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Nutrient Dynamics in Florida Springs and Relationships to Algal Blooms

Permanent Link: http://ufdc.ufl.edu/UFE0024853/00001

Material Information

Title: Nutrient Dynamics in Florida Springs and Relationships to Algal Blooms
Physical Description: 1 online resource (156 p.)
Language: english
Creator: Albertin, Andrea
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: algae, florida, isotopes, lyngbya, nutrients, stoichiometry, vaucheria
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: NUTRIENT DYNAMICS IN FLORIDA SPRINGS AND RELATIONSHIPS TO ALGAL BLOOMS Increased abundance of filamentous algae has been observed in many of Florida?s karst springs over the past 50 years and has been associated with increased ambient nitrate concentrations. However, no quantitative relationship exists between nitrate concentrations and algal biomass. Studies were conducted to assess nutrient dynamics in Florida springs, particularly the effects of increased nitrate levels on the growth of Lyngbya wollei, and Vaucheria sp., the two most common mat-forming algal species found in these springs. Threshold values of nitrate for algal growth were studied in two recirculating stream experiments. The stable isotopes of algae and spring sediments (d15N and d13C) as well as nitrate (d15N-NO3 and d18O-NO3) and dissolved organic carbon (d13C) in spring water were assessed regionally, at multiple boil sites throughout North central Florida and the Panhandle and along four spring river runs. Additionally, seasonal variation in stable isotope composition of algae was measured over the course of one year at two springs. In the final study, nutrient cycling within algal mats and in adjacent sediments was assessed using interstitial water samplers and advective and diffusive flow through mats was estimated. Results indicate that Lyngbya wollei growth is stimulated by nitrate additions despite very low phosphorus conditions. Multiple factors are likely affecting stable isotopic values in algae, but results point to relatively distinct species-specific ?13C compositions, which may be indicative of an algae?s relative uptake of and degree of preference for CO2 (aq) vs. HCO3- as a carbon source. Unlike ?13C, algal ?15N values did not show strong species-specific signatures. Finally, thick algal mats contain relatively large amounts of nutrients, particularly NH4+ and organic phosphorus, and diffusion of nutrients occurs out of algal mats into the sediment as well as into the overlying water column.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Andrea Albertin.
Thesis: Thesis (Ph.D.)--University of Florida, 2009.
Local: Adviser: Clark, Mark W.
Local: Co-adviser: Sickman, James.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024853:00001

Permanent Link: http://ufdc.ufl.edu/UFE0024853/00001

Material Information

Title: Nutrient Dynamics in Florida Springs and Relationships to Algal Blooms
Physical Description: 1 online resource (156 p.)
Language: english
Creator: Albertin, Andrea
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: algae, florida, isotopes, lyngbya, nutrients, stoichiometry, vaucheria
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: NUTRIENT DYNAMICS IN FLORIDA SPRINGS AND RELATIONSHIPS TO ALGAL BLOOMS Increased abundance of filamentous algae has been observed in many of Florida?s karst springs over the past 50 years and has been associated with increased ambient nitrate concentrations. However, no quantitative relationship exists between nitrate concentrations and algal biomass. Studies were conducted to assess nutrient dynamics in Florida springs, particularly the effects of increased nitrate levels on the growth of Lyngbya wollei, and Vaucheria sp., the two most common mat-forming algal species found in these springs. Threshold values of nitrate for algal growth were studied in two recirculating stream experiments. The stable isotopes of algae and spring sediments (d15N and d13C) as well as nitrate (d15N-NO3 and d18O-NO3) and dissolved organic carbon (d13C) in spring water were assessed regionally, at multiple boil sites throughout North central Florida and the Panhandle and along four spring river runs. Additionally, seasonal variation in stable isotope composition of algae was measured over the course of one year at two springs. In the final study, nutrient cycling within algal mats and in adjacent sediments was assessed using interstitial water samplers and advective and diffusive flow through mats was estimated. Results indicate that Lyngbya wollei growth is stimulated by nitrate additions despite very low phosphorus conditions. Multiple factors are likely affecting stable isotopic values in algae, but results point to relatively distinct species-specific ?13C compositions, which may be indicative of an algae?s relative uptake of and degree of preference for CO2 (aq) vs. HCO3- as a carbon source. Unlike ?13C, algal ?15N values did not show strong species-specific signatures. Finally, thick algal mats contain relatively large amounts of nutrients, particularly NH4+ and organic phosphorus, and diffusion of nutrients occurs out of algal mats into the sediment as well as into the overlying water column.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Andrea Albertin.
Thesis: Thesis (Ph.D.)--University of Florida, 2009.
Local: Adviser: Clark, Mark W.
Local: Co-adviser: Sickman, James.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024853:00001


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1 NUTRIENT DYNAMICS IN FLORIDA SPRINGS AND RELATIONSHIPS TO ALGAL BLOOMS By ANDREA RUTH ALBERTIN A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR TH E DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2009

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2 2009 Andrea Ruth Albertin

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3 To my husband, Francisco, for all of your loving support

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4 ACKNOWLEDGMENTS I thank my advisors, Dr. James Sickma n and Dr. Mark Clark for all of their support and encouragement throughout these four years. This has been an incredibly enriching experience. I would also like to thank the rest of my committee members, Drs. H. Popenoe, M. Brenner and E. Phlips for all of their input and support. The results of this study are a collaborative effort among people in numerous institutions and departments within UF. I thank all of you: Martin Anderson, Delores Lucero, Aga Pinowska, Mi Youn Ahn, R. Jan Stevenson, Scott Fulbrigh t, Kathleen McKee, Sylvia Lang, Kevin Ratkus, Ed Dunne, Jordan Mayor, Kathy Curtis, Jason Curtis, Alicia Peon, Cynthia Gomez -Martin, Leonardo Martinez, Antonio de la Pena, Jenny Saqui, Pio Saqui, Dina Liebowitz, Larry Korhnak, Matt Cohen, Andy Ogram, Rupes h Bhodia, Dakshina Kadiyala, Jaya Das, Jango Badha, Eric Ostmark, Martin Sandquist, Alyson Dagang, Solomon Haile, Yu Wang, Gavin Wilson, Yubao Cao, Cheryl Combs, Rhiannon Pollard, Kelly Jacoby, Grace Crummer, Ted Schuur, Melissa Martin, Haryun Kim, Hiral G ohil, Moshe Dorin, Abid Al -Agely, Robert Compitello, Todd Osbourne, Kanika Inglett, Patrick Inglett, Tae Goo Oh. I thank the Florida Department of Environmental Protection, particularly Russ Frydenborg and Denise Miller for funding and for their support of the project as well as the numerous park rangers that helped me while I was doing my field work in springs within the Florida State Parks system Finally, I would like to deeply thank my family, my husband Chico, my mother Verena, my sisters Helena and Christina and my brothers -in -law, Mark and Stefan for all of their unwavering support throughout these four years.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................................... 4 LIST OF TABLES ................................................................................................................................ 8 LIST OF FIGURES ............................................................................................................................ 10 ABSTRACT ........................................................................................................................................ 12 CHAPTER 1 INTRO DUCTION ....................................................................................................................... 14 2 GROWTH RESPONSEOF LYNGBYA WOLLEI TO NITRATE ADDITIONS UNDER CONDITIONS OF LOW PHOSPHORUS ................................................................ 16 Introduction ................................................................................................................................. 16 Methods ....................................................................................................................................... 19 Study Site and Experimental Setup .................................................................................... 19 Nutrient Dosing .................................................................................................................... 20 Algae Collection and Sample Preparation ......................................................................... 21 Water Sampling and Analysis ............................................................................................. 22 Algae Sampling and Analysis ............................................................................................. 24 Statistical Analysis ............................................................................................................... 24 Results .......................................................................................................................................... 25 Water Chemistry .................................................................................................................. 25 Algal Relative Growth Rate ................................................................................................ 26 C:N:P Ratios of Algal Tissue .............................................................................................. 27 Lyngbya wollei Growth Response to Nitrate Additions .................................................... 29 Discussion .................................................................................................................................... 29 Algal Response to Nitrogen Additions under Apparent Phosphorus Limitation............. 29 Nutrient Criteria for Florida Springs .................................................................................. 34 3 15N STABLE ISOTOPE COMPOSITION OF ALGAE, SEDIMENT AND NITRATE IN FLORIDA SPRINGS ............................................................................................................ 53 Introduction ................................................................................................................................. 53 Methods ....................................................................................................................................... 55 Study Sites ............................................................................................................................ 55 Algae, Sediment and Water Sample Collection ................................................................. 56 Algae, Sediment an d Water Sample Processing and Analysis ......................................... 57 Rapid Habitat and Periphyton Assessment (RHPA) ......................................................... 59 Statistical Analysis ............................................................................................................... 59 Results .......................................................................................................................................... 60 15N NO3 18O NO3) ............................ 60

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6 15N .................................................................................................... 60 Correlations among Algal Stable Isotope Signatures, Water Quality and Environmental Variables ................................................................................................. 61 Stable Isotopic Variation along Longitudinal Gradients ................................................... 62 Dual Isotope Analysis of Spring Water Nitrate along Longitudinal Gradients ....... 62 Silver Springs River Run ............................................................................................. 62 Weeki Wachee Springs River Run .............................................................................. 63 Rainbow Springs River Run ........................................................................................ 63 Wakulla Springs River Run ......................................................................................... 63 15N ..................................................................................... 64 Discussion .................................................................................................................................... 64 15N NO3 18O NO3) .................... 64 15N of Algae and Sediment ............................................................................................... 69 15N Gradients in Spring -Fed River Runs .......................................................................... 71 15N ........................................................................................ 72 Conclusion............................................................................................................................ 73 4 13C STABLE ISOTOPE COMPOSITION OF ALGAE, SEDIMENT AND DISSOLVED INORGANIC CARBON IN FLORIDA SPRINGS ......................................... 83 Introduction ................................................................................................................................. 83 Methods ....................................................................................................................................... 85 Study Sites ............................................................................................................................ 85 Algae, Sediment and Water Sample Collection ................................................................. 86 Algae, Sediment and Water Sample Processing and Analysis ......................................... 86 13C13C of Algae ........... 88 Statistical Analysis ............................................................................................................... 89 Results .......................................................................................................................................... 89 Analysis of Algae and Sediment Stable Isotopes and C:N Molar Ratios ........................ 89 Variation in Isotope Signatures among Algal Species ...................................................... 91 Correlations among Algal Stable Isotope Signatures, Water Quality and Environmental Variables ................................................................................................. 91 Relationships between Total Dissolved Inorgani 13C of Dissolved Inorganic Carbon and Algae .......................................................................... 92 13C of Algae and Sediment along Longitudinal Gradients ......................... 92 Rainbow Springs River Run ........................................................................................ 93 Weeki Wachee Springs River Run .............................................................................. 93 Wakulla Springs River Run ......................................................................................... 93 Silver Springs River Run ............................................................................................. 94 13C ........................................................................................ 94 Discussion .................................................................................................................................... 94 Dissolved Inorganic Carbon in Florida Springs ................................................................ 94 13C Values in Algae ............................................................................. 97 13C ........................................................ 100 13C Values in Spring Sediments ....................................................... 101 5 NUTRIENT PROFILES OF ALGAL MATS IN FLORIDA SPRINGS .............................. 113

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7 Introduction ............................................................................................................................... 113 Methods ..................................................................................................................................... 114 Sampling Locations ........................................................................................................... 114 Algal Mat Nutrient Profile s ............................................................................................... 114 Chemical Sampling and Laboratory Analyses ................................................................. 115 Nutrient Diffusion Out of Algal Mats .............................................................................. 117 Algal Mat Tracer Study ..................................................................................................... 117 Results ........................................................................................................................................ 118 Interstitial Nutrient Profiles in Large Algal Mats ............................................................ 118 Manatee Springs ......................................................................................................... 118 Weeki Wachee ............................................................................................................ 119 Silver Glen .................................................................................................................. 120 Stable Isotope Composition and C:N:P Ratios in Algal Mat Profiles ............................ 120 Diffusive Flux out of Algal Mats ...................................................................................... 122 NaCl Tracer Experiments in Large Algal Mats ............................................................... 122 Discussion .................................................................................................................................. 123 6 CONCLUSION ......................................................................................................................... 141 APPENDIX LOCATIONS OF SAMPLING SITES ................................................................. 143 LIST OF REFERENCES ................................................................................................................. 145 BIOGRAPHICAL SKETCH ........................................................................................................... 156

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8 LIST OF TABLES Table page 2 1 Target nitrate concentrations for Experiments 1 and 2. ....................................................... 37 2 2 FLZ8 micronutrient concentrations ....................................................................................... 38 2 3 1) and DIN/TP ratio for Experiment 1. N refers to the number of stream channels per treat ment. .......................... 39 2 4 1) for Experiment 2. N refers to the number of stream channels per treatment. ...................................................................... 41 2 5 Repeated measures analysis of variance for Lyngbya wollei relative growth rates and nutrient molar ratios in Experiments 1 and 2. Significant P values (p<0.05) are shown in bold. ........................................................................................................................ 43 2 6 Repeated measures analysis of variance for Vaucheria sp. relative growth rates and nutrient molar ratios in Experiments 1 and 2. Significant P values (p<0.05) are shown in bold. ........................................................................................................................ 44 2 7 Initial and final C:N, C:P and N:P molar ratios of Lyngbya wollei in Experiments 1 and 2. Target treatment concentrations (NO3 1) are shown below treatment numbers. .................................................................................................................................. 45 2 8 Initial and final C:N, C:P and N:P molar ratios of Vaucheria sp. in Experiments 1 and 2. Target treatment concentrations (NO3 1) are shown below treatment numbers. .................................................................................................................................. 46 2 9 Parameter estimates of t he dose response curve (model) for Lyngbya wollei Relative growth rate (RGR) data from Experiments 1 and 2 were combined. ................................. 47 2 10 Estimated effect doses (ED) of NO3 for Lyngbya wollei. .................................................... 48 3 1 15N NO3 18O NO3) from 17 Florida springs sampled in 2005, 2006 and 2008. Water samples were collected directly above the boil of each spring, at a depth of 0.5 m. ............................................................................................ 74 3 2 Significant Spearman correlations (p 1515N and indicators of nutrient availability and nutrient sources ................................................. 75 3 3 Spring river run longitudinal s tudy site numbers, site codes and their distance from the spring boil (km). ............................................................................................................... 76 4 1 Significant Spearman correlations (p 1313C and indicators of nutrient a vailability and nutrient sources ............................................... 104

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9 5 1 Dates of multisampler deployment, and the make up and condition of algal mats in three Florida springs. ............................................................................................................ 127 5 2 water chemistry of three algal mats found in Florida Springs, 2006. Multisampler depth is in cm and water chemistry concentrations are in mg/L. ...................................... 128 5 3 Specific discharges through algal mats at three springs. ................................................... 129 5 4 Diffusion flux out of a large Lyngbya wollei mat (Weeki Wachee Springs) and out of a la rge, senescing Vaucheria sp. mat (Manatee Springs) in April 2006 ........................... 130

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10 LIST OF FIGURES Figure page 2 1 Cross -sectional view of a single stream channel ................................................................. 49 2 2 Lyngbya wollei relative growth rates (RGR) under different nitrate concentrations during Experiments 1 and 2. .................................................................................................. 50 2 3 Va ucheria sp. relative growth rates (RGR) under different nitrate concentrations during Experiments 1 and 2. .................................................................................................. 51 2 4 Lyngbya wollei relative growth rate dose response curve ................................................... 52 3 1 15N NO3 18O NO3) from 17 Florida springs sampled in 2005, 2006 and 2008. Water samples were collected directly above the boil of each spring, at a depth of 0.5 m. R2 = 0.71 and the slope of the line is 0.64. ..................... 77 3 2 1515N NO3 of springwater from 10 headwater springs sampled in 2006. .................................................. 78 3 3 15N values of algae, sediments and nitrate in NO3 of spring water and nitrate concentrations (mg L1) of 10 headwater springs sampled in 2006. ........................................................................................................................................ 79 3 4 Stable isotope composition of nitrate in spring water from the Rainbow, Silver, Wakulla and Weeki Wachee River runs sampled in 2006 .................................................. 80 3 5 Stable isotope co 15N NO3 of spring water measured along four spring river runs in January 2006 .................................................................................. 81 3 6 15N composition of algae at Ichetucknee Blue Hole and Manatee Springs from May 2005 to March 2006. .............................................................................................................. 82 4 1 Stable isotope composition of algae and sediment from 63 spring sites sampled in 2006. ...................................................................................................................................... 105 4 2 The relat 13C and C:N molar ratio of algae and sediment from 63 spring sites sampled in 2006. ......................................................................................... 106 4 3 Stable isotope composition of Lyngbya wollei Vaucheria sp. and Spirogyra sp. f rom 61 spring sites, 2006. ............................................................................................................ 107 4 4 13C of the three dominant algal species and spring water pH at boil areas sampled in 2006. Each trend line is for a particular species: Vaucheria sp., r2 = 0.48, Lyngbya wollei r2 = 0.40 and Spirogyra sp., r2 = 0.41. .......... 108

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11 4 5 1313C of DIC and pH of headwater sprin gs sampled in April and August 2008 ...................................................... 109 4 6 Relationships between spring water total DIC (mg C L113C of DIC and pH of headwater springs sampled in April and August 2008 ...................................................... 110 4 7 13C composition of algae and sediment measured along four spring river runs in January 2006. ........................................................................................................................ 111 4 8 13C composition of algae at Manatee Springs and Ichetucknee Blue Hole from May 2005 to March 2006. ............................................................................................................ 112 5 1 Location of multisampler deployments and investigations of nutrient profiles and movement within algal mats. Map made by Martin Anderson. ........................................ 131 5 2 Multisampler device used to collect water column, algal mat and sediment interstitial waters. ................................................................................................................................... 132 5 3 Chemical profiles measured by multisamplers at Manatee Springs on April 19, 2006. At each spring, two replicate samplers were simultaneously installed ............................. 133 5 4 Chemical profiles measured by mul tisamplers at Manatee Springs on August 24, 2006. At each spring, two replicate samplers were simultaneously installed .................. 134 5 5 Chemical profiles measured by multisamplers at Weeki Wachee Sprin gs on April 19, 2006 ....................................................................................................................................... 135 5 6 Chemical profiles measured by multisamplers at Weeki Wachee on August 23, 2006. At each spring, two replicate samplers were simultaneously installed ............................. 136 5 7 Chemical profiles measured by multisamplers at Silver Glen Springs September 5, 2006. At each spring, two replicate samplers were simultaneously installed .................. 137 5 8 Stable isotope profile of algae and sediment surrounding Multisampler 1 at Weeki Wachee Springs, August 23, 2006 ...................................................................................... 138 5 9 Stable isotope profile of Lyngbya wollei a nd sediment surrounding Multisampler 2 at Silver Glen Springs, September 2, 2006. ............................................................................ 139 5 10 Profiles of tracer dilution at three springs ........................................................................... 140

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12 Abstract of Diss ertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy NUTRIENT DYNAMICS IN FLORIDA SPRINGS AND RELATIONSHIPS TO ALGAL BLOOMS By Andrea Ruth Albertin August 2009 Chair: Mark W. Clark Cochair: James O. Sickman Major: Soil and Water Science Increased abundance of filamentous algae has been observed in many of Floridas karst springs over the past 50 years and has been associated with increase d ambient nitrate concentrations. However, no quantitative relationship exists between nitrate concentrations and algal biomass. Studies were conducted to assess nutrient dynamics in Florida springs, particularly the effects of increased nitrate levels on the growth of Lyngbya wollei and Vaucheria sp., the two most common mat -forming algal species found in these springs. Threshold values of nitrate for algal growth were studied in two recirculating stream experiments. The stable isotopes of algae and sprin g sediments ( 15N and 13C) as well as nitrate (15N NO3 and 18O NO3) and dissolved organic carbon ( 13C) in spring water were assessed regionally, at multiple boil sites throughout North central Florida and the Panhandle and along four spring river runs. Additionally, seasonal variation in stable isotope composition of algae was measured over the course of one year at two springs. In the final study, nutrient cycling within algal mats and in adjacent sediments was assessed using interstitial water sampler s and advective and diffusive flow through mats was estimated. Results indicate that Lyngbya wollei and Vaucheria sp. growth is stimulated by nitrate additions despite very low phosphorus conditions.

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13 Multiple factors are likely affecting stable isotopic val ues in algae, but results point to relatively distinct species -13C compositions, which may be indicative of an algaes relative uptake of and degree of preference for CO2 (aq) vs. HCO3 1315N values did not show strong species -specific signatures. Finally, thick algal mats contain relatively large amounts of nutrients, particularly NH4 + and organic phosphorus, and diffusion of nutrients occurs out of algal mats into the sediment as well as into the overlying water column.

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14 CHAPTER 1 INTRODUCTION More than 700 karst springs are found in the state of Florida and their discharge comes from underlying aquifer systems. These aquifers are recharged by seepage from the surface and by sinking streams and sinkholes, m aking the groundwater that feeds springs particularly susceptible to human activities and land use within a spring recharge basin. Nitrate levels have increased in most springs over the last 50 years, while P concentrations have remained relatively low (Sc ott et al. 2004). Increased nuisance growth of algae observed in springs throughout the state has been associated with increased concentrations of nitrate in the water (Florida Springs Task Force, 2000) although N:P ratios and algal growth potential assays indicate that P alone or both N and P in combination limit algal growth (Stevenson et al. 2007; Pinowska et al. 2009). Additionally, extensive surveys conducted at springs throughout the state indicate that nutrient supply rates alone do not control the distribution of algae (Pinowska et al., 2009). The Florida Springs Research Initiative was created by the state in 1999 in order to develop management strategies and establish nutrient criteria to reduce the adverse effects of increased nutrient loading in springs. This study forms part of a larger project conducted in collaboration with Drs. A. Pinowska and R.J. Stevenson from Michigan State University, funded by the Florida Department of Environmental Protection as part of the Springs Initiative. A pri mary goal of the project was to help establish water quality targets, mainly nitrate concentration levels, for Florida springs. The overall objective of my research was to assess nutrient dynamics in Florida springs, particularly the effects of increased nitrate levels on the growth of Lyngbya wollei and Vaucheria sp., the two most common nuisance algae found in these springs. Four studies were conducted. In the first study (discussed in Chapter 2), two recirculating stream experiments were

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15 conducted to t est the effect of nitrate additions on the growth of Lyngbya wollei and Vaucheria sp. under conditions of low phosphorus, conditions found in many springs throughout the state. Additionally, I sought to obtain threshold values for nitrate stimulation of al gal growth that could be used in nutrient criteria establishment. I used stable isotope analysis in two studies to determine nitrate and carbon sources to benthic algal mats and possible factors controlling algal abundance, discussed in Chapters 3 and 4. T he stable isotopes of nitrate ( 15N and 18O) and dissolved inorganic carbon ( 13C -DIC) in spring water were measured at multiple headwater springs throughout north central Florida. Algae and spring sediments ( 15N and 13C) were measured regionally, at multiple boil sites throughout north central Florida and the Panhandle and along four spring -fed river runs, the Weeki Wachee, Rainbow, Silver and Wakulla Rivers. Finally, seasonal variation in stable isotope composition of algae was measured over the course of one year at two springs, M anatee and Ichetucknee Blue Hole. In the fourth study, discussed in Chapter 5, the primary objective was to determine the potential for thick Lyngbya wollei and Vaucheria sp. mats to regenerate nutrients to sustain algal growth. Interstitial water samples were used to obtain nutrient profiles within algal mats and I estimated advective and diffusive movement of dissolved nutrients out of large algal mats

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16 CHAPTER 2 GROWTH RESPONSEOF LYNGBYA WOLLEI TO NITRATE ADDITIONS UNDER CONDITIONS OF LOW PHOSPHORUS I ntroduction Eutrophication is a severe problem in aquatic ecosystems world -wide and often results in the undesirable proliferation of algae. Solutions usually involve prescriptive reductions in nutrient loading from point and nonpoint pollution sources, however, much controversy exists over the total and relative amounts of nutrient reduction required to reverse eutrophication effects (Schindler et al ., 2008; Howarth & Paerl 2008; Lewis and Wurtsbaugh 2008). In freshwater systems, nitrogen and phosphorus are the two most important nutrients determining algal growth (Elser et al. 2007; Borchardt, 1996), and phosphorus has traditionally been considered more likely to limit primary production than nitrogen (Hutchinson 1957). In a long -term whole -lake study, Schindler et al (2008) found that P additions, with no N additions, maintained eutrophic conditions, with no reduction in phytoplankton biomass. They additionally suggest that reducing N can favor N -fixing cyanobacteria and therefore, mitigation efforts i n freshwater systems and possibly estuaries, should focus on P reduction. However, in a large meta analysis study of nitrogen and phosphorus bioassay experiments, Francoeur (2001) found that nitrogen was as likely to limit algal biomass growth as phosphoru s in lotic environments. Similar results were found by Dodds & Welch (2000). Howarth & Paerl (2008) argue that both N and P mitigation efforts are required to control coastal eutrophication and Lewis & Wurtsbaugh (2008) propose a new N+P control paradigm of nutrient limitation in freshwater systems to replace the original P paradigm. They state, though, that reducing phosphorus loads is still likely to be the most practical management tool for controlling phytoplankton abundance. In many of Floridas karst springs, N:P ratios and algal growth potential assays indicate that P alone or both N and P in combination (i.e., co -limitation) limit algal growth (Stevenson et

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17 al. 2007; Pinowska et al. 2009). Yet, increases in filamentous algae in Florida springs are often attributed to N rather than P since N concentrations have been increasing in many springs, while P concentrations have remained relatively stable and low (Florida Springs Task Force, 2000; Scott et al. 2004). Strong (2004) found significant increase s in mean nitrate N concentrations over the last 100 years in a population of 109 springs (from 0.43 to 1.13 mg L1), but no significant changes in orthophosphate were found in a population of 35 springs where values ranged from 0.046 to 0.096 mg L1. Nitr ate N increased in the spring -fed Rainbow River between 1957 and 2006 from 0.08 mg N L1 to 1.22 mg N L1 (Cowell & Dawes, 2008) and nitrate concentrations of several springs in the Suwannee River Basin have increased in the last 40 years (from 0.1 mg N L1 to more than 5 mg N L1) (Hornsby & Ceryak, 1999 cited in Katz et al., 1999). Phosphorus concentrations are thought to remain low in most springs due to the rapid adsorption of phosphorus by calcitic soils and by the limestone matrix of the aquifer (Rhue Harris & Nair, 2006; Cohen, 2008). Potential sources of nitrate to groundwater and springs in Florida include inorganic fertilizers, confined animal feeding operations, sewage effluent and atmospheric deposition (Bacchus & Barile, 2005; Katz et al., 1999). Lyngbya wollei (Farlow ex Gomont) Speziale and Dyck, and Vaucheria sp. De Candolle are the two most common filamentous algae found in Florida springs, forming large benthic or floating algal mats (often more than 1 m thick and 2+ meters wide) (Stevenso n et al., 2004; Stevenson et al. 2007). Algal mats can be detrimental to spring ecology by out competing native submerged aquatic vegetation (Doyle & Smart, 1998) and algal decay can cause oxygen depletion in the water column (Anderson, Gilbert & Burkhold er, 2002). Dense algal mats also interfere with the recreational use of springs in Florida (Cowell & Botts, 1994), particularly L. wollei mats which can cause an allergic reaction known as swimmers itch due to the

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18 production of lyngbyatoxin and aplysia toxin (Mynderse et al. 1977; Cardellina, Marner & Moore, 1979). Although most of the observed increase in algal biomass in Florida springs is anecdotal, a recent study by Quinlan et al. (2008) of Silver Springs, one of the largest springs in Florida, foun d that the epiphytic and algal mat biomass is higher today than that reported in 1957 (Odum, 1957a). At the same time, nitrate concentrations in the water had doubled, from 0.50 mg to 1.1 mg N L1(Phelps, 2004 cited by Quinlan et al. 2008). Reference stud ies by Odum (1957b) and Whitford (1957) also provide estimates of earlier algal species composition and biomass from which to draw comparisons, adding weight to the argument that algal biomass has increased in many springs. However, it is unclear how incre asing nitrogen inputs to Florida springs can cause eutrophication when algal and springwater stoichiometry suggests P limitation. Liebigs Law of the Minimum states that growth is controlled not by the total supply of nutrients, but by the nutrient in sca rcest supply (Hooker, 1917). This principle of nutrient control of primary production has been validated in many studies which tested algal growth response to altered N and/or P supply (e.g. Francoeur, 2001; Elser et al., 2007). But few experiments have ad dressed the question of whether additions of a nonlimiting nutrient can cause increased algal growth when another nutrient is found in limiting amounts, e.g., can algal growth be stimulated by additions of nitrogen under conditions of apparent phosphorus limitation? The main objective of my study was to determine if nitrate additions could stimulate growth of Lyngbya wollei and Vaucheria sp. under conditions of apparent phosphorus limitation, simulating what is believed to have occurred in many Florida spr ings during the 20th Century. In doing so, I also sought to establish threshold values for nitrate stimulation of algal growth that could be used as nutrient criteria for Floridas springs. Additionally, I investigated the influence

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19 of varying nitrate conc entrations on algal molar C:N:P ratios under conditions of low phosphorus. However, due to confounding results with Vaucheria growth data, only experimental results for L. wollei will be presented and discussed. I used a series of recirculating stream chan nels (Rier & Stevenson, 2006; Mulholland et al. 1991), operated under controlled laboratory conditions to test two specific hypotheses in regard to algal growth in Florida springs: (1) L. wollei growth can increase with additions of nitrate under conditions of apparent phosphorus limitation (i.e., less than the Redfield N:P ratio of 16:1) and (2) threshold values of nitrate concentration for algal growth exist for L. wollei Methods Study Site and Experimental Setup Two experiments were carried out in a cl imate controlled greenhouse on the University of Florida campus in Gainesville, Florida between March 21 and May 25, 2006. Both studies were conducted in 20 recirculating stream channels. Each channel consisted of a closed loop made of 5 -cm diameter PVC pi pe, 122 cm long and 91 cm tall. The upper horizontal section of the stream channel was cut in half length -wise to provide a channel for the algal cultures to grow in ambient sunlight (Figure 2 1). Groundwater from the Floridan Aquifer and a nutrient soluti on of nitrate plus micronutrients were continuously added to the recirculating streams using two peristaltic pumps. The groundwater was obtained on the University of Florida campus from a 350ft well and had low nutrient concentrations (NO2 + NO3 < 1 g N L1, soluble reactive phosphorus = 9 g P L1); there are only a few natural springs in Florida with lower N and P concentrations (Stevenson et al., 2004). Although using water from a low -nutrient -concentration spring would have been ideal, it was logistically infeasible given time and transportation constraints (the nearest spring was over 3 hours away by car). Every 3 to 4 days, 350 gallons of well water were pumped into a

PAGE 20

20 plastic tank and trucked to the greenhouse. The anoxic well water was aerated for 24 hours to remove hydrogen sulfide (H2S) before the water was added into the stream channels; high levels of H2S are harmful to algae. During the oxygenation process nearly all of the ambient iron in the water was precipitated, therefore iron and other m icronutrients were included in the experimental nutrient additions to reach ambient levels in natural springs and avoid micronutrient limitation. Earlier studies of Florida springs indicate that micronutrient limitations is not likely in situ (Stevenson et al., 2004) Before nutrient dosing occurred in Experiments 1 and 2, the stream channels were sterilized by soaking in a 5% bleach solution for approximately 24 hours, rinsed and soaked in tap water for 48 hours and then soaked with water from the Floridan Aquifer for 4 days. All the tubing used in the experiment was also soaked for 4 days in water from the aquifer prior to nutrient dosing. Continuous water flow in each channel was maintained with an air pump which produced bubbles that lifted the water (e.g an air lift), causing it to circulate. Current velocity was maintained at approximately 25 cm s1 using a valve in each stream channel that controlled the amount of air that was pumped into the channel. This flow rate is a good approximation of the water velocity found in many first magnitude springs in Florida. A small hole (0.7 cm) was drilled at the end of each stream channel to allow excess water to flow out. There was a complete turnover of water in each channel every eight hours, with an injection r ate of 15.1 ml min1. To help regulate stream channel water temperature, the channels were operated in a large pool of water made up of concrete blocks covered with pond lining which was filled with 0.5 m of water. Nutrient Dosing Experiment 1 was run for 28 days and consisted of 7 treatments: 2 treatments with no nitrate additions (Control A and Control B) and 5 treatments of varying nitrate additions (from 1

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21 1) in the form of NaNO3 (Table 2 1). All but one of the control treatments (Control A) received a micronutrient supplement (FLZ8) to prevent micronutrient limitations during the course of the experiment (Table 2 2). The micronutrient solution was continuously pumped into each channel at a rate of 0.198 ml min1. The supplement was adapte d from the Z8 medium (Kotai, 1972) to reflect median water chemistry in Flor ida springs based on extensive field surveys in 2003 (Stevenson, Pinowska & Wang, 2004). The only P the algae received came from the well water and any P that was released from the algal tissues themselves and subsequently assimilated. All treatments were randomly assigned to three stream channels except for the control treatment with no micronutrient additions, which was randomly assigned to two stream channels. Based on the results from Experiment 1, a narrower range of nitrate levels was tested in Experi ment 2. Experiment 2 was run for 21 days and consisted of 7 treatments: 1 control treatment with no nitrate additions and 6 treatments of nitrate additions (in the form of NaNO3) ranging from 25 to 750 g N L1 (Table 2 1). All seven treatments received the FLZ8 micronutrient supplement used in Experiment 1 (Table 2 2) at the same injection rate (0.198 ml min1) and P was not added to any treatment. The six treatments receiving nitrate additions were ran domly assigned to three stream channels and the control treatment was randomly assigned to two stream channels. Algae C ollection and Sample Preparation The Vaucheria sp. used in Experiments 1 and 2 was collected in the boil area of Alexander Springs in the Ocala National Forest (latitude 29.08128, longitude 81.57563). The Lyngbya wollei for Experiment 1 was collected in the boil area of Ichetucknee Head Springs (latitude 29.98408, longitude 82.76184) and in the boil area of Alexander Springs for Experiment 2.

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22 bolting cloth ( TETKO Inc., Elmsford, NY, U.S.A.) to remove excess moisture and then weighed. The fresh mass of each fragment was 1g ( 0.1 g). Each weighed fragment was then attached to an unglazed 2.5 cm2 white ceramic tile with one small rubber band, making sure that the majority of filament ends were loose and free -floating. The tiles were previously soaked for 2 weeks in deionized water. Six tiles each of Vaucher ia sp. and L. wollei were randomly placed in every stream channel for Experiment 1. Nine tiles per species were placed in each stream channel for Experiment 2. During both experiments, all 20 streams were covered with a gray plastic screen placed four inch es above the channels to reduce incident light levels by approximately 50%, to prevent photo inhibition and better represent field conditions. With the screen in place, light levels reaching the algae at 12:00 pm varied from as low as 130 mol m2s1 duri ng cloudy days to as high as 850 mol m2s1 during sunny days. Light measurements were taken using a Licor Li 192 underwater quantum sensor (LI COR, Inc. Lincoln, NE, U.S.A.) Water Sampling and A nalysis During Experiments 1 and 2, temperature, conductiv ity, pH, and dissolved oxygen (DO) were measured every three days in every stream channel using a YSI 556 Multi probe System (YSI Incorporated, Yellow Springs, OH, U.S.A.). For Experiment 1 (four weeks duration), the pH ranged from 6.3 to 8.8, the DO from 8.3 to12 mg L1, the conductivity range was 292 to 357 1 and the temperature range was 19.6 to 22.4 C. During Experiment 2 (3 weeks duration), the pH range was 7.0 to 8.6 and the DO ranged from 3.5 to 9.9 mg L1. The conductivity range 1 and temperature ranged from 19.1 to 21.6 C. Oxygen concentrations, particularly for Experiment 1, were often higher than what is found in the upwelling areas of many springs, but within the range of concentrations found in lower reaches

PAGE 23

23 of spring -fed rivers, where DO concentrations range from 0.9 to 10 mg L1 and algae is found in high abundance (Stevenson et al. 2004). These relatively high DO levels were unavoidable since the stream channels were aerated in order to maintain circulation. All other parameters were always within the range of values found in Florida springs. Temperature was measured throughout the course of the experiments in two stream channels every 15 minutes with a HOBO H8 Outdoor/industrial 4 channel external data logger (Onset Computer Corporation, Bourne, MA, U .S.A.). The average temperature was 21.0 C during Experiment 1 and 20.5 C during Experiment 2. Water samples for chemical analyses were taken five times during Experiment 1 (Days 0, 7, 14, 21 and 28) and four times during Experiment 2 (Days 0, 7, 14 and 21). The samples were analyzed for total Kjeldahl nitrogen (TKN), total phosphorus (TP), soluble reactive phosphorus (SRP), nitrate (NO3), ammonium (NH4), and dissolved organic carbon (DOC). Samples were filtered through a 0.45 m polycarbonate membrane u sing a filter holder and syringe. Filtered aliquots were collected for SRP, DOC, NH4 +, and NO3 -. Unfiltered samples were collected for TKN and TP. Samples for TKN, TP, DOC, NH4 +, NO3 were acidified to pH 2 with concentrated H2SO4. All samples were transpo rted on ice and stored at 4C until analyzed except for SRP samples, which were stored frozen. The holding time was 28 days for NO3 -, NH4 +, SRP, DOC, TKN, and TP. Soluble reactive phosphorus, NH4 +, and NO3 were measured on a Bran+Luebbe Auto Analyzer 3 ( Bran+Luebbe, Norderstedt, Germany) using EPA Methods 365.1, 350.1 and 353.2 respectively. DOC was measured in a Shimadzu 5050 TOC analyzer (Shimadzu Corporation, Kyoto, Japan). Total Kjeldahl nitrogen was determined by H2SO4 and Kjeldahl salt digestion and flow injection determination of ammonium (EPA Method 351.2). Total phosphorus was

PAGE 24

24 measured as SRP on a Bran+Luebbe Auto Analyzer 3 after digestion with H2SO4 and potassium persulfate (EPA Method 365.1). Algae Sampling and Analysis During Experiment 1, on e tile per species in each stream was harvested on Days 7 and 14 and two tiles per species were harvested on Days 21 and 28. During Experiment 2, three tiles per species per stream were harvested on Days 7, 14 and 21. Each algal fragment was removed from i ts tile, gently patted with Nitex bolting cloth to remove excess moisture, weighed for fresh mass and stored frozen. The fragments were subsequently freeze dried at 91C under a 35 mTorr vacuum, weighed for dry mass and ground and homogenized in a ball gr inder. Percent nitrogen and carbon of the dried algal tissue were measured by high temperature combustion using a Flash EA 1112 Nitrogen/Carbon Analyzer with MAS 200 R Autosampler (Thermo Fisher Scientific Inc, Waltham, MA, U.S.A.). Phosphorus content of d ried algal tissues was measured on combusted (550C) and acid digested (6N HCl) samples as SRP (Anderson, 1976) on a Technicon Autoanalyzer ( Technicon Instruments Corporation Wilmington, MA, U.S.A.) Statistical Analysis Lyngbya wollei and Vaucheria sp. gr owth data were analyzed separately. Nitrate concentration effects on algal growth were expressed in terms of relative growth rate (RGR), which was calculated as follows (Hunt, 1990): RGR = ln (final dry mass) ln (initial dry mass)/# of days (2 1) Treatm ent effects on algal relative growth rate over time were analyzed using a repeated measures ANOVA with SAS statistical software. Pair -wise comparisons were analyzed using least squares means. To determine threshold values of nitrate leading to increased al gal growth, the relative growth rate data from Experiments 1 and 2 were combined. Treatment 1 of Experiment 1

PAGE 25

25 (Control A) was excluded from this analysis, however, because it was the only treatment of the two experiments that did not receive the FLZ8 micro nutrient addition. The data were analyzed using a four -parameter logistics model in the drc (dose response curve) package of the R statistical software package (Ritz & Streibig, 2005). This model is appropriate for data that has an asymmetric dose response where the variance is not homogeneous, and the data are not normally distributed. Molar nutrient ratios were calculated from total nitrogen, total carbon and total phosphorus content of algal tissue. Nitrate concentration effects on algal C:N, C:P and N: P ratios were analyzed with a repeated measures ANOVA using SAS. Results Water Chemistry In Experiment 1, nitrate concentrations on Day 0 were similar to target treatment values, 1 1 NO3 (Table 2 3). Nitrate decreased sign ificantly in all treatments throughout the course of the experiment. Soluble reactive phosphorus ranged from 5 1 1 1 where it remained until Day 28 in all treatments. Total phosphorus ranged f 1 1 1), 1), ranging from 28 to 1081. Dissolved organic carbon increased in all treatments by Day 21 and then dropped by Day 28 to values similar to initial concentrations. 1 1 and were similar to target treatment values during Experiment 2 (Table 2 4). Nitrate concentrations decreased in all treatments with time, with the greatest decline occurring between Day 0 and Day 7. As in Experiment 1, SRP and TP values were low in all treatments on all days since no

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26 phosph1 1 on Day 0 and was reduced 11 on Day 0 to 3 to 4 1 on Day 21. The DIN:TP ratio increased in all but one treatment (Tr 1) from Day 0 to Day 21. The highest ratios (above 100) were obtained in the higher nitrate 1 NO3). Dissolved organic carbon levels during Experiment 2 increased in all treatments from Day 0 to Day 21. Algal Relative Growth Rate The growth response of Lyngbya wollei to nitrate additions for both experiments is shown in Figure 2 2 and treatment vs. time effects are shown in Table 2 5. Relative growth rate (g/g/day) of L. wollei in Experiment 1 decreased signif icantly (p<0.05) in all treatments from Day 0 to Day 28. Growth rate was positively affected by nitrate concentration (p<0.05). The highest average growth rates on Day 7 and 28 were obse 1 target concentration), with rates of 0.143 and 0.083 g/g/day respectively. Treatment 1 (Control A, which had no micronutrient additions) had the lowest average growth rates, with rates of 0.113 and 0.036 g/g/day on Days 7 a nd 28. Significant differences in growth rates (p<0.05) were found between Treatment 1 and all other treatments. In Experiment 2, the relative growth rate of L. wollei was significantly affected by time (p<0.05). The control and two lowest nitrate treatme nts had consistently lower RGR than the high nitrate treatments (p -value = 0.08) (Table 2 5). Relative growth rate (g/g/day) of L. wollei decreased significantly (p<0.05) in all Treatments from Day 0 to Day 21 (Figure 23). Treatment 7, which had the highe st nitrate additions, had the highest growth rate on Day 7 (0.188 g/g/day) 1) had the highest growth rate on Day 21 (0.105 g/g/day). The control (Treatment 1) showed the lowest average growth rates on Days 7 and 21, with rates of 0.153 and 0.059 g/g/day, respectively.

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27 The growth response of Vaucheria sp. to nitrate additions for both experiments is shown in Figure 2 3 and treatment vs. time effects are shown in Table 2 6 For Experiment 1, r elative growth rate data for Vaucheria sp. were log transformed to meet the assumption of normality. Growth rate was significantly affected by nitrate concentration and time (p<0.05) (Table 2 6 ). All treatments in Experiment 1 had higher relative growth rates on Day 28 than on Day 7 and the p e ak in growth rate occurred on Day 21 for all treatments except for Treatme nt 3 (0.005 mg/L), which had continually increasing growth rates from Day 7 to 28 (Figure 2 3 top ). Treatment 7 (5.0 mg/L) had the highest relative growth rate on Days 7 and 28 (0.040 and 0.063 g/g/day, respectively). Both control treatments (Treatment 1 and 2) had the negative growth rate on Day 7 and Treatment 1 had the lowest growth rate on Day 28 (0.021 g/g/day). In Experiment 2, Vaucheria sp. relative growth rate was not signif icantly affected by nitrate concentration or time (Table 2 8) and growth rates were low overall (Figure 2 3, bottom). Treatment 4 had the highest average relative growth rate on Day 7 (0.066 g/g/day) and Treatment 5 (0.025 mg/L) had the highest average rel ative growth rate on Day 21 (0.047 g/g/day) The highest nitrate concentration treatment, Treatment 7 (5 mg/L), had the lowest average growth rates on Days 7 and 21 (0.015 and 0.005 g/g/day respectively). Relative growth rate decreased in all but two treat ments (Treatments 2 and 3) from Day 7 to Day 21. C:N:P Ratios of Algal Tissue Lyngbya wollei C:N, C:P and N:P ratios were significantly affected by both nitrate concentration and time (p<0.05) in both Experiments 1 and 2 (Table 25). During Experiment 1, C:N ratios increased in all treatments from Day 0 to Day 28, with the greatest increase (approximately two fold) in Treatments 2 through 5 (Table 2 6). C:P ratios also increased in all treatments over time, with Treatments 5, 6 and 7, rising from about 200 to over 400. N:P ratios decreased in the lower

PAGE 28

28 nitrate concentration treatments (Treatments 1 to 4) over time, increased slightly in Treatment 5 and almost doubled in Treatments 6 and 7 (from 29 on Day 0 to 52 and 57 on Day 21). For L. wollei in Experimen t 2, all nutrient ratios increased between Day 0 and Day 21 except for the N:P ratio of the control (Treatment 1), which decreased slightly from 19 on Day 0 to 18 on Day 21 (Table 2 6). The largest increase in C:N ratio was approximately two -fold and found in Treatments 1, 2 and 3, which received the lowest nitrate concentrations. C:P ratios increased 2 to 4 times in Treatments 1 to 7 from initial to final experiment days. Treatment 4 showed the greatest increase, from a value of 140 on Day 0 to 576 on Day 21. The N:P ratio of the control decreased, but initial N:P ratios of 19 increased to a range of 24 to 48 on Day 21 in all other treatments. In Experiment 1, Vaucheria sp. C: N, C:P and N:P ratios were significantly affected by both nitrate concentr ation an d time (p<0.05) (Table 2 6 ). All C:N and C:P ratios increased from Day 0 to Day 28. The highest C:N ratios (19 and 20) were obtained on Day 28 in Treatments 4 and 5 (T able 2 8 ). C:P ratios increased by approximately 2 -fold in the lower nitrate concentratio n treatments (Treatments 1 to 4) and by approximately 4 -fold in Treatments 6 and 7; the initial C:P ratio of 163 was increased to 606 and 672 respectively on Day 28. The N:P molar ratio decreased in Treatment 1 from Day 0 to Day 28 (from 18 to 17) but incr eased considerably in Treatments 6 and 7, from 18 to 45 and 51. In Experiment 2, Vaucheria sp. C:N, C:P and N:P ratios were not significantly affected by nitrate concentration, but they were significantly affected by time (Table 2 6). The C:N ratio of Vauc heria sp. increased approximately two -fold in all treatments, from the initial ratio of 8 to either 15 or 16 (Table 2 8 ). C:P ratios increased by 2 to 3 -fold in all treatments between initial

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29 and final days, with the highest ratios ranging from 441 to 459 in Treatments 4 through 7. N:P ratio increased from 18 on Day 0 to a range of 20 to 30 on Day 21. Lyngbya w ollei Growth Response to Nitrate Additions In order to determine threshold nitrate values for Lyngbya. wollei growth, a 4 parameter logistics model was used. The dose response curve for L. wollei is shown in Figure 2 4 and the parameter estimates of t he model are listed in Table 2 9 The lower limit of response (lowest relative growth rate) was 0.088 g/g/day and the upper limit of response was 0.127 g/g/day. The nitrate concentration resulting in 50% growth saturation, the ED50, was 41.5 g NO3 L1(Table 2 10). The ED10 (the nitrate concentration at which the growth response was 10% saturated) was 15.6 g NO3 L1. The ED90 (concentration at which the growth response was 90% saturated), was 110 g NO3 L1. No dose response curve (drc) models were found that effectively described Vaucheria sp. relative growth rate. Discussion Algal Response to N itrogen Additions under Apparent P hosphorus Limitation Unlik e many experiments conducted on the effect of nutrient amendments on algal growth (Rier & Stevenson, 2006; Stelzer & Lamberti, 2001; Francoeur, 2001; Luttenton & Lowe, 2006), this study tested the effects of supplementing only one nutrient, nitrogen, while maintaining phosphorus under what would traditionally be defined as limiting conditions. Despite no addition of phosphorus, both Lyngbya wollei showed positive relative growth rat es throughout the course of both experiments The growth rates, however, bec ame increasingly lower by the end of each experiment (the maximum average growth rate for L. wollei at Day 28 of Experiment 1 was 0.083 g/g/day and 0.105 g/g/day at Day 21 of Experiment 2). Although low, these values are within the range of values reported in the literature for L. wollei (converted to

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30 relative growth rates in Pinowska et al. 2009), which range from 0.052 (Yin, Carmichael & Evans, 1997) to 1.47 (Speziale, Turner & Dyck, 1991). In L. wollei single filament experiments where both N and P amendments were added, Pinowska et al (2009) obtained maximum relative growth rates of 0.4, more than twice the maximum growth rate obtained in either Experiments 1 or 2. Additionally, they obtained higher growth rates at low P and high N concentrations than a t low N and high P concentrations. Relative g rowth rate values for Vaucheria sp. were inconsistent and are difficult to explain. During Experiment 1, growt h rates were higher on Day 28 than Day 7 with highest growth rates occurring in the highest nutrient concentration treatments (5 and 0.5 mg L1 NO3) (Figure 2 3 ), while during Experiment 2, growth rates were lower in all treatments on Day 21 than Day 7 (Figure 2 3 ), and the lowest NO3 concentration treatments (the control and 0.25 mg L1) showed the high est growth rates Despite low growth rates and confounding data for Vaucheria sp. the question still remains as to how the algae were able to grow for three to four weeks with only nitrate additions under conditions of extremely low phosphorus (SRP concen trations by Day 7 in all treatments of 1 1, Tables 2 3 and 2 4). This appears to contradict Liebigs Law of the Minimum, which states that growth is controlled by the essential nutrie nt in shortest supply, which was phosphorus. The application of Liebigs Law to algal ecology is grounded in the concept of ecological stoichiometry. The Redfield Ratio of 106C:16N:1P is commonly used to assess nutrient limitations in freshwater systems, a lthough it was originally developed for oceanic phytoplankton (Redfield, 1958) and both ambient and nutrient cell ratios are often used to predict which nutrient may potentially limit growth.

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31 When using ambient ratios to predict nutrient limitations, disagreement exists about which nutrient forms are more indicative of availability (e.g. DIN:SRP vs TN:TP) (Lohman, Jones & Baysinger, 1991; Dodds, 2003). Inorganic forms of nitrogen (NO2/NO3 and NH4) are readily available for uptake, as are some dissolved orga nic forms, like urea (Berman & Chava, 1999). Large organic N molecules may be available to varying degrees and particulate N is only available once transformed into inorganic forms by bacteria (Lewis & Wurtsbaugh, 2008). With phosphorus SRP is highly avai lable and dissolved organic phosphorus (DOP) becomes bio available when alkaline and acid phosphatases are excreted which enzymatically cleave phosphate groups off organic molecules (Paerl, 1982). Particulate phosphorus (that which is not part of living tissue) is available to varying degrees, either unavailable (e.g. metallic precipitates) or potentially available (e.g., adsorbed P on clay or silt) (Lewis & Wurtsbaugh, 2008). Therefore, using TN:TP can overestimate readily available nutrie nts, while using DIN:SRP can underestimate nutrient availability (Lohman et al. 1991). Morris & Lewis (1988) found that the DIN:TP ratio best predicted nutrient limitation for phytoplankton because it incorporates both external and intracellular nutrient sources indicating that particulate P is more available that particulate N. They classified lakes with a DIN:TP ratio (by weight) of <0.6 as N -limited and lakes with a ratio > 4 as P limited, while those with ratios between 0.6 and 4 were considered to be under intermediate limitation. In both experiments of my study, ambient ratios indicate intermediate limitation in all but 1, with DIN:TP ranging from 1.1 to 4.7 (Tables 2 3 and 2 4). Dodds (2003) found tha t at low DIN and SRP concentrations, both N and P can limit growth, and this is likely the case in my low nutrient treatments. Treatments with 1 suggest P limitation, with DIN:TP ratios from 11 to 1080.

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32 Additionally, the DIN:TP ratio in the water decreased in all treatments on Days 7 and 14, as nutrients were being drawn down during the days of the highest growth. DIN:TP then increased in the final day of every treatment, further pointing toward P limiting conditions. Nitrate lev els in the highest concentration treatments (Treatment 7 of Experiment 1 and Treatments 6 and 7 of Experiment 2) remained near target concentrations, indicating saturated N concentrations. It is therefore surprising that growth rates were greatest in the h igher concentration treatments, where the DIN:TP ratios were extremely high, especially at the end of the study. Examination of molar cell ratios in both experiments also points to apparent P limitation when compared to the Redfield benchmark of 106:16:1, particularly in the treatments with n itrate 1. I obtained N:P ratios of up to 57:1 and C:P ratios of up to 630:1 for L. wollei and N:P ratios of up to 51:1 and C:P ratios of up to 672:1 for Vaucheria sp. by weeks three and four of the experiments suggesting deplete d internal P supplies. However, the optimal stoichiometric ratio for L. wollei and Vaucheria sp. in Florida springs is not known and this can deviate from the Redfield ratio benchmark due to both species -specific and environmental factors (Duarte et al., 1 992; Borchardt, 1996). Hillebrand & Sommer (1999) found that benthic algae from the Baltic Sea had an optimal stoichiometric ratio of 119C:17N:1P, while a review of published data by Kahlert (1998) proposed an optimum stoichiometric ratio for freshwater pe riphyton of 158:18:1. Townsend et al. (2008) found that the optimal ratio for the freshwater algae Spyrogyra fluviatilis was much higher, at 1800:87:1. They attributed the higher carbon content of the algae to more cellular structural requirements, particu larly the thallus, which is not found in phytoplankton. Therefore, the optimal cell ratio s for L. wollei and Vaucheria sp. may be much higher than the Redfield ratio and needs to be further investigated.

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33 Although both ambient and cell nutrient ratios point to likely P limitation, both L. wollei and Vaucheria sp. growth was stimulated by nitrate additions and therefore it is doubtful that it was truly under limiting P conditions as defined by Liebigs Law of the Minimum. Positive gr owth rates in all treatmen ts at the end of both experiments (including the control which received no N or P supplements) may be due to several factors. First, the algae likely relied on luxury P supplies stored in their cells to supplement low phosphorus concentrations, which helps explain higher growth rates for L. wollei in both experiments and Vaucheria sp. (in Experiment 2 only) during the initial weeks of the experiment as compared to the end, when, as shown by the high N:P and C:P ratios, nutrient stores were most likely exhau sted. The growth response curve fitted for L. wollei (Figure 2 4 ) did not follow the typical inverted J form of Michaelis Menten, Monod or Droop nutrient uptake models (Droop, 1974; Borchardt, 1996) in which initial growth rates are approximately zero. I nstead, the growth rate of L. wollei was best described by an S shaped, logistic curve in which rates, even at the lowest nitrate concentrations, were above zero; e.g., the algae were never completely depleted of nutrients and presumably came in with a luxury store of P. Phosphorus uptake in algae can be 5 to 50 times greater than physiological requirements (Cembella, Antia & Harrison, 1984), which does not occur to the same degree with nitrate ions (Reynolds, 1993). As previously mentioned, Pinowska et al. (2009) found that L. wollei growth rates were more negatively affected by a lack of N than P, indicating in part the algaes ability to better store P than N in its cells. Nutrient molar ratios of the initial Lyngbya mats (Day 0) showed that the algae we re initially more P limited in Experiment 1 (N:P = 29:1) than in Experiment 2 (N:P = 19) (Table 2 7 ) and this may have accounted for the slightly higher growth rates, particularly during the initial weeks of Experiment 2 as compared to Experiment 1 (Figure

PAGE 34

34 2 2). Decreasing growth rates, however, may have also been due (at least in part) to self -shading and reduction of nutrient diffusion into internal portions of the algal fragments as patches of algae increased in biomass. In addition, senescing algae, dia toms and bacteria from biofilm that grew in the stream channels, particularly those with higher nutrient concentrations, may have been sources of both N and P during the experiments. Dissolved organic carbon concentrations increased in 6 of 7 treatments in Experiment 1 and in all treatments of Experiment 2 (Tables 2 3 and 2 4). Recycled nutrients were likely immediately taken up by algae (and diatoms, bacteria, etc.) to help maintain growth; high nutrient demand and turnover rates resulted in very low nutri ent concentrations (Dodds, 2003). Finally, the algae in this study may have required lower nutrient concentrations to grow than algae under natural conditions which can be more physiologically stressful. Algae were grown under relatively high light levels (not near -limiting for growth) and temperature conditions remained constant and were similar to conditions found in the springs. Algae growing under less than optimal light conditions (the light:nutrient hypothesis (Sterner et al. 1997)) may require more nutrients to grow (Dickman, Vanni & Horgan, 2006; Hessen et al., 2002; Borchardt, 1996), although studies testing this hypothesis in benthic ecosystems have shown mixed results (Cross et al., 2005; Leonardos & Geider, 2004; Hill & Fanta, 2008). Nutrient C riteria for Florida Springs Although many studies have been conducted on algal growth response to nutrient amendments, relatively little information is available on actual threshold concentrations by which to establish nutrient criteria (Francoeur, 2001; S tevenson et al. 2008). The threshold values generated by the logistics model for Lyngbya wollei (Figure 2 4 and Tables 2 9 and 2 10), 1 (ED101 (ED50) and 1 (ED90) are similar to threshold, or breakpoint values reported in

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35 the literature. As mentioned previously, no dose response model was found to describe Vaucheria sp. growth. Grimm & Fisher (1986) suggested that periphyton growth in an Arizona stream was N -1 NO3N and results from Lohman et al. (1991) indicate that periphyton growth is N -limi ted in an Ozark stream at concentrations as high L1. In a large meta analysis of benthic algae in temperate streams, Dodds, Smith & Lohman (2002) found that L1 total N, mean chlorophyll values were considerably higher. Using th e thres hold values generated by my model to set nutrient criteria for springs would be difficult since these values are very low when compared to nitrate concentrations found in many Florida springs. Results from a comprehensive survey of 63 spring sites throughout Florida conducted in 2006 (Pinowska et al., 2007) show that only eight sites had values below 11 and none of the sites had NO3/NO2 1. NO3/NO2 concentrations from 19071979 for 87 springs range from below detect 11 (Strong, 2004). As mentioned previously, in many of Floridas springs, N:P ratios and algal growth potential assays indicate P alone or both N and P limit algal growth (Stevenson et al. 2007). Yet, results from this experiment show that under laboratory conditions, Lyngbya wollei can grow if given N even if P is in very low supply and that higher NO3 concentrations result in higher growth rates. Therefore, reductions in N concentrations should r educe algal growth rates in spring systems where this nutrient is found in excess supply. However, algal biomass would likely continue to accumulate, albeit at a slower rate, and nutrient reduction programs may not show quick results. The situation is furt her complicated because high concentrations of dissolved inorganic N and P are stored within thick L. wollei mats (>1m) (Sickman et al ., 2009) which are

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36 potentially available for uptake by the algae. Additionally, even though L. wollei cannot store N in it s cells as it can P, growth continued even in the control treatments of -my experiments, where NO3 concentrations ranged from 2 1. Finally, biomass accumulation in benthic algae is heavily dependent on factors other than nutrients, such as light, disturbance, grazing and the presence of submerged aquatic vegetation (e.g. Doyle & Smart, 1998; Lohman et al. 1991; Luttenton & Baisden, 2006; Borchardt; 1996). Pinowska et al. (2009) did not find a direct relationship between nutrient concentrations and algal abundance in Florida springs and other factors either alone or in combination with nutrients must be affecting algal growth. Studies are needed on how biotic and abiotic factors interact in controlling algae abundance in order to establish management plans to reduce L. wollei biomass. The ability of L. wollei to grow under surprisingly low nutrient conditions, even when water column and tissue stoichiometry suggest that they should not be growing, makes the task of establishing nutrient criteria in Florida springs more difficult.

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37 Table 2 1. Target nitrate concentrations for Experiments 1 and 2. Tr eatment Target nitrate concentrations ( 1 ) Experiment 1 Experiment 2 1 0 0 2 0 25 3 1 50 4 5 150 5 50 250 6 500 500 7 5000 750

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38 Table 2 2. FLZ8 micronutrient concentrations. The micronutrient solution was continuously pumped into each stream channel at a rate of 0.198 ml min1. Each stream channel contained 7 L of water at a given time, and water was pumped in continuously at a rate of 15 ml min1. Micronutrients Concentration FeCl 3 6H2O 231 EDTA Na2 306 ZnSO 4 7H 2 O 7 (NH 4 ) 6 Mo 7 O 24 4H 2 O 22 Co(NO 3 ) 2 6H 2 O 4 VOSO 4 6H 2 O 1 Al 2 (SO 4 ) 3 K 2 SO 4 2H 2 O 12 NiSO 4 (NH 4 ) 2 SO 4 6H 2 O 5 Cd(NO 3 ) 2 4H 2 O 4 Cr(NO 3 ) 3 7H 2 O 1 Na2WO4 2H2O 1 KBr 3 KI 2 Cu(SO 4 ) 5H 2 O 3 H 3 BO 3 78 MnSO 4 H 2 O 42

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39 Table 2 1) and DIN/TP ratio for Experiment 1. N refers to the number of stream channels per treatment. Treatment Target NO 3 Concentrations Experiment Day n N NO 3 N NH 4 TKN TP SRP DIN/TP Ratio DOC 1 Control A 0 2 10 16 203 12 15 2.2 1335 0 7 2 2 12 205 13 4 1.1 2290 14 2 2 16 184 15 3 1.2 1654 21 2 8 5 166 8 2 1.6 1820 28 2 8 5 207 7 4 1.9 1941 2 Control B 0 3 7 17 272 12 9 2.0 1854 0 7 3 2 7 347 11 3 0.8 2443 14 3 2 8 200 10 2 1.0 2132 21 3 8 10 176 4 2 4.5 2308 28 3 8 5 159 5 3 2.6 1756 3 0 .5 0 3 7 28 242 12 7 2.9 1953 7 3 2 17 266 9 3 2.1 2393 14 3 2 8 215 11 3 0.9 2160 21 3 8 5 206 7 3 1.9 2349 28 3 8 5 197 5 3 2.6 2087 4 5 0 3 16 14 301 13 7 2.3 1867 7 3 2 12 367 11 2 1.3 2406 14 3 4 10 262 10 2 1.4 2188 21 3 8 3 206 7 2 1.6 2078 28 3 8 5 236 4 3 3.3 1855

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40 Table 2 3. Continued. Treatment Target NO 3 Concentrations Experiment Day n N NO 3 N NH 4 TKN TP SRP DIN/TP Ratio DOC 5 50 0 3 61 11 418 16 8 4.5 1731 7 3 4 6 341 9 2 1.1 2373 14 3 2 10 316 10 2 1.2 2364 21 3 8 4 181 7 3 1.7 2043 28 3 8 5 207 6 2 2.2 1922 6 500 0 3 507 13 350 14 7 37 1779 7 3 315 11 453 9 2 36 2242 14 3 250 34 301 10 3 28 2279 21 3 330 9 295 5 2 68 2212 28 3 226 5 270 6 3 39 1876 7 5000 0 3 5798 22 486 15 5 388 1815 7 3 4395 9 380 8 2 551 2405 14 3 3462 24 387 9 2 387 2178 21 3 4320 5 330 4 2 1081 2262 28 3 4207 5 324 5 3 842 1838

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41 Table 2 4. Average streamwater nutrient concentrations ( 1) for Experiment 2. N refers to the number of stream channels per treatment. Treatment Target NO3 Concentrations Experiment Day n NO 3 NH 4 TKN TP SRP DIN/TP Ratio DOC 1 Control 0 2 5 10 149 11 2 1.4 1656 7 2 5 4 299 10 4 0.9 2432 14 2 8 9 277 4 4 4.3 2615 21 2 5 6 226 3 2 3.7 2368 2 25 0 3 37 9 274 13 3 3.5 2177 7 3 5 5 303 4 3 2.5 2413 14 3 5 8 338 7 2 1.9 2803 21 3 5 8 308 3 1 4.3 2482 3 50 0 3 45 7 230 11 3 4.7 2079 7 3 5 2 308 4 2 1.8 2631 14 3 7 8 328 4 2 3.8 2784 21 3 71 8 245 3 2 26.3 2465 4 150 0 3 186 7 274 11 3 17.5 2291 7 3 9 4 299 4 2 3.3 2579 14 3 62 6 287 4 2 17.0 2607 21 3 37 10 230 3 1 15.7 2437 5 250 0 3 376 7 358 36 2 10.6 2195 7 3 18 5 274 4 2 5.8 2547 14 3 66 14 367 3 2 26.7 2689 21 3 237 12 303 3 2 83.0 2632

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42 Table 2 4. Continued Treatment Target NO3 Concentrations Experiment Day n NO 3 NH 4 TKN TP SRP DIN/TP Ratio DOC 6 500 0 3 659 8 319 8 3 83.4 2404 7 3 292 5 352 5 2 59.4 2572 14 3 367 11 435 7 5 54.0 2635 21 3 522 11 367 3 2 177.7 2514 7 750 0 3 766 9 284 8 9 96.9 2104 7 3 559 5 342 6 2 94.0 2503 14 3 622 10 401 6 3 105.3 2666 21 3 743 14 347 4 2 189.3 2440

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43 Table 2 5. Repeated measu res analysis of variance for Lyngbya wollei relative growth rates and nutrient molar ratios in Experiments 1 and 2. Significant P values (p<0.05) are shown in bold. Experiment Variable Source of variation (between groups) P Source of Variation (within gro ups) P Source of Variation (within groups) P 1 Relative Growth Rate NO 3 Concentration (N) <0.0001 Time <0.0001 Time x N 0.7403 C:N <0.0001 <0.0001 0.0275 C:P <0.0001 <0.0001 <0.0001 N:P <0.0001 0.3242 <0.0001 2 Relative Growth Rate NO 3 Co ncentration (N) 0.0778 Time <0.0001 Time x N 0.9287 C:N 0.0015 <0.0001 <0.0001 C:P 0.0155 <0.0001 0.0005 N:P <0.0001 <0.0001 0.0001

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44 Table 2 6. Repeated measures analysis of variance for Vaucheria sp. relative growth rates and nutrient mol ar ratios in Experiments 1 and 2. Significant P values (p<0.05) are shown in bold. Experiment Variable Source of variation (between groups) P Source of Variation (within groups) P Source of Variation (within groups) P 1 Relative Growth Rate N0 3 Concent ration (N) 0.0008 Time 0.0043 Time x N 0.1484 C:N <0.0001 <0.0001 0.0221 C:P <0.0001 <0.0001 <0.0001 N:P <0.0001 0.0014 <0.0001 2 Relative Growth Rate NO 3 Concentration (N) 0.2733 Time 0.3969 Time x N 0.5047 C:N 0.6131 <0.0001 0.2804 C:P 0.6841 <0.0001 0.2042 N:P 0.2108 0.0034 0.5987

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45 Table 2 7 Initial and final C:N, C:P and N:P molar ratios of Lyngbya wollei in Experiments 1 and 2. Target treatment concentrations (NO3 1) are shown below treatment numbers. Experiment Molar Ratio Day 1 ) 1 2 3 4 5 6 7 Control A Control B 0.5 5 50 500 5000 1 C:N 0 7 7 7 7 7 7 7 28 12 15 15 16 15 10 11 C:P 0 198 198 198 198 198 198 198 28 286 319 299 345 436 543 630 N:P 0 29 29 29 29 29 29 29 28 23 22 20 22 30 52 57 1 ) 1 2 3 4 5 6 7 Control 25 50 150 250 500 750 2 C:N 0 7 7 7 7 7 7 7 21 15 16 13 12 11 11 11 C:P 0 140 140 140 140 140 140 140 21 268 372 408 576 510 532 528 N:P 0 19 19 19 19 19 19 19 21 18 24 32 48 46 48 47

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46 Table 2 8. Initial and final C:N, C:P and N:P molar ratios of Vaucheria sp. in Experime nts 1 and 2. Target treatment concentrations (NO3 1) are shown below treatment numbers. Experiment Molar Ratio Day Treatment number and nitrate concentration ( L 1 ) 1 2 3 4 5 6 7 Control A Control B 0.0005 0.005 0.05 0.50 5.00 1 C:N 0 9 9 9 9 9 9 9 28 17 17 17 19 20 13 14 C:P 0 163 1 63 163 163 163 163 163 28 293 341 330 351 451 606 672 N:P 0 18 18 18 18 18 18 18 28 17 20 19 19 23 45 51 Treatment number and nitrate concentration ( L 1 ) 1 2 3 4 5 6 7 Control 0.025 0.05 0.15 0.25 0.50 0.75 2 C:N 0 8 8 8 8 8 8 8 21 16 15 16 16 15 16 15 C:P 0 142 142 142 142 142 142 142 21 318 363 390 449 446 459 441 N:P 0 18 18 18 18 18 18 18 21 20 24 24 28 29 29 30

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47 Table 2 9 Parameter estimates of the dose response curve (model) for Lyngbya wollei Relati ve growth rate (RGR) data from Experiments 1 and 2 were combined. Parameter (intercept) Parameter description Estimate Standard error t value p value b Slope 2.245 0.836 2.685 0.0078 c Maximum RGR 0.127 0.003 46.831 1.02E 115 d Minimum RGR 0.088 0.004 2 3.942 4.00E 63 e ED50 41.54 8.39 4.95 1.47E 06 Power Power 0.964 0.453 2.129 0.0344 Heterogeneity adjustment: variance is a power of the mean

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48 Table 2 10. Estimated effect doses (ED) of NO3 for Lyngbya wollei. Effect Dose (ED) NO3 dose 1 ) Standard error 10 15.6 6.47 50 41.5 8.39 90 110 46.3

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49 Figure 2 1. Cross -sectional view of a single stream channel. Aquifer water with nutrients Water bath to regulate temperature NO 3 and Micronutrients in DDI Water Florida Aquifer Water Air Pump Pump Macroalgae Pump Excess water outflow

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50 Figure 2 2. Lyngbya wollei relative growth rat es (RGR) under different nitrate concentrations during Experiments 1 and 2. A) Experiment 1 B) Experiment 2 0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 7 14 21 28 Day RGR g/g/day (1) Control A (2) Control B (3) 0.0005 (4) 0.005 (5) 0.05 (6) 0.50 (7) 5.00 NO3 (mg/L) A B

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5 1 0.06 0.04 0.02 0.00 0.02 0 04 0.06 0.08 7 14 21 28 RGR g/g/day Day Control A Control B 0.0005 0.005 0.05 0.50 5.00 NO3(mg/L) Figure 2 3. Vaucheria sp. relative growth rates (RGR) under different nitrate concentrations during Experiments 1 and 2. A) Experiment 1. B) Experiment 2 A B

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52 Figure 2 4 Lyngbya wollei rel ative growth rate dose response curve. Relative growth rates (RGR) for Experiments 1 and 2 are combined. Treatment means are shown as open diamonds. The lower limit of response (lowest relative growth rate) is 0.088 g/g/day and the upper limit of response is 0.127 g/g/day. The nitrate concentration resulting in 50% growth saturation, the ED50, is 41.5 g NO3 L1. The ED10 (the nitrate concentration at which the growth response wa s 10% saturated) is 15.6 g NO3 L1 and the ED90 (concentration at which the growth response is 90% saturated), is 110 g NO3 L1. RGR g/g/day NO 3 L 1 )

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53 CHAPTER 3 15N STABLE ISOTOPE COMPOSITION OF ALGAE, SEDIMENT AND NITRATE IN FLORIDA SPRINGS Introduction Increasing hu man populations and landuse change in Florida have led to increases in nitrate in the Floridan Aquifer (de Brabandere, Frazer & Montoy, 2007; Munch et al. 2006; Katz, Bohlke & Hornsby, 2001), which extends throughout the entire state of Florida and parts of Georgia, South Carolina, Mississippi and Alabama (Cohen, 2008). The aquifer is particularly susceptible to land use activities due to its karst topography, which provides a direct conduit between the surface application of nitrogen and the aquifer (Bac chus & Barille, 2005; Katz, 2004). Floridas calcitic soils and the limestone matrix of the aquifer adsorb phosphorus (Rhue, Harris & Nair 2006; Cohen, 2008), but highly mobile nitrate anions have no such exchange capacity (Panno et al ., 2001). Nitrogen levels in many Florida karst springs have been steadily increasing over the last 50 years from background concentrations of less than 0.1mg/L to concentrations as high as 5 mg/L, while phosphorus levels have remained relatively stable (Hornsby and Ceryak, 1999 in Katz et al 1999; Scott et al. 2004; Strong, 2004). At the same time, an increase in filamentous algae has been observed in many springs, particularly Lyngbya wollei and Vaucheria sp., the two most common mat -forming species found in Floridas spr ings (Stevenson et al ., 2004). Increases in algae are often attributed to increases in nitrate concentrations in spring water, although no direct link has been found between nitrate concentrations and algal abundance (Pinowska et al., 2009, Stevenson et al ., 2004). However, micro and mesocosm experiments indicate that reducing nitrogen loads to springs where concentrations are high could reduce algal growth rate and therefore, biomass accumulation (Stevenson et al. 2008; Chapter 2, this document).

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54 Sources o f nitrogen to groundwater and springs include inorganic fertilizers, confined animal feedlot operations, sewage effluent and atmospheric deposition (Bacchus & Barile, 2005; Katz et al., 1999). Tracing these sources in Floridas springs is challenging, howe ver, because spring systems reflect groundwater quality vertically, spatially and temporally (Katz, 2004). 15N) can be a useful tool to elucidate sources of N in systems, but many natural and anthropogenic sources have overlapping 15N values and therefore distinguishing between sources of nitrogen can be difficult (Kendall, 1998; Einsiedl & Mayer, 2006; Derse et al ., 2007). Interpretation is further complicated due to the mixing of multiple N sources as well as fractionation proce sses, such as denitrification and assimilation of nitrogen by primary producers (Kendall, 1998; de Brabandere, Frazer & Montoya, 2007). The denitrification process produces isotopically lighter N2 and N2O gases, leaving behind 15N -enriched residual nitrate The 15N signature of the residual N can be similar to that of animal and septic waste (Panno et al 2001). Potential fractionation during assimilation of NH4 and NO3 by algae can range from 27 to 0 (Fogel & Cifuentes, 1993 in Kendall, 1998). Nitrate conce ntrations in the water column can also affect algal 15N, since under limiting nitrogen conditions, most of the nitrogen would be assimilated. Algal 15N would therefore reflect source 15N since little or no isotopic fractionation would occur (Umezawa et al. 2007). 15N -NO3 18O NO3) is used to further 15N ranges overlap (Fukada, Hiscock, & Dennis, 2004, Dahnke et al. 2008; Pellerin et al. 2009; Wankel et al. 2009). 18O can be used to separate NO3 fertilizer from soil nitrogen and NH4 in fertilizer and rain. Additionally, both the 1815N of the residual nitrate increase systematically as a result of denitrification. The 18O relative 15N is close to 1:2 (producing a line with a slope of

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55 15N on the x axis) and this may allow isotopically distinct sources to be identified even when significant denitrification has occurred (Bttcher et al., 1990; Kendall, 1998). In this study, I used both the dual isotopic analysis of spring water and 15N analysis of filamentous mat -forming algae and spring sediments to help determine nutrient sources to benthic algal mats and identify factors controlling algal abundance. Spe cifically, I assessed nitrate sources to spring water using the dual isotopic analysis of nitrate ( 15N NO3 and 18O NO315N of algae and spring sediments at two scales, (1) regionally, at multiple spring sites throughout Central Flori da and the Panhandle and (2) along four spring fed 15N of algae over the course of one year at two springs to examine seasonal variability. Additionally, I assessed the relationships 15N indicators of nutrient availability and sources through correlation analysis. Methods Study Sites 15N) was conducted on filamentous algae and sediments in Florida springs on three scales: (1) regionally, (2) along spring river run gradients (starting at the spring boil of four separate springs and sampling progressively further downstream) and (3) on a monthly basis during the course of one year at two springs. For the regional study, 63 spring sites throughout the Panhandle an d north central Florida were sampled in 2006. The spring sites included the boil area as well as sites downstream. The complete list of sites and locations sampled is found in Appendix A. Additionally, the boil area of 17 springs was sampled in the summer of 2005, January 2006 and summer of 2008 for the dual isotopic analysis of nitrate (15N NO3 and 18O NO3) in spring water. However, not all springs were sampled all three years

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56 (Table 1). Four spring river runs were sampled in January 2006 for the gradien t study: Silver River, Rainbow River, Wakulla River and the Weeki Wachee River. The sites sampled along each river run are listed in Table 2 and site codes correspond to the codes listed in Appendix 1. Finally, the seasonal study was conducted monthly from April 2005 to March 2006 at Manatee Springs and Ichetucknee Blue Hole Spring. Only the boil areas were sampled. Algae, Sediment and Water Sample Collection Algae and sediment samples were collected either within the boil area of each spring, or for sites located downstream from the boil, samples were collected along a 100 m section of the river run. Samples were primarily collected by snorkeling, but had to be collected from a canoe at some locations due to the presence of alligators. At each site, a compo site sample of each of the most common algal species was collected, shaken in the water to remove any loosely attached debris and placed into 1 gallon Ziploc bags (SC Johnson, Racine, WI, USA) filled with site water. Additionally, a small algal sample (app rox 0.5 1 g fresh mass) was collected and placed in a scintillation vial to confirm the accuracy of field identification. Samples were then transported to the laboratory on ice. Separate sediment samples were collected from the exposed spring bottom and f rom under algal mats by coring with a 2.5 cm diameter syringe to a depth of approximately 3 to 10 cm, depending on the composition of the spring bottom. The open end of the syringe was then sealed with a spatula to bring the sample to the surface. When sam pling from a canoe, an Eckman Dredge was used to collect the sediment. Whenever possible, at least three samples each of exposed and covered sediment were collected and combined to form a composite sample. Samples were transported in plastic containers to the laboratory on ice. Water samples were collected at each site either from a kayak or from the shore depending on the location of the boil, at a depth of 0.5 m from the surface. If the site was located along the

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57 river run, the sample was collected at the start (upstream end) of the 100-m section. Samples were filtered in the field either through 0.45 m cartridge filters (Millipore model number GWSC04550, Millipore, Billerica, MA, U.S.A.) using a peristaltic pump or through 0.45 m polycarbonate membrane s (Whatman Inc., Florham Park, NJ, U.S.A.) using a filter holder and 15N NO3 18O NO3, SRP, DOC, NH4 +, and NO3 -. Unfiltered samples were collected for TKN and TP. Samples for TKN, TP, DOC, NH4 +, NO3 were acidified to pH 2 with concentrated H2SO4. All samples were transported on ice and 15N -NO3 18O NO3 and SRP samples, which were stored frozen. The holding time was 28 days for NO3 -, NH4 +, SRP, DOC, TKN, and TP. The holding time for the isotope samples was 28 days to three years (all samples were analyzed in 2008). Additionally, temperature, conductivity, pH, and dissolved oxygen (DO) were measured at each site using a YSI 556 Multi -probe System (YSI Incorporated, Yellow Springs, OH, U.S.A.). Measurements were taken directly above the boil or if the site was located along the river run, at the start of the 100 -m section. Algae, Sediment and Water Sample Processing and Analysis Algae samples were picked clean of inv ertebrates and debris within 24 hours of field collection, stored frozen and later lyophilized at 91C under a 35-mTorr vacuum. Once dry, they were again picked clean of any debris initially missed and ground and homogenized in a ball mill. The samples co llected and 15N of algae and sediments were also used to determine percent C, N and P. Algae samples that were placed in scintillation vials for species verification were preserved using M3 solution and sent to the Center for Water Sciences at Michigan State University, where they were identified. Macroinvertebrates were removed from sediment samples which were then homogenized by stirring, also within 24 hours of field collection. Sediments were stored frozen and

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58 subsequently dried in an oven a t 60C for 5 days. They were then passed through a sieve to remove coarse debris (e.g, twigs, leaves, whole mollusk shells) and ground and homogenized in a ball mill. Nitrogen isotopic composition of algae and sediments was measured on a Thermo Finnigan De lta -Plus XP isotope ratio mass spectrometer (Thermo Fisher Scientific, Inc., Waltham, MA, U.S.A.) at the University of Florida using an elemental analyzer inlet system and continuous flow of He. The International Atomic Energy Association standard for N1 w as included in each run. Nitrogen isotope values air. Percent nitrogen and carbon of the dried algal tissue and sediments were measured by high temperature combustion using a Flash EA 1112 Nitrogen/Carbon Analyzer with MAS 200 R Autosampler (Thermo Fishe r Scientific Inc, Waltham, MA, U.S.A.). Phosphorus content of dried algal tissues and sediment was measured on combusted (550C) and acid digested (6N HCl) samples as SRP (Anderson, 1976) on a Technicon Autoanalyzer ( Technicon Instruments Corporation Wilmington, MA, U.S.A.) At Michigan State University, sediments were analyzed for % water content, dry mass (DM), ash free dry mass (AFDM) (Eaton et al. 1995) available phosphorus (PO4 -) and available nitrogen (NH4 +, NO2/NO3 -) following the extraction of 1g of wet sediment with Truogs reagent and KCl (Allen 1989) All samples for the dual -isotope analysis of nitrate ( 15N NO3 and 18O NO3) in spring water were analyzed at the University of Florida using the bacterial deni trifier method (Sigman et al., 2001; Casciotti et al., 2002) in which nitrate is converted to N2O by the denitrifying bacteria Pseudomonas aureofasciens 1518O of the N2O produced were then measured on a Thermo Finnigan Delta Plus XP isotope ra tio mass spectrometer at the University of Florida using continuous flow of He. The International Atomic Energy Association standard

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59 atmospheric air, oxygen iso VSMOW. Soluble reactive phosphorus, NH4 +, and NO3 were measured on a Bran+Luebbe Auto Analyzer 3 (Bran+Luebbe, Norderstedt, Germany) using EPA Methods 365.1, 350.1 and 353.2, respectively. T otal Kjeldahl nitrogen was determined by H2SO4 and Kjeldahl salt digestion and flow injection determination of ammonium (EPA Method 351.2). Total phosphorus was measured as SRP on a Bran+Luebbe Auto Analyzer 3 after digestion with H2SO4 and potassium persu lfate (EPA Method 365.1). Rapid Habitat and Periphyton Assessment (RHPA) At each of the spring sites, a modified Rapid Habitat and Periphyton Assessment (RHPA) (Stevenson and Bahls 1999) was conducted. Although not directly a part of this study, data obtained were used in a correlation analysis with the algal and sediment isotope data. The RHPA consisted of establishing 7 to 9 transects across the spring run at each site, posi tioned approximately 10 m apart. Nine observation points were designated for each transect, for a total of either 63 or 81 points per site. At each point, current velocity was estimated, the substratum type was characterized, macrophytes and algae were identified and the thickness of the algal mat and stream depth were measured. Additionally, any bank conditions (binding roots, canalized, or incised) were documented and for every second transect, the buffer composition (trees, shrubs, herbs, or bare) was evaluated and the canopy cover was measured with a spherical convex crown densitometer. Statistical Analysis Spearman correlations were used to determine relationships between algal and sediment stable isotope composition and indicators of nutrient availabil ity and sources, as well as other

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60 environmental variables collected during the RHPA. Variables correlated to algal and sediment 15N include: (1) site water physical -chemical parameters from the 2006 survey plus data from a survey conducted in 2003 for FDEP by A. Pinowska and R.J. Stevenson (Michgan State University), (2) algal and sediment C:N:P molar ratios, as well as bioavailab le N and P of the sediments, (3) average site depth and current velocity, (4) average site canopy cover, (5) site buffer zone characteristics, (6) diatom water quality and trophic -state indicators developed by Stevenson et al. (2008). (6) land use characte ristics and LDIs. Land use characteristics for each site and LDI (Landscape Development Intensity) indexes were calculated from data provided by the Florida Department of Environmental Protection (FDEP) by A. Pinowska. A subset of the regional study sites (34) were used in the correlation analysis. Only samples from the spring boil areas were used, in order to avoid autocorrelation among multiple sites along spring runs. Results 15N -NO3 18O -NO3) 15N 18O values of the 17 springs analyzed are shown in Figure 31 and listed in Table 3 15 15181518O Volusia, Lafayette, Little River and Wakulla Springs, all sampled in 2008. The lowest values 1518O Hole, Madison Blue and Rainbow Springs, all sampled in 2005. A positive relationship was 1518O (r2 = 0.71), with most sites falling along a line with slope of 0.64. 15N 1515N NO3 of water from 10 headwater springs sampled in 2006 is shown in Figure 32. The springs sampled were: Fanning, Guaranto, Lafayette Blue, Little Fanning, Little River, Madison Blue, Rainbow, Silver

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61 15N 15N NO3 in water. If a trendline is drawn through the algal data, the r2 value is 0.34. The 15N values was substantial, from 8 to +6 and was not species -specific, while 15N NO3 15N values of algal tissue were found for Vaucheria sp. at Little River Springs ( 7 ) and Troy Springs ( 6 ), while the highest values were found for Spirogyra sp. at multiple sites along the Wakulla Springs river run (7 and 8 ). No distinct relationship wa s found between sediment 1515N NO3 in 15N was never negative and ranged from 0 to 10 Exposed sediment showed a wider range in values than sediment under algal mats. No relationship was 15N of algae, sediments and spr ing water NO3 and NO3 concentrations in the sites sampled in 2006 (Figure 33). Correlations among Algal Stable Isotope Signatures, Water Quality and Environmental Variables 15N and sediment 15N and variables relating to indicators of nutrient availability and sources are listed in Table 3 2. To avoid Type 1 errors in this analysis, I set the p level at 0.001 to account for the relatively large number of correlations that were made. For alga 15N, significant positive and negative correlations were found between numerous variables. The strongest associations were found with average water concentrations of total N and NO2/NO3N (negative correlations) of the 3 major sampling events (Fall and Spring 2003 and Winter 2006). These relationships are not surprising because when both total N and NO2/NO3N concentrations are high, more isotopically light N 14N) is available to the algae for uptake, resulting in isotopically lighter algal tissues (lo wer 15N values).

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62 15N was the 1513C and C:N analysis of algal tissues indicate that the majority of the organic matter in the sediment (bot h under algal mats and in exposed sediment) comes from vascular plants (see Chapter 4 of this document) and therefore, the strong correlation 15N of both types of sediment samples is likely because the organic matter is of similar origin. For 15N, (sediment with no algal mat cover), the strongest correlation was with the percent C of sediment under algae (negative), which may be an indicator of denitrification occurring in the sediment. During denitrification, carbon is used a s a source of energy (so less C remains in the sediment) and the residual N is enriched (higher amount of 15N). Stable I sotopic Variation along Longitudinal Gradients The sites sampled at each of the four spring river runs and their distances from the spr ing boil are listed in Table 3 3. The site codes are the same ones used (and therefore the same locations) as in the regional study. Dual I sotope Analysis of Spring Water Nitrate along Longitudinal Gradients Each of the four river runs sampled in the gradi ent study had distinct dual isotopic signatures of spring 15N NO3 18O NO3) (Figure 3 15N NO3 ranged from 18O NO3 ranged from 5 to 7 The variability 15N and 18O), despite sampling distances of up to 9 km between different sites. Silver Springs River Run Three algal species, Lyngbya wollei Vaucheria sp. and Spirogyra sp. were found along the 15N of algae, and nitrate of spring w ater in relation to distance from the boil is shown in Figure 3 5 15N values ranged from 2 to 6 L. wollei showed

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63 15N values from the boil until the fifth site (from 2 to 6 ), with a decline in the last site to 4 Vaucheria 15N showed an increasing trend with increasing distance 15N NO3 of spring water showed almost no variability, remaining around 7 at each site (total length of 7.2 km). Weeki Wachee Springs River Run Seven species of algae were found along the Weeki Wachee river run: Vaucheria sp., Spirogyra sp., Lyngbya wollei, Hydrodictyon sp., Cladophora glomerata, Aphanothece sp. and Calaglossa sp. (Figure 3 5) 15N varied from site to site, with values ranging f rom 1 to 5 Lyngbya wollei 15N NO3 of spring water remained between 6 and 7 throughout the river run (total length of 8 km). Rainbow Springs River Run Stable isotope composition ( 15N) of the algae and water nitrate along the Rainbow Springs river run are shown in Figure 3 5 15N values ranged from 2 to 9 with exposed 15N values. Lyngbya wollei 15N had a narrow, but increasing trend as dis tance from the boil increased ( 15N NO3 of spring water remained at 4 throughout the run (total length of 7.7 km). Wakulla Springs River Run Five species of algae were found along the Wakulla Springs river run: Compsopogon sp., Vaucheria sp., Spirogyra sp., Lyngbya wollei and Enteromorpha 15N of algae and nitrate along the river run gradient are shown in Figure 3 5 15N values showed relatively little within -15N NO3 of spring water rema ined between 9 and 10 throughout the run (total length of 9.8 km).

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64 15N 15N of Vaucheria sp. at Manatee springs, with a relatively wide range of values ( 8 to 1 ) (Figure 3 6). The lowest v alues were obtained in July 2005 and 15N values of Vaucheria sp. fluctuated more than those of Lyngbya wollei throughout the course of the year (Figure 3 6). L. wollei values were confined to a range of 1 to +1 while Vaucheria sp. values ranged from 1.3 to 3.5 Discussion Dual I 15N -NO3 18O -NO3) Nitrate in groundwater is derived from both natural and anthropogenic so urces. The 15N values between 20 and +30 and normal ranges of 15N of groundwater nitrate can generally be attributed to the following sources: (1) inorganic fertilizer ( 7 to +7 ), (2) cultivated and natural soi ls ( 3 to +14 ), (3) atmospheric deposition (NH4 and NO3 in rain, 7 to +8 ) and (4) animal and septic waste (+2 to +25 ) (Einseidl & 18O values of nitrate of these same source s fall within the following ranges (1) inorganic fertilizer (15 to 25 ), (2) cultivated and natural soils ( 5 to 15 ), (3) atmospheric deposition (NH4 and NO3 in rain, 20 to 80 ) and (4) animal and septic waste ( 5 to +15 ) (Einseidl & Mayer, 2006; Ken dall, 1998; Durka et al. 1994). Therefore, when isotopic ranges of N sources overlap, the dual isotope analysis of nitrate can be used to differentiate between sources. However, the utility of this method depends on being able to identify the importance of denitrification processes in the particular system studied because the residual nitrate of denitrification has a similar isotopic signature as that of animal waste (Fukada, 2004).

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65 If one assumes that variations in nitrate isotopes measured in the springs are the result of mixing of different sources rather than denitrification, then inferences can be made about the dominant sources of nitrate to the springs. Five springs sampled in 2008, Troy, Wekiwa, Volusia, Lafayette and Little River had both 1518O between 10 and 20 which strongly indicates organic N sources, such as manure or septic waste (Table 3 1, Figure 3 1) (Kendall, 1998, Panno, 2001). The remaining springs (which also include those mentioned above, but sampled in previous yea 1518O values between 3 and 9 which indicate an inorganic N -source, such as NH4 from either fertilizer and/or rain or soil nitrogen, but which also fall within the lower range of organic N sources (Kendall, 1998). Katz (2008) found that inorganic fertilizers were major sources of nitrogen at Ichetucknee Head Springs and Blue Hole, 15N value for Wakulla Springs of 8 (similar to my study, 9 in 2005 and 2006), which he attributed to both inorganic and organic sources based on N mass balance calculations for the spring by Chelette et al. (2002, in Katz, 2004). The most important sources of N identified (in decreasing importance) were: treated wastewater effluent, atmospheric deposition, wastewater residuals, fertilizers and on -site waste disposal systems. Isotope values are higher for both 15N 18O in samples taken in 2008 versus those taken in 2005 for several springs. Troy, Lafayette, and Little River show relatively large 15N 18O), while Ichetucknee Head Spring and Manatee Springs increase d to a lesser extent (1 to 3 in both). Several possible explanations need to be considered to explain these results. First, the 2005 samples were stored frozen for three years before being analyzed and holding time may have affected the water samples (al l samples for the dual isotope analysis of nitrate were analyzed in the summer of 2008). However,

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66 six other springs that were sampled across multiple years did not show this trend (Fanning, Guaranato, Ichetucknee Blue Hole, Rainbow, Silver River and Wakull 15N NO3 values obtained for Troy Springs in 2005 and 2006 (7 ) and Manatee Springs (6 ) are the same values listed by Katz (2004, derived from Blke (2002)) for both springs. Therefore, holding time does not appear to have influenc ed my results. Another possible explanation would be that in 2005, sampling may have occurred when the aquifer was in a condition of low flow, while in 2008 sampling may have occurred during conditions of higher flow or recharge. Water sampled in 2008 coul d have had a shorter residence time, passing more quickly through preferential flows into the aquifer and therefore reflected more heavily local source values, while water discharged in 2005 may have been older and a reflection of mixing of multiple source s across a larger area of the springshed. Katz (2004) indicates that there is a substantial increase in water contributions from local flow systems like sinkholes during conditions of high recharge. Using dye tracer studies, Wilson & Skiles (1988, in Katz, 2004), showed that water can move through conduit systems to springs in as little as days to weeks, although groundwater discharged from Suwannee River Basin springs has average residence times of 10 to 20 years (Katz, Hornsby & Bhlke, 2001). Additional ly, samples could have included more atmospheric nitrate deposition in 2008, 18O values, than those obtained in 2005. Einsiedl & Mayer (2006) 18O valu es were up to 25 higher than during conditions of low flow in the aquifer, which they attributed to atmospheric deposition. However, atmospheric deposition measured in the Bradford Forest of North central Florida was lower in 2008 than in 2005 ( http://nadp.sws.uiuc.edu ). During the spring and summer of 2005, wet deposition (NO3 + NH4) was 3.88 and 4.54 kg/ha respectively,

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67 while in spring 2008, wet deposition was 1.36 kg/ha. Data for summer 2008 are not available yet. Therefore, although recharge vs. low flow conditions in the aquifer does not appear to be a factor in explaining higher isotope values in 2008 vs 2005, it cannot be ruled out due to a lag time between aquifer recharge and spring discharge. As mentione d previously, both 1815N are enriched during the denitrification process and isotopic values are similar to those obtained with animal waste, complicating source identification. Katz (2004) used several lines of evidence to support the supposition that denitrification in Florida karstic systems is negligible: (1) spring waters are aerobic and contain low concentrations of DOC (i.e., redox levels are above those required for denitrification and there is little substrate to support heterotrophic respiration) and (2) rati os of N2:Ar gases dissolved in spring waters were consistent with atmospheric equilibration during groundwater recharge. Excessive N2:Ar, ratio for example, would indicate an additional source of N2 gas in the aquifer, e.g., denitrification input. However, Katz does not rule out the possibility of denitrification occurring during the past within the aquifer system. Although no measurements of the N2:Ar ratio were done in this study to determine the importance of denitrification, the 0.64 slope of the trend line shown in Figure 3 1 raises the possibility that most of the springs I sampled could have had a common nitrate source and that variations in nitrate isotopic composition were driven by denitrification in the aquifer system (a slope of approximately 0.5 would be expected as a result of denitrification). While boil water had low, but measurable oxygen levels (1 2 mg L1), previous studies have shown that discharging groundwater in most springs is a mixture of matrix and conduit water sources, and each tra vels along different flowpaths and has different residence times (Martin & Dean, 2001). It is possible that denitrification is occurring in matrix flows, which have longer residence time, or at

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68 microsites within the conduit flow, but the anoxic character of the water is lost when mixing with oxygenated waters takes place. Denitrification does not rely on carbon alone as an electron donor and was shown to occur with ferrous iron, pyrite (H2S) and organic matter as possible electron donors in a karst aquifer in France (Pauwels, Foucher & Kloppmann, 2000) and likely occurs with H2S and DOC in a karst aquifer in Germany (Einseidl & Mayer, 2006; Einsiedl, Maloszewski & Stichler, 2005). If the trend line in Figure 3 1 is extrapolated to the xaxis intercept, one could infer that the 15N NO3 value of approximately 3 which is 15N values typical for ammonia -based fertilizers or ammonium and nitrate in precipitation (Kendall, 1998). In the majority of N budgets calculated for springsheds, inorganic fertilizers are the largest anthropogenic source of nitrates (based on mass load) (Cohen, 2008). However, the amount of nitrogen that actually reaches the Upper Floridan Aquifer is unaccounted for since load reduct ion in the soil matrix due to biological uptake, for example, is unknown and likely highly variable across the landscape (Cohen, 2008). Not knowing the importance of denitrification in matrix flows of the aquifer makes interpretation of the results of thi 15N NO3 18O NO3 within sites across multiple years as well as between springs underlines the complexity of spring systems, which integrate surface derived inputs across wide areas and multiple time scales. S hort residence times occurring through preferential flows provide little potential for N source fractionation, while longer residence times through matrix flows allow for source transformation and subsequent fractionation, and can result in the loss of the isotopic signature of the original nitrogen source. Additionally, Cohen (2008) stresses that biological nitrogen fixation (BNF) is usually not taken into account in watershed -scale nitrogen budgets although it can

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69 represent up to 28% of the total budget ( Van Breemen et al ., 2002, in Cohen, 2008) and occurs in Florida at high but variable rates in the understory of longleaf pine savannas (Hiers et al. 2003 in Cohen, 2008). The isotopic signature of BNF is from 3 to 1 similar to that of the atmosphere (0 ) (Kendall, 1998) and can decrease the 15N NO3 signal of a more enriched source through mixing. 15N of Algae and Sediment A poor positive relationship (r2 1515N NO3 in spring water discharged from the boil, the primary source of N to the alga e (Figure 3 3). 15N was always lower than that of the source water, likely due to fractionation during algal uptake, during which more 14N than 15N is assimilated resulting in an isotopically lighter signature than that of the source (Fry, 2002). Th e poor relationship is likely due to different fractionation factors for algae of different species as well as algae of the same species but from different locations. De Brabandere, Frazer & Montoya (2007) found that fractionation in periphyton attached to macrophytes in the spring -fed Chassahowitzka and Homossassa rivers varied from 0.7 to 2.5 and state that fractionation reported in the literature for free -floating algae in the water column ranges from 2.5 to 10 (multiple sources listed therein). Foge l and Cifuentes (1993) state that fractionation values of up to 27 have been recorded for algae growing in culture. 15N, there was a strong negative correlation to water column total N and NO2/NO3N concentrations (Table 2 2) and strong positi ve correlations to P availability indices, 15N was high when N was in short supply, but P was available. If N is in short supply compared to P it would suggest N limitation and therefore more complete assimilation of water column nitrate and less is otopic fractionation. In contrast, when N supplies are relatively greater than P demand, then algal cells can be more discriminating in the isotope form of their nitrate

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70 source (14N vs. 15N), thereby producing greater fractionation and isotopically light a lgal tissues. However, 15N of algae, sediments and spring water at 10 spring sites, no direct relationship was found (Figure 3 3). This disparity in results is difficult to explain but may be due to sample size. A larger data set was used to calculate the Spearman correlations (63 spring sites), whereas only 10 sites were analyzed for the data shown in Figures 3 2 and 3 15N NO3 was only available for these sites. 15N of sediment (exposed or beneath an algal mat) was never negative 15N NO3 in spring water (Figure 3 2) or with NO3 concentrations in spring water (Figure 3 15N is a reflection of the organic matter 15N (bot h autochthonous and that of terrestrial origin) as well as diagenic processes, such as 15N) (Brenner et al. 1999; Finlay, 2001) and the lack of negative values may point to denitrification as an important pr ocess occurring in 1515N of sediment under algal mats, which would be expected if the source material under sediments was primarily algae and little or no transformation/fractionation had occurred. 15N values above 5 may be indicative of N from soils (both natural and fertilized soil) as well as animal and/or septic waste. However, as mentioned 15N values of residua l N in sediments (Kendall 15N values of 8 to +4 can indicate inorganic fertilizers as a source of nitrogen, but theses values can overlap with values of other sources, including soil N (fertilized or natural), N from precipitati on and nitrogen fixation. Lyngbya wollei has the ability to fix atmospheric N2 15N of 0 to +2 (Kendall,

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71 1998). Again, fractionation during the uptake of NH4 and NO3 is an additional factor that complicat 15N values. 15N Gradients in Spring -Fed River Runs 15N of epiphytic periphyton, macrophytes and dissolved nitrate increased as nitrate concentrations decreased dow nstream. Decreasing concentrations were attributed to biological uptake of N with little to no nitrate inputs from surface or ground water. This resulted in a smaller nitrogen pool and therefore less source discrimination or isotopic fractionation during a ssimilation. In Toda et al. (2002), the isoto pic signature of the nitrogen source, rather than a decrease in fractionation, was more important in 15N of epilithic periphyton (predominantly attached algae) increased with increasing total N concent rations downstream. Concentration increases were ascribed to increased N loading rates from several sewage 15N 15N of the periphyton. 15N NO3 15N in my study. Results from the four river runs sampled illustrate the difficulty in 15N values of different algal species in many Florida Springs (Figure 5). Neither the nitrate 1518O nor the nitrogen water chemistry varied within the same river along a longitudinal gradient (Figure 3 4 and Table 3 3), yet some algal species showed relatively large isotopic variabil 15N of Spirogyra sp. in the Weeki Wachee River increased from 15N of L. wollei did not vary along 8 km of the same river run. Differences in species -specific fractio nation during 15N of different species at the same site. The effect of environmental factors (e.g. light and current velocity) and physiological factors (e.g.

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72 growth rate) on fractionation during the uptake of N need to be better understood to explain species -1515N -NO3 values. 15N 15N of Vaucheria sp. at Manatee Springs varied substantially (from 8 to +1), but values were predominantly below 4 for the majority of the year, which indicates inorganic NH4 fertilizer and/or N from rain as probable sources (Figure 3 15N -NO3 15N NO3 va lues of 6 and 7 in August 2005 and April 2008, respectively, and Katz (2004) lists a value of 6 These values also indicate NH4 fertilizer, N from rain and soil nitrogen as important sources, which corresponds with values found in the algae samples. Lo wer 15N values are expected for algae than for N NO3 in the source water due to fractionation during algal uptake. The average algal mat area and mat thickness for Manatee and Ichetucknee Blue Hole were calculated by Sickman et al. 15N of Va ucheria sp. is compared to mean thickness of the algal mat both Manatee and Blue Hole (both variables were sampled on the same 15N values correspond to months in which the average algal mat 15N signatures were obtained during months when the average algal mat was thickest (average thickness ranged from < 1 cm to 20 cm.) These values indicate a change in the source of N for the algae corresponding to algal mat thickness. When the mat is thickes t, the algae may be relying on N that has been recycled within the mat itself due to decreased diffusion of N into the inner portions of the mats (Stevenson & Glover, 1993) 15N signatures for autotrophs that were taking up isotopically light NH4 regenerated from decomposing zooplankton. A similar processes may be occurring within Vaucheria mats, where the algae is taking up isotopically lighter N from decomposing algae as well as other biota within the mat.

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73 Unlike Vaucheria 15N values for Lyngbya wollei at Ichetucknee Blue Hole were relatively constant (Figure 3 6). The range in isotopic signatur e of L. wollei was typical of inorganic fertilizers, soil N and/or nitrogen fixation ( 1 to +1 ), of which this species is capable 15N values throughout the year, however, despite high variability in Vaucheria s 15N, points to nitrogen-fixation as a likely source of N for L. wollei Conclusion In conclusion, the stable isotope measurements of algae, sediments and nitrate provided information on potential sources of N to spring algae and sediments, however, ow ing to the complexity of biogeochemical cycling of N in these systems many questions remain unanswered. Assuming that nitrate isotope composition is indicative of N sources, some springs may be 15N NO3) while others show signs of fertilizer pollution or inputs from atmospheric deposition. However, the tight correlation between O and N isotopes of nitrate in most springs, might suggest a uniform nitrate source to most Florida springs; isotopic variation of nitra te, instead, is being produced by denitrification in the aquifer. Finally, studies need to be conducted on physiological and environmental factors affecting within and between -species variability in fractionation during algal uptake of nitrogen.

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74 Table 3 15N NO3 18O NO3) from 17 Florida springs sampled in 2005, 2006 and 2008. Water samples were collected directly above the boil of each spring, at a depth of 0.5 m. Spring Year sampled 15 N NO 3 18 O NO 3 Fanning 2005 8.0 7.4 2006 7.9 5.5 2008 7.7 5.7 Guranato 2006 5.1 8.0 2008 5.4 7.2 Ichetucknee Head 2005 3.5 2.9 2008 3.9 6.3 Ichetucknee Blue Hole 2005 4.4 3.9 2008 4.2 7.2 Jackson Blue 2005 2.9 4.9 Lafayette Blue 2005 8.0 7.5 2006 9.3 9.3 2008 13.3 11.4 Little Fanning 2006 7.9 5.4 Little River 2006 5.7 7.8 2008 11.0 11.1 Madison Blue 2005 3.6 3.0 2006 4.2 6.4 Manatee 2005 5.7 5.1 2008 6.6 7.0 Rainbow 2005 3.9 3.3 2006 4.0 6.0 2008 4.2 5.8 Silver River 2005 6.8 6.2 2006 7.4 7.4 2008 7.6 7.4 Troy 2005 7.1 6.5 2006 7.2 10.1 2008 20.2 15.3 Volusia Blue 2008 14.5 10.8 Wakulla 2005 8.8 8.2 2006 9.2 5.5 2008 9.7 5.1 Wekiwa 2008 15.9 13.9 Weeki Wachee 2008 6.2 4.6

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75 Table 3 2. Significant Spearman correlations (p 1515N and indicators of nutrient availability and nutrient sources. Only variables collected in spring boil areas were analyzed for a total of 34 sites. There were often 15N of algae and sediments was correlated to two water chemistry data bases: (1) water chemistry from the 2006 survey and (2) water chemistry from an average of the 2003 and 2006 surveys. Variables Correlation coefficient n 15N of algal tissue and Total Kjeldahl N of springwater (2006) 0.427 56 Sediment under algae C:N molar ratio 0.442 50 Average NO 2 /NO 3 N of springwater (2003 + 2006) 0.586 47 Total N of springwater (2003 + 2006) 0.598 47 15 N of sediment under algae and 15N 0.513 48 Total Kjeldahl N of spring water (2006) 0.465 52 13C 0.453 49 Sediment under algae %C 0.453 51 Sediment under algae C:N 0.468 50 15 N exposed sediment and 15 N 0.513 48 Total P in springwater (2006) 0.443 53 Sedime nt under algae %C 0.575 37

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76 Table 3 3. Spring river run longitudinal study site numbers, site codes and their distance from the spring boil (km ). Spring Run Site Number Site Code Distance from boil Silver Springs 1 SLV 01 0.0 2 SLV 02 0.5 3 SLV 03 1.3 4 SLV 04 3.2 5 SLV 05 5.3 7 SLV 07 7.2 Rainbow Springs 1 RAI 01 0.0 2 RAI 05 1.3 3 RAI 02 1.6 4 RAI 06 3.5 5 RAI 03 5.2 6 RAI 07 7.6 7 RAI 04 7.7 Wakulla Springs 1 WAK 01 0.0 2 WAK04 0.5 3 WAK 05 1.0 4 WAK02 1.6 5 WAK 06 2.6 6 WAK03 3.2 8 WAK 08 9.8 Weeki Wachee Springs 1 WEK 01 0.0 2 WEK 02 0.2 3 WEK 03 0.6 4 WEK 04 1.8 5 WEK 05 3.1 6 WEK 06 4.0 7 WEK 07 8.1

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77 0 2 4 6 8 10 12 14 16 0 5 10 15 20 25 15N-NO 3 18O-NO3 Figure 3 15N NO3 18O -NO3) from 17 Florida springs s ampled in 2005, 2006 and 2008. Water samples were collected directly above the boil of each spring, at a depth of 0.5 m. R2 = 0.71 and the slope of the line is 0.64.

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78 0 2 4 6 8 10 12 -1 0 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 15N of Algae and Sediment 15N-NO3 of Spring Water Macroalgae Sediment under algal mats Exposed sediment Figure 3 2. 1515N NO3 o f springwater from 10 headwater springs sampled in 2006.

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79 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 0 1 2 3 4 5 6 NO3 mg L-1 15N Macroalgae Sediment under algal mats Exposed sediment Nitrate in spring water Figure 3 15N values of algae, sediments and nitrate in NO3 of spring water and nitrate concentrations (mg L1) of 10 headwater springs sampled in 2006.

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80 3 4 5 6 7 8 2 4 6 8 10 12 15N 18O Rainbow River Silver River Wakulla River Weeki Wachee River Figure 3 4 Stable isotope composition of nitrate in spring water from the Rainbow, Silver, Wakulla and Weeki Wachee River runs sampled in 2006. Samples were taken starting at the boil area of each site and ending 7.2 to 9.8 km downstream, depending on the site.

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81 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 Distance from boil (km) 15N -1 0 1 2 3 4 5 6 7 0 1 2 3 4 5 6 7 8 9 Distance from boil (km) 15N Lyngbya wollei Dicotomosiphon sp. Spirogyra sp. Hydrodicton sp. Cladophora sp. Aphano sp. Caloglossa sp. Nitrate Vaucheria sp. Enteromorpha sp. Compsopogon sp. 0 1 2 3 4 5 6 7 8 9 10 11 0 1 2 3 4 5 6 7 8 9 10 Distance from boil (km) 15N -3 -2 -1 0 1 2 3 4 5 0 1 2 3 4 5 6 7 8 9 Distance from boil (km) 15N A B C D 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 Distance from boil (km) 15N -1 0 1 2 3 4 5 6 7 0 1 2 3 4 5 6 7 8 9 Distance from boil (km) 15N Lyngbya wollei Dicotomosiphon sp. Spirogyra sp. Hydrodicton sp. Cladophora sp. Aphano sp. Caloglossa sp. Nitrate Vaucheria sp. Enteromorpha sp. Compsopogon sp. 0 1 2 3 4 5 6 7 8 9 10 11 0 1 2 3 4 5 6 7 8 9 10 Distance from boil (km) 15N -3 -2 -1 0 1 2 3 4 5 0 1 2 3 4 5 6 7 8 9 Distance from boil (km) 15N A B C D Figure 3 5. Stable isotope composition of algae and 15N NO3 of spring water measured along four spring river runs in January 2006. A) Silver River. B) Weeki Wachee River. C) Wakulla River. D) Rainbow River.

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82 -2 -1 0 1 2 3 4 5/28/05 7/17/05 9/5/05 10/25/05 12/14/05 2/2/06 3/24/06 Date 15N Lyngbya wollei Vaucheria sp. -10 -8 -6 -4 -2 0 2 4/8/05 5/28/05 7/17/05 9/5/05 10/25/05 12/14/05 2/2/06 3/24/06 Date 15N Vaucheria sp. Figure 3 15N composition of algae at Ichetucknee Blue Hole and Manatee Springs from May 2005 to March 2006. A 13C of Lyngbya wollei and Vaucheria sp. at Ichetucknee Blue Hole. 13C of Vaucheria sp. at Manatee Springs.

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83 CHAPTER 4 13C STABLE ISOTOPE COMPOSITION OF ALGAE, SEDIMENT AND DISSOLVED INORGANIC CARBON IN FLORIDA SPRINGS Introduc tion Increases in the abundance of floating and benthic algal mats have been observed in many of Floridas karst springs during the last 50 years, particularly of Lyngbya wollei (Farlow ex Gomont) Speziale and Dyck, and Vaucheria sp. De Candolle, the two m ost widely distributed mat -forming species (Odum, 1957; Whitford, 1956; Quinlan et al., 2008; Stevenson et al. 2008). These nuisance algal mats can out -compete native submerged aquatic vegetation (Doyle & Smart, 1998), greatly altering the ecology of spring systems. Additionally, increased algal biomass detrimentally affects the recreational use of springs in Florida (Florida Springs Task Force, 2000; Cowell & Botts, 1994). Although nutrient availability is thought to affect algal abundance (Florida Springs Task Force, 2000; Stevenson et al. 2007), a direct cause -effect relationship has not been clearly shown and multiple factors are likely influencing both biomass accrual and distribution in springs. The stable isotope signature of carbon 13C) in algae and dissolved inorganic carbon (the primary carbon source of algae in springs) can be used to gain a better understanding of factors affecting algal growth and distribution. 13C compositi 13C of various forms of dissolved inorganic carbon (DIC) used in photosynthesis and ii) fractionation of C isotopes during algal uptake (i.e., preferential use of 12C over 13C) (Fry, 2006; Finlay 2004). In Florida springs, DIC sources include atmospheric CO2 charged in precipitation, CO2 produced by heterotrophic respiration in soils as water percolates into the Floridan Aquifer and DIC produced by weathering of carbonate minerals in the aquifer. Most algae have the ability to use both CO2 and HCO3 as a source of carbon during photosynthesis and the relative abundance of these DIC species in spring waters depends on the pH and geochemical character of the water. Previous

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84 studies have found differences of 7 to 10 in 13C, between HCO3 and CO2 (aq) (Finlay 2004). For example, algal reliance on dissolved CO213C values, caused by strong respiratory production of CO2, could produce algal tissue of 45 (Fry 2006). Additionally, both light regime and current velocity can affect DIC source discrimination by algae. Increased insolation results in increasing rates of photosynthesis, resulting in higher carbon demand which 13C values in algae ( Hill and Middleton, 2006). However, under conditions of higher current velocity, a system can be replenished by isotopically lighter CO2 (aq), 13C values (Finlay, 1999). 13C of organic matter in spring sediments is affected b 13C of source materials 13C of the DIC taken up during aquatic photosynthesis (Brenner, 13C composition of aquatic primary producers is often more variable than that of terrestrial autotrophs (Finlay, 2004); terrestrial C3 plants generally produce detrital materials ranging from 34 to 1313C values in algae are more variable with ranges of 3 to 46 (Raven et al 2002, Fry, 2006). Finlay (2001) found that the particulate terrestrial detritus of temperate streams has a constrained mean value of 28.2 +/ 13C of the detritus in these systems w as integrated through space and time. Diagenesis occurring in the sediment once the organic matter has been deposited 13C values (Brenner 1999). For example, microbial decomposition of the organic matter may select for isotopically lighter ca rbon (12C) over 13C, resulting in enriched residual carbon. 13C stable isotope of carbon of algae and spring sediments as well 13C of the dissolved inorganic carbon (DIC) of spring water were measured at multiple scales

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85 to help determine carbon sources to benthic algal mats and factors controlling algal abundance. 13C of DIC and total DIC concentrations at multiple headwater springs throughout the state, (2) deter 13C composition of algae and spring sediments through surveys at a regional scale and along four 13C composition of filamentous mat -forming algae over the course of one year at two springs, and (4) assess the 13C of algae, carbon sources and indicators of nutrient availability at the regional scale Methods Study Sites 13C analysis was conducted on mat -forming algae and sediments in Florida springs on three scales: (1) regionally, ( 2) along a longitudinal gradient (starting at the spring boil and sampling 8 to 10 km progressively further downstream) of the spring-fed Silver, Rainbow, Wakulla and the Weeki Wachee Rivers and (3) on a monthly basis in the boil areas of Manatee and Ichet ucknee Blue Hole Springs during the course of one year. The same sites were sampled as for the 5N analysis of algae and sediments, which is described in Chapter 3. The complete list of sites and locations sampled for the regional, gradient and seasonal studies is found in Appendix A. Specific sites sampled for the longitudinal gradient study are l isted in Table 3 3 and site codes correspond to those listed in Appendix A. Additional sampling trips were conducted in April and August of 2008 to 18 headwater springs in order to collect samples for dissolved inorganic carbon (DIC) analysis of spring wa ter and 13C analysis of algae. The sites sampled are listed in Table 4 2 and site codes correspond to those listed in Appendix A.

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86 Algae, Sediment and Water Sample Collection 15N analysis of algae and sediment (descri 13C analysis of algae and sediment. Water samples for chemical/physical parameters (TKN, TP, NH4 +, NOx -, SRP, DOC, temperature, pH, 15N of a lgae and 13C of algae and sediment, described in the statistical analysis section below. Detailed descriptions of sampling methodology can be found in the methods section of C hapter 3. This includes samples from the 2006 regional study, the 2006 longitudinal gradient study and the seasonal study conducted in 2005 and 2006. Algae, Sediment and Water Sample Processing and Analysis Algae samples were picked clean of invertebrates and debris within 24 hours of field collection, stored frozen and later lyophilized at 91C under a 35-mTorr vacuum. Once dry, they were again picked clean of any debris initially missed and ground and homogenized in a ball mill. The samples collected and 13C of algae and sediments were also used to determine percent C, N and P. Algae samples that were placed in scintillation vials for species verification were preserved using M3 solution and sent to the Center for Water Sciences a t Michigan State University, where they were identified. Macroinvertebrates were removed from sediment samples which were then homogenized by stirring, also within 24 hours of field collection. Sediments were stored frozen and subsequently dried in an oven at 60C for 5 days. They were then passed through a sieve to remove coarse debris (e.g, twigs, leaves, whole mollusk shells) and ground and homogenized in 13C isotopic analysis, sediment samples were acid fumigated with HCl to remove inorganic carbon (Harris et al ., 2001). A subset of algae samples collected in 2006 was

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87 also acid fumigated to see whether or not calcium carbonate was deposited on the algal tissue 13C values. Carbon isotopic composition of algae and sediments was measured on a Thermo Finnigan Delta -Plus XP isotope ratio mass spectrometer (Thermo Fisher Scientific, Inc., Waltham, MA, U.S.A.) at the University of Florida using an elemental analyzer inlet system and continuous flow of He. The International Atomic Energy Association s tandard for sucrose was included in each run and 13 standards (Vienna PeeDee Belemnite for C). Percent carbon and nitrogen of the dried algal tissue and sediments were measured by high temperature combustion using a Flash EA 1112 Nitrogen/Carbon Analyzer with MAS 200 R Autosampler (Thermo Fisher Scientific Inc, Waltham, MA, U.S.A.). Phosphorus content of dried algal tissues and sediment was measured on combusted (550C) and acid digested (6N HCl) samples as SRP (Anderson, 1976) on a Technicon Autoanalyzer ( Technicon Instruments Corporation Wilmington, MA, U.S.A.) At Michigan State University, sediments were analyzed for % water content, dry mass (DM), ash free dry mass (AFDM) (Eaton et al. 1995) available p hosphorus (PO4 -) and available nitrogen (NH4 +, NO2/NO3 -) following the extraction of 1g of wet sediment with Truogs reagent and KCl (Allen, 1989) Soluble reactive phosphorus, NH4 +, and NO3 were measured on a Bran+Luebbe Auto Analyzer 3 (Bran+Luebbe, Norderstedt, Germany) using EPA Methods 365.1, 350.1 and 353.2, respectively. Total Kjeldahl nitrogen was determined by H2SO4 and Kjeldahl salt digestion and flow injection determination of ammonium (EPA Method 351.2). Total phosphorus was meas ured as SRP on a Bran+Luebbe Auto Analyzer 3 after digestion with H2SO4 and potassium persulfate (EPA Method 365.1).

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88 13C 13C of Algae Water samples for DIC analysis were collected in April and A ugust of 2008 either from a kayak or from the shore above the spring boil depending on the location of the boil. Glass vials (30ml) containing 4 to 6 mg of blue copper sulfate crystals were used for sample collection (US EPA, 2006). The cap was unscrewed w hile underwater (approximately 0.3 to 0.5 m below the surface), the sample vial was completely filled (leaving no headspace) and then the cap was screwed back on while still underwater, making sure that the sample had no contact with the atmosphere to avoi d CO2 exchange (US EPA, 2006). Samples were transported on ice to the laboratory where they were stored in a refrigerator at 4C until analysis. For reasons that are still unknown, many of the water samples collected in April 2008 froze in the refrigerator and burst. A subsequent sampling trip was then rescheduled in August to revisit sites where the samples had been lost as well as to resample several sites to compare DIC variability in samples that had not burst, which is why some, but not all sites, have two samples (April and August) (Table 4 2). A composite sample of each of the dominant algal species was also collected at each site by snorkeling, shaken in the water to remove any loosely attached debris and placed into 1 gallon Ziploc bags (SC Johnson, Racine, WI, USA) filled with site water. Samples were then transported to the laboratory on ice. The algal samples were processed as described above. An additional step was taken, however. A subsample was taken from each site and washed in a solution of H 13C values of acidified vs. unacidified samples to see if CaCO3 potentially deposited on the algal tissues during drying 13C value. Additionally, a YSI 556 Multi -probe System (YSI Incorporated, Yellow Springs, OH, U.S.A.) was used to measure temperature, conductivity, pH, and dissolved oxygen at each site above the spring boil.

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89 All samples were analyzed at the University of Florida. Total DIC was measured on an AutoMate Automatic Acidification System Coupled with a UIC 5011 Coulometer and th 13C of DIC and algae was measured on a Delta -Plus XP Isotope Ratio Mass Spectrometer. Statistical Analysis 13C composition and indicators of nutrient availability an d sources, as well as other environmental variables collected during the Rapid Habitat Periphyton Analysis, which is described in the Methods section of Chapter 3. 13C are the same as those listed in Chapter 3 an d include: (1) site water physical -chemical parameters, (2) algal and sediment C:N:P molar ratios, as well as bioavailable N and P of the sediments, (3) average site depth and current velocity, (4) average site canopy cover, (5) site buffer zone characteri stics, (6) land use characteristics and LDIs. Land use characteristics for each site and LDI (Landscape Development Intensity) indexes were calculated from data provided by the Florida Department of Environmental Protection (FDEP) by A. Pinowska. A subset of the regional study sites (34) was used in the correlation analysis. Only samples from the spring boil areas were used, in order to avoid autocorrelation among multiple sites along spring runs. Samples collected in April and August of 2008 for DIC analys is were not included in the correlation analysis. Results Analysis of Algae and Sediment Stable Isotopes and C:N Molar Ratios 15N values of algae and sediment obtained for analysis in Chapter 2 were plotted against 13C values of the same samples (Figure 4 1). Algae and sediment in the 63 springs sampled for the 2006 regional study revealed a substantial range of values in stabl e isotopic composition. For 13C ranged from 12 to 13C values ( 12 ) were found for

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90 Spirogyra sp. collected from the boil areas of Juniper and Alexander Springs in the Ocala 13C values ( 44 ) were obtained for Vaucheria sp. from Wakulla, 15N values ranged from +8 to 7 The highest values (+8 ) were found in Spirogyra sp. collected along the Wakulla Springs river run and in Lyngbya wollei samples collected nea 15N value (7 ) was found in Vaucheria sp. from Little River Springs. Isotope values were less variable for sediments than for algae (Figure 4 1) and all but two 13C and 15N ranges found for algae. Exposed sediment refers 13C values for exposed sediment ranged from 20 to 32 with the most enriched value found at Ponce de Leon Springs and the lowest value found along the Weeki Wachee and Silver River spring runs. 15N values for exposed sediment ranged from 0 to 10 The highest value was obtained at both Rainbow and Wekiwa Springs and the lowest value (0 ) was found along the Weeki Wachee Springs river run. Sediment samples collected from underneath algal mats had a 13C values, from 25 to 32 The most enriched values ( 25 ) were found in Pitt, Juniper and Silver Glen Springs, and the lowest value was found at Ichet ucknee Springs. 15N values for sediment under algal mats showed a similar range as that of exposed sediment (0 to 8 ). 13C of algae and sediment and their respective C:N molar ratios are shown in Figure 4 2. Sediment C:N ra tios (both exposed and under algal mats) showed a wide range of values, from 6 to 112, with both the highest and lowest values for exposed sediment, while algal C:N range was much lower, from 6 to 18. There was no apparent 13C of alga e and sediment and C:N ratio.

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91 Variation in Isotope Signatures among Algal Species The three most common species found during the regional study, Lyngbya wollei Vaucheria sp. and Spirogyra 13C isotopic compositions (Figure 4 3 ). Vaucheria 131513C ranged from 44 to 15N values ranged from 7 (Little River Springs) to +6 (Wakulla and Weeki Wachee Springs). Spirogyra 131513C ranged from -38 to 12 with 15N values ranged from 1 (Weeki Wachee Springs) to +8 (Wakulla Springs). For L. wollei, 13C values ranged from 40 (Williford Springs) to 15N values ranged from 2 (Rainbow Springs) to +7 (Alexander Springs). Correlations among Algal Stable Isotope Signatures, Water Quality and Environmental Variables 13C and variables relating to indicators of nutrient availability and sources are listed in Table 4 1. To avoid Type 1 errors in this analysis, I set the p level at 0.001 to account for the relatively large number of correlations 13C, significant positive and negative correlations were found between numerous variables. The strongest correlations were found with the pH of water (positive) followed by the C:P ratio of exp osed sediment (negative). 13C and variables relating to indicators of nutrient availability and sources are shown in Table 4 1. For sediment collected beneath an algal mat, the strongest relationships to 13C were the C:N ratio of sediment under algae and the average concentration of orthophosphate in the water. This average includes data from 2003 (Fall 13C of exposed sediment (sediment with

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92 no algal ma t on top of it), was most strongly related (negatively) to average conductivity (2003 + 2006) and the diatom indicator of sulfate concentrations in spring water. The strongest positive correlations were with an indirect measure of low P conditions (an indi cator developed by R.J. Stevenson representing the percent of diatoms that grow under low phosphorus conditions) and dissolved oxygen. Relationships between Tota l Dissolved Inorganic Carbon, pH and the 13C of Dissolved Inorganic Carbon and Algae 13C (Table 4 1) and species -specific relationships are shown in Figure 4 4. The r2 13C of Vaucheria sp., Lyngbya wollei and Spirogyr a sp. and pH at 63 spring sites sampled in 2006 were 0.48, 0.40 and 0.41, respectively (Figure 4 13C showed a stronger relationship to pH (positive) (r2 = 0.76) and total DIC (negative) (r2 13C of dissolved inorganic carbon (DIC) (positive) (r2 = 0.50) (Figure 4 5). Species -specific distributions relating to total DIC were also discernible. Vaucheria sp.was generally found in springs with higher total DIC concentrations, while Spirogyra sp. was found in all but one case, in springs with low total DIC (Figure 4 5, A). Lyngbya wollei was more ubiquitous, but tended to 1313C of DIC and pH, species-13C of DIC also showed a stronger relationship to total DIC (negative) (r2 = 0.519) than pH (positive) (r2 = 0.34), while the r2 value of total DIC vs pH was 0.812 (negative), the strongest relationship of all (Figure 4 6). 13C of Algae and Sediment along Longitudinal Gradients The site s sampled at each of the four spring river runs and their distance from the spring boil are listed in Table 3 3 of Chapter 3 (this document). The site codes are the same ones used

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93 (and therefore the same locations) in the regional study and exact locations are listed in Appendix A. Rainbow Springs River Run 13C values of the algae and the sediment from the Rainbow Springs river run are shown in Figure 4 7 Two algal species were found, Lyngbya wollei which showed a wide range of values along the river run ( 34 to 24 ) and Vaucheria sp., with a much narrow er range ( 38 to 36 ). Sediment samples were generally more enriched than algal samples ( 28 to 24 ), and the 13C values. Weeki Wachee Springs River Run Seven species of algae were found along the Weeki Wachee river r un: Vaucheria sp., Spirogyra sp., Lyngbya wollei, Hydrodictyon sp., Cladophora glomerata., Aphanothece sp.balls and Calaglossa sp. (Figure 47 ). Algal species and sediment samples were separated out fairly 13C values, except for Spirogyra sp. which showed a sharp increase in values within the first km, from 37 to 21 The range of Dichotomosiphon 13C ( 44 to 42 ) was very similar to values seen at other sites for both Vaucheria sp. and Compsopogon sp. (Figure 4 7) 13C values did not vary widely for sediment samples ( 31 to -26 ). Wakulla Springs River Run 13C values of algae and sediments for the Wakulla Springs river run are shown in Figure 4 7 Five species of algae were found along the run: Compsopogon sp., Vaucheria sp., Spirogyra sp., Lyngbya wollei and Enteromorpha sp. Compsopogon sp. and Vaucheria sp. had 13C (between 45 and 40 ) that did not vary much along the river run, while values for Sprirogyra were much more enriched and incr eased sharply with a 1.5 km distance,from 32 to 23. The sediment samples showed little variation along the run, from ( 31 to 27 ).

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94 Silver Springs River Run Three algal species, Lyngbya wollei Vaucheria sp. and Spirogyra sp. were found along the Silver Springs River run (Figure 47 ). The three algal species and the sediment samples w ere 1313C values ranged from 41 to 31 with Vaucheria sp. having the lowest values ( 41 to 13C values were more enriched, ranging from 31 to 13C values were l owest at the spring boil for the algae and sediment sampled under a benthic algal mat and the values for sediment collected under an algal mats more closely followed the pattern of L. wollei and Vaucheria sp. than exposed sediment. Seasonal Variation in Al gal 13C Vaucheria 13C values decreased sharply (8 ) from May to June 2005 (from 36 to 44) and then remained relatively stable until March 2006, fluctuating betwee n 43 and 46 (Figure 4 8 ). At Ichetuc13C values varied seasonally in both Lyngbya wollei and Vaucheria sp. (Figure 4 8 ). Vaucheria sp. values ranged from 45 to 40 and L. wollei 13C ranged from 40 to 34 Discussion Dissolved Inorganic Carbon in Florida Springs Dissolv ed inorganic carbon (DIC), composed of CO2 and HCO3 to varying degrees, is the primary carbon source available to algae for photosynthesis in Florida Springs. Therefore, the 1313C of the DIC at 18 headwater springs sampled in my study ranged from 13 to 6 (Table 4 2, Figure 4 6). The more negative values are typical of groundwater values found by Deines et al. (1974) representing carbonate dissolution in a closed-system in Pennsylvania ( 12 to 14 ), where half of the DIC comes from carbonate dissolution and the remaining half was contributed by CO2 produced

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95 13C value of 0 to 2 (Deines et al. 13C from a limestone sediment core in Biscayne Bay ranged from +0.33 to 3.5 with most values between 0 and 1 per m il. Soil CO2, on the other hand, has 13C values of approximately 13C of the predominant source of organic matter, i.e. terrestrial vegetation (Deines et al. 1974; Doctor et al ., 2008). More 13C -DIC values ( 15 to 20 ) would indicate water from an open system where soil CO2 has stronger influence, but CO2 exchange with the atmosphere also occurs, which increases 13C values as atmospheric CO2 has a value of approximately 8 (Doctor et al. 2008). Therefore, Florida springs with more enriched isotopic values may be indicative of a greater contribution from carbonate dissolution and atmospheric CO2 than soil CO2. Marfia et al. (2004) found a similar range of total DIC (5.4 to 112.9 mg C L113C DIC ( 7.4 to17.4 ) in groundwater in a karst aquifer in Belize as those found in my study and they attributed these values to both open and closed system carbonate dissolution. 13C DIC (r2 = 0.51) (Figure 4 6 A). At high total DIC (25 to 50 mg C113C values were obtained ( 10 to 12 ). Marfia et al 13CDIC in 13C DIC, which they a ttributed to closed system carbonate dissolution. However, they found that at low total DIC, surface waters 13C DIC values than groundwater (the same trend I found in my study). They suggested several possibilities for this suc h as degassing of CO2 and preferential uptake by plants of 12C vs 13C of DIC for photosynthesis, both resulting in an isotopically more enriched substrate and lower total DIC concentrations. Doctor et al. (2008) also found that 13C values of DIC coupled with decreasing DIC concentration were influenced by

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96 degassing of CO2 in a headwater stream in Vermont, as did Waldron, Scott & Soulsby (2007) in a headwater sub -catchment of the Dee River in Scotland. 13C of DIC as well as total concentrations in Florida springs could therefore indicate that similar processes are occurring and that the aquifer is a mix between open and closed carbonate dissolution systems. However, since the water samples were collected above the spring boil preferential uptake by primary producers of the isotopically lighter carbon has not occurred at this point. High total DIC 13C could be indicative of greater influence from CO2 from the soil and the atmosphere, e.g. under recharge conditions, and more 13C values coupled with low DIC concentrations could be indicative of degassing of CO2 as the water comes up out of the spring boil, leaving more enriched HCO3 and less total DIC. The strong negative relationship found between total DIC values and pH (r2 = 0.81) (Figure 4 6, C) also supports this as the lowest pH values (7.6 to 8) correspond to the highest total DIC concentrations (27 to 50 mg C L1) and at these pH levels, there is more CO2 (approximately 10%) than at pH above 8.2 where almost all of the DIC is in the form of HCO3. The poor relationship b13C DIC and pH (r2 = 0.34) (Figure 46, D) may be because at the lowest pH levels (7.6), the majority of the DIC in the water is still in the form of HCO3 so the scatter in 13C may reflect the mix of HCO3 (the predominant form) and CO2 ions as w ell as a mix of sources of the CO2 ions (i.e. atmospheric vs. soil). Katz (2004) states that many of the springs in Florida discharge water that comes largely from the shallow portions of the Floridan Aquifer, rather than deeper portions, adding weight to the argument that the range in isotope and total concentration values for DIC represents both open and closed system carbonate dissolution. Katz based his findings on several chemical characteristics, such as high dissolved oxygen levels in groundwater di scharged and low

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97 dissolved solids in the water. At both Rainbow and Silver Springs, (Faulkner, 1973, cited in Katz, 2004) found that groundwater flowing toward the springs was comprised of 92% shallow and 8 % deep water from the aquifer. However, this does not occur at all springs or at all times. Osmond et al (1971, cited in Katz 2004) found that at base flow, water discharged at Wakulla Springs was comprised of 35% shallow and 65% deeper water. Factors Affecting 13C Values in Algae 13C values in algae, however, results from the regional and gradient studies point to relatively distinct species -13C compositions. Spirogyra 13C values, up to 12 while Vaucheria sp., Dichotomosiphon sp and Compsopogon sp consistently had the lowest values, commonly ranging from 45 to 38 (Figures 4 4 and 4 7). Species -13C of algae is likely due to several reasons. A p rimary one may be an algal species relative uptake of and/or degree of preference for CO2 (aq) vs. HCO3 ion as a carbon source. The proportion of each of 13C, as HCO3 13C valu es than CO2 13C does not necessarily mean that algae are taking up the isotopically heavier carbon from HCO3 since there may simply not be as much light CO2 available and therefore less isot ope source discrimination would result. The pH of spring water can also cause shifts in the CO2 (aq) HCO3 equilibrium, with HCO3 prevalent as pH rises within the range of pH observed in Florida springs (ca. 6.0 to 8.6). The most enriched values for Spi rogyra sp. ( 12 ), Lyngbya wollei ( 20 ) and Vaucheria sp. (32 ) came from springs where pH values were above 8 (Figure 44). At this pH virtually all of the DIC is in the form of HCO3 -. The most negative 13C values (below -35 ) for algae found during the 2006 regional study came from sites with pH below 6.5 (Figure 44) and at this

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98 pH, approximately 50% of the DIC is composed of CO2. If concentrations are not limiting, CO2 uptake does not require energy expenditure by the algae, while HCO3 assimilation is actively pumped into algal cells (Fogel & Cifuentes,1993) When DIC concentrations are low, however, DIC (CO2 as well) is actively transported into algae and the majority of this DIC doesnt leave the al gal cell until it is fixed through RuBP carboxylase in photosynthesis, resulting in relatively little fractionation ( 5 ) and in turn in more enriched algal 13C (Fogel & Cifuentes,1993). 13C values likely indicate strong respiration inputs as well because respired CO2 (approximately 20 ) is further fractionated by approximately 20 when assimilated by algae during photosynthesis, resulti 13C values as low as 45 (Fry, 2006). I measured values as low as 46 for Vaucheria sp. at Manatee Springs during the seasonal study. (Note: during respiration, heterotrophic bacteria selectively respire 12CO2 over 13CO2 13C o f CO2 13C to the pH of spring water (Table 4 1, Figure 45, C) may also be due in part to high respiration rates which 13C of CO2 as well as increased CO2 in the water column, which in turn can lower the pH of the water through its effect on carbonate equilibrium. 1313C of DIC (Figure 4 5), the strongest relationship was found with pH (r2 = 0.76), then total DIC (r2 = 13C of DIC (r2 = 0.50), which was surprising, as I expected the strongest 13C DIC, a direct reflection of the isotopic composition of the carbon source. However, multiple factors can affect isotopic fractiona tion during DIC uptake, including 13C DIC. Species -specific patterns were also observed in relation to DIC and pH (Figure 4 5). Vaucheria sp. was generally found in spri ngs with lower pH and higher total DIC concentrations, while

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99 Spirogyra sp. was found in springs with higher pH and low total DIC (Figure 4 5, A). Lyngbya wollei was more ubiquitous, but tended to be present in sites with lower total DIC and higher pH. Sinc 1313C of DIC, species -specific tendencies were also found with this variable. These findings support the argument that some species are better adapted to or show preference for HCO3 uptake vs. CO2 uptake. The relationship between algae, total DIC concentrations and pH merits further investigation and may be an important factor in determining algal distribution in Florida Springs. 13C values. Cornelisen et al 13C values in Ulva pertusa under saturating light conditions and they offered two possible explanations: (1) higher irradiance leads to increased photosynthesis rates and the algae need to actively take up HCO3 to meet carbon d emand and/or (2) increased irradiance results in more efficient CO2 fixation inside algal cells regardless of the original carbon source and increased retention of heavier carbon (13C) inside algal cells, leads to more enriched values. Kubler &Raven (1995 in Cornelisen, 2007) found that higher light conditions not only increased carbon demand, but also provided the energy required to assimilate HCO3, which is actively pumped in 13C than CO2. Wiencke & Fischer (1990) found differences of 20 in the algae Desmaretsia antarctica which they attributed to changes 13C of the algae, but these would be important considerations in future investigations to better understand 1313C values as the algae can be replenished with isotopically lighter CO2 and HCO3 (Finlay, 1999). Another potentially important finding from the stable isotope measurements and 13C and diatom indicators

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100 of P availability in spring boil water (i.e., % high P individuals in spri ngs and Florida Springs Nutrient Index (Table 4 1). There is evidence to suggest that algal taxa switch between CO2 (aq) and HCO3 carbon sources as a function of the availability of limiting nutrients (R. Jan Stevenson, unpublished data). When P availabil ity is low, algae may primarily utilize HCO3 ion as a carbon source during photosynthesis; when P availability is high, algae may utilize greater amounts of CO2 13C of these DIC species previously discussed, increasing inputs of P to springs would increase the assimilation of isotopically lighter CO2 (aq) (relative to HCO3 -13C. Beardall et al (1982 in Fogel & Cifuentes,1993) found this same trend in phytoplankton under N limited conditions, which resulted in the activation of the system for concentrating HCO3 in phytoplankton. As N limitation increased, amounts of carboxylating enzymes decrea sed, which are required in RuBP carboxylase activation. They suggested that the increased CO2 concentrations within the cell (from pumped HCO3) needed for RuBP carboxylase activation outweigh the energy required to assimilate HCO3. Seasonal and Longitudi 13C At Manatee Springs, there was a rapid decline in Vaucheria 13C from April to June 2005 (from 36 to 44 ) and then values remained relatively stable until March 2006 (Figure 4 13C coincides with a time of rapid biomass increase at the spring (Sickman et al 13C due to increased carbon demand and less source discrimination (Hill and Middleton, 2006), DIC is most likely not a limiting nutrient in this case. Instead, this rapid decline lends strength to the argument that high respiration rates (and the assimilation of respired CO2) results in very low 13C. At Ichetucknee Blue Hole, high respiration rates of primary producers may also accou nt, in

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101 large part, for the low isotopic signatures found in both Lyngbya wollei and Vaucheria sp. as the boil area of Blue Hole is completely covered by the macrophyte Vallisneria americana. Along longitudinal gradients, Compsopogon, Vaucheria and Dicotomo siphon sp. 13C values with little variability along 8 to 10 km of the four river runs (Figure 4 7). These species likely have similar uptake capacities of CO2 vs. HCO3. Additionally, microsite variability along the river run appe ars to have affected these species isotopic composition less than Lyngbya wollei and Spirogyra sp. These two species showed more 13C from site to site within each river run, with changes of up to 10 which may have been due to factors su ch a current velocity and irradiance. 13C Values in Spring Sediments 13C had a relatively well -13C range, regardless of whether or not the source was from exposed sediments or from sediment collected from under an algal mat. More than 90% of the samples fell within the range of 30 to 25 which was higher than the majority of algal samples (Figure 4 1). This pattern was also consistent in the four river runs sampled (Figure 4 7). This range is similar to that rep orted by Finlay (2001) of 28.2 +/ 0.2 13C of terrestrial C3 plants is 34 to 22 (Rounick & Winterbourne, 1986) and for C4 13C values are approximately 12 to 13 Therefore, the sediment carbon isotope values could suggest a 13C values of 30 to 25 could also result from post -depositional processing of isotopically depleted a lgal tissues (30 ) in sediments since decomposition/respiration/methanogenesis all favor loss of 12C over 13C leaving the residual substrate enriched in 13C. 13C values of algae and sediment were plotted against C:N molar ratios, the majority o f sediment samples had C:N ratios above 10 and up to 112, while all of the algal

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102 samples had C:N ratios between 5 and 18 (Figure 4 2). C:N ratio is used to determine differences in origin of organic matter in sediments because algal C:N generally has a val ue in the range of 5 to 8 while vascular plants generally exhibit ratios from 20 to 80, largely due to recalcitrant support tissue (Meyers & Ishiwatari, 1993; Vreca & Muri, 2006). Therefore, the majority of the organic matter in my sediment samples likely came from vascular plants. In a study conducted in Lake Panasoffkee, FL, a shallow lake dominated by macrophytes, Brenner et al. (2006) found 13C values (an average of -27 ) in emergent vegetation, which they attributed to recalcitrant structural tissue (e.g. lignin and cellulose) and unlimited CO2 availability from the atmosphere, respectively. Phytoplankton mean C:N was 6.5. The relatively higher range in C:N found in algal samples in my study (up to 17) may reflect more cellular structural requirements, such as the thallus, which isnt found in phytoplankton (Townsend et al. 2008) as well as possible N -limitation at some spring sites (Borchardt, 1996). The variable that was most strongly correlated to 13C of sediment under algal mats was its C:N molar ratio ( 0.576) (Table 4 1), again pointing to vascular plants (not necessarily of terrestrial origin, however) as the primary component of the organic matter in spring sediments of the sites sampled a nd shows a similar trend as that found by Brenner et al (2006). In summary, I found a very strong relationship between carbon isotope composition, pH and total DIC. This relationship likely results from differential use of HCO3 and CO2 (aq) during photo 13C values and their relative usage can set 13C of the algae. Additionally, under high total DIC conditions, more isotopically light CO2 and HCO3 are available to the algae for assimilation, resulting in 13C values. Factors controlling the relative usage of these DIC species during algal photosynthesis include water column pH, respiration rates of primary producers and perhaps the availability of P. The

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103 effects of current velocity and irrad iance on isotopic composition, which were not analyzed in this study need to be considered in future studies to better understand within-species isotopic variability. The relatively strong species -specific relationship between algae, total DIC concentratio ns and pH may be an important factor in determining algal distribution in Florida Springs and merits further investigation.

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104 Table 4 1. Significant Spearman correlations (p 1313C and indicators of nutrient availability and nutrient sources. Only variables collected in spring boil areas were analyzed for a total of 34 sites. There were often multiple algal 13C of algae and sediments was correlated to two water chemistry data bases: (1) water chemistry from the 2006 survey and (2) water chemistry from an average of the 2003 and 2006 surveys. Variables Correlation coefficien t n 13 C vs. pH (2006) 0.683 54 13 C 0.475 52 Dissolved oxygen 0.466 50 Diatom indicator: Species richness 0.453 51 NO 2 /NO 3 N of springwater (2006) 0.463 56 Exposed sediment %C 0.468 51 Sediment under algae C:N molar ratio 0.468 50 Diatom indicator: % high P individuals in springs 0.470 51 Diatom indicator: Florida Springs Nutrient Index 0.477 47 Exposed sediment C:P molar ratio 0.487 51 13 C of sediment under algae vs. Ortho phosphate in s pring water (2003+2006) 0.535 43 Total P in spring water (2003+2006) 0.520 51 Dissolved oxygen (2006) 0.496 46 Sediment under algae C:P molar ratio 0.444 51 Sediment under algae C:N molar ratio 0.576 51 13 C of exposed sediment vs Diatom indicat or: % low P individuals 0.613 37 Dissolved oxygen (2006) 0.607 36 Algal N:P molar ratio 0.475 43 Total P in spring water (2006) 0.499 42 Diatom indicator: Florida Springs TP Index 0.541 51 Diatom indicator: Strontium 0.550 34 Ortho phosphat e in spring water (2006) 0.564 41 Total P in spring water (2003+2006) 0.572 33 Average of buffer width 0.621 39 Diatom indicator: Sulfate 0.699 51 Conductivity (2003 + 2006) 0.754 37

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105 -50 -45 -40 -35 -30 -25 -20 -15 -10 -5 -10 -5 0 5 10 15 15N 13C Sediment under algae Exposed sediment Macroalgae Figure 4 1. Stable isotope composition of algae and se diment from 63 spring sites sampled in 2006.

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106 0 10 20 30 40 50 60 70 80 90 100 110 120 -50 -45 -40 -35 -30 -25 -20 -15 -10 13C C:N Sediment under algae Exposed sediment Macroalgae Figure 4 13C and C:N molar ratio of algae and sediment from 63 spring sites sampled in 2006.

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107 -50 -45 -40 -35 -30 -25 -20 -15 -10 -5 -10 -8 -6 -4 -2 0 2 4 6 8 10 15N 13C Lyngbya wollei Vaucheria sp. Spyrogyra sp. Figure 4 3. Stable isotope composition of Lyngbya wollei Vaucheria sp and Spirogyra sp. from 61 spring sites, 2006.

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108 R2 = 0.40 R2 = 0.48 R2 = 0.41 6.0 6.5 7.0 7.5 8.0 8.5 9.0 -50 -45 -40 -35 -30 -25 -20 -15 -10 13C pH Lyngbya wollei Vaucheria sp. Spyrogyra sp. Linear (Lyngbya Linear (Vaucher Linear (Spyrogy Figure 4 13C of the three dominant algal species and spring water pH at boil areas sampled in 2006. Each trend line is f or a particular species: Vaucheria sp. r2 = 0.48, L yngbya wollei r2 = 0.40 and Spirogyra sp. r2 = 0.41.

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109 -55 -50 -45 -40 -35 -30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30 35 40 45 50 55 60 Total DIC (mg C L-1) Algae 13C Lyngbya wollei Vaucheria sp. Spyrogyra sp. Other spp. -50 -45 -40 -35 -30 -25 -20 -15 -10 -5 -13 -12 -11 -10 -9 -8 -7 -6 -5 13C DIC Algae 13C Lyngbya wollei Vaucheria sp. Spyrogyra sp. Other sp. -55 -45 -35 -25 -15 -5 5 7.4 7.6 7.8 8.0 8.2 8.4 8.6 8.8 pH 13C Lyngbya wollei Vaucheria sp. Spyrogyra sp. Other sp. A B C Figure 4 1313C of DIC and pH of headwater springs sampled in April and August 2008. A) total DIC (mg C L1) 13C of algae (r2 = 0. 70). 13C of DIC 13C of algae (r2 = 0.50) C) pH 13C of algae (r2 = 0.76)

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110 Figure 4 6. Relationships between spring water total DIC (mg C L113C of DIC and pH of headwater springs sampled in April an d August 2008. 13C of DIC vs. total DIC (mg C L1) (r2 = 0.52). B) 13C of DIC vs. pH (r2 = 0.34). C) T otal DIC vs. pH (r2 = 0.81) 7.4 7.6 7.8 8 8.2 8.4 8.6 8.8 -13 -12 -11 -10 -9 -8 -7 -6 -5 13C DIC pH 7.4 7.6 7.8 8 8.2 8.4 8.6 8.8 0 5 10 15 20 25 30 35 40 45 50 55 Total DIC (mg C L-1) pH 0 5 10 15 20 25 30 35 40 45 50 55 60 -13 -12 -11 -10 -9 -8 -7 -6 -5 13C DIC Total DIC (mg C L-1) A B C 7.4 7.6 7.8 8 8.2 8.4 8.6 8.8 -13 -12 -11 -10 -9 -8 -7 -6 -5 13C DIC pH 7.4 7.6 7.8 8 8.2 8.4 8.6 8.8 0 5 10 15 20 25 30 35 40 45 50 55 Total DIC (mg C L-1) pH 0 5 10 15 20 25 30 35 40 45 50 55 60 -13 -12 -11 -10 -9 -8 -7 -6 -5 13C DIC Total DIC (mg C L-1) 7.4 7.6 7.8 8 8.2 8.4 8.6 8.8 -13 -12 -11 -10 -9 -8 -7 -6 -5 13C DIC pH 7.4 7.6 7.8 8 8.2 8.4 8.6 8.8 0 5 10 15 20 25 30 35 40 45 50 55 Total DIC (mg C L-1) pH 0 5 10 15 20 25 30 35 40 45 50 55 60 -13 -12 -11 -10 -9 -8 -7 -6 -5 13C DIC Total DIC (mg C L-1) A B C

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111 50 45 40 35 30 25 20 15 10 0 1 2 3 4 5 6 7 8 9 10 13 C Distance from boil (km) Lyngbya wollei Dicotomosiphon sp. Spirogyra sp. Hydrodicton sp. Cladophora glomerata Aphanothece sp. balls Caloglossa sp. Vaucheria sp. Enteromorpha sp. Compsopogon sp. Sediment under algae Exposed sediment 50 45 40 35 30 25 20 0 1 2 3 4 5 6 7 8 9 10 11 13 C Distance from boil (km) 45 40 35 30 25 20 0 1 2 3 4 5 6 7 8 13 C Distance from boil (km) 40 38 36 34 32 30 28 26 24 22 20 0 1 2 3 4 5 6 7 8 9 13 C Distance from boil (km) Figure 4 13C composition of algae and sediment measured along four spring river runs in January 2006. A) Rainbow River. B) Weeki Wachee River. C) Wakulla River. D) Silver River

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112 -48 -46 -44 -42 -40 -38 -36 -34 April-05 May-05 July-05 September-05 October-05 December-05 February-06 March-06 May-06 Date 13C Vaucheria sp. -46 -44 -42 -40 -38 -36 -34 -32 -30 May-05 July-05 September-05 October-05 December-05 February-06 March-06 May-06 Sampling Date 13C Lyngbya wollei Vaucheria sp. Figure 4 13C composition of algae at Manatee Springs and Ichetucknee Blue Hole from May 2005 to March 2006. 13C of Vaucheria sp. at Manatee Springs. B) 13C of Lyngbya wollei and Vaucheria sp. at Ichetucknee Blue Hole. A B

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113 CHAPTER 5 NUTRIENT PROFILES OF ALGAL MATS IN FLORIDA SPRINGS Introduction The filamentous algae Lyngbya wollei and Vaucheria sp. form thick benthic mats in many of Floridas karst springs (Stevenson et al ., 20 07). Despite the high biomass accrual of algae that has occurred over the past 50 years (Florida Springs Task Force, 2000; Quinlan et al 2008), relatively little is known about the physiology of benthic and floating algal mats and factors that allow such thick mats to occur in many springs with relatively low ambient nutrient concentrations. Spring nutrient supply rates alone do not control the distribution of algae in Florida springs (Pinowska et al ., 2009). At Silver Glen Springs, for example, persisten t Lyngbya wollei mats more than 1 m thick occur under ambient NOx concentrations of 0.05 mg L1 and orthophosphate of 0.03 mg L1. One possible explanation may be that the algae are relying at least in part on the regeneration of nutrients within the mat i tself as it grows in size and inner portions begin to senesce due to lack of light and/or nutrients. Benthic efflux of nutrients or nutrient regeneration within mats has been shown to supply algae with nutrients necessary for growth, rather than having to rely solely on direct supply from the water column (Sndback et al. 2003; Trimmer et al ., 2000; Tyler, McGlathey & Anderson, 2003; McGlathery et al 1997). Lyngbya sp. mats have been observed to attain high biomass densities, and this may allow for nutrie nt entrainment and recycling within mats Beer, Spencer & Bowes (1986) calculated fresh weight densities of up to 13.8 kg/m2 (equivalent to 1.14 kg dry weight (DW)) for L. birgei in the Southeastern U.S. and Cowell (1990) recorded biomass densities of 1.25 kg DW/ m2 for L. wollei in Kings Bay, FL. The major objective of my study was to determine the potential for large algal mats to regenerate nutrients to sustain algal growth. Specific objectives of this study were to 1)

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114 characterize nutrient profiles o f large Lyngbya wollei and Vaucheria sp. mats, the two most common species of algae found in Florida Springs and 2) estimate advective and diffusive movement of dissolved nutrients out of large algal mats To accomplish this, I analyzed mat internal dissol ved nutrients using interstitial water samplers known as multisamplers at Weeki Wachee, Manatee and Silver Glen Springs during spring and summer 2006. I also analyzed the isotopic composition of algal tissue and underlying sediment ( 1513C) and measured NaCl movement out of algal mats. Methods Sampling Locations Nutrient profiles within algal mats as well as advective flow through mats were measured in the boil areas of Manatee, Weeki Wachee and Silver Glen Springs (Figure 5 1 ). These sites were chosen because Weeki Wachee had the thickest Lyngbya wollei mats and Manatee Springs the thickest Vaucheria sp. mats observed during surveys conducted in January 2006. Silver Glen was added as a comparison site to Weeki Wachee because i t also has thick L. wollei mats, but the water chemistry varied between the two locations. Algal M at Nutrient Profiles Interstitial water samplers, or multisamplers (Martin et al ., 2003), were used to assess nutrient profiles within algal mats. Samplers w ere deployed twice at Weeki Wachee and Manatee Springs (April and August 2006) and once at Silver Glen Springs (September 2006). Sampling was conducted at different times of the year in order to observe nutrient profiles during different stages of algal gr owth cycles and environmental conditions. Duplicate samplers were deployed at each site, near the boil area, where the algal mats were thickest. They were generally 2 to 3 meters apart.

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115 The samplers used in my study were an adaptation of the sediment sampl er of Martin et al ., (2003) and consisted of a 1.5 -m tall PVC pipe with small holes drilled every 10 cm (Figure 5 2). Tygon tubing (0.25 inch ID) was glued to the inner surface of each hole (inside the multisampler) and run through its entire length. Two l ayers of 500m nylon screen were glued to the outside of each hole in the form of a blister to help filter particulates and keep the tube from being blocked. The multisamplers were inserted vertically through the thickest part of the algal mat and pushed to a depth of approximately 10 20 cm into the sediment. They were left in place for one week to allow for equilibration. Water samples were drawn from each tube using a syringe while sitting in a canoe. To purge stagnant water from the tubing, one tube vo lume of water was withdrawn from each tube (15 30 ml, depending on the length of each tube) and discarded before water samples were collected. The multisampler allowed samples to be drawn from the sediments upwards through algal mats and into spring waters above the mats, all in a vertical column. Parameters measured from samples collected at each depth in the multisampler were: TKN, TP, SRP, NO3, DOC and trace metals for all sampling dates and sites. NH4, was measured only during the April 2006 sampling ev ent at Manatee and Weeki Wachee Springs. Additionally, algae and sediment samples were taken from the algae/sediment interface, in the upper (surfac e) portion of the mat as well as in the deeper portions to be analyzed for % C, N and P as well as 1315N isotope analysis. Chemical Sampling and Laboratory Analyses Water samples were filtered through a 0.45 m polycarbonate membrane using a filter holder and syringe. Filtered aliquots were collected for soluble reactive phosphorus (SRP), dissolved organic carbon (DOC), NH4 +, and NO3 -. Unfiltered samples were collected

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116 concurrently for total Kjeldahl nitrogen (TKN) and total phosphorus (TP). Samples for TKN, TP, dissolved organic carbon (DOC) and NH4 +, NO3 were acidified to pH 2 with concentrated H2SO4. All samples were transported on ice and stored at 4C until analyzed except for SRP samples, which were stored frozen. Holding times were 28 days for NO3 -, SRP, DOC, TKN and TP, and NH4 +. Soluble reactive phosphorus, NH4 +, and NO3 -, were measured on a flow -injection analyzer using EPA methods (EPA Methods 365.1, 350.1 and 353.2 respectively). Total Kjeldahl nitrogen was determined by H2SO4 and Kjeldah l salt digestion and flow -injection determination of ammonium (EPA Method 351.2). Total nitrogen (TN) was computed as the sum of TKN plus NO3 -. Total phosphorus was measured as SRP on a Technicon Autoanalyzer after digestion with H2SO4 and potassium persul fate (EPA Method 365.1). Carbon and nitrogen content of lyophilized algal tissues were determined on a Thermo Flash EA 1112. Phosphorus content of dried algal tissues was measured on combusted (550C) and acid digested (6N HCl) samples as SRP on the Techni con Autoanalyzer (Anderson, 1976). 13C isotopic analysis, sediment samples were acid fumigated with HCl to remove 15N analysis did not undergo acid fumigation. Carbon and nitrogen stable isotopic composition of alga e and sediments was measured on a Thermo Finnigan Delta Plus XP isotope ratio mass spectrometer (Thermo Fisher Scientific, Inc., Waltham, MA, U.S.A.) at the University of Florida using an elemental analyzer inlet system and continuous flow of He. The Inter national Atomic Energy Association standards 13 relative to international standards (Vienna Pee Dee Belemnite for C and atmospheric air for N).

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117 Nutrient Diffusio n Out of Algal Mats Ammonium and phosphate diffusion out of algal mats was calculated using the nutrient profiles obtained with the multisamplers in April 2006. One profile from Weeki Wachee Springs (Lyngbya wollei ) and one profile from Manatee Springs ( Va ucheria sp.) were used. Diffusive flux was calculated using Ficks Law: (5 1) Where: J = flux; mass diffusing across unit area per unit time (i.e., mg/m2/day) D = Diffusion coefficient (ie. 106 cm2/sec) dC = change in concentration (mg/ L) dX = d istance between the changes in concentration that are being considered (cm) The diffusion coefficients used were the following (Li & Gregory, 1974): (1) NH4+ : 16.8 x 106 cm2/sec at 18C and 19.8 x 106 cm2/sec at 25C (2) H2PO4: 7.15 x 106 cm2/sec at 18C and 8.46 x 106 cm2/sec at 25C Flux was calculated using two different estimates of algal mat porosity to obtain a range of values: 0.5 and 0.8. Porosities of 0.63 to 0.86 were calculated for shallow, muddy estuarine sediment in Florida Bay from depths of 20 cm to 0 (sediment/water column interface), respectively(Ullman & Aller, 1982). Porosities of 0.5 are typical of an uncompacted soil of medium to fine texture (Brady & Weil, 2002) and I assumed that 50% of the algal mat, by volume, was algae a nd 50% was extracellular water. NO3 flux was not calculated because there were only trace concentrations within the algal mat. Algal M at Tracer Study In order to estimate advective movement of water and nutrients into and out of thick algal mats, a tracer study was conducted in August 2006 at Weeki Wachee, Manatee and Silver Glen springs using multisamplers. Two liters of NaCl tracer solution were injected along the edge of

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118 replicate multisamplers facing the boil (i.e., what I interpreted to be the upstrea m side of the sampler). To inject the tracers I used a 2 -meter long rod onto which a length of 0.25 in Tygon tubing was attached. Tracer was forced into the tubing at a consistent rate while the end of the tubing was moved up and down along the entire len gth of the installed multisamplers. In the case of Manatee spring, tracer was also injected in the water column above the mat. Water column injection was done because the experiment had to be conducted in a backwater area in the spring owing to a lack of a lgal mats in swifter flowing portions of the spring. A different syringe was then used to draw a sample of water from each sampler port within the mat. Samples were collected at the following times: 5 minutes, 15 minutes, 30 minutes and 60 minutes after in jection. The samples were then analyzed using a conductivity meter to quantify NaCl tracer. Results Interstitial Nutrient Profiles in Large Algal Mats Multisampler deployments were conducted in both Vaucheria and Lyngbya mats at Weeki Wachee, Manatee and Silver Glen springs, however, due to natural variations in algal growth patterns, my observations in Vaucheria mats (Manatee spring) are limited to senescing rather that actively growing algae (Table 5 1). I observed complex patterns and strong gradients o f algal nutrients within all algal mats at all three springs (Figures 5 3 to 57). Even on the same day, there could be substantial variability in nutrient profiles between the two replicate multisamplers. Therefore, in this section I will describe the broad patterns of nutrient concentrations observed on each date rather than try to describe and interpret every observable variation. Manatee Springs Nutrient concentrations and gradients in Vaucheria mats at Manatee were the highest of the three springs studied; this may be related to the fact that the mat was senescing. TKN and TP concentrations increased by 2 3 orders of magnitude from the overlying water column moving

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119 into the mat interior. Peak TKN values were found within algal mats and were 18 to 28 mg L1 on April 19, 2006 and 6 to 9 mg L1 on August 24, 2006 (Figures 5 3 and 5 -4). The mats studied in April 2006 were 6080 cm deep, while those studied in August were thinner, 2050 cm, which may account for the lower TKN and TP values observed in August deployments. There were abrupt changes in nitrate (decreasing), ammonium (increasing) and Fe (increasing) within the mat, suggesting low redox conditions, however, the depth of the oxic anoxic transition was near the bottom of the algal mat rather than nea r the surface. Within the sediment, TKN and ammonium concentrations declined slightly. TP concentrations followed the same general pattern as TKN, however peak concentrations (0.7 to 3.8 mg L1) were observed within the sediments rather than the bottom of the algal mat. Based on the difference between SRP and TP, the vast majority of the TP observed in mat interstitial waters and sediments was organic P; for TKN, the majority was contributed by organic N, however, there was still a substantial amount of ino rganic N in the form of ammonium. One of the most noteworthy observations from the multisampler deployments at Manatee was the extremely high Fe concentrations observed within the senescing algal mat. Concentration peaks were 38 to 50 mg L1 in April 2006 and 5.8 to 8.1 mg L1 in August 2006, and on both dates Fe concentrations were greater than TKN levels on a weight:weight basis. The concentration of Fe generally peaked at the very bottom of the mat and then declined slightly within the surficial sediment s. Weeki Wachee At Weeki Wachee on both deployment dates, TKN and TP values within the Lyngbya mats varied by 1 2 orders of magnitude over the multisampler profile which encompassed the water column, algal mat and about 2030 cm of sediment material (Figu res 5 5 and 5 6). Peak TKN values were found within the algal mat and ranged between 2 to 4.5 mg L1 with the majority of N contributed by ammonium and organic nitrogen. At a point 10 30 cm within the algal mat

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120 (measured from the surface), there were stron g gradients in both nitrate (decreasing) and ammonium (increasing), suggesting that this was a zone of rapidly declining dissolved oxygen, as was observed in the Manatee profiles. Increasing Fe concentration within this same region reinforces the inference for anoxic conditions. Concentrations of TKN and ammonium (measured in April only) declined below the sediment algal interface. Profiles of TP and SRP were generally similar to patterns for TKN, however the gradients of P were more modest; peak TP levels were ca. 0.2 to 0.4 mg L1 with the majority contributed by organic P. Silver Glen Multisampler deployments in Lyngbya mats at Silver Glen were conducted only on September 5, 2006. The replicate mats ranged in thickness from about 30 to 70 cm. Concentrati ons and gradients of nutrient were highest in the thicker algal mat (Figure 5 7). Peak TKN and TP were generally found near the bottom of the algal mats and values ranged from 5.5 to 39 mgN L 1 and 0.46 to 10.4 mg-P L 1 for the two replicate samplers, res pectively. While ammonium was not measured during the multisampler deployments, I observed no strong gradients in nitrate concentrations, which suggests that redox levels were higher than those required for nitrate reduction within the mats. For both TKN a nd TP the majority of N and P were contributed by organic N and P. Stable Isotope Composition and C:N:P Ratios in Algal Mat Profiles 1315N of algal tissue and sediment) as well as C:N:P molar tissue ratios and interstitia l water chemistry for the algal mat profiles at Weeki Wachee, Silver Glen and Manatee Springs are shown in Table 5 2. The isotopic composition of the Weeki Wachee Springs Lyngbya wollei profile are shown in Figure 5 13C values of algae ranged from 21 to 13C was in the middle of the algal mat, at a depth of 70 cm in the multisampler, and the lowest values were found in the sediment/algal mixture (depths

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121 15N was found in the mixture of Lyngbya/sediment (+4 ) and the lowest values were toward the top of the mat, but not at its surface (+1 ). The isotopic composition of the Silver Glen Springs Lyngbya wollei profile is shown in Figure 5 13C of the algae s howed very little variation through the profile, ranging from 20 to 17 The sediment sample was the least enriched and had a value of 29 15N values of the algal profile ranged from 0 to 3 with decreasing value moving upwards through the alg 15N value for the sediment was lower, at 4 A profile of the algal mat was not shown for Manatee Springs because of the small sample 1315N, and only two algal tissue samples from August 2006 were analyzed). Very little phosphorus was found in the decomposing Lyngbya/sediment samples taken at Weeki Wachee Springs, as is evident by the high N:P and C:P ratios (72 and 1052, respectively (Table 5 2). For the algal samples, C:N, N:P and C:P ratios all decreased moving from the lower (deeper) portions of the mat towards the surface. The C:N ratio of the sample taken at the top of the mat (multisampler depth 130 cm) is close to what would be expected from the Redfield Ratio (C:N:P of 106:16:1). The N:P and C:P ratios show strong phosphorus limitation. The C:N ratios at Silver Glen Springs did not vary widely throughout the profile, ranging from 7 to 8 (Table 5 2). The N:P and C:P ratios of the sediment were ve ry low, 2 and 15, respectively. Algal tissue showed strong P -limitation throughout the profile except for the sample taken at the depth corresponding to 30 cm in the multisampler. The two sediment samples taken at Manatee Springs in April 2006 had very dif ferent molar ratios for N:P and C:P (Table 5 2). Algal tissue molar ratios for samples taken in August 2006 did not vary from each other.

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122 Diffusive Flux out of Algal Mats At both Weeki Wachee and Manatee Springs, there was diffusive flux of NH4 out of the algal mat and down into the sediments as well as into the overlying water column (Table 5 4), with the highest flux out of the Vaucheria mat and into the water column (5 to 9.5 mg/m2/day depending on the porosity of the algal mat) Flux of PO4 was much lo wer. The highest flux was out of the Lyngbya wollei mat at Weeki Wachee, 0.03 to 0.05 mg/m2/day, depending on porosity of the mat. NaCl T racer Experiments in Large Algal Mats Salt tracer concentration was measured in units of S cm1 (i.e., conductivity un its) and corrected for background conductivity of spring water. Concentrations measured at each of the multisampler ports took from 15 to 30 minutes to reach peak levels before they began to slowly decline. The rate of decrease of NaCl tracer expressed as the amount of change (percent) since the peak concentration was reached, was computed for each multisampler port and plotted against port elevation above the bottom (Figure 5 10). Tracer decrease is likely proportional to the rate of advective water movement through the mat and my observations suggest that it varied as a function of the distance of the multisampler port above the spring bottom (Figure 510). Average advective flow through the mat at Weeki Wachee was at least 10x greater than at Silver Glen with Manatee flows falling in between. Advective flow was generally greatest at the top of the mat, followed by the bottom of the mat; flow within the middle of the mats was lowest. Higher apparent advective flow at the bottom of the mats could be indica tive of vertical water movement out of sandy bottom sediments or binding of Na+ and Clions to exchange sites in the sediments. The two sampling points at Manatee spring that are denoted with an are locations above the algal mat (all of the other sample s are within the mat). As previously noted, the Manatee mat

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123 used to install the multisamplers was in a zone of very low water velocity. Interestingly, the rate of tracer decline at these two points is less than that measured within the Weeki Wachee mat and only slightly greater than the rate within the interior of the Manatee mat. While it is difficult to translate the tracer data into actual water velocities, I made a first approximation of rates of water movement by making assumptions about the distributi on of tracer around the multisampler and by treating the algal mat as a porous medium, like soil. I assumed that the tracer was evenly mixed within a rectangular column of water with dimensions of 0.5 m long, 0.5 m wide and with a height equal to the thick ness of the algal mat (in meters). Next, I assumed that water moved through this control volume, in a horizontal direction only through the upstream face of the control volume; this face had an area of 0.5 m x the mat thickness (height). Next I computed th e average fractional rate of decrease of tracer within the control volume per second and multiplied this rate by the total volume of the control volume the product is the volume of water exchanged in the control volume per second. Finally I divided the v olume of water exchanged per second by the cross -sectional area of control volume (0.5 m x the mat thickness) this quotient is analogous to specific discharge through a porous medium such as soil (i.e., units = m s1). Mean values for specific discharge through the mats ranged from 4.0 x 108 m s1 at Silver Glen to 9.0 x 107 m s1 at Weeki Wachee (Table 5 10). Maximum rates determined for regions near the top of the mats were about 2x greater than the mean values shown in Table 5 10. For comparison, hy draulic conductivity through silty sand ranges from ca. 103 to 107 m s1. Discussion Elemental analysis of interstitial waters demonstrated that large Vaucheria and Lyngbya mats within these springs contain biologically significant quantities of N and and potentially

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124 bioavailable dissolved organic phosphorus that could supply actively growing algae. High dissolved nutrient levels could mean that algal nutrient demand is less than the rate of nutrient production within the mat. In other stream systems of N orth America, nutrient levels in algal mats (thinner mats) reach very low levels owing to uptake by algae (R. Jan Stevenson, unpublished data). But, nutrient exchange between the inner parts of the mat and the upper, actively growing layers could be transp ort limited and driven primarily by diffusion rather that advective water fluxes. Middle portions of the mat exhibited the highest nutrient concentrations and lowest advective flow. Additionally, N:P ratios of Lyngbya wollei tissue at both Silver Glen and Weeki Wachee Springs indicate phosphorus limitation, and therefore much of the organic phosphorus in interstitial waters may not be available to this species. Vaucheria sp. mat tissue concentrations did not indicate P limitation. Despite high nutrient conc entrations in interstitial water, Sickman et al. (2009) showed that the total mass of C, N and P contained within these same algal mats (both in algal biomass and interstitial waters) represents only a few hours of flux of organic C, N (predominantly NO3 -) and P from the spring boils. While C, N and P mass in the mats was high on an areal basis, the volume of groundwater flow from the boils may result in a greater potential rate of external nutrient delivery to actively growing algae on the surface of the m ats (Sickman et al ., 2009). L. wollei mats are persistent at Weeki Wachee and Silver Glen Springs, while Vaucheria sp. mats at Manatee Springs undergo sloughing and almost completely disappear at certain times of the year, although not at regular interval s (A. Albertin, personal observation). Higgins, Hecky & Guilford (2008) found that in thick Cladophora glomerata mats (a green algae) of Lake Erie, sloughing occurred at both nutrient -depleted and nutrient -enriched sites and they hypothesized that self -sha ding, once the algal mats attained a certain size and density, was responsible. This

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125 may be occurring at Manatee Springs. Additionally, seasonal flooding of the Suwanee River, which is located approximately 300 m from the boil, caused incursions of tannins into the spring run, which attenuated light in portions of the run. After flooding events, algal die -off was observed. Self -shading may not be as much of a problem in Lyngbya wollei mats because this species can absorb light across the entire visible spec trum due to the presence of phycobilins, chlorophyll a and carotenoid pigments (Speziale et al ., 1991). Speziale et al (1991) found that maximum photosynthesis occurred within the subsurface layers of L. wollei mats in the southeastern U.S. and that surfa ce layers of floating mats were photoinhibited at high irrandiances. While my study discovered potential sources of nutrients to large algal mats in Florida springs, I was unable to definitively determine the primary source of N and P to actively growing L yngbya and Vaucheria mats. The strongest evidence for internal nutrient cycling is simply the fact that high nutrient levels exist in the mats as compared to other locations where algae completely draw down internal nutrient sources and are reliant on exte rnal nutrient supplies. From a mass balance perspective, external nutrient supply from groundwater is much larger than the standing stock of dissolved nutrients within the mats (Sickman et al 2009). However, this mass balance approach is static and does n ot take into consideration the turnover time of nutrients within the mat. More information is needed to definitively determine whether, and to what degree, actively growing algae are using internally regenerated N and P. Dissolved oxygen measurements and m etal speciation analysis within the mats and underlying sediments would allow for better understanding of biogeochemical processes taking place within large mats. Diurnal variations in nutrient uptake within mats need also be considered. In future studies, isotopic tracers (e.g., 15N -labelled ammonium and nitrate or 32P labeled phosphate) could be

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126 released within large mats and used to quantify potential rates of internal nutrient uptake. Finally, at sites like Weeki Wachee and Silver Glen Springs, where t hick mats persist for months to years without completely dying back, I hypothesize that large and diverse populations of heterotrophic microbes may make up a significant portion of the biomass in these mats. To my knowledge, there have been few or no stud ies of microbial ecology or biogeochemistry in algal mats of Florida springs. Taken together, these proposed studies could provide insights into rates of decomposition and internal nutrient loading and be used in modeling simulations of algal mats.

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127 Tabl e 5 1. Dates of multisampler deployment, and the make up and condition of algal mats in three Florida springs. Site/Date Dominant Algal Species Condition of Mat on Surface Weeki Wachee 4 19 2006 Lyngbya wollei Growing 8 23 2006 Lyngbya wollei Growing Manatee 4 19 2006 Vaucheria spp. Senescing 8 24 2006 Vaucheria spp. Senescing Silver Glen 9 5 2006 Lyngbya wollei Growing

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128 Table 5 files and water chemistry of three algal mats found in Florida Springs, 2006. Multisampler depth is in cm and water chemistry concentrations are in mg/L. Water Chemistry Sampling Date Spring Multi sampler No. Depth in Sampler Sample typ e 15N 13C C:N N:P C:P NOx TKN TP SRP 8/23/2006 Weeki Wachee 1 10 Lyngbya/ Sediment 4 32 15 72 1052 0.013 0.526 0.061 0.007 8/23/2006 1 50 Sediment 4 33 16 65 1030 0.011 1.500 0.081 0.011 8/23/2006 1 70 Lyngbya 2 21 13 73 971 0.012 1.616 0.090 0 .015 8/23/2006 1 90 Lyngbya 1 25 12 70 819 0.012 3.278 0.296 0.046 8/23/2006 1 110 Lyngbya 1 26 12 61 719 0.013 1.238 0.127 0.019 8/23/2006 1 130 Lyngbya 3 31 8 39 318 0.072 0.220 0.010 0.001 9/5/2006 Silver Glen 2 20 Lyngbya/ Sediment 4 29 8 2 15 0.042 23.735 4.848 0.869 9/5/2006 2 30 Lyngbya 3 20 8 34 267 0.046 39.501 10.442 0.882 9/5/2006 2 40 Lyngbya 2 17 8 18 156 0.027 13.972 2.473 0.381 9/5/2006 2 60 Lyngbya 2 20 7 38 272 0.022 0.088 0.028 0.004 9/5/2006 2 90 Lyngbya 0 17 8 39 308 0.021 0.074 0.026 0.003 4/19/2006 Manate e 1 10 Vaucheria/ Sediment 5 32 22 30 651 0.009 8.311 3.534 0.233 4/19/2006 2 10 Vaucheria/ Sediment 2 32 20 2 38 0.020 28.295 3.845 0.004 8/24/2006 1 30 Vaucheria 1 22 10 13 132 0.162 0.598 0.053 0.003 8/24/2006 1 40 Vaucheria 5 26 10 12 126 0.177 0.191 0.030 0.003

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129 Table 5 3. Specific discharges through algal mats at three springs. Spring Specific Discharge (m s 1 ) Weeki Wachee 9.0 x 10 7 Manatee 3.7 x 10 7 Silver Glen 4.0 x 10 8

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130 Table 5 4. Diffusion flux out of a large Lyngbya wollei mat (Weeki Wachee Springs) and out of a large, senescing Vaucheria sp. mat (Manatee Springs) in April 2006. Flux is calculated for two temperatures (18C and 25C) and for two porosities (0.5 and 0.8). Negat ive flux indicates diffusion from the mat to the sediment and positive flux indicates diffusion upwards to the water column. MS= multisampler number and it refers to profiles shown in Figures 5 3 (Manatee) and 5 5 (Weeki Wachee). Depth in MS refers to dist ance from the bottom of the multisampler). Site MS Profile Nutrient Diffuison coefficient 18C 10-6cm2 /sec Diffuison Coefficient 18C 10-6cm2/sec Start (Depth in MS) End (Depth in MS) Total di stance (cm) Concentration gradient (ug/cm3 or mg/L) Porosity= 0.5 Porosity = 0.8 Flux at 18C mg/m2/day Flux at 25C mg/m2/day Flux at 18C mg/m2/day Flux at 25C mg/m2/day Weeki Wachee 1 NH4 + 16.8 19.8 10 60 50 2.83 0.41 0.48 0.66 0.77 W eeki Wachee 1 NH4 + 16.8 19.8 60 90 30 3.46 0.84 0.99 1.34 1.58 Weeki Wachee 1 PO4 7.15 8.46 10 60 50 0.23 0.01 0.02 0.02 0.03 Weeki Wachee 1 PO4 7.15 8.46 60 90 30 0.27 0.03 0.03 0.04 0.05 Manatee 2 NH4 + 16.8 19.8 10 20 10 3.53 2.57 3.02 4.10 4.84 Manatee 2 NH4 + 16.8 19.8 20 60 40 27.94 5.07 5.97 8.11 9.56 Manatee 2 PO4 7.15 8.46 10 60 50 0.01 0.00 0.00 0.00 0.00

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131 Figure 5 1. Location of multisampler deployments and investigations of nutrient profiles and movement within algal mats. Map made by Martin Anderson.

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132 Figure 5 2. Multisampler device used to collect water column, algal mat and sediment interstitial waters. Sedi ment Algal Mat Water Column Each plastic tube corresponds to a distinct depth within the multisampler The end of a plastic tube covered by 500 micron screen

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133 20 0 20 40 60 80 100 120 140 0 00 0 01 0 10 1 00 10 00 Position Above Sediment Water Interface (cm) mg/L Fe TKN NH4 NO3 Sediment Algae Water Column 20 0 20 40 60 80 100 120 140 0 00 0 01 0.10 1.00 10 00 Position Above Sediment Water Interface (cm) mg/L TP SRP Sediment Algae Water Column Replicate 1 Replicate 2 20 0 20 40 60 80 100 120 140 0.00 0.01 0 10 1 00 10 00 Position Above Sediment Water Interface (cm) mg/L Fe TKN NH 4 NO 3 Sediment Algae Water Column 20 0 20 40 60 80 100 120 140 0 00 0 01 0 10 1 00 10 00 Position Above Sediment Water Interface (cm) mg/L TP SRP Sediment Algae Water Column Figure 5 3. Chemical profiles measured by multisamplers at Manatee Springs on April 19, 2006. At each spring, two replicate samplers were simultaneously installed. Approximate position of sediment, algae and water column are indicated along the right side of each figure. T he x axes are logarithmic.

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134 20 10 0 10 20 30 40 50 60 0 00 0 01 0 10 1 00 10 00 Position Above Sediment Water Interface (cm) mg/L Fe TKN NO 3 Sediment Algae Water Column 20 10 0 10 20 30 40 50 60 0 00 0 01 0 10 1 00 10 00 Position Above Sediment Water Interface (cm) mg/L TP SRP Sediment Algae Water Column Replicate 1 Replicate 2 20 0 20 40 60 80 100 120 0 00 0 01 0 10 1 00 10 00 Position Above Sediment Water Interface (cm) mg/L Fe TKN NO 3 Sediment Algae Water Column 20 0 20 40 60 80 100 120 0 00 0 01 0 10 1 00 10 00 Position Above Sediment Water Interface (cm) mg/L TP SRP Sediment Algae Water Column Figure 5 4. Chemical profiles measured by multisamplers at Manatee Springs on August 24, 2006. At each spring, two replicate samplers were simultaneously installed. Approximate position of sediment, algae and water column are indicated along the right side of each figure. The xaxes are logarithmic.

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135 40 20 0 20 40 60 80 100 120 0 00 0 01 0 10 1 00 10 00 Position Above Sediment Water Interface (cm) mg/L Fe TKN NH 4 NO 3 Sediment Algae Water 40 20 0 20 40 60 80 100 120 0 00 0 01 0 10 1 00 10 00 Position above sediment water interface (cm) mg/L SRP TP Sediment Algae Water Column Replicate 1 40 20 0 20 40 60 80 100 120 0 00 0 01 0 10 1 00 10 00 Position Above Sediment Water Interface (cm) mg/L Fe TKN NH 4 NO 3 Sediment Algae Water Column 40 20 0 20 40 60 80 100 120 0 00 0 01 0 10 1 00 Position above sediment water interface (cm) mg/L SRP TP Algae Sediment Water Column Replicate 2 Figure 5 5. Chemical profiles measured by multisamplers at Weeki Wachee Springs on April 19, 2006. At each spring, two replicate samplers were simultaneously installed. Approximate position of sediment, algae and water column are indicated along the right side o f each figure. The x axes are logarithmic.

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136 40 20 0 20 40 60 80 100 120 0 00 0 01 0 10 1 00 10 00 Position above sediment water interface (cm) mg/L Fe TKN NO 3 Algae Water Column Sediment 40 20 0 20 40 60 80 100 120 0 00 0 01 0 10 1 00 10 00 Position above sediment water interface (cm) mg/L TP SRP Algae Water Column Sediment Replicate 1 Replicate 2 40 20 0 20 40 60 80 100 120 0 00 0 01 0 10 1 00 10 00 Position above sediment water interface (cm) mg/L Fe TKN NO 3 Algae Water Column Sediment 40 20 0 20 40 60 80 100 120 0 00 0 01 0 10 1 00 10 00 Position above sediment water interface (cm) mg/L TP SRP Algae Water Column Sediment Figure 5 6. Chemical profiles measured by multisamplers at Weeki Wachee on August 23, 2006. At each spring, two replicate samplers were simultaneously installed. Approximate locations of sediment, algae and wate r column are indicated along the right side of each figure. T he x axes are logarithmic.

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137 20 10 0 10 20 30 40 50 60 70 80 90 100 110 0 00 0 01 0.10 1 00 10.00 Position Above Sediment Water Interface (cm) mg/L NO 3 TKN Fe Sediment Algae Water Column 20 10 0 10 20 30 40 50 60 70 80 90 100 110 0 00 0 01 0 10 1 00 10.00 Position Above Sediment Water Interface (cm) mg/L TP SRP Sediment Algae Water Column Replicate 1 Replicate 2 20 10 0 10 20 30 40 50 60 70 80 90 100 110 120 0 00 0 01 0 10 1.00 10 00 Position Above Sediment Water Interface (cm) mg/L NO3 TKN Fe Sediment Algae Water Column 20 10 0 10 20 30 40 50 60 70 80 90 100 110 120 0 00 0 01 0 10 1 00 10 00 Position Above Sediment Water Interface (cm) mg/L TP SRP Sediment Algae Water Column Figure 5 7. Chemical profiles measured by multisamplers at Silver Glen Springs September 5, 2006. At each spring, two replicate samplers were simultaneously installe d. Approximate locations of sediment, algae and water column are indicated along the right side of each figure. T he x axes are logarithmic.

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138 0 20 40 60 80 100 120 140 -35 -30 -25 -20 -15 -10 -5 0 13C Depth in Multisampler Lyngbya spp. Lyngbya/sediment 0 20 40 60 80 100 120 140 0 1 2 3 4 5 15N Depth in Multisampler Lyngbya spp. Lyngbya/sediment Figu re 5 8. Stable isotope profile of algae and sediment surrounding Multisampler 1 at Weeki Wachee Springs, A ugust 23, 2006. 13C vs. the depth in the multisampler (cm). B) 15N vs. the depth in the multisampler (cm). Lyngbya/sediment is so labeled because of the large amount of decomposing algae in the sediment sample.

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139 0 10 20 30 40 50 60 70 80 90 100 -35 -30 -25 -20 -15 -10 -5 0 13C Depth in Multisampler Lyngbya Sediment 0 10 20 30 40 50 60 70 80 90 100 -5 -4 -3 -2 -1 0 1 2 3 15N Depth in Multisampler Lyngbya Sediment Figure 5 9 Stable isotope profile of Lyngbya wollei and sediment surrounding Multisampler 2 at Silver Glen Springs, September 2, 2006. 13C vs. the depth in the multisampler 15N vs. the depth in the multisampler (cm). A B

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140 0 10 20 30 40 50 60 70 80 90 100 0.0% 0.1% 1.0% 10.0% Decrease in Tracer Concentration per Minute Distance From Bottom (cm) Silver Glen Manatee Weeki Wachee above algal mat Figure 5 10. Profiles of tracer dilution at three springs. The rat e of decrease of NaCl tracer (measured in units of conductivity) expressed as percent change from peak concentration are plotted on the xaxis.

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141 CHAPTER 6 CONCLUSION There is no simple cause and effect relationship between nutrient concentrations and alga l abundance in Florida Springs. Results from extensive field surveys conducted throughout North central Florida and the Panhandle indicate that the abundance of Lyngbya wollei one of the most abundant filamentous algae found in springs, was not directly r elated to nitrate or phosphorus concentrations in spring water (Stevenson et al 2007; Pinowska et al. 2009). Multiple factors, both biotic and abiotic, are likely affecting algae in springs. Despite these complex relationships, these studies shed light on factors affecting algal growth. I found that under laboratory conditions, Lyngbya wollei growth is stimulated by additions of nitrogen, even if phosphorus is in very low supply. The stoichiometry of algal tissue at the end of the experiments suggested st rong P -limitation, N:P ratios of up to 57:1 and C:P ratios of up to 630:1. However, growth rates for L.wollei remained positive, indicating that it was never under truly limiting P conditions and implies that the optimal stoichiometric ratio for L. wollei in Florida springs likely deviates from the Redfield ratio benchmark. Higher growth rates were obtained in my experiments at higher nutrient concentrations and therefore, reductions in N concentrations should reduce algal growth rates in spring systems alt hough algal biomass would continue to accumulate. The threshold value for L.wollei growth produced by logistics model, 1 1 are low when compared to nitrate concentrations found in many Flo rida springs, making the task of establishing nutrient criteria in Florida springs difficult. 1518O) indicates that organic nitrogen sources, such as manure or septic waste are likely important sources of N at springs such as Troy, Wekiwa, Volusia, Lafayette and Little River. At springs such as Ichetucknee Head Springs,

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142 Ichetucknee Blue Hole, Rainbow, Jackson and Madison Blue Springs, inorganic N sources, such as NH4 from either fertilizer and/or rain or soil n itrogen are likely important sources. However, I 1518O of nitrate at some springs across multiple years and therefore seasonal sampling is crucial. Additionally, the importance of denitrification in and above the Floridan Aq uifer needs to be established in order to better interpret isotope signatures; the tight correlation between O and N isotopes of nitrate in most springs, might suggest a uniform nitrate source, such as inorganic fertilizers, rather than heavy inputs from organic N sources. 15N signatures were not species -specific and varied across sites despite little 1518O of nitrate in spring water at those same sites. This variability is likely due to environmental and physiological factors affecting fractionat ion during algal uptake of N, which need to be understood in order to better interpret results. In contrast, relatively strong species -13C values were found across spring sites as well as a strong relationship 13C values, pH and total DIC. This relationship likely results from differential use of HCO3 and CO2 13C values. Species -specific tendencies found with total DIC concentrations and pH may be important in determin ing algal distribution in springs and need to be further investigated. Finally, I found that high nutrient concentrations exist within thick Lyngbya wollei and Vaucheria sp. mats, although I was unable to determine whether or not this was a primary source of N and P to actively growing algae. More information, such as dissolved oxygen measurements and studies on the microbial ecology within thick algal mats and in underlying sediments would allow for a better understanding of ongoing biogeochemical processe s.

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143 APPENDIX LOCATIONS OF SAMPLING SITES Spring Spring code Site name Site code Boil Latitude Longitude Alexander ALE Head ALE 01 Yes 29.08128 81.57563 Downstream ALE 02 No 29.08231 81.57754 Chassahowitzka CHA Blue holes CHA 01 Yes 28.71617 82.575 02 Dock CHA 02 Yes 28.71558 82.57630 Brown spring CHA 03 Yes 28.71721 82.57586 Cypress CYP Head CYP 01 Yes 30.65855 85.68430 Fanning FAN Head FAN 01 Yes 29.58757 82.93541 Gainer GAI Pipe GAI 01 Yes 30.42736 85.54827 Side boil GAI 02 Yes 30 .42884 85.54854 Morten Spring GAI 03 Yes 30.42875 85.54649 Guaranto GUR Head GUR 01 Yes 29.77973 82.94001 Ichetucknee ICH Head ICH 01 Yes 29.98408 82.76184 Blue Hole ICH 02 Yes 29.98068 82.75866 Below Blue Hole ICH 03 No 29.98007 82.75895 Mission spring ICH 04 Yes 29.97628 82.75783 Devils Ear ICH 05 Yes 29.97388 82.75996 Mill Pond ICH 06 Yes 29.96658 82.76005 Before bridge ICH 07 No 29.95495 82.78507 Coffee spring ICH 08 Yes 29.95937 82.77526 Indian IND Head IND 01 Yes 30.25077 84.32203 Jackson Blue JAC Head JAC 01 Yes 30.79037 85.13998 Boat ramp JAC 02 No 30.78249 85.16022 Rock cliff JAC 04 Yes 30.79023 85.14290 Juniper JUN Head JUN 01 Yes 29.18365 81.71201 Fern Hammock JUN 02 Yes 29.18364 81.70801 A fter bridge on route 19 JUN 04 No 29.21283 81.65431 Lafayette Blue LAF Head LAF 01 Yes 30.12592 83.22617 Little River LTR Head LTR 01 Yes 29.99642 82.96675 Madison Blue MAD Head MAD 01 Yes 30.48056 83.24439 Manatee MNT Head MNT 01 Yes 29.48952 82. 97692 Pitt PIT Head PIT 01 Yes 30.43288 85.54616 Ponce de Leon PON Head PON 01 Yes 30.72090 85.93071 Rainbow Spring RAI Head RAI 01 Yes 29.10223 82.43741 KP Hole RAI 02 Yes 29.09294 82.42848 Before tubers sign RAI 03 No 29.06305 82.42788 B efore bridge RAI 04 No 29.05223 82.44700 RAI 05 No 29.09275 82.43133 RAI 06 No 29.07650 82.42760 After bridge RAI 07 No 29.05407 82.44717

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144 Spring Spring code Site name Site code Boil Latitude Longitude Silver Glen SGL Head SGL 01 Yes 29.24 603 81.64345 Natural Well SGL 02 Yes 29.24583 81.64385 Trial in the woods SGL 03 Yes 29.24400 81.6463 Silver River SLV Head SLV 01 Yes 29.21619 82.05252 Second pool SLV 02 Yes 29.21584 82.04987 Birds of prey SLV 03 No 29.21561 82.04112 Old swimming area SLV 04 No 29.20500 82.02902 Cabbage palm SLV 05 No 29.20211 82.01127 SLV 07 No 29.20715 81.99660 Troy TRY Head TRY 01 Yes 30.00598 82.99756 Volusia Blue VOL Head VOL 01 Yes 28.94758 81.33969 Downstream from stairs VOL 02 No 28.94679 81.33921 Wakulla WAK Head WAK 01 Yes 30.23533 84.30287 Turnaround WAK 02 No 30.23318 84.28870 Bird colony WAK 03 No 30.22507 84.27470 WAK 04 No 30.23650 84.29831 WAK 05 No 30.23439 84.29505 WAK 06 No 30.22836 84.280 01 Upstream from bridge on 98 WAK08 No 30.18037 84.24817 Washington Blue WGT Head WGT 01 Yes 30.45279 85.53044 WGT 02 Yes Weeki Wachee WEK Head WEK 01 Yes 28.51747 82.57349 Boat dock WEK 02 No 28.51901 82.57361 WMA WEK 03 No 28.52481 82.59583 Roger's Park WEK 04 No 28.53057 82.62407 WEK 05 No 28.51874 82.57739 WEK 06 No 28.52216 82.58459 WEK 07 No 28.51860 82.59268 Wekiwa WKW Head WKW 01 No 28.71193 81.46037 Canoe launch WKW 02 No 28.71269 82.45948 Williford WIL Head WIL 01 Yes 30.43966 85.54763

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156 BIOGRAPHICAL SKETCH Andrea Albertin was born and lived in Costa Rica until she was 7 years old. She and her family, her parents and two sisters, then moved to the United States, Panama, Pakistan and back to the United States again in 1991 after she graduated from high school. She studied biology with an emphasis in b otany at the College of William and Mary in Virginia and then moved ba ck to Costa Rica in 1996 to pursue practical training in tropical plant taxonomy. She returned to the United States in 1999 to study a grofo restry and received a masters degree from the School of Forest Conservation and Resources at the University of Flori da. She subsequently worked in Co sta Rica for three years for the Organization for Tropical Studies. She returned to the University of Florida in 2005 and received her Ph.D. from the Soil and Water Science Department in the summer of 2009. She and her husband, Francisco, have a beautiful baby boy, Matthias.