Li and o thers, 1972 ; Patrick and Khalid, 1974 ) in overlying waters ( net flux on or off the soil particles ) as governed by the equilibrium phosphorus concentration (EPCo) ( Carritt and Go odgal, 1954 ) In wetlands, the amount of P that can be adsorbed to the soils is often related to the soil iron (Fe) and aluminum (Al) content ( Lijklema, 1976 ) However in the alkaline soils of south Florida, soil calcium (Ca) also is an important determin ant of soil P sorption capacity ( Reddy and others, 1998 ) oil adsorption is not considered a sustainable P removal mechanism because of relatively fast reaction time and the finite sorption capacity of soils for P ( Kadlec, 2009 ; Kadlec and Wallace, 2009 )

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31 The suspended solids influx ( load ) to STAs includes eroded soil particles, macrophyte detritus, and algae or other plankton ic organisms all of w hich contain P ( Stuck and others, 2001 ) The suspended forms settle out due to gravity under reduce flow velocities or by being trapped within the litter layer or adhering to the biofilms ( Schmid and others, 2005 ) Sedimentation of suspended solids can account for a significa nt portion of total P removal by STAs and sustainability is constrained by increase in bottom elevation due to sediment accretion that eventually will prevent surface water flows. P recipitation of P with Ca, Fe, Al and Mg cations re present s an additional pathway of P removal in wetlands ( Reddy and others, 1999b ; Reddy and others, 2005 ) It is not easy to differentiate precipitation from adsorption because precipitates often form on the surfaces of soil particles ( Scinto and Reddy, 2003 ) ; hence this mechanism is referred to as co precipitation Reddy and DeLaune ( 2008 ) provide a thorough discussion on the conditions that promote P co precipitation with available cations and explain the processes that result in the formation of apatite (Ca 5 (Cl)(PO 4 ) 3 ) and hydroxylapatite (C a 5 (OH)(PO 4 ) 3 ) within Everglades soils ( ; Reddy and others, 1993 ) The actual mechanism underlyin g Ca P association may be either adsorption of P onto the surface of CaCO 3 precipitates or the formation of mixed crystals during co precipitation ( Otsuki and Wetzel, 1972 ; Scinto, 1997 ) H igh primary productivity and associated P requirement s make biological uptake an important mechanism contributing to wetland P removal. Plants and microorganisms typically utilize only dissolved P i Prior s tudies have investigated P uptake potential of wetland plants ( Greenway, 2003 ; Reddy and Debusk, 198 5 ; Tanner, 1996 ) and a lgae

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32 and other microorganisms ( Havens and others, 1999 ) Nearly all of the P incorporated into microbial biomass and majority of the macrophyte P is returned to the P cycle through decomposition ( Kadlec and Wallace, 2009 ; Reddy and others, 1995 ) However, reducing conditions in wetlands slow decomposition and over time, result s in organic matter accumulation. The P fraction that is stored in refractory biomass compounds in accrue d sediments contributes to long term sustainable P removal. The conditions supporting and enhancing each of the above mentioned four P removal mechanisms depend on soil characteristics, vegetation type and abundance and water column chemistry, including c ation availability and the distribution of the total P pool among the various functional P forms. Maximizing P treatment in STAs requires an understanding and quantification (and manipulation) of the relative contributions of each of these processes to net P removal. Performance of the ST A s in terms of P removal is assessed by monitoring inflow and outflow water quality parameters on a short time scale ( weekly or bi weekly ) In addition periodic soil and vegetation monitoring is conducted. The lack of deta iled information on P cycling among the active storage compartments (including water column, plant biomass, surface litter and soil) is responsible for the ck approach still used to evaluate the Everglades STAs ( Zurayk and others, 1997 ) In dept h knowledge of key biogeoc hemical processes that regulate continued accrual of organic matter, and promote transformation of reactive P forms into non reactive forms is necessary for designing interventions that will help STA to maintain optimum treatment efficiency and meet mandated performance goals in future. C onsolidation and sophisticated integration of available information is required t o derive critical

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33 understanding that may be useful for long term sustainability of the STAs. By using the STAs as a case example, t his dissertation examin e d the role of wetland vegetation age and soil nutrient storage in regulating P treatment efficiency. This study also explored the relative stability of sequestered P in an attempt to determine long term sustainabilit y of treatment wetlands specifically in response to disturbance s e.g. extreme weather event s or changes in the immediate environment such as pH and redox shifts Site Description The study was conducted in the Everglades STAs, which are located south of Lake Okeechobee i n the state of Florida The c urrent network of six STAs occup ies a pproximately 18 ,000 hectares of land area and provide s an economically feasible means of reducing P inputs to the Everglades Protection Area (EPA) (Figure 1 3 and Figure 1 4 ) A d etailed description of the STA operational history and performance is presented in Appendix B. The STAs are operated and managed by the South Florida Water Management District (SFWMD). This dissertation present s result s of studies conducted in STA 1W, STA 2 and STA 3/4 Dissertation Overview The quality and quantity of sequestered P has immed iate and profound implications for STA treatment performance A complex set of bio geochemical processes control s and regulate s P cycling and dictate s long ter m stability of stored P Transformation of P from reactive pools to non reactive pools within the STAs can be considered a predictor of the long term sustainability of STAs The ultimate goal of this dissertation was to investigat e the fate of sequestered P in relation to the treatment efficiency of the STAs over time.

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34 This study b eg an with the examination of spatio temporal changes in P storages in STA soils and then progressed to develop a novel technique f o r measur ing soil accretion rates in STAs Relati onship between soil accretion rates and operational age of STAs was explored to determine impacts in P removal efficiency with time Phosphorus mass balance s were developed by quantifying P pools in recently accreted soil (RAS) and antecedent pre STA soil to determine allocation of P transferred from the water column to various P storage compartments. Floc and RAS were characterized to identify the relative proportion s of v arious functional P forms to assess treatment efficiency of the STAs Finally, this i nformation was synthesized to provide insights into STA performance over the entire period of operation and assess the long term sustainability outlook for the STAs in the future. Dissertation Objectives and Hypotheses The first objective of this dissertat ion was to r eview available datasets on STA soil physico chemical variables and dete rmine spatio temporal changes in surface and sub surface soil nutr ient storage to e xplore relationship between hydraulic and water quality param eters, soil nutrient storage s and STA age These data were f urther used to p erform preliminary P mass balance. The hypothesis for this objective was that treatment efficiency or P removal efficiency declines after a protracted period of operation (Chapter 2) Objective 2 was to d etermine the soil accretion rate in the STAs by utilizing stratigraphic characteristics of the soil profiles to identify the boundary between recently accreted soil (RAS) and antecedent pre STA soil. The hypothesis behind this objective was that t he STA s are accreting systems and accumulating organic matter conserves attributes of prevailing conditions (e.g. nutrient loading, vegetation community). Changes in these stratigraphic characteristics can be exploited

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35 to identify the depth of RAS deposited on t op of pre STA soil (Chapter 3). Objective 3 was to e xplore the relationship between soil accretion rates and operational age of the STAs and p erform P mass balance using P storages in RAS and pre STA soil and the amount of P removed from the water column. Cycling of P within different P storage compartments of the STAs was also estimated The main h ypothesis for this objective was that m ost of the P retained from the water column is stored in RAS which has a higher P concentration than pre STA soil With increasing age, the rate of soil and P accretion declines, resulting in higher outflow P concentration s Internal re distribution of P within RAS and pre STA soil is mediated by vegetation. This controls whether the STAs function as a nutrient source or si nk (Chapter 4). Determination of the relative proportion of reactive and non reactive P pools in the STAs and a ssess ment of the influence of wetlands vegetation communities (EAV vs. SAV) on reactivity of P pools was the fourth objective, addressed in (Chap ter 5). I expected that differences in the wetland vegetation type s (EAV vs. SAV) will influence the proportion of P forms incorporated in to RAS and sequestered in the STAs. The p resence of more reactive ( i.e., potentially mobil e ) P forms will reduce the l ong term sustainability of the STAs Dissertation Layout The dissertation is organized in 6 chapters. Chapter 1 (this chapter) introduces the main processes occurring in the treatment wetlands, factors critical in controlling long term treatment efficiency and provides an overview of the objectives and rationale behind the dissertation. This is followed by C hapter 2, which presents an analysis of datasets on STA soil physic o chemical variables and spatio temporal changes in surface and sub surface soil nutr ient storages After e xplor ing the relationship s between hydraulic and water quality variables, soil nutrient storage and STA age, a preliminary P

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36 mass balance for STAs was conducted Chapter 3 presents detailed information about a novel change point techn ique (CPT) that was developed to measure soil accretion rates in wetlands. The CPT was used to determine the d epth of recently accreted soil (RAS) in select STAs. Chapter 4 focuses on the s oil and P accretion rates that were determined using RAS depths and operational age of the STAs. The r elationship between a ccretion rates and STA age is also presented Influence of w etland vegetation on accretion rates and P mass balance using RAS depth is also presented to show P cy cling through various P storage compar tments in the STAs. Chapter 5 contains results from the study on c hemical characterization of f unctional P forms in RAS This was performed to determine the relative proportion of reactive and non reactive P storage pools. The r ole of vegetation and other geochemical variables were explored and long term sustainability of STA s was examined Finally, Chapter 6 provides a synthesis of conclusions drawn from all the dissertation studies.

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37 Figure 1 1 Cross section view of e mergent and submerged aquatic veget ation in FWS wetland s Higher water depth enables growth of submerged and f loating a quatic v egetation.

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38 Figure 1 2 Common biogeochemical processes with regard to phosphorus cycling in typical free water surface (FWS) wetland Arrows show direction of m ovement ; size do es not necessarily represent relative mass or volume of processes

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39 Figure 1 3. Map showing the locations of the original six Stormwater Treatment Areas (STAs; in green), the Everglades Agricultural Area and the Everglades Protection Are a in South Florida. Compartments B and C are expansions to the STAs and are indicated in red ( Germain and Pietro, 2011 )

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40 Figure 1 4. C onfiguration of the treatment cells within each Stormwater Treatment Area (STA). The dominant vegetation type in each cell is also indicated ( Germain and Pietro, 2011 )

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41 CHAPTER 2 SPATIO TEMPORAL CHANGES IN SOIL NUTRIENT STORAGE IN THE EVERGLADES STORMWATER TREATMENT AREAS : IMPACT ON PHOSPHORUS REMOVAL PERFORMANCE Background Constructed wetlands exhibit a broad range of biogeochemical and physical characteristics, and are utilized worldwide for enhancing aspects of surfac e water quality ( Brix, 1994 ; Kadlec and Wallace, 2009 ) These artificial ecosystems are designed to reduce th e concentration of water borne contaminants by either transform ing or assimilati ng pollutants. Constructed treatment wetlands are particularly popular for intercepting agricultural drainage waters (ADW) which often contain high concentration s of nutrients such as nitrogen (N) and phosphorus (P). Such is the case with large scale treatment wetlands in south Florida, which were constructed as filtra tion marshes to remove excess n utrients from surface runoff before it enter the Everglades (Figure 1) ( Chimney and Goforth, 2001 ; Goforth, 2001 ; Perry, 2004 ; Redfield, 2000 ) These wetlands are referred to as the Everglades STAs, and are tasked with reduc ing total P (TP) concentrations in surface runoff to ecologically benign levels ( Walker, 1995 ) The strategic location of the STAs has allowed them to retain over 1,450 metric tons of P which has resul ted in a considerable load reduction of P to the Everglades STA o utflow total P flow weighted mean concentrations (FWMC) were reduced from 152 g P L 1 to 38 g P L 1 during the period from 1994 to 2011 ( Ivanoff and others, 2012 ) High P loads in an oligotrophic system are known to cause a shift in the biotic communit ies by disrupting natural n utrient characteristics and can ultimately lead to eutrophic or hyper eutrophic conditions ( Khan and A nsari, 2005 )

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42 Following excessive P inputs, the northern Everglades ecosystem has exhibit ed signs of widespread impaired ecosystem function, including extensive growth of Typha spp. (cattail) in place of the natural inhabitant Cladium jamaicense (sawgra ss) ( Hagerthey and others, 2008 ; Vaithiyanathan and Richardson, 1999 ) To counter these undesirab le changes the Comprehensive Everglades Restoration Plan (CERP) was developed with a goal to restore, protect and preserve the remaining Everglades ecosystem ( USACE and SFWMD, 2000 ) The CERP is b roadly aimed at improving quality, quantity, timing and flow of water for both ecological integrity and human needs in south Florida. A major component of this plan water quality improvement, includes reduction of P inputs by implementing best management practices (BMPs) in the EAA ( Diaz and others, 2005 ; Izuno and Capone, 199 5 ; Rice and others, 2002 ) and subsequent treatment of ADW that leave s the EAA. T reatment is carried out by intercepting ADW in the STAs where biogeochemical processes remove P from the water column ( DeBusk and others, 2001a ; Gu and others, 2001 ; Nungesser and Chimney, 2001 ) The first full scale treatment wetland in south Florida, known as the Everglades Nutrient Removal Project (ENRP) became operational in 1994 ( Ch imney and others, 2006 ; Guardo and others, 1995 ) Subsequent expansion of the ENRP and addition of total footprint of approximately 18,000 ha of effective treatment ar ea ( Ivanoff and others, 2012 ) Although the STAs have sequestered a substantial amount of P during their operational history, they are known to exhibit variable treatment performance in terms of P removal efficiency over time ( Pietro and others, 2008 ) T h e spatio temporal variability in STA t reatment performance has been

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43 attributed to factors such as antecedent land use, vegetation condition and species composition nutrient and hydraulic loading, hydraulic residence time, hydroperiod, soil characteristics and P content cell topography and co nfiguration extreme weather events construction activities and regional operations ( Germain and Pietro, 2011 ) A s tudy conducted on 49 treatment wetlands found that T P removal was more a function of mean hydraulic residence time than mean hydraulic loading rate ( Carleton and others, 2001 ) However, a broader overview of P removal performance across a range of FWS wetlands suggested that background concentrations, P loading rates (PLR) temperature and season al effects and ecological variables such as water depth and vege tation type and cover etc. are the main controlling factors (for details see Chapter 10 Kadlec and Wallace, (2009 ) ). This review also recognized constraints in P processing when low outflow concentrations are required which highlights the challenges experienced by the Everglades STAs where outflow TP FWMCs are currently mandated to be in the 1 3 19 g P L 1 range. A thorough examination of 21 variables including inflow T P concentration, hydraulic and T P loading rates, T P fractions, calcium (Ca) and pH did not yeild a single variable that ha s gr eate st influence in controlling T P concentration or T P areal settling rate in STAs ( Jerauld, 2010 ) This study however emphasized t he importance of background soil P concentration and also showed an inverse relationshi p between STA age s and outflow T P concentrations ( Jerauld, 2010 ) STA age could be a key factor in det ermining STA performance because it is a lumped term that represents multiple wetland characteristics that change over time, such as soil P and plant biomass and tissue P concentrations Further information on key factors affecting performance of

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44 treatment wetlands in general and the STAs in particular are presented in Chapter 1 as a review of published literature ( Carleton and others, 200 1 ; Carleton and others, 2000 ; Carleton and Montas, 2010 ; Chimney and Pietro, 2006 ; Dierberg and others, 2002a ; Dierberg and others, 2005 ; Fisher and Reddy, 2010 ; Gu and others, 2001 ; Gu, 2006 ; Gu, 2008 ; Ivanoff and others, 2012 ; Juston and DeBusk, 2006 ; Juston and DeBusk, 2011 ; Kadlec, 1997 ; Kadlec, 1999 ; Kadlec, 2005 ; Kadlec and Hammer, 1988 ; Kadlec and Wallace, 2009 ; Luderitz and Gerlach, 2002 ; Martin and Anderson, 2007 ; McCormick and Odell, 1996 ; Moustafa and others, 1996 ; Nouri and others, 2010 ; Nungesser and Chimney, 2001 ; Pietro and others, 2006 ; Reddy and others, 1999a ; Richardson, 1985 ; Richardson and Qian, 1999 ; Walker and Kadlec, 2011 ) Juston and DeBusk, (2006 ) explored relationships between mass loading of P and subsequent outflow concentrations within the STAs and compared them with seven other treatment we tlands in Florida. Their analysis of historic data concluded that a long term average annual PLR at or below 1.3 g m 2 yr 1 is conducive to outflow TP concentrations less than ~ 30 g P L 1 irrespective of vegetation type ( Juston and DeBusk, 2006 ) An extensive study of the Everglades STAs for the entire period of operation (1994 2011) found a significant positive correlation between PLR and outflow T P conce ntration with dramatic increases in outflow concentrations from STAs when PLR was greater than 1.0 g m 2 yr 1 ( Ivanoff and others, 2012 ) This analysis also elucidated differences in vegetative response to PLR, with a substantially greater increase in outflow TP co ncentration in EAV cells in comparison to SAV cells at PLRs greater than 1.0 g m 2 yr 1 ( Ivanoff and others, 2012 ) However, EAV cells are typically

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45 situated in the front end of STA flow ways, which experience higher inflow TP concentrations, w hich may affect outflow TP concentrations. Performance of the STAs for regulatory compliance is quantified by measuring hydrologic parameters i.e. volume and chemical characteristics of inflow and outflow waters to and from STAs. This approach overlooks t he complex biogeochemical processes that regulate P removal from the water column and control s the stability of sequestered P pools in the STAs. With continued STA operation, P removed from the water column accumulates as recently accreted organic soil and contributes to the incremental enrichment of the surficial layer of soil potentially leading to the saturation of internal P storage compartments ( Lowe and Keenan, 1997 ) Recently accreted soils (RAS) share an active interface with floc (unconsolidated detritus that is deposited on the consolidate d wetland surface layer) and the overlying water column and depending on the existing biogeochemical factors nutrient concentrations in the RAS layer could potential ly influence STA TP outflows ( White and others, 2006 ) Therefore, an understanding of the complex processes that regulate long term sustainable P removal in the STAs is desired for effective management and for meeting Everglades restoration goals. An assessment and characterization of nutrient storages in STA soils could be the first step towards dismantling the black box like approach ( Zurayk and others, 1997 ) used to evaluate treatment wetland function Investigation of changes in soil P storages over temporal and spatial scale s could provide meaningful insights into STA performance and P removal efficiency over time. Objective s and Hypotheses The main objective of this study wa s to r eview available datasets on STA soil physico chemical parameters and dete rmine spatio temporal changes in surface and

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46 sub surface soil nutrient storages Subsequently, relationship s between hydraulic and water quality param eters, soil nutrient storage and STA age w ere investigat ed to explore t he trajectory of T P removal efficiency in aging STAs. A preliminary T P mass balance was performed to understand where the bulk of retained P was distributed within the STA soil profile. These objectives were supported by the hypothesis that TP removal efficiency of STA declines afte r a continued period of operation. In addition internal redistrib ution of P within soil profiles, mediated by vegetation controls overall P removal efficiency of STAs. Methods A comprehensive review of existing information on STA soil nutrient storage wa s conducted to document changes in soil nutrient status over time and to explore relat ionships between soil P storage and T P retained from the water column. Surface soil P storages in all six STAs were compared to explore the effect of STA age on T P remova l rates. Phosphorus distribution within various compartments of STAs water column, floc, surface soils (0 10 cm), and sub surface soils (below 10 cm) was determined. Temporal changes in P storage wit hin these compartments was used to generate estimates o f P flux, which was then used to develop overall T P mass balance s for the STAs Site Description The Everglades STAs have a combined surface area of approximately 26,300 ha, with about 18,000 ha of effective treatment area ( Ivanoff and others, 2012 ) T his area is distributed among six STAs, each of which is compris ed of multiple, independently managed units called cells ( Figure 1 4 ) Each cell is actively managed to have on e dominant vegetation community depending on the intended treatment

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47 objectives. The two broad categories of vegetation are emergent aquatic vegetation (EAV) and submerged aquatic vegetation (SAV) [SAV cells also contain floating aquatic vegetation (FAV) sp ecies] The South Florida Water Management District (SFWMD) is responsible for operating, maintaining and optimizing the performance of all the STAs to ensure compliance with operating permits The six operational STAs include: STA 1E and STA 1W, STA 2, ST A 3/4, STA 5, and STA 6. A det ailed description of STAs and associated T P removal is presented in Table B 3 ( Appendix B). Data Sources Data used in this study were obtained from the SFWMD and the Wetland Biogeochemistry Lab (WBL) University of Florida. D etailed information regarding operations and management of STAs was obtained from South Florida Environment Reports (SFERs) ( Chimney and others, 2000 ; Germain and Pietro, 2011 ; Ivanoff and others, 2012 ; Pietro and others, 2010 ) Data used for this analy sis represented 495 floc samples and 1700 soil samples spanning the entire period of record (POR) for all STAs up to water year ( WY ) 2008 [ Each WY runs from May 1 through April 30 of the following calendar year] Sampling dates indicated that STA soils wer e collected approximately every three years from WY 2004 through WY2008; however the earliest data from WY1994 was obtained from STA 1W Floc depth was variable across sample sites S oil cores were divided into two sections surface soils (0 10 cm) and su b surface soil (10 30 cm). F loc and soil dataset used for analysis contained physico chemical information such as bulk densi ty, ash free dry weight (AFDW) organic matter content (loss on ignition ; LOI ), pH, iron (Fe) Ca sulfur (S) total carbon ( T C), T P and total nitrogen ( T N).

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48 Using bulk density, core depth and soil nutrient concentrations, P C and N storage within floc, surface soils and sub surface soils was determined N utrient storage was not calculated where floc depth, bulk density or nutrient co ncentration data was missing Soil Nutrient Mass Storage s Total nutrients ( C, N and P ) storage in floc (variable depth) and soils ( 0 10 and 10 30 cm ) were calculated Mean floc depth for each sampling event was used for calculating P, N and C storage in th e floc fraction while a depth of 10 cm was universally used for surface soil storage calculation s Nutrient storage per unit area (g m 2 ) for both floc and soil layers was calculated as follows: F X S = ( C X D fb d f ) /100 2 1) S X S = ( C X Ds b d s )/100 2 2) w here F X S = Floc nutrient (X) storage (g m 2 ) S X S = Soil nutrient storage (g m 2 ) X = Nutrient X (carbon, nitrogen or phosphorus) C = Nutrient concentration (mg kg 1 ) D fb = Bulk density of floc (g m 3 ) D sb = Bulk density of soil (g m 3 ) d f = Depth of floc ( cm ) d s = Depth of soil ( cm ) Relationships between T P retained by the STAs and P mass storage (g P m 2 ) in floc and the top 10 cm surface soils were explored. T he effect of STAs age on floc and soil P mass storage was examined for all STAs Relationships between T P areal storage in the STAs and concomitant C and N mass storage was also explored. Phosphorus Mass Balance Mass balances can be calculated with varying degrees of complexity either considering only the mass of P that entered but did not leave a wetland (by subtraction of outflow from inflow data) ( Boyt and others, 1977 ; Sloey and others, 1978 ) or, through

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49 quantification of P flux, across various compartments within the wetland (soil and biomass) and finally P storage in soils ( Dolan and others, 1981 ; Fetter and others, 1978 ; Headley and others, 2003 ; Lee and others, 2012 ) Even simple P mass balances are useful in determining the sources of P to the wetland (surface water, groundwater, preci pitation) and for calculating gross P removal effectiveness ( Bhadha and others, 2011 ; Chung and others, 2008 ) increasingly difficult to assemble owing to sample collection and processing challenges ( Correll, 1998 ) but may aid in illuminating internal processes that could be useful to the understand fate of r etained nutrients by the STAs. Phosphorus mass balances performed as a part of this study utilized an approach with somewhat greater level of complexity involving cumulative TP retained from the water column (P Wc ; g P m 2 ) by STAs over their POR (up throu gh WY2008) and corresponding changes in areal P mass storage (g P m 2 ) in floc and the top 10 cm of surface soil (Figure 2 1). The difference between floc P storage (FPS; g P m 2 ) and P Wc indicate d net movement of P within floc and surface soil layer and was represented as P flux F The sign of P flux F enrichment ( movement ) with +ve P flux F signifying flux from the underlying surface soil layer into the floc layer. Conversely, FPS smaller than P Wc indicate d net mo vement of P down into the surface soil (P flux F ; ve ), this would be the case when floc gets consolidated and transformed into soil. T he earliest ava ilable soil P storage (SPS; g P m 2 ) for the top 10 cm of surface soil was used as background P (P BG ) and w as subtracted from WY2007 SPS. A net positive change indicated P enrichment of the surface horizon either from the floc above (P flux F ; ve) or from the subsurface soil below (P flux SS ; +ve ; Figure 2 1) Soil P storage in

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50 WY1995 was used as the background (P BG ) for STA 1W while SPS in WY2005 was taken as background for both STA 1E and STA 3/4. S oil PS in WY2001 was used as background for STA 2, STA 5 and STA 6. The arrows in Fig. 2 1 indicate the direction of P flux (g P m 2 ) from one storage compartment to another. For all practical purposes, soils represent the only long term nutrient storage pool in wetlands while nutrients in live vegetation serve only as a temporary transient pool ( Howard Williams, 1985 ) hence P present in vegetation was not considered for T P mass balance calculations. C ritical assumptions made for developing T P mass balance s for the STAs are listed below : T he total mass of T P retained from the water column ( P Wc) initially resides as floc therefore floc P storage (FPS ) at any given time reflects the fraction of T P incorporated from the water column as well as contribution from vegetative detrital matter (physical se ttlement of particulate forms, adsorption absorption of soluble forms, biological immobilization by microbial communities) Floc P contributed by vegetative detrital matter deposition may represent a fraction that could be obtained from underlying soils by rooted plants (EAV) or directly from the water column by submerged and floating plants (SAV/FAV) For comparisons at STA level, both EAV and SAV /FAV cells within one STA were averaged to obtain FPS for that STA. Floc becomes soil over time, so with a long observation period some of the water column TP have passed through the floc and into the surface soil. Flux of P from underlying soil ( P flux SS ) to overlying soil or floc i s regulated by redox conditions and the equilibrium P concentration (EPCo). Phosph orus in live vegetation biomass at a given time (i.e., plant standing stock) accounts for only a tiny fraction of T P in the STAs and represents a transient pool which ultimately gets transformed into floc and soil after plant senescence following the deca y continuum pathway. Data Analysis All calculations and comparison of nutrient storage pools were performed using Excel Nutrient mass storages were not calculated if floc depth, bulk density

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51 measurements or nutrient concentrations were unavailable. Total P storage in analys e s represented floc and 0 10 cm soil P storages. Area weighted mean values were used to determine nutrient storages within each STA cell, which were then added together to provide total storage for the whole STA in a given year. Relation ships within nutrient mass storages in STA soils, and between STA age and soil and floc P storages were explored using Excel spreadsheet regression models. Results P hysi c o Chemical P roperties Among all STAs, floc and soil bulk density were highest in STA 1 E suggesting these is much higher mineral fraction in the surface soils ( Table 2 1 ) Floc bulk density ranged from 0.04 to 0.26 g cm 3 whereas soil bulk density varied from 0.2 to 1.0 g cm 3 across all STAs for all sampling events. The range of mean floc depth (cm) across STAs was higher in WY2004 than in WY2007 ( Table 2 2) Floc depth decreased in STA 1W and STA 5 whereas it increased in STA 2 during this period. Phosphorus F loc and soil P concentration s (mg P kg 1 ) showed an increase from WY2004 to WY20 07 (Table 2 3). Floc P concentration was lowest in STA 2 whereas it was highest in STA 1W The r ange of soil P concentration was lowest in STA 1E and highest in STA 5. F loc and soil P storage in STAs is presented in Table 2 4 In WY2007, STA 5 surface soi ls (0 10 cm) had highest P storage. Caution should be exercised in comparing SPS in the 0 10 cm depth surface soil across STAs. In older STAs such as STA 1W, most of the 0 10 cm soil represents consolidated floc and only some antecedent pre STA soil. How ever, i n younger STAs, much of the 0 10 cm soil depth may represent pre STA soil with only a small fraction

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52 derived from consolidat ion of floc. Therefore comparing P storage in the top 10 cm of surface soil across different STAs will represent dissimilar c ontributions from floc and pre STA soil depending on the operational age of STA, and the rate of soil accretion. The percentage of T P (floc + soil) derived from water column operational history is plotted in Figure 2 2. As the STAs a ged the percentage of T P storage derived from water column increased (r 2 =0.86) However, n o clear relationship (r 2 =0.20) was observed between the mass of T P removed from the water column and T P storage in WY2007 (Figure 2 3). The one to one line in Figure 2 3 differentiates between the proportion of T P in floc + soil derived from pre STA soil and T P transferred from the water column. This indicated increasing proportion of TP in surface soils because of net P retention from overlying water column with incr A comparison of T P retained from the water column during the operational history of STAs and the amount stored in floc and soil is presented in Table 2 5. There was no relationship when P storage was regressed against T P retained from th e water column for all STAs each water year (Figure 2 4). Similarly, no relationship was obtained when cell averages were analyzed instead of whole STAs ( Figure 2 5 ). Additionally, when floc P concentrations (Figure 2 6) and floc P storages (Figure 2 7) we re regressed against inflow T P flow L 1 ) no relationship was observed at the c ell level. Nitrogen Total N concentration s (mg N kg 1 ) across STAs are shown in Table B 1 ( Appendix B ) while FNS and S N S are shown in T able 2 6. In most cases SNS increased over time except for a slight decrease in STA 1W during WY200 8 This decrease may have result ed from rehabilitation activities which involved remov ing most

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53 of the surface soil A similar dip in SPS was observed for STA 1 W in WY2008, supporting the assertion above. Soil N and P storage for WY2007 showed a positive linear relationship ( r 2 = 0 .67; Figure 2 8 ) This suggest ed that P was stored primarily in organic form with a pproximately 3 1 to 54 g N per g of P stored per m 2 in the STAs High N :P ratios suggest ed that STA soils were P limited Carbon The c oncentration of C (g C kg 1 ) in floc and soil is presented in Table B 2 ( Appendix B ) whereas carbon storages are shown in Table 2 7 Soil P S and soil C storage for WY2007 sh owed a p ositive linear r elationship ( r 2 = 0 .66; Figure 2 8 ) The range of C st ored in STAs varied from 470 to 820 g C per g of P stored per m 2 in the STAs Total mass of N and C (mt) stored in floc and surface (0 10 cm) soil is presented in Table 2 8. Mass B alance The outcomes of T P mass balance s for five STAs are presented in Figure 2 9 with calculated P storages and flux es between STA P storage compartments (STA 1E was not included in this calculation because of unavailability of floc data for WY2007) All STAs showed a net positive retention of T P from water column. Soil PS showed positive change s i n STA 1W, STA 5 and STA 6 whereas STA 2 and STA 3/4 showed a negative change in SPS in comparison to the background P storage Th e negative change s in SPS were i nterpreted as a redistribution of P in to the floc or subsurface soils (below 10 cm). STA 1W and STA 3/4 were considered functioning favorably for long term P storage as calculations s uggested flux of P into sub surface soils downwards

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54 from surface soils. F or the other STAs, net P flux from sub surface soil to floc and surface soil was observed. Discussion Wetland s, in general, accumulate organic matter because of production of detrital material from biota (predominantly vegetation) and suppressed rates of decomposition ( Reddy and others, 1993 ; Rogers, 1983 ) A ccreting organic matter forms the largest sink for i nfluent nutrients, particularly for P of which up to ~80% is stored in soils ( Faulkner and Richardson, 1989 ; Kadlec, 2009 ; Reddy and others, 1999a ) relative to other ecosystem components such as plant biomass and plant litter ( Heliotis and DeWitt, 1983 ) In the Everglades STAs, l ong term sustainability lies in consistently maintaining conditions that are favorable for converting influent reactive P forms into non bioa vailable (non reactive) forms M onitoring and permit compliance of STA performance require quantification of T P load reductions by measuring hydrologic parameters i.e. volume and chemical characteristics of inflow and outflow waters. P erformance determi ned in this fashion provide only limited information such that higher than expected outflow P concentrations only serve as an indicator of a problem without providing insight into the underlying causal processes. Such information serves little purpose if the goal is to enhance treatment performance or to forecast future treatment capabilities The assessment and characterization of stored nutrient s (P) therefore provide s basic information for maintaining long term nutrient removal effectiveness of treatmen t wetlands in general and that of the STAs specifically Examining the changes in P pools in floc, surface soil and sub surface soil s is a first step in that direction, specifically because nutrient concentration s in floc and soils have the potential to in fluence the

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55 overlying water column concentration depending on existing biogeochemical factors ( White and others, 2006 ) Phosphorus Retention Phosphorus retention in treatment wetlands is mediated by both short term ( Kadlec, 1997 ; Kadlec, 2005 ; Reddy and others, 1995 ) and long term P removal pathways ( Kadlec, 2009 ; Reddy and others, 1999a ) which are regulated by the existing biogeochemical conditions Although removal of P from the water column may appear to be a rapid phenomenon formation of stable storage compounds, which are less readily released into solution can only be achieved after a considerable period ( Hamad and others, 1992 ) This time allows P to diffuse into the soil matrix (an irreversible process with finite capacity) or be incorporated into vegetation (biota) an d form refractory organic compounds (infinite capacity). The p resence of Ca and Mg in alkaline soils ( Moore and others, 1998 ) and Fe and Al in aci dic soils ( Lijklema, 1976 ) influence s formation of stable P minerals whereas uptake by veget ation (and other biota) eventually leads to the production of relatively stable organic P forms. In the former scenario the quantity of available minerals which is often finite constrains unlimited production of stable P mineral forms O n the other hand formation of stable organic P through v egetation uptake and biomass growth could continue indefinitely as long as favorable conditions are maintained. Therefore accretion of organic matter as new soil in wetlands provides the long term sustainable pathw ay for P removal. Analysis of physico chemical attributes of STA soils allowed investigation of temporal changes in nutrient storage and examination of relatio nships between nutrient storage changes with respect to STA performance and operational age The STAs exhibited considerable variability for stored P in floc and surface soils. One possible

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56 reason for this variability could be differences in the periodic cycle of drying and rewetting experienced by each STA. During summer months when STAs experience dry co nditions, organic soils oxidized and P may have been lost on soil rewetting ( Fisher and Reddy, 2001 ; Ne wman and Pietro, 2001 ; Olila and others, 1997 ) Thus drying and re wetting could play a key role in redistribution of P within the STAs as the release d P is assimilated by downstream biological communi ties. This downstream movement of P as an enrichment front has been observed in Water Conservation Area 2A with a zone of greater P impact closer to the inflows ( D eBusk and others, 2001b ; Debusk and others, 1994 ; Koch and Reddy, 1992 ) T he large size of the STAs and elongated water flow paths are amenable to es tablishment of a similar longitudinal gradient in P stored in the water column, vegetation and soils ( Walker, 1995 ) Such internal re distribution and longitudinal P gradient s along with enrichment of surface soil s from continuous extern al loading could be another reason for the variability in P storage in STA soils. Absence of a clear relationship between inflow T P loads and floc and soil P storages (Figure s 2 4 to 2 8) could be a consequence of the following reasons : first, insufficien t information on soils (limited data points) to capture inherent spatial variability ; s econd, water column data represented T P retained only in that particular water year whereas P measurements in the case of floc and soils were cumulative for the POR; t h ird, the proportion of P in the vegetation and biota was not accounted for in these relationships and fourth, error in measurement of nutrients in soils and the water column could have mask ed any small relationship that may exist. These reasons only provid e a partial explanation for the observed lack of relationship while there could be many other factors that are sufficiently complex to resolve at STA or individual cell

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57 scales For example : a ) S oils data may not be tru ly representative of the entire STA, b ) There have been difference s in vegetation coverage across cells over the POR and insufficient information about the role of plants in P redistribution along soil profile c ) There have been variability in hydraulic residence times and dynamic range of P loading rates (PLR) and, d ) There is inherent heterogeneity in STA soils and impacts from extreme weather events such as drying, flooding and hurricanes. The scope of current analysis did not allow examination of each of these individual factors in detai l. The analysis however did provide a clear indication that the soil P proportion derived from the water column increased with time (Figure s 2 2 and 2 3) Phosphorus Mass Balance Long term sustainability and efficiency of STA operations is contingent on un derstanding the spatial distribution and accurate quantification of P storage pools in the STAs. The fate of accreted P is influenced by its association with reactive organic substrates and factors controlling its potential mobilization. The change in SPS from pre STA P levels was manifested as redistribution of P in to either the floc or subsurface soils (below 10 cm). These changes were examined by developing P mass balances for the STAs. Comparison of STAs with varying operational age indicated that STA s urface soils for STAs up to 8 years of age function as a source for P (upward P flux F ) whereas surface soils for STA with longer operation age function as a net sink for P (downward P flux F ; Figure 2 9) However, s ince no STA has experienced a net export of P at its outflow, they have been functioning as a net sink for P removal. In STA 1W, after 13 years of operation, net downward P flux from floc layer to the surface soil and into the underlying sub surface soils was inferred from mass balance calculati ons. This result

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58 could be an artifact of using a fixed soil core depth (top 10 cm) for mass balance calculations without taking into account the actual depth of RAS, which accumulated after the STA became operational. In the absence of an actual bounda ry b etween RAS and pre STA soil an accurate mass balance calculation and determination of precise movement of P within the soil profile is not possible. However, this mass balance approach provides a preliminary understanding of the distribution of P retained from the water column within STA soil profile across the three major compartments floc, surf ace soil and sub surface soil. Some STAs experienced a drastic increase in their surface soil P storage relative to the background levels (P BG ). These increases could not be fully accounted for by TP retained from the water column, suggesting an alternate pathway of P movement from surface soils to floc via vegetation. In such cases, the role of vegetation in mining and redistributing sub surface P from organic so ils to the surface becomes highly important. Results from this study agree with mesocosm experiments conducted with TP surface water concentrations (<100 g L 1 ), which demonstrated that emergent macrophytes mined over 50% of their total P requirements fro m the underlying peat soil ( White and others, 2006 ; White and others, 2004 ) The P mass balances in this stud y also highlighted the need to identify accurately the boundary between RAS and pre STA soil, to enable more robust P storage calculations and determination of soil and P accretion rates in the STAs. Impact of STA Age on Phosphorus Retention The s uccess o f Everglades restoration depend s on sustainable P removal from surface runoff and continued sequestration of P in non reactive forms within accreting soils of the STAs. Design of the original six Everglades STAs was based on steady

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59 state model calibrations involving a constant areal rate of P removal dependent on inflow P concentration ( Kadlec, 1997 ; Kadlec, 2005 ; Walker, 1995 ) It was assumed that accumulation of refractory stable P forms would continue at a steady rate after an initial brief stabilization period in each STA. However, the STAs experienced a decline in annual floc and surface soil P accretion rates as the system s aged (Figure s 2 10 and 2 1 1 ) suggesting that smaller annual increments of P were stored in the floc and soil layer over time Alternatively, in younger STAs, most of the 0 10 cm soil depth may have been native soil with only a smal l fraction of consolidated floc whereas in older STAs most of the 0 10 cm soil represent ed consolidated floc and very little native soil (Figure s 2 2 and 2 3). The declining trend in annual P accretion with S TA age may indicate exhaustion of localized sites for P adsorption in the soil matrix and saturation of existing demands by vegetation and luxury uptake by microbial communities ( Carleton and others, 2001 ) It is also pos sible that the PLR in the STAs over their operational history exceeded ( Qian and Richardson, 1997 ; Richardson and Qian, 1999 ) This could have resulted in loss of P from STA soils, which was subsequently observed as a declining trend in P accretion over time. While it is hard to determine if the maximum potential for P uptake by biotic communities has been reached, a comparison of soil P storages using long term data analysis over the period of each s that a constant measure of refractory organic P was not uniformly accreted over the en tire course of STA operatio n. This observation could however be an artifact of the sampling design, where soil samples represented only the top 10 cm of nutrient storage and miss ed a portion of

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60 accreted P in cases when the RAS depth was greater than 10 cm. In the absence of fix ed soil reference point s a valid conclusion cannot be drawn unless a clear boundary between RAS and pre STA soil is known. With the current soil data it was not possible to distinguish between native soil and consolidated floc. The amount of error in SPS ca lculation changed with STA age as the boundary of the 0 10 cm surface soil shifted with new soil accretion. Soil P storage calculations only reflect ed the top 10 cm of soil possibly underestimating the total accretion of nutrients over the POR in cases of old STAs where RAS depth exceeded 10 cm The observed decrease in SPS in some STAs could therefore represent upward shifting of the 10 cm boundary in the soil layer. Over time as more detrital material was consolidated and incorporated as soil, the top 1 0 cm layer account ed for more and more of the newly accreted material while the pro portion of the 0 10 cm soil fraction composed of pre STA soil in pre vious cores was reduced Since SPS was calculated only from the top 0 10 cm soil layer this could have r esulted in overall underestimation of total accreted P since the inception of a STA and eventually being perceived as a declining trend in P accretion. Summary The Everglades STAs are unique because of their large size and low target outflow T P concentra tions ( 13 19 1 ). The general range of inflow P concentrations in many other treatment wetlands are 1 2 orders of magnitude greater than the STAs. The large expanse of STAs, past land use ( agricultural farm or historic wetland), extreme weather events (e.g., drought s storms), and suspension of operations due to nesting of migratory water fowl species, are only a few examples of the complex challenges experienced during the management of the STAs. The s tatus of S TA

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61 operational phases (start up, routine operation, or recov ery) and management activities (e.g., drawdown, cell rehabilitation vegetation conversion and control) also influence outflow P concentrations from the STAs. Each of these factor s ha s some bearing o n the overall treatment performance o f the STAs, and detailed understanding of the fate and transformation of sequestered P in STA soils may help adaptive management to optimize STA efficiency. The results presented in C hapter 1 (this chapter) set the stage for subsequent forays in to enhancin g our understanding of P processing in wetlands by using the STAs as a case example. The n ext chapter presents details on development of a simple technique for identifying the bounda ry between RAS and pre STA soil by utilizing stratigraphic properties of s oils that were formed after startup of the STAs.

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62 Table 2 1. B ulk density (g cm 3 ; mean SD) for f loc and soil samples from the STAs. Total number of samples is presented in parenthes e s WY STA 1E STA 1W STA 2 STA 3/4 STA 5 STA 6 Floc 2003 ----0.06 0.06 (58) -2004 -0.08 0.04 (88) 0.1 0 0.08 (70) -0.08 0.06 (104) 0.04 0.03 (22) 2007 0.26 0(1) 0.06 0.07 (47) 0.15 0.04(62) 0.11 0.04 (28) 0.11 0.03 (15) -Soil 1995 -0.18 0.0 6(36) ----1996 -0.2 0 0.06 (23) ----2000 -0.26 0.06 (31) ----2001 --0.21 0.08(10) -0.34 0.14 (10) 0.52 0.17 (10) 2003 ----0.50 0.25 (59) -2004 -0.22 0.06 (89) 0.23 0.06(74) -0.47 0.24 (108) 0.58 0.24 (31) 2005 1.07 0.44(94) --0.34 0.1 (323) --2006 -0.24 0.05 (28) ----2007 1.01 0.37(103) 0.26 0.09(133) 0.25 0.08(115) 0.27 0.1 (289) 0.34 0.15 (82) -2008 -0.23 0.05 (52) ----

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63 Table 2 2 Mean floc depth across the STAs (cm; mean SD) for sampling years. WY STA 1E STA 1W STA 2 STA 3/4 STA 5 STA 6 2003 ----6.8 2.7 -2004 -18.2 7.3 5.2 2.4 -9.0 4.0 7.8 3.1 2007 9.0 0 # 4 4 2.3 7.1 3.6 7.3 3.8 5.1 2.7 -# STA 1E: Only o ne floc sample wa s recorded STA 1W: M ean floc depth was calculated by using available data from Cells 2, 4 and 5B only Table 2 3. Total p hosphorus concentration in floc and soils in the STAs (mg P kg 1 ; mean SD). WY STA 1E STA 1W STA 2 STA 3/4 STA 5 STA 6 Flo c 2003 ----1180 444 -2004 -726 272 856 339 -824 325 1028 520 2007 644 0* 1192 261 870 167 1072 130 1187 485 -Soil 1995 -479 130 ----1996 -353 96 ----2000 -507 194 ----2001 --521 157 -465 74 236 103 2003 ----465 197 -2004 -272 77 506 133 -445 139 455 236 2005 177 136 --688 187 --2006 -452 188 ----2007 160 135 598 316 511 186 599 175 615 396 -2008 -500 226 ----* STA 1E: Only one floc sample was recorded

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64 Table 2 4 Total p hosphorus areal storage in floc and soils in the STAs (g P m 2 ; mean SD). Values represent entire floc depth and top 10 cm of surface soil. WY STA 1E STA 1W STA 2 STA 3/ 4 STA 5 STA 6 Floc 2003 ----3.3 1.7 -2004 -9.6 4.8 2.8 2.1 -4.4 2.3 3.2 2 .7 2007 15.1 0* 4.4 1.6 8.7 4.9 8.5 4.6 6.7 3.1 -Soil 1995 -7.7 1.5 ----1996 -3.5 1.1 ----2000 -6.9 3 ---2001 --12.7 5.6 -15.2 2.9 10.8 2.4 2003 ----19.1 9.6 -2004 -5.8 2.6 12.2 8.2 -18.9 8.0 23.3 11.8 2005 13.2 7.8 --23.3 8.5 --2006 -11.3 6.1 ----2007 10.1 6.2 14.6 5.9 12.5 6 1 6.1 6.7 20.7 13.7 -2008 -10.7 4.7 ----* STA 1E: Only one floc sample was recorded Table 2 5 Comparison of total p hosphorus removed from the water column and floc phosphorus storage and soil phosphorus storage. STA a rea used for calcul ations is shown. Water Year Age (yr) STA area ( h a) FPS (g P m 2 ) SPS (g P m 2 ) P storage (g P m 2 ) Total P in STA (mt) Phosphorus removed from water*(mt) STA 1E 2007 3 2073 -10.10 10.1 209 24 STA 3/4 2007 4 6683 8.50 16.10 24.6 1644 222 STA 6 2004 6 912 3.16 23.29 26.5 241 25 STA 2 2007 8 3329 8.70 12.50 21.2 706 181 STA 5 2007 8 2462 6.70 20.70 27.4 675 158 STA 1W 2007 13 2695 4.40 14.70 19.1 515 339 Data source: Pietro and others, (2008 ) Table 5 2 for all STAs except STA 6; f or STA 6 SFER 2005 Table 4 1 ( Goforth and others, 2005 )

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65 Table 2 6. Total n itrogen areal storage in floc and soils in the STAs (g N m 2 ; mean SD). Values represent entire floc depth and top 10 cm of surface soil. WY STA 1E STA 1W STA 2 STA 3/4 STA 5 STA 6 Floc 2003 ----96 61 -2007 -92 43 125 66 139 72 170 79 -Soil 1995 -478 122 ----1996 -637 133 ----2000 -770 163 ----2001 --605 89 -809 100 623 172 2003 ----8 65 193 -2004 -622 145 609 117 -877 203 1029 353 2005 345 246 --832 179 --2006 -646 123 ----2007 312 141 792 159 642 123 646 178 689 223 -2008 -622 115 ----* Total nitrogen concentration f or floc was not available for STAs 1W, 2, 5 and 6 during WY2004.

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66 Table 2 7. Total c arbon areal storage in floc and soils in the STAs ( k g C m 2 ; mean SD). Values represent entire floc depth and top 10 cm of surface soil. WY STA 1E STA 1W STA 2 STA 3/4 STA 5 STA 6 Floc 2003 ----1 .30 0.85 -2007 -1 5 2 0. 64 2 2 8 1 .2 2 16 1 .2 2.41 1.3 -Soil 1995 -10 .7 1 .6 ----1996 -8 .09 2 .9 ----2000 -6 .24 0.74 ----2001 --10 2 1 5 -11 .8 1 6 8 .3 2 .1 2003 ----12 .3 2 .5 -2004 -10 3 2 .2 9 0 4 2 .4 -12 .4 2 .6 13 .8 3 .7 2005 5 .17 3 .6 --12 6 9 2 .8 --2006 -10 8 2 0 ----2007 4 55 2 .1 8 .6 1 .4 10 .3 2 .1 9 7 2 .7 9 7 5 3 .2 -2008 -10 1 1 5 ---* Total carbon concentra tion for floc was not available for STAs 1W, 2, 5 and 6 during WY2004. Table 2 8 Variation in areal and total nutrient storages in the STAs with different age s Nutrient masses represent entire floc depth and top 10 cm of surface soil. STA WY Age (yr) Area (h a) Areal storage (floc + surface soil, g m 2 ) Total mass in STA (mt) P N C P N C STA 1E 2007 3 2073 10.1 312 4550 209 6,470 94,400 STA 3/4 2007 4 6683 24.6 785 11870 1644 52,460 793,520 STA 6 20 04 6 912 26.5 1,029 13790 241 9,380 125,710 STA 2 2007 8 3329 21.2 767 12570 706 25,530 418,480 STA 5 2007 8 2462 27.4 859 12160 675 21,150 299,450 STA 1W 2007 13 2695 19.1 884 10100 515 23,820 272,160

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67 Figure 2 1. Phosphorus mass balance calculatio ns for soil P storage with respect to net P retained from the water column. All values are in g P m 2 Arrows indicate flux of P between compartments. Top row arrow indicates direction of P movement between water and floc. Middle row arrows show P movement between floc and surface soil (0 10 cm ). Lower row arrows indicate P movement between surface (0 10 cm) and sub surface soil (10 30 cm ).

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68 Figure 2 2 Relationship between STA age and fraction of total phosphorus storage in floc + soil derived fro m the water column.

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69 Figure 2 3 Relationship between total P retained from the water column through WY2007 and total P storage in floc + soil (g P m 2 ). A one to one ( 1:1 ) line differentiates between P derived from pre STA soil and P retained from the wa ter column.

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70 Figure 2 4 Relationship between total P retained (g P m 2 ) from the water column and total P storage in floc + soil (g P m 2 ). Data represent annual STA area weighted averages.

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71 Figure 2 5 Relationship between total P retained (g P m 2 ) from water column and total P storage in floc + soil (g P m 2 ). Data represent annual c ell averages (not area weighted)

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72 Figure 2 6 Relationship between floc total P concentration (mg P kg 1 ) and inflow total P flow weighted mean concentration ( FWMC ; g L 1 ). Data represent annual c ell averages.

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73 Figure 2 7 Relationship between floc P storage (g P m 2 ) and inflow total P flow weighted mean concentration (FWMC; g L 1 ). Data represent annual c ell averages.

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74 Figure 2 8 Relationship between soil carb on storage (kg C m 2 ) and soil P storage (g P m 2 ) in WY2007 except for STA 6 d ata which are from WY2004.

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75 Figure 2 9 Phosphorus mass balance calculations for soil P storage with respect to net P retained from the water column. All values are in g P m 2 Arrows indicate flux of P between compartments. Top row arrows indicate direction of P movement between water and floc. Middle row arrows show P movement between floc and surface soil (0 10 cm ). Lower row arrows indicate P movement between surface (0 10 cm) and sub surface soil (10 30 cm).

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76 Figure 2 10 Relationship between mean floc P storage per year (g P m 2 yr 1 ) and STA age *STA 6 data pertains to WY2004 while other STAs data represent WY2007.

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77 Figure 2 11 Relationship between mean surface soil (0 10 cm) P storage per year (g P m 2 yr 1 ) and STA age *STA 6 data pertains to WY2004 while other STAs data represent WY2007.

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78 CHAPTER 3 CHANGE POINT TECHNIQUE FOR MEASUREMENT OF SOIL ACCRETION RATES IN CONSTRUCTED WETLANDS Background Wetlands rece ive sediments, nutrients, and other contaminants from various point an d non point sources. As such they serve as sinks, sources, and transformers of influent materials ( Kadlec and Wallace, 2009 ; Reddy and DeLaune, 2008 ; Rooth and others, 2003 ) Pollutants removed from the water column are lost to the atmosph ere, taken up by vegetation or incorporated in soil. The particulate fraction of inflow and plant litter material accretes in the system. This ne wly accreted material, referred to as recently accreted soil (RAS), serve as the long term integrator of prevai ling wetland conditions and preserve s a record of nutrient loading ( Inglett and Reddy, 2006 ; Reddy and DeLau ne, 2008 ; Smol, 1992 ) Soil that existed prior to wetland creation or prior to a perturbation in a exhibit s phys ic o chemical characteristics different from RAS. Such di fferences between RAS and the native soil the two layers. Therefore, investigation of wetland soil profile characteristics could provide reliable markers that correspond to the transition zone between RAS and native s oil in the depth profile. These markers can be utilized for measuring s oil accretion rate in w etlands by identifying this boundary and measuring RAS that accrued over a known period Wetland soils provide a long term sink for various pollutants ( Reddy and DeLaune, 2008 ) and therefore soil accretion rates have been related to the performance of treatment wetlands ( Kadlec, 2009 ) In addition buildup of accreted soils has a potential to adversely affect treatment efficiency of constructed wetlands because of a reduction in hydraulic volume and retention time. Outflow nutrient concentrations are

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79 a lso impacted by the interaction of RAS with the overlying water column ( Kadlec and Wallace, 2009 ) Hence measurement of soil accretion rates and quantification of soil elevation changes in wetlands are important for cont inued treatment efficiency and maintaining long term nutrient storages in these systems S oil accretion rates in wetlands are regulated by existing physical, chemical and biological conditions includin g nutrient and sediment loading hydrologic regimes and the seasonal cycle of vegetation growth and senescence ( Callaway and others, 1997 ; Callaway and others, 1 996a ; Craft and Richardson, 1993b ; Reddy and others, 1993 ) Thus, the soil build up represents a n integrated outcome of multiple processes operating simultaneous ly in a wetland system. Several methods have been developed to measure vertical soil accretion in coastal marsh areas ( Callaway and others, 1997 ; Church and others, 1981 ; Ibanez and others, 2010 ; Langley and others, 2009 ; Morse and others, 2004 ) These methods were used to determine soil elevation changes relative to eustatic sea level rise. Few studies however, have been conducted in inland freshwater wetlands ( Craft and Richardson, 1993a ; Craft and Richardson, 1993b ; Reddy and others, 1993 ; Rybczyk and others, 2002 ) and constructed wetlands ( Harter and Mitsch, 2003 ; Kadlec, 2009 ) Commonly availa ble techniques for soil elevation measurement can be used for measuring accretion over short period s (months to years ) ( Thomas and Ridd, 2 004 ) or for longer period s (decades to centuries ) ( Brenner and others, 2001 ; DeLaune and others, 1978 ) Accretion rate measurement techniques can also be grouped on the basis of methodology : a) u se of tracers (depositional markers), b) d irect elevation change measurement (using specialized instruments) and c) t opographic surveys.

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80 A ccretion measurement metho ds employ sophisticated techniques that require specific equipment and field conditions for successful implementation. For example tracer techniques using radiometric markers are only applicable in wetlands that have been functional for a sufficiently lon g duration to exhibit a signature corresponding to an enrichment peak in accreted sediments. Other accretion methods depend on artificially introduced marker s (such as feldspar clay) within the soil horizon to determine accretion of material over time. Use of surface elevation tables (SETs) and surveying requires using specialized equipment in the field. All existing methods depend on special ized skills during deployment i.e., retrieval of equipment and conducting survey s under submerged conditions. Additi onally, the abovementioned requirements limit the application of existing techniques at multiple sites. The a bsence of a straightforward and simple soil accretion measurement technique for wetlands present s a challenge for estimating the rate of soil forma tion and how it affects long term nutrient storage in wetland soils. Wetland managers could potentially benefit from this information to develop appropriate strategies to enhance the longevity and efficiency of treatment wetlands. This chapter presents re sults of a study conducted in large sub tropical treatment wetlands in s outh Florida to test a new and relatively simple change point technique (CPT) for determin ing soil accretion rates. Methods Site Description Three large constructed wetlands (STA 1W, S TA 2 and STA 3 /4 ) in South Florida were chosen for this study. These wetlands are part of a network of treatment wetlands known as the Stormwater Treatment Areas (STAs) (Figure 3 1 ). At the time of

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81 sample collection the operational age of the selected STA s ranged from 6 16 years. The STAs were constructed with a uniform structural configuration that includes a combination of flow ways that are comprised of treatment cells, with each cell having one dominant vegetation community e mergent aquatic vegetatio n (EAV), or submerged and floating aquatic vegetation (SAV /FAV ) ( Goforth, 2005 ) Intact soil cores were collected along a transect parallel to the flow direction in each cell. The t otal number and location of sampling sites was determined by taking into consideration the size and shape of each cell. Existing quarter mile grid sampling maps obtained from the SFWMD were utilized to identify the sampling locations in this study Detailed information about three STAs ( Appendix B) and sample collection maps ( Appendix C) and sampling sites i s presented in Appendix D (Table s D 1, D 2 and D 3) STA 1W: As a part of the long te rm management goals of STA 1W rehabilitation activities were carried out during WY200 7 08, in cluding tilling and demucking in C ell 2B and C ell 4 and an effort to convert from EAV to SAV in Cell 3 S oil samples collected from these cells were not subjected to isotopic ratio analysis, but all other analyses were carried out Soil sampling took place in July 2009. A t otal of 41 soil cores were collected ( Appendix C, Figure C 1) Triplicate samples were collected from eight sites. STA 2: S oil sampling was carri ed out in October 2009. A t otal of 29 intact soil cores were collected ( Appendix C, Figure C 2) Triplicate samples were collected from five sites. STA 3/4: As of 2008, Cells 1A, 1B, 2A and 3A were designated as EAV and were managed as such. Cells 2B and 3 B were designated SAV. However, Cells 1B and 2B were converted to SAV in WY2009 and were considered as SAV for this study. Soil

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82 cores were collected in January and February 2010 A total of 58 soil cores collected from EAV and SAV cells ( Appendix C, Figur e C 3). Triplicate samples were collected from nine sites. Soil Samp l ing and Processing Soil cores (n=128) were collected usi ng a stainless steel tube (10.2 cm internal diameter [ ID ] 0.2 cm wall thickness [WT] ). Depth of soil cores ranged from 10 40 cm as limited by the depth of bedrock from the wetland soil surface. Soil cores were transferred into clear cellulose acetyl butyrate tubes (10.2 cm ID, 0.16 cm WT ) in the field and transported to the laboratory for storage at 4 o C until they were analyzed T hickness of the unconsolidated surface detrital layer (floc) was measured before removing this material from the soil core The remaining s oil core was then sectioned at 2 cm intervals along its entire length. The total number of such sections were 733 (ST A 1W), 505 (STA 2) and 573 (STA 3/4) [For details see Tables C 1, C 2 and C 3 ( Appendix C)]. Surface material (floc) and 2 cm soil sections were dried at 70 o C for bulk density determination. Dried samples were finely ground using a ball mill and passed thr ough a 2 mm mesh before chemical analysis. Chemical and Isotopic Analysis T otal P was determined by the ashing and HCl digestion ( Andersen, 1976 ) using standard molybdate colorimetry for analysis ( U.S. Environmental Protection Agency, 1993 ) Total nitrogen (TN), total carbon (TC) and stable i sotop e ratios of C and N ( 13 C and 15 N) were determined using a Costech Elemental Analyzer (Model 4010, Costech Analytical Industries, Inc., Valencia, CA) coupled to a Finnigan MAT Delta Plus XL Isotope Ratio Mass Spectrometer (CF IRMS, Thermo Finnigan, San Jos e, CA) via a Finnigan Conflo II interface. Elemental calibration was accomplished using peach leaves (2.93%

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83 N, 44.65% C). Inorganic C was removed prior to 13 C analysis using the HCl fumigation ( Harris and Horwath, 2001 ) Soil samples were analyzed separately for 15 N, TC and TN (non acid fumigated samples) and 13 C (acid fumigated samples) to avoid potential error in the 15 N measurement due to HCl fumigation. Ratios of C and N stable isotopes (R sample ) are expressed as per mille ( ) differences from the ratio of a standard (R std atmospheric N 2 and Pee Dee Belemnite, for N and C, respectively) using delta notation ( ) as : sample = [(R sample / R std ) 1] x 1000. Change point Analysis A c hange point (CP) refers to a point along a distribution of values of a variab le where the values before and after the change point are significantly different. The method for identification of a change point uses deviance reduction along a distribution of points such that the sum of deviances on either side of the change point is m inimized compared to the deviance of the overall dataset. The percent error reduction associated with splitting the data is calculated by an iterative process identifying a point (change point) that minimizes the deviance ( Qian and others, 2003 ) A schematic depiction of how a CP was used as an indicator of the boundary between RAS and native soils in a treatment wetland is presented in Figure 3 2 The software program me SegReg 1 ( Oosterbaan and others, 1990 ) was used to identify the CP in soil variables along depth profile s, with a 90% confidence interval (CI). The SegReg identified one or more CPs in the data whereupon separate linea r regressions were run on the data subsets as defined by the CPs The location where these line segments intersected was interpreted as the boundary between RAS and native soil. The depth from the soil surface to the first CP corresponded to the thickness 1 http://www.waterlog.info/segreg.htm

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84 of RAS layer The depth profiles for physico chemical properties such as bulk density, TP TN, TC nutrient ratios (N:P, C:P and C:N) and 15 13 C were used to identify CP s in soil cores using SegReg program. Only f our variables bulk density, TP content 15 13 C yielded consistent CPs along depth profiles, and allowed to identify RAS depth. An example of the SegReg output for a representative soil core using all four variables is presented in Figure 3 3 The RAS depths obtained by SegReg for each of the four variables bulk density, TP content, 15 13 C were averaged to obtain mean RAS depth for each soil core. Mean RAS d epth for each soil core from a cell were then averaged to obtain the mean RAS depth for that cell Mean RAS depths for all cells within a STA were subsequently used to calculate a grand mean RAS depth for that STA. Comparison of differences in RAS depths a mong parameters within each STA were tested with one way ANOVA s followed by the Tukey Kramer HSD test s (p<0.05) using JMP (Version 7; SAS Institute Inc., Cary, NC, 1989 2007) Operational age of STAs at the time of soil sampling was used to calculate mean annual soil and P accretion rates Operation age s for STA 1W, STA 2 and STA 3/4 were 16, 10 and 6 years respectively However, C ells 5A and 5B in STA 1W were constructed much later ( WY 2009), so the operational age for those cells was taken as 10 years. In cases where the CP depth was an odd value the average bulk density of the RAS layer was calculat ed using the mean bulk densit ies of the 2 cm soil section s above and below the CP depth and then using this mean value along with all other RAS sections to c alculate mean bulk density for the whole RAS layer. F or example, if the CP depth was 7 c m then the average bulk densit ies for the 4 6 cm and 6 8 cm soil

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85 section s were used along with the bulk densities for the 0 2 and 2 4 cm soil sections to calculate the average bulk density for RAS. Average TP (mg P kg 1 ) for RAS was also calculated in a similar manner. Mean bulk density and TP for the whole RAS layer were used for calculating total P storage in RAS (g P m 2 ) and for calculating annual P accretion rates (g P m 2 yr 1 ) The robustness of CPT was tested by determining CP depths on pre existing data available from the Water Conservation Area 2A (WCA 2A) ( Reddy and others, 1993 ) Reddy and others, (1993 ) used radiometric marker tech nique for determination of accretion rates where peak concentration of Cesium ( 137 Cs ), a radioactive fallout product of nuclear bomb testing, corresponded to year 1963 64. Depth of 137 Cs peak along the soil profile represented depth of accumulated soil sin ce 1963 64 Stratigraphic properties of WCA 2 soil cores (bulk density, TP and 137 Cs activity (pCi section 1 ) ) were used to determine CP depth by SegReg program. The SegReg results were compared with the depth of 137 Cs peaks obtained for each sampling stat ion in WCA 2A ( p=0.26, test ). Results The mean RAS depth for STA 1W, STA 2 and STA 3/4 was 14.7 5.1 cm, 11 3.3 and 10 4.6 cm, respectively. The mean annual soil accretion rate for STA 1W, STA 2 and STA 3/4 for an operational history of 16, 10, and 6 years, were 1 0.3 cm yr 1 1.1 0.3 cm yr 1 and 1.7 0.8 cm yr 1 respectively. Within each STA, RAS depths obtained by using different soil characteristics 15 13 C) were similar except for STA 1W (Figure 3 4). In STA 1W, RA S depth estimated by bulk density was twenty five percent higher than that estimated by TP however this trend was not seen in STA 2 and STA 3/4. In STA 3/4,

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86 RAS depth estimated by bulk density was thirty percent greater than that estimated by using 13 C h owever this was not significant. Three way ANOVA results on the normalized dataset suggested a significant difference in RAS depth predicted by four parameters. Bulk density predicted fifteen percent higher CP depth in comparison to TP, however this effect was dependent on STA (site*soil variable, p<0.05). In all three studied STAs, RAS depths were consisten t for other two soil physico chemical variables ( 15 N 13 C ). There was no influence of dominant vegetation on mean RAS depths determined by four soil variables across three STAs This indicated that there was no significant influence of a specific dominant wetland vegetation on CP depths and all four variables offered similar results when used for CP estimation (Figure 3 5). Discussion Soil that existed prior to wetland creation (native soils) exhibit characteristics that are dissimilar from RAS ( White and others, 2006 ) This difference in physico chemical between two layers. This stratigraphic information conserved in t he soil profile was utilized for CPT. The study was undertaken in STAs constructed on erstwhile agricultural farmland containing historically oligotrophic peat soil (Histosols). STAs were established for reducing TP inputs to the Everglades by removing inf luent P from the water column and sequestering it in RAS. Accreting organic soils did not differ from native soil in C and N characteristics, but had an elevated P signature, which generated a CP when analyzed using the SegReg program. Investigation of dep th profiles for total C, tot al N, and nutrient ratios (N:P, C:P and C:N) did not produce a clear CP along soil profiles. On the other hand, analysis of stable isotope ratios of C and N along soil depth profiles yielded CPs that were consistent with those g enerated from bulk density and TP

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87 values. In aquatic ecosystems, C and N isotope signatures in soil are widely used to detect changes in plant and microbial processes related to the change in existing conditions ( Chang and others, 2009 ; Inglett and Reddy, 2006 ) Such changes in biogeochemical properties and processes were elucidated by examining stable isotope ra tios of N and C ( 15 N 13 C ). The mean RAS depths across different vegetation types were similar for studied soil variables in all three STAs. This suggested that the SegReg CP determination technique could be applied to wetlands with different vegetation. Additionally the RAS depth determined using different soil properties were similar except depths estimated by bulk density and TP. It is possible that CP depth predicted by TP represents a better estimate of RAS depth in STAs in comparison to BD estimates. This may b e caused by external P loading received by STAs since their inception where CP in TP profile is a better indicator of actual boundary between RAS and pre STA soil. Bulk density, on the other hand, represents characteristics that are somewhat secondary to t he direct P loading. As the mass (weight) of accreted soil increases it compresses soil to a point until the internal resistance to further compression is balanced by the force exerted by the mass of RAS. The resultant increase in BD was noticed as a CP in SegReg program; however the identifiable point of increased BD was slightly deeper than the actual boundary between RAS and pre STA soil. This may be due to differences in composition of RAS and pre STA soil and not due to biogeochemical processes occurri ng in the soil profile. Overall, reasonably accurate CP depth results could be obtained by using selective soil variables for determination of RAS depth using the SegReg CP technique in wetland systems with variable aquatic vegetation.

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88 A decline in soil ac cretion rate with increasing operational age was observed. This decline in RAS depth over time could be a result of soil compaction as the weight of overlying soil increases over time. Additionally, occurrence of brief dry periods could result in oxidation The accretion rates determined by CPT for three STAs falls within the average range (0.3 1.9 cm yr 1 ) as observed by using other measurement techniques (Table 3 1) across a range of wetla nd systems The results obtained by CPT were compared with a well established marker horizon technique ( 137 Cs peak) on an existing dataset ( Reddy and others, 1993 ) The RAS depths and 137 Cs peak depths were not si gnificantly different across the sampling locations (Figure 3 test). This observation confirmed the utility and reliability of simple CPT as an alternative to the existing methods that usually require elaborate procedures. This served as a test of reliability and robustness of CPT for det ermination of RAS depths and calculating annual accretion rates. Available accretion measurement techniques vary widely on the key principle utilized for determining elevation change in wetland soils over time ( Table 3 1 ). Tracer techniques depend on artif icially introduced markers (feldspar or plaster) ( Cahoon and Turner, 1989 ; Knaus and Gent, 1989 ) or atmosphe rically deposited radioactive Cesium and Lead ( DeLaune and others, 1978 ; Stam, 1999 ) Sedimentation Erosion Tables (SET) ( Boumans and Day, 1993 ; Eerdt, 1985 ; Schoot and De Jong, 1982 ) and Surface Elevation Table ( Cahoon and others, 2002 ) u tilize special set of plates and pins for measurement of elevation changes. Stakes and rods ( Pestrong, 1965 ; Reed, 1989 ) sediment pins ( Letzsch and Fr ey, 1980 ) Photo Electronic Erosion Pin (PEEP; Lawler,

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89 (1991 ) ), anchored tiles ( Past ernack and Brush, 1998 ) and the bridge method ( Perillo and others, 2003 ) are examples of techniques using specialized instruments. Surveying methods using eco sounder sy stem ( Takekawa and others, 2010 ; Verlaan and Spanhoff, 2000 ) dendro geomorphic ( Hupp and Bazemore, 1993 ) sediment flux measurements ( Noe and H upp, 2009 ) peat probing, water surface elevation changes, and topographic surveys ( Kadlec, 2009 ) have also been used for calculating accretion rates in wetl and ecosystems. In comparison, the CPT offers a simple, easily implementable procedure that generates robust results. It does not require presence of a radioactive layer or an introduced marker horizon or specialized instruments for conducting a survey, wh ich enables its rapid replication at multiple sites. The CPT is particularly useful in systems where a natural or anthropogenic perturbation is known to have impacted the biological state of a system, creating a stratigraphic signature embedded in accreted soil corresponding to a specific time in the history of a wetland. There are, however some scenarios where use of CPT may not be advisable. For instance, high energy systems that experience frequent suspension and resettling of sediments could result in d estruction of CP signature and may not be appropriate for application of CPT. Also, soil accretion rates cannot be calculated for wetlands that lack information about operational history or a specific historical time point which may correspond to a discont inuity in the soil profile. Sequential vertical layering of RAS ( Kadlec, 2009 ; Rybczyk and others, 2002 ) in low energy wetland systems (treatment wetlands) are prone to disruption by bioturbation ( Robbins, 1986 ) and by plant mediated processes that take place in the root zone. Such processes could result in attenuation of

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90 specific signatures and present a challenge to identify CP. In addition, the outc omes of CPT are dependent on a consistent solid phase boundary within the accreting soil profile. Any mobile constituents or chemical processes that occur at the surface, but are different at depth (such as pH mediated solubility, decomposition, etc.) coul d artificially cause surface sediments to be different from deep sediments, without there being any change in the system. Pre existing conditions at a location could have a significant role in soil characteristics and therefore should be considered during selection of variables for examining existence of CP in a soil profile. And lastly, CPT can be applied to soil cores that are deep enough to travers the boundary between RAS and the native soil. Nevertheless, CPT presents a new and simple approach for mea surement of vertical accretion rates in low energy systems, such as constructed wetlands. It provides an alternative to existing techniques and offers a simple method for soil accretion rate measurement. It presents a practical option for managers who are interested in evaluating long term accretion of contaminants as a measure of performance of treatment wetlands.

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91 Table 3 1. Soil accretion m easurement methods and published accretion rates from wetland studies. Location State/ Country Method Accretion Rate s (cm yr 1 ) Reference Waquoit Bay Massachusetts 210 Pb 0.3 0.5 Orson and Howes ( 1992 ) Narragansett Bay Rhode Island 210 Pb 0.2 0.6 Brickerurso et al. ( 1989 ) Farm River Connecticut 210 Pb 0.5 McCaffrey ( 1980 ) Flax Pond New York 210 Pb 0.5 0.6 Armentano and Woodwe ll ( 1975 ) Great Marsh Delaware 210 Pb 0.5 Church et al. ( 1981 ) Delmarva Peninsula Virginia 210 Pb 0.1 0.2 Kastle r and Wiberg ( 1996 ) Chesapeake Bay, Ma ryland 210 Pb 0.2 0.4 Stevenson et al. ( 1985 ) Chesa peake Bay, Maryland 210 Pb 0.5 0.7 Kearney and Ward ( 1986 ) Chesapeake Bay, Maryland 210 Pb 0.4 0.8 Griffin and Rabenhorst ( 1989 ) Floodplain wetland Las Tablas de Daimiel, Spain 210 Pb 1.6 3.8 Sanch ez Carillo et al. ( 2001 ) Severn Estuary England 210 Pb 0.4 French et al ( 1994 ) St. Johns River Basin Florida 210 Pb 0.2 0.4 Brenner et al ( 2001 ) Pamlico Sound North Carolina 137 Cs 0 0.5 Craft et al. ( 1993a ) Everglades Florida 137 Cs 0.1 1.2 Reddy et al. ( 1993 ) St. Johns River Basin Florida 137 Cs 0.3 0.5 Brenner et al. ( 2001 ) San Francisco Bay California 137 Cs 0.4 4.2 Patrick and DeLaune ( 1990 ) T idal fresh water mars h Virginia 137 Cs 0.8 Neubauer et al. ( 2002 )

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92 Table 3 1. Continued Location State/ Country Method Accretion Rates (cm yr 1 ) Reference Multiple sites Oregon and Washington 137 Cs 0.2 0.7 Thom ( 1992 ) Eastern Scheldt Netherlands 137 Cs 0.4 1.6 Oenema and DeLaune ( 1988 ) Mu ltiple sites England, Netherlands, Poland 137 Cs 0.3 1.9 Callaway et al. ( 1996a ; 1996b ) Chesapeake Bay Maryland 210 Pb and 137 Cs 0.3 0.8 Kearney and Stevenson ( 1991 ) Everglades Florida 210 Pb and 137 Cs 0.1 0.8 Craft and Richardson ( 1998 ) Chesapeake Bay Maryland 210 Pb and 137 Cs 0.3 0.8 Kearney et al. ( 1994 ) Long Island Sound Connecticut 210 Pb and 137 Cs 0.1 0.7 Anisfeld et al. ( 1999 ) Barn Island Connecticut 210 Pb and 137 Cs 0.1 0.4 Orson et al. ( 1998 ) Nauset Marsh Massachusetts 210 Pb and 137 Cs 0 2.4 Roman et al. ( 1997 ) Louisiana coast Louisiana 210 Pb and 137 Cs 0.5 0.9 DeLaune et al. ( 1989 ) Island of Sylt Germany 210 Pb and 137 Cs 0.6 1.5 Kirchner and Ehlers ( 1998 ) Louisiana Louisiana Stable tracers using REE a 0.8 3.0 Knaus and Van Gent ( 1989 ) Multiple sites Maine Marker horiz on 0 1.3 Wood et al. ( 1989 ) Sapelo Island Georgia Marker horizon 0.2 0.7 Let zsch ( 1983 ) a r are e arth e lements

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93 Table 3 1. Continued Location State/ Country Method Accretion Rates (cm yr 1 ) Reference Barn Island Connect icut Marker horizon 0.1 0.4 Orson et al. ( 1998 ) Eastern Scheldt Netherlands Marker horizon 0.4 1.6 Oenema and DeLaune ( 1988 ) Nauset Mars h Massachusetts Marker horizon 0 2.4 Roman et al. ( 1997 ) Rookery Bay Florida Marker horizon and SET b 0.4 0.8 Cahoon and Lynch ( 1997 ) Louisiana coast Louisiana Feldspar Marker Horizon 0.7 1.0 Cahoon and Turner ( 1989 ) Scolt Head Island, England Marker horizon 0.1 1.4 Stoddart et al. ( 1989 ) Scolt Head Island, England Marker horizon 0.1 0.8 French and Spencer ( 1993 ) Tijuana Estuary Marker horizon 0.1 8.5 Cahoon et al. ( 1996 ) STA 1W (n=28) c Florida CPT (using bulk density, TP content 15 and 13 1 0.3 This dissertation study STA 1W Cell 5A and 5B (n=12) c Florida 1.2 0.6 STA 2 (n=29) c Florida 1.1 0.3 STA 3 /4 (n=39) c Florida 1.7 0.8 b s ediment e levation t able c values in parentheses indicate the number of soil cores analyzed

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94 Figure 3 1. Location of the three Stormwater Treatment Areas ( STA 1W, STA 2 and STA 3/4 ) used in this study and the n umber of soil cores colle cted from each STA.

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95 Figure 3 2. A cross section view of a typical free water surface treatment wetland and s chematic depiction of a boundary between recently accreted soil (RAS) and native soils, which is identifiable as a change point using stratigrap hic characteristics of the soil profile.

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96 Figure 3 3. SegReg output using bulk density (g cm 3 ), total phosphorus content (mg P kg 1 ), and stable isotopic ratio s 13 15 respectively] in a representative soil profile from a si te in STA 2. The c hange point is identified with a 90% confidence interval Each data point represents a 2 cm soil core section.

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97 Figure 3 4 Depth of RAS for STA 1W, STA 2, and STA 3/4 as determined by SegReg change points using four variables (bulk dens ity, total phosphorus, isotope ratio of C and N [ 13 C and 15 N respectively]) Only significant difference in RAS depths between bulk density and TP in STA 1W (each STA tested separately using Tukey Kramer HSD test, p< 0.05). Error bars represent standard error of the mean. The total number of soi l cores (n) used in this analysis was 40, 29 and 58 for STA 1W, STA 2, and STA 3/4 respectively

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98 Figure 3 5 Variation in RAS depth between two dominant vegetation types Emergent Aquatic Vegetation (EAV) and submerged aquatic vegetation (SAV) for four parameters bulk density (g cm 3 ), total phosphorus (mg P kg 1 ), stable isotope r atio of C and N [ 13 C and 15 N respectively] No significant differences observed (each STA tested separately using Tukey Kramer HSD test, p< 0.05 ). Error bars represent standard error of the mean

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99 Figure 3 6. Comparison of RAS depth obtained by using SegReg prog ram and 137 C s peak s from Everglades W ater C onservation A rea 2. Three soil profile characteristics bulk density (g cm 3 ), total phosphorus (mg P kg 1 ) and 137 Cs activity (pCi section 1 ) were used for SegReg CP determination. No significant difference betw een RAS depth obtained by paired t test) Error bars represent standard deviation in SegReg CP depths.

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100 CHAPTER 4 SOIL AND NUTRIENT ACCRETION RATES IN TREATMENT WETLANDS OF THE EVERGLADES BASIN Background Constructed treatment w etl ands are dynamic ecosystems characterized by unique hydrology, soils, vegetation and high net primary productivity. These ecosystems are used worldwide to remove water borne contaminants. I nfluent chemicals are either assimilated internally or transformed into benign products that are exported from the system ( Kadlec and Wallace, 2009 ) Internal assimilation can occur by physical settling of suspended organic and inorganic constituents or may involve complex processes leading to the eventual incorporation o f influent chemicals into plant biomass. The release of contaminants back into the water column after vegetation senescence is inhibited by the reducing conditions present in the wetland environment Consequently, two processes in wetlands h igh rates of net primary productivity and suppressed rates of decomposition result in the buildup of material at the soil water interface ( DeBusk and Reddy, 1998 ) which provides a long term sink for influent constituents ( e.g., nutrients) S oil accretion is a sustainable pathway in treatment wetlands f or sequestering non volatile contaminants that cannot be easily transformed into ecologically benign products C onstructed wetlands exhibit a wide range of t reatment efficienc ies depending on the to be removed ( i.e., target substance or attr ibute), and the prevailing bio geochemical conditions with in the wetland over its period of operation. F or example, treatment efficiencies for total suspended solids (TSS), biochemical oxygen demand (BOD), and pathogens ( bacteria and viruses ) have been repo rted as high as 70% ( Kadlec and Wallace, 2009 ) and range from 40 50% and 40 90% for N and P

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101 respectively ( Andersson and others, 2005 ; Chen, 2011 ; Germain and Pietro, 2011 ; Vymazal, 2007 ) The t reatment capability of constructed wetlands is a consequence o f complex biogeochemical processes taking place simultaneously within the water column, the soil profile in wetland vegetation and microorganisms and at the soil water vegetation interface. The factors that affect these biogeochemical processes in turn a ffect the treatment efficiency of constructed wetlands. Previous reviews of treatment wetland performance for specific constituents have attempted to understand the complex pathways and underlying biogeochemical processes that result in treatment. Most no tably, studies on C, N and P processing in natural and constructed wetlands ( Brix, 1994 ; Craft and Richardson, 1993a ; D'Angelo and Reddy, 1999 ; Kayranli and others, 2010 ; McLatchey and Reddy, 1998 ; Reddy and Debusk, 1985 ; Reddy and others, 1999a ; Saunders and Kalff, 2001 ; Vymazal, 2007 ) have provided insights to help optimize treatment performance and extend the functional life of constructed wetland systems ( Kadlec and Wallace, 2009 ; Vymazal, 2011 ) This chapter is an attempt to understand the ke y processes regulating long term P removal by treatment wetlands The study was undertaken on a small subset of treatment wetlands which are characterized by having exceptionally large treatment area s receive agricultural drainage water as inflows and ha ve an extremely low outflow P concentration target. These large treatment wetlands are referred to as the Everglades Stormwater Treatment Areas (STAs), and the target outflow P concentration fall s within the range of 1 3 19 g P L 1 Removal of P in treatm ent wetlands takes place via two distinct pathways: sorption and burial ( Reddy and others, 1999a ) The P burial involves biotic components

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102 in whereby a fraction (10 20%) of P contained in microbial and plant biomass avoids decomposition and recycl ing within the wetla nd ( Reddy and others, 1993 ; Rybczyk and others, 2002 ) Continued burial of residual biotic detritus result s in accumulation of organic soil that provides a sustainable mechanism of P removal in treatment wetlands ( Reddy and others, 1999a ) The effectiveness of P removal in treatment wetlands is influenced by factors such as hydraulic loading rate (HLR), inflow P concentr ation, substrate type, biomass growth rate and soil P concen tration ( Gu and others, 2001 ; Kadlec, 2005 ) Althoug h creation of soil and associated sequestration of P is the only sustainable mechanism for P removal in wetlands it remains one of the least explored aspect s of P retention in these systems [p p 364 ( Kadlec and Wallace, 2009 ) ]. The soil and P accretion ra tes in free surface wetlands have been quantified in only few instances ( Craft and Richardson, 1993b ; DeLaune and others, 1989 ; Reddy and others, 1993 ; Rybczyk and others, 2002 ) This chapter presents the results of research conducted to address the existi ng knowledge gap in terms of soil accretion in wetlands by using the STAs as a case study Information on soil accretion rates in wetlands allows an accurate determination of nutrient retention in the system over the period of record ( POR ) I nsights into t he rate of soil build up and nutrient concentrations in RAS are important for two reasons First, P concentration s and forms in RAS dictate P exchange rates between soil and the water column which can reduce the efficiency of a treatment wetland ( Reddy and others, 2002 ) Earlier studies carried out in W ater C onservation A rea (WCA) 2A showed decreases in P uptake from the overlying water column with P enrichment of the floc and surface soil ( Fisher and Reddy, 2001 ; Richardson and Vaithiyanathan, 1995 )

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103 Second, knowledge of accretion rates is ne cessary for optimizing design criteria and to estimate the functional life of a treatment wetland before soil build up reduces storage capacity and water residence time, necessitating extensive engineering interventions This could have serious implication s in terms of the functional life of treatment wetland s before expensive rehabilitation ( e.g., dredging) is required. In the absence of a clear visual boundary between RAS and antecedent soils in the STAs it wa s not possible to discern RAS depth accuratel y by visual inspection This challenge, h owever, was addressed by using stratigraphic characteristics of accret ed soil to determine RAS depth in the STAs ( Chapter 3) and subsequent ly determin ing accretion rates in the se treatment wetlands (this chapter) O bjective s and Hypotheses The first objective of this study was to e xplore the relationship between soil accretion rates and operational age of the STAs. T he operating h ypothesis was that most P retained from the water column in the STAs is stored in RAS w hich act s as a nutrient enriched repository and generally has higher P concentration s than pre STA soil Furthermore, w ith increasing age the rate of soil and P accretion would decline, resulting in a higher outflow P concentration. The s econd objective was to develop a refined P mass budgets using information on soil P storages in RAS and pre STA soil and total P removed from the water column This mass balance approach was an advancement from the one presented in Chapter 2, because it utilized actual de pth of RAS instead of a fix 0 10 cm surface soil depth for P storage calculations. Th e operating hypothesis was that distribution of P within RAS and pre STA soi l is mediated by vegetation, thus vegetation plays a crucial role in controlling whether the ST As function as a nutrient source s or sink s

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104 Methods Site Description Three large constructed wetlands (STA 1W, STA 2 and STA 3 /4 ; Appendix B ) in s outh Florida were chosen for this study (Figure 4 1 ). At the time of this study the operational age of select ed STAs ranged from 6 16 years. All STAs were constructed with a similar internal configuration i.e., a number of parallel flow ways each having one or more treatment cells, with each cell managed for one dominant vegetation community e mergent aquatic v egetation (EAV), or submerged and floating aquatic vegetation (SAV/FAV) ( Goforth, 2005 ) Intact soil cores were co llected along a transect parallel to the direction of flow in each cell. The number and location of sampling sites was determined based on the size and shape of each cell. Existing quarter mile grid sampling maps obtained from the SFWMD were utilized to id entify the sampling locations in this study Detailed information about three STAs ( Appendix B) and sample collection maps ( Appendix C) and sampling sites is presented in Appendix D (Tables D 1, D 2 and D 3) STA 1W: As a part of the long term management go als of STA 1W rehabilitation activities were carried out during WY200 7 08, in cluding tilling and demucking in C ell 2B and C ell 4 and effort s to convert from EAV to SAV in Cell 1B and Cell 3 Cell 1B and Cell 3 were converted to SAV from EAV and were class ified as EAV conversion cells, however for the purpose of analysis those cells were designated as SAV cells Soil samples collected from these cells were not subjected to isotopic ratio analysis, but all other analyses were carried out Soil sampling took place in July 2009. A total of 41 soil cores were collected ( Appendix C, Figure C 1). Triplicate samples were collected from eight sites.

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105 STA 2: S oil sampling was carried out in October 2009. A t otal of 29 intact soil cores were collected ( Appendix C, Figu re C 2). Triplicate samples were collected from five sites. STA 3/4: As of 2008, Cells 1A, 1B, 2A and 3A were designated as EAV and were managed as such. Cells 2B and 3B were designated SAV. However, Cells 1B and 2B were converted to SAV in WY2009 and wer e considered as SAV for this study. Soil cores were collected in January and February 2010 A total of 58 soil cores collected from EAV and SAV cells ( Appendix C, Figure C 3). Triplicate samples were collected from nine sites. Soil Sampling and Processing Soil cores (n=128) were collected usi ng a stainless steel tube (10.2 cm internal diameter [ID] 0.2 cm wall thickness [WT] ). Depth of soil cores ranged from 10 40 cm as limited by the depth of bedrock from the wetland soil surface. Soil cores were trans ferred into clear cellulose acetyl butyrate tubes (10.2 cm ID, 0.16 cm WT ) in the field and transported to the laboratory for storage at 4 o C until they were analyzed Thickness of the unconsolidated surface detrital layer (floc) was measured before removin g this material from the soil core The remaining s oil core was then sectioned at 2 cm intervals along its entire length. The total number of such sections were 733 (STA 1W), 505 (STA 2) and 573 (STA 3/4) [For details see Tables C 1, C 2 and C 3 ( Appendix C)]. Surface material (floc) and 2 cm soil sections were dried at 70 o C for bulk density determination. Dried samples were finely ground using a ball mill and passed through a 2 mm mesh before chemical analysis. T otal P was determined by the ashing and HCl digestion ( Andersen, 1976 ) using standar d molybdate colorimetry for analysis ( U.S. Environmental Protection Agency,

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106 1993 ) Total nitrogen (TN) and total carbon (TC) were determined using a Costech Elemental Analyzer (Model 4010, Costech Analytical Industries, Inc., Valencia, CA) coupled to a Finnig an MAT Delta Plus XL Isotope Ratio Mass Spectrometer (CF IRMS, Thermo Finnigan, San Jose, CA) via a Finnigan Conflo II interface. Elemental calibration was accomplished using peach leaves (2.93% N, 44.65% C). Data Analysis Phosphorus storage (g P m 2 ) in f loc, RAS and pre STA soil were calculated using Equation 2 1 and 2 2 ( Chapter 2) for STA 1W, STA 2 and STA 3/4 In this study, however, bulk density, TP concentrations, and depth of soil cores were determined on the soil cores collected in WY2010 ( Chapter 3) The change point depth obtained by the CPT was used to differentiate the boundary between RAS and pre STA soil. The m ass of P in RAS and pre STA soil was ob tained by calculating P storage for each 2 cm soil section and then summing P storage over all sections within each soil layer Maximum soil core depth considered for this analysis was 30 cm hence each STA had different pre STA soil depth depending on the mean RAS depth as determined by subtracting RAS depth from the total soil core depth (30 cm). As a result, P storage in the pre STA soil fraction of STA 1W, STA 2 and STA 3/4 represented 17, 19 and 20 cm deep sections respectively. RAS depth s for all soil core s from within a cell were averaged to obtain the mean RAS depth for that cell The mean RAS depths for all cells within each STA were used to calculate mean RAS depth for the whole STA. Soil accretion rates ( cm yr 1 ) were calculated using average RAS depths and the operational age of 16, 10, and 6 years for STA 1W, STA 2 and STA 3/4 respecti vely Phosphorus accretion rates (g m 2 yr 1 ) were determined using total P storage in RAS over the operational age of each STA

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107 corrected to a unit surface area Comparison of differences in RAS depths among different cells within each STA were tested with one way ANOVAs followed by the Tukey Kramer HSD test s (p<0.05) using JMP (Version 7; SAS Institute Inc., Cary, NC, 1989 2007). Mass Balance s Phosphorus mass balance s were calculated using T P retained from the water column over the POR and P mass storage ( g P m 2 ) in floc RAS and pre STA soil for each STA T otal P retained from the water column was obtained from the 2010 South Florida Environmental Report ( Pietro and others, 2010 ) It was assumed that floc P sto rage (FPS ) at any given time reflect ed the fraction of P supplied from the water column ( P Wc) as well as any P moved upwards from RAS. If FPS was smaller than P Wc it was assumed that P had move d from floc into the RAS (P flux F ; ve ) Total P stored in R AS (RAS PS; g P m 2 ) indicate d net P derived from floc (P flux F ) as well as any P from pre STA soil (P flux PSS ). When RAS PS was +ve it indicated move ment of P from pre STA soil (P flux PSS, +ve ). These calculations are illustrated in Figure 4 2 The arr ows indicate direction of P flux from one compartment to other. For all practical purposes, soils represent the sole long term nutrient storage pool in wetlands, whereas nutrients in live vegetation serve as a transient pool ( Howard Williams, 1985 ) hence P present in vegetation was not considered in P mass balance calculations. C ritical assumptions made for developing P mass balance s are listed below T he total mass of T P retained from the water column ( P Wc) initially resides as floc therefore floc P storage (FPS ) at any given time reflects the fraction of T P incorporated from the water column as well as contribution from vegetative de trital matter (physical settlement of particulate forms, adsorption absorption of soluble forms, biological immobilization by microbial communities)

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108 Floc P contributed by vegetative detrital matter deposition may represent a fraction that could be obtaine d from underlying soils by rooted plants (EAV) or directly from the water column by submerged and floating plants (SAV/FAV) For comparisons at STA level, both EAV and SAV/FAV cells within one STA were averaged to obtain FPS for that STA. Floc becomes soil over time, so with a long observation period some of the water column TP have passed through the floc and into the surface soil. Flux of P from pre STA soil ( P flux P SS ) to overlying soil or floc i s regulated by redox conditions and the equilibrium P conce ntration (EPCo). Phosphorus in live vegetation biomass at a given time (i.e., plant standing stock) accounts for only a tiny fraction of TP in the STAs and represents a transient pool which ultimately gets transformed into floc and soil after plant senesc ence, following the decay continuum pathway. Results Comparison of EAV and SAV bulk density and TP depth profiles for STA 1W STA 2 and STA 3/4 is presented in Figure 4 3. B ulk density of EAV cells was lower than SAV cells u ntil a depth of 14 cm in STA 1W and at all depths in STA 2 In STA 3/4 no difference s were seen between EAV and SAV until top 8 cm, however deeper sections showed higher bulk density in EAV cells In general bulk density was higher in STA 3/4 than in the other STAs Total P concentrati on was higher in surface soils of EAV cells ( 5 to 16 cm ) compared to SAV cells in all STAs. Total P concentration decreased with depth, with most pronounced decrease observed until 12 to 14 cm in both EAV and SAV cells in all STAs There is little chan ge in the deeper strata corresponding to the surface soil Comparison of EAV and SAV 15 13 depth profile for all three STAs are presented in Figure 4 4. Higher 15 values suggest nutrient enrichment in the top soil layers in comparison 15 13 between EAV and SAV cells was similar to the other parameters i.e., t here

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109 was a marked difference in enrichment between EAV and SAV cells in the top soil layers. The s oil 13 profile for ST A 3/4 was dissimilar from the other two STAs such that the depth profile of EAV cell exhibited less negative values of 13 in the surface layer of EAV cells in comparison to SAV cell. This indicated enrichment (or evidence of non discrimination again st heavier C isotope) by the surface layer of EAV cells in STA 3/4 whereas in STA 1W and STA 2 this property was exhibited by SAV cells The C:N and N:P ratios in soil profiles between EAV and SAV cells for all three STAs are presented in Figure 4 5. The C :N ratio did not show much difference between EAV and SAV cell s in STA 1W and STA 3/4 ; t he EAV and SAV C:N ratio s across most of the soil profile appeared highly correlated. The N:P ratio s showed a steady increase with depth and were similar for both EAV a nd SAV cells of STA 1W and STA 3/4 however STA 2 showed marked difference between EAV and SAV cells below 5 cm depth. In most of the STAs, P in the water column is depleted p rogressively as water flows from EAV to SAV cells, which resulted in higher soil p rofile N: P ratios in SAV cells compared EAV cells This was not the case for STA 2 probably because the P loading rate s for EAV and SAV cells were similar Also, EAV and SAV cells in STA 2 are arranged as parallel one cell flow ways, and unlike the other STAs where outflow from EAV cells is the inflow to SAV cells, receive water without any pre treatment by an EAV cells Inter cell variability in s oil p hysico chemical characteristics for each cell of the three STAs is presented in Appendix D ( Figure s D 1, D 2 and D 3). Soil and Phosphorus Accretion Rates The depth of RAS was deter mined by identifying the change point (CP) in each soil core independently utilizing four variables: bulk density, total P content, 15 N and

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110 13 C ( see detailed me thodology in Chapter 3) Nutrient mass ratios ( C:N and N: P ) were also examined but the absence of a well defined CP in the soil profile s precluded their use in the analysis The mean depth of RAS as determined by CP techniqu e (CPT) was 14.7 5.1, 11 3.3 and 10 4.6 cm in STA 1W, STA 2 and STA 3/4 respectively ( Figure 4 6 ). RAS depth was significantly different between STA 1W and STA 3/4. A verage RAS depths were used to calculate soil (cm yr 1 ) and P (g m 2 yr 1 ) accreti on rates for each cell in the STAs ( Table 4 1 ) The mean values presented in this table are average s of each cell. The r elationship between soil and P accretion rates suggest ed a declining trend in P and soil accretion with time in the STAs ( Figure s 4 7 an d 4 8 ) Phosphorus Mass Balance P hosphorus mass balance s were calculated for the STAs using CP depths (Table 4 1) as a boundary indicator between RAS and pre STA soil. P hosphorus retained over the POR in STA 1W, STA 2 and STA 3/4 was 14.8, 7.0 and 4.6 g P m 2 respectively P hosphorus mass balance s for all three STAs is presented in Figure 4 9 L arge variability was observed in the flux of P from pre STA soil to RAS All three STAs experienced po sitive P flux from pre STA soil to RAS This flux was highest in STA 3/4 with the shortest operational age ( 7 years ) and low est POR P retention. Floc P storage was highest in STA 2. Discussion Considerable variability was found in the physico chemical properties along soil profiles of STA s The RAS serve s as long ter m integrator of existing conditions in wetlands ( Inglett and Reddy, 2006 ; Reddy and DeLaune, 2008 ; Smol, 1992 ) and the observed variability in STA soil characteristics could be attributed to diverse conditions

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111 in these wetlands during their operational history D ifferences observed in soil characteristics bet ween EAV and SAV cells varied from one STA to other, and insufficiently robust to conclude if these differences were due to vegetation or other confounding factors (Figure s D 1, D 2 and D 3 ; Appendix D ) Soil Physico C hemical P roperties High P concentratio ns in the surface soil of both EAV and SAV cells reflect ed high P loading and incorporation of influent P into RAS. As STA age increase d the amount of P stored in newly created soils was increasingly derived from P retained from the water column. This rel ationship was established in Chapter 2 (Figure 2 2) and evidence of P enrichment in STA surface soil was further observed when cells with different vegetation type were compared ( Figure 4 3 ) STA 1W with longest operational history (16 years) showed relat ively higher P concentrations until a depth of 12 to 13 cm, whereas in STA 2 and STA 3/4 this depth was at 8 to 10 cm (Figure 4 3) H igher bulk densities in those soil fractions resulted in higher P storages in RAS compar ed to pre STA soil S 15 N 13 displayed generally larger values in the top layers in comparison to the deeper core sections These results a re an evidence of increased nutrient inflows and reduced organic matter decomposition under saturated conditions after STA establ ishment and was attributed to increased uptake (or decreased discrimination) from the inflow water and subsequent diagenesis of dead plant matter, whose mineralized and lo st from the system The m arked difference in the heavier isotope enrichment between EAV and SAV cells was attributed to higher P loading to EAV cells in comparison to the SAV cells Soil 15 suggested increased incorporation of

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112 heavier N isotope in EAV cells while 13 suggested enhanced incorporation of heavier C isotope in STA 1W and STA 2 commensurate with the existing literature ( Inglett and Reddy, 2006 ) In STA 3/4, surface layers of EAV ce lls, however, displayed greater values of 13 than SAV cells. The a bundance of P could have triggered higher biotic productivity in the EAV cells of STAs where rapid emergent macrophyte growth constrain ed discrimination against heavier isotopes as EAV accessed atmospheric CO 2 ( 8 resulting in increase in 13 values of surface soil This reversed pattern in STA 3/4 could also be attributed to the effects of vegetation conversion where prior EAV cells were converted into SAV cells The soils in the converted cells may still have exhibit e d characteristics that were indicative of their past vegetation community Soil and Phosphorus Accretion Rates Soil accretion has been established as the long term sustainable P removal mechanism in wetland s ( Kadlec, 2009 ; Reddy and others, 1999a ) A detailed listing of methods and measured soil accretion rates from a range of freshwater and coastal wetland syste m s is prese nted in Table 3 1 ( Chapter 3) The lowest soil accretion rates (< 0.1 cm yr 1 ) were reported for bogs that received inputs from rainfall rather than surface runoff ( Cameron, 1970 ; Glaser and others, 1997 ; Moore and Bellamy, 1974 ) Accretion rates in productive wetland systems such as the northern r egion of Everglades (WCAs) have been reported as high as 1 cm or more per year ( Craft and Richardson, 1993b ; Re ddy and others, 1993 ) S tudies conducted on treatment wetlands suggest soil accretion rates ranging from 0.2 to 13.7 cm yr 1 ( CH2M.HILL, 2003 ; Coveney and others, 2002 ; Keller and Knight, 2004 ) Phosphorus accretion rates from these systems varied from 0.01 to 2.0 g P m 2 yr 1 White and others, (2001 ) reported

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113 average soil accumulation of 0.6 cm yr 1 for the Orlando Easterly Wetland, with an average P accretion rate of 0.66 g P m 2 yr 1 The Houghton Lake marsh is one of the longest running surf ace flow treatment wetlands (30+ years), and the results of a long term accretion study suggest ed sediment and P accretion rate s of 1.33 cm yr 1 and 1.5 g P m 2 yr 1 respectively ( Kadlec, 2009 ) Phosphorus accretion increases with P loading to a wetland ( Reddy and others, 1993 ) h owever, an increase in accretion does not necessarily result into low surface water outflow P concentrations, especially for intermittently flooded wetlands like the STAs where decomposition of organic detritus during periods of dryout can release lab ile P back to the water column ( Newman and Pietro, 2001 ) Studies conducted in the Everglades system have illustrated the role of calcium (Ca) in P sequestration in these wetlands ( Porter and Sanchez, 1992 ; Richardson and Vaithiyanathan, 1995 ) Soil fractionation studies ha ve shown Ca bound P t o be the major form of P i in WCA 2 soils ( Koch and Reddy, 1992 ; Qualls and Richardson, 1995 ) Phosphorus co precipitation with CaCO 3 as a n important mechanism for P removal has been prop osed in a variety of wetland systems ( Scinto, 1997 ) I n the context of the STAs it has been proposed that SAV is better suited for P removal than EAV, a hypothesis supported by studies at the mesocosm ( Dierberg and others, 2002b ) STA prototype ( Nungesser an d Chimney, 2001 ) and field scales ( Juston and De Busk, 2006 ) Soil accretion in SAV systems could therefore be a result of both Ca P co precipitation and uptake by macrophyte s. The cycle of f looded drained conditions in the STAs may not provide an opportunity for amorphous co precipitated Ca P to be co nverted into stable crystalline forms. Th is may eventually impact the long term stability of

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114 sequestered P in the STAs as Ca associated P will be prone to dissolution following redox and pH changes. Dry out conditions also promote oxygen availability in soi ls, resulting in enhanced mineralization rates and subsequent release of P ( McLatchey and Reddy, 1998 ) These processes are integrated into the soil accretion rates determined for the STAs in this study, and could be one explanation for decreasing accretion rate over time as the STAs under went multiple dry rewetting cycles resulting in soil oxidation a nd loss of labile P forms. Another explanation for the declining trend of soil and P accretion rates with increasing STA age (Figure s 4 7 and 4 8) could be compaction of old soils as new soil s accrue d on the surface of previously accumulated surface This suggests that altho ugh new soil is consistently accumulating the proportional increase in thickness of soil layers many be non linear This was supported by an experimental study conducted within the STAs, where soil accretion rates were large in the short term, but decline d over time ( Chimney and others, 2000 ) Secondly, two of the older cells in STA 1W (Cell 1B and Cell 4) were rehabilitat ed in 2005 to 2007 when a pproximately 180,000 cubic yards of P enriched floc and subsurface soil including 19 mt of P, were removed. Th e loss of this soil and associated P could have been reflected as a decrease in P and sediment accretion rates for STA 1W Phosphorus Mass Balance Th e P mass balance developed after ascertaining the boundary between RAS and pre STA soil was an improvement from the preliminary mass balance analysis ( Chapter 2) in that the former analysis account ed for P storages within RAS ins tead of a fix ed 0 10 cm surface soil section The p reliminary P mass balance ( Chapter 2 ) utilized P storages in 0 10 cm of surface soil which could have misrepresent ed P movement to

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115 or from soils to the water column and distort ed the actual amount of P th at was retained from the water column and the portion that was derived from pre STA soil The a bility to differentiate between RAS and pre STA soil P storage allow ed calculation of total P flux from pre STA soil to RAS. At any given time the vegetation bi omass represent s only a small proportion of P present in wetland storage compartments ( Faulkner and Richardson, 1989 ) hence it was not included in P mass balance calculation s for the STAs The P flux from pre STA soil to RAS wa s indicat ive of the m ining subsurface P by vegetation and deposition on the surface through detrital accumulation which eventually bec a me part of RAS ( Reddy and DeLaune, 2008 ; Reddy and others, 200 2 ) This P flux redistribut ed P within the soil profile where P from deeper soil was brought to the surf ace layer. The movement of P from pre STA to RAS involve s a series of complex biological processes involving wetland vegetation and microbial assembla ges. Summary Phosphorus retention in the STAs does not seem to be a simple straightforward process of P removal by biotic and abiotic processes, but instead is a complex interplay where redistribution and mobilization of P stocks take place within the soi l profile. Wetland vegetation play a crucial role in this redistribution of P, however clear differences on the basis of vegetation types (EAV and SAV/FAV) were not clearly observed from this experimental study. D ifferent functional forms of P undergo cons iderable transformation as P is cycled through various compartments with in wetlands ( Qualls and Richardson, 2003 ; Reddy and others, 1999a ) Such changes have a great influence on the stability of accreted P and subsequently, the overall effectiveness of the STAs This is why characterization of P stability in RAS was carried

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116 out using an operationally defined P fractionation scheme d etails of which are presented in the next c hapter ( Chapter 5 ).

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117 Table 4 1 Soil ( cm yr 1 ) and phosphorus (g m 2 yr 1 ) accretion rate s in STA 1W, STA 2 and STA 3/4 (mean sd) Vegetation STA Recently Accreted Soil depth Soil acc retion P accretion (cm) (cm yr 1 ) (g m 2 yr 1 ) STA 1W 14.7 5.1(n=28) 0.9 0.3 1.3 0.6 EAV Cell 1A 19 .3 1.2 0.46 1.6 0.88 EAV Cell 2A 16 .1 1 .0 0.1 2 .0 0.21 SAV Cell 1B 1 3.5 0.8 0.17 0.8 0.46 SAV Cell 2B 15.9 1 .0 0.34 1.7 0.66 SAV Cell 3 12.9 0.9 0.3 1.2 0.5 SAV Cell 4 10.8 0.7 0.22 0.7 0.22 STA 1W Cell 5 12 5.5 (n=12) 1.2 0.55 2 .0 1.2 EAV Cell 5A # 10 .4 1 .0 0.42 2.0 1.37 SAV Cell 5B # 12.6 1.2 0.65 2.1 1.1 STA 2 11 3.3 (n=29) 1.1 0.3 1 .9 0.9 EAV Cell 1 8. 9 1 .0 0.26 1.0 0.13 EAV Cell 2 10.5 1.0 0.26 1.6 0.41 SAV Cell 3 12.5 1.2 0.4 2.5 1 SAV Cell 4 12.9 1.3 0.94 2.7 0.94 STA 3/4 10 4.6 (n=39) 1.7 0.77 3.3 2 EAV Cell 1A 8 .2 1.4 0.48 2.7 0.9 EAV Ce ll 2A 12 .1 2.0 1.1 5.5 4.2 SAV Cell 1B 1 1.9 2.0 0.83 2.4 0.97 SAV Cell 2B 8 .5 1.5 0.46 3.8 1.5 # Cell 5A and cell 5B came online in WY2000 much later than the rest of the STA (WY1994). Number of soil cores analyzed are in parentheses.

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118 F igure 4 1. Location of the three treatment wetlands used in this study, the Stormwater Treatment Areas : STA 1W, STA 2 and STA 3/4 and the n umber of soil cores collected from each STA.

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119 Figure 4 2 Phosphorus mass balance calculations for s oil P storage wi th respect to net P retained from the water column. All values are in g P m 2 A rrows indicate flux of P between compartments. Top arrow indicates P movement from the water column to floc. Middle row arrows show P movement between floc and RAS Lower row a rrows indicate P movement from pre STA soil to RAS.

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120 Figur e 4 3 Differences in soil profile b ulk density and t otal phosphorus content between two vegetation communities, EAV and S AV in STA 1W, STA 2 and STA 3/4 Symbols represent m ean values for each p arameter Error bars represent one standard error of the mean.

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121 Figure 4 4 15 13 vegetation communities, EAV and S AV in STA 1W, STA 2 and STA 3/4. Symbols represent m ean values for each parameter Error bars represent one standard error of the mean.

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122 Figure 4 5 Differences in soil profile C: N ratio and N :P ratio between two vegetation communities, EAV and S AV in STA 1W, STA 2 and STA 3/4. Symbols represent m ean values for each parameter Error b ars represent one standard error of the mean

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123 Figure 4 6. RAS depth as determined using change point analyses for different cells of STA 1W (a) STA 2 (b) STA 3/4 (c) and for entire STA (d) Horizontal lines within boxes represent median values. Test of significance between RAS depths determined for each STA cell using a Tukey Kramer HSD test ( p< 0.05)

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124 Figure 4 7 Soil accretion rate ( cm yr 1 ) as a function of STA age for STA 1W, STA 2 and STA 3/4 Error bars represent one standard error of the mean.

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125 Figure 4 8 P hosphorus accretion rate (g P m 2 yr 1 ) as a function of STA age for STA 1W, STA 2 and STA 3/4. Error bars represent one standard error of the mean.

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126 Figure 4 9 Phosphorus mass balance calculations for soil P storage with respect to net P retained from the water column. All values are in g P m 2 Arrows indicate flux of P between storage compartments. Top arrow indicates P movement from the water column to floc. Middle row arrows show P movement between floc and RAS Lower row arrows indicate P movement from pre STA soil to RAS.

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127 CHAPTER 5 STABILITY OF PHOSPHORUS IN RECENTLY ACCRETED SOILS: ASSOCIATED VEGETATION EFFECTS Background Constructed wetlands have biogeochemical processes that result in the transformation and assimilation of pollutants. Accumulation of organic matter that forms recently accreted soil (RAS) is an example of one such assimilatory process which provides a sink for influent constituents ( Rogers, 1984 ) Characteristics of RAS in constructed wetlands are often dissimilar from antecedent soils ( White and others, 200 1 ) These differences usually arise because of the existing wetlan d vegetation, hydrologic regime nutrient and sediment loading environmental disturbance, and management intervention ( Kadlec, 2009 ; White and others, 2001 ) As such, interplay of these factors reg ulates how sequestered nutrients are distributed into pools of varying chemical stability and the extent of their recalcitrance determines constructed wetland treatment performance ( Fisher and Reddy, 2010 ) Characterization of the relative stability of sequestered nutrients in constructed wetlands is important for understanding the risk of releasing these nutrients back to the water column in response to changin g environmental conditions. This information is also crucial for planning int erventions aimed at maintaining a an extended period ( Newman and Pietro, 2001 ; Olila and others, 1997 ) The Everglades Stormwater Treatment Areas (STAs) provide a representative example of large scale constructed wetlands that were est ablished to remove excess phosphorus (P) from agricultural drainage waters originating in the Everglades Agricultural Area (EAA) ( Chimney and others, 2006 ) The long term functioning of the STAs as si nks for P is based on sustained incorporation of P in accret ed soil ( Kadlec,

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128 2009 ; Reddy and others, 1999a ; Walker and Kadlec, 2011 ) This requires the continuous accrual of P in stable fractions that are resistant to release in response to changes in environmental conditions including fluctuation in redox cond itions, pH and temperature, the availability of electron acceptors, microbial activity, and anthropogenic disturbances ( Fisher and Reddy, 2001 ; Pant and Reddy, 2001 ) The m obility and reactivity of sequestered P in the STAs are controlled by the chemical composition of P in soil and water, the relative sizes of various P pools in the soil, interactions of soluble P fractions with solid soil phases, and decomposition of soil organic matter ( Moore and others, 1998 ) Both organic and inorganic forms of P are found in wetland soils; however, the relative proportion of each of these forms depends on soil type mineral or organic, and the forms of any P added to the system. Organic P usually constitutes more than half of soil total P (TP) in wetlands ( Moore and others, 1998 ) Organic P forms extracted from mineral wetland soils include inositol phosphates, phospholipids, and nucleic acids ( Turner and others, 2006 ) whereas a significant proportion of organic P occur s as phosphodiesters or products of phosphodiester hydro lysis in organic soils ( Turner and Newman, 2005 ) As much as one third of inositol P can be complexed with humic and fulvic acids, thereby reducing the bioavailability of this soil P fraction The reactivity of organic P forms determines their movement and potential availabil ity, and has significant implications for long te rm storage of P in accreted soils in treatment wetlands. Quantification of reactive and non reactive P pools in the STAs is useful for determining the potential P flux from RAS to the overlying water column under no rmal

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129 operating conditions as well as for estimating potential P loss during changes in hydrologic condition, such as drought ( Fisher and Reddy, 2001 ) E stimates of the relative proportion of reactive and n on reactive pools in accreted P are useful in predicting sustainable P removal in the STAs and for achieving long term goals for the Everglades restoration. Soil and P accretion rates for the Evergla des STAs, and related P storage in floc, RAS and pre STA soil were d etermined in previous studies (s ee Chapter 2 and Chapter 4). These studies showed that treatment performance across the STAs have been variable although these systems have consistently removed P from the water column. The removed P has been sequestered in RAS, which forms the top 10 14 cm of P enriched surface soil in the studied STAs (STA 1W, STA 2 and STA 3/4) Objective s and Hypotheses The main objectives of this study were to determine the relative proportion of reactive and non reactive P fractions in Everglades STA s oils and assess the influence of wetland vegetation e mergent a quatic v egetation ( EAV ) and s ubmerged and floating a quatic v egetation ( SAV /FAV ) on the reactivity of these P fractions Th e operating hypothesis was that the differences in veg etation will have a pronounced effect on P processing and will actively influence the quantity of P forms in RAS. The quality and consequently the reactivity of accreted P in RAS will determine its potential mobility and impact treatment efficiency of STAs Methods Site Description Two STAs with different operational age were selected for this study: STA 1W = 16 or 10 years (depending on the cell) and STA 2 = 10 years (Figure 5 1). In STA 1W,

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130 soil samples were collected from two EAV cells Cells 3 and 5A a nd one SAV cell Cell 5B. Cells 5A and 5B were constructed later than the other cells in STA 1W and only had an operational age of 10 years. Cell 3 underwent conversion from an EAV dominated cell to a SAV cell, but was classified as an EAV cell in this st udy. In STA 2, Cells 1 and 2 were EAV while Cells 3 and 4 were SAV for the entire period of record. Soil and Chemical Analysis Intact soil cores (n =44) were collected during April to June, 2011, using a stainless steel tube (10.2 cm internal diameter [ID] ; and 0.2 cm wall thickness [WT]). The depth of soil cores ranged from 10 40 cm as limited by the depth of the bedrock from the soil surface. Soil cores were transferred into clear cellulose acetyl butyrate tubes (10.2 cm ID, 0.16 cm WT) in the field and transported to the laboratory for storage at 4 o C until they were analyzed. Initial processing involved sectioning of all cores into three layers floc, RAS and pre STA soil. Floc was collected separately after recording its depth. The remainder of each s oil core was divided into RAS and pre STA soil. The depth of RAS was the same as calculated earlier ( Chapter 3) using the change point technique. Mean RAS depths in soil cores from STA 1W and STA 2 are presented in Table D 4 in Appendix D. RAS was further divided into sections of 4 cm each (there were 2 3 4 cm sections in each soil core depending on RAS depth). The remainder of the soil core below RAS was designated as pre STA soil (antecedent native soil). Floc and s oil samples were dried at 70 o C for bulk density determination. Dried samples were finely ground using a ball mill and passed through a 2 mm sieve before chemical analysis. T otal P was determined with the ashing and HCl digestion method ( Andersen, 1976 ) using standard molybdate colorimetry for analysis ( U.S. Environmental Protection

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131 Agency, 1993 ) Total nitrogen (TN) and total carbon (TC) were determined using a Costech Elem ental Analyzer (Model 4010, Costech Analytical Industries, Inc., Valencia, CA). Elemental calibration was accomplished using peach leaves (2.93% N, 44.65% C). Metals such as calcium (Ca), magnesium (Mg), iron (Fe) and aluminum (Al) were determined in the s oil extract obtained by treating floc and soil samples with 1 M HCl fraction by inductively coupled plasma (ICP) mass spectrometry. Soil Phosphorus Fractionation Soil P fractions were measured using the simplified chemical P fractionation scheme described i n Figure 5 2 ( Ivanoff and others, 1998 ) The procedure involved sequential chemical extraction of a 1:50 dry sediment to solution mixture with: a) 1 M HCl representing inorganic P (labile P bound to Ca, Mg, Fe, and Al [P i ]), and b) 0.5 M NaOH representing organic P associated with fulvic and humic fractions (moderately to highly resistant organic P [P o ]). Soil P extracted with acid and alkali are defined as the reactive P pool. Phosphorus remaining in soil af ter the sequential extractions (residual P [Pr]) was measured by ignition and defined as non reactive P that included both organic and inorganic compounds, although little is known about the structure and chemical composition of this P fraction. Extracts f rom P fraction were centrifuged at 6000 rpm for 10 min, filtered through filter and analyzed for soluble reactive P (SRP) or digested with sulfuric acid and potassium persulfate and analyzed for TP. Solutions were analyzed by colorimetry, determi ned by reaction with molybdate using a Technicon AAII autoanalzer ( Murphy and Riley, 1962 ; U.S. EPA, 1993 ) Residual P was determined usin g an ignition method ( Andersen, 1976 ) and analyzed as described above for TP.

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132 Data Analysis The purpose of sub dividing RAS into 4 cm sections was to explore the changes in P pools at a finer depth resolution and capture the age effect manifested in deeper sediments. Hence, in a 12 cm RAS layer for example, soil characteristics close to the boundary between accreted and pre STA soi l would be different from RAS closer to the surface floc. Homogenizing the entire RAS layer for analysis could lose any depth information, and fail to capture any gradients in the various P fractions. The mass of TP for each RAS section was added to produ ce one overall value for entire RAS section. Ultimately, for data analysis, interpretation and synthesis, each site contributed a maximum of three sample points floc, RAS and pre STA soil. For sites with no floc, only two soil layers (RAS and pre STA soi l) were used. For pre STA soil, P storages were calculated for a layer 15 cm deep, while measured soil depth was used in P storage calculations for the floc and RAS fractions. Statistical analysis was performed to compare means of soil nutrients pools (TP, total nitrogen [TN], and total carbon [TC]) from STA 1W and STA 2 separately for comparisons of vegetation treatment effect. Similar comparisons were performed separately for EAV and SAV cells for each P fraction Pi, Po and Pr in floc, RAS and pre STA s oil using student's t tests assuming equal variances with a level of These analyses were carried out to explore differences in P fractions due to vegetation affects.

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133 Results Soil Physico C hemical Properties The s oil physical and chemi cal characteristics showed differences between two vegetation type (EAV or SAV) as well as among different soil core sections (floc, RAS and pre STA) when compared independently for each STA Bulk density The bulk density of floc in SAV cells of STA 1W wa s significantly greater than that of EAV cells whereas in STA 2, floc, RAS and pre STA sections displayed higher bulk density in SAV cells as compared to EAV cells (Table 5 1). Loss on Ignition The LOI in floc fraction of STA 1W sho wed a significant diffe rence between EAV and SAV cells (Table 5 2). In STA 2, LOI in EAV and SAV cells was significantly different for all soil sections. Floc samples from the SAV cell had a low mean LOI compared to the other soil sections suggesting a higher mineral fraction in floc. Total Phosphorus No significant differences in TP content were detected between STA 1W EAV and SAV cells for all soil sections(Table 5 3). In STA 2, TP content in EAV and SAV cells was significantly different for all three sections. Floc TP concent ration was lower in SAV cells whereas it was higher for RAS and pre STA soil sections when compared to EAV cells of STA 2. Total P storage pools for each soil fraction in STA 1W and STA 2 are presented in Table 5 4. Total P content and TP storages in samp les from each cell of STA 1W and STA 2 are presented in Appendix E (Tables E 4 and E 5).

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134 Total Nitrogen Results for TN in STA 1W showed a significant difference between EAV and SAV cells for floc but no differences in RAS or pre STA soil (Table 5 5). Total N content in floc and RAS was significantly different between EAV and SAV cells in STA 2 but there was no difference for pre STA soil. SAV cells had lower TN concentrations in floc and RAS compared to EAV cells in both STA 1W and STA 2. Total N storage po ols for each soil fraction for STA 1W and STA 2 are presented in Table 5 6. Average TN content and TN storages in samples from each cell of STA 1W and STA 2 are presented in Appendix E ( Tables E 6 and E 7 ). Total Carbon Results for STA 1W showed significa nt differences in TC content between EAV and SAV cells for floc but no differences in RAS or pre STA soil in EAV and SAV cells (Table 5 7). Total C content in floc, RAS and pre STA soil in STA 2 were significantly different between EAV and SAV cells. Floc TC content was lower in SAV cells compared to EAV cells of STA 1W while TC content in floc, RAS and pre STA soil of SAV cells was lower than in EAV cells of STA 2. Total C storage pools for each soil fraction for the STA 1W and STA 2 are presented in Table 5 8. Average total C and mass C storages in the samples from each cell of STA 1W and STA 2 are presented in Appendix E (Tables E 8 and E 9). Metals Comparisons between the metals content in EAV and SAV cells of STA 1W and STA 2 in all soil fract ions are p resented in Table 5 9 for Ca, Table 5 10 for Mg, Tab le 5 11 for Fe and Table 5 12 for Al. The Ca content in floc samples was significantly higher in SAV cells then in EAV cells for both STAs. The Mg content in RAS fraction of SAV

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135 cells was significantly hi gher than EAV cells of STA 2. The Fe content in pre STA samples was significantly higher in SAV cells then in EAV cells for STA 1W. Siginficant differences in Al were observed for RAS and pre STA soil between EAV and SAV cells of both STAs. Phosphorus Frac tions The relative size of the P fractions (Po, Pi and Pr) varied from one cell to another, but showed a similar pattern for floc, RAS and pre STA soil: Pi ranged from 15 45% of TP, whereas Po was 35 50% and Pr was 20 35% of TP, respectively. These results from STA 1W and STA 2 are shown in Figures 5 3 (A) and 5 4 (A) respectively and relative proportions are presented in Figures 5 3 (B) and 5 4 (B) In STA 1W, Pi content was highest in floc for the SAV cell Cell 5B whereas it was slightly lower i n floc in the EAV cell Cell 5A. Cell 3 had lower Pi content in comparison to the other two cells (Figure 5 3) The relative proportion of Po was mostly c onstant in floc, RAS and pre STA soil. Residual P was highest in RAS and pre STA soil of SAV cells (C ell 3 and Cell 5B) In STA 1W (both EAV and SAV cells combined), Pi in floc samples was 30% of TP while both RAS and pre STA soil was 27% of TP as Pi. Organic P in floc was 41%, and 37% and 40% of TP in RAS and pre STA soil respectively. In STA 2, the re lative proportion of Pi was highest in floc for the SAV cells Cell 3, whereas it was lower for floc in EAV cells (Cell 1 and Cell 2) (Figure 5 4). The relative proportion of Po was higher in floc, RAS and pre STA soil of EAV cells compared to SAV cells. Residual P was in the same range for floc, RAS and pre STA soil In STA 2s (both EAV and SAV cells combined), t he Pi in floc samples was 30% of the TP. RAS

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136 and pre STA soil had 26% and 25% of TP respectively. Organic P in floc was 40% of TP, and 40% and 52 % of TP in RAS and pre STA soil respectively. Vegetation E ffects Significant differences were observed between EAV and SAV cells when both STAs were analyzed together, such that EAV floc (Po) was greater than SAV floc SAV RAS (Pi) was greater than EAV RA S and SAV pre STA (Po and Pr) was greater than EAV pre STA fraction ( Table 5 13 ) Individually, STA 1W showed higher Po content in EAV floc in comparison to SAV floc, and higher Po content in SAV pre STA sections (Tables 5 14). The relative proportion of P r was lower for EAV cells in STA 1W in comparison to SAV cells. In STA 2, floc Po was higher in EAV cells in comparison to SAV floc Po (Table 5 15) For RAS fraction Pi content was significantly higher in SAV cells. Pre STA soil had significanty higher Pi Po and Pr fractions in SAV cells compared to EAV cell s Residual P was found to be almost equal in both EAV and SAV cells of both STAs except for pre STA soil section of STA 2. (Table 5 15) To assess the influence of SAV and EAV on partitioning P into v arious fractions, Pi and Po content was plotted against TP concentration for all soil sections pooled over both STAs by vegetation type (Figures 5 5 and 5 6). No clear difference between SAV and EAV cells was detected in either STA. However, the Pearson co rrelation coefficient, calculated separately for EAV and SAV cells using pooled data from both STAs, showed that Pi is strongly correlated with TP in SAV cells while Po is strongly correlated with TP in EAV cells. The r eactive P constituted 75% of TP in fl oc sections of EAV cells and 62% of TP in SAV cells (Figure 5 7). In RAS, reactive P was 64% of TP for EAV and 67% of TP for SAV cells. However, floc and RAS sections of EAV cells showed higher Po fractions (50% and 40% of TP, respectively) compared to SAV (23% and 37%

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137 of TP, respectively). Pre STA soil was similar for EAV and SAV cells, with a higher proportion of reactive P fractions distributed as organic P (65% and 78%, respectively). Correlations A mong Soil Properties Correlations among various soil p arameters for all soil fractions from both STA 1W and STA 2 are shown in Table 5 16. Positive correlations were observed between Pi and Ca (r = 0.54) and Mg (r =0.31) whereas negative c orrelations were found between P i and Fe (r = 0. 3 7) and Al (r = 0.20 ). I ron and Al were negatively correlated with TP, Pi and Po. Total P and Pr had low but significant correlations with Ca. Inorganic P was significantly correlated with more STA soil parameters compared to Po EAV Cells : Correlations among various soil paramet ers for all soil fractions from EAV cells of both STA 1W and STA 2 are shown in Table 5 17. High positive correlation were observed between TP and Po (r=0.90) whereas no correlation was found between Ca and Po. Negative correlations were found between TP a nd Fe (r = 0.58) and Al (r = 0.46). SAV Cells : Correlations among various soil parameters for all soil fractions from SAV cells of both STA 1W and STA 2 are shown in Table 5 18. High positive correlation were observed between TP and Pi (r=0.80) and Ca and Pi (r=69). Negative correlations were found between TP and Fe (r = 0.56) and Al (r = 0.39 ). STA 1W : Correlations among various soil parameters for STA 1W are shown in Table 5 1 9 Positive correlations were observed between Pi and Ca (r = 0.58) and Mg (r =0. 44). Negative correlations were found between TP and Fe (r = 0.68) and Al (r = 0.57). A negative correlation was also observed between Pi and Al (r = 0.36). Total P was significantly correlated with Ca (r = 0.46) and Mg (r =0.26). Iron and Al were

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138 positivel y inter correlated. No correlation was found between Po with Ca or Mg. No significant correlation was found between TP and TN. Correlation matrices elucidating relationships within SAV and EAV cells in STA 1W are presented in Tables E 16 and E 17 ( Appendix E ) STA 2 : Correlations among various soil parameters for STA 2 are shown in Table 5 20 The highest correlations were between Pi and Ca (r = 0.61) and Mg (r =0.36). Negative correlations were found between TP and Fe (r = 0.51) and Al (r = 0.40). There was no correlation between Pi and Al; however, Pi and Fe were negatively correlated (r =0.33). Iron and Al were positively inter correlated. Total P was significantly correlated with Ca (r = 0.30) but not with Mg. Organic P was negatively correlated with Mg (r = 0.37) but no correlation was observed for Po with Ca. Negative correlations were found between TP and TN (r = 0.31) and TC (r = 0.51). Correlation matrices elucidating relationships within SAV and EAV cells in STA 2 are presented in Tables E 18 and E 19 ( Appendix E ) Discussion About thirty percent of TP is present in non reactive P fraction for different soil sections (floc, RAS and pre STA soil ; Figure 5 18). Data range is limited in p re STA soil, and showed no difference between two vegetation types (EAV and SAV) Flo c and RAS fractions were, however, more variable and exhibited a greater range of TP values. The h igh conce nt ration of Pi in the near surface soil suggests that P i may be loosely bound to organic matter, bound to solid phases such as CaCO 3 or present as recently precipitated, amorphous, mono calcium phosphate.

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139 Given the important role Ca plays in the retention of P in wetlands with alkaline soils, the relationship between Ca and TP in floc, RAS and pre STA soil was explored for STA 1W in Figure 5 9 (n=50) and for STA 2 in Figure 5 10 (n=75). Pre STA soil showed no difference between SAV and EAV cells and were clustered together for both STAs (Figures 5 9 and 5 10) RAS samples, from both SAV and EAV cells, were located in the center of gr aph s with intermediate TP and Ca values. Floc samples exhibited greatest dissimilarity between SAV and EAV cells and the distinct clusters for each vegetation were separated apart in plot s for STA 1W and STA 2 (Figures 5 9 and 5 10). SAV Cell 5A ( STA 1W ) h ad higher Ca concentration per unit of P in comparison to EAV cells. However, f loc characteristics of SAV Cell 3 (STA 1W) which underwent conversion from EAV to SAV, were similar to EAV cell possibly due to as an EAV cell. In STA 2, EAV c ells had higher TP content in floc in comparison to SAV cells. SAV cells showed relationship between soil TP and Ca indicating that P movement into floc is controlled by Ca and could be a co precipitation mechanism induced by epiphyton periph yton assemblag es in open water. It also suggested that SAV cells had a higher proportion of Pi in floc fracti ons in comparison to EAV cells. P ositive correlation between Pi with Ca and Mg suggest that P i dynamics in STA soils are governed by Ca and Mg. Earlier P sorptio n studies conducted in the EAA and WCAs also show positive relationships between P sorption and Ca ( Porter and Sanchez, 1992 ; Richardson and Vaithiyanathan, 1995 ) When explored separately for each soil section floc, RAS and pre STA, the vegetation effects on P fractions for STA 1W were found to be insignificant except for Po in floc and the pre STA soil. For STA 2, significant differences were observed

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140 between EAV and SAV cells for floc, RAS and pre STA soil. A s ignificant difference was observed in floc section for Po fractions between EAV and SAV. Organic P was higher in floc of EAV cells. For RAS sectio ns, P i was significantly higher in SAV cells. Pre STA soil fractions indicated higher Pi, Po and P r fractions in SAV cells in comparison to EAV cells. The comparison across two studied STAs is confounded by the fact that these two system were considerably dissimilar due to different hydraulic and P loading, basin characteristics, vegetation coverage, and management interven tions Reactions that fix P in wetland soils include precipitation of Fe with hydroxide and phosphate in aerobic pore waters ( Fox, 1989 ) the formation of the ferrous phosphate mineral vivianite in the anaerobic zone ( Emerson and Widmer 1978 ; Manning and others, 1991 ; Woodruff and others, 1999 ) and co precipitation of phosphate with calcite in hard water systems ( House and Denison, 1997 ; Koschel and others, 1983 ; Kch ler Krischun and Kleiner, 1990 ) Higher Pi levels in RAS suggest re mineralization of labile Po, and retention of P i through adsorption and precipitation. Precipitation of P with Fe 3+ could be enhanced by a fluctuating water table, which these STAs regul arly experienced except for SAV cells where high water levels are actively managed (although sections of SAV cells also experience dry conditions during severe droughts) Water level drawdown and soil drainage are commonly used in treatment wetlands to c onsolidate flocculated material, accelerate soil accretion, and allow access for maintenance operations ( Kadlec and Wallace, 2009 ) This could result in releasing Pi to the water column upon re flooding ( Newman and Pietro, 2001 ; Olila and others, 1997 ) Drying and rewetting can also release Po through microbial cell lysis ( Turner and Haygarth, 2001 ) while redox changes could destabilize Po complexed with Fe A recent

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141 study, explored four different management options for enhancing SRP removal by treatment wetland soils ( Li ndstrom and White, 2011 ) These authors compared physical and chemical treatments such as dry down, surface additions of alum or calcium carbonate (CaCO 3 ) and physical removal of the accreted organic soil as a potential means to reduce P flux from the so ils. The results demonstrated organic soil layer removal and surface alum addition as the most effective options. Summary Soil P, not extracted by either acid or alkali, is considered as residual P and operationally defined as nonreactive P. For all practi cal purpos es, nonreactive P is unavailable for biotic or abiotic transformations. Approximately 25 30% of soil TP in the STAs was non reactive The stability of this fraction can be attributed to the presence of P associated with highly stable organic mate rials such as lignin and organometallic complexes. P hosphorus enriched STA soils (floc and RAS) typically contained less T P in the non reactive pool than did pre STA soil In this study, the Pi and Po fractions in floc and RAS sections together accounted f or 65 70% of al l TP stored in soil. This P can be classified as reactive, and it is prone to be released into the water column when environmental conditions become favorable. A sizeable pool of reactive P in STA soils, presents a risk for disrupting treatm ent efficiency of STAs and, if released into the water column it could result in P impacts downstream. The l ong term stability of P in treatment wetlands is dependent on the relative proportion of non reactive P. Exploration of P accretion and partitioning in various fractions as a function of STA age could provide insights on how the stability of P fractions varies over time.

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142 Table 5 1 Summary statistics for bulk density of soil sections in EAV and SAV ce lls of STA 1W and STA 2 and results of t tests o f differences between vegetation communities. Bulk Density (g cm 3 ) Avg sd (n) STA 1W STA 2 EAV # SAV P value EAV SAV P value Floc 0.09 0.04 (9) 0.15 0.05 (7) 0.021 0.06 0.03 (14) 0.12 0.01 (7) < 0.00 1 *** RAS 0.27 0.06 (10) 0.32 0.05 ( 7) 0.123 ns 0.22 0.07 (14) 0.28 0.07 (13) 0.022 Pre STA soil 0.31 0.05 (10) 0.28 0.04 (7) 0.205 ns 0.17 0.1 (14) 0.29 0.09 (13) 0.004 ** (* for P<0.05, ** for P<0.01 and *** for P<0.001 ns= not significant ; two sample t test, assuming equa l variance) # STA 1W Cell 3 analyzed as EAV cell. Table 5 2 Summary statistics for loss on ignition of soil sections in EAV and SAV ce lls of STA 1W and STA 2 and results of t tests of differences between vegetation communities Loss on Ignition ( % ) Avg sd (n) STA 1W STA 2 EAV # SAV P value EAV SAV P value Floc 80 4 (9) 66 6 (7) <0.001 *** 72 12 (14) 29 6 (7) < 0.00 1 *** RAS 83 7 (10) 84 4 (7) 0.891 ns 85 4 (14) 69 13 (13) < 0.00 1 *** Pre STA soil 89 2 (10) 88 4 (7) 0.348 n s 87 1 (14) 75 22 (13) 0.038 (* for P<0.05, ** for P<0.01 and *** for P<0.001 ns= not significant ; two sample t test, assuming equal variance) # STA 1W Cell 3 analyzed as EAV cell

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143 Table 5 3 Summary statistics for total phosphorus content of soil sections in EAV and SAV ce lls of STA 1W and STA 2 and results of t tests of differences between vegetation communities. TP (mg kg 1 ) Avg sd (n) STA 1W STA 2 EAV # SAV P value EAV SAV P value Floc 1052 361 (9) 924 176 (7) 0.405 ns 1097 248 (14 ) 766 293 (7) 0.014 RAS 561 268 (10) 509 125 (7) 0.645 ns 384 114 (14) 608 175 (13) 0.001 ** Pre STA soil 294 125 (10) 364 108 (7) 0.247 ns 197 45 (14) 318 114 (13) 0.001 ** (* for P<0.05, ** for P<0.01 and *** for P<0.001 ns= no t significant ; two sample t test, assuming equal variance ) # STA 1W Cell 3 analyzed as EAV cell Table 5 4 Summary statistics for total p hosphorus storage pools for each soil fraction in EAV and SAV ce lls of STA 1W and STA 2. TP (g P m 2 ) STA 1 W STA 2 EAV SAV EAV SAV (Avg sd) Cell 5A Cell 3 Cell 5B Cell 1 Cell 2 Cell 3 Cell 4 Floc 9.3 2.2 5.8 1.8 8.1 3.9 6.2 2.4 4.7 3.3 7.5 3.9 -RAS 17.8 13.3 12.8 4.6 15.5 6.6 5.7 2 9.8 3.2 13.5 5.4 18.8 5.4 Pre STA soil 19.7 7.9 8.7 1.3 15.5 6.5 3.6 0.7 6.8 5.9 11.5 6.6 17.1 9.5

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144 Table 5 5 Summary statistics for total nitrogen content of soil sections in EAV and SAV cells of STA 1W and STA 2 and results of t tests of differences betwe en vegetation communities TN (g N kg 1 ) Avg sd (n) STA 1W STA 2 EAV SAV P value EAV SAV P value Floc 31 3 (9) 28 3 (7) 0.021 26 4 (14) 12 2 (7) <0.001 *** RAS 32 7 (10) 33 3 (7) 0.900 ns 30 2 (14) 26 5 (13) 0.019 Pre STA soil 32 3 (10) 34 3 (7) 0.254 ns 28 1 (14) 30 5 (13) 0.259 ns (* for P<0.05, ** for P<0.01 and *** for P<0.001 ns= not significant ; two sample t test, assuming equal variance ) Table 5 6 Summary statistics for total n itrogen storage poo ls for each soil fraction in EAV and SAV ce lls of STA 1W and STA 2. TN (kg Nm 2 ) STA 1W STA 2 EAV SAV EAV SAV (Avg sd) Cell 5A Cell 3 Cell 5B Cell 1 Cell 2 Cell 3 Cell 4 Floc 0.2 0.1 0.3 0.2 0.2 0.1 0.2 0.1 0.1 0.1 0.1 0 -RAS 0.9 0.5 0.9 0.3 1 0.3 0.5 0.2 0.7 0.2 0.7 0.4 0.8 0.3 Pre STA soil 1.5 0.2 1.4 0.2 1.4 0.2 0.6 0.1 0.8 0.5 1 0.2 1.5 0.3

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145 Table 5 7 Summary statistics for total carbon content of soil sections in EAV and SAV cells of STA 1W and STA 2 and results of t tests of differences between vegetation communities TC (g/kg) Avg sd (n) STA 1W STA 2 EAV SAV P value EAV SAV P value Floc 416 34 (9) 356 37 (7) 0.004 ** 369 50 (14) 196 21 (7) <0.001 *** RAS 4 69 78 (10) 454 21 (7) 0.627 ns 447 20 (14) 384 63 (13) 0.001 ** Pre STA soil 485 15 (10) 477 15 (7) 0.306 ns 472 11 (14) 421 77 (13) 0.020 (* for P<0.05, ** for P<0.01 and *** for P<0.001 ns= not significant ; two sample t test, assumi ng equal variance ). Table 5 8 Summary statistics for total carbon storage pools for each soil fraction in EAV and SAV ce lls of STA 1W and STA 2. TC (kg C m 2 ) STA 1W STA 2 EAV SAV EAV SAV (Avg sd) Cell 5A Cell 3 Cell 5B Cell 1 Cell 2 Cel l 3 Cell 4 Floc 3 0.6 3.7 2.4 3 1.2 2.2 0.8 1.6 1 1.9 0.5 -RAS 13.8 5.8 12.6 3.8 13.7 3.7 7.6 2.3 10.4 2.9 10.2 5.3 11.4 4.8 Pre STA soil 23.6 3.7 21 2.7 19.7 2.9 9.6 1.6 14 9.1 13.7 2 2 2.1 3.5

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146 Table 5 9. Summary statistics for calcium content of soil sections in EAV and SAV cells of STA 1W and STA 2 and results of t tests of differences between vegetation communities. C alcium ( g Ca kg 1 ) Avg sd (n) STA 1W STA 2 EAV SAV P value EAV SAV P value Floc 36.5 9.5 (9) 82.1 13.6 (7) <0.001 *** 43.5 18 (14) 198.1 38.2 (7) <0.001 *** RAS 39.3 15 (10) 43.9 12.3 (7) 0.516 ns 35.6 9.5 (14) 96.6 55.5 (13) <0.001 *** Pre STA soil 29.2 6.6 (10) 36.3 18.7 (7) 0.279 ns 29 5.7 (14) 32.2 10 (13) 0.302 ns (* for P<0.05, ** for P<0.01 and *** for P<0.001 ns= not significant ; two sample t test, assuming equal variance). Table 5 10 Summary statistics for magnesium content of soil sections in EAV and SAV cells of STA 1W and STA 2 and results of t tests of differences between vegetation communities Magnesium (g Mg kg 1 ) Avg sd (n) STA 1W STA 2 EAV SAV P value EAV SAV P value Floc 2.6 0.7 (9) 3.4 1 (7) 0.075 ns 3.1 3.9 (14) 6.2 1.7 (7) 0.054 ns RAS 3.1 0.6 (10) 2.7 0.4 (7) 0.214 ns 3.5 0.4 (14) 5.5 1.1 (13) <0.001 *** Pre STA soil 2.4 0.5 (10) 2.1 0.8 (7) 0.369 ns 3.1 0.6 (14) 3 0.8 (13) 0.670 ns (* for P<0.05, ** for P<0.01 and *** for P<0.001 ns= not significant ; two sample t test, ass uming equal variance).

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147 Table 5 11 Summary statistics for iron content of soil sections in EAV and SAV cells of STA 1W and STA 2 and results of t tests of differences between vegetation communities Iron ( mg Fe kg 1 ) Avg sd (n) STA 1W STA 2 EAV SAV P value EAV SAV P value Floc 210 74 (9) 208 92 (7) 0.965 ns 211 219 (14) 128 99 (7) 0.356 ns RAS 718 357 (10) 1082 424 (7) 0.074 ns 515 222 (14) 471 324 (13) 0.682 ns Pre STA soil 1183 308 (10) 1749 417 (7) 0.006 ** 748 301 (14) 990 412 (13) 0.092 ns (* for P<0.05, ** for P<0.01 and *** for P<0.001 ns= not significant ; two sample t test, assuming equal variance). Table 5 1 2 Summary statistics for aluminum content of soil sections in EAV and SAV cells of STA 1W and STA 2 and results of t tests of differences between vegetation communities Aluminum ( mg Al kg 1 ) Avg sd (n) STA 1W STA 2 EAV SAV P value EAV SAV P value Floc 413 147 (9) 604 319 (7) 0.132 ns 279 429 (14) 184 157 (7) 0.581 ns RAS 754 125 (10) 11 67 234 (7) <0.001 *** 1362 690 (14) 899 412 (13) 0.046 Pre STA 795 135 (10) 1150 238 (7) 0.001 ** 723 259 (14) 1815 1181 (13) 0.002 ** (* for P<0.05, ** for P<0.01 and *** for P<0.001 ns= not significant ; two sample t test, assuming equa l variance).

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148 Table 5 13. Summary statistics for phosphorus content in P fractions in floc, RAS and pre STA soil from EAV and SAV cells in STA 1W and STA 2 and results of t tests of differences between vegetation communities Both STAs (mg kg 1 ) Floc R AS Pre STA soil Avg sd (n) EAV SAV P value EAV SAV P value EAV SAV P value Pi 269 151 (23) 332 154 (14) 0.232 ns 104 107 (24) 174 101 (20) 0.033 55 73 (24) 94 68 (20) 0.075 ns Po 528 210 (23) 192 93 (14) <0.001 *** 186 69 (24) 207 104 (20) 0.425 ns 101 32 (24) 166 46 (20) <0.001 *** Residual P 241 94 (23) 214 54 (14) 0.339 ns 146 57 (24) 171 92 (20) 0.285 ns 70 27 (24) 109 45 (20) 0.001 ** (* for P<0.05, ** for P<0. 01 and *** for P<0.001, ns= not significant ; two sample t test, assuming equal variance ).

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149 Table 5 1 4 Summary statistics for phosphorus content in P fractions in floc, RAS and pre STA soil from EAV and SAV cells in STA 1W and results of t tests of differences between vegetation communities STA 1W (m g P kg 1 ) Floc RAS Pre STA soil Avg SD (n ) EAV SAV P value EAV SAV P value EAV SAV P value Inorganic P ( Pi ) 287 198 (9) 305 61 (7) 0.817 ns 160 137 (10) 125 49 (7) 0.531 ns 91 100 (10) 80 56 (7) 0.802 ns Organic P (P o ) 539 244 (9) 240 105 (7) 0.009 ** 192 89 (10) 204 31 (7) 0.756 ns 98 25 (10) 174 28 (7) <0.001 *** Residual P 240 127 (9) 208 69 (7) 0.553 ns 146 70 (8) 130 43 (7) 0.612 ns 69 17 (10) 108 57 (7) 0.058 ns (* for P<0.05, ** for P<0. 01 and *** for P<0. 001, ns= not significant ; two sample t test, assuming equal variance ). Table 5 15 Summary statistics for phosphorus content in P fractions in floc, RAS and pre STA soil for EAV and SAV cells in STA 2 and results of t tests of differences between vegetati on communities STA 2 (mg P kg 1 ) Floc RAS Pre STA soil Avg SD ( n ) EAV SAV P value EAV SAV P value EAV SAV P value Inorganic P ( Pi ) 258 115 (14) 359 198 (7) 0.178 ns 65 54 (14) 200 109 (13) 0.001 ** 30 28 (14) 102 72 (13) 0.002 ** Organic P (P o ) 521 189 (14) 145 47 (7) <0.001 *** 182 53 (14) 209 124 (13) 0.470 ns 104 35 (14) 162 51 (13) 0.002 ** Residual P 241 70 (14) 220 37 (7) 0.481 ns 147 47 (14) 193 100 (13) 0.151 ns 71 32 (14) 110 39 (13) 0.012 (* for P<0 .05, ** for P<0. 01 and *** for P<0.001, ns= not significant ; two sample t test, assuming equal variance ).

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150 Table 5 1 6 Pearson c orrelation coefficients for select parameters measured in all soil fractions in both STA 1W and STA 2 A ll correlations evaluated =125). ns=not significant. Both STAs Bulk density TP Ca Mg Fe Al Pi TN TC Po LOI TP 0.49 Ca ns 0.28 Mg ns ns 0.57 Fe 0.60 0.53 0.35 0.16 Al 0.50 0.41 0.28 ns 0.49 Pi 0.22 0.77 0.54 0.3 1 0.37 0.20 TN 0.18 0.21 0.72 0.56 0.39 ns 0.49 TC 0.26 0.48 0.76 0.51 0.47 0.16 0.66 0.87 Po 0.49 0.78 ns 0.27 0.38 0.33 0.37 ns ns LOI ns 0.36 0.79 0.54 0.38 0.16 0.58 0.77 0.88 ns P r 0.42 0.78 0.31 ns 0.42 0.2 8 0.61 0.22 0.49 0.59 0.41

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151 Table 5 1 7 Pearson c orrelation coefficients for select parameters measured in all soil fractions in EAV cells from both STA 1W and STA 2 A ll correlations = 56 ). ns=not significant. EAV cells (both STAs) Bulk density TP Ca Mg Fe Al Pi TN TC Po LOI TP 0.46 Ca ns 0.39 Mg ns ns 0.56 Fe 0.53 0.58 ns 0.24 Al 0.31 0.46 ns 0.36 0.41 Pi ns 0.76 0 .58 ns ns 0.23 TN ns 0.23 0.59 0.63 ns ns 0.34 TC 0.47 0.76 0.70 0.42 0.44 0.27 0.68 0.61 Po 0.53 0.90 ns 0.32 0.63 0.49 0.53 ns 0.54 LOI 0.33 0.63 0.80 0.56 0.27 ns 0.64 0.67 0.95 0.37 P r 0.47 0.78 0.37 ns 0.51 0. 26 0.58 ns 0.70 0.68 0.60

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152 Table 5 1 8 Pearson c orrelation coefficients for select parameters measured in all soil fractions in SAV cells from both STA 1W and STA 2 A ll correlations = 69 ). ns=not significant SAV cells (both STAs) Bulk density TP Ca Mg Fe Al Pi TN TC Po LOI TP 0.56 Ca 0.33 0.42 Mg ns 0.24 0.71 Fe 0.64 0.56 0.53 0.47 Al 0.62 0.39 0.45 ns 0.50 Pi 0.35 0.80 0.69 0.45 0.50 ns TN 0.20 0.24 0.80 0.62 0.46 ns 0.60 TC 0.29 0.43 0.79 0.59 0.53 ns 0.71 0.94 Po 0.38 0.59 ns ns ns ns ns 0.25 ns LOI 0.25 0.35 0.79 0.59 0.50 0.22 0.65 0.83 0.87 ns P r 0.45 0.80 0.38 0.25 0.42 0.32 0.63 0.27 0.44 0.57 0.39

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153 Table 5 1 9 Pearson correlation coefficients for select parameters measured in all soil fractions from STA 1W All correlations =50). ns=not significant STA 1W Bulk density TP Ca Mg Fe Al Pi TN TC Po LOI TP 0.70 Ca ns 0.46 Mg ns 0.26 0.58 Fe 0.70 0.68 0.37 0.41 Al 0.62 0.57 ns ns 0.73 Pi 0.36 0.80 0.58 0.44 0.51 0.36 TN ns ns 0.45 0.50 0.24 ns 0.45 TC 0.35 0.61 0.67 0.38 0.47 0.33 0.66 0.73 Po 0.68 0.80 ns ns 0.49 0.46 0.50 ns 0.35 LOI 0.40 0.73 0.88 0.51 0.60 0.40 0.72 0.44 0.80 0.30 P r 0.62 0.82 0.31 ns 0.53 0.55 0.57 ns 0.50 0.63 0.59

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154 Table 5 20 Pearson correlation coefficients for select parameters measured in soil fractions from STA 2 All correlati ons ). ns=not significant. STA 2 Bulk density TP Ca Mg Fe Al Pi TN TC Po LOI TP 0.42 Ca ns 0.30 Mg ns ns 0.54 Fe 0.49 0.51 0.39 ns Al 0.55 0.40 0.32 ns 0.62 Pi ns 0.75 0.61 0 .36 0.33 ns TN ns 0.31 0.79 0.51 0.38 0.24 0.65 TC ns 0.51 0.78 0.48 0.43 ns 0.75 0.90 Po 0.41 0.77 ns 0.37 0.33 0.32 0.28 ns ns LOI ns 0.34 0.78 0.50 0.28 ns 0.65 0.84 0.89 ns P r 0.29 0.77 0.35 ns 0.33 0.25 0.65 0.32 0.51 0.56 0.40

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155 Figure 5 1. Location of soil sampling sites in the STAs. Field triplicate sites are shown in red boxes. (Map source SFWMD)

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156 Figure 5 2. Phosphorus f ractionation scheme used to characteriz e P forms in STA soils Modifie d from Ivanoff and others, (1998 )

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157 A B Figure 5 3 Phosphorus fractions (organic [Po] inorganic [Pi] and residual P [Pr] ) in floc, RAS and pre STA soil in STA 1W. A) Total P content. B) R elative proportion of P fractions

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158 A B Figure 5 4 Phosphorus fractions (organic [Po] inorganic [Pi] and residual P [Pr] ) in floc, RAS and pre STA soil in STA 2. A) Total P content. B) Relative proportion of P fractions

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159 Figure 5 5 Inorganic P [Pi] content plotted against TP for all soil sections in EAV and SAV cells from STA 1W and STA 2 Figure 5 6 Organic P [Po] content plotted against TP in EAV and SAV cells from STA 1W and STA 2

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160 Figure 5 7 Percent composition of stable and reactiv e phosphorus pools in the floc, RAS and pre STA soil of EAV and SAV cells pooled over both STA 1W and STA 2

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161 Figure 5 8 Non reactive phosphorus ( stable P) as a fraction of total phosphorus in floc, RAS and pre STA soil of STA 1W and STA 2

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162 Figur e 5 9 Relationship between phosphorus (mg P kg 1 ) and calcium (g Ca kg 1 ) in EAV and SAV cells of STA 1W. Open symbols represent EAV cells and closed symbols represent SAV cells. (n=50). For regression line n= 35, P value < 0.05.

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163 Figure 5 10 Relation ship between phosphorus (mg P kg 1 ) and calcium (g Ca k g 1 ) in EAV and SAV cells of STA 2. Open symbols represent EAV cells and closed symbols represent SAV cells. (n=75) For regression line n= 33, P value < 0.01.

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164 CHAPTER 6 CONCLUSIONS Constructed treatme nt wetlands are dynamic ecosystems primarily established in urban or agricultural watersheds to treat nutrient/ contaminant rich water. These systems are attractive because of their low cost and ability to provide additional ecosystem services. Often these systems are evaluated simply by monitoring inflow and outflow contaminant concentrations with limited information about the internal processes regulating contaminant removal transformation or retention in the system The lack of detailed information on nutrient cycling among different wetland compartments (including water column, plant biomass, surface litter and soil) result in ck that is generally used to evaluate t performance ( Zurayk and others, 1997 ) An in depth understanding of interactions between the biogeochemical processes responsible for water treatment could aid in performance optimization, reduction in op erational costs, and prediction of future treatment responses to varied operating conditions. Thi s dissertation research is one attempt towards advancing our understanding about the main processes regulating treatment efficiency of constructed wetlands. This was done by quantifying changes in various nutrient storage pools in soils and using this info rmation to understand the biogeochemical processes and transformations that take place in wetland soils. Specifically, by measuring the quantity and chemical stability of soil phosphorus (P) fractions, the long term sustainable performance prospect of trea tment wetlands were examined. Free water surface treatment wetlands located in southern Florida were selected as the main sites for this study. These wetlands, referred to as the Everglades

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165 Stormwater Treatment Areas (STAs), were strategically located in s everal agricultural watershed s to remove excess P in surface runoff originating from agricultural farms. In context of the STAs, understanding the internal processes that regulate treatment efficiency is of great importance (and urgency) because these syst ems not only represent a huge financial investment but the legally mandated water treatment goals and the ecological risks to the Everglades of ineffective treatment are very high. By investigating the storage and movement of P fractions within STA soil l ayers, an attempt was made to recognize factors that control and regulate important biogeochemical processes that affect long term removal efficiency and P storage in treatment wetland s. Th e value of this research is enhanced by the fact that the results c an be directly applied to enhance treatment efficiency of the STAs W etland soils are the main repository of removed nutrients (particularly P), therefore this dissertation started with quantification of soil nutrient storage pools and examined how those p ools changed over time, and ultimately established relationship s between soil nutrient storage and STA age ( Chapter 2). This was followed by developing a simple change point technique (CPT) to aid in measur ing of soil and P accretion rates in treatment wet lands ( Chapter 3). The boundary betwe en recently accreted soils (RAS ) and pre STA soil was identified by CPT. S oil accretion rates in STAs were determined by utilizing depth of RAS layer from the surface and the STA age where as P mass in RAS was used to c alculate P accretion rates. Subsequently P mass storages in floc, RAS and pre STA soil were calculated and P mass balance s were developed for STA 1W, STA 2 and STA 3/4 ( Chapter 4). Long term sustainable P removal depends on the stability of accreted P, he nce chemical characterization of

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166 accreted P in STA soils was performed ( Chapter 5). In the following sections of this chapter each dissertation research objective presented i n the I ntroduction ( Chapter 1) is re evaluated in the context of the knowledge ga ined from this research and the goal of having better understanding of P removal mechanisms in treatment wetlands. This research was guided by following objectives and supporting hypotheses Objective 1: Review available datasets on STA soil physico chemi cal variables and dete rmine spatio temporal changes in surface and sub surface soil nutrient storage. Explore relationship between hydraulic and water quality param eters, soil nutrient storages and STA age Perform preliminary P mass balance using these da ta ( Chapter 2). protracted period of operation. Objective 2: Determine the soil accretion rate in the STAs by utilizing stratigraphic characteristics of the soil profile s to i dentify the boundary between recently accreted soil (RAS) and antecedent pre STA soil ( Chapter 3). Hypothesis: The STAs are accreting systems and accumulating organic matter conserves attributes of prevailing conditions ( e.g. nutrient loading, vegetation c ommunity). Changes in t hese stratigraphic characteristics can be exploited to identify the dept h of RAS deposited on top of pre STA soil Objective 3: Explore the relationship between soil accretion rates and operational age of the STAs. Perform P mass bal ance using P storages in RAS and pre STA soil and the amount of P removed from the water column. Determine P cycling within different P storage compartments of the STAs ( Chapter 4). Hypothesis: Most of the P retained from the water column is stored in RAS which has a higher P concentration than pre STA soil With increasing age, the rate of soil and P accretion declines, resulting in higher outflow P concentration s Internal re distribution of P within RAS and pre STA soil is mediated by vegetation. This c ontrols whether the STAs function as a nutrient source or sink Objective 4 : Determine the relative proportion of reactive and non reactive P pools in the STAs. Assess the influence of wetlands vegetation communities (EAV vs. SAV) on reactivity of P pools ( Chapter 5) Hypothesis: Different vegetation type s (EAV vs. SAV) will influence the proportion of P forms incorporated in to RAS and sequestered in the STAs. The p resence of more reactive ( i.e., potentially mobil e ) P forms will reduce the long term sustai nability of the STAs

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167 Objective 1: Spatio Temporal Changes i n Soil Nutrient Storages A n inventory of nutrients (P, N and C) stored in STA soils was developed by review ing all existing data on floc and soil nutrient storage s and subsequent ly explor ing chang es in those pools over time Phosphorus concentration and storage within various compartments of the STAs the water column, floc (unconsolidated detritus ), surface soil (0 10 cm), and sub surface soil (below 10 cm) were determined. Analysis of the physic o chemical attributes of STA soils allowed investigation of tempo ral changes in nutrient storage and examination of relationships between changes in nutrient storage with respect to STA performance and operational age ( Chapter 2). Annual P storage rates d eclined with increasing STA operational age, although the proportion of P stored in surface soil increasingly came from P retained from the water column over time. The decline in P storage rates could indicate that accumulation of refractory organic P frac operational history. Continued P loading of the STAs resulted in an increased proportion of soil P pools being derived from P retained from the water column. Temporal changes in P storage within the active compartments of the STAs were used to generate estimates of P flux between these compartments and develop an overall P mass balance O ver the period of STA operation it was observed that surface soils of STAs changed from being a source into net si nk for P However, this analysis was restricted to P storage within the top 10 cm of surface soil, which may not have included the entire depth of RAS, hence conclusions drawn from these data are more ges. Subsequently, a more complete mass balance was developed after identification of the boundary between RAS and pre STA soil ( Chapter 4).

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168 Objective 2: Soil Accretion i n Treatment Wetlands Soil accretion is related to the performance of treatment wetlan ds as soils provide a long term sink for various pollutants. Knowledge of soil accretion rates in the STAs is important to quantify P mass storages accurately and develop robust mass balance s; however it was difficult to measure accretion rates in the abs ence of a marker horizon. Therefore, a novel analytical technique CPT, was developed by exploiting the stratigraphic characteristics of RAS. This allowed for identification of the boundary between RAS and pre STA soil, and hence RAS depth in three STAs of varying age STA 1W, STA 2 and STA 3/4 ( Chapter 3) Objective 3: S oil Accretion and Operational Age of Treatment Wetlands S oil a ccretion is the long term sustainable mechanism for removal of nutrients (specifically P in this case) in wetlands; however, it remains the least investigated component of treatment wetland performance ( Kadlec and Wallace, 2009 ) Changes in soil accretion rates with increasing operational age of the STAs were evaluated. Wetland soils aggregat e biotic and abiotic processes hence results from this study were useful in understand ing some of the biogeochemical processes that control and regulate P removal in the STAs Soil and P accretion rates were determined using RAS depths identified with C PT ( Chapter 2). A declining trend in s oil and P accretion rates with increasing age was observed for STA 1W, STA 2 and STA 3/4 which had operational ages of 16, 11 and 7 years respectively ( Chapter 4). Th is confirme d the hypotheses that w ith increasing age, the rate of soil and P accretion d eclines Developing reliable P mass balances for these wetlands required accurate estimates of soil accretion rates a nd associated soil P storages The a bility to differentia te between P storages in RAS and pre STA with reasonable confidence

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169 allowed calcul ation of total P flux from pre STA soil into RAS. The results of P mass balance s developed using this approach ar e presented in Chapter 4 High P flux from pre STA soil to RAS was indicative of the role of vegetation in mining subsurface P and deposition o n the surface through detrital accumulation which eventually becomes a part of RAS ( Reddy and DeLaune, 2008 ; Reddy and others, 2002 ) The movement of P from pre STA to RAS layer involve d a series of complex biological processes including growth senescence and decomposition of wetland vegetation and microbial assemblages. Objective 4: Stability of Phosphorus in Recently Accreted Soil P hosphorus s equestered in wetlands that can be mobili zed in response to changes in nutrient concentration gradients or changes in physical and chemical conditions (such as redox, electron acceptors and hydrologic regimes) is considered reactive Reactive P that becomes bio available can have adverse ecologic al impacts. It therefore was important to investigate the composition and stability of P in RAS to determine the long term efficacy of P retention in the STAs Chemical characterization of P present in STA soils was carried out using an operationally defin ed fractionation scheme modified from Ivanoff and others, (1998 ) P hosphorus enriched STA surface layers (floc and RAS) contained a high er proportion of reactive P than did pre STA soil Thi s reactive pool was comprised of Pi and Po fractions that together accounted for 65 70% of all TP in floc and RAS. Investigation s of the influence of vegetation type on partitioning of P found significant effect on Pr fraction. The relative proporti on of P r was lower in EAV cells compared to SAV cells in STA 1W, whereas no vegetation effect was observed for Pr in STA 2 ( Chapter 5).

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170 A separate evaluation of floc, RAS and pre STA soil found that the influence of vegetation type on P fractions in STA 1W were n ot significant except for differences in Po in floc and pre STA soil. For STA 2 significant differences in P fractions were observed between EAV and SAV cells for floc (Po), RAS (Pi) and pre STA soil (Po, Pi and P r ) ( Chapter 5). Phosphorus mass balance s s uggested that a large portion of P in RAS was mined from pre STA soil Fractionation analysis indicated that about 70% of P in RAS was reactive and potentially could be mobiliz ed This highlights the risk of P loss from the STAs following changes in the en vironment (e.g., redox and pH changes, availability of electron acceptors, etc.). A decline in soil accretion rate was observed with increasing STA operation age of, which raise d an important question regarding continued performance of the STAs. Without co ntinued high rates of soil accretion, the treatment performance o f the STAs could diminish Synthesis Phosphorus retention pathways in treatment wetlands are comprised of complex biotic and abiotic processes. This complexity is mainly due to multiple physi cal, biological and chemical mechanisms that interact simultaneously to provide treatment. These reactions result in removal of P from the water column, conversion of constituents from dissolved to particulate and inorganic to organic forms and vice versa ( R eddy and DeLaune, 2008 ) Along with these conversions, mobilization of sequestered P and redistribution of P pools within the soil profile also take place. While P is cycled through various storage compartments within wetlands, different functional forms of P undergo transformations ( Koch and Reddy, 1992 ; Newman and Pietro, 2001 ; Qualls and Richardson, 2003 ; Reddy and others, 1999a ) Such changes influence the stability

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171 of accreted P and overall treatment performance in wetlands. The main goal of this stud y was to understand the impacts of operational age, hydraulic and P loading rates, dominant vegetation type on regulation of the stability of accreted P in treatment wetlands. These efforts were aimed to understand how these factors may have affected treat ment perform ance and long term fate of P in the STAs A summary based on the outcomes of this dissertation research at one site (STA 2) is presented in Figure 6 1 (A= E AV cells and B= SAV cells). This synthesis highlight s the passage that influent P takes as it is removed from the water column and eventually is stored as accreted soil in EAV and SAV cells The schematic indicates the partitioning of accreted P into reactive and non reactive forms within the main storage compartments of STA soils. Phosphorus loading rates experienced by EAV cells were slightly lower than in SAV cells for the POR and the annual rate of P retention (water column to floc) was similar for both vegetation types. However, the annual P accretion rate to RAS in SAV cells was twice th at of EAV cells. Comparison of the proportion of reactive and non reactive P in floc, RAS and pre STA soil found a higher percentage of reactive P throughout the soil profile. A greater proportion of reactive P (Pi and Po fractions combined) was observed i n the floc and RAS of SAV cells compared to EAV cells, i.e., floc and RAS of SAV cells contained a larger proportion of P that was prone to mobilization in response to changes in environmental conditions than in EAV cells. P ositive correlations between TP and Ca in floc and RAS suggested Ca P co precipitation as an important mechanism of P removal in SAV cells Among reactive P pools, the proportion of Pi was higher in SAV cells while Po was greater in EAV cells

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172 Residual P comprised 30 35% of TP in floc an d RAS of both vegetation types. Only Pr can be considered as truly removed from the standpoint of future bio availability There is insufficient knowledge regarding the unde rlying reasons for the chemical stability of P r pool in wetlands and further studie s are necessary to identify reasons that impart chemical stability. With advanced scientific techniques such as nuclear magnetic resonance (NMR) and X ray Absorption Near Edge Structure (XANES) absorption spectroscopy, the elemental composition and the str ucture of the stable P fraction could possibly be determined ( Cheesman and others, 20 12 ) With regard to continued P removal by STAs factors that promote the transformation of retained P into non reactive forms need to be further investigated Future Outlook and S ustainability of STAs The ecosystems of south Florida are hydrologically l inked, beginning from the headwaters of the Kissimmee River and ending with Florida Bay and the Florida Keys. Human perturbation has caused many social, economic and environmental impacts on this system. The impacts of agricultural drainage waters from the Everglades Agricultural Area (EAA) on the Water Conservation Areas and the southern Everglades have received much attention, and the six STAs constructed to remedy some of those problems. STAs represent a huge financial commitment in terms of initial cap i tal costs and annual operating and management costs. Although, cumulatively the STA s removed 1500 mt of P ( Ivanoff and others, 2012 ) which otherwise would have adverse ly impact ed t he Everglades ecosystem, there are multiple issues that bring the long term sustainability of the STAs and the stability of their sequestered P into question

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173 First, declining trend in soil and P accretion rates with increasing age as observed f or STA 1W, STA 2 and STA 3/4 is an indicator of slow down of P removal rates. With STA age decrease in the quantity of TP retained from the water column could result in failure to meet legally stipulated outflow P concentration. Second, an independent econ omic analysis conducted by the National Research Council found that the cost of P removal by the STAs is $ 240 kg 1 ( Council, 2011 ) w hich escalates to $600 $1200 when the proportion of P r in RAS (30 10 %) is conside red Such high cost for storage of P in non reactive fractions may require greater financial investments, which may not be readily available in the current economic environment. The environmental risk s associated with the potential mobilization and release of reactive P from the STAs to the downstream Everglades remains a grave concern Third a vast amount of P exists both in the native soils and has been imported into the Everglades basin as fertilizer, and the STAs potential to remove P in runoff is not limit less. The total quantity of P fertilizer applied in the EAA greatly exceeds the design parameters used to estimate P removal by STAs ( Reddy and others, 2011 ) The STAs have been loaded with P for many years now and floc and RAS which exist as an interface with overlying water column have higher TP concentration than pre STA soil Fourth p romotion of best management practices upstream of the STAs may result i n decreasing P concentration in inflow waters, however the introduction of low P concentration water to the STAs could cause P flux from the soil back to the overlying water column ( Reddy and others, 2012 )

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174 Fifth south Florida is prone to extreme weather events such a s tropical storms and droughts, and based on recent weather trends, it is not difficult to conclude that the probability of such events reoccurring in future is high. The existing safe guards against these extreme events are less than adequate for existing network of six S TAs. Hurricanes have caused considerable damage to vegetation in some STA cells, necessitating costly rehabilitation efforts to bri ng those cells back online. STA managers face increasingly tough challenges to keep STA cells hydrated during summer months when water demand throughout the District soars. During large rain events when huge volumes of water pass through STAs scouring chan nels and negatively impacting system hydraulics The flooding situation however might improve after the construction of C omp artments B and C (Figure 1 3) are completed which will provide more storage capacity and control in the timing and volume of flow through the STAs. Sixth a is missing. One option is to transport STA soil with its sequestered P out of the Everglades basin, but the economic implications for such action could be very high. If P is translocated within the basin then it will only delay the ecological consequences unless adequate measures are taken to prevent remobilization. During years 2005 2007, rehabilitation of STA 1W resulted in the removal of approximately 18 0,000 yd 3 of floc and subsurface soils, equivalent to 19 mt of P in which soil was disposed in a manner that precluded its P from reaching the Everglades Some experts have even suggested reopening the STAs for farming. Recently accreted organic soils wit h high quantities of P could serve as productive agricultural soils. Another option is in situ immobilization by application of specialized chemicals that have high affinity for P.

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175 However, these steps can be seen as very practical, particularly when the e conomics of treatment footprint of 18,000 ha. Although the above mentioned points may seem to suggest a bleak outlook where long term sus tainability of the STAs is concerned there are benefits that the STA s provide. Other than being the best substitute for natural wetlands that were once part of the historical landscapes, the STAs offer other benefits that go beyond the ir main function of P removal. For instance, the STAs provide high quality habitat for fi sh, birds and other wildlife and fulfill ecological functions in the landscape. The accreted soil of STAs sequesters C and N along with P. Calculations for surface soil (10 cm) suggested that the STAs store thousands of metric tons of C ( Chapter 2, Table 2 8). When nutrient removal costs fo r both C and N are included in total costs then the per unit cost of P removal does not appear so high. STAs already provide popular recreation activities such as bird watching, photography, fishing and hunting. The vast amount of data that has been collected from regular monitoring of the STAs could be mined to enhance the design of interventions that improve P removal in the STAs and other treatment wetlands. The role of STAs in reduction of P inputs to the Everglades a nd the success of Everglades restoration efforts cannot be overstated. In light of the knowledge gained from this dissertation on the quantity and quality of sequestered P, further steps can be taken to improve the efficiency and future of these large trea tment wetlands.

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176 A B Figure 6 1. Summary of total phosphorus (TP) loading rates, TP accretion rates and distribution of reactive and non reactive TP pools in floc, recently accreted soils (RAS) and pre STA soil. A) Emergent aquatic vegetation. B) Subm erged aquatic vegetation cells of STA 2.

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177 APPENDIX A ADDITIONAL DATA AND INFORMATION PERTAINING TO CHAPTER 1 Table A 1. Treatment Wetlan d Technology conferences Source: ( Kadlec and Wallace, 2009 ) Year Location Title (Proceedings) 1976 Ann Arbor, Michiga n Freshwater Wetland and Sewage Effluent Disposal 1978 Tallahassee, Florida Environmental Quality Through Wetlands Utilization 1978 Lake Buena Vista, Florida Wetland Functions and Values 1979 Higgins Lake, Michigan Freshwater Wetland and Sanitary Was tewater Disposal 1979 Davis, California Aquaculture Systems for Wastewa ter Treatment 1981 St. Paul, Minnesota Wetland Va lues and Management 1982 Amherst, Massachusetts Ecological Considerations in Wetlands Treatment of Municipal Wastewaters 1986 Orlan do, Florida Aquatic Plants for Water Treatment and Res ource Recovery 1988 Chattanooga, Tennessee 1st International Conference on Constructed Wetlands f or Wastewater Treatment 1989 Tampa, Florida Wetlands: Concerns and Successes 1990 Cambridge, United Kingdom 2nd International Conference on Constructed Wetlands for Water Pollution Control 1991 Pensacola, Florida Constructed Wetlands for Wat er Quality Improvement 1992 Columbus, Ohio INTE COL Wetlands Conference 1992 Sydney, Australia 3rd International Conference on Wetland Systems for W ater Pollution Control 1994 Guangzhou, China 4th International Conference on Wetland Systems for W ater Pollution Control 1994 Atlanta, Georgia On Site Wastewater Treatment; 7th Symposium on Individual and Small Commu nity Sewage Systems 1995 T ebo Czech Republic Nutrient Cycling and Retention in Wetlands and Their Use for Wastewater Treatment 1996 Vienna, Austria 5th International Conference on Wetland Systems for Water Pollution Control 1996 Niagara on the Lake, Ontario Constructed Wetlan ds in Cold C limates 1997 Romulus, Michigan Constructed Wetlands for the Treatment of Landfill Leachates

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178 Table A 1. Continued. Year Location Title (Proceedings) 1997 T ebo Czech Republic Nutrient Cycling and Retention in Natural an d Constructed We tlands 1998 Aguas de So Pedro, Brazil 6th International Conference on Wetland Systems for Water Pollution Cont rol 1998 Orlando, Florida On Site Wastewater Treatment; 8th Symposium on Individual and Small Co mmunity Sewage Systems 1999 Salt Lake City, Ut ah Wetlands and Remediation 1999 T ebo Czech Republic Transformations of Nutrients in Natural an d Constructed Wetlands 1999 Baltimore, Maryland Wetlands for Wastewater Recycling 1999 Tartu, Estonia Constructed Wetlands for Wastewater Treatment in Co ld Climates 2000 Quebec, Canada INTE COL Wetland s Conference 2000 Orlando, Florida 7th International Conference on Wetland Systems for Water Poll ution Control 2001 Burlington, Vermont Wetlands and Remed iation II 2001 T ebo Czech Republic Wetlands: Nutrients, Me tals, and Mass Cycling 200 1 Fort Worth, Texas On Site Wastewater Treatment: 9th Symposium on Individual and Small Community Sewage Systems 2002 Dar es Salaam, Tanzania 8th International Conference on Wetland Systems for W ater Pollution Control 2003 Borov Lada, Czech Republic N atural and Constructed Wetlands: Nutrients, Metals, and Management 2003 Tartu, Estonia Constructed and Riverine Wetlands for Optimal Control of Wastewater at Catchment Scale 2003 Lisbon, Portugal The Use of Aquatic Macrophytes for Wastewater Treatment in Constru cted Wetlands 2004 Wexford, Ireland Nutrient Management in Agricultural Watersheds: A Wetlands Solution 2004 Avignon, France 9th International Conference on Wetland Systems for W ater Pollution Control 2005 Ghent, Belgium 1st Wetland Polluta nt Dynamics and Control (WETPOL) 2006 T ebo Czech Republic Wastewater Treatment, Plant Dynamics, and Management in Constructed and Natural Wetlands 2006 Lisbon, Portugal 10th International Conference on Wetland Systems for Water Poll ution Control 2007 Padua, Italy Multi Functions of Wet lan d Systems 2007 Tartu, Estonia 2nd Wetland Pollutant Dynamics and Control

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1 79 APPENDIX B ADDITIONAL DATA AND INF ORMATION PERTAINING TO CHAPTER 2 STA Description Stormwater Treatment Area 1 East (STA 1E) is located northeast of the Arthur R. Marshall Loxaha tchee National Wildlife Refuge ( LNWR ) in Palm Beach County, FL an d began operation in WY2005. This STA has three flow ways ( East, Central, and West) covering approximately 2,104 ha. STA 1E has been adversely affected by high hydraulic loading during storm events (in WY 2006), water control structur e failures, topographic issues (Cells 5 and 7), dryout of cells during regional drought (WY2009) and vegetation die off Through WY2012, STA 1E has treated over 600,000 ac ft of water and retained approximately 94 mt of TP ( Ivanoff and others, 2012 ) The period of record ( POR ) inflow flow weighted mean ( FWM ) TP c oncentration was 176 g L 1 while the POR outflow FWM TP concentration was 57 g L 1 ( Ivanoff and others, 2012 ) Stormwater Treatment Area 1 West (STA 1W) began operation in WY1995 and is located northwest of the Arthur R. Marshall LNWR It has three flow ways totaling 2,700 ha of effective treatment area: East (Cell s 1A, 1B and 3), West (Cell s 2A, 2B and 4), and North (Cells 5A and 5B). The East and West Flow ways were formerly known as the Everglades Nutrient Removal Project ; the North Flow way was added in WY2000. Cell s 1 and 2 were reconfigured in WY 2007, creating Cell s 1A, 1B, 2A and 2B. S upplemental water has been delivered from Lake Okeechobee to maintain hydration during dry months To date STA 1W has treated over 3.3 million ac ft of water and retained approximately 480 mt of TP ( Ivanoff and others, 2012 ) The POR mean inflow FWM TP concentration was 171 g L 1 while the POR mean outflow FMW TP conce ntration was 51 g L 1 ( Ivanoff and others, 2012 ) Over its period of operation,

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180 STA 1W has been impacted by extreme weather events (regional drought s and tropical storm s ) construction activities, and high hydraulic and nutrient loadings STA 1W underwent a substantial rehabilitation and enhancement effort during 2005 2007. Approximately 180,000 yd 3 of P enriched floc and surface soil w ere removed from Cell s 1B and 4. This resulted in a total removal of 19 mt P from STA 1W The WY2007 soil phosphorus storage (SPS) values in Table 2 9 reflect P storage before soil removal, while soil samples collected in WY2008 represent post rehabilitation SPS. The observed decrease in SPS in the later samples could be attributed to the rehabilitation activities. Stormwater Treatment Area 2 (STA 2) is located in western Palm Beach County immediately west of WCA 2A. STA 2 original ly consisted o f three one cell flow ways (Cells 1, 2 and 3) wi th a combined 2,565 ha of effective treatment area and began operation in the WY 2000. The treatment area was expanded by 770 ha with the construction of Cell 4, which became operational in December 2006. Compartment B construction will add approximately 2, 760 ha of additional treatment area to STA 2 From WY2000 WY2012, STA 2 has treated over 2.8 million ac ft of water and retained approximately 269 mt of TP ( Ivanoff and othe rs, 2012 ) The POR inflow FWM TP concentration was 102 g L 1 while the POR outflow FWM TP conce ntration was 22 g L 1 ( Ivanoff and others, 2012 ) Stormwater Treatment A rea 3/4 (STA 3/4) is located northeast of the Holey Land Wildlife Management Area and north of WCA 3A It has a total treatment area of 6,691 ha and receives runoff originating within the S 2/7, S 3/8, S 236 and C 139 basins and water releases from Lake Ok eechobee STA 3/4 has three flow ways : East

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181 (Cells 1A and 1B), Central (Cells 2A and 2B) and West (Cells 3A and 3B) Since it began operation in October 2003, STA 3/4 has treated approximately 3.7 million ac ft of runoff, retaining over 440 mt of TP, and r educing the FWM TP concentration from 114 g L 1 at the inflow to 18 g L 1 at the outflow ( Ivanoff and others, 2012 ) Similar to the other STA s, STA 3/4 has been impacted by extreme weather events (regional drought s and tropical storm s ) and high hydraulic loadings during the wet season. The WY2011 dry season r esulted in a complete dry out of all cells in STA 3/4 in June 2011. Stormwater Treatment Area 5 (STA 5) totals 2 46 5 ha and is located west of Rotenberger wildlife management area It is divided into three west to east oriented flow ways each with two cells. STA 5 began operation in WY1999. Since WY2000, STA 5 has treated over 1.2 million ac ft of runoff water and reta ined approximately 212 mt of TP. The POR inflow FWM TP was 225 g L 1 and the POR outflow FWM TP concentration was 93 g L 1 ( Ivanoff and others, 2012 ) Over its period of operation, STA 5 has been impacted by high inflow nutrient concentrations and extreme weather events (regional drought s and tropical storm s ). Stormwater Treatment Area 6 (STA 6) is the smallest of the six STAs with a footprint of 915 ha. It is divided int o three east to west oriented flow ways each with only one cell. The two sou thernmost cells Cells 3 and 5 comprise Section 1 while the northern Section 2 has only Cell 2 which was added in WY2007. The completion of Compartment C construction will connect STA 5 and STA 6 and they may be identified as STA 5/6 in the future The POR inflow TP FWM concentration in STA 6 was 100 g L 1 and POR outflow FMW TP concentration was 3 4 g L 1 ( Ivanoff and others, 2012 )

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182 Table B 1 Mean total nitrogen concentration in floc and soils in STAs ( g N kg 1 ; mean 1 SD). Values represent entire floc depth and the top 10 cm of surface soil W Y STA 1E STA 1W STA 2 STA 3/4 STA 5 STA 6 Floc 2003 ----30 5 -2007 15.1 0* 23 2 14 3 18 2 28 2 -Soil 1995 -28 2 ----1996 -32 4 ----2000 -30 3 ----2001 --3 0 -26 6 13 3 2003 ----22 7 -2004 -28 3 28 3 -23 7 21 6 2005 5.9 5.1 --26 5 --2006 -27 3 ----2007 5.6 4.8 26 7 28 2 25 5 21 6 -2008 -28 4 ----# Total nitrogen concentration for floc was not available for STAs 1W, 2, 5 and 6 during WY2004.

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183 Table B 2. Mean total carbon concentration in floc and soils in STAs ( g C kg 1 ; mean SD). Values represent entire floc depth and the top 10 cm of surface soil Year STA 1E STA 1W STA 2 STA 3/4 STA 5 STA 6 Floc 2003 ----389 56 -2007 274 13 242 32 275 22 375 28 -Soil 1995 -360 12 ----1996 -510 46 ----2000 -483 40 ----2001 --466 9 -381 80 169 46 2003 ----312 91 -2004 -467 47 419 55 -322 102 266 79 2005 87 76 --391 85 --2006 -450 38 ----2007 82 71 398 69 452 38 381 79 297 94 -2008 -450 60 ----# Total carbon concentration for floc was not available for STA 1W, 2, 5 and 6 during WY2004.

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184 Table B 3 STA performance for WY2011 (May 1, 2010 April 30, 2011) and the period of record (POR) 1994 2011. Source: ( Ivanoff and others, 20 12 ) STA 1E STA 1W STA 2 STA 3/4 STA 5 STA 6 All STAs Effective Treatment Area in Permit (acres) 5,132 6,670 8,240 16,543 6,095 2,257 44,937 Adjust ed Effective Treatment Area (acres) a 4,881 6,670 7,406 16,543 5,660 1,584 42,744 Rainfall Total Annual Rainfall (inches) 34.0 b 35.0 b 38.1 40.2 39 42.2 b 38.1 South Florida Water Management Model (SFWMM) Simulation Rainfall Range (inches) 39.8 77.5 36.6 7 7.4 35.4 71.6 32.3 70.7 38.6 61.4 46.8 57.6 --Inflow Total Inflow Volume [acre feet (ac ft)] 35,616 125,933 170,838 303,447 26,609 72,722 735,165 Total Inflow total phosphorus (TP) Load [metric ton (mt)] 4.955 23.461 15.248 26.208 5.258 10.141 85.271 Flow weighted Mean (FWM) Concentration Inflow TP [parts per billion (ppb)] 113 151 72 70 160 113 94 Hydraulic Loading Rate (HLR) [centimeters per day (cm/d) d 0.61 1.58 1.93 1.53 0.39 3.83 1.44 TP Loading Rate (PLR) [grams per square meter per year (g/m 2 /yr)] d 0.25 0.87 0.51 0.39 0.23 1.58 0.49 Outflow Total Outflow Volume (ac ft) 25,758 126,881 159,914 312,067 24,319 74,591 723,530 Total Outflow TP Load (mt) 0.691 3.99 3.049 6.305 1.42 2.317 17.772 FWM Concentration Outflow TP (ppb) 22 25 15 16 47 25 20 Outflow Plus Diversion Structures FWM TP (ppb) 22 25 15 17 47 25 20 Hydraulic Residence Time (days) 49 27 23 28 13 5 --TP Retained (mt) 4.264 19.471 12.199 19.903 3.838 7.824 67.499 TP Removal Rate (g/m 2 /yr) 0.22 0.72 0.41 0.3 0.17 1.22 0.39 Loa d Reduction (percent) 86% 83% 80% 76% 73% 77% 79% Period of Record Performance Start Date Sep 04 Oct 93 Jun 99 Oct 03 Oct 99 Oct 97 1994 2011 Total Inflow Volume (ac ft) 563,131 3,160,086 2,568,599 3,369,553 1,182,264 671,380 11,515,014 Total TP Load R etained to Date (mt) 84.469 465.434 250.619 400.612 205.029 64.132 1,470.30 FWM Concentration TP Outflow to Date (ppb) 62 52 23 17 95 33 38

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185 Table B 3 Continued. a Adjusted effective treatment areas (AETA) reflect treatment cells temporarily off line for plant rehabilitation, infrastructure repairs, or Long Term Plan (LTP) enhancements (see Table 5 4 in Volume I, Chapter 5 for more info rmation about the operational status of the STAs). AETA = # days online/365 (for each flow way or cell) (effective treatment area for each flow way or cell) then add the AETAs for all cells in each STA b The total annual rainfall received by the STA w as below the range of values used to develop the interim effluent limits ( IELs ) c SFWMM South Florida Water Management Model. d Inflow volume or TP load/adjusted effective treatment area.

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186 APPENDIX C ADDITIONAL DATA AND INF ORMATION PERTAINING TO C HAPTER 3 Table C 1. Number of 2 cm sections produced by sectioning soil cores collected from sampling locations in STA 1W. (Total 733 core sections) Cell 1A 129 Cell 2A 78 Cell 3 97 Cell 5A 86 1B# 15 2F 19 3B 24 5A112 16 1B(i) 23 2Q 18 3I 21 5A112(a) 18 1I 24 2Q(a) 20 3I(a) 16 5A112(b) 16 1I (a)* 22 2Q(b) 21 3I(b) 17 5A150 17 1I (b)* 23 3P 19 5A74 19 1P 22 Cell 1B 85 Cell 2B 70 Cell 4 74 Cell 5B 114 1AB 12 2AB 17 4C 13 5B 108 21 1AB(a) 19 2U 16 4F 16 5B 125 12 1AB(b) 16 2U(a) 18 4 F(a) 14 5B 125(a) 14 1AE 17 2U(b) 19 4F(b) 16 5B 125(b) 14 1T 21 4J 15 5B 162 19 5B 202 18 5B 83 16 # This s ite was located in a canal so another soil core [ 1B(i) ] was collected 3 m away from the canal *(a) and (b) indicat e replicate soil cores collected from th is site Table C 2 Number of 2 cm sections produced by sectioning soil cores collected from sampling locations in STA 2.. (Total 505 core sections ) Cell 1 106 Cell 2 201 Cell 3 105 Cell 4 93 A103 20 B117 22 C129 18 D111 8 A103 (a)* 15 B151 20 C165 15 D124 19 A103 (b)* 20 B187 20 C201 16 D124 (a) 15 A138 21 B26 17 C21 13 D124 (b) 21 A172 16 B31 23 C75 18 D129 18 A51 14 B31(a) 22 C75 (a) 16 D139 12 B81 22 C75 (b) 9 B98 14 B98(a) 21 B98(b) 20

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187 Table C 3. Number of 2 cm sections produced by sectioning soil cores collected from sampling locations in STA 3/4. (Total 573 core sections ) Cell 1A 138 Cell 1B 177 Cell 2A 133 Cell 2B 125 1A 19~ 2 1B 24 9 2A 1 19 2B 13 8 1A 2 1 11 1B 28 13 2A 12 7 2B 17 6 1A 3 8 1B 4 10 2A 16 13 2B 17(a) 7 1A 32 11 1B 52 6 2A 24 5 2B 17(b) 7 1A 32 (a)* 12 1B 52(a) 12 2A 24(a) 7 2B 21 11 1A 32 (b)* 14 1B 52(b) 7 2A 24(b) 6 2B 24 16 1A 36 6 1B 56 17 2A 28 4 2B 28 8 1A 48 14 1B 60 19 2A 28(a ) 5 2B 3 7 1A 52 9 1B 60(a) 20 2A 28(b) 5 2B 40 8 1A 52(a) 8 1B 60(b) 17 2A 38 9 2B 44 8 1A 52(b) 8 1B 8 7 2A 42 7 2B 44(a) 11 1A 56 10 1B 80 17 2A 5 13 2B 44(b) 12 1A 7 9 1B 84 12 2A 53 14 2B 55 8 1A 71 9 1B 87 11 2A 53(a) 3 2B 59 8 1A 74 7 2A 57 16 ~ Soil cores too sh ort to be considered for analysis (a) and (b) depicts two replicates collected from same site.

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188 Figure C 1. Soil core sampling locations in each cell of STA 1W (Base map source: SFWMD)

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189 Figure C 2. Soil core sampling lo cations in each cell of STA 2. (Base map source: SFWMD)

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190 Figure C 3. Soil core s ampling locations in each cell of STA 3/4 (Base map source: SFWMD).

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191 APPENDIX D ADDITIONAL DATA AND INF ORMATION PERTAINING TO CHAPTER 4 Soil Profiles Difference betwee n Operational Cells STA 1W Soil physico chemical parameters along the soil profile were averaged over each 2 cm strata in all soil cores from each cell of STA 1W (Figure D 1) Since not all cells in STA 1W became operational at the same time difference s i n cell age and could be responsible for the variability observed in different parameters. Cell s 2B and 4 underwent significant rehabilitation work during WY 2006 2007 including tilling and removal of surface soil therefore s oil 15 and 13 valu es for soil cores from these two cells were not determined Higher bulk density in the top layers of C ell s 4 and 2B (Figure D 1 (a) ) could be a result of compaction from earth moving equipment used during rehabilitation activities, or consolidation and co mpaction caused by other processes. The concentration of T P was highest on the surface and showed decrease with increasing depth in all STA 1W cells (Figure D 1 ( b ) ) T his could be attributable to the fact that surface soil layer interacts with the over lyi ng water column, periphyton and floc and often serve as a major repository of P inputs to the system, while deeper soil layers experience P depletion as a result of P mining by plants. Except for C ell 1B, all cells in STA 1W showed greater values for 15 N in the upper soil layers (approximately 10 12 cm) relative to deeper sections (Figure D 1 ( c ) ). Cells 3 and 13 C greater values in the top soil layers whereas Cells 1B and 5A show ed lesser enrichment near the soil surface (Figure D 1(d) ) I n comparison to other cells Cell 5B (SAV) showed decrease in the 13 C values The average soil

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192 C: N ratio in all cells of STA 1W was relatively constant with depth (Figure D 1 (e)). However, average N: P ratio of soil cores in STA 1W showed an incre asing trend with depth (Figure D 1 ( f ) ). STA 2 V arious physico chemical parameters along soil profile were averaged over each 2 cm strata in all soil cores collected from each cell of STA 2 (Figure D 2) Cell s 1, 2 and 3 had been in operation since WY 2000 while C ell 4 was still in its stabilization phase as late a s WY2007 (3 years before soil sampling) Differences in cell age could account for some of the variability in various parameters among the cells Bulk density was low in the top soil layers which increased in deeper layers (Figure D 2 ( a) ) Cell 1 and 2 had considerably lower bulk density at depth compared to C ell s 3 and 4. Total P decreased with depth. This could be attributable to the fact that surface soil layer interacts with the over lying wate r column, periphyton and floc and often serve as a major repository of P inputs to the system, while deeper soil layers experience P depletion as a result of P mining by plants (Figure D 2 ( b) ) Total P in surface layers was relatively higher in C ell s 1 a nd 2 (EAV) compared to C ell s 3 and 4 (SAV). All cells of STA 2 had higher 15 N values in the top 10 12 cm of soil (Figure D 2 ( c ) ). However, only the top soil layers of Cell s 3 and 4 (SAV cells) exhibited greater 13 C whereas Cell s 1 and 2 (EAV cel ls) did not show this trend (Figure D 2 (d) ). The reason for divergent trend in 13 C values for EAV and SAV cells can be attributed to differences in C processing by different vegetation types in these cells. The C: N mass ratio was relatively constant with increa sing depth across all cells (Figure D 2 ( e) ). However, N: P ratio s in Cell s 1 and 2 showed a consistent increasing trend with the

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193 depth while Cell s 3 and 4 exhibited a decreasing N:P ratio after 20 2 5 cm (Figure D 2 ( f) ) T h e varying trends seen in the deeper soil depths could reflect past land use prior to the establishment of the STAs STA 3/4 V ariation with depth among different soil physico chemical parameters in all soil cores collected from STA 3/4 is shown in Figure D 3. C ell 1B function ed as an EAV cell for most of its operational history before it was conver ted to SAV cell in WY2008. Soil sampling was carried out WY2010. Therefore, the variability observed in surface soil in this cell may be a result of changed vegetation as a consequence of new hydroperiod Bulk density showed a consistent increasing trend with soil depth in all cells ex cept for a small increase around 19 21 cm (Figure D 3 (a) ) Cell 1B had lower bulk density compar ed to C ells 1A, 2A and 2B. Total P decreased with depth wi th relatively higher TP values in the surface layers Cell s 1A and 2A (EAV) than in C ell s 1B and 2B (SAV) (Figure D 3 (b)). Cell s 1A and 2A were enrich ed for heavier 15 N in the top soil layers down to 8 cm, below which the soils from all four cells had 15 N content (Figure D 3 (c) ) Cell s 1 A 2A and 2B had greater 13 C values in the surface layers whereas C ell 1B showed no increase in 13 C values in the top soil sections (Figure D 3 (d)). Carbon:nitrogen mass ratios were relatively uniform with depth across all cells (Figure D 3 (e) ) However, N : P ratio, in all cells generally increas ed with depth (Figure D 3 (f) ) although the N : P ratio in c ell s 2A and 2B decreased after 27 cm and 2 1 cm depth respectively.

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194 Table D 1. STA 1W soil c ore collection sites by vegetation type and cell. A total of 41 soil cores were collected from these locations EAV EAV EAV SAV SAV SAV EAV Conversion Cell 1A Cell 2A Cell 5A Cell 2B Cell 4 Cell 5B Cell 3 Cell 1B 1B # 2F 5A112 2AB 4C 5B108 3B 1AB 1B(i ) 2Q 5A112(a) 2U 4F 5B125 3I 1AB(a) 1I 2Q(a) 5A112(b) 2U(a) 4F(a) 5B125(a) 3I(a) 1AB(b) 1I (a)* 2Q(b) 5A150 2U(b) 4F(b) 5B125(b) 3I(b) 1AE 1I (b)* 5A74 4J 5B202 3P 1T 1P 5B83 5B162 # This s ite was located in a canal so another soil core (1B(i)) was collected 3 m away from the canal (a) and (b) indicate replicate soil cores collected from th is site. Table D 2. STA 2 soil core collection sites by vegetation type and cell. A total of 29 soil cores were collected from these locations EAV EAV SAV SAV Cell 1 Cell 2 Cell 3 Cell 4 A103 B117 C129 D111 A103(a)* B151 C165 D124 A103(b)* B187 C201 D124(a) A138 B26 C21 D124(b) A172 B31 C75 D129 A51 B31(a) C75(a) D139 B81 C75(b) B98 B98(a) B98(b) (a) and (b) signify replicate soil cores collected from th is site

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195 Table D 3. STA 3/4 soil core collection sites by vegetation type and cell. A total 58 soil cores were collected from these locations EAV EAV SAV SAV Cell 1A Cell 2A Cell 1B Cell 2B 1A 19 2A 1 1B 24 2B 13 1A 21 2A 12 1B 28 2B 17 1A 3 2A 16 1B 4 2B 17(a) 1A 32 2A 24 1B 52 2B 17(b) 1A 32(a)* 2A 24(a) 1B 52(a) 2B 21 1A 32(b)* 2A 24(b) 1B 52(b) 2B 24 1A 36 2A 28 1B 56 2B 28 1A 48 2A 28(a) 1B 60 2B 3 1A 52 2A 28(b) 1B 60(a) 2B 40 1A 52(a) 2A 38 1B 60(b) 2B 44 1A 52(b) 2A 42 1B 8 2B 44(a) 1A 56 2A 5 1B 80 2B 44(b) 1A 7 2A 53 1B 84 2B 55 1A 71 2A 53(a) 1B 87 2B 59 1A 74 2A 57 (a) and (b) signify replicate soil cores collected from th is site.

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196 Table D 4. Summary statisti cs for change point depth s calculated with SegReg in soil cores collected from STA 1W STA 2 and STA 3/4 EAV EAV EAV SAV SAV SAV EAV conversion STA 1W Cell 1A Cell 2A Cell 5A # Cell 2B Cell 1B Cell 4 Cell 3 Cell 5B # Sites (n ) 5 4 5 4 5 5 5 7 Mean (cm) 19.3 16.7 10.4 15.8 13.5 10.8 12.9 12.4 Standard deviation (cm) 7.3 1.5 4.2 5.4 2.7 3.5 4.8 6.5 CV* (%) 38 9 40 34 20 32 37 52 STA 2 Cell 1 Cell 2 Cell 3 Cell 4 --Sites (n ) 6 10 7 6 --Mean (cm) 8.9 10.4 12.5 12.9 --Standard deviat ion (cm) 1.8 2.6 4 3.8 --CV* (%) 20 25 32 29 --STA 3/4 Cell 1A Cell 2A Cell 1B Cell 2B --Sites (n ) 10 6 13 10 --Mean (cm) 8.2 11.9 12.1 8.4 --Standard deviation (cm) 2.9 6.7 5 2.8 --CV* (%) 35 56 41 33 --* Coeffic ient of v ariation # Cell 5A and 5B went online in WY2000 while the other cells in STA 1W started operation in WY1994

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197 Table D 5 Bulk d ensity profiles in soil cores collected from each cell of STA 1W Depth Mean b ulk d ensity (g cm 3 ) 1 SD (cm) Cell 1 A Cell 1B Cell 2A Cell 2B Cell 3 Cell 4 Cell 5A Cell 5B 1 0.19 0.09 0.31 0.02 0.11 0.05 0.29 0.06 0.2 0.04 0.34 0.07 0.21 0.14 0.23 0.04 3 0.22 0.07 0.35 0.07 0.16 0.06 0.31 0.04 0.21 0.05 0.37 0.09 0.32 0.25 0.3 0.03 5 0.24 0.06 0.33 0.02 0.18 0.06 0.34 0.06 0.23 0.06 0.45 0.06 0.42 0.26 0.32 0.04 7 0.27 0.03 0.3 0.04 0.24 0.04 0.36 0.04 0.27 0.07 0.44 0.06 0.4 0.08 0.31 0.07 9 0.25 0.06 0.27 0.06 0.26 0.04 0.36 0.03 0.33 0 .05 0.44 0.08 0.37 0.07 0.33 0.11 11 0.25 0.01 0.28 0.09 0.28 0.02 0.38 0.02 0.34 0.06 0.43 0.07 0.34 0.08 0.28 0.07 13 0.25 0.03 0.28 0.07 0.31 0.03 0.38 0.04 0.35 0.03 0.4 0.03 0.33 0.11 0.29 0.1 15 0.28 0.01 0.31 0.08 0.33 0.03 0.37 0.06 0.33 0.05 0.37 0.03 0.33 0.09 0.28 0.11 17 0.26 0.03 0.31 0.06 0.33 0.02 0.35 0.03 0.35 0.05 0.36 0.03 0.32 0.1 0.29 0.09 19 0.25 0.04 0.28 0.07 0.35 0.03 0.35 0.01 0.36 0.05 0.36 0.04 0.32 0.07 0.27 0.11 21 0.24 0.05 0.26 0.04 0.37 0.04 0.36 0.08 0.35 0.04 0.32 0.05 0.3 0.1 0.27 0.08 23 0.24 0.07 0.26 0.08 0.36 0.03 0.31 0.05 0.35 0.02 0.31 0.07 0.3 0.11 0.26 0.06 25 0.23 0.09 0.26 0.0 7 0.34 0.08 0.28 0.08 0.33 0.07 0.23 0.05 0.29 0.12 0.25 0.08 27 0.21 0.07 0.24 0.01 0.33 0.08 0.25 0.07 0.32 0.07 0.23 0.09 0.26 0.1 0.23 0.06 29 0.19 0.07 0.22 0.06 0.34 0.11 0.22 0.05 0.29 0.08 0.23 0.09 0.26 0.09 0.19 0.03 31 0.18 0.06 0.19 0.01 0.32 0.1 0.22 0.06 0.27 0.08 -0.24 0.09 0.17 0.04 33 0.18 0.06 0.18 0.06 0.26 0.06 0.19 0.05 0.32 0.1 -0.17 0.03 0.17 0.02 35 0.15 0.03 0.24 0.1 0.22 0.06 -0.27 0.05 --0.16 0.04 37 0.14 0.02 0.16 0.02 0.2 0.02 -0.19 0.04 ---39 0.13 0.01 -0.19 0 -0.22 0.05 ---41 0.12 0.02 ---0.19 0.01 ---43 0.13 0.03 ------

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198 Table D 6 Total p hosphorus p rofile s in soil cores collected from each cell of STA 1W Depth Mean t otal p hosphorus (mg/kg) 1 SD (cm) Cell 1A Cell 1B Cell 2A Cell 2B Cell 3 Cell 4 Cell 5A Cell 5B 1 1033 455 435 129 1475 245 729 242 802 219 542 95 1085 437 941 256 3 811 343 365 119 1209 304 525 68 744 281 557 113 769 398 714 164 5 672 381 296 164 1074 216 533 113 744 336 405 55 482 200 570 156 7 562 423 277 164 868 325 554 68 449 199 398 81 442 167 412 117 9 469 443 297 224 704 249 455 124 346 260 338 114 378 147 401 116 11 466 406 341 340 590 130 382 120 265 117 280 117 373 163 374 108 13 452 364 211 44 420 45 387 115 231 65 217 32 332 108 388 200 15 345 86 205 40 364 54 361 111 213 46 211 23 273 67 353 173 17 250 14 187 23 466 296 354 110 203 37 199 11 260 78 336 174 19 220 10 180 15 299 37 390 136 204 41 192 11 262 82 325 194 21 203 17 168 23 309 36 354 110 200 43 189 14 237 81 299 159 23 190 18 168 29 298 36 313 114 199 31 180 21 222 117 295 138 25 177 23 168 31 272 67 235 109 190 48 174 19 229 117 263 70 27 174 22 155 18 259 95 195 101 185 40 160 26 212 114 263 141 29 169 16 130 26 255 95 165 85 180 45 163 21 216 126 198 46 31 165 10 110 19 240 90 166 86 171 53 -165 106 156 28 33 165 19 113 42 207 67 147 25 193 44 -77 14 144 22 35 161 8 140 58 192 64 -174 41 --136 20 37 153 18 106 11 133 29 -149 36 ---39 149 23 -130 0 -140 14 ---41 160 10 ---167 34 ---43 155 14 -------

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199 Table D 7 B ulk d ensity and to tal phosphorus profiles in soil cores collected from each cell of STA 2. STA 2 Depth Mean b ulk density (g cm 3 ) 1 SD Mean total phosphorus(mg kg 1 ) 1 SD (cm) Cell 1 Cell 2 Cell 3 Cell 4 Cell 1 Cell 2 Cell 3 Cell 4 1 0.11 0.01 0.14 0.08 0.28 0.1 0.25 0.08 1460 397 1413 305 779 257 901 248 3 0.14 0.04 0.16 0.07 0.28 0.07 0.33 0.11 758 259 1129 436 776 353 637 144 5 0.17 0.02 0.21 0.07 0.32 0.07 0.35 0.1 433 96 746 333 614 290 549 99 7 0.21 0.02 0.28 0.06 0.33 0.05 0.38 0.06 315 58 533 151 660 314 503 107 9 0.22 0.04 0.26 0.08 0.34 0.06 0.41 0.03 290 61 361 69 589 295 483 115 11 0.22 0.04 0.26 0.07 0.33 0.06 0.44 0.08 259 27 311 76 562 259 459 134 13 0.2 0.06 0.25 0.09 0.31 0.08 0.47 0.2 226 33 265 61 411 127 410 108 15 0.2 0.04 0.24 0.08 0.3 0.07 0.42 0.22 211 25 239 39 372 61 377 134 17 0.2 0.03 0.22 0.07 0.29 0.06 0.27 0.04 196 29 223 39 472 199 332 90 19 0.2 0.03 0.22 0.07 0.27 0.06 0.25 0.03 181 36 214 45 363 87 275 29 21 0.19 0.01 0.2 0.06 0.27 0.05 0.24 0.02 162 17 197 42 344 45 254 26 23 0.17 0.01 0.2 0.06 0.32 0.09 0.25 0.02 161 29 194 38 320 74 250 20 25 0.17 0.02 0.18 0.05 0.44 0.25 0.27 0.04 149 35 197 51 271 91 224 20 27 0.17 0.01 0.2 0.07 0.57 0.47 0.29 0.07 138 21 209 115 206 54 231 43 29 0.16 0.01 0.21 0.1 0.56 0.63 0.3 0.06 135 27 210 127 203 78 228 41 31 0.16 0.02 0.22 0.14 0.57 0.66 0.33 0.02 132 22 206 107 209 79 206 16 33 0.15 0.01 0.26 0.28 0.33 0.05 0.31 0.03 117 15 177 47 197 94 223 12 35 0.16 0.03 0.17 0.03 0.34 0 0.34 0.03 120 0 166 27 152 0 214 39 37 0.14 0.02 0.18 0.02 -0.29 0.04 110 0 155 21 -224 62 39 0.13 0.03 0.18 0.01 -0.41 0 110 0 161 24 -290 0 41 0.14 0 0.18 0.02 -0.47 0 100 0 154 11 -303 0 43 -0.17 0.01 ---145 6 --45 -0.13 0 ---150 0 --

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200 Table D 8 B ulk d ensity and total phosphorus profiles in soil cores collected from each cell of STA 3/4. STA 3/4 Depth Mean bulk density (g cm 3 ) 1 SD Mean t otal p hosphorus (mg kg 1 ) 1 SD (cm) Cell 1A Cell 1B Cell 2A Cell 2B Cell 1A Cell 1B Cell 2A Cell 2B 1 0.17 0.13 0.13 0.06 0.22 0.18 0.27 0.13 1298 948 979 275 1026 375 770 182 3 0.24 0.16 0.18 0.09 0.28 0.15 0.37 0.15 1100 1017 780 257 881 265 738 241 5 0.27 0.13 0.23 0.09 0.36 0.13 0.46 0.16 699 138 670 222 764 211 679 208 7 0.38 0.2 0.28 0.09 0.39 0.14 0.48 0.13 540 99 547 242 705 193 631 151 9 0.45 0.29 0.31 0.12 0.44 0.16 0.52 0.1 476 103 44 6 146 659 152 574 86 11 0.45 0.22 0.34 0.13 0.46 0.2 0.5 0.11 420 99 413 164 595 169 523 109 13 0.45 0.15 0.33 0.24 0.43 0.19 0.46 0.1 418 152 354 148 564 254 487 126 15 0.49 0.18 0.35 0.31 0.43 0.29 0.47 0.07 368 103 322 112 509 266 480 80 17 0.42 0.15 0.4 0.4 0.48 0.27 0.41 0.09 340 137 295 98 544 285 445 110 19 0.41 0.15 0.32 0.18 0.45 0.19 0.37 0.09 349 80 288 71 558 246 307 68 21 0.47 0.1 0.38 0.23 0.4 3 0.13 0.31 0.02 288 19 265 60 461 254 295 129 23 0.54 0.05 0.33 0.16 0.48 0.18 0.33 0 248 40 254 80 436 261 345 0 25 0.67 0.04 0.29 0.08 0.51 0.29 0.34 0 198 62 265 90 390 361 342 0 27 -0.35 0.11 0.38 0.17 0.34 0 -255 100 480 511 373 0 29 -0.42 0.17 0.51 0.28 0.53 0 -208 107 475 385 170 0 31 -0.46 0.11 0.61 0 --160 40 543 0 -33 -0.44 0.1 0.62 0 --168 37 656 0 -35 -0.57 0.27 0.56 0 --158 56 671 0 -37 -0.63 0.11 0.5 0 --142 74 706 0 -39 -0.62 0 ---187 0 --

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201 Figure D 1. Profiles of m ean (a) b ulk density, (b) t otal phosphorus content (c) s oil 15 (d) s oil 13 (e) C : N ratio and (f) N : P ratio in 2 cm soil core sections collected from each cell in STA 1W

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202 Figure D 2. Profiles of m ean (a) b ulk density, (b) t otal phosphorus content (c) s oil 15 (d) s oil 13 (e) C : N ratio and (f) N : P ratio in 2 cm soil cores secti ons collected from each cell in STA 2

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203 Figure D 3. Profiles of m ean (a) b ulk density, (b) t otal phosphorus, (c) s oil 15 (d) s oil 13 (e) C : N ratio and (f) N : P ratio in 2 cm soil cores sections collected from each cell in STA 3/4

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204 Figure D 4. Bulk d ensity p rofile in each soil core collected from STA 1W. -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 1A 1I) -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.10 0.15 0.20 0.25 0.30 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 1A 1I(a)) -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.10 0.15 0.20 0.25 0.30 0.35 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 1A 1I(b)) -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 1A 1P) -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.10 0.15 0.20 0.25 0.30 0.35 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 1A 1B) -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.10 0.15 0.20 0.25 0.30 0.35 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 1A 1B(i))

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205 Figure D 4. C ontinued. -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 1B 1AB) -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 1B 1AB(a)) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 0.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 1B 1AB(b)) -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 1B 1AE) -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 1B 1T) -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 5B 162)

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206 Figure D 4. C ontinued. -24 -20 -16 -12 -8 -4 0 0.05 0.10 0.15 0.20 0.25 0.30 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 5B 125) -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 5B 125(a)) -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.10 0.15 0.20 0.25 0.30 0.35 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 5B 125(b)) -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 5B 202) -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 5B 108) -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 0.85 1.05 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 5A 74)

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207 Figure D 4. C ontinued. -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 5A 112) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 5A 112(a)) -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 5A 112(b) -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 3 3B) -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 0.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 5B 83) -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 3 3P)

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208 Figure D 4. C ontinued. -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 3 3I) -32 -28 -24 -20 -16 -12 -8 -4 0 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 3 3I(a) -32 -28 -24 -20 -16 -12 -8 -4 0 0.15 0.25 0.35 0.45 0.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 3 3I(b) -32 -28 -24 -20 -16 -12 -8 -4 0 0.15 0.25 0.35 0.45 0.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 2B 2U) -32 -28 -24 -20 -16 -12 -8 -4 0 0.15 0.20 0.25 0.30 0.35 0.40 Depth (cm) Bulk density (g/cm3) Bulk density variation in soil profile (Site: STA 1W, Cell 2B 2U(a) -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.10 0.20 0.30 0.40 0.50 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 2B 2U (b))

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209 Figure D 4. C ontinued. -32 -28 -24 -20 -16 -12 -8 -4 0 0.15 0.20 0.25 0.30 0.35 0.40 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 2B 2AB) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 5A 150) -32 -28 -24 -20 -16 -12 -8 -4 0 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 4 4C) -32 -28 -24 -20 -16 -12 -8 -4 0 0.15 0.20 0.25 0.30 0.35 0.40 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 4 4F) -32 -28 -24 -20 -16 -12 -8 -4 0 0.15 0.25 0.35 0.45 0.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 4 4F(a)) -32 -28 -24 -20 -16 -12 -8 -4 0 0.15 0.25 0.35 0.45 0.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 4 4F(b))

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210 Figure D 4. C ontinued. -32 -28 -24 -20 -16 -12 -8 -4 0 0.15 0.25 0.35 0.45 0.55 0.65 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 4 4J) -32 -28 -24 -20 -16 -12 -8 -4 0 0.00 0.10 0.20 0.30 0.40 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 2A 2F) -32 -28 -24 -20 -16 -12 -8 -4 0 0.00 0.10 0.20 0.30 0.40 0.50 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 2A 2Q (b)) -32 -28 -24 -20 -16 -12 -8 -4 0 0.00 0.10 0.20 0.30 0.40 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 2A 2Q) -32 -28 -24 -20 -16 -12 -8 -4 0 0.00 0.10 0.20 0.30 0.40 0.50 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 1W, Cell 2A 2Q (a))

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211 Figure D 5 Total p hosphorus p rofile in each soil core collected from STA 1W. -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 1A 1I) -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 2000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 1A 1I(a)) -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 1A 1I(b)) -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 1A 1B(i)) -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 1A 1P) -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 1200 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 1B 1T)

PAGE 212

212 Figure D 5. C ontinued -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 50 100 150 200 250 300 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 1B 1AE) -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 1B 1AB) -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 100 200 300 400 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 1B 1AB(a)) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 100 200 300 400 500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 1B 1AB(b)) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 1200 1250 1300 1350 1400 1450 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 1A 1B) -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 5B 108)

PAGE 213

213 Figure D 5. C ontinued -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 5B 125) -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 5B 125(b)) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 5B 162) -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 5B 202) -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 5B 125(a)) -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 5B 83)

PAGE 214

214 Figure D 5. C ontinued -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 1200 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 5A 74) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 5A 150) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 5A 112) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 2000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 5A 112(a)) -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 2000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 5A 112(b)) -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 3 3I)

PAGE 215

215 Figure D 5. C ontinued -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 3 3P) -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 3 3B) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 3 3I(a)) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 3 3I(b)) -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 2B 2U) -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 2B 2U(b))

PAGE 216

216 Figure D 5. C ontinued -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 2B 2AB) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 2B 2U(a)) -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 4 4C) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 100 200 300 400 500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 4 4F) -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 4 4F(a)) -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 4 4F(b))

PAGE 217

217 Figure D 5. C ontinued -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 4 4J) -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 2000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 2A 2F) -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 2000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 2A 2Q) -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 2A 2Q(a)) -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 1W, Cell 2A 2Q(b))

PAGE 218

218 Figure D 6. Bulk d ensity p rofile in each soil core collected from STA 2. -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.10 0.15 0.20 0.25 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell A 103) -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.10 0.15 0.20 0.25 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell A 103(a)) -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.10 0.15 0.20 0.25 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell A 103(b)) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.10 0.15 0.20 0.25 0.30 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell A 51) -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.10 0.15 0.20 0.25 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell A 138) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell A 172)

PAGE 219

219 Figure D 6. C ontinued -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell C 75) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell C 75(a)) -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell C 75(b)) -28 -24 -20 -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 0.85 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell C 21) -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell C 129) -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.55 1.05 1.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell C 165)

PAGE 220

220 Figure D 6. C ontinued -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.55 1.05 1.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell C 201) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.55 1.05 1.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell B 26) -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.10 0.15 0.20 0.25 0.30 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell B 81) -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell B 98) -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.10 0.15 0.20 0.25 0.30 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell B 98(a)) -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.10 0.15 0.20 0.25 0.30 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell B 98(b))

PAGE 221

221 Figure D 6. C ontinued -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.10 0.15 0.20 0.25 0.30 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell B 117) -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.10 0.15 0.20 0.25 0.30 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell B 151) -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.10 0.15 0.20 0.25 0.30 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell B 187) -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell B 31) -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell B 31(a)) -20 -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 0.85 1.05 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell D 111)

PAGE 222

222 Figure D 6. C ontinued -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 0.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell D 124) -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 Depth (cm) Bulk density (g/cm3) Bulk density variation in soil profile (Site: STA 2, Cell D 124(a)) -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 0.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell D 124(b)) -28 -24 -20 -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell D 139) -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 0.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 2, Cell D 129)

PAGE 223

223 Figure D 7. Total p hosphorus p rofile in each soil core collected from STA 2. -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 2000 2500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell A 103) -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell A 103(a)) -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 2000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell A 103(b)) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 2000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell A 51) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell A 172) -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell A 138)

PAGE 224

224 Figure D 7. C ontinued -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell C 21) -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell C 129) -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell C 165) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell C 75) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell C 75(a)) -20 -16 -12 -8 -4 0 0 500 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell C 75(b))

PAGE 225

225 Figure D 7. C ontinued -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell C 201) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell B 26) -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 2000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell B 81) -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell B 98) -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 2000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell B 98(a)) -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 2000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell B 98(b))

PAGE 226

226 Figure D 7. C ontinued -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 1200 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell B 117) -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell B 151) -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell B 187) -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 2000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell B 31) -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 2000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell B 31(a)) -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell D 111)

PAGE 227

227 Figure D 7. C ontinued -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell D 124) -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell D 124(a)) -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell D 124(b)) -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell D 139) -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 2, Cell D 129)

PAGE 228

228 EAV cell EAV cell EAV cell EAV cell EAV cell EAV cell Figure D 8. Bulk d ensity p rofile in each soil core collected from STA 3/4. -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 0.85 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2A 1) -28 -24 -20 -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 0.85 1.05 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2A 5) -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2A 12) -28 -24 -20 -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 0.85 1.05 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2A 16) -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2A 38) -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2A 42)

PAGE 229

229 EAV cell EAV cell EAV cell EAV cell EAV cell EAV cell Figure D 8 C ontinued -12 -8 -4 0 0.05 0.25 0.45 0.65 0.85 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2A 24) -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 0.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2A 24(a)) -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 0.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2A 24(b)) -8 -4 0 0.05 0.25 0.45 0.65 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2A 28) -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 0.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2A 28(a)) -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 0.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2A 28(b))

PAGE 230

230 EAV cell EAV cell EAV cell SAV cell SAV cell SAV cell Figure D 8 C ontinued -32 -28 -24 -20 -16 -12 -8 -4 0 0.00 0.20 0.40 0.60 0.80 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2A 57) -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2A 53) -8 -4 0 0.05 0.07 0.09 0.11 0.13 0.15 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2A 53(a)) -12 -8 -4 0 0.05 0.25 0.45 0.65 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2B 17) -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 0.85 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2B 17(a)) -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 0.85 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2B 17(b))

PAGE 231

231 SAV cell SAV cell SAV cell SAV cell SAV cell SAV cell Figure D 8 C ontinued -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 0.85 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2B 3) -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 0.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2B 21) -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2B 24) -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2B 28) -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2B 40) -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 0.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2B 55)

PAGE 232

232 SAV cell SAV cell SAV cell SAV cell SA V cell EAV cell Figure D 8 C ontinued -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2B 44) -24 -20 -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2B 44(a)) -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 0.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2B 44(b)) -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2B 59) -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 2B 13) -20 -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 0.85 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1A 3)

PAGE 233

233 EAV cell EAV cell EAV cell EAV cell EAV cell EAV cell Figure D 8 C ontinued -24 -20 -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1A 32) -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 0.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1A 32(a)) -28 -24 -20 -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 0.85 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1A 32(b)) -20 -16 -12 -8 -4 0 0.05 0.55 1.05 1.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1A 7) -24 -20 -16 -12 -8 -4 0 0.00 0.20 0.40 0.60 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1A 21) -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 0.85 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1A 36)

PAGE 234

234 EAV cell EAV cell EAV cell EAV cell EAV cell EAV cell Figure D 8 C ontinued -28 -24 -20 -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 0.85 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1A 48) -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 0.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1A 71) -24 -20 -16 -12 -8 -4 0 0.05 0.10 0.15 0.20 0.25 0.30 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1A 56) -20 -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1A 52) -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 0.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1A 52(a)) -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 0.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1A 52(b))

PAGE 235

235 EAV cell EAV cell EAV c ell EAV cell EAV cell EAV cell Figure D 8 C ontinued -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1A 74) -20 -16 -12 -8 -4 0 0.05 0.55 1.05 1.55 2.05 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1B 4) -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1B 8) -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1B 24) -28 -24 -20 -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 0.85 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1B 28) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1B 56)

PAGE 236

236 EAV cell EAV cell EAV cell EAV cell EAV cell EAV cell Figure D 8. C ontinued -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 0.85 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1B 80) -24 -20 -16 -12 -8 -4 0 0.05 0.10 0.15 0.20 0.25 0.30 0.35 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1B 87) -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 0.55 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1B 84) -12 -8 -4 0 0.05 0.10 0.15 0.20 0.25 0.30 0.35 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1B 52) -24 -20 -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 0.85 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1B 52(a)) -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1B 52(b))

PAGE 237

237 EAV cell EAV cell EAV cell Figure D 8. C ontinued -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.25 0.45 0.65 0.85 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1B 60) -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.00 0.20 0.40 0.60 0.80 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1B 60(a)) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0.05 0.15 0.25 0.35 0.45 0.55 0.65 Depth (cm) Bulk density (g/cm 3 ) Bulk density variation in soil profile (Site: STA 3/4, Cell 1B 60(b))

PAGE 238

238 EAV cell EAV cell EAV cell EAV cell EAV cell EAV cell Figure D 9. Total p hosphorus p rofile in each soil core collected from STA 3/4. -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 1200 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2A 1) -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2A 5) -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2A 12) -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 2000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2A 16) -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2A 38) -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2A 42)

PAGE 239

239 EAV cell EAV cell EAV cell EAV cell EAV cell EAV cell Figure D 9 C ontinued -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2A 24) -16 -12 -8 -4 0 0 200 400 600 800 1000 1200 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2A 24(a)) -12 -8 -4 0 0 200 400 600 800 1000 1200 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2A 24(b)) -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2A 28) -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2A 28(a)) -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2A 28(b))

PAGE 240

240 EAV cell EAV cell EAV cell SAV cell SAV cell SAV cell Figure D 9 C ontinued -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2A 53) -8 -4 0 0 200 400 600 800 1000 1200 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2A 53(a)) -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 2000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2A 57) -16 -12 -8 -4 0 0 100 200 300 400 500 600 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2B 3) -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 2000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2B 21) -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2B 24)

PAGE 241

241 SAV cell SAV cell SAV cell SAV cell SAV cell SAV cell Figure D 9 C ontinued -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2B 17) -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2B 17(a)) -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2B 17(b)) -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2B 28) -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2B 40) -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2B 55)

PAGE 242

242 SAV cell SAV cell SAV cell SAV cell SAV cell EAV cell Figure D 9 C ontinued -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2B 44) -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2B 44(a)) -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2B 44(b)) -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2B 59) -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 2B 13) -20 -16 -12 -8 -4 0 0 500 1000 1500 2000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1A 3)

PAGE 243

243 EAV cell EAV ce ll EAV cell EAV cell EAV cell EAV cell Figure D 9 C ontinued -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1A 7) -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 2000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1A 21) -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1A 36) -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1A 32) -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 1200 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1A 32(a)) -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1A 32(b))

PAGE 244

244 EAV cell EAV cell EAV cell EAV cell EAV cell EAV cell Figure D 9 C ontinued -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1A 48) -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 1200 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1A 56) -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1A 71) -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1A 52) -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1A 52(a)) -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1A 52(b))

PAGE 245

245 EAV cell EAV cell EAV cell EAV cell EAV cell EAV cell Figure D 9 C ontinu ed -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1A 74) -20 -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1B 4) -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1B 8) -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1B 24) -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1B 28) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1B 56)

PAGE 246

246 EAV cell EAV cell EAV cell EAV cell EAV cell EAV cell Figure D 9 C ontinued -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1B 80) -28 -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 1000 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1B 84) -24 -20 -16 -12 -8 -4 0 0 200 400 600 800 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1B 87) -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1B 52) -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1B 52(a)) -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1B 52(b))

PAGE 247

247 EAV cell EAV cell EAV cell Figure D 9 C ontinued -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1B 60) -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1B 60(a)) -36 -32 -28 -24 -20 -16 -12 -8 -4 0 0 500 1000 1500 Depth (cm) TP (mg/kg) TP variation in soil profile (Site: STA 3/4, Cell 1B 60(b))

PAGE 248

248 APPENDIX E ADDITIONAL DATA AND INF ORMATION PERTAINING TO CHAPTER 5 Table E 1. STA 1W and S TA 2 soil core collection sites by vegetation type and cell. A total 44 soil cores were collected from these locations. Soil core sampling locations EAV SAV EAV conversion STA 1W Cell 5A Cell 5B Cell 3 5A112 5A150 5B108 5B202 3I 3P 5A1 12(a) 5A74 5B125 5B83 3I(a) 3B 5A112(b) -5B125(a) 5B162 3I(b) ---5B125(b) ---EAV SAV STA 2 Cell 1 Cell 2 Cell 3 Cell 4 --A103 B117 C129 D111 --A103( a) B151 C165 D124 --A103(b) B187 C201 D124( a) --A138 B26 C21 D124(b) --A172 B81 C75 D129 --A51 B98 C75(a) D139 ---B98(a) C75(b) ----B98(b) ----

PAGE 249

249 Table E 2. Mean d epth of RAS at STA 1W sampling sites used for sep a rating RAS from pre STA soil STA 1W EAV SAV EAV conversion Cell 5A Cell 5B Cell 3 Site Depth (cm) Site Depth (cm) Site Depth (cm) 5A112 8 5B108 8 3I 12 5A112(a) 8 5B125 8 3I(a) 10 5A112(b) 8 5B125(a) 8 3I(b) 10 5A150 10 5B125(b) 12 3P 10 5A74 16 5B202 8 3B 12 --5B83 10 ----5B162 12 --Table E 3. Mean d epth of RAS at STA 2 sampling sites used for separating RAS from pre STA soil STA 2 EAV SAV Cell 1 Cell 2 Cell 3 Cell 4 Site Depth (cm) Site Depth (cm) Site Depth (cm) Site Depth (cm) A103 8 B117 10 C129 8 D 111 6 A103(a)* 12 B151 12 C165 12 D124 8 A103(b)* 8 B187 14 C201 10 D124(a) 12 A138 10 B26 8 C21 8 D124(b) 12 A172 8 B81 12 C75 8 D129 12 A51 8 B98 8 C75(a) 12 D139 12 -B98(a) 8 C75(b) 4 --B98(b) 8 ---

PAGE 250

250 Table E 4 Depth of soil fraction, bulk density, total phosphorus concentration and TP storage for each soil fraction at sampling sites in STA 1W. STA 1W Floc RAS Pre STA soil EAV Depth Bulk density TP Conc. TP Storage Depth Bulk density TP Conc. TP Storage Depth Bulk density TP Conc. TP Storage cm g cm 3 mg Pkg 1 g P m 2 cm g cm 3 mg P kg 1 g P m 2 cm g cm 3 mg Pkg 1 g Pm 2 Cell 5A 5A 112 8 0.11 1219 11.2 8 0.29 461 10.5 15 0.35 369 19.5 5A 112(a) 5 0.12 1080 6.5 8 0.31 444 11.0 15 0.34 428 21.8 5A 112(b) 8 0.08 1340 8.8 8 0.29 827 19.0 15 0.39 443 25.6 5A 150 16 0.05 1339 10.9 10 0.32 245 7.9 15 0.23 182 6.4 5A 74 ----16 0.37 684 40.5 15 0.34 497 25.3 SAV Cell 3 3B 8 0.18 334 4.7 12 0.31 226 8.4 15 0.33 22 2 10.9 3I 8 0.08 1094 7.3 12 0.23 446 12.5 15 0.26 186 7.2 3I(a) 6 0.05 1460 4.3 10 0.17 1045 17.9 15 0.26 210 8.3 3I(b) 8 0.06 940 4.5 10 0.22 789 17.2 15 0.28 198 8.3 3P 14 0.09 660 8.3 10 0.21 384 8.1 15 0.29 202 8.9 Cell 5B 5B 108 6 0.21 1002 12.8 8 0.35 426 12.0 15 0.19 255 7.3 5B 125 5 0.14 1199 8.1 8 0.26 568 12.0 15 0.28 322 13.4 5B 125(a) 6 0.13 986 8.0 8 0.28 353 7.9 15 0.28 298 12.3 5B 125(b) 5 0.10 778 3.8 12 0.33 426 17.0 15 0.32 364 17.6 5B 162 8 0.17 1011 1 3.7 12 0.28 508 17.2 15 0.27 396 16.2 5B 202 4 0.20 798 6.5 8 0.31 552 13.9 15 0.28 326 13.5 5B 83 6 0.09 690 3.9 10 0.39 733 28.6 15 0.32 588 28.2 *For pre STA soil, TP storages were calculated only for a 15 cm deep soil layer, assuming constant bulk d ensity throughout the layer

PAGE 251

251 Table E 5 D epth of soil fraction, bulk density, total phosphorus concentration and TP storage for each soil fraction at sampling sites in STA 2. STA 2 Floc RAS Pre STA soil EAV Depth Bulk density TP Conc. TP Storage Depth Bulk density TP Conc. TP Storage Depth Bulk density TP Conc. TP Storage cm g cm 3 mg Pkg 1 g P m 2 cm g cm 3 mg P kg 1 g P m 2 cm g cm 3 mg Pkg 1 g Pm 2 Cell 1 A103 10 0.08 1014 7.7 8 0.18 255 3.7 15 0.14 178 3.8 A103 (a) 10 0.08 1098 8.3 12 0.16 275 5.3 15 0.13 162 3.1 A103 (b) 12 0.07 1031 8.9 8 0.14 297 3.3 15 0.14 174 3.6 A138 8 0.07 760 4.2 10 0.21 276 5.7 15 0.11 172 2.9 A172 8 0.04 1009 3.1 8 0.31 302 7.5 15 0.12 186 3.3 A51 9 0.04 1444 5.3 8 0.17 636 8.5 15 0.17 192 5.0 Cell 2 B117 7 0.08 644 3.6 10 0.25 317 8.1 15 0.13 181 3.6 B151 5 0.02 1455 1.5 12 0.15 554 10.2 15 0.18 220 5.8 B187 12 0.03 1117 3.8 14 0.19 455 12.3 15 0.41 199 12.2 B26 4 0.02 798 0.6 8 0.38 482 14.7 15 0.39 330 19.2 B81 7 0.12 1293 10.7 12 0.27 380 12.5 15 0.15 170 3.8 B98 10 0.04 1361 5.0 8 0.26 395 8.2 15 0.11 249 4.1 B98(a) 6 0.07 1116 4.8 8 0.20 406 6.4 15 0.12 174 3.1 B98(b) 10 0.07 1218 8.1 8 0.21 340 5.8 15 0.09 176 2.3 For pre STA soil fraction, mass P storages were calculated only for 15 cm depth, assuming constant bulk density for the entire 15 cm depth.

PAGE 252

252 Table E 5 Continued STA 2 Floc RAS Pre STA soil S AV Depth Bulk density TP Conc. TP Storage Depth Bulk density TP Conc. TP Storage Depth Bulk density TP Conc. TP Storage cm g cm 3 mg Pkg 1 g P m 2 cm g cm 3 mg P kg 1 g P m 2 cm g cm 3 mg Pkg 1 g Pm 2 Cell 3 C129 8 0.12 523 5.2 8 0.25 370 7.5 15 0.26 280 10.7 C165 7 0.10 506 3.5 12 0.30 389 14.2 15 0.22 242 8.0 C201 11 0.12 362 4.9 10 0. 32 513 16.4 15 0.39 236 13.8 C21 5 0.13 886 5.9 8 0.46 399 14.6 15 0.39 431 25.3 C75 10 0.12 1083 12.8 8 0.23 777 14.5 15 0.14 284 6.2 C75 (a) 10 0.13 1020 13.2 12 0.24 753 21.9 15 0.20 278 8.3 C75 (b) 7 0.10 979 7.0 4 0.27 525 5.7 15 0.18 297 8.0 Cell 4 D111 ----6 0.25 967 14.6 15 0.25 294 10.8 D124 ----8 0.18 751 10.6 15 0.35 75 3.9 D124 (a) ----12 0.24 655 19.1 15 0.32 405 19.4 D124 (b) ----12 0.29 585 20.5 15 0.26 363 14.2 D129 ---12 0.31 610 22.8 15 0.39 414 24.0 D139 ----12 0.34 607 25.1 15 0.38 534 30.3 *For pre STA soil, TP storages were calculated only for a 15 cm deep soil layer, assuming constant bulk density throughout the layer

PAGE 253

253 Table E 6 Depth of soil fra ction, bulk density, total nitrogen concentration and TN storage for each soil fraction at sampling sites in STA 1W STA 1W Floc RAS Pre STA soil EAV Depth Bulk density TN Conc. T N Storage Depth Bulk density TN Conc. T N Storage Depth Bulk density TN Conc. T N Storage cm g cm 3 g Nkg 1 k g N m 2 cm g cm 3 g Nkg 1 k g N m 2 cm g cm 3 g Nkg 1 k g N m 2 Cell 5A 5A 112 8 0.11 29.0 0.27 8.0 0.3 28.1 0.64 15 0.4 28.6 1.51 5A 112(a) 5 0.12 28.3 0.17 8.0 0.3 27.6 0.69 15 0.3 28.7 1.47 5A 112(b) 8 0.0 8 27.7 0.18 8.0 0.3 24.6 0.56 15 0.4 28.9 1.67 5A 150 16 0.05 33.9 0.28 10.0 0.3 35.6 1.15 15 0.2 38.8 1.36 5A 74 ----16.0 0.4 28.6 1.69 15 0.3 34.0 1.73 SAV Cell 3 3B 8 0.18 33.5 0.47 12.0 0.3 35.8 1.34 15 0.3 35.7 1.75 3I 8 0.08 33.2 0.22 12.0 0.2 31.4 0.88 15 0.3 32.3 1.25 3I(a) 6 0.05 32.6 0.10 10.0 0.2 48.9 0.84 15 0.3 31.8 1.25 3I(b) 8 0.06 34.2 0.16 10.0 0.2 33.5 0.73 15 0.3 33.0 1.37 3P 14 0.09 30.4 0.38 10.0 0.2 31.4 0.66 15 0.3 30.3 1.34 Cell 5B 5B 108 6 0.21 29.6 0.38 8.0 0.4 37.1 1.05 15 0.2 38.1 1.08 5B 125 5 0.14 23.9 0.16 8.0 0.3 28.9 0.61 15 0.3 32.5 1.36 5B 125(a) 6 0.13 24.9 0.20 8.0 0.3 30.3 0.68 15 0.3 31.4 1.30 5B 125(b) 5 0.10 25.5 0.12 12.0 0.3 29.8 1.1 9 15 0.3 31.8 1.54 5B 162 8 0.17 27.9 0.38 12.0 0.3 34.7 1.17 15 0.3 34.8 1.42 5B 202 4 0.20 30.2 0.25 8.0 0.3 33.2 0.83 15 0.3 32.6 1.35 5B 83 6 0.09 32.2 0.18 10.0 0.4 35.8 1.40 15 0.3 36.8 1.76 *For pre STA soil, TN storages were calculated only for a 15 cm deep soil layer, assuming constant bulk density throughout the layer

PAGE 254

254 Table E 7 Depth of soil fraction, bulk density, total nitrogen concentration and TN storage for each soil fraction at sampling sites in STA 2. STA 2 Floc RAS Pre STA soil EAV Dept h Bulk density TN Conc. T N Storage Depth Bulk density TN Conc. T N Storage Depth Bulk densit y TN Conc. T N Storage cm g cm 3 g Nkg 1 k g N m 2 cm g cm 3 g Nkg 1 k g N m 2 cm g cm 3 g Nkg 1 k g N m 2 Cell 1 A103 10 0.08 25.9 0.20 8.0 0.2 29. 2 0.43 15 0.1 26.7 0.56 A103 (a) 10 0.08 29.2 0.22 12.0 0.2 30.4 0.58 15 0.1 26.1 0.51 A103 (b) 12 0.07 27.3 0.24 8.0 0.1 31.8 0.36 15 0.1 28.3 0.58 A138 8 0.07 26.8 0.15 10.0 0.2 31.4 0.65 15 0.1 29.4 0.50 A172 8 0.04 28.6 0.09 8.0 0.3 31.8 0.79 15 0. 1 29.9 0.54 A51 9 0.04 28.2 0.10 8.0 0.2 29.0 0.39 15 0.2 28.7 0.75 Cell 2 B117 7 0.08 30.3 0.17 10.0 0.3 30.1 0.76 15 0.1 26.1 0.52 B151 5 0.02 28.3 0.03 12.0 0.2 29.3 0.54 15 0.2 28.5 0.75 B187 12 0.03 26.9 0.09 14.0 0.2 30 .9 0.83 15 0.4 26.8 1.63 B26 4 0.02 13.2 0.01 8.0 0.4 24.5 0.75 15 0.4 27.9 1.63 B81 7 0.12 24.3 0.20 12.0 0.3 29.9 0.98 15 0.1 27.9 0.62 B98 10 0.04 24.3 0.09 8.0 0.3 29.2 0.60 15 0.1 28.9 0.47 B98(a) 6 0.07 29.2 0.13 8.0 0.2 31.3 0.50 15 0.1 27.9 0.5 0 B98(b) 10 0.07 28.0 0.19 8.0 0.2 29.9 0.51 15 0.1 26.8 0.35 *For pre STA soil, TN storages were calculated only for a 15 cm deep soil layer, assuming constant bulk density throughout the layer

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255 Table E 7 Continued STA 2 Floc RAS Pre STA soil SAV Dep th Bulk density TN Conc. T N Storage Depth Bulk density TN Conc. T N Storage Depth Bulk density TN Conc. T N Storage cm g cm 3 g Nkg 1 k g N m 2 cm g cm 3 g Nkg 1 k g N m 2 cm g cm 3 g Nkg 1 k g N m 2 Cell 3 C129 8 0.12 10.1 0.10 8.0 0.3 22.0 0.4 5 15 0.3 28.7 1.10 C165 7 0.10 16.1 0.11 12.0 0.3 30.9 1.13 15 0.2 37.8 1.25 C201 11 0.12 11.9 0.16 10.0 0.3 32.2 1.03 15 0.4 19.0 1.11 C21 5 0.13 12.0 0.08 8.0 0.5 28.5 1.04 15 0.4 19.0 1.12 C75 10 0.12 11.9 0.14 8.0 0.2 16.2 0.30 15 0.1 32.6 0.71 C 75 (a) 10 0.13 11.4 0.15 12.0 0.2 17.5 0.51 15 0.2 28.1 0.84 C75 (b) 7 0.10 13.2 0.09 4.0 0.3 23.5 0.26 15 0.2 31.1 0.84 Cell 4 D111 ----6.0 0.3 25.5 0.38 15 0.2 34.9 1.29 D124 ----8.0 0.2 30.7 0.43 15 0.3 30.5 1.59 D124 (a) ----12.0 0.2 30.5 0.89 15 0.3 29.0 1.39 D124 (b) ----12.0 0.3 30.2 1.06 15 0.3 30.3 1.19 D129 ----12.0 0.3 27.4 1.03 15 0.4 30.9 1.79 D139 ----12.0 0.3 28.0 1.16 15 0.4 32.2 1.82 For pre STA soil fraction mass N storages were calculated only for 15 cm depth, assuming constant bulk density for the entire 15 cm depth.

PAGE 256

256 Table E 8 Depth of soil fraction. bulk density, total carbon concentration and TC storage for each soil fraction at sampling sites in S TA 1W STA 1W Floc RAS Pre STA soil EAV Depth Bulk density TC Conc. TC Storage Depth Bulk density TC Conc. TC Storage Depth Bulk density TC Conc. TC Storage Cell 5A cm g cm 3 g Ckg 1 kg C m 2 cm g cm 3 g Ckg 1 kg C m 2 cm g cm 3 g Ckg 1 kg C m 2 5A 112 8 0.11 3.8 412.5 8.0 0.3 10.2 448.1 15 0.4 25.3 478.5 5A 112(a) 5 0.12 2.4 399.7 8.0 0.3 11.2 450.9 15 0.3 24.3 475.2 5A 112(b) 8 0.08 2.6 391.1 8.0 0.3 8.9 385.9 15 0.4 27.4 473.3 5A 150 16 0.05 3.2 397.0 10.0 0.3 15.7 483.8 15 0.2 17.5 499.4 5A 74 16.0 0.4 23.2 391.5 15 0.3 23.6 464.1 SAV Cell 3 3B 8 0.18 6.7 476.2 12.0 0.3 19.0 509.3 15 0.3 25.3 516.6 3I 8 0.08 2.8 416.7 12.0 0.2 12.7 454.5 15 0.3 18.8 483. 0 3I(a) 6 0.05 1.1 368.4 10.0 0.2 11.3 661.4 15 0.3 18.9 479.2 3I(b) 8 0.06 2.0 426.3 10.0 0.2 9.6 440.9 15 0.3 20.1 483.3 3P 14 0.09 5.7 458.5 10.0 0.2 10.2 482.7 15 0.3 21.9 496.4 Cell 5B 5B 108 6 0.21 4.8 377.5 8.0 0.4 13.0 460.8 15 0.2 13.9 488.7 5B 125 5 0.14 2.0 296.6 8.0 0.3 8.7 411.8 15 0.3 19.6 470.7 5B 125(a) 6 0.13 2.6 328.3 8.0 0.3 10.2 454.5 15 0.3 19.7 474.4 5B 125(b) 5 0.10 1.8 379.1 12.0 0.3 18.6 464.3 15 0.3 23.1 476.0 5B 162 8 0.17 4.5 334.9 1 2.0 0.3 15.9 469.7 15 0.3 19.7 483.9 5B 202 4 0.20 3.3 398.8 8.0 0.3 11.9 472.8 15 0.3 20.6 496.1 5B 83 6 0.09 2.1 379.3 10.0 0.4 17.4 446.2 15 0.3 21.5 448.9 *For pre STA soil, TC storages were calculated only for a 15 cm deep soil layer, assuming cons tant bulk density throughout the layer

PAGE 257

257 Table E 9 Depth of soil fraction, bulk density, t otal carbon concentration and TC storage for each soil fraction at sampling sites in STA 2. STA 2 Floc RAS Pre STA soil EAV Depth Bulk density TC Conc. TC Storage Depth Bulk density TC Conc. TC Storage Depth Bulk density TC Conc. TC Storage Cell1 cm g cm 3 g Ckg 1 kg C m 2 cm g cm 3 g Ckg 1 kg C m 2 cm g cm 3 g Ckg 1 kg C m 2 A103 10 0.08 2.6 342.8 8.0 0.2 6.5 445.8 15 0.1 9.5 453.6 A103 (a) 1 0 0.08 2.9 377.2 12.0 0.2 8.4 441.2 15 0.1 8.9 458.6 A103 (b) 12 0.07 3.0 354.0 8.0 0.1 4.9 436.4 15 0.1 9.6 469.2 A138 8 0.07 2.3 411.6 10.0 0.2 9.3 450.3 15 0.1 8.3 484.6 A172 8 0.04 1.2 379.6 8.0 0.3 11.0 442.8 15 0.1 8.5 473.4 A51 9 0.04 1.4 377.0 8.0 0.2 5.7 426.1 15 0.2 12.5 478.7 Cell 2 B117 7 0.08 2.4 429.8 10.0 0.3 11.6 457.1 15 0.1 9.6 481.4 B151 5 0.02 0.4 406.9 12.0 0.2 8.3 448.2 15 0.2 12.5 475.5 B187 12 0.03 1.4 401.6 14.0 0.2 12.3 457.1 15 0.4 29. 1 476.4 B26 4 0.02 0.2 223.2 8.0 0.4 12.6 415.3 15 0.4 27.6 474.4 B81 7 0.12 2.9 345.9 12.0 0.3 15.0 456.8 15 0.1 11.0 494.0 B98 10 0.04 1.3 343.0 8.0 0.3 9.1 441.0 15 0.1 7.5 457.2 B98(a) 6 0.07 1.7 384.5 8.0 0.2 6.9 435.8 15 0.1 8.5 472.0 B98(b) 10 0.07 2.5 382.9 8.0 0.2 7.5 444.5 15 0.1 6.0 465.0 *For pre STA soil, TC storages were calculated only for a 15 cm deep soil layer, assuming constant bulk density throughout the layer.

PAGE 258

258 Table E 9 continued. STA 2 Floc RAS Pre STA soil SAV Depth Bulk dens ity TC Conc. TC Storage Depth Bulk density TC Conc. TC Storage Depth Bulk density TC Conc. TC Storage Cell 3 cm g cm 3 g Ckg 1 kg C m 2 cm g cm 3 g Ckg 1 kg C m 2 cm g cm 3 g Ckg 1 kg C m 2 C129 8 0.12 1.7 175.8 8.0 0.3 7.5 368.7 15 0.3 16.0 416.6 C165 7 0.10 1.6 237.3 12.0 0.3 16.0 438.8 15 0.2 14.4 436.3 C201 11 0.12 2.7 199.3 10.0 0.3 14.6 456.8 15 0.4 14.0 239.1 C21 5 0.13 1.4 205.6 8.0 0.5 16.3 446.4 15 0.4 15.5 264.2 C75 10 0.12 2.1 181.0 8.0 0.2 4.9 263.0 15 0.1 10.1 465.1 C75 (a) 10 0.13 2.3 178.5 12.0 0.2 8.2 281.1 15 0.2 13.5 452.2 C75 (b) 7 0.10 1.4 195.7 4.0 0.3 4.1 375.3 15 0.2 12.3 455.0 Cell 4 D111 ----6.0 0.3 4.8 318.6 15 0.2 17.9 486.8 D124 ----8.0 0.2 5.9 416.9 15 0.3 23.4 449.5 D124 (a) ----12.0 0.2 12.5 429.8 15 0.3 21.4 447.3 D124 (b) ----12.0 0.3 15.2 433.6 15 0.3 18.1 461.0 D129 ----12.0 0.3 14.3 380.6 15 0.4 25.8 445.6 D139 ----12.0 0.3 15.7 378.8 15 0.4 25.7 452.8 *For pre STA soil, TC storages were calculated only for a 15 cm deep soil layer, assuming constant bulk density throughout the layer.

PAGE 259

259 Table E 10 Average total phosphorus concentration and TP storage for each soil fraction over all sampling sites in EA V and SAV cells of STA 1W. [Mean 1 SD; N= number of samples] STA 1W Floc RAS Pre STA soil TP Conc. TP Storage TP Conc. TP Storage TP Conc. TP Storage N mg P kg 1 g P m 2 N mg P kg 1 g P m 2 N mg P kg 1 g P m 2 EAV Cell 5A 4 1244 123 9 .3 2.2 5 532 227 17.8 13.3 5 384 122 19.7 7.9 SAV Cell 3 5 898 427 5.8 1.8 5 578 332 12.8 4.6 5 204 13 8.7 1.3 Cell 5B 7 924 176 8.1 3.9 7 509 125 15.5 6.6 7 364 108 15.5 6.5 Table E 11 Average t otal phosphorus concentration and TP storage for each soil fraction over all sampling sites in EAV and SAV cells of STA 2 [Mean SD; N= number of samples] STA 2 Floc RAS Pre STA soil TP Conc. TP Storage TP Conc. TP Storage TP Conc. TP Storage N mg P kg 1 g P m 2 N mg P kg 1 g P m 2 N mg P kg 1 g P m 2 EAV Cell 1 6 1059 221 6.2 2.4 6 340 146 5.7 2 6 177 11 3.6 0.7 Cell 2 8 1125 278 4.7 3.3 8 416 78 9.8 3.2 8 212 55 6.8 5.9 SAV Cell 3 7 766 2 93 7.5 3.9 7 532 170 13.5 5.4 7 292 65 11.5 6.6 Cell 4 ---6 696 146 18.8 5.4 6 347 155 17.1 9.5

PAGE 260

260 Table E 12 Average total nitrogen concentration and TN storage for each soil fraction over all sampling sites in EAV and SAV cells of STA 1W. [Mean SD; N= number of samples] STA 1W Floc RAS Pre STA TN Conc. TN Storage TN Conc. TN Storage TN Conc. TN Storage EAV N g Nkg 1 kg N m 2 N g Nkg 1 kg N m 2 N g Nkg 1 kg N m 2 Cell 5A 4 29.7 2.8 0.22 0.05 5 28.9 4.1 0.95 0.48 5 31.8 4.5 1.55 0.15 SAV Cell 3 5 32.8 1.4 0.27 0.16 5 36.2 7.3 0.89 0.27 5 32.6 2 1.39 0.21 Cell 5B 7 27.7 3.1 0.24 0.1 7 32.8 3.2 0.99 0.29 7 34 2.6 1.4 0.21 Table E 1 3 Total nitrogen concen tration and TN storage for each soil fraction over all sampling sites in EAV and SAV cells of STA 2. [Mean SD; N= number of samples] STA 2 Floc RAS Pre STA TN Conc. TN Storage TN Conc. TN Storage TN Conc. TN Storage EAV N g Nkg 1 kg N m 2 N g Nkg 1 kg N m 2 N g Nkg 1 kg N m 2 Cell 1 6 27.7 1.2 0.17 0.06 6 30.6 1.3 0.53 0.17 6 28.2 1.5 0.57 0.09 Cell 2 8 25.6 5.4 0.11 0.07 8 29.4 2.1 0.68 0.18 8 27.6 0.9 0.81 0.52 SAV Cell 3 7 12.4 1.9 0.12 0.03 7 24.4 6.3 0.67 0.38 7 28 6.9 0.99 0.2 Cell 4 --6 28.7 2.1 0.82 0.33 6 31.3 2 1.51 0.27

PAGE 261

261 Table E 1 4 Total carbon concentration and TC storage for each soil fraction over all sampling sites in EAV and SAV cells of STA 1W. [Mean SD; N= number of samples] STA 1W Floc RAS Pre STA TC Conc. TC Storage TC Conc. TC Storage TC Conc. TC Storage EAV N g C kg 1 kg C m 2 N g C kg 1 kg C m 2 N g C kg 1 kg C m 2 Cell 5A 4 400 9 3 0.6 5 432 42 13.8 5.8 5 478 13 23.6 3.7 SAV Cell 3 5 429 42 3.7 2.4 5 510 89 12.6 3.8 5 492 15 21 2.7 Cell 5B 7 356 37 3 1.2 7 454 21 13.7 3.7 7 477 15 19.7 2.9 Table E 1 5 Total carbon concentration TC and storage for each soil frac tion over all sampling site s in EAV and SAV cells of STA 2 [Mean SD; N= number of samples] STA 2 Floc RAS Pre STA TC Conc. TC Storage TC Conc. TC Storage TC Conc. TC Storage EAV N g C kg 1 kg C m 2 N g C kg 1 kg C m 2 N g C kg 1 kg C m 2 Cell 1 6 374 24 2.2 0.8 6 440 8 7.6 2.3 6 470 12 9.6 1.6 Cell 2 8 365 64 1.6 1 8 444 14 10.4 2.9 8 474 11 14 9.1 SAV Cell 3 7 196 21 1.9 0.5 7 376 79 10.2 5.3 7 390 96 13.7 2 Cell 4 ---6 393 44 11.4 4.8 6 457 16 22.1 3.5

PAGE 262

262 Table E 1 6 Pearson correlation coefficients for select parameters measured in soil cores from EAV cells of STA 1W. All correlations were evaluated =14). ns= not significant. STA 1W EAV Bulk density TP Ca Mg Fe Al Pi TN TC Po LOI TP 0.86 Ca ns ns Mg ns ns 0.93 Fe 0.77 0.62 ns ns Al 0.88 0.64 ns ns 0.77 Pi 0.50 0.73 0.61 0.56 ns ns TN ns ns 0.81 0.91 ns ns 0.51 TC 0.64 0.86 0.73 0.64 0.51 ns 0.81 0.53 Po 0.88 0.89 ns ns 0.66 0.76 ns ns 0.61 LOI ns 0.69 0.82 0.70 ns ns 0.71 0.51 0.94 0.45 P r 0.80 0.79 ns ns 0.59 0.72 0.54 ns 0.67 0.68 0 .48 Table E 1 7 Pearson c orrelation coefficients for select parameters measured in soil cores from SAV cells of STA = 0.05 (N =36). ns= not significant. STA 1W SAV Bulk density TP Ca Mg Fe Al Pi TN TC Po LOI TP 0.65 Ca ns 0.53 Mg ns ns 0.52 Fe 0.74 0.71 0.4 3 0.46 Al 0.66 0.57 ns ns 0.73 Pi 0.43 0.90 0.79 0.38 0.62 0.37 TN ns ns 0.42 0.35 ns ns 0.35 TC 0.30 0.56 0.67 0.32 0.46 0.32 0.72 0.79 Po 0.62 0.77 ns ns 0.48 0.42 0.53 ns 0.29 LOI 0.40 0.78 0.90 0. 48 0.67 0.47 0.92 0.45 0.78 0.30 Residual P 0.52 0.86 0.40 ns 0.54 0.58 0.73 ns 0.49 0.67 0.65

PAGE 263

263 Table E 1 8 P earson correlation coefficients for select parameters measured in soil cores from EAV cells of STA 2. All correlations were evaluated a = 0.05 (N =42). ns= not significant. STA 2 EAV Bulk density TP Ca Mg Fe Al Pi TN TC Po LOI TP 0.48 Ca ns 0.37 Mg ns ns 0.58 Fe 0.32 0.67 ns 0.38 Al 0.37 0.47 ns 0.36 0.47 Pi 0.33 0.83 0.56 ns 0.41 ns TN ns 0.27 0.61 0.67 ns ns 0.54 TC 0.44 0.77 0.73 0.41 0.42 0.28 0.83 0.65 Po 0.49 0.92 ns 0.40 0.69 0.52 0.63 ns 0.55 LOI 0.33 0.64 0.84 0.55 0.27 ns 0.80 0.76 0.95 0.37 Residual P 0.36 0.81 0.51 ns 0.49 ns 0 .74 0.26 0.73 0.69 0.65 Table E 1 9 P earson correlation coefficients for select parameters measured in soil cores from SAV cells of STA 2. All correlations were evaluated =33). ns= not significant. STA 2 SAV Bulk density TP Ca Mg Fe Al Pi TN TC Po LOI TP 0.45 Ca 0.62 0.65 Mg 0.34 0.56 0.65 Fe 0.65 0.39 0.69 0.49 Al 0.69 0.40 0.64 0.47 0.69 Pi 0.3 7 0.86 0.69 0.43 0.37 ns TN 0.48 0.55 0.82 0.47 0.64 0.35 0.70 TC 0.48 0.59 0.77 0.49 0.60 ns 0.71 0.96 Po ns ns ns ns 0.33 ns ns 0.32 ns LOI 0.38 0.40 0.72 0.43 0.46 0.34 0.59 0.85 0.86 ns Residual P 0.41 0.76 0.44 0.4 0 ns 0.30 0.57 0.39 0.44 0.50 0.36

PAGE 264

26 4 Figure E 1 Relation of TP with Po and Pi and LOI with Po in floc, RAS and pre STA soil from EAV and SAV cells of STA 1W.

PAGE 265

265 Figure E 2 Relation of TP with Po and Pi and LO I with Po in floc, RAS and pre STA soil from EAV and SAV cells of STA 2.

PAGE 266

266 LIST OF REFERENCES Acharya, G., 2000. Approaches to valuing the hidden hydrological services of wetland ecosystems. Ecological Economics. 35:63 74 Alvarez Cobelas, M.; Angeler, D.G.; Sanchez Carrillo, S.; Almendros, G., 2012. A worldwide view of organic carbon export from catchments. Biogeochemistry. 107 Andersen, J., 1976. Ignition method for determination of total phosphorus in lake sediments. Water Research. 10:3 29 331 Andersson, J.L.; Bastviken, S.K.; Tonderski, K.S., 2005. Free water surface wetlands for wastewater treatment in Sweden: nitrogen and phosphorus removal. Water Science and Technology. 51:39 46 Anisfeld, S.; Tobin, M.; Benoit, G., 1999. Sedimentation rates in flow restricted and restored salt marshes in Long Island Sound. Estuaries. 22:231 244 Armentano, T.V.; Woodwell, G.M., 1975. Sedimentation Rates in a Long Island Marsh Determined by 210 Pb Dating. Limnology and Oceanography. 20:452 456 Babatunde, A.O.; Zhao, Y.Q.; O'Neill, M.; O'Sullivan, B., 2008. Constructed wetlands for environmental pollution control: A review of developments, research and practice in Ireland. Environment International. 34 Bachand, P.A.M.; Horne, A.J., 2000. Denitrification in constructed free water surface wetlands: I. Very high nitrate removal rates in a macrocosm study. Ecological Engineering. 14:9 15 Barbier, E.B., 2011. Wetlands as natural assets. Hydrological Sciences Journal Journal Des Sciences Hydrologiques. 56 Bastian R.K.; Hammer, D.A., 1993. The use of constructed wetlands for wastewater treatment and recycling. in: Moshiri G.A., ed. Constructed wetlands for water quality improvement. Boca Raton, FL.: Lewis Publ. Battin, T.J.; Luyssaert, S.; Kaplan, L.A.; Aufdenkamp e, A.K.; Richter, A.; Tranvik, L.J., 2009. The boundless carbon cycle. Nature Geoscience. 2 Belanger, T.V.; Scheidt, D.J.; Platko, J.R., 1989. Effects of Nutrient Enrichment on the Florida Everglades. Lake and Reservoir Management. 5:101 111 Bergstrom, J.C .; Stoll, J.R.; Titre, J.P.; Wright, V.L., 1990. Economic value of wetlands based recreation. Ecological Economics. 2:129 147 Bhadha, J.H.; Jawitz, J.W.; Min, J.H., 2011. Phosphorus Mass Balance and Internal Load in an Impacted Subtropical Isolated Wetland Water Air and Soil Pollution. 218:619 632

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287 BIOGRAPHICAL SKETCH Rupesh Kumar Bhomia was born in a small town Pilani, in the state of Rajasthan, India. His early childhood and education was spread across various locations in northern changed jobs from one paper manufacturing unit to another. T h os e paper mills were generally located in the rural forested regions of the country and growing in the shadow of those tall smoke stack s, Rupesh developed a curious desire to study learn more about natural environment at an early age. That desire was officially fulfilled in 2001 when he enrolled for a M.Sc. program at t he S chool of Environmental Sciences, Jawaharlal Nehru University New Delhi He then had the privilege to attend Worchester College, Oxford University ; graduating in 2004 with M.Sc. in Biodiversity, Conservation and Management. He returned to India and was employed at the Indian Institute of Forest Management (IIFM), Bhopal where he managed a project on Sustainable Forest Management In mid 2005, he joined a non governmental organization WWF India based in New Delhi While at the Forests Division of WWF India, he managed multiple projects on Protected Area management, ecoto urism and sustainable livelihoods, and conducted forest officers training workshops In 2008, he was recruited by Dr. K. R. Reddy in the Wetlands Biogeochemistry Laboratory, at the University of Florida. This dissertation is the center piece of his rewardin g academic journey since then