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Benthic microalge and nutrient flux in Florida Bay, USA

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Title:
Benthic microalge and nutrient flux in Florida Bay, USA
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Book
Language:
English
Creator:
Neely, Merrie Beth
Publisher:
University of South Florida
Place of Publication:
Tampa, Fla
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Subjects

Subjects / Keywords:
Phosphorus
Nitrogen
Chlorophyll
Mesocosm
Microphytobenthos
Dissertations, Academic -- Marine Science -- Doctoral -- USF   ( lcsh )
Genre:
non-fiction   ( marcgt )

Notes

Summary:
ABSTRACT: The objective of this study was to address the relationship between benthic microalgal communities and the phosphate nutrient dynamics of Florida Bay sediments and how they relate to benthic and water column primary production. In situ phosphate (P) flux between the sediment and the water column was measured in three regions of Florida Bay. Differences in the ratio of inorganic to organic phosphate flux were found between the three regions in relation to the amount of phosphate measured in the water column. Based upon the average sediment flux in my study, more than 1600 metric tons of P would be supplied by the sediment per year in Florida Bay. Based upon my measurements, dissolved nutrient flux from the sediment can be an important contribution to pelagic phytoplankton blooms in Florida Bay, accounting for 6.5 - 41% of demand and TDN accounts for 100% of the N demand.My findings were similar to others for both benthic nutrient flux and benthic microalgal chlorophyll a concentration. Benthic microalgae in Florida Bay contribute 700 kg Chl a per day to the system. Mesocosm experiments demonstrated that benthic microalgae and water column phytoplankton can respond differently to changes in nutrient availability. The dissolved nutrient in least supply in the water column does not necessarily correspond to the limiting nutrient for benthic microalgae. ³³P acted as a tracer between sediment and water column dissolved P pools. The presence of benthic microalgae enhanced the transport of ³³P to the water column as compared to simple Fickian diffusion. This was supported by the positive flux of dissolved P from the sediment to the water column pools in control treatments with a living benthic microalgal layer. Primary production by benthic microalgae were measured using dissolved O₂ evolution and PAM fluorometry.Primary production for BMA habitat in Florida Bay was between 400 and 800 tons of C per day, based upon O₂ production and PAM fluorometry, respectively.
Thesis:
Dissertation (Ph.D.)--University of South Florida, 2008.
Bibliography:
Includes bibliographical references.
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Mode of access: World Wide Web.
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System requirements: World Wide Web browser and PDF reader.
Statement of Responsibility:
by Merrie Beth Neely.
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Title from PDF of title page.
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Document formatted into pages; contains 185 pages.
General Note:
Includes vita.

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University of South Florida Library
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University of South Florida
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All applicable rights reserved by the source institution and holding location.
Resource Identifier:
aleph - 002046331
oclc - 495852173
usfldc doi - E14-SFE0002649
usfldc handle - e14.2649
System ID:
SFS0026966:00001


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Benthic Microalgae and Nutrient Flux in Florida Bay, USA by Merrie Beth Neely A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy College of Marine Science University of South Florida Co Major Professor: Gabriel A. Vargo Ph.D. Co Major Professor: Kent A. Fanning Ph.D. Paul R. Carlson, Ph.D. Peter Howd, Ph.D. Karen Steidinger, Ph.D. Laura Yarbro, Ph.D. Date of Approval: November 20, 2008 Keywords: phosphorus, nitrogen, chlorophyll, mesocosm, microphytobenthos Copyright 2008 Merrie Beth Neely

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i Acknowledgements Portions of this project were funded by: USDOC/NOAA Award # NA06OP0519 to Dr. Oceanography Student Grant in Aid to Merrie Beth Neely and Jennifer Jurado. Special thanks go to the Keys Marine Laboratory Staff; Jennifer Jurado, Gary Hitchcock, and Chris Kelble from the University of Miami; Dr. Rob Masserini, USF College of Marine Science; and Bill Sargeant and Dr. Cynthia Heil, Florida Fish and Wildlife Conservation Commission Fish and Wildlife Research Institute ; the Florida Institute of Oceanography SEAKEYS buoy system; Dr. Carmelo Tomas and Dr. Larry Cahoon, University of North Carolina,Wilmington

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ii Table of Contents Li st of Tables ................................ ................................ ................................ .................... vi List of Figures ................................ ................................ ................................ ................. viii Chapter 1. Benthic microalgae and nutrient flux in Florida Bay, USA ...................... 1 Introduction ................................ ................................ ................................ ..................... 1 Florida Bay Ecosystem ................................ ................................ ............................... 2 Benthic Microalgae ................................ ................................ ................................ ..... 4 Benthic Microa lgae and Sediment Resuspension ................................ ....................... 5 Dissertation Objectives ................................ ................................ ............................... 6 Chapter 2. Sediment phosphate flux in Florida Bay, USA. ................................ .......... 7 Introduction ................................ ................................ ................................ ..................... 7 Materials and Method s ................................ ................................ ................................ .... 8 Results and Discussion ................................ ................................ ................................ 12 Nitrogen ................................ ................................ ................................ .................... 44 Summary ................................ ................................ ................................ ....................... 45 Chapter 3. Benthic Microalgal Chlorophyll a Standing Stock in Florida Bay ......... 48 Introduction ................................ ................................ ................................ ................... 48 Benthic Microalgae a nd Sediment Resuspension ................................ ..................... 51 Benthic Microalgal primary productivity and models ................................ .............. 52 Benthic Microalgae in Florida Bay ................................ ................................ ........... 54 Goals and objectives ................................ ................................ ................................ 57 Materials and methods ................................ ................................ ................................ .. 57

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iii Results ................................ ................................ ................................ ........................... 59 Statistical analysis ................................ ................................ ................................ ..... 63 Discussion ................................ ................................ ................................ ..................... 64 Summary ................................ ................................ ................................ ....................... 66 Chapter 4. Mesocosm bi oassays as a tool to investigate microalgal benthic pelagic coupling in Florida Bay ................................ ................................ ..................... 67 Introduction ................................ ................................ ................................ ................... 67 Florida Bay Nutrient Limitation ................................ ................................ ............... 67 Bioassays ................................ ................................ ................................ ................... 70 Materials and methods ................................ ................................ ................................ .. 71 Results ................................ ................................ ................................ ........................... 75 Nutrients: Initial Field Conditions ................................ ................................ ............ 75 Mesocosm results ................................ ................................ ................................ ...... 76 Chlorophyll concentration ................................ ................................ ........................ 98 Discussion ................................ ................................ ................................ ................... 107 Nutrient concentrations ................................ ................................ ........................... 107 Chloroph yll concentration ................................ ................................ ...................... 108 Summary ................................ ................................ ................................ ..................... 112 Chapter 5. Short term response of benthic microalgae to 33 P additions to the sediment. ................................ ................................ ................................ ........................ 114 Introduction ................................ ................................ ................................ ................. 114 Materials and Methods ................................ ................................ ................................ 116 Results ................................ ................................ ................................ ......................... 121 Preliminary experiments ................................ ................................ ......................... 121 Laborato ry experiments ................................ ................................ .......................... 122 Sediment water column P pools ................................ ................................ ............. 126 Discussion ................................ ................................ ................................ ................... 129 Summary ................................ ................................ ................................ ..................... 130

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i v Chapter 6. The use of dissolved oxygen probes and Pulse Amplitude Modulated (PAM) fluorometry in the evaluation of benthic microalgal primary production in Flo rida Bay ................................ ................................ ............. 131 Introduction ................................ ................................ ................................ ................. 131 Oxygen probes ................................ ................................ ................................ ........ 132 PAM fluorometry ................................ ................................ ................................ .... 132 Materials and Me thods ................................ ................................ ................................ 134 Dissolved Oxygen ................................ ................................ ................................ ... 134 PAM Fluorometry ................................ ................................ ................................ ... 136 Results ................................ ................................ ................................ ......................... 137 DO Electrodes ................................ ................................ ................................ ......... 137 PAM Fluorometry ................................ ................................ ................................ ... 149 Discussion ................................ ................................ ................................ ................... 158 Summary ................................ ................................ ................................ ..................... 161 Chapter 7. Conclusion ................................ ................................ ................................ .. 163 Sediment Phosphate Flux ................................ ................................ ............................ 163 Benthic microalgal chlorophyll a standing stock ................................ ........................ 164 Mesocosms as a tool to measure limiting nutrients in benthic microalgae ................ 165 Radiolabelled tracers of P flux through benthic microalgae ................................ ....... 166 Measuring primary production in benthic microalgae ................................ ................ 166 Everglades restoration efforts ................................ ................................ ..................... 167 Future work ................................ ................................ ................................ ................. 168 Literature Cited ................................ ................................ ................................ ............ 169 Bibliography ................................ ................................ ................................ .................. 179 Appendices ................................ ................................ ................................ ..................... 1 83

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v Appendix A. 1 84 Appendix B 18 5 Appendix C. Primary Production Equations 18 6 About the Author End Page

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vi List of Tables Table 2.1. Student's T test results of TDP, SRP and DOP flux from the sediment by treatment type between locations and by time of day between locations. Arsnicker represents Arsnicker Key in the southeast bay, Carl Ross represents Carl Ross Key in the western bay and End repr esents End Key in the central bay. .............. 13 test results showing statistical significance between replicate light and dark treatments by date and parameter. ................................ ................................ ............................. 42 Table 2.3. Average DOP flux in Florida Bay. ................................ .................... 43 Table 2.4. Average TDN values and range of flux in Florida Bay. The last c olumn provides the range of the percent increase from initial values during incubation. ................................ ........................... 45 Table 3.1 (reproduced from Cahoon, 2006, with permission). Spatial dis tribution of intertidal and subtidal studies measuring microphytobenthic production by all methods as of 2003. Data are numbers of published studies from Cahoon (1999) and more recent references. ................................ ................................ .. 49

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vii Table 3.2. (reproduced from Cahoon, 2005, with permission). Values of microphytobenthic photosynthetic parameters reported in published literature: E k (saturating light intensity, mol photons m 2 s 1 ), P max (maximu m, biomass normalized photosynthetic rate, mg C mg chl a 1 h 1 ), alpha (slope of P E relationship, mg C mg chl a 1 h 1 ( mol photons m 2 s 1 ) 1 ), P (biomass normalized photosynthetic rate mg C mg chl a 1 h 1 ........... 50 Table 3.3 Ranges and average pigment values for water column and benthic microalgae in Florida Bay. ................................ ...................... 61 Table 3.4 ANOVA levels of significance for comparison of chlorophyll a and phaeopigment among locations ................................ .................. 64 Table 4.1. Initial nutrient field concentration in M L 1 ................................ ... 75 Table 6.1 Net benthic primary productivity (NBPP), sediment respiration (SR) and gross benthic primary production (GBP) see Appendix C for calculations. ................................ ................................ ................... 138

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viii List of Figures Figure 1.1. Map of bottom type in Florida Bay (Prager and Halley, 1997). Dark brown tan and orange areas represent bottom unvegetated by seagrass, but available for benthic microalgal production. ......................... 2 Figure 2.1. Typical light and dark incubation chambers ( <7L) used for the measurement of nutrient flux to and from the sediment. The photo shows the sampling ports and the ambient water reservoir (IV bags). ................................ ................................ ................................ ........... 9 Figure 2. 2. A map of Florida Bay indicating the major physical and biological regions and the red dots indicate the locations sampled during this study. ................................ ................................ ....................... 11 Figure 2.3. Summary of morning TDP flux by chamber and by date for Carl Ross Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Total flux represents the net P flux in that chamber a t the end of the incubation period. Positive flux is into the sediment, while negative flux is out of the sediment. ......................... 14 Figure 2.4. Summary of afternoon TDP flux b y chamber and by date for Carl Ross Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Afternoon flux represents the net P flux in that chamber since the mid day sampling period. Positive flux is into the sediment, while negative flux is out of the sediment. .................. 15

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ix Figure 2.5. Summary of Total TDP flux for Carl Ross Key. Individual d ark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Total flux represents the net P flux in that chamber at the end of the incubation period. Positive flux is into the sediment, while neg ative flux is out of the sediment. ................................ ......................... 16 Figure 2.6. Summary of morning SRP flux at Carl Ross Key. Individual dark chambers represented in blue colored bars and indi vidual light chamber results represented in yellow colored bars. Morning flux represents the net P flux in that chamber through the mid day sampling period usually between 12:00 and 13:00 EST. Positive flux is into the sediment, while negative flux is out of the sediment. ...... 17 Figure 2.7. Summary of afternoon SRP flux rates at Carl Ross Key. Individual dark chambers represented in blue colored bars and individu al light chamber results represented in yellow colored bars. Afternoon flux represents the net P flux in that chamber since the mid day sampling period. Positive flux is into the sediment, while negative flux is out of the sediment. ................................ ......................... 18 Figure 2.8. Summary of Total SRP flux rates at Carl Ross key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow c olored bars. Total flux represents the net P flux in that chamber at the end of the incubation period. Positive flux is into the sediment, while negative flux is out of the sediment. ................................ ......................... 19

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x Figure 2.9 Summary of morning DOP flux rates (calculated) at Carl Ross Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Morning flux represe nts the net P flux in that chamber through the mid day sampling period usually between 12:00 and 13:00 EST. Positive flux is into the sediment, while negative flux is out of the sediment. ................................ ................................ ............... 20 Figure 2.10. Summary of afternoon SRP flux rates (calculated) at Carl Ross Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented i n yellow colored bars. Afternoon flux represents the net P flux in that chamber since the mid day sampling period. Positive flux is into the sediment, while negative flux is out of the sediment. ......................... 21 Figure 2.11. Summary of Total DOP flux rates (calculated) at Carl Ross Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Total flux represents the net P flux in that chamber at the end of the incubation period. Positive flux is into the sediment, while negative flux is out of the sediment. ................................ ......................... 22 Figure 2.12. Summary of morning TDP flux rates at Arsnicker Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Morning flux represents the net P flux in that chamber thr ough the mid day sampling period usually between 12:00 and 13:00 EST. Positive flux is into the sediment, while negative flux is out of the sediment. ................................ ................................ ................................ ... 23

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xi Figure 2.13. Summary of afternoon TDP flux rates at Arsnicker Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Afternoon flux represents the net P flux in that chamber since the mid day sampling period. Positive flux is into the sediment, while negative flux is out of the sediment. ................................ ......................... 24 Figure 2.14. Summary of Total TDP flux at Arsnic ker Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Total flux represents the net P flux in that chamber at the end of the incubation period. Positive flux is into t he sediment, while negative flux is out of the sediment. ................................ ......................... 25 Figure 2.15. Summary of morning SRP flux rates at Arsnicker Key. Individual dark chambers represented i n blue colored bars and individual light chamber results represented in yellow colored bars. Morning flux represents the net P flux in that chamber through the mid day sampling period usually between 12:00 and 13:00 EST. Positive flux is into the sedim ent, while negative flux is out of the sediment. ................................ ................................ ................................ ... 26 Figure 2.16. Summary of afternoon SRP flux at Arsnicker Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Afternoon flux represents the net P flux in that chamber since the mid day sampling period. Positive flux is into the sediment, while negative flux is out of the sedimen t. ................................ ................................ ........ 27

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xii Figure 2.17. Summary of total SRP flux rates at Arsnicker Key. Individual dark chambers represented in blue colored bars and individual light chamber res ults represented in yellow colored bars. Total flux represents the net P flux in that chamber at the end of the incubation period. Positive flux is into the sediment, while negative flux is out of the sediment. ................................ ......................... 28 Figure 2.18. Summary of morning DOP flux rates (Calculated) at Arsnicker Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Morning flux represents the net P flux in that chamber through the mid day sampling period usually between 12:00 and 13:00 EST. Positive flux is into the sediment, while negative flux is out of the sediment. ................................ ......................... 29 Figure 2.19, Summary of afternoon DOP flux rates (calculated) at Arsnicker Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow co lored bars. Afternoon flux represents the net P flux in that chamber since the mid day sampling period. Positive flux is into the sediment, while negative flux is out of the sediment. .................. 30 Figure 2.20. Summary of total DOP flux rates (calculated) at Arsnicker Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Total flux represent s the net P flux in that chamber at the end of the incubation period. Positive flux is into the sediment, while negative flux is out of the sediment. ................................ ......................... 31

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xiii Figure 2.21. Summary of the morning TDP flux at End Basin. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Morning flux represents the net P flux in that chamber through the mid day sampling period usually between 12:00 and 13:00 EST. Positive flux is into the sediment, while negative flux is out of the sediment. ...... 32 Figure 2.22. Summa ry of the afternoon TDP flux at End Basin. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Afternoon flux represents the net P flux in that chamber since the mid day sampl ing period. Positive flux is into the sediment, while negative flux is out of the sediment. ................................ ......................... 33 Figure 2.23. Summary of the total TDP flux at End Basin. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. T otal flux represents the net P flux in that chamber at the end of the incubation period. Positive flux is into the sediment, while negative flux is out of the sediment. ................................ ......................... 34 Figure 2.24. Summary of morning SRP flux at End Basin. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Morning flux represents the net P flux in that chamber throu gh the mid day sampling period usually between 12:00 and 13:00 EST. Positive flux is into the sediment, while negative flux is out of the sediment. ...... 35

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xiv Figure 2.25. Summary of afternoon SRP flux at End Basin. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Afternoon flux represents the net P flux in that chamber since the mid da y sampling period. Positive flux is into the sediment, while negative flux is out of the sediment. ................................ ................................ ........ 36 Figure 2.26. Summary of total SRP flux at End basin. Indiv idual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Total flux represents the net P flux in that chamber at the end of the incubation period. Positive flux is into the sediment, wh ile negative flux is out of the sediment. ................................ ......................... 37 Figure 2.27. Summary of morning DOP flux (Calculated) at End basin. Individual dark chambers represented in blue col ored bars and individual light chamber results represented in yellow colored bars. Morning flux represents the net P flux in that chamber through the mid day sampling period usually between 12:00 and 13:00 EST. A positive flux is into the sediment, whi le negative flux is out of the sediment. ................................ ................................ ............................. 38 Figure 2.28. Summary of afternoon DOP flux rates (calculated) at End basin. Individual dark chambers represented in bl ue colored bars and individual light chamber results represented in yellow colored bars. Afternoon flux represents the net P flux in that chamber since the mid day sampling period. Positive flux is into the sediment, while negative flux is out of the sed iment. ............................... 39

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xv Figure 2.29. Summary of total DOP flux rates (calculated) at End basin. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Total flux represents the net P flux in that chamber at the end of the incubation period. Positive flux is into the sediment, while negative flux is out of the sediment. ................................ ......................... 40 Figure 3.1. October 2005, Map of colored water in Florida Bay. Reproduced with permission, FWC FWRI. ................................ .............. 55 Figure 3.2. November 1995, Map of colored water in Florida Bay. Reproduced with permission FWC FWRI. ................................ ............... 55 Figure 3.3. December 1995, map of colored water in Florida Bay. Reproduced with permission, FWC FWRI. ................................ .............. 56 Figure 3.4. Mean chlorophyll a and phaeopigment in western Florida Bay from replicate sediment cores (first Y axis) and a single water column sample when applicable (second Y axis). Error bars represent the standard error of replicate samples. Note that the 1 st and 2 nd Y axis scales differ by an order of magnitude. This station represents the intertidal microphytobenthos. The water column data was provided by Jennifer Jurado, University of Miami. ................... 60 Figure 3.5. Mean chlorophyll a and phaeopigment for replicate sediment cores in central Florida Bay. Error bars represent the standard error of replicate samples. This site was representative of subtidal microphytobenthos. ................................ ................................ ................... 62 Figure 3.6. Mean chlorophyll a and phaeopigment for replicate sediment cores in southeastern Florida Bay. Error bars represent the standard error of replicat e samples. This site was representative of subtidal microphytobenthos. ................................ ................................ ..... 63

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xvi Figure 4.1 (reproduced from Tomas et al. 1999, with permission) Depiction of nutrient li mitation zones within Florida Bay based upon bioassays of natural pelagic phytoplankton populations, from Tomas et al. 1999. Zone A represents areas where nitrogen and possibly silica are limiting during most of the year. Zone B represents areas where pr imarily N and sometimes P were limiting. Zone C represents areas primarily P limiting with rare N limitation. ....... 69 Figure 4.2. The site locations where sediment an d water were collected for the mesocosm experiments, Carl Ross Key and End Key. The sites are considered representative of western and central Florida Bay, respectively. ................................ ................................ ...................... 72 Figure 4.3. The mesocosms arranged in the randomized block design within the lagoonal flow through seawater system at the field laboratory in Layton, FL. ................................ ................................ .......... 73 Figure 4.4. Average TDP results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) during winter. The error bars represent the standard error, and are only shown in one direction to facilitate viewing. ................................ ................................ ................................ ..... 77 Figure 4.5. Average TDP results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) during summer. The error bars represent the standard error, and are only shown in one direction to facilitate viewing. ................................ ................................ ................................ ..... 78

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xvii Figure 4.6. Average TDP results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from western Florida Bay (Carl Ross Key) in winter. The error bars represent the standard error, and are only shown in one direction to facilitate viewing. ................................ .... 79 Figure 4.7. Av erage SRP results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in winter. The error bars represent the standard error, and are o nly shown in one direction to facilitate viewing. ............. 80 Figure 4.8. Average SRP results from replicate samples of triplicate nutrient addition treatments (N, P, N a nd P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in summer. The error bars represent the standard error, and are only shown in one direction to facilitate viewing. ............. 81 Figure 4.9. Average SRP results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from western Florida Bay (Carl Ross Key) in win ter. The error bars represent the standard error, and are only shown in one direction to facilitate viewing. ................................ .... 82 Figure 4.10. Average TDN results from replicate sa mples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in summer. The error bars represent the standard error, and are only shown in one direction to facil itate viewing. ............. 84

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xviii Figure 4.11. Average TDN results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms u sing sediment from western Florida Bay (Carl Ross Key) in winter. The error bars represent the standard error, and are only shown in one direction to facilitate viewing. ................................ .... 85 Figure 4.12. Average TDN results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in winter. The error bars represent the standard error, and are only shown in one direction to facilitate viewing. ............. 86 Figure 4.13. Average silica results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in summer. The error bars represent the standard error, and are only shown in one direction to facilitate viewing. ............. 87 Figure 4.14. Average silica results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from western Florida Bay (Carl Ross Key) in winter. The error bars represent the standard error, and are only shown in one direction to facilitate viewing. ................................ .... 88 Figure 4.15. Average silica results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in winter The error bars represent the standard error, and are only shown in one direction to facilitate viewing. ............. 89

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xix Figure 4.16. Average nitrite results from replicat e samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in summer. The error bars represent the standard error, and are only shown in one direction to f acilitate viewing. ............. 90 Figure 4.17. Average nitrite results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesoc osms using sediment from western Florida Bay (Carl Ross Key) in winter. The error bars represent the standard error, and are only shown in one direction to facilitate viewing. ................................ .... 91 Figure 4.18. Average nitrite results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in winter. The error bars represent the standard error, and are only shown in one direction to facilitate viewing. ............. 92 Figure 4.19. Average nitrate plus nitrite results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in summer. The error bars represent the standard error, and are only shown in one direction to fac ilitate viewing. ............. 93 Figure 4.20. Average nitrate plus nitrite results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Contro l) in mesocosms using sediment from western Florida Bay (Carl Ross Key) in winter. The error bars represent the standard error, and are only shown in one direction to facilitate viewing. ................................ .... 94

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xx Figure 4.21. Average nitrate plus nitrite results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in winter. The error bars represent the standard error, and are only shown in one direction to facilitate viewing. ............. 95 Figure 4.22. Average ammonium results from rep licate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in summer. The error bars represent the standard error, and are only shown in one direction to facilitate viewing. ............. 96 Figure 4.23. Average ammonium results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) i n mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in winter. The error bars represent the standard error, and are only shown in one direction to facilitate viewing. ............. 97 Figure 4.24. Average ammonium results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from western Florida Bay (Carl Ross Key) in winter. The error bars represent the standard error, and are only shown in one direction to facilitate viewing. ................................ .... 98 Figure 4.25. Average water column chlorophyll a ( g L 1 ) in central Florida Bay mesocosms by nutrient addition treatment (control, N, P, and NP) during summer 2002. Values are the average o f three replicates of treatment mesocosms in a randomized block design sampled daily. ................................ ................................ ......................... 100

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xxi Figure 4.26. Average sediment chlorophyll a ( g L 1 ) in central Florid a Bay mesocosms by nutrient addition treatment (control, N, P, and NP) during summer 2002. Values are the average of three replicates of treatment mesocosms in a randomized block design sampled daily. ................................ ................................ ......................... 101 Figure 4.27. Average water column chlorophyll a ( g L 1 ) in central Florida Bay mesocosms by nutrient addition treatment (control, N, P, and NP) during winter 2003. Values are the average of three replicates of treatment mesocosms in a randomized block design sampled daily. ................................ ................................ ......................... 102 Figure 4.28. Average sediment chlorophyll a ( g L 1 ) in central Florida Bay mesocosms by nutrient addition treatment (control, N, P, and NP) during winter 2003. Values are the average of three replicates of treatment mesocosms in a randomized block design sampled daily. ................................ ................................ ................................ ........ 103 Figure 4.29. Average sediment chlorophyll a ( g L 1 ) in western Florida Bay mesocosms by nutrient addition treatment (control, N, P, and NP) during winter 2003. Values are the average of three replicates of treatment mesocosms in a randomized block design sampled daily. ................................ ................................ ................................ ........ 104 Figure 4.30. Average water column chlorophyll a ( g L 1 ) in central Florida Bay mesocosms by nutrient addition treat ment (control, N, P, and NP) during winter 2003. Values are the average of three replicates of treatment mesocosms in a randomized block design sampled daily. ................................ ................................ ......................... 106

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xxii Figure 4.31. Temperature (left y axis) and salinity (right y axis) in August 2002 for the central Florida Bay mesocosm experiment. ....................... 109 Figure 4.32. Temperature (left y axis) and salinity (right y axis) in January 2003 for the western Florida Bay mesocosm experiment. ........ 110 Figure 4.33. Temperature (left y axis) and salinity (right y axis) in January 2003 for the central Florida Bay mesocosm experiment. .......... 111 Figure 5.1. The locations where field cores and water were collected in Florida Bay for all the experiments. ................................ ....................... 117 Figure 5.2. Cartoon depiction of experimental setup. From left to right: initial cores are received with BMA layer intact, the overlying water column is removed and sodium azide is added to the killed controls, filtered seawater collected from the field location is added to restore the water column and samples sit undisturbed overnight, the experiment commences upon th e addition of carrier free 33 P or PO 4 (blank) to the sediment in killed and live treatments, over time the amount of 33 P in the water column is measured. ............................... 119 Figur e 5.3. Various depth of injection below the sediment water interface were evaluated to determine the minimum depth necessary to prevent water column contamination by the radiolabelled 33 P using killed BMA communities from End Key and Carl Ross Key in wes tern and central Florida Bay, respectively. ................................ ... 122 Figure 5.4. Average benthic flux of 33 P (femtomoles L 1 h 1 ) from the sediment in cores taken in August 2003 from western Florida Bay. Error bars represent standard error of 5 replicates. Carrierfree 33 PO 4 in low nutrient seawater was injected into the sediment at 2cm below the sediment water interface. A n enhancement dose of

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xxiii 37 M of P was added to the water column in the live and killed treatments after 8 hours, but not controls. ................................ ............... 123 Figure 5.5. The average 33 P flux (femtomoles L 1 h 1 ) from the sediment in cores tak en from western Florida Bay, May 2004. Error bars represent standard error of 5 replicates per sampling interval. ............... 125 Figure 5.6. The average 33 P flux (femtomol es L 1 h 1 ) from the sediment in cores taken from central Florida Bay, May 2004. Error bars represent standard error of 5 replicates per sampling interval. Note the Y axis is an order of magnitude less than the western Florida Bay figure. ................................ ................................ ............................... 126 Figure 5.7. Daily flux of TDP to the overlying water column from the western Florida Bay sediment during the August 2003 experiment. All results indicate flux from the sediment to the water column. ........... 127 Figure 5.8. Daily TDP flux to the overlying water column from the sediment pool in western Florida Bay during the course of the May 2004 experiment. The measurement from the light 5 sample was lost. All results indicate flux from the sediment to the water column. ................................ ................................ ................................ .... 128 Figure 5.9. Daily TD P flux to the overlying water column from the central Florida Bay sediment during the course of the May 2004 experiment. The measurement from the dark 2 sample was lost. All results indicate flux from the sediment to the water column. ........... 129 Figure 6.1. Station map indicating the locations were DO in benthic chambers (Carl Ross Key and End Key only) and PAM fluorometry of benthic microalgae were measured. ............................... 135

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xxiv Figure 6.2. DO concentration (left y axis) within light and dark benthic chambers and ambient PAR values (right y axis) over time on July 17, 2002 in central Florida Bay. PAR was n ot measured at the final sampling period. ................................ ................................ ...................... 139 Figure 6.3. DO concentration (left y axis) within light and dark benthic chambers and ambient PAR values (right y ax is) over time on August 2, 2002 in central Florida Bay. PAR was not measured at the final sampling period. ................................ ................................ ....... 140 Figure 6.4. DO concentration (left y axis) within a light benthic chamber and ambient PAR values (right y axis) over time on September 11, 2000 in western Florida Bay. PAR was not measured at the final sampling period. ................................ ................................ ...................... 141 Figure 6.5. DO concentration (left y axis) within light and dark benthic chambers and ambient PAR values (right y axis) over time on November 13, 2000 in western Florida Bay. ................................ .......... 142 Figure 6.6. DO concentration (left y axis) within light and dark benthic chambers and ambient PAR values (right y axis) over time on November 14, 2000 in western Florida Bay. ................................ .......... 143 Figure 6.7. DO concentration (left y axis) within light and dark benthic chambers and ambient PAR values (right y axis) over time on March13, 2001 in western Florida Bay. ................................ .................. 144 Figure 6.8. DO concentration (left y axis) within light and dark benthic chambers and ambient PAR values (right y axis) over time on March 15, 2001 in western Florida Bay. ................................ ................. 145

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xxv Figure 6.9. DO concentration (left y axis) within light and dark benthic chambers and ambient PAR values (right y axis) over time on March 16, 2001 in western Florida Bay. ................................ ................. 146 Figure 6.10. DO concentration (left y axis) within light and dark benthic chambers and ambient PAR values (right y axis) over time on May 16, 20 01 in western Florida Bay. ................................ ............................ 147 Figure 6.11. DO concentration (left y axis) within a light benthic chamber and ambient PAR values (right y axis) over time on May 7, 2002 in western Florida Bay. ................................ ................................ ........... 148 Figure 6.12. DO concentration (left y axis) within light and dark benthic chambers and ambient PAR values (right y axis) over time on August 8, 2002 in western Florida Bay. ................................ ................. 149 Figure 6.13. Time of day effect on Yield versus Electron Transport Rate (ETR) derived from instantaneous measu rements at the three sites in western, central and southeastern Florida Bay from field sampling events between 2000 and 2002. ................................ ............... 150 Figure 6.14. Seasonal effect on Yield versus Electron Transport Rate (ETR) derived from instantaneous measurements at the three sites in western, central and southeastern Florida Bay from field sampling events between 2000 and 2002. ................................ ............... 151 Figure 6.15. Regional differences in Yield versus Electron Transport Rate (ETR) derived from instantaneous measurements at the three sites in western, central and southeastern Florida Bay from field sampling events between 2000 and 2002. ................................ ............... 152

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xxvi Figure 6.16. Electron transport rate (ETR) from triplicate rapid light curves in southeastern Florida Bay on May 2, 2002 at the 10:00 am and 12:00pm sampling interval. ................................ .............................. 153 Figure 6.17. Electron transport rate (ETR) from duplicate rapid light curves in central Florida Bay on April 4, 2002 at the 10:00 am, 12:00pm and 1:30pm sampling interval. ................................ ................ 154 Figure 6.18. Electron transport rate (ETR) from duplicate rapid light curves in central Florida Bay on July 17, 2002 at the 9:00 and 11:00 am and 1:00 and 3:00 pm sampling interval. ................................ 155 Figure 6.19. Electron transport rate (ETR) from triplicate rapid light curves in western Florida Bay on March 15, 2001 at the 9:00 and 11:30 am and 1:15pm sampling interval. ................................ ................ 156 Figure 6.20. Electron transport rate (ETR) from duplicate rapi d light curves in western Florida Bay on March 16, 2001 at the 10:00 and 11:45 am sampling interval. ................................ ................................ .... 157 Figure 6.21. Electron transport rate (ETR) from triplica te rapid light curves in western Florida Bay on May 4, 2002 at the 3:00 pm sampling interval. ................................ ................................ .................... 158

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xxvii Benthic M icroalgae and N utrient F lux in Florida Bay, USA Merrie Beth Neely ABSTRACT The objective of this study was to address the relationship between benthic microalgal communities and the phosphate nutrient dynamics of Florida Bay sediments and how they relate to benthic and water column primary p roduction. In situ phosphate (P) flux between the sediment and the water column was measured in three regions of Florida Bay. Differences in the ratio of inorganic to organic phosphate flux were found between the three regions in relation to the amount o f phosphate measured in the water column. Based upon the average sediment flux in my study, more than 1600 metric tons of P would be supplied by the sediment per year in Florida Bay. Based upon my measurements, dissolved nutrient flux from the sediment can be an important contribution to pelagic phytoplankton blooms in Florida Bay, accounting for 6.5 41% of demand and TDN accounts for 100% of the N demand. My findings were similar to others for both benthic nutrient flux and benthic microalgal chlorop hyll a concentration. Benthic microalgae in Florida Bay contribute 700 kg Chl a per day to the system. Mesocosm experiments demonstrated that benthic microalgae and water column phytoplankton can respond differently to changes in nutrient availability. T he dissolved nutrient in least supply in the water column does not necessarily correspond to the limiting nutrient for benthic microalgae. 33 P acted as a tracer between sediment and water column dissolved P pools. The presence of benthic microalgae enhanc ed the transport of 33 P to the water column as compared to simple Fickian diffusion. This was supported by the positive flux of dissolved P from the sediment to the water column pools in control treatments with a living benthic microalgal layer. Primary p roduction by benthic microalgae were measured using dissolved O 2 evolution and PAM fluorometry. Primary production for BMA habitat in Florida Bay was between 400 and 800 tons of C per day, based upon O 2 production and PAM fluorometry, respectively.

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1 Chapter 1. Benthic microalgae and nutrient flux in Florida Bay, USA Introduction The benthic microalgae that live in the upper centimeters of the sediment where the bottom lies within the euphotic zone have been (MacIntyre et al. 1996). These benthic microalgae can form dense mats at the sediment surface (Grant and Gust, 1987) and are comprised mostly of cyanobacteria and diatoms (MacIntyre and Cullen, 1995; Pinckney et al. 1995). Th e pennate diatoms are both attached to, and free living in and on, the sediments (MacIntyre and Cullen, 1995). Primary production by the microphytobenthos is poorly understood, and ignored in most monitoring programs. Those measurements of benthic microalg al biomass and primary production that have been published are generally from European estuaries or subtropical Pacific waters (Cahoon, 2006; Colijn and De Jonge, 1984). Numerous studies have shown that benthic microalgal biomass and primary production c an equal or exceed that of the water column (Cahoon and Cooke, 1992, Nelson et al. 1999, Charpy and Charpy Roubaud, 1990), but spatially, benthic microalgal biomass can be very patchy (Rizzo and Wetzel, 1985). Even within seagrass beds the microphytobenth os is an important contribution to overall benthic primary production (Moncreiff, 1992). Benthic primary production is effectively limited to the upper millimeter or so of the sediment; basically that depth to where light penetrates permitting photosynthe sis by the cells (MacIntyre and Cullen, 1995). However, viable cells have been found to several Cullen, 1995; Nelson et al. 1999). Vertical migration by motile benthic diato ms in the intertidal zone may be used as a means to escape desiccation (Pinckney and Zingmark, 1991) and UV exposure at low tide (Cooke, 1991). Other reasons cells are found at depth in sediments is due to burial (physical mixing of the sediments) from ti des, currents and waves (MacIntyre and Cullen, 1990, MacIntyre et al. 1996), and bioturbation.

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2 Photoinhibition has generally not been shown in benthic microalgae (Colijn and van Buurt, 1975; MacIntyre and Cullen, 1995; Mills and Wilkinson, 1986; Charpy a nd Charpy Roubaud, 1990), probably as a consequence of the potential light limited conditions due both to turbidity at the sediment/water interface and lack of light penetration beyond the upper few millimeters of sediment. In contrast, MacIntyre and Cull en (1995) found photoinhibition to be prevalent in both pelagic phytoplankton and benthic microalgae resuspended into the water column in San Antonio Bay, although measurements of nonresuspended benthic microalgae were not part of the study. Florida B ay Ecosystem Florida Bay (Figure 1.1) is a triangular shaped, shallow (average depth <2m) embayment dominated by mud banks forming large basins within the interior of the bay (Schomer and Drew, 1982; Fourqurean et al. 1992; Fourqurean et al. 1993). It is bounded to the north by the Everglades, to the east and south by the Florida Keys, and to the west by the Gulf of Mexico. Parts of Florida Bay are seasonally hypersaline, due to the restricted tidal influence caused by the mud banks and the high degree of evaporation relative to direct precipitation (Schomer and Drew, 1982; Phlips and Badylak, 1996). Figure 1.1. Map of bottom type in Florida Bay (Prager and Halley, 1997). Dark brown tan and orange areas represent bottom unvegetated by seagrass, but ava ilable for benthic microalgal production.

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3 Considerable attention has been focused on the area since massive die off of seagrasses were macrophyte dominated benthic primary production has been transitioning to a phytoplankton dominated system in many basins (Phlips and Badylak, 1996). Die off events continue today in some parts of the bay, although it is not as widespread or catastrophic as a few years ago. Subsequent to the seagrass die off, mixed diatom cyanobacterial blooms were noted in the central portions of the bay, but these too have varied in intensity and area ( Steidinger, et al. 199 8 2001 ). Recently, predominantly cyanobacterial blooms have been co occurring in the central bay and also the eastern bay and Card Sound area, where they had never previously been reported ( personal observation Heil unpublis hed data). Diminished light transmittance to benthic macrophytes became a problem due to sediment resuspension in the die off areas and from the water column phytoplankton blooms, which may have inhibited recolonization of the seagrasses (Kelble et al. 2005).The cyan obacterial blooms have also been implicated in major benthic die off in the Rankin Bight region, including sponges and megafauna ( Butler et al. 1995). There are three primary sources of water input to Florida Bay: The Gulf of Mexico, the Atlantic Ocean a cross the reef tract, and the Everglades (Schomer and Drew, 1982). The latter has undergone extensive water redistribution projects during the last century in an effort to reduce flooding and provide drinking water to urbanized areas of south Florida, and for irrigation of the expanding agricultural interests of the area (Schomer and Drew, 1982; Smith et al. 1989). As a result of this diversion of freshwater input from the north, the naturally hypersaline conditions in Florida Bay have been exacerbated in the mid late 20 th century (Phlips and Badylak, 1996; Fourqurean et al. 1992; Rudnick et al. 1997). Florida Bay is a nutrient limited system (Fourqurean et al. 1992). Nutrient limitation of phytoplankton and seagrasses in Florida Bay depends upon geograp hical location within the bay (Fourqurean et al. 1992, Fourqurean et al. 1993, Phlips et al. 1995; Phlips and Badylak, 1996). Tomas et al. (1995,1999) using bioassays, described P limitation increasing across Florida Bay from west to east and indicated t hat N and Si can

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4 be co limiting in western Florida Bay during the annual winter diatom bloom. central Florida Bay varies between nitrogen and phosphate limitation (Fourqurean et al. 1992; Fourqurean et al. 1993; Phlips and Badylak, 1996, Tomas et al. 1995 & 199 9 ). Many researchers have documented the patterns in water column nutrient availability in the bay, beginning with Fourqurean et al. ( 1993 ) This general trend has been supported by several other researchers in large and small scale field and laborat ory studies (Vargo et al. 2001 a and b, Jurado and Hitchcock 2001, Brand et al. 2001). Coarser coral algal sediments are found in the eastern region of the bay (Fourqurean et al. 1993). Fine grained mud or sands are prevalent elsewhere, especially in th e more restricted basins. These fine grained sediments and the attached or free living microalgae are susceptible to resuspension into the water column. The bays carbonate sediments chemically bind most available phosphorus (P), leading to nutrient limi tation of benthic and water column productivity. Unlike the weak bonds to clays and other organic particles, the bonds between the carbonate and P molecules are very tight and rarely break except during redox reactions (Millero, 2000). Silica and nitroge n via surface and groundwater flow into the bay, combine with the tight chemical adsorption of P on to the carbonate sediments and lead to temporal and spatial nutrient limitation of the water column phytoplankton and benthic macroalgae and seagrasses (Tom as et al 1996 1999). Benthic Microalgae It is unknown just how important benthic pelagic coupling is to the nutrient cycling of the Florida Bay ecosystem. Relatively few rates of benthic primary productivity or nutrient flux are available. The role of benthic microalgae in contributing to bay wide primary productivity and nutrient cycling has also not been quantified. Further complicating matters is the unknown, but unarguably widespread distribution of patches of benthic microalgae. Where seagrass die off has occurred the only source of benthic primary production would now be from macroalgae (drift and attached mats) or benthic microalgae. Benthic algal communities within the bay vary from a thin film of diatoms over relatively unconsolidated sedim ents to inch thick Laurencia sp mats carpeting the bottom (personal observation). Such communities might

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5 vary widely in primary productivity, and would certainly vary in sediment stabilization capability as well as biomass. Benthic microalgae cannot be considered in the same context as water column phytoplankton or seagrasses because they exist as an inter related community of autotrophic and heterotrophic bacteria. These communities involve several different types of microa lgae and their extended polysaccharide matrix ( MacIntyre et al. 1996). Some microalgae are associated with sediment substrate (epipelic) and others are free living (epipsammic) ( MacIntyre et al. 1996). Community composition can vary by depth in the sedim ent and the associated photic and redox environment ( Underwood and Barnett, 2006 ). Free living benthic microalgae migrate within and over the substrate, even colonizing seagrass ( MacIntyre and Cullen 1995). One poorly understood aspect of benthic micro algal communities is their effect on the carbon and nutrient flux between the water column and the sediments. Microalgal layers have been shown to modify the flux of nutrients from the sediment into the water column in laboratory experiments sand agar pet ri dish experiments (Sundback and Graneli, 1988) and in the field measuring along a tidal bore (Keizer et al. 1989). Bioturbation from megafauna and different rates of porewater advection due to fine scale bottom topography and grain size sorting can infl uence nutrient flux rates ( Huettal and Gust, 1992, Sundback and McGlathery, 2005 ). A glaring hole in the ongoing research in Florida Bay is the role of benthic microalgal communities in the coupling of benthic pelagic primary production and mediation of nutrient flux from the sediments. Benthic Microalgae and Sediment Resuspension Some microalgae can secrete a mucilaginous sheath or polysaccharide matrix binding themselves both to other organisms and the sediment grains (Yallop et al. 1994), thus providi ng an effective mechanism to stabilize the sediment on which they reside and minimize turbidity at the sediment/water interface. In addition to their contribution to primary production in coastal ecosystems, benthic microalgal mats have been shown to dram atically increase the turbulence and shear velocity needed to erode sediments (Yallop et al. 1994). The binding capabilities of their extruded exopolymer polysaccharides are extraordinary and can even increase with desiccation (Yallop et al.

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6 1994). When erosion does occur, benthic microalgal mats can quickly re establish themselves, often in as little as a few hours. The sediment types associated with microalgal mats can be quite diverse and the stabilizing properties of these mats is dependent to some d egree on the type of sediments on which they are found and the species of microalgae growing there (Yallop et al. 1994; Amspoker and McIntire, 1978). Dissertation Objectives The specific objectives of my dissertation were to measure the benthic microalgal chlorophyll a standing stock and benthic nutrient flux, primarily phosphate, across Florida bay. Another objective was to find evidence in support of benthic microalgal mediation of phosphate flux to, or from, the sediment to the water column. The final objective was to evaluate nutrient limitation on benthic microalgal growth across Florida Bay for comparison with known zones of nutrient limitation in pelagic phytoplankton.

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7 Chapter 2. Sediment phosphate flux in Florida Bay, USA. Introduction Florida Bay is a subtropical lagoonal estuary south of the Everglades system in Florida, USA. It is considered a primarily phosphate limited system in the interior and eastern portions of the bay, while the northern and western bay temporally differ in li miting nutrients (Tomas et al. 1999). Adverse ecological effects to the bay have practices in the Everglades system, which supplies freshwater to the bay, have been mos t implicated as the cause of these perturbations. Recent and proposed changes to the Everglades were brought about to alleviate and restore Florida Bay. In order to better to Florida Bay, scientists have been gathering information to construct a nutrient budget and 3D models for the region (Madden and MacDonald 2007) The sediment/water column nutrient flux is an important component of this nutrient budget. Seagrasses an d attached and drift macroalgae dominate the 2200 km 2 submerged vegetative landscape of Florida Bay. These highly productive macrophytes also dominate the primary production of the bay (Nielsen et al. 2005; Yarbro and Carlson, 2008). However, nearly 1/3 of the bay bottom is devoid of seagrass and in these areas benthic microalgae (BMA) would be a source of primary production (Prager and Halley 1997). Field studies have indicated that nutrification of the water column can be ameliorated as benthic microalgae near nutrient sources take up excess nutrients (Welsh, 1980; Admiraal, 1977). This can occur very quickly, on the order of a few days (Darrow, et al. 2003). Ulthicke and Klumpp (1997) found that ammonium addition led to increased chlorophyll and phaeopigment content of the benthic microalgal layer, w hich also led to higher maximum gross and daily net production. Heil et al. (2004) suggests that this buffering capacity of the microphytobenthos has reduced the effects of coastal nutrification to the Great Barrier Reef, Australia. Sundback and McGlat hery (2005)

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8 reference the buffering capacity of microphytobenthos in conceptual interaction models of coastal eutrophication. Fickian diffusive processes provide the baseline for the flux of nutrients to and from the sediments. However, other physical p rocesses, such as tidal pumping and the passage of waves, increase porewater nutrient advection rates (Zeitzschel, 1980, Harrison, et al. 1983) from the bottom to the overlying water. Keizer et al. (1989) found increased water column P and Si concentratio also due to changes in pressure and water velocity. Bioroughness, or microtopography of the bottom, causes increased porewater flushing immediately upstream and downstream of ripples, and within small depressions d ue to small scale changes in pressure (Thibodeaux, 1987; Huettel and Gust, 1992). This localized flushing delivers nutrients to the benthic microalgal resources on the surface of the sediment and may explain patchiness. Finally, the sediment/water column n utrient flux is also an important missing link, since Florida Bay is a nutrient limited system (Fourqurean et al. 1992; Fourqurean et al. 1993; Lapointe, 1989 ; Phlips et al. 1995; Phlips and Badylak, 1996). Whether the BMA play a role in sediment/water co lumn flux of Florida Bay is completely unknown. Such information would better characterize any historical adverse impact man has had on these environments and how meaningful any attempt at remediation might be. The objective of this study was to address the relationship between benthic microalgal communities and the phosphate nutrient dynamics of Florida Bay sediments and how they relate to benthic and water column primary production. I present my findings on whether t he nutrient fluxes that may limit b enthic microalgal productivity differ between regions in Florida Bay. Materials and Methods In situ measurement of soluble reactive phosphate (SRP), total dissolved phosphate (TDP) and total dissolved nitrogen (TDN) were made from benthic chambers (<7L) in serted into submerged sediment devoid of seagrass in Florida Bay. Clear and opaque chambers (Fig. 2.1) were deployed for 3 to 9 hours per day. Between 1 and 4 replicates of each chamber type were used in each deployment.

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9 Figure 2.1. Typical light a nd dark incubation chambers (<7L) used for the measurement of nutrient flux to and from the sediment. The photo shows the sampling ports and the ambient water reservoir (IV bags). To ensure a good seal, the acrylic chambers are inserted into the sediment and held down with dive weights if necessary. These chambers contain a gentle water circulation device (a fan blade that was manually turned) but effectively measure only diffusive flux. These chambers are similar to those used by Cahoon and Cooke (199 2). The chambers had 1 liter of ambient water reservoirs (collapsible IV bag filled with site seawater collected at the time of deployment) attached to them to replace sample volumes. This replacement reservoir was used to prevent extraction of sediment porewater because of vacuum pressure caused by reducing the volume in the chamber. Redox reactions within the sediment can mobilize P release into the porewaters and overlying water column. Therefore, dissolved oxygen (DO) levels within chambers were fr equently monitored. DO levels measured by microelectrodes inserted into the chambers, were typically between 6 and 8 mg l 1 and never decreased below 1.7 mg l 1 during the monitored incubations. Placement and recovery of the chamber and sample collectio n was accomplished by wading. Concurrent with the field incubations, ambient irradiance was measured

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10 periodically using a Licor 2 Quantum sensor and light meter. Temperature and salinity measurements were made periodically during the incubation period. Studies were conducted bimonthly between May 2000 and August 2002 and were not synoptic. A major disadvantage of using benthic chambers is their disruption of the normal mixing of the water column and surface sediments by eliminating wave and current e ffects (Malan and McLachlan, 1991). Enclosure of the bottom may also alter the vertical distribution of microorganisms within the benthos. Additionally, decreased diffusion rates of gases into and out of the sediments can also occur, limiting photosynthe sis (MacIntyre and Cullen, 1995). However, these chambers are the best method available for measuring oxygen production, since a semi closed system is required. Sampling sites were Whipray Basin, Arsnicker Keys, and Carl Ross/Sandy Key (Figure 2.2); provi ding representation of north central, eastern and western Florida Bay, respectively. Carl Ross/Sandy Key was the site most exposed to wind and tidal currents and a bird rookery was located on a nearby mangrove island. This site was open to the Gulf of Me xico to the south and west. There was less tidal action at Arsnicker Key; however, a tidal cut between a gap in the mangroves was located adjacent to the sampling site. Whipray Basin had no noticeable tide range, but was much more influenced by brackish water moving southward out of the Everglades and had a greater salinity range than the other two sites. All three sites were adjacent to mangrove islands and seagrass beds. Seagrasses (or rhizomes) and macroalgae were rarely located within any of the cham bers. Approximately 60mls of sample water was extracted from each chamber at each sample period throughout the day. Depending upon the chamber design, water was removed using a syringe with an 18 gauge needle that pierced a septum or through a three way valve located on the side of the chamber.

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11 Figure 2.2. A map of Florida Bay indicating the major physical and biological regions and the red dots indicate the locations sampled during this study. Phosphate (P) and nitrogen (N) samples were immedi ately filtered through a fired GF/F syringe filter assembly. Filtrate was placed into a fired scintillation vial, and only 4 was added. Samples were held in the field on ice until transported back to the laborator y at USF St. Petersburg where they were held at <0C until further analysis. Phosphate concentration was determined from discrete replicate samples using the colorimetric method of Solrzano and Sharpe (1980) on a Beckman Model DU520 spectrophotometer wi th a 5 cm cell path. Field samples were usually analyzed within two to four weeks following collection. The sample absorbance at 885 was compared with a standard and matrix (de ionized water) blanks and reagent blanks were subtracted from the samples to remove any error associated with the chemical additions. Dissolved

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12 organic phosphate (DOP) was calculated by subtraction of SRP from TDP in the same chamber and sampling interval. Samples that were possibly contaminated, based upon comparisons among rep licates, were culled from the dataset prior to statistical analysis. Dissolved organic nitrogen (DON) measurements were performed by Dr. Rob Masserini, USF on a Technicon Autoanalyzer II following Valderama ( 1981 ) DON was determined after the oxidation of all N in the sample to NO 3 The organic value is then derived by subtracting the inorganic value in this case NO 3 NO 2 and NH 4 from the total dissolved nutrient value. Time, tide, cloud cover, wind direction and speed estimates were also made and c ompared with measurements obtained from nearby monitoring stations in the SEAKEYS data buoy system (data courtesy of the Florida Institute of Oceanography (FIO) and the National Oceanic and Atmospheric Administration (NOAA)). Parametric statistics were us ed to analyze the data, since values were normally distributed, and homogeneous in variances. Results and Discussion TDP, SRP and DOP are presented graphically in Figures 2.3 to 2. 29 Not all chambers were able to be sampled at all times of the day due to failures so, when available, a portion of an incubation is presented for some chambers. These failures were due to high tides that prevented sampling or extreme weather events. Phosphate flux to and from the sediment in Florida Bay had high standard erro r and was variable by date and by location. It was frequently near the limits of detection by the colorimetric method of Solrzano and Sharp (1980). The absolute range of TDP flux was 8.1 M m 2 h 1 into the sediment (positive values) and 3.3 M m 2 h 1 out of the sediment (negative values). The greatest TDP flux out of the sediment occurred at Arsnicker Key in one dark chamber on July 11, 2001 (Figs. 2.12 2.14). This same chamber showed increased flux out of the sediment as the day progressed while mo st other chambers at that location shifted to flux into the sediment during afternoon hours. There were several instances of TDP flux into the sediment at both Carl Ross Key and Whipray Basin that were near the maxima, however the greatest TDP flux into t he sediment occurred at Carl Ross Key also in July 2001 (Figs. 2.3 2.5).

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13 SRP was variable by date and location and had a high standard error, but was always much lower than TDP. The absolute range of SRP flux was 6.6 M m 2 h 1 into the sediment (posit ive values) and 1.8 M m 2 h 1 out of the sediment (negative values). The greatest SRP flux into the sediment occurred at Carl Ross key in May 2002 (Figs. 2.6 2.8) and the greatest SRP flux out of the sediment occurred at Whipray in May 2001 (Figs. 2.24 2 .26). It should be noted that SRP flux out of the sediment was very rare throughout the study in all locations and was usually near the limits of detection (Figs. 2.7, 2.16, and 2.25) Y et significant differences in SRP flux rates in the morning vs. the afternoon were found at all stations (Table 2.1) SRP flu x out of the sediment only occurred in the afternoons and more frequently in dark chambers than in light chambers, but this treatment difference was not statistically significant between any of the locations when samples were grouped (Table 2.1 ). There were significant differences ( p <0.01) in SRP flux between all locations when comparing time (morning vs. afternoon measurements) when samples were grouped, and in DOP flux between Ar s nicker and Carl R oss Keys ( p <0.01, Table 2.1 ). Table 2. 1. Student's T test results of TDP, SRP and DOP flux from the sediment by treatment type between locations and by time of day between locations. Arsnicker represents Arsnicker Key in the southeast bay, Carl Ross repr esents Carl Ross Key in the western bay and End represents End Key in the central bay. Parameter Location Arsnicker vs Carl Ross Carl Ross vs End Arsnicker vs End Light vs Dark TDP 0.447 0.388 0.265 SRP 0.190 0.232 0.112 DOP 0.413 0.229 0.408 morning vs afternoon TDP 0.066 0.246 0.477 SRP 2E 07** 8E 12** 4E 19** DOP 0.0178** 0.460 0.456 **p=0.01

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14 Figure 2.3. Summary of morning TDP flux by chamber and by date for Carl Ross Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Total flux represents the net P flux i n that chamber at the end of the incubation period. Positive flux is into the sedime nt, while negative flux is out of the sediment.

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15 Figure 2.4. Summary of afternoon TDP flux by chamber and by date for Carl Ross Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colo red bars. Afternoon flux represents the net P flux in that chamber since the mid day sampling period. Positive flux is into the sediment, while negative flux is out of the sediment.

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16 Figure 2.5. Summary of Total TDP flux for Carl Ross Key. Individual da rk chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Total flux represents the net P flux in that chamber at the end of the incubation period. Positive flux is into the sediment, while nega tive flux is out of the sediment.

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17 Figure 2.6. Summary of morning SRP flux at Carl Ross Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Morning flux represents the n et P flux in that chamber through the mid day sampling period usually between 12:00 and 13:00 EST. Positive flux is into the sediment, while negative flux is out of the sediment.

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18 Figure 2.7. Summary of afternoon SRP flux rates at Carl Ross Key. Ind ividual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Afternoon flux represents the net P flux in that chambe r since the mid day sampling period. Positive flux is into the sediment while negative flux is out of the sediment.

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19 Figure 2.8. Summary of Total SRP flux rates at Carl Ross key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Total flux re presents the net P flux in that chamber at the end of the incubation period. Positive flux is into the sediment, while negative flux is out of the sediment.

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20 Figure 2.9 Summary of morning DOP flux rates (calculated) at Carl Ross Key. Individual dark cham bers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Morning flux represents the net P flux in that chamber through the mid day sampling period usually between 12:00 and 13:00 EST. Positive flux is into the sediment, while negative flux is out of the sediment.

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21 Figure 2.10. Summary of afternoon SRP flux rates (calculated) at Carl Ross Key. Individual dark chambers represented in blue colored bars and individual light chamber results represente d in yellow colored bars. Afternoon flux represents the net P flux in that chamber since the mid day sampling period. Positive flux is into the sediment, while negative flux is out of the sediment.

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22 Figure 2.11. Summary of Total DOP flux rates (calcula ted) at Carl Ross Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Total flux represents the net P flux in that c hamber at the end of the incubation period. Positive flux is into the sediment, while negative flux is out of the sediment.

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23 Figure 2.12. Summary of morning TDP flux rates at Arsnicker Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Morning flux represents the net P flux in that chamber through the mid day sampling period usually between 12:00 and 13:00 EST. Positive flux is into the sediment, while negative flux is out of the sediment.

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24 Figure 2.13. Summary of afternoon TDP flux rates at Arsnicker Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Afternoon flux represents the net P flux in that chambe r since the m id day sampling period. Positive flux is into the sediment, while negative flux is out of the sediment.

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25 Figure 2.14. Summary of Total TDP flux at Arsnicker Key. Individual dark chambers represented in blue colored bars and indi vidual light chamber res ults represented in yellow colored bars. Total flux represents the net P flux in that chamber at the end of the incubation period. Positive flux is into the sediment, while negative flux is out of the sediment.

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26 Figure 2.15 Summary of morning SRP flux rates at Arsnicker Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Morning flux represents the net P flux in that chamber through the mid day sampling period usually between 12:00 and 13:00 EST. Positive flux is into the sediment, while negative flux is out of the sediment.

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27 Figure 2.16. Summary of afternoon SRP flux at Arsnicker Key. Individual dark chambers represented in blue colored bars and individual light cha mber results represented in yellow colored bars. Afternoon flux represents the net P flux in that chamber since the mid day sampling period. Positive flux is into the sediment, while negative flux is out of the sediment.

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28 Figure 2.17. Summary of total S RP flux rates at Arsnicker Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Total flux represents the net P flux in that chamber at the end of the incubation period. P ositive flux is into the sediment, while negative flux is out of the sediment.

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29 Figure 2.18. Summary of morning DOP flux rates (Calculated) at Arsnicker Key. Individual dark chambers represented in blue colored bars and individual light chamber results re presented in yellow colored bars. Morning flux represents the net P flux in that chamber through the mid day sampling period usually between 12:00 and 13:00 EST. Positive flux is into the sediment, while negative flux is out of the sediment.

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30 Figure 2. 19, Summary of afternoon DOP flux rates (calculated) at Arsnicker Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Afternoon flux represents the net P fl ux in that cham ber since the mid day sampling period. Positive flux is into the sediment, while negative flux is out of the sediment.

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31 Figure 2.20. Summary of total DOP flux rates (calculated) at Arsnicker Key. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Total flux represents the net P flux in that chambe r at the end of the incubation period. Positive flux is into the sediment, while negative flux is out of the sediment.

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32 Figure 2 .21. Summary of the morning TDP flux at End Basin. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Morning flux represents the net P flux in that chamber through the mid d ay sampling period usually between 12:00 and 13:00 EST. Positive flux is into the sediment, while negative flux is out of the sediment.

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33 Figure 2.22. Summary of the afternoon TDP flux at End Basin. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Afternoon flux represents the net P flux in that chambe r since the mid day sampling period. Positive flux is into the sediment, while negative flux is out of the sediment.

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34 F igure 2.23. Summary of the total TDP flux at End Basin. Individual dark chambers represented in blue colored bars and indivi dual light chamber results represented in yellow colored bars. Total flux represents the net P flux in that chamber at the end of the incubation period. Positive flux is into the sediment, while negative flux is out of the sediment.

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35 Figure 2.24. Summary of morning SRP flux at End Basin. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Morning flux represents the net P flux in that chamber through the mid day sampling period usually between 12:00 and 13:00 EST. Positive flux is into the sediment, while negative flux is out of the sediment.

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36 Figure 2.25. Summary of afternoon SRP flux at End Basin. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Afternoon flux represents the net P flux in that chamber since the mid day sampling period. Positive flux is into the sediment, while negative flux is out of the sediment.

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37 Figure 2.26. Summary of total SRP flux at End basin. Individual dark chambers represented in blue colored bars and individual light chamber results repres ented in yellow colored bars. Total flux represents the net P flux in that chamber at the end of the incubation period. Positive flux is into the sediment, while negative flux is out of the sediment.

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38 Figure 2.27. Summary of morning DOP flux (Calculate d) at End basin. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Morning flux represents the net P flux in that chamber through the mid day sampling period usually betwee n 12:00 and 13:00 EST. A positive flux is into the sediment, while negative flux is out of the sediment.

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39 Figure 2.28. Summary of afternoon DOP flux rates (calculated) at End basin. Individual dark chambers represented in blue colored bars and individua l light chamber results represented in yellow colored bars. Afternoon flux represents the net P flux in that chamber since the mid day sampling period. Positive flux is into the sediment, while negative flux is out of the sediment.

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40 Figure 2.29. Summa ry of total DOP flux rates (calculated) at End basin. Individual dark chambers represented in blue colored bars and individual light chamber results represented in yellow colored bars. Total flux represents the net P flux in that chambe r at the end of the incubation period. Positive flux is into the sediment, while negative flux is out of the sediment.

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41 In general, trends in P flux were consistent among chambers at the same location and sampling date, and only differed in the magnitude of the flux. There were some instances when one or more treatment chambers deviated substantially from the others in the direction of P flux (example, Figure 2.13) Due to the relatively small chamber size, t hese inconsistencies between chambers were un c ommon and may represent bioturbation or seeps and sinks in the underlyi ng sediment/groundwater system. Whipray Basin and Arsnicker Keys exhibited similar phosphate flux values as Carl Ross Key during the same sampling periods (Figs. 2.3 2.29) despite diffe rences in sediment grain size (observed) and reduced tidal pumping. Hourly P flux rates reported here are similar to those of Yarbro and Carlson ( 1999; 2008 ). There is no clear pattern between phosphate flux in light and dark chambers at different locatio ns when enough measurements were made to allow statistical tests. Nor was there any statistically significant differences between these treatments (Table 2.1 ). No clear seasonal pattern of phosphate flux was found For the most part, t ime comparisons (morning vs. afternoon) between light and dark treatments at each station for each date were not statistically significant, although there were several exceptions no overall pattern was discernable (Table 2.2 ). DOP is the primary component of the availa ble P pool in the water column, although the amount and TDP:DOP ratio varies across Florida Bay from West to East with greatest values in the central region (Table 2.3) F lux of organic P dominates the system, whether into or out of the sediment, since o rganic P concentrations exceeded inorganic P concentrations in all locations at most times of the year and in most sampling chambers. Table 2. 3 shows the average hourly DOP flux rates by bay region for the entire study period. The ratio of organic to ino rganic P flux is high except at the southeastern station. The central station had the highest ratio (71% DOP). This findin g is consistent with what other s have found in Florida Bay, but contrasts with most oceanic systems where inorganic forms of P are p redominant (Riley and Chester, 1972)

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42 test results showing statistical significance between replicate light and dark treatments by date and parameter.

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43 Table 2.3. Average DOP flux in Florida Bay. Treatment Location Light Dark ( Mm 2 h 1 ) ( Mm 2 h 1 ) Western 0.227 0.189 %DOP 57% 56% Central 0.262 0.265 %DOP 71% 71% Southeastern 0.055 0.076 %DOP 18% 22% As mentioned before, dissolved organic P flux at all sites tended to be into the sediment in the morning hours with diminished magnitude of flux into the sediment, or flux out of the sediment, during afternoon. The reason for this is unknown, but I specul ate that it is due to uptake by BMA that are increasing primary production in response to light availability. The central bay (End Key) station more frequently exhibited total dissolved organic P flux into the sediment from the water column and this trend was of greater magnitude in light chambers (Figs. 2.27 2.29). In eleven of sixty six instances there were statistically significant differences ( p <0.1) between all forms of P flux in the light and dark treatments, three at the p =0.05 level (Table 2.2). The differences in the light chambers is presumed to be indicative of enhanced algal uptake or release of nutrients in the water whether BMA or pelagic phytoplankton. In contrast, the Carl Ross Key station more frequently exhibited total dissolved organi c P flux out of the sediment into the water column (Figs. 2.9 2.11), while the m agnitude and direction of flux w as more variable at Carl Ross Key. Total organic P flux was more balanced between light and dark chambers at the Carl Ross Key station than at the End station. However, light chambers exhibited release of DOP into the water column in the morning hours while dark chambers showed diminished DOP release into the water column or flux into the sediment. As with End the magnitud e of P flux

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44 diminished in the afternoon at Carl Ross Key. In ten of ninety six instances, there were statistically significant differences between all forms of P flux in the light and dark treatments, five at the p =0.05 level and one at the p =0.01 level. (Table 2.2 ). Arsnicker Key was only sampled twice with few consistencies between the treatments among sampling dates. This location had a trend similar to Carl Ross Key where DOP flux was out of the sediment in the morning and then into the sediment in the afternoon, leading to a net flux of DOP out of the sediment for all treatments on both sampling events (Fig.2.21 2.23) T test indicated total SRP values between light and dark treatments were significantly different ( p =0.1) in one of the t wo sampling events (Table 2.2 ). Based upon growth rate requirements estimated from in situ growth rates and biomass in western Florida Bay (Vargo et al. 1999), DOP flux from the sediment c ould supply 6.5 41% of the P required by water column phytoplankt on during bloom and nonbloom conditions, respectively Nitrogen Total dissolved nitrogen (TDN) was comprised mostly of dissolved organic forms throughout Florida Bay in excess of 50%. TD N flux range d from 408.69 (out of the sediment) to 393.59 M m 2 h 1 (into the sediment) but averages 38.38 M l 1 throughout the bay Table 2.4 shows the average TDN values and fluxes by location in the bay. Absolute values were more variable in the central bay; however, average values were quite similar among the thre e locations. Southeastern Florida Bay showed the least variable flux rate with no flux into the sediment, but this was probably because it was only sampled twice. I did not evaluate statistical differences in morning vs. afternoon or light vs dark chamber s for TDN. Still, TDN flux from the sediment could supply 100% of the nitrogen demand of the water column phytoplankton, providing the form of available nitrogen is usable by the cells.

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45 Table 2.4. Average TDN values and range of flux in Florida Bay. Th e last column provides the range of the percent increase from initial values during incubation. TDN Avg H 2 O Column Flux % of initial TDN Location ( M l 1 ) ( Mm 2 h 1 ) Western 37.58 208.08 to 153.99 47 275% Central 40.86 408.64 to 393.59 33 359% Southeastern 47.94 14.32 to 47.51 111 136% Summary Despite temporal and spatial variability, p hosphorus flux from the sediment would be an important source of P to both the benthic microalgae, macrophytes and phytoplankton in the overlying water column. I estimate that 6 41% of the water column phytoplankton needs could be met by benthic flux. Bas ed upon the area of bay at 2200km 2 1/3 of which is available for microphytobenthos colonization, and a loss of 4000 hectares of seagrass due to dieoff, my average TDP flux values would contribute ~1650 metric tons of P to the entire system per year, 9.1 m etric tons per year from areas newly devoid of seagrass due to dieoff. My calculation could be an overestimate since the dark incubation rates were simulated and were not done during the normal dark cycle when diurnal processes could have resulted in net P uptake by the sediment. Repeated anoxia events, or shoaling and deepening of the anoxic layer, would release loosely bound P buried in the sediment. SRP values were frequently near the limits of detection, yet significant differences in SRP flux rates in the morning vs. the afternoon at all stations indicate that benthic microalgal community could be mediating P fluxes during periods of high photosynthesis. Since organic forms of phosphorus dominate Florida Bay, P is being recycled through organisms li ke benthic microalgae.

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46 Although more typical of a shallow coastal lagoon system, autochthonous organic matter accumulation is high in the bay. This is further enhanced by the long residence time of some basins and the lack of tidal flushing for more ~ o f the area of the bay. This suggests the bay would be a sink for nutrients from the upstream sources. Rizzo (1990) and Sundback et al. (1991) both documented nutrient uptake by the microphytobenthos both from the sediment and the water column. Nutrients taken up from the water column allow the microphytobenthos to act as a temporary nutrient sink in Florida Bay. Nutrient flux from the sediment would be a source and my findings indicate it c ould support water column production The duration and magnitude of what this nutrient flux would support depends upon pelagic phytoplankton biomass and need, which would vary Sundback and McGlathery (200 5 ) suggest the trophic status of the sediment controls whether benthic pelagic interactions are coupled or decoup led. Autotrophic (oxic) sediments, and tropical carbonate sediments, lead to a decoupled benthic pelagic system as the microphytobenthos traps and recycles nutrients, preventing release to the water column. Heterotrophic sediments are coupled with the wa ter column system as anoxic conditions promote the flux of nutrients from the sediment through the microphytobenthos community and into the overlying water column. In their scenario, the coupling/decoupling persists for weeks to months in the environment before switching in response to changing physical and chemical conditions. Due to the amount of organic matter in the bay ( Halley et al.1999) and proximity of the anoxic layer to the sediment surface, conditions in Florida Bay where microphytobenthos domin ate, might favor this alternating scenario, but occurring on the order of hours to days perhaps even on a diurnal cycle. The presence of Laurencia mats during some times of the year, although not investigated in this study, would enhance sediment water column interactions This is because the mats cause shoaling of the sediment anoxic layer beneath the mat and in some cases, depending upon thickness of the mat, would include anoxic conditions within this microhabitat. Yarbro and Carlson (2008) do not report consistent diel patterns in P flux in benthic chambers deployed within seagrass beds, despite diurnal changes from net

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47 autotrophy to net heterotrophy in the chambers. However, the seagrass and epiphyte community is known to dominate nutrient cycling both by changing oxic conditions in the rhizosphere and by direct uptake and release of nutrients from both the sediment and water column (Koch, et al. 2005; Nielsen, et al. 2005; Yarbro and Carlson, 2008). The diel effe ct of a complete shift between autotrophy and heterotrophy on nutrient flux in the microphytobenthos community would be dampened relative to that found within seagrass beds. Although unresolved in this study, tidal pumping of P from the sediments may be important in western Florida Bay due to the variability in the sediment grain size, although peak P concentrations did not seem to correspond to any consistent tidal level. Tidal influences are diminished at Arsnicker Keys and there is nearly no tidal ran ge evident in End Basin. This research will enhance the current understanding of benthic pelagic interactions in western Florida Bay and near shore environments, and provide baseline estimates for nutrient exchange between the benthos and water column whic h include biotic factors.

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48 Chapter 3. Benthic Microalgal Chlorophyll a Standing Stock in Florida Bay Introduction Benthic Microalgae (Microphytobenthos) Because their production is underappreciated, b enthic microalgae that live in the upper centimeters of the sediment where the bottom lies within the euphotic zone have et al. 1996). These benthic microalgae (BMA) can form dense mats at the sediment surface ( Grant and Gust, 1987) and are comprised mostly of cyanobacteria and diatoms (MacIntyre and Cullen, 1995 ; Pinckney et al. 1995). Benthic microalgae can also be termed microphytobenthos. Numerous studies have shown that benthic microalgal biomass and primar y production can equal or exceed that of the water column (Cahoon and Cooke, 1992 ; Nelson et al. 1999 ; Charpy and Charpy Roubaud, 1990), but spatially, benthic microalgal biomass can be very patchy (Rizzo and Wetzel, 1985). Even within seagrass beds the m icrophytobenthos is an important contribution to overall benthic primary production (Moncreiff, 1992). Pri mary production by the microphytobenthos is poorly quantified on a broad geographic scale, and ignored in most monitoring programs (Cahoon 2006). Th ose measurements of benthic microalgal biomass and primary production that have been published are generally from European estuaries or US waters (Table s 3. 1 and 3.2 from Cahoon 2006 ; Cahoon 1999 ; Heil et al. 2004 ; Colijn and De Jonge, 1984). Benthic primary production is effectively limited to the upper millimeter or so of the sediment; basically that depth to where light penetrates permitting photosynthesis by the cells (MacIntyre and Cullen, 1995). However, viable cells have been found to several c Cullen, 1995 ; Nelson et al. 1999 ; Aller et al. 2001 ).

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49 Table 3.1 (reproduced from Cahoon, 2006, with permission). Spatial distribution of intertidal and subtidal studies me asuring microphytobenthic production by all methods as of 2003. Data are numbers of published studies from Cahoon (1999) and more recent references.

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50 Table 3.2. (reproduced from Cahoon, 2006, with permission). Values of microph ytobenthic photosynthetic parameters reported in published literature: E k (saturating light intensity, mol photons m 2 s 1 ), P max (maximum, biomass normalized photosynthetic rate, mg C mg chl a 1 h 1 ), alpha (slope of P E relationship, mg C mg chl a 1 h 1 ( mol photons m 2 s 1 ) 1 ), P (biomass normalized photosynthetic rate mg C mg chl a 1 h 1 P ennate diatoms can be found free living in and on the sediments (MacIntyre and Cullen, 1995 ) or living within polysaccharide tubes interstitially ( Yallop et al. 1994 ). Vertical migration by motile benthic diatoms in the intertidal zone may be used as a means to escape desiccation (Pinckney and Zingmark, 1991) and UV exposure at low tide (Cooke, 1991). Other reasons cells are found a t depth in sediments is due to burial (physical mixing of the sediments) from tides, currents and waves (MacIntyre and Cullen, 199 5; MacIntyre et al. 1996), and bioturbation.

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51 Benthic Microalgae and Sediment Resuspension Some microalgae can secrete a mucilaginous sheath or polysaccharide matrix binding themselves both to other organisms and the sediment grains (Yallop et al. 1994), thus providing an effective mechanism to stabilize the sediment on which they reside and min imize the effects of turbidity at the sediment/water interface. In addition to primary production in coastal ecosystems, benthic microalgal mats have been shown to dramatically increase the turbulence and shear velocity needed to erode sediments (Yallop e t al. 1994). The binding capabilities of their extruded exopolymer polysaccharides are extraordinary and can even increase with desiccation (Yallop et al. 1994). When erosion does occur, benthic microalgal mats can quickly re establish themselves, often in as little as a few hours. The sediment types associated with microalgal mats can be quite diverse and the stabilizing properties of these mats is dependent to some degree on the type of sediments on which they are found and the species of microalgae gr owing there (Yallop et al. 1994 ; Amspoker and McIntire, 1978). Benthic microalgae physically alter the benthic environment for infaunal and epifaunal organisms by stabilizing the sediments The are an important food source for benthic filter feeders like gastropods, bivalves, sponges and infaunal worms (Cahoon and Cooke, 1992), which in turn support higher trophic levels. Benthic cells re suspended into the water column due to tides or wind events are potential food sources for both benthic and pelagic or ganisms (MacIntyre and Cullen, 1996). Baillie and Welsh (1980) showed that tidally re suspended benthic microalgae were transported directly to the oyster reefs found at the fringes of mudflats adjacent to a saltmarsh. The locations of greatest re suspe nded cell transport coincided with these oyster reefs indicating the oyster reefs flourished where the maximal food availability was found (i.e. re suspended benthic microalgae). Baillie and Welsh, (1980) also calculated that if the top 1 mm of sediment we re resuspended in 10 15% of the mudflat in Branford Harbor, Connecticut then the benthic microalgal cell numbers in the water column would equal that of the pelagic phytoplankton numbe rs. De Jonge, (1985) found more benthic microalgae in the water column due to resuspension by physical processes than was found in the upper 0.5 cm of

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52 the sediment. Resuspension of sediment along with benthic microalgal cells may offset any potential increase in water column primary productivity by decreasing light availabil ity at depth and to the benthos. MacIntyre et al. (1996) suggest that the water column and sediment should not be treated as mutually exclusive environments, but that this interface is a dynamic area with influence from both systems. C3 plants are more ph otosynthetically efficient at low to intermediate light availability than high light, which can have implications for competition (Lawlor 2001). Photoinhibition has generally not been shown in benthic microalgae (Colijn and van Buurt, 1975 ; MacIntyre an d Cullen, 1995 ; Mills and Wilkinson, 1986 ; Charpy and Charpy Roubaud ; 1990) ; probably as a consequence of the potential light limited conditions from turbidity at the sediment/water interface and lack of light penetration beyond the upper few millimeters o f sediment. In contrast, MacIntyre and Cullen (1995) found photoinhibition to be prevalent in both pelagic phytoplankton and benthic microalgae resuspended into the water column in San Antonio Bay, although measurements of nonresuspended benthic microalga e were not part of the study. Benthic Microalgal primary productivity and models Photosynthesis is the process by which light energy, water and carbon dioxide are converted into complex, energy rich organic molecules by chlorophyll containing plants ( Lawlor, 2001). More specifically it is an oxidation reduction reaction, where electron donor and acceptor molecules in a cell bearing photosynthetic pigments and exposed to light split water molecules resulting the release of heat energy and O 2 (Lawlor 2 001). Respiratory losses balance photosynthetic gains of oxygen The p hotosynthetic rate of plants involves the orientation of the cell to the light, the amount of light, temperature and available nutrients (Forster and Kromkamp, 2006). Beyond the limit ing nutrients of nitrogen, phosphorus and silica, d issolved inorganic carbon may become limiting to the microphytobenthos during periods of high production and high porewater O 2 (Forster and Kromkamp, 2006). As a result of only some of the microphytobenth os cells being functionally able to photosynthesize, by their proximity to the sediment surface and as a result of migratory behavior, they are termed the Photosynthetically Active Biomass (PAB) (Serodio et al. 1997).

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53 Different methods of modeling primar y production by the PAB have been developed, including the SML (surface monolayer), UNI (uniform distribution of cells with depth) and the KY models (exponentially decreasing gradient of chlorophyll with depth in the sediment). A comparison of these model s, by Forster and Kromkamp (2006) indicated that all three models were capable of simulating actual measured field conditions, although all overestimated actual primary production. Some models were more strongly affected by the application of various rate s of respiration between 1 and 10% of gross primary production However, the rates used in this model were estimated because respiration is seldom measured and var ies due to light and temperature regime s However, a ll the models would be enhanced by the application of more site specific measurements and more refined estimates of all parameters, most particularly respiration. Darrow et al. (2003) developed a model of benthic primary production on the West Florida Shelf that coupled regenerated nutrient s from a pelagic phytoplankton bloom to subsequent production by benthic diatoms. Their one dimensional model, with 16 variables, was used to model the benthic diatom community response to a pulse of riverine water over the shelf that resulted in a bloom The remnants of the pelagic bloom was transported to the sediment and provided nutrients sufficient to stimulate benthic production. Th e benthic production effectively served as a temporary sink of regenerated nutrients on the shelf Global microphyt obenthic primary production has been estimated at 0.34 0.5 Gt C yr 1 based upon average productivity to a depth of 50m (Charpy Roubaud and Sournia, 1990) and depth weighted production estimates (Cahoon, 1999), respectively. Tropical areas tend to have higher productivity rates, as expected with warmer, clearer water and greater light levels of longer duration, averaging 527 g C m 2 yr 1 and biomass values of 90 350 mg C hl a m 2 (Cahoon, 2006). However, these are likely overestimates since they are scal ed up from smaller studies, utilize different measuring techniques and do n o t adequately account for localized differences in light and temperature regimes that control productivity. Significant d ifferences in productivity exist between inter and subtida l zones. I t is im practical to make broad spatial and temporal synoptic measurements and

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54 in general there are too few studies worldwide to have an adequate understanding of the range of global productivity of the microphytobenthos. Benthic Microalgae i n Florida Bay Florida Bay began experiencing massive die (Carlson et al. 1990), and more recently persistent algal blooms ( Figs.3. 1 3.3 ). Diminished light transmittance to the benthos has been an ongoing problem in s ome basins due to sediment resuspension and algal blooms. This problem also has recently increased in magnitude. As a result of the die off, the macrophyte dominated benthic primary production has been shifting to a phytoplankton dominated system in many basins (Phlips and Badylak, 1996). Chlorophyll a and primary production of pelagic phytoplankton are commonly measured water quality parameters. Extensive monitoring data exist s for Florida Bay, although it has only recently received increased attention from the scientific community (Fourqurean et al. 1992 ; Rudnick et al. 1999 ; Tomas et al. 1999 ). Tomas et al. (1999) found that the lowest water column biomass and growth rates were in the eastern regions of Florida B ay, with intermediate values in the western bay while central F lorida bay exhibited both the highest biomass and growth rates. This finding is partially consistent with the distribution of dissolved nutrients although phosphate availability appears to be limiting throughout most of the bay ( Fourqurean et al. 1992 As information about Florida Bay accumulates, it is becoming obvious that the biomass of the benthic microalgal communit y has been under sampled and little is known about the coupling of benthic pelagic primary productio n. The contribution of benthic microalga l productivity in seemingly unvegetated bottom areas to the baywide primary productivity has also not been quantified. Approxima tely one third of the 2200km 2 bay is unvegetated inter or sub tidal bottom ( Prager an d Halley, 1997 ) and about 4000 hectares of seagrass have been permanently lost due to the die off (Carlson, et al. 1990 ; Durako and Zieman 2007) making that bottom now available for enhanced benthic algal production, varying from a thin film of diatoms ov er relatively unconsolidated sediments to inch thick Laurencia sp. mats carpeting the bottom.

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55 Figure 3.1. October 2005, Map of colored water in Florida Bay. Reproduced with permission, FWC FWRI. Figure 3.2. November 1995, Map of colored water in Florida Bay. Reproduced with permission FWC FWRI.

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56 Figure 3.3. December 1995, map of colored water in Florida Bay. Reproduced with permission, FWC FWRI. The contribution of benthic microalga l productivity in s eemingly unvegetated bottom areas to the baywide primary productivity has also not been quantified. Approxima tely one third of the 2200km 2 bay is unvegetated inter or sub tidal bottom ( Prager and Halley, 1997 ) and about 4000 hectares of seagrass have be en permanently lost due to the die off (Carlson, et al. 1990 ; Durako and Zieman 2007) making that bottom now available for enhanced benthic algal production, varying from a thin film of diatoms over relatively unconsolidated sediments to inch thick Lauren cia sp. mats carpeting the bottom. Coarser coral algal sediments are found in the eastern region of the bay (Fourqurean et al. 1993). Fine grained mud or sands are prevalent elsewhere, especially in the more restricted basins. These fine grained sedimen ts and the attached or free living microalgae are susceptible to resuspension into the water column. Many different causes of benthic microalgal resuspension have been suggested, ranging from continental shelf sediments stirred up by the passage of hurri canes and strong storms off North Carolina (Cahoon and Cooke, 1992) to resuspension of both fine and coarse grained sediments by tides and waves (MacIntyre and Cullen, 1996; Baillie

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57 and Welsh, 1980). The latter forces would probably be most implicated in Florida Bay given its shallow depth In fact, I have personally observed that a sustained 10 20 knot wind has reduced secchi depth from >1m to <0.4m in a matter of minutes in western Florida Bay. Resuspension of sediments during sustained wind events ha s been less evident to me in central and southeastern Florida Bay, but, algal blooms do decrease water clarity at these locations. Goals and objectives The purpose of this study was to determine the chlorophyll a concentration of microphytobenthos in Flori da Bay and calculate the potential areal benthic microalgal producti on These are key measurements to include in any model of Florida Bay. The goal w as to m easure the temporal and spatial distribution of benthic microalgal chlorophyll a within Florida Bay. Specifically, whether benthic microalgal biomass contributes significantly to the overall ecosystem primary productivity where seagrasses are sparse or absent a nd if benthic microalgal chlorophyll values vary seasonally or spatially Materials and methods Samples were collected from three locations within Florida Bay, USA between May 2000 and August 2002. Sampling sites were Whipray Basin, Arsnicker Keys, and Carl Ross/Sandy Key; providing representation of n orth central, southeas tern and western Florida Bay, respectively. The Carl Ross/Sandy Key location was representative of intertidal environments in the bay, while the other two locations were both representative of subtidal microphytobenthos. Chlorophyll is a lipophilic molec ule a good electron donor and receptor (when oxidized) and probably the most abundant biological pigment on earth (Lawlor, 2001). Benthic chlorophyll samples were collected at the end of the sampling day from sediment where benthic nutrient flux chambers (light and dark, ~7 liter volume) had been deployed for coincident nutrient flux measurements throughout the day. Five replicates sediment mini cores selected by chance were taken from within the 0.06m 2 area of sediment the chamber enclosed. Usually 4 o r 5 chambers were deployed resulting in up to 25 benthic chlorophyll samples per sampling day.

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58 Mini corers were 10cc syringes with the ends cut off unger to preserve the upper layer containing the majority of the benthic microalgae. Due to the mini corer prior to removal from the sediment. Seagrasses, macroalgae and lar ge debris wer e removed from the mini cores. Mini c ores were standardized to 2cm depth, with any excess sediment below 2cm depth expelled from the plunger prior to capping with P arafilm strips. Replicate samples were placed into bags labeled with the chamber treatmen t, date and location and placed on ice for immediate transport back to the laboratory at USF. There was undoubtedly some degradation in chlorophyll a due to storage on ice for ~10 hours until freezing at the laboratory, but this was the most practical sam pling and transport method. Every sample was treated this way so the associated sampling error would be consistent among samples. Samples were held for up to 2 months at 18C prior to extraction in 90% acetone with hexane fractionation, according to the method outlined by Whitney and Darly ( 1979 ) The only deviation from this procedure was the elimination of the addition of MgCO 3 which was determined to be an unnecessary process. The Whitney and Darly ( 1979 ) method minimizes overestimation of chloroph yll a caused by chlorophyllide a contamination (a degradation product) which absorbs light in the same wavelengths as chlorophyll a Chlorophyll a most strongly absorbs light at 430 and 660nm wavelengths. Briefly, this procedure requires extraction of the sediment in 9 0% acetone for 12 24 hours at 4C in the dark. Then samples are centrifuged and decanted into separatory funnels to which hexane is then added. The acetone/hexane mixture is then shaken vigorously on a reciprocating shaker for 5 minutes. The acetone fraction, containing the chlorophyllide a and other degradation products, is then drained off the bottom and the overlying hexane fract ion, containing the viable chlorophyll, is analyzed spectrophotometrically. The hexane fractions of the samples were measured, using a Beckman DU520 spectrophotometer at four wavelengths both before and 2 minutes after acidification with 50% hydrochlori c acid. This yield ed measurements for chlorophyll a, b and

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59 phaeopigments other than chlorophyllide a Replicate benthic chlorophyll samples were pooled for each treatment chamber for each sampling day and location. Benthic chlorophyll a and phaeopigme nt concentrations were determined on an areal basis (mg Chl a m 2 ) for the upper 2cm of sediment. Jennifer Jurado, University of Miami collected water column chlorophyll a samples at the start of the sampling day only at the western Florida Bay location. A known volume of ambient station water was filtered through a GF/F filter in the field and stored in the dark in aluminum foil on ice until she returned to the laboratory. Samples were then frozen at 0C for up to 2 weeks until analysis. Samples were e xtracted in 100% methanol with DMSO according to the method of Shoaf and Lium, (1976) by Jennifer Jurado at the University of Miami. Samples were analyzed fluorometrically using a Turner Designs Model 10AU fluorometer both before and after acidification with 1N hydrochloric acid Results Benthic chlorophyll a values show seasonal patterns and interannual variability in Florida Bay. Benthic chlorophyll a values ranged from 0.56 112 mg Chl a m 2 throughout the bay. Benthic phaeopigment values range d from 7.07 to ~350 mg phaeopigments m 2 The average baywide chlorophyll a value during my study was 1 4.98 mg C hl a m 2 The average baywide phaeopigment value during my study was 72. 79 mg C hl a m 2 Depth integrated water column values from western Florida Bay ranged from 0.58 2.63 mg Chl a m 2 but averaged 1.48 mg Chl a m 2 (Table 3.3). Phaeopigments dominated the pigment ratio spatially and temporally in the bay. The average chlorophyll a for all Florida Bay samples was 23% of the measured pigment per sample (ranged from 1 86%), and very rarely exceeded 50% (<1% of the total number of samples). Benthic microalgal biomass contained proportionally more phaeopigment than water column measurements a bout 55 93% phaeopigment (Figs. 3.4 3.6 ) when averaged among replicates compared to about 40% phaeopigment in the water column This was due to the accumulation of dead plant matter at the sediment water interface (pelagic phytoplankton, macroalgal and seagrass detritus).

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60 My sediment pigment values were also similar to those measured subtidally on the WFS near the middle grounds ( Darrow et al. 2003 and Vargo, unpublished data). Highest chlorophyll concentrations in the bay were found during the summer, lower concent r ations were found in the wintertime ( Figs.3.4 3.6 ) and coincident with fall phytoplankton blooms in the western bay (Fig. 3.4 ). Figure 3.4 Mean chlorophyll a and phaeopigment in western Florida Bay f rom replicate sediment cores ( first Y axis ) and a single water column sample when applicable ( second Y axis ) Error bars represent the standard error of replicate samples. Note that the 1 st and 2 nd Y axis scales differ by an order of magnitude. This station represents the intertidal micro phytobenthos. The water column data was provided by Jennifer Jurado, University of Miami.

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61 B enthic chlorophyll a values near Carl Ross Key in western Florida Bay were 5 75 times greater than water column concentrations during non bloom conditions (Fig. 3. 4). Depth integrated water column concentrations were equal to benthic concentrations during blooms (8.3 27.4 mg C hl a m 2 ) in western Florida Bay based upon earlier measurements by Vargo, et al (1999, 2001). Average benthic chlorophyll a in the inter tidal western bay was 17.4 mg m 2 and phaeopigment was 91.6 mg m 2 A seasonal trend in benthic chlorophyll a concentration is evident in the data with highest values in the spring and summer and lowest values in the winter (Fig. 3.4). This is in contras t to water column chlorophyll a with peaks in the fall and winter coincident with the seasonal diatom bloom (Jurado and Hitchcock, 2001). Peaks in benthic phaeopigment followed the seasonal peaks in benthic chlorophyll in the western bay, being highest in the early summer and late fall winter. Phaeopigment at the western Florida Bay also had the highest phaeopigments compared (p<0.001) to the central and southeastern sites. Table 3.3 Ranges and average pigment values for water column and benthic microalgae in Florida Bay. Location Water chl a Benthic Chl a Benthic Phaeo (mg m 2 ) (mg m 2 ) (mg m 2 ) Western Range 0.58 2.63 0.56 111.77 7.07 350 Average 1.48 17.39 91.58 Central Range 2.26 42.9 10.2 77.71 Average 9.17 28.32 Southeastern Range 3.39 35 27.12 153 Average 17.43 61.07

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62 Figure 3.5 Mean chlorophyll a and phaeopigment for replicate sediment cores in central Florida Bay. Error bars represent the standard error of replicate samples. This site was representative of subtidal microphytobenthos. Central Florida B ay chlorophyll a and phaeopigment values appeared more stable seasonally (Fig. 3.5), however, there were fewer sampling dates over a shorter time period at this location than western Florida Bay. There was much less variability between sampling dates, however, the lowest values were still found in the fall and winter and the highest in the summer. Average benthic chlorophyll a in the central bay was 9.17 mg m 2 and phaeopigment was 28.3 mg m 2 Highest phaeopigments in the central bay were found during and after summer 2001 bloom in the water column, otherwise benthic phaeopigment and chlorophyll a at this location remained fairly constant. A bloom did not occur at this location the following summer. Average phaeopiment was the lowest of the three sites and significantly different from the other two locations (p<0.001).

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63 Figure 3.6 Mean chlorophyll a and phaeopigment for replicate sediment cores in southeastern Florida Bay. Error bars represent the standard error of replicate samples. This site was representative of subtidal microphytobenthos. Southeastern Florida Bay was only sampled on three occasions for benthic chlorophyll a and always in the spring/summer (Fig. 3.6) Average benthic chlorophyll a in the southeastern bay was 17.4 mg m 2 and phaeopigment was 61.1 mg m 2 Samples taken in the central bay during the same time period were comparable in chlorophyll a magnitude to those from the southeast bay. P haeopigment in the southeast was significantly different from the other two locations (p<0.001), but limited sampling prevented an analysis of seasonal differences in phaeopigment at this location. Statistical analysis All chlorophyll a measurements were normally distributed and expressed homogeneous variance s, therefore parametric statistics were used to analyze differences between the locations and treatments Using a one way ANOVA, there was no statistical

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64 difference in chlorophyll a or phaeopigment between light and dark chambers at all locations. However, all the study sites were significantly differen t from each other (Table 3.4). The synoptic sampling events in July 2001 and May 2002 support this finding. Similar results were f ound when only the July 2001 and May 2002 samples from the southeastern and central stations were compared using a one way ANOVA. Table 3.4 ANOVA levels of significance for comparison of chlorophyll a and phaeopigment among locations Discussion The average measurements of chlorophyll a concentration from my study in Florida Bay, while comparable to other measurements from Florida, were less than those reported by others working in both temperate an d tropical environments (Cahoon, 1999; Ulthicke and Klumpp, 1997). P ossible explanation s for this difference between Florida Bay and temperate waters include nutrient limitation of biomass and grazing pressure on the microphytobenthos. However, the micro phytobenthic chlorophyll a concentration substantially exceeded water column chlorophyll a concentration underscoring the importance of quantifiying benthic microalgal production in areas of the bay not vegetated by seagrasses and sediment nutrient dynamic s. Based upon my average areal chlorophyll a measurement and the estimation of the unvegetated portion of the bay at 773 km 2 areal benthic microalgal biomass in Florida Bay would be 708.84 kg Chl a The similarity in biomass values between light and dark chambers likely stems from the 2 cm depth of my sample cores and that they were collected from an enclosed chamber which was inserted into the sediment This procedure likely captur ed the cells within a confined area despite any treatment effect on verti cal or horizontal migration Location Benthic Chl a Benthic Phaeo West v Central <0.001 <0.001 West v Southeast <0.01 <0.001 Central v Southeast <0.01 <0.001

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65 Although initially similar, Aller et al. (2001) found that chl orophyll a in diffusively open sediment degraded at different rates after about 10 days under oxic and anoxic conditions. This was the result of both reactivity rat e and comparative pool size under anoxic conditions b ut decomposition was favored under oxic conditions. Re exposure and re oxidation of sediments by bioturbation or resuspension translates into permanent decreases in carbon preservation when compared to unidirectional burial or continuously anoxic conditions. The r edox layer is very shallow in Florida Bay sediments. Sediments are easily resuspended by winds and bioturbation as well. Both these factors favor preservation of chlorophyll a and carbon buri ed in Florida Bay sediments. The similarity in benthic microalgal biomass among sample locations is surprising given the differences in dissolved nutrient availability and sediment type across Florida Bay. However, r esults were variable among chambers wh ich would reduce the probability for statistical significance between locations. There were no significant difference s in benthic chlorophyll concentration between light and dark chambers ( p >0.05). There was variability among some chambers on a sampling date and this was caused by patchiness. This patchiness has been reported by many researchers, and is not restricted to benthic microalgal communities. Variability in available nutrients within sediment can arise through biological, chemical and physical properties, including bioturbation. Redox changes not only affect nutrient availability, but also the micro community (Aller, et al. 2001). Other physical forces, including fluid dynamics of porous sediments as a result of microtopography can affect the nutrient microhabitat (Huettel and Gust, 1992). Temporal differences in benthic microalgal biomass, particularly in western Florida Bay were evident. The pattern of higher benthic microalgal biomass in the summer, coincident with lower water column bio mass is consistent with greater light transmission to the bottom as well as warmer water temperatures. Lower microalgal chlorophyll a concentration in the winter was coincident with increased water column chlorophyll a concentration possibly as a result of diatom blooms or sediment resuspension due to the passage of fronts. This temporal pattern did not hold true at the other locations. This may have been due fewer sampling events or the fact that the other

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66 two locations were subtidal compa red to intertidal western Florida Bay. However, diminished benthic microalgal chlorophyll a concentration was noted in the central region during the summer of 2001 when a major water column bloom was ongoing. This suggests microphytobenthic chlorophyll a concentration may be more regulated by light availability and secondarily by temperature in Florida Bay. Summary Changes in potential areal microphytobenthic production resulting from perturbations like seagrass die off, may be offset in some areas of Flo rida Bay by other perturbations pelagic phytoplankton blooms and increased turbidity diminishing light to the bottom. Temporal but not spatial differences were evident in microphytobenthic chlorophyll a concentration across the bay, despite anticipated nutrient limitation. Small scale patchiness was evident in chlorophyll a concentration measurements, as a result of microhabitats and bioturbation. Chlorophyll a concentration values in my study were similar to other measurements from Florida, but less than temperate and other tropical systems. As in other studies, the benthic microalgal chlorophyll a concentration equaled or far exceeded that of the water column, yet it remains relatively uninvestigated and not included in modeling efforts for Florida B ay. In summary, my results have shown that microphytobenthic production as evidenced by BMA chlorophyll a concentration, would be an important component to overall primary production in Florida Bay and should be included in existing and future monitoring programs and modeling efforts.

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67 Chapter 4. Mesocosm bioassays as a tool to investigate microalgal benthic pelagic coupling in Florida Bay Introduction Benthic microalgae are important contributors to primary productivity in areas where the euphotic zone intercepts the bottom, with chlorophyll a standing stock often exceeding that of the water column (MacIntyre et al. 1996; Cahoon, 1992). This is particu larly true in Florida Bay, a shallow subtropical lagoon located at the southern tip of peninsular Florida. Florida Bay is a large estuary, about 2200 km 2 with an average depth of <2m. It is bounded to the north by the Everglades, to the east by the Flo rida Keys and to the west by the Gulf of Mexico (Schomer and Drew, 1982). Florida Bay has been the subject of (Durako and Zieman 2007; Carlson et al. 1999; Butler et al. 199 5; Phlips et al. 1995) and recent efforts at Everglades restoration (Rudnick et al. 1999). The Gulf of Mexico, the Atlantic Ocean, and the Everglades are the three primary sources of water input to Florida Bay (Schomer and Drew, 1982). The Everglades have undergone extensive water redistribution projects during the last century in an effort to reduce flooding and provide drinking water to urbanized areas of south Florida, and for irrigation of the expanding agricultural interests of the area (Schomer and D rew, 1982; Smith et al. 1989). These water sources and their associated nutrient load drive primary productivity. Although poorly quantified, o ther important sources of nutrients to the Bay include atmospheric deposition and benthic flux from both ground water in the Everglades region and sediment porewaters in the Bay itself (Price, 2005). Florida Bay Nutrient Limitation Among all the resources necessary for growth or maintenance of an organism, that in shortest supply is considered limiting. Nutrients limit phytoplankton and seagrass biomass and primary productivity in Florida Bay (Fourqurean et al. 1992; Fourqurean et al. 1993; Phlips et al. 1995; Phlips and Badylak, 1996; Kelble et al. 2005). Light may

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68 also limit benthic primary productivity in some regions of the bay and at certain times of year when blooms or turbidity reduce transparency. However, due to the shallowness of Florida bay and typically clear waters, light is not generally limiting to primary production (Kelble et al. 2005). Many rese archers have documented patterns in water column nutrient availability in the bay beginning with Fourqurean et al. (1993). Phosphorus is in very low concentrations, near the limits of detection, in a majority of the Bay. The greatest concentrations of P are found in the western Bay where Gulf of Mexico water is P enriched in comparison to the remain der of the bay. Dissolved nitrogen is available in such high concentrations in the bay that it is not considered limiting except during phytoplankton blooms. This general trend has been supported by several other researchers in large and small scale field and laboratory studies (Vargo et al. 2001 a and b ; Jurado and Hitchcock 2003 ; Brand et al 2001). The relationship between dissolved nutrient supply and phytoplankton demand is neither simple, nor static. Diversity among phytoplankton includes nutr ient preference, reducing competition for a limited resource Temporal and spatial variation in nutrient limitation occurs in coastal areas where nutrified freshwater mixes with oligotrophic marine water, rather than the steady state condition of either e nd member. Bioassays have been used to identify conditions that limit phytoplankton growth and biomass. (D'Elia et al. 1986 ; Pennock and Sharp 1994 ; Smith and Hitchcock, 1996; Jurado and Hitchcock, 2003 ).

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69 Figure 4.1 (reproduced from Tomas et al. 199 9, with permission) Depiction of nutrient limitation zones within Florida Bay based upon bioassays of natural pelagic phytoplankton populations, from Tomas et al. 1999. Zone A represents areas where nitrogen and possibly silica are limiting during most o f the year. Zone B represents areas where primarily N and sometimes P were limiting. Zone C represents areas primarily P limiting with rare N limitation. Tomas et al. (1995 & 1999) used nutrient bioassays to determine growth rate and chlorophyll bioma ss for natural pelagic phytoplankton populations. They described phosphate (P) limitation increasing across Florida Bay from West to East in the pelagic population and indicated that nitrogen (N) and silica (Si) can be co limiting in western Florida Bay du ring the annual winter diatom bloom (Figure 4.1). Central Florida Bay varies between N and P limitation (Fourqurean et al. 1992; Fourqurean et al. 1993; Phlips

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70 and Badylak, 1996; Tomas et al. 199 9 ). However, N or P limitation was dependent upon the pe lagic phytoplankton community structure and standing stock. Resources can be limiting to phytoplankton in several ways. At the most basic level, N and P are necessary components to cellular processes that regulate primary production like nucleic acids and ATP. Species can differ in their uptake efficiency, allo wing those species to more rapidly accumulate nutrients available in short supply or species may differ in their growth rate allowing faster growing species to dominate the community and utilize more resources or both. Competition for nutrient resources is at the core of both scenarios. From a management perspective, factors affecting phytoplankton growth and biomass are most relevant, because the input of N and P can be controlled while community structure, competition and primary production cannot. Nutrient limitation of pelagic phytoplankton growth and biomass (Tomas et al. 1999) and dissolved nutrient availability (Fourqurean et al. 1993) are well documented in Florida Bay, but do not always coincide spatially Nutrient availability does not acco unt for remineralization and the importance of the microbial loop. Bioassays Hydrodynamic and biological models of the Bay are being fine tuned to assist managers in making distribution and water quality decisions as part of restoration efforts. Since l imiting resources, e.g. nutrients in Florida Bay, are important controls on primary production, and thus higher trophic level production, it is important to quantify the spatial and temporal differences in nutrient limitation of production and biomass. A lthough often ignored, and certainly undersampled in comparison to pelagic phytoplankton and seagrass primary production, b enthic microalgae are significant sources of primary produc tion Their proximity to the sediment and buried nutrients is often presu med to relieve them of the nutrient limitation that pelagic phytoplankton might suffer (Sundback and McGlathery, 2005). However, this is not necessarily true, especially in Florida Bay where the carbonate sediments tightly bind phosphate through chemical mechanisms. This is coupled with a relatively low concentration of iron bound phosphorus which would be likely to release P to the sediment porewaters during redox reactions under anoxic conditions (Nixon et al. 1980; Krom and Berner 1981 ; Caraco et

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71 al. 1992 ). But, balancing this is a shallow redox zone minimizing the thickness of the diffusive layer through which any loosely bound sedimentary P would have to travel. As a result of this capacity for release of sediment phosphorus, nitrogen limitation is most often implicated for marine waters (Ryther and Dunstan, 1971; Howarth, 1988). Lesser nitrogen fixation rates (Howarth 1988) an d greater denitrification rates (Seitzinger 1988) compared to freshwater systems are also contributing factors to N limit ation in marine waters Si lica limitation of diatoms has also been reported in Florida Bay ( Tomas et al. 1999; Jurado and Hitchcock, 2001 ) and coastal regions (Malone et al. 1980 ; Officer and Ryther 1980). Mesocosm bioassays are one tool to assess nutrien t limitation of algal biomass (Elser et al. 1988; Tomas et al. 1999). Which nutrient is limiting is determined by comparing the changes in algal biomass ( g chl a L 1 ) or growth rates after additions of the limiting nutrient alone and in combination with other nutrients over several days to control assays These types of assays were performed at two sites in Florida Bay to examine if the nutrient(s) limiting benthic microalgal biomass differ(s) between western and central Florida Bay and if the nutrients limiting benthic microalgal biomass differ spatially and temporally from those that limit pelagic microalgal production. Materials and methods Sediment was collected from two field sampling sites; Carl Ross Key in western Florida Bay and Whipray Basin i n central Florida Bay (Fig. 4.2). Sediments ~ 4cm deep were placed into the mesocosms constructed of shallow, clear plastic boxes (17.5cm wide x 15 cm tall x 32.5 cm long) containing a coiled tubing nutrient delivery s ystem in the bottom. A single experi ment was conducted in August 2002 at the central Florida Bay location and in January 2003 at both locations. After filling at the field site, the mesocosms (Fig. 4.3) were transported to the Keys Marine Laboratory in Layton, FL where they were placed into a water table that circulated ambient seawater to maintain temperature for the duration of the experiment. The mesocosms were exposed to ambient light, but were protected from evaporation and rainfall by a thin layer of plastic food wrap over the top of the mesocosm which was secured by a thin plastic rim. Water overlying the sediment in each mesocosm was

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72 removed and replaced with 2 liters of 0.45 filtered water collected from the field site. A gentle circulation device (miniature water pump) was placed in each mesocosm to continuously recirculate the water column above the sediments. Once these preparations were complete, the benthic microalgal c ommunity within the mesocosm was allowed to equilibrate for ~48 hours prior to commencing the experiment. Figure 4.2. The site locations where sediment and water were collected for the mesocosm experiments, Carl Ross Key and End Key. The sites are con sidered representative of western and central Florida Bay, respectively.

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73 Figure 4.3. The mesocosms arranged in the randomized block design within the lagoonal flow through seawater system at the field laboratory in Layton, FL. Dissolved nutrient availability in the water column was measured as the change in concentration over time. Nutrients were only added to the sediment so increases in dissolved nutrients in the water column had to come from benthic flux. Three nutrien t treatments (N alone, P alone, and NP) and controls (no nutrient additions) were tested. Triplicate mesocosms were sampled for each treatment and control utilizing a randomized block experimental design to assign treatments to the mesocosms in the ambien t seawater bath enclosure. Inorganic forms of N (NH 4 Cl) and P (KH 2 PO 4 ) were added to the sediment daily through tubes buried in the sediment followed by a flush of ambient water from the mesocosm to ensure complete delivery of the nutrient pulse to the s ediment. The daily concentrations added were 0.667 M L 1 PO 4 5.33 M L 1 NH 4 Control mesocosms had the nutrient delivery tubing in the bottom but received only

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74 flushes of ambient water from the mesocosms. The nutrient concentrations in the water column were sampled immediately before and after the nutrient/ambient water additions. Samples were collected at approximately the same time each morning. Th e methods of Solrzano and Sharp (1980) for total dissolved phosphate (TDP) and soluble reactive phosph ate (SRP), Valderama (1981) for total dissolved nitrogen (TDN) and Gordon et al. ( 1993) for inorganic nutrients were used. Dissolved organic nitrogen (DON) and dissolved organic phosphate (DOP) were determined by subtraction of the inorganic forms I measu red from total values. Initial salinities were maintained by the addition of MilliQ water. Temperature and salinity were recorded daily. Three benthic chlorophyll cores (top ~1 cm of sediment) and one or two water column chlorophyll samples were taken d aily immediately prior to the nutrient addition. Experiments were maintained for at least six days plus the initial equilibration period. Changes in chlorophyll a photochemical Yield (PAM fluorometer) and dissolved nutrient s as a function of nutrient e nrichment in the treatment mesocosms were measured against the control mesocosms as indications of limiting nutrients. The summer 2002 experiment was limited to the central Florida Bay only, due to logistics. A rain event caused contamination in the mes ocosms on the evening of Day 6, dropping salinity by ~50% and potentially providing an unquantified input of atmospheric N and P in the form of rainwater. This experiment was nine days in duration. No nutrient additions were made after the rainfall contamination although measurements continued The winter 2003 experiments were conducted at locations in western and central Florida Bay. The experiments were conducted during the passage of a cold front, which persisted from Day 2 through Day 6. The se experiments were seven days in duration. Nutrient additions and dissolved nutrient measurements were made only for the first seven days in the summer experiment and the first two days and the final day in the winter experiment. The benthic microalgal biomass was measured for nine days in the summer experiments and seven days in the winter experiment, to ensure sufficient time elapsed for a change in biomass to occur.

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75 Results Nutrients: Initial Field C onditions Conditions at the time when the field collection of sediment for the mesocosm experiments occurred will be discussed first and are summarized in Table 1. Central Florida Bay showed some overlap in the initial TDP concentration of the water column at the c ollection site for both mesocosm experiments. TDP was greater in the western than central portion of the bay, in keeping with the in situ chamber findings outlined elsewhere in this dissertation. Water column SRP at the collection site was initially nea r the limits of detection in central Florida Bay mesocosms during the winter experiments, but was an order of magnitude greater in the summer at the same location. Water column SRP at the collection site was initially greater in western Florida Bay compar ed to central Florida Bay in the winter experiment, mirroring the TDP findings. Table 4.1. Initial nutrient field concentration in M L 1 with the predicted limiting nutrient determined from the Redfield Ratio of the listed nutrient species of available dissolved nutrients. At both locations, dissolved silica was much greater (~5 times) initially in summer, but both had similar ranges in winter. During the winter, nitrite was initially at

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76 the limit of detection in western Flor ida Bay. Average initial nitrite was higher in central Florida Bay in January than in August. Nitrate+nitrite was also at the limits of detection in western Florida Bay in January and central Florida Bay in August. Nitrate+Nitrite was at its greatest c oncentration in January in central Florida Bay and about of this was due to nitrite. Mesocosm results The results of the multi day mesocosm experiments were mixed. In central Florida Bay TDP concentrations w ere variable throughout the experiment, with f ew significant differences between treatments and control (Figs. 4.4 and 4.5). Despite the P additions, TDP did not accumulate in the water column during the two experiments (n=6). The increase in TDP concentration on August 7 th could be the result of hi gher concentration nutrient additions that were accidently applied to some unidentified mesocosms. However in western Florida Bay mesocosms, TDP did accumulate in the water column in the P and the NP treatment additions (Fig. 4.6). This difference was sig nificant when compared to the N and control treatments by Dday 2 of the experiment. TDP in the P only treatment differed significantly from the NP addition and this also occurred by Day 2 of the experiment. Water column TDP concentration increased throug hout the course of the experiment in the P addition, but after an initial increase instead remained level after Day 2 in the NP treatment. SRP was variable during both mesocosm experiments using sediment from central Florida Bay (Figs. 4.7 and 4.8). The winter experiment did not reveal any statistically significant differences between treatments and controls except for the first two days of the experiment. In the summer, there were significant differences between P addition treatments for the first, thi rd and fourth days of the experiment. SRP always decreased in the water column throughout the duration of the experiment in central Florida Bay, regardless of treatment, however, this trend was not statistically significant. Presumabley this loss was to the BMA community. The increase in SRP concentration on August 7 th could be the result of higher concentration nutrient additions that were accidently applied to some unidentified mesocosms.

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77 In western Florida Bay, SRP did lea ve the sediment and accumulate in the water column in the P and the NP treatment additions (Fig 4. 9). This difference was significant in these treatments versus the N only and the control by D ay 2 of the experiment. The P and NP additions differed signi ficantly from each other and N and control by D ay 2 of the experiment. As seen with TDP, accumulation of SRP in the overlying water column did not increase throughout the experiment in the NP treatment, but instead remained level or slightly decreased aft er Day 2. Central Florida Bay mesocosms were significantly different by treatment from each other on Days 1 and 2 of the experiment only in January and Days 1, 3 and 4 in the August experiment. Figure 4.4. Average TDP results from replicate samples of t riplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) during winter. The sample dates appear on the x axis. The error bars represent the standard error, and are on ly shown in one direction to facilitate viewing.

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78 Figure 4.5. Average TDP results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin ) during summer. The sample dates appear on the x axis. The error bars represent the standard error, and are only shown in one direction to facilitate viewing.

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79 Figure 4.6. Average TDP results from replicate samples of triplicate nutrient addition treat ments (N, P, N and P, and Control) in mesocosms using sediment from western Florida Bay (Carl Ross Key) in winter. The sample dates appear on the x axis. The error bars represent the standard error, and are only shown in one direction to facilitate viewin g.

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80 Figure 4.7. Average SRP results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in winter. The sample dates appear on the x axis. The error bars represent the standard error, and are only shown in one direction to facilitate viewing.

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81 Figure 4.8. Average SRP results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in summer. The sample dates appear on the x axis. The error bars represent the standard error, and are only shown in one direction to facilitate viewing.

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82 F igure 4.9. Average SRP results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from western Florida Bay (Carl Ross Key) in winter. The sample dates appear on the x axis. The error bars represent the standard error, and are only shown in one direction to facilitate viewing. TDN was variable in the three mesocosm experiments (Figs. 4.10 4.12). TDN concentration increased over time in all three experiments for the N addition treatme nts. The NP treatment showed similar results for both locations during the winter experiment (Figs. 4.11 12). During the summer experiment TDN concentration in the water column was balanced by uptake in the phytoplankton, either benthic or pelagic, by Da y 4, and actually resulted in loss of TDN from the water column by Day 7 (Fig. 4.10). The control and P only treatments did not show an increase in TDN except in January 2003 in the central Florida Bay when all mesocosms had greater concentrations by the end of the experiment (Fig. 4.12). The increase in TDN concentration on August 7 th could be the

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83 result of higher concentration nutrient additions that were accidently applied to some unidentified mesocosms. During the summer experiment, statistically sign ificant differences in water column TDN concentrations were found by Day 3 in the N, and NP, addition treatments versus P only, and controls. Significant differences were noted between N and NP addition treatments versus P only and controls at the conclus ion of the winter central Florida Bay experiment, but were not evident during the first two days of the experiment. Due to high variability between samples within treatments, western Florida Bay mesocosm treatments did not exhibit statistically significa nt differences, but followed the same trend with higher TDN concentrations in the overlying water column in the N and NP addition treatments, respectively. At the conclusion of the experiment, TDN was mostly organic forms of nitrogen and possibly ammonium Because ammonium values were offscale (at the upper limit of detection), I was unable to determine the proportion of ammonium present in the TDN.

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84 Figure 4.10. Average TDN results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in summer. The sample dates appear on the x axis. The error bars represent the standard error, and are only shown in one direction to facilitate vi ewing.

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85 Figure 4.11. Average TDN results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from western Florida Bay (Carl Ross Key) in winter. The sample dates appear on the x axis. The error bars represent the standard error, and are only shown in one direction to facilitate viewing.

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86 Figure 4.12. Average TDN results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in winter. The sample dates appear on the x axis. The error bars represent the standard error, and are only shown in one direction to facilitate viewing. Central Florida Bay mesocosms in the summer all showed a dramatic drop in dissolved silica concentration in the water column between Days 1 and 4 in all treatments (Fig. 4.13). By Day 5 the dissolved silica concentration decreases in all but the NP treat ments, followed by another drop on day 6 and another dramatic increase on Day 7. There was high variability among replicates pointing to a potential error in the laboratory analysis. The high values for NP on Days 5 and 7 were replicated among samples, bu t the winter experiments, dissolved silica increased by the second day of the experiment and on the final day remained the same or decreased again to levels similar to Day 1 (Figs. 4.14 15). Again, P treatments had the lowest average dissolved silica value of

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87 either treatment or controls. High variability in the second sample again indicates a potential error in the laboratory analysis, among replicates analyzed on different days. Figure 4.13. Average silica results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in summer. The sample dates appear on the x axis. The error bars represent the standard error, and are only shown in one direction to facilitate viewing.

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88 Figure 4.14. Average silica results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and C ontrol) in mesocosms using sediment from western Florida Bay (Carl Ross Key) in winter. The sample dates appear on the x axis. The error bars represent the standard error, and are only shown in one direction to facilitate viewing.

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89 Figure 4.15. Averag e silica results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in winter. The sample dates appear on the x axis. The error bars represent the standard error, and are only shown in one direction to facilitate viewing. Dissolved nitrite in central Florida bay mesocosms during summer showed significant differences among treatments by Day 2 of the experiment (Fig. 4.16). In contrast to the silica concentration pattern for Days 4 6, the nitrite peaked on Day 5, dropping back to levels similar to Days 2 5 on the final day for the N treatments, and to below the limits of detection in the NP treatments. As expected N, followed by NP trea tments were always greater in dissolved nitrite than controls and P treatments, except the NP treatments on Day 6, as mentioned previously. The increase in nitrite concentration on August 7 th could be the result of higher concentration nutrient additions t hat were accidently applied to some unidentified mesocosms.

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90 During the winter, nitrite was initially below the limit of detection in western Florida Bay (Fig. 4.17). By day 2 of the mesocosm experiment it was measureable, but still very low and there were not significant differences between treatments. This same result was found on the last day of the experiment in western Florida Bay mesocosms. Central Florida Bay mesocosms showed a drop in N, NP and controls on day two, while P remained near the values for day 1 (Fig. 4.18). None of these differences was significant however. By the last day of the experiment, nitrite levels in the N, NP and controls were similar in concentration to the start of the experiment, but again not significantly different fro m each other. Figure 4.16. Average nitrite results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in summer. The sample dates appear on the x axis. The error bars represent the standard error, and are only shown in one direction to facilitate viewing.

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91 Figure 4.17. Average nitrite results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and C ontrol) in mesocosms using sediment from western Florida Bay (Carl Ross Key) in winter. The sample dates appear on the x axis. The error bars represent the standard error, and are only shown in one direction to facilitate viewing.

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92 Figure 4.18. Average nitrite results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in winter. The sample dates appear on the x axis. The er ror bars represent the standard error, and are only shown in one direction to facilitate viewing. Nitrate+nitrite generally mirrored the nitrite patterns (Figs. 4.19 4.21), with one exception. In winter in western Florida Bay, significant differences wer e found between treatments and controls by the end of the experiment (Fig. 4.20). Nitrate+nitrite values were an order of magnitude greater than nitrite alone in western Florida, but only 2 3 times as great in central Florida Bay, indicating there was lit tle available nitrate at this location. The increase in Nitrate+nitrite concentration on August 7 th could be the result of higher concentration nutrient additions that were accidently applied to some unidentified mesocosms.

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93 Figure 4.19. Average nitrate plus nitrite results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in summer. The sample dates appear on the x axis. The error bars represent the standard error, and are only shown in one direction to facilitate viewing.

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94 Figure 4.20. Average nitrate plus nitrite results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from western Florida Bay (Carl Ross Key) in winter. The sample dates appear on the x axis. The error bars represent the standard error, and are only shown in one direction to facilitate viewing.

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95 Figure 4.21. Average nitrate plus nitrite results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in winter. The sample dates appear on the x axis. The error bars represen t the standard error, and are only shown in one direction to facilitate viewing. Central Florida Bay mesocosms showed clear differences in ammonium concentration between both N and NP treatments and P only treatments as well as controls in the summer (Fig 4.22) but not the winter experiments (Fig. 4.23). Ammonium was near the upper limit of detection in the summer by the third day for the N and NP treatments in the summer experiment. In the winter at both locations (Fig. 4.23 and 4.24), ammonium was at the upper limit of detection by the second day of the experiment for all treatments and controls. Because of this, differences between treatments were not able to be determined during the winter.

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96 Figure 4.22. Average ammonium results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in summer. The sample dates appear on the x axis. The error bars represent the standard error, a nd are only shown in one direction to facilitate viewing.

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97 Figure 4.23. Average ammonium results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from central Florida Bay (End Key, Whipray Basin) in winter. The sample dates appear on the x axis. The error bars represent the standard error, and are only shown in one direction to facilitate viewing.

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98 Figure 4.24. Average ammonium results from replicate samples of triplicate nutrient addition treatments (N, P, N and P, and Control) in mesocosms using sediment from western Florida Bay (Carl Ross Key) in winter. The sample dates appear on the x axis. The error bars represent the standard error, and are only shown in one direction to facilitate viewing. Chlorophyll concentration A positive response to nutrient additions was seen in both the water column and the sediment microalgal communities in central Florida Bay in the summer mesocosm experiment. Both responded positively to the combined NP addition with an increase in chlorophyll a standing stock. However, the communities responded differently when either N or P was added. Based on chlorophyll a standing stock the central Florida Bay water column community was initially P limited and then by August 6 th was N limited, while P additions still elicited a significant difference from controls (Fig. 4.25). This condition persisted throughout the remainder of the ex periment even after a rainstorm dramatically dropped the salinity in the mesocosms and introduced an unknown amount of N and P into all the mesocosms.

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99 On August 5 th N addition treatments in the sediment community were significantly lower in chlorophyll a standing stock than control treatments (Fig.4.26). P additions lead to greater chlorophyll a standing stock, but the results were not significantly different from controls (Fig. 4.26). On August 7 th both the N and P treatments remained significantly l ower in concentrations than controls. T he NP treatments were not significantly different than controls on the 7th. By August 8th, NP and P additions, respectively, were now greater in chlorophyll a concentration than either controls or N treatments. Con trol and N treatments were now not different from each other. These differences noted on the 8 th were significant throughout the remainder of the experiment. There was no apparent biomass response in the benthos to the rainfall event that lowered salinit y by ~50% but there could have been unmeasured changes in community composition. The increase in chlorophyll a concentration could be the result of higher concentration nutrient additions that were accidently applied to some unidentified mesocosms on the 7th.

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100 Figure 4.25. Average water column chlorophyll a ( g L 1 ) in central Florida Bay mesocosms by nutrient addition treatment (control, N, P, and NP) during summer 2002. The sample dates appear on the x axis. Values are the average of three replicates of treatment mesocosms in a randomized block design sampled daily.

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101 Figure 4.26. Average sediment chlorophyll a ( g L 1 ) in central Florida Bay mesocosms by nutrient addition treatment (control, N, P, and NP) during summer 2002. The sampl e dates appear on the x axis. Values are the average of three replicates of treatment mesocosms in a randomized block design sampled daily. Like the summer, the central Florida Bay water column community initially responded to NP additions (Fig. 4.27) in winter by increasing chlorophyll a standing stock. N alone reduced chlorophyll a standing stock, in contrast to the summer experiment at the same location. By January 25th the water column chlorophyll a standing stock response to NP and P additions w ere significantly different from each other and also from N additions and controls. By January 28 th water column chlorophyll a concentration decreased dramatically in the NP treatments and was not significantly different from controls or N addition treatm ents. Phosphorus additions on January 26 th were significantly different from all other treatments and the control, suggesting a shift to P limitation of the water column community. Phospho r us limitation persisted from January 28 th through the 30 th On J anuary 28 th NP and N treatments had reduced

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102 chlorophyll a standing stocks that were significantly different from both controls and each other. The NP treatments rebounded on the final day of the experiment to again be greater in chlorophyll a concentratio n than controls. All treatments and controls were significantly different from each other on the final day of the experiment. Figure 4.27. Average water column chlorophyll a ( g L 1 ) in central Florida Bay mesocosms by nutrient addition treatment (control, N, P, and NP) during winter 2003. The sample dates appear on the x axis. Values are the average of three replicates of treatment mesocosms in a randomized block design sampled daily.

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103 Figure 4.28. Average sediment chlorophyll a ( g L 1 ) in central Florida Bay mesocosms by nutrient addition treatment (control, N, P, and NP) during winter 2003. The sample dates appear on the x axis. Values are the average of three replicates of treatme nt mesocosms in a randomized block design sampled daily. During the winter, sediment chlorophyll a standing stock response differed from water column results (Fig. 4.28). The sediment community from central Florida Bay was P limited at least during th e latter part of the experiment. P addition treatments showed the greatest increase in benthic microalgal chlorophyll a concentrations, followed by N and NP which were not significantly different from each other except on the last three days of the experim ent. However, N additions did not reduce chlorophyll a standing stock as it did in the summer at this location. On January 28th N addition treatments showed the greatest average chlorophyll a concentration, but this was not significantly different from P treatments. On January 29th, P addition treatments were the greatest average chlorophyll a concentration, while the N only treatment lost a significant amount

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104 of chlorophyll a and was actually below control treatments for biomass. On January 30 th the P t reatment had now dropped dramatically while the N only treatment had rebounded. The NP treatment, which during the summer at this location had the greatest average chlorophyll a concentration, was greater than control treatments, but not as high in concen tration as the P alone treatments. The NP treatments did not differ significantly from N treatments for January 23 27th, but did show an increase in chlorophyll a standing stock on the final day of the experiment, although not significantly different from either control or N alone Figure 4.29. Average sediment chlorophyll a ( g L 1 ) in western Florida Bay mesocosms by nutrient addition treatment (control, N, P, and NP) during winter 2003. The sample dates appear on the x axis. Values are the average of three replicates of treatment mesocosms in a randomized block design sampled daily.

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105 In the winter in western Florida Bay, the mesocosm experiment indicated the water column and sediment were more similar to each other in response to nutrient additi ons, but different than the central Florida Bay. In both water column and sediment, nutrient additions resulted in decreased chlorophyll a concentrations throughout the experiment and these differences were significant by January 25th (Figs. 4.29 and 4.30). Initially in western Florida Bay, control treatments had the greatest sediment chlorophyll a concentration followed by N> NP > P additions (Fig. 4.29) By January 28th, the P and NP treatments were not statistically different from each other, but did differ from the P and Control. On the final day the order of sediment chlorophyll a concentration from greatest to least was Control > N> P>NP all were significantly different from each other. Since all the treatments and controls declined in chlorophyll a concentration, some factor other than nutrients must have also been limiting, such as light or temperature.

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106 Figure 4.30. Average water column chlorophyll a ( g L 1 ) in central Florida Bay mesocosms by nutrient addition treatment (control, N, P, and NP) during winter 2003. The sample dates appear on the x axis. Values are the average of three replicates of treatment mesocosms in a randomized b lock design sampled daily. Similarly, in the water column in western Florida Bay, all nutrient addition treatments showed a loss of chlorophyll a (Fig. 4.30). On January 25 th water column chlorophyll a concentration was greatest in controls followed b y N> NP > P. All treatment additions were significantly different from controls, but not from each other on January 25 th and 26th. January 27 th and 28th, none of the treatments or controls were significantly different from each other. By January 29th, c ontrols again had the greatest water column chlorophyll a concentration. The NP treatments were slightly lower than controls> P> N addition treatments. Only the control and the N treatments were significantly different from each other on January 29th. On the final day of the experiment phytoplankton biomass increased significantly in the water column, again N

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107 was less than control in chlorophyll a concentration, followed by NP, P and Controls. Control was significantly different from N and NP/P treatment s, and N was significantly different from NP/P treatments too on the final day. The NP and P treatments were not significantly different from each other on January 30th. A summary table of the significant differences is presented in Appendix A. Discussion I compared two methods of assessing phytoplankton response to nutrient limitation in these experiments: chlorophyll a standing stock and water column dissolved nutrient concentration. The latter has been commonly measured temporally and spatial ly supply in the water column must then be limiting phytoplankton biomass and that nutrient found in high concentrations must not be limiting phytoplankton growth. B enthic chlorophyll a standing stock is not commonly measured temporally and spatially, and sediment bioassays are not a part of the existing Florida Bay monitoring program. Increase in chlorophyll a concentration over time in response to nutrient addition indicates phytoplankton growth in response to nutrient additions, suggesting the absence of that nutrient was what limited growth. Numerous investigators have highlighted the disparity between dissolved nutrient availability and nutrient limitation of bio mass. Another hindrance to its use is that dissolved nutrient availability does not indicate benthic or pelagic community uptake or some combination thereof. Nutrient concentrations Central Florida Bay, during both summer and winter experiments, was initially very low in all species of dissolved phosphate (TDP and SRP) suggesting P could be limiting to phytoplankton and benthic microalgae. Daily samples were variable, even within treatments. However, no significant differences in the concentration o f any forms of P were found between nutrient addition treatments or controls in either of these experiments even over time. SRP exhibited a decreased over time in all nutrient addition treatments and controls for both experiments by the second or third da y. This evidence supports P uptake by the sediment or benthic microalgae but I could not distinguish them in this experimental design

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108 Dissolved nitrogen exceeded the Redfield Ratio compared to disso lved phosphate Differences in dissolved TDN concentra tion in mesocosms hint at colimitation of N and P temporally. Nitrate+nitrite and nitrite concentrations suggest differential uptake of nitrogen species in response to nutrient addition. Ammonium availability also supports differential uptake of nitrogen but only for the summer experiment in central Florida Bay. I cannot determine this during the winter since ammonium measurements were at or above the upper limit of detection. Based upon dissolved nutrient availability in central Florida Bay, P would be the limiting nutrient for benthic and pelagic phytoplankton. Colimitation by N would be possible if sufficient P is regenerated or newly introduced to the system. Western Florida Bay was neither N, nor P, limited based upon dissolved nutrient availability in one winter mesocosm experiment. Mesocosms were initially greater in dissolved phosphate concentration and showed clear differences in TDP and SRP concentration between both P addition treatments and N only additions and controls. The magnitude of the se differences increased throughout the course of the experiment. This is probably a combination of thermally depressed phytoplankton production limiting uptake of available P, allowing diffusion of the P addition from the sediment to the water column bu t also suggests P sufficiency and N limitation TDN:TDP again exceeded the Redfield Ratio in the winter experiment. Ammonium concentration (at least 31 M) was offscale at the upper limit of detection for all treatments. As in central Florida bay, nitr ite was near the limits of detection and much less than nitrate concentration, but spatial differences between central and western Florida Bay were not apparent from the experiment. Chlorophyll concentration When change in chlorophyll a concentration was used to assess response to nutrient availability, temporal and spatial differences were found between pelagic and benthic communities. Summer m esocosm experiments revealed phytoplankton biomass (chlorophyll a ) in the water column increased more quickly in response to sediment nutrient additions than benthic microalgal biomass (chlorophyll a ). However, by the termination of the experiment, a similar trend in biomass was apparent in t he benthic

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109 microalgal community Winter trends were not as clear, perhaps due to temperature or light limiting biomass more than nutrients. Figure 4.31. Temperature (left y axis) and salinity (right y axis) in August 2002 for the central Florida Bay mesocosm experiment.

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110 Figure 4.32. Temperature (left y axis) and salinity (right y axis) in January 2003 for the western Florida Bay mesocosm experiment.

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111 Figure 4.33. Temperature (left y axis) and salinity (right y axis) in January 2003 for the central Florida Bay mesocosm experiment. Chlorophyll a concentration was more controlled by temperature during the winter experiments than nutrient limited, as evidenced by the lack of significant differences between treatments and controls and what seems to be a release of temperature limitatio n on the final day of the experiment (Fig. 4.32 and 4.33) Chlorophyll a changes in both the water column and sediment communities were negligible for the duration of the winter experiments in both locations, despite nutrient additions. The water column was always quicker to respond. Only on the final day of the experiment did growth increase appreciably (doubling), but there was no advantage to communities with nutrient additions. A longer experimental duration may have elucidated nutrient limitation at this location in the winter, particularly after passage of the cold front.

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112 Based on chlorophyll a concentration the mesocosm bioassays during both summer 2002 and winter 2003 indicate nutrient limitation in benthic microalgal communities from central Fl orida Bay. In central Florida Bay, the limiting nutrient for the benthic microalgal community varied from NP and P limitation in the summer to P and shorter term N limitation in the winter. The water column in central Florida Bay was also nutrient limite d in both experiments but N limited in central Florida Bay in the summer and P limited in the winter. Ultimately N and P were temporally colimiting on the order of days, to the water column population in central Florida Bay. In contrast to central Flori da Bay, nutrient limitation was not demonstrated in the sediment community in western Florida Bay during the winter. The water column community, like that of the sediment, did not show a significant response to nutrient additions versus controls for more t han a day during the experiment. Those differences attributable to treatment effect were negative biomass responses rather than positive ones. Summary It is common to measure dissolved nutrient availability in the Bay and uncommon to conduct water column bioassays. Sediment bioassays in the Bay are very rare Using dissolved nutrient availability as a predictor of phytoplankton nutrient limitation would have only been accurate for the sediment community in central Florida Bay, but not the water column c ommunity. Western Florida Bay was much more complicated, however the loss of chlorophyll a in both water column and sediment phytoplankton community in response to nutrient addition would not have been predicted based solely on dissolved nutrient availabi lity. Two bioassays would statistically be considered coincidence and more experiments are necessary, however my findings suggest it would be perilous to assume the pelagic and benthic communities respond in unison to perceived nutrient limitation based up on dissolved nutrient availability. Colimiting nutrients and ephemeral short term community response to nutrient limitation would not be evident from dissolved nutrient availability or from infrequent bioassays whether measuring the water column or sedime nt community. Tomas et al. (1999) highlighted the disparity between nutrient availability and nutrient limitation in natural Florida bay water column phytoplankton populations. They

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113 point out that dissolved nutrient availability arises dually from nut rient uptake/ assimilation and autochthonous/allochthonous supply. Benthic pelagic coupling of these dual processes, combined with phytoplankton community composition and response rates further complicate relationships between nutrients and chlorophyll a standing stock. Bioassays are a much better method than measuring dissolved nutrient availability to gauge phytoplankton response to nutrient additions. Experimental bioassay findings of nutrient colimitation in both the sediment and water column in this study, and in the water column in other studies ( Tomas et. 1999 ; Jurado and Hitchcock 2001; Vargo et al. 2001a), do not consistently support temporal and spatial trends in nutrient supply and availability in Florida Bay.

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114 Chapter 5 Short term response of benthic microalgae to 33 P additions to the sediment. Introduction Benthic microalgae (BMA) contribut e to ecosystem primary productivity in regions where sufficient sunlight reaches the benthos (MacIntyre et al. 1996; Cahoon, 1992). In Florida, these areas include the West Florida Shelf, and those portions of coastal embayments, such as Florida Bay, that are not light limited (Kelble, et al. 2005). Florida Bay is a large triangular shaped embayment located at the southern tip of pen insular Florida. Part of Everglades National Park, it is a negative estuary approximately 2200 km 2 in size (Schomer and Drew, 1982; Fourqurean et al. 1992). It is bounded to the east and south by the Florida Keys and the reef tract, and to the west by th e Gulf of Mexico. To the north are the Everglades from which it receives freshwater inflow, mainly through Taylor Slough and the C111 canal system (Schomer and Drew 1982; Rudnick et al. 1999). Florida Bay has been intensively investigated since the late ecosystem changes like seagrass and sponge dieoffs, and persistent phytoplankton blooms ( Carlson et al. 1999; Butler et al. 1995; Phlips et al. 1995 ). This combined with Everglades restoration efforts, has spurred interest in the d evelopment of a comprehensive ecosystem model ( Madden et al. 2005 2007). Nutrient budgets are essential to modeling primary productivity and must include benthic flux (Madden et al. 2005). Phosphate (P) is most often implicated as the nutrient limiting p rimary production in Florida Bay (Fourqurean et al. 1992; Tomas et al. 1999). Biology, geology, chemistry and physics can affect benthic P flux in Florida Bay. In situ experiments provide net nutrient flux from the benthic community (Yarbro and Carlson, 2 008) and problems related to geology and chemistry can be avoided. Multiple investigators have shown that biology, specifically the microbial web within BMA vegetated sediment, is important to benthic nutrient flux (Admiraal, 1977; Nilsson and

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115 Sundback, 1 993; Sundback and McGlathery, 2005). However it remains difficult to measure specific components of the benthic community in situ and determine what nutrients they may be using (Sundback and McGlathery, 2005). Thus controlled laboratory experiments using intact sediment cores can be useful to examine the microbial web related benthic nutrient flux (Nilsson and Sundback, 1993; Cornwell et al. 2001; Sundback and McGlathery, 2005). BMA coexist within seagrass beds, on the sediment and some species are epiph ytic on seagrass blades (MacIntyre et al. 1996; Cahoon, 1992). In competition for nutrient resources with seagrasses, BMA are dwarfed in the volume of phosphate uptake and mobilization (Nielsen et al. 2005 ). However, due to the variety of components in t he BMA community, they may be capable of utilizing phosphate both from porewaters and loosely bound to the sediments within and below the redox zone (Sundback and McGlathery 2005 ) Seagrasses and the symbiotic cyanobacteria Klebsiella sp ., which is present in some seagrass species, can alter the oxic conditions of the sediment surrounding the seagrass roots and rhizomes (Fourqurean and Zieman 1991 ; Kirchstein et al. 1993 ; Nielsen et al. 2005). Sediments can release P based upon the redo x condition of the sediment (Sundback and McGlathery 2005). Anoxic conditions can mobilize iron bound P and that loosely adsorbed onto sediment grains, particularly clays, into the porewaters. Phosphorus can be sorbed onto carbonate sediments commonly f ound in Florida Bay (Millero, 2000). Benthic microalgae are an important food source to higher trophic levels particularly juvenile fish and epifaunal gastropods and infaunal filter feeding bivalves that can regenerate P into the water or sediment (Fenchel and Kofoed, 1976). This community is comprised of free living and attached organisms (MacIntyre et al. 1996), some which secrete a mucilaginous matrix that stabilize sediments against erosion (Admiraal, 1977; Huettel and Gust, 1992) and inhibit diffusion of nutrients in porewaters (Nilsson and Sundback, 1991 ; Sundback and McGlathery, 2005). Uptake and release of nutrients by BMA has been demonstrated both to and from the sediment and the water column benthic pelagic coupling (Sundback and Graneli,

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116 1988 ; Nilsson and Sundback, 1991; Sundback and McGlathery, 2005). This process would be an important source and sink of nutrients in coastal systems and estuaries. The ability to trace nutrients injected into one part of a benthic pelagic system would more d irectly implicate the benthic microalgal community in the mobilization and delivery of nutrients to other parts of the system. This has been demonstrated through the mass balance measurement of dissolved and particulate nutrients within the sediment, in p orewaters, and in the overlying water column (Robson et al. 2008). Isotopic ratios can be useful tracers (both stable and radioactive) and have been used in pelagic systems for many years (Steeman Nielsen, 1951; Hoare et al. 2005; Kroeger et al. 2006). S ediment porewater is much more difficult to label with a tracer than the water column and radioactive elements require controlled use to ensure proper containment, storage and disposal. This is compounded in Florida Bay by the geochemical sorption of P o nto carbonate sediments (Millero, 2001 ). The radiolabelled P tracer is ineffectively mixed into the sediment (Jensen et al. 1998). Measuring the pools of available dissolved P within the sediment and the water column fractions over time, while unable to overcome th is obstacle, can be used to evaluate the transport of labeled P isotopes in the presence and absence of BMA. Evaluating the potential for benthic microalgae to utilize benthic P was the purpose of this study. The objectives were to determine if flux of 33 P from the sediment occurs at a statistically significant level for areas with, or without, a benthic microalgal layer, and to use changes in the measured nutrient pools over time to support benthic microalgal mediation of 33 P flux. Materials and Methods To test the flux of radiolabelled 33 P through the BMA I used the method of Sororkin (1992). Briefly, the experiments included an abiotic control and a treatment control (core without the addition of 33 P ). The abiotic or killed, control accounted for physical adsorption of the 33 P to the carbonate sediments and represented F ickian diffusion across the sediment water interface. Cores with microalgal layers (live) but with nonradioactive PO 4 added served as treatment controls. So me cores were incubated in the dark to evaluate the effect of light on flux. The overlying water column was

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117 carefully decanted and replaced with filtered water from the sampling site without 33 P added. The water column was subsampled over time. The amou nt of 33 P in the overlying water column was then measured as a function of time and presence/absence of microalgal layer. In the first experiment I added a large amount of P ( ~37 M ) to t he water column to evaluate the effect on 33 P flux In subsequent ex periments I added light and dark P enhanced treatments. Figure 5.1. The locations where field cores and water were collected in Florida Bay for all the experiments. These experiments were conducted using sediment from End Key in central Florida Bay and Carl Ross Key in western Florida Bay (Fig. 5.1) Physical parameters were recorded at the field collection sites and temperature was recorded at sampling

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118 intervals throughout the laboratory experiment. Cores (2.5cm diam.) were removed from areas of the sediment devoid of above and belowground seagrass biomass. Sediment cores were taken with 60cc syringes with the end removed. As the cores were inserted into the sediment the plunger was simultaneously retracted until the core reached a depth of ~10 cm Cores were capped with #7 rubber stoppers on the bottom to ensure that sediment profiles remained intact Cores were immediately transported to the laboratory submerged in ambient seawater from the site. Upon return to the laboratory, damaged or dis turbed cores were removed from the experiment. The sides of the core sleeves were pierced at a depth of 2cm below the sediment water interface with a metal probe heated on a Bunsen burner. This depth was determined based upon preliminary experiments. The hole was plugged with a piece of modeling clay to ensure no porewater escaped. Cores were haphazardly arranged in 3 or 5 replicates of treatments. The treatments consisted of light and dark replicates of : killed + 33 P live + 33 P live control ( F ig 5.2 ).

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119 Figure 5.2 Cartoon depiction of experimental setup. From left to right: initial cores are received with BMA layer intact, the overlying water column is removed and sodium azide is added to the killed controls, filtered seawater collected from the field location is added to restore the water column and samples sit undisturbed overnight, the experiment commences upon the addition of carrier free 33 P or PO 4 (blank) to the sediment in killed and live treatments, over time the amount of 33 P in the w ater column is measured. The water column was carefully siphoned off each core. Sodium a zide (0.75 M) was added to the surface of cores Additional water from the field site was collected in 2L brown N alge ne bottles. This water was filtered through 0.7 GF/F filters. Twenty m illiliters of filtered water from the sample site was added to the top of all cores. The following morning 0 .1ml of carrier free 33 P or low nutrient seawater (P <0.001M) at the appropriate concentration, was added to the sediment through the hol e at the 2 cm depth with a syringe Only a small amount of liquid was added to the sediment in order to minimize the effects of porewater

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120 additions. The hole was then recapped wit h the clay to prevent porewater from leaking out. 33 P additions were made t o the sediment not the overlying water column. P enhanced additions were made to the water column by the addition of 0.5ml of 20M orthophosphate standard T otal dissolved P (TDP ) and soluble reactive P (SRP) was measured in the initial field filtered seawater and the light and dark controls at the conclusion of the experiment. Initial (t 0 ) measurements were taken from the overlying water column from each treatment immediately f ollowing the addition of the 33 P or ambient water. Samples were subsequently collected from the water column within each core at various intervals for up to 24 hours. Dark samples were kept under aluminum foil covers except when samples were being collec ted. Light samples were exposed to dim natural and fluorescent at 14h light: 10h dark. Samples were held at ambient room temperature, which varied from 20 23 C. S amples ( 100L ) were collected from each core using a pipettor. Tips were changed between s amples. Samples were placed into labeled glass scant vials with 10mls of scintillation liquid and ra dioactivity was measured the following day on a scintillation counter. Activity was corrected for decay and the concentration per L after correction for r emoval of the overlying water column due to subsampling. P reliminary experiments were conducted to determine the best way to kill the microalgal layer. Potential problems of removing the microalgae included minimizing disturbance of the sediments and n ot altering the microzonation of the nutrients within the porewater/sediment complex. The methods I tested were physical removal, chemical killing (treating the sediment with copper sulfate, bleach, or sodium azide) or heat killing (pasteurization). Chem ical killing methods were the most efficient and maintained the polysaccharide matrix around the cells, but generated hazardous waste handling concerns and some methods affected the measurements of phosphorus either by affecting the redox potential of the sediment or by introducing color that confounded the colorimetric measurement. Of the chemical agents I tested, sodium azide was the most effective with the least pH interference. Heat killing altered the sediment/porewater complex and evaporated porewat ers thus changing the concentration. Another option was the inclusion of a competitive inhibitor to autotrophic phosphate uptake (AsO 3 ) in abiotic

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121 controls but again there were hazardous waste concerns and heterotrophic activity might confound results Long term dark exposure for the abiotic controls was determined to be too time consuming for practical use. A preliminary time course experiment was undertaken to determine the amount of time it takes 33 P to enter the water column in live samples, to maximize 33 P uptake while minimizing release in killed samples. I also evaluated the depth necessary for reliable insertion of the 33 P without immediate transport to the overlying water column due to porewater disturbance. R elease or uptake by the sedim ent in live samples that deviated from controls or killed samples was deemed biologically produced. Although dominated by BMA I could not determine what element of the benthic community might be responsible for this release or uptake. Because of the pro blems associated with P radioisotopes in carbonate sediments mentioned in the introduction, change in the nutrient concentrations over time was used to show the flux of P between the sediment and water column pool. I used pre and post experiment water co lumn TDP measurements from control samples in comparison to the P added to the sediment and after correcting for the removal of water as a result of subsampling I assum ed evaporation during the experiment was negligible. Results Preliminary experiments T he first preliminary experiment conducted was to test the minimum depth below the sediment water interface needed to ensure the injection process did not introduce 33 P into the overlying water column. This experiment was conducted using only central Flor ida Bay sediment, because this location had the least consolidated sediments. The results of this experiment are shown in Figure 5.3 and indicate that a minimum of 4mm was necessary to maintain the integrity of the sediment water interface for central Fl orida Bay sediments. Despite this result a standard injection depth of 2cm was used during future experiments to ensure water column contamination was not an issue. The second preliminary experiment was to determine the minimum sampling interval to mea sure P flux to the overlying water column. P flux is almost immediate in live samples, so a 5 minute interval was chosen for the initial sampling. Practically, this interval was not able

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122 to be sampled except initially, so longer intervals were used throu ghout the rest of the experiment. Figure 5.3 Various depth of injection below the sediment water interface were evaluated to determine the minimum depth necessary to prevent water column contamination by the radiolabelled 33 P using killed BMA communities from End Key and Carl Ross Key in western and central Florida Bay, respectively. Laboratory experiments The first laboratory experiment was conducted in August 2003 using sediment from western Florida Bay. I did not use P enhanced treatments in this first experiment, but i nstead the live samples were P enhance d partway through the experiment. Due to limite d cores, only 3 replicates were used for each treatment. Figure 5.4 shows the results of this experiment and the statistical results are presented in A ppendix B Although variable in concentration among replicates, 33 P immediately went into the water col umn from the sediments in the live samples. Killed samples showed 33 P in the water column by the first hour, but accumulation did not seem apparent until hour 4.

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123 Controls and killed samples were significantly different from each other several times ear ly in the experiment and consistently different after 4 hours. But, there was not a significant difference between killed and live samples after 4 hours. Dark and light live samples both indicate 33 P release from the sediment initially followed by uptake by the sediment or the vessel wall, although not statistically different from each other (n=3). I did not find any effect from P enhancement of the water column with nonradiolabelled PO 4 Figure 5.4. Average benthic flux of 33 P (femtomoles L 1 h 1 ) from the sediment in cores taken in August 2003 from western Florida Bay. Error bars represent standard error of 5 replicates. Carrierfree 33 PO 4 in low nutrient seawater was injected into the sediment at 2cm below the sediment water interface. An enhanc ement dose of 37 M of P was added to the water column in the live and killed treatments after 8 hours, but not controls. During the second experiment in May 2004, sediment from both sites in Florida Bay was used, with 5 replicate cores per treatment. P enhanced treatments were also

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124 used for direct comparison with treatments, instead of enhancing the cores mid experiment as had been done previously. Figure 5.5 shows the results of this experiment for western Florida Bay. As in the previous experiment, 33 P immediately entered the water column in live treatments. Replicates were variable and treatments were not significantly different from each other, however trends are evident related to live v. killed samples and enhanced v. live samples. Controls a nd killed samples were significantly different from each other, but light and dark controls did not differ from each other. The live dark samples averaged twice the 33 P concentration of light samples. P enhanc ed live dark samples were also greater in 33 P flux than P enhanc ed light samples in contrast to the August 2003 experiment. The amount of 33 P released to the water column was an order of magnitude greater for western Florida Bay than central Florida Bay. This supports field measurements of greater d issolved P concentration in the western Bay water column made at other times however flux measurements were similar between locations. In central Florida Bay, P enhance d treatments showed the greatest flux of 33 P from the sediment, followed by killed sa mples, live samples, and controls, respectively, (Fig. 5.6). The dark P enhance d cores had greater average flux than light treatments, similar to western Florida Bay. There were no significant differences in flux between dark and light P enhance d treatm ents, or between any other treatments due to high variability. Killed treatments were significantly different from controls and live treatments after the first hour. There were no significant differences between live and control samples during the experi ment, although the dark live samples were greater in average 33 P flux, followed by the light live samples and controls.

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125 Figure 5.5. The average 33 P flux (femtomoles L 1 h 1 ) from the sediment in cores taken from western Florida Bay, May 2004. Error bars represent standard error of 5 replicates per sampling interval.

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126 Figure 5.6 The average 33 P flux (femtomoles L 1 h 1 ) from the sediment in cores taken from central Florida Bay, May 2004. Error bars represent standard error of 5 replicates per sampling interval. Note the Y axis is an order of magnitude less than the western Florida Bay figure. Sediment water column P pool s In support of my experimental evidence of 33 P as a tracer between sediment and water column in control treatments I measured the amount of TD P introduced into the sediment pool and available in the water column pool at the beginning (t 0 ) and end (t f ) of the experiments. My dissolved phosphate pool results show the net direction of TD P flux was always from the sediment to the water column during the August 2003 ( F ig 5.7 ) and May 2004 (Fig s. 5.8 and 5.9 ) experiments. These figures also i ndicate that light treatments accumulat ed more TDP from the sediment, however not significantly different from dark treatments The m agnitude of the flux differed between the two sites Although sediment porewaters were not measured this probably reflect s differences in original P concentration and possibly sediment sorptive potential.

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127 Figure 5.7. Daily flu x of TDP to the overlying water column from the western Florida Bay sediment during the August 2003 experiment. All results indicate flux from the sediment to the water column.

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128 Figure 5.8 Daily T DP flux to the overlying water column from the sediment pool in western Florida Bay during the course of the May 2004 experiment. The measurement from the light 5 sample was lost. All results indicate flux from the sediment to the water column.

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129 Figure 5.9. Daily TDP flux to the overlying water column from the central Florida Bay sediment during the course of the May 2004 experiment. The measurement from the dark 2 sample was lost. All results indicate flux from the sediment to the water column. Discussion 33 P flux to the water column was immediate in the live samples and they were significantly different than killed in both locations. This implies biological mediation in P flux. TDP flux from the sediment to the water co lumn pools in control samples supports this finding In western Florida Bay, live samples showed the greatest average 33 P flux followed by killed samples and then controls in the first experiment. Live un enhanced treatments again were the greatest avera ge 33 P flux in the second western Florida Bay experiment, followed by P enhanced live treatments, killed and controls. This finding is not easily explained but i t is possible that P enhancement could have triggered luxury P consumption in BMA. In central Florida Bay, P enhanc ed treatments showed the greatest average 33 P flux followed by killed samples, live samples and then controls. This order may reflect the BMA community at this location is comprised of species unable to store excess P

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130 T hat l ive un enhanc ed samples released less 33 P to the water column than the killed samples suggests P uptake from the sediment pore waters by BMA. It is important to remember the amount of 33 P accumulated in the water column was very small in comparison to the western Florida Bay experimental cores and the variability within treatments was high. Differences in 33 P flux magnitude between the two field locations mirror TDP concentration in situ In the May experiments dark live treatments were greater in avera ge 33 P flux than light live treatments for both ambient and P enhanced treatments at both locations The August experiment had the opposite result with light live treatments exceeding dark live treatments in 33 P flux. T here were fewer rep licates during th is first experiment and light and dark treatments were more similar to each other following P enhancement of the water column Chlorophyll a concentrations were not measured on the samples, but patchiness could have led to variability in the BMA layer amo ng cores. Although inconsistent results were found among experiments, this suggests that BMA light dependent reactions somehow affect 33 P flux I expected the presence of live BMA to help or hinder the 33 P flux to the water column in comparison to killed controls depending upon nutrient concentrations and diffusion gradients. The accumulation of 33 P in the water column over the killed BMA samples was not a linear process. Reaching initial equilibrium in the killed treatments took between 1 and 5 hours and concentrations did not remain stable indicating uptake by the sediment or vessel wall, or sampling error. Sampling from slightly different locations within the tubes could account for this or perhaps t here was minor sediment water interface disturbance related to the sampling that affected diffusion Summary In Florida Bay, t he presence of a living benthic microalgal layer quickly affects the release of 33 P from the sediment to the overlying water c olumn beyond F ickian diffusion. This finding is supported by changes in the sed iment and water dissolved P pool Differences between light and dark treatments suggest differential release of 33 P by BMA during light dependent reactions. The results sugge st BMA involvement in the mediation of P flux from the sediment to the water column.

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131 Chapter 6. The use of dissolved oxygen probes and Pulse Amplitude Modulated (PAM) fluorometry in the evaluation of benthic microalgal primary production in Florida Bay Introduction Quantifying primary production is important for examining ecosystem health and estimating the energy available for transfer into biomass at higher trophic levels. Primary production is the rate per unit area, or per unit volume, at which c arbon is fixed into biomass by producers (Lawlor, 2001) In aquatic systems, primary production is typically measured by determining the oxygen concentration within a closed system, by measuring the amount of inorganic 14 C incorporated into organic matte r or by fluorescence techniques like pulse amplitude modulated (PAM) fluorometry. These techniques measure net primary production, rather than gross, because all the methods are indirect. The O 2 method, while taking into account respiration when dark bottles are used, does not account for the non light requiring (dark) reactions of photosynthesis ( Revsbech et al. 1981 ). Nor is O 2 produced by algae only under aerobic conditions but can be produc ed by algae containing hydrogenase under anaerobic conditions using water as the reductant (Lawlor, 2001) 14 C measurements do not account for heterotrophy and remineralization of carbon, even if predators are excluded and incubations are short ( Hancke et al. 2008 ). Finally, fluorescence techniques measure the theoretical limits of primary production, rather than the actual fixation of carbon (Walz, 1998) Most methods of measuring primary production can be difficult to carry out in the sediments. 14 C mea surement can be complicated by heterogeneous labeling of the sediments, which can lead to underestimates of the carbon fixation rate (Revsbech et al. 1981). In addition, it can be difficult to determine the total inorganic carbon at the sediment/water int erface (Revsbech et al. 1981).

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132 Despite some sources of error, O 2 measurement has been a useful field method for measuring net primary production accurately and rapidly (Revsbeck, et al. 1981). O 2 is evolved during photosynthesis in plants when a water mo lecule is split in the presence of light, CO 2 and chlorophyll. Plants fix the carbon from carbon dioxide and produce carbohydrates. For each ml of oxygen produced, 0.536 mg of carbon has been fixed during photosynthesis (Lawlor, 2001). Thus the basic phot osynthesis equation is: Eq. 6. 1 6CO 2 + 6H 2 O C 6 H 12 O 6 + 6O 2 Oxygen probes Commonly, dissolved oxygen (DO) measurements involve either the Winkler titration method or microelectrodes. The latter can be inserted into the sediment or placed within an incubation chamber on the bottom. They have the advantage of minimal disruption of the physical and chemical gradients in the sediment (Revsbeck, et al. 1981; MacIntyre et al. 1996). Incubation chambers are the best field method available for measuring sediment oxygen evolution, since a semi closed system is required. However, a major disadvantage of using incubation enclosures is they can disrupt mixing of the water column and surface sediments by eliminating wave and current effects (Malan and McLachlan, 1991). Encapsulating the bottom may alter the vertical distribution of microorg anisms within the benthos. Additionally, decreased diffusion rates of gases into and out of the sediments in the semi closed system can also occur, limiting carbon available for photosynthesis (MacIntyre and Cullen, 1995). The Winkler method has been us ed to measure O 2 since the late nineteenth century and most recently adapted for seawater use in 1968 (Strickland and Parsons). Clarke s have been successfully used to determine benthic O 2 evolution in North Carolina (Cahoon and Cooke, 1992) and Florida Bay ( Yarbro and Carlson 200 8; Yates and Halley 2001), among other places. PAM fluorometry The PAM fluorometer has the following advant ages over traditional methods of measuring primary production: instantaneous readings, minimal disturbance of the benthos, and accuracy. The PAM derives the effective quantum Yield (Fv/Fm) of

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133 photosystem II during photosynthesis, but actually measures the photosynthetic Yield by applying a saturating light pulse to the sediment microalgal layer inducing maximum chlorophyll fluorescence Yield The photochemical Yield is then calculated, which has been shown to be closely correlated with the effective quant um Yield of photosynthesis in macroalgae and some seagrasses (Beer and Bjork, 2000). The PAM also has a 2 quantum sensor to measure photosynthetically active radiation (PAR) which allows calculation of the electron transport rate. Rapid light curves and induction curves are also possible using this instrument in conjunction with the application of continuous actinic light (Walz, 1998 ). When PAR is known, the apparent relative rate of electron transport (ETR, M e m 2 s 1 ) is calculated. Rapid light resulting in O 2 production O 2 production is assumed to be linearly related to ETR (Walz, 1998), however, species specific exceptions to this assumption have been found (Masojide k et al. 2001) that are linear only at low light levels. The orientation of the light source to the photosynthetic target is perhaps the most important aspect of PAM fluorometry, for reliability and comparison of repeated measurements. Water temperature is the second most important consideration for comparison of measurements ETR is enzym e dependent (photochemical Yield) and requires an optimal temperature range. H igh temperatures (Necchi, 2004), due to high light ,can cause photoinhibition that decrea ses fluorescence Yield (Walz, 1998). Migration within the sediment is often invoked as a hindrance to accurate light curve readings. The application of light in instantaneous measurements or in rapid light curves is so short in duration that this can be eliminated as a confounding factor in the use of the PAM (Serodio et al 2005). Both oxygen electrodes and PAM fluorometry have the benefit of reliable field measurements that lead to an estimation of primary production. Electrodes are cost effective but require maintenance and calibration for reliable results. PAM fluorometers are costly but require little field preparation and maintenance. Oxygen electrodes are most efficient at measuring relatively high oxygen concentrations (oxic conditions) and are limited in accuracy by the sensitivity of the electrode ( Revsbech et al. 1981 ). Oxygen

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134 techniques measure net benthic production (Cahoon and Cooke, 1992), whereas fluorescence techniques measure only the photosynthetic components of the benthic microalgal community (Walz, 1998) PAM may overestimate photosynthetic capacity in well established populations (S chmitt Jansen and Altenburger, 2007) and its accuracy can be adversely affected by refractive fluorescent compounds in sediments (Serodio et al. 1997) Materials and Methods Dissolved Oxygen The study sites were End Key in central Florida bay and Carl Ross in western Florida bay (Fig. 6. 1). Sampling occurred between November 2000 and August 2002 and measurements were concurrent with benthic nutrient f lux measurements. I measured O 2 production during a short incubation period (less than 10 hours) in both light and dark chambers of a known volume placed over sediment devoid of seagrasses. I placed, recovered and sampled the chambers by wading. To ensur e a good seal, the acrylic chambers were inserted into the sediment. These chambers contain both a gentle water circulation device and water replacement mechanism (attached collapsible IV bag with water) and are similar to those used by Cahoon and Cooke ( 1992). An oxygen microelectrode was inserted through a port in the chamber wall prior to deployment.

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135 Figure 6.1. Station map indicating the locations were DO in benthic chambers (Carl Ross Key and End Key only) and PAM fluorometry of benthic micro algae were measured. Dissolved oxygen production was measured in millivolts throughout the incubation with a Lazar DO 166MT 1 microelectrode zeroed in 1M NaHSO 3. The electrode was connected to a battery operated pH meter for readout. Electrodes were cal ibrated in air at ambient temperature and pressure. Microelectrodes were recalibrated daily prior to sampling. These microelectrodes do not require stirring at the membrane water interface and can measure DO between 0.1 and 20 ppm (mg L 1 ), with 0.01ppm level of accuracy. Because respiration of the entire benthos enclosed beneath the chamber occurs (both microalgal and animal), this method only measures net benthic primary production (NBPP) in the clear chambers. Dark chambers were used to measure sedi ment respiration (including dark photosynthetic reactions). The two values were added to

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136 calculate gross benthic production (GBP) for the incubation period. The equations used to derive these measurements are set forth in Appendix C Despite the flaws inh erent in this method, GBP was found to be a better estimate of microalgal production than NBPP in Onslow Bay, NC (Cahoon and Cooke, 1992). Areal net primary productivity (ANPP) estimates were made from the GBP extrapolated to 733.33 km 2 designated as bar e bottom baywide by Prager and Halley (199 7 ) plus that 40 km 2 of seagrass lost to dieoff since 1992. Concurrent with most of the field incubations, ambient PAR was measured throughout the incubation using a Licor 2 quantum sensor and light meter or the 2 sensor on the PAM fluorometer. Temperature, salinity and initial and final secchi depth were recorded as well. Time, tide, cloud cover, wind direction and speed estimates were also made and can be compared with measurements obtained from nearby monito ring stations in the SEAKEYS data buoy system (data courtesy of the Florida Institute of Oceanography and NOAA) PAM Fluorometry The study sites were End Key in central Florida bay, Arsnicker Key in s outheastern Florida B ay, and Carl Ross Key in western Florida bay. End and Arsnicker Keys were always submerged, but Carl Ross Key is intertidal on a semidiurnal basis. The chambers were deployed in areas devoid of seagrass and I was careful not to disturb the area where the PAM fluorometry measurements we re made. Instantaneous measurements and rapid light curves were taken throughout the sampling period adjacent to the benthic chambers using a Walz DIVING PAM fluorometer. This resulted in quantum Yield and ETR values as well as other photosynthetic param eters. The actual absorption of light by the microphytobenthos (AF) must be determined to obtain absolute rates of electron transport (ETR) for use in the following equation: Eq. 6. 2 ETR = Yield PAR 0.5 AF Yield and PAR are measured by the instr ument. The value of 0.5 refers to half the photons being absorbed by Photosystem II. The absorption factor (AF) is the fraction of incident light absorbed by the microphytobenthos as determined from the average of several measurements from a controlled l ight source both with, and without, a

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137 microphytobenthic community covering the PAR sensor. Erroneous data that were the source of equipment malfunction were removed from the dataset and differences in ETR or Yield by location, time of day or season were evaluated by linear regression. Results DO Electrodes The range of DO I measured varied from 5.80 To 8.93 mg L 1 The lowest DO values were found during the spring of 2001 and 2002 ( Figs.6. 7 6. 9) when only the western Bay location was sampled and August 2002 (Figs. 6. 3 and 6. 12) when both the western and central bay were sampled. The greatest values were found in central Florida Bay in July 2002 (Fig. 6. 2) and November 2000 (Fig. 6. 5) when only the western bay was sam pled. In general, at the time of initial electrode deployment both chambers were similar in DO concentration. Despite some variability, DO in the light chambers tended to increase with increasing PAR. DO usually peaked in the afternoon, but in three sa mpling periods the peak was at noon. As PAR decreased in the afternoon, light chamber DO continued to increase or leveled off. PAR measurements were much more variable than DO due to cloudiness, although averaged for the minute preceding the measurement. Dissolved oxygen flux in the dark chambers, generally, remained level or decreased throughout the incubation period. One time, in July 2002, I deployed oxygen sensors in two light chambers and one dark chamber (Fig. 6. 2). Initially one light chamber ha d a lower DO concentration than the dark, but the other was higher in concentration The difference among chambers was 0.3mg L 1 high in comparison to other sampling periods and this may indicate the initial calibration was flawed. Despite the quantita tive difference, both light chambers had similar qualitative DO results. The other instance when DO in the light chamber dipped lower than the dark one was in August 2002 during one sampling period at mid day, but later rebounded (Fig. 6. 12). In a few i nstances DO in light chambers decreased in late afternoon, coincident with decreasing PAR (Figs. 6. 4, 6. 5, 6. 9 and 6. 10). In two instances DO increased again following a mid afternoon drop, however the overall changes to DO concentration were <0.01 mg L 1 (Figs. 6. 4 and 6. 11). I cannot determine if th ese atypical fluctuation s in DO

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138 represents variation in respiration or photosynthesis because dark chambers were not able to be measured during either of these incubations as a result of a broken electrode, an d PAR measurements for the afternoon were not available for one of the two sampling periods. Over time, DO dropped in dark chambers in comparison to light chambers There were two exceptions in November 2000 and March 2001 in western Florida Bay ( Figs.6 6 and 6. 9), when single measurements showed DO increases of 0.1 and 0.2 mg L 1 h 1 respectively within the chamber. However, in both instances the overall trend in the dark chambers was decreasing DO. Table 6.1 Net benthic primary productivity (NBPP), sediment respiration (SR) and gross benthic primary production (GBP) see Appendix C for calculations. Net O 2 (light) NBPP Net O 2 (dark) Sed Resp GBP Date Hour s mmol L 1 mg C m 2 h 1 mmol L 1 mg C m 2 h 1 mg C m 2 h 1 9/11/2000 6 0.12 16.18 ND ND 16.18 11/13/2000 4.5 0.20 36.33 0.30 65.40 101.73 11/14/2000 6 0.45 61.31 0.20 32.70 28.61 3/13/2001 3 0.10 27.25 0.15 49.05 21.80 3/15/2001 6 0.45 61.31 0.40 65.40 4.09 3/16/2001 6.3 0.10 12.98 0.10 15.57 2.60 5/16/2001 9 0.40 36.33 0.63 68.67 32.33 5/7/2002 4.5 0.13 23.23 ND ND 23.23 7/17/2002 2.5 0.01 2.59 0.00 0.31 2.28 8/2/2002 3.6 0.00 1.01 0.00 0.92 1.93 8/8/2002 3 0.04 11.51 0.12 40.22 28.72 ND = not determined The production values for each sampling date are presented in Table 6. 1. Positive values in the net O 2 columns indicate a net increased in DO throughout the incubation, negative readings indicate a net decrease in DO throughout the incubation. Net Benthi c Primary Production typically exceeded respiration, resulting in a net autotrophy in the benthos. There were three sample periods where NBPP was heterotrophic The latter two periods were only weakly heterotrophic and the first sampling date may have be en

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139 affected by lack of mixing within the chamber. Based upon an average NBPP of 21.86 mg C m 2 h 1 benthic microalgae inhabiting otherwise unvegetated bottom would contribute ~406000 kg C (406 metric tons) to Florida Bay daily. Figure 6. 2. DO conce ntration (left y axis) within light and dark benthic chambers and ambient PAR values (right y axis) over time on July 17, 2002 in central Florida Bay. PAR was not measured at the final sampling period.

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14 0 Figure 6. 3. DO concentration (left y axis) within light and dark benthic chambers and ambient PAR values (right y axis) over time on August 2, 2002 in central Florida Bay. PAR was not measured at the final sampling period.

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141 Figure 6. 4. DO concentration (left y axis) within a light benthic chamber and ambient PAR values (right y axis) over time on September 11, 2000 in western Florida Bay. PAR was not measured at the final sampling period.

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142 Figure 6. 5. DO concentration (left y axis) within light and dark benthic chambers and ambient PAR values (right y axis) over time on November 13, 2000 in western Florida Bay.

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143 Figure 6 .6 DO concentration (left y axis) within light and dark benthic chambers and a mbient PAR values (right y axis) over time on November 14, 2000 in western Florida Bay.

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144 Figure 6. 7. DO concentration (left y axis) within light and dark benthic chambers and ambient PAR values (right y axis) over time on March13, 2001 in western Flori da Bay.

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145 Figure 6. 8. DO concentration (left y axis) within light and dark benthic chambers and ambient PAR values (right y axis) over time on March 15, 2001 in western Florida Bay.

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146 Figure 6. 9. DO concentration (left y axis) within light and dark b enthic chambers and ambient PAR values (right y axis) over time on March 16, 2001 in western Florida Bay.

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147 Figure 6. 10. DO concentration (left y axis) within light and dark benthic chambers and ambient PAR values (right y axis) over time on May 16, 2001 in western Florida Bay.

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148 Figure 6. 11. DO concentration (left y axis) within a light benthic chamber and ambient PAR values (right y axis) over time on May 7, 2002 in western Florida Bay.

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149 Figure 6. 12. DO concentration (left y axis) within light and dark benthic chambers and ambient PAR values (right y axis) over time on August 8, 2002 in western Florida Bay. PAM Fluorometry The PAM fluorometry results are presented in Figures 6. 13 6. 21. The instantaneous Yield measurements, those taken from one pulse of actinic light applied to the benthic microalgal community under ambient PAR conditions, indicate differences in the Yield and ETR by location/season and time of day. The Yield calcul ation is independent of ambient PAR, but ETR is derived from multiplying Yield with PAR (see equation 6. 2). When plotted by time of day, the highest Yield and ETR values were found in the morning samples. Lower Yield und in the afternoon, despite abundant light (Fig. 6. 13).

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150 Figure 6. 13. Time of day effect on Yield versus Electron Transport Rate (ETR) derived from instantaneous measurements at the three sites in western central and southeastern Florida Bay from field sampling events between 2000 and 2002. Although there appears to be a seasonal signal to Yield (Fig. 6. 14), this is confounded by location (Fig. 6. 15) since the southeastern site was only sampled one day, in the morning, and represented the majority of wet season sa mples analyzed. All the southeastern site samples were characterized by high instantaneous Yield and low ETR. The central and western bay sites were variable in instantaneous Yield and ETR, however there was a positive linear correlation between the two parameters. Most of the central Florida Bay measurements were clustered near <0.4 Yield /<100 ETR, while some central Florida Bay measurements and nearly all western Florida Bay measurements were >0.4 Yield />100 ETR. Tem perature differen ces on sampling days varied from 3 to 4.5C between morning and afternoon measurements Serodio et al (1997) found major

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151 differences in temperature (<15C, or 30C>) affected Yield measurements in intertidal communities in Portugal, but that between these values measures were comparable. While the magnitude and range of temperature differences would be different in the Florida Bay system, the temperatures values during my experiments were within the normal temperature distribution for the region and thus not expected to adversely impact my comparisons. Figure 6. 14. Seasonal effect on Yield versus Electron Transport Rate (ETR) derived from instantaneous measurements at the three sites in western central and southeastern Florida Bay from field sampling events between 2000 and 2002.

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152 Figure 6. 15. Regional differences in Yield versus Electron Transport Rate (ETR) derived from instantaneous measurements at the three sites in western central and southeastern Florida Bay from field sampling events between 2000 and 2002. The results of the rapid light curves of benthic microalgae outside the incubation chambers over the course of a sampling day are presented in Figures 6. 16 6. 21. Rapid light curves are genera ted from actinic light throughout a spectrum (low to high) applied to a sample that has not been dark adapted. The maximum ETR, measured during the higher light intensities at the end of a curve, tended to be low early in the morning and high in the after noon ( Figs.6. 16, 6. 17, 6. 19). One exception was in July 2002 in central Florida Bay when the 1:00pm sampling event was lowest overall (Fig. 6. 18). The southeastern Florida B ay, although only sampled once, had the highest ETR from rapid light curves (Fig. 6. 16). This is in contrast to the instantaneous samples where the Southeast had low ETR coincident with high Yield Western Florida bay also had

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153 intervals and among replicat es (Figs. 6. 19 6. curves were consistently in central Florida bay and were about 1/5 that found at the other two locations in the bay ( Figs.6. 17 and 6. 18). The shape of the curves from the southeastern and western Florida bay stations were nearly linear. The central bay curves were more parabolic. Figure 6. 16. Electron transport rate (ETR) from triplicate rapid light curves in southeastern Florida Bay on May 2, 2002 at the 10:00 am and 12:00pm sampling interval.

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154 Figure 6. 17. Electron transport rate (ETR) from duplicate rapid light curves in central Florida Bay on April 4, 2002 at the 10:00 am, 12:00pm and 1:30pm sampling interval.

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155 Figure 6. 18. Electron transport rate (ETR) from duplicate rapid light curves in central Florida Bay on July 17, 2002 at the 9:00 and 11:00 am and 1:00 and 3:00 pm sampling interval.

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156 Figure 6. 19. Electron transport rate (ETR) from triplicate rapid lig ht curves in western Florida Bay on March 15, 2001 at the 9:00 and 11:30 am and 1:15pm sampling interval.

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157 Figure 6. 20. Electron transport rate (ETR) from duplicate rapid light curves in western Florida Bay on March 16, 2001 at the 10:00 and 11:45 am s ampling interval.

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158 Figure 6. 21. Electron transport rate (ETR) from triplicate rapid light curves in western Florida Bay on May 4, 2002 at the 3:00 pm sampling interval. Discussion Dissolved oxygen trends were usually as expected, with light chambers increasing in DO throughout the incubation as a result of benthic community photosynthesis and dark chambers remaining stable or decreasing as a result of benthic community respiration. DO in light chambers usually followed PAR values, with a few exceptions in the late afternoons. Photoinhibition or increased benthic respiration caused by temperature stress might explain those instances where DO dropped and then rebounded. The oxygen e lectrodes gave reasonable measurements, but were difficult to use in the field in remote parts of Florida Bay because of power supply issues.

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159 The areal baywide productivity estimated from the dissolved oxygen method in my study was 0.016 0 .061 g C m 2 h 1 compared to a net loss of ~ 0.25 g C m 2 h 1 over mud bottom in Manatee Basin, Florida Bay (Yates and Halley, 2000). Their SHARQ deployment assembly is much larger, is not inserted into the sediment and must be deployed in deeper water in a different area, but benthic microalgal biomass would still be expected to be abundant over unvegetated bottom anywhere in Florida Bay. It is possible that their method was less sensitive and underestimated production, or that my method underestimated benthic respi ration because night measurements were not made Based upon my results, and the results of other researchers, areal productivity of areas colonized by benthic microalgae is significant compared to the water column (Cahoon, 2005) while much less than seagr ass beds ( Nielsen et al. 200 7 ; Yarbro and Carlson, 2008). The PAM fluorometer proved to be much easier to use in the field than the O 2 electrodes, despite finicky controls. It provides much more information on the physiology of the algal community, beyon d deriving the O 2 production, and the measurements are non destructive. However, results for sediment microalgal communities must be tempered with overestimation of fluorescence values as a result of the presence of refractory components which also fluore sce. Extracted chlorophyll measurements have shown that phaeopigments exceed chlorophyll by as much as 5:1 at these locations in Florida Bay (Chapter 3 in this dissertation) In addition, PAM fluorometry is relatively new and few measurements of benthic microalgae exist worldwide for comparison. The two methods should not necessarily be considered comparable due to the whole benthic community being measured by O 2 probes while only photoautotrophs are measured by PAM. Instantaneous PAM measurements provid e insight into the photosynthetic efficiency (capacity) of the algal community at the light history it was experiencing at the time of the measurement. The PAM fluorometer eliminates the nonphotochemical aspects of production and measures only the photoch emical changes in the plant. (Schreiber et al. 1996) Yield (Y=Fv/Fm, where Fm is the maximal fluorescence Yield, and Fv is the maximal variable fluorescence), is a reliable measure of the potential

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160 quantum Yield of photosystem II (Schreiber et al 1996; S aroussi and Beer, 2007). Changes in fluorescence Yield reflect changes in photochemical efficiency or increase of heat dissipation like photoinhibition (Walz, 1998). In my study, t he time of day differences in ETR and Yield for the instantaneous measur ements (Fig. 6.14) was probably due to the light history prior to the measurements or photosynthetic efficienc y differences However it may also be the result of high temperature or photoinhibition of the benthic microalgal community. These differences m ay reflect differing species composition, although I did not include this as part of my investigation. Diel differences in ETR in rapid light curves and instantaneous measurements have been reported in microalgae by other researchers (Masojidek, et al. 2001). Serodio et al. (2005), found three processes work simultaneously in BMA to respond to high light conditions that might be experienced in the int ertidal area: decreased photosynthetic efficiency (down regulation of photosynthesis through energy dissipating mechanisms), increased carbon metabolism activity, leading to an increase in ETR; and downward migration in the sediments. I based my areal pro ductivity calculations upon the assumption that d ifferences in ETR are linearly positively correlated to O 2 production from photosynthesis at the same irradiance level since they are mathematically related via equation 6. 2 above (Saroussi and Beer, 2007). Rapid light curves minimize ETR differences associated with variable light intensity, and O 2 production ( M 0 2 mg 1 Chl h 1 ) for this method is ~three times ETR. Since the relationship between O 2 production and ETR is roughly linear at low irradiance and BMA would likely experience light in this range I used the average ETR from all the light curves at irradiances between 200 and 500 E m 2 s 1 to calculate the areal O 2 production. The average O 2 production measured by PAM fluorometry would result in the production of ~817000 kg C (817 metric tons) to Florida Bay daily. Linearity in the rapid light curve suggests that the benthic microalgal community in the Southeast was not reaching the maximum photosynthetic capacity even at high light or that some ot her factor was limting ETR Later in the day the ETR was similar at the two highest light intensities, indicating the maximum production rate was achieved. In the western bay and more so in the central bay, maximum ETR in rapid light curves

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161 was achieved at lower light intensity. T he higher light intensity end of the curve and sometimes those curves performed at the midday sampling periods when ambient PAR was high in those parts of the bay, reveal depressed ETR. So production rates in western and central Florida Bay suggest the benthic microalgae were adapted to lower light conditions than the Southeast Sc h mitt Jansen and Altenburger (2007) found PAM fluorometry was a good indicator of production in response to pollution in pelagic algae, but on ly for relatively young blooms (<9 weeks in their system). Stable communities did not show discernable changes in production in response to various factors. I did not measure benthic community composition during, so I cannot evaluate whether community st ability might be a factor in production for Florida Bay. Diel differences in ETR for the rapid light curves indicate that a s enzymes were activated and irradiance intensified, O 2 production increased except whe n inhibited by high light conditions This result is similar to findings in freshwater cyanobacteria (Masojidek, et al. 2001) and BMA off Portugal ( Serodio et al. 200 6 ). The light intensities at the lower end of the curve are much more realistic for the be nthic microalgae in Florida Bay, h owever, the light intensities achieved at the higher end of the light curves are unlikely to be realized by benthic microalgae unless exposed at low tide This is possible at Carl Ross Key and at most of the benthic microalgal habitat in western Florida Bay. De spite being intertidal, northwestern Florida Bay experiences the most light limitation except for Rankin Basin (Kelble et al, 2005) The central bay has episodic pelagic phytoplankton blooms that cause light limitation. The Southeast is probably never light limited, but production may be nutrient limited. Summary Both PAM fluorometry and oxygen production are methods of measuring primary production comparable among systems over time. Since PAM fluorometry is new technology and has not been widely used to examine benthic microalgae, the historical measurement of oxygen production and 14 C are still probably most useful to managers to assess long term ecosystem response, but PAM fluorometry will be of future use when more measurements have been collected for comparison. The ease of use, repeatability

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162 and vast amount of information achieved by using PAM fluorometry argue for its application in monitoring programs and a variety of instruments using this technology are available to best measure different pri mary producers in the lab and field. Based on both DO and PAM fluorometry in this study, benthic microalgae in Florida Bay are a significant source of primary production in this system and should be included in modeling management tools. Parts of Flori da Bay that are vegetated by benthic microalgae are primarily autotrophic, with temporal and spatial heterotrophy supporting Florida Bay as a net autotrophic system. Areal benthic microalgal production rates based upon oxygen evolution were similar to t hose reported for other areas around the world (Cahoon, 2005), but more than that reported for mud bottom in Florida Bay by Yates and Halley (2001). PAM fluorometry rapid light curve data suggests benthic microalgae are adapted for lower light intensitie s in Florida Bay and primary production was most efficient at 2 00 500 E m 2 s 1 This would approximate the PAR reaching the submerged bottom throughout most of the day in Florida Bay. Benthic microalgae production was hampered by high light, at least in central and western Florida Bay at some time periods during the day, as a result of photoinhibition or downregulation of ETR to protect photosystem II This could be a consideration for areas where benthic microalgae are exposed during low tide. Insta ntaneous PAM measurements suggest differences in the photosynthetic efficiency of at the different locations.. Dissolved oxygen curves and PAM fluorometry support the potential for photoinhibition or heat losses in the afternoon, and that benthic microalg al production tends to increase with greater light intensities to a maximum efficiency at ~20% of peak surface PAR irradiance.

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163 Chapter 7. Conclusion Benthic microalgae are a fascinating community underappreciated in terms of ecological importance and primary productivity throughout the world, and in Florida Bay. This community is one of the most important aspects of benthic pelagic coupling to underst and, as anthropogenic nutrients continues to be a problem in estuarine and coastal ecosystems. I hope to continue working with BMA in my career and hope it is someday included in monitoring programs as a matter of practice. This conclusion represents a s ynthesis of my findings on BMA and sediment nutrient flux in Florida Bay. Sediment Phosphate Flux The three regions of Florida Bay where I performed in situ experiments proved to be variable temporally and spatially in terms of P flux from the sediment. My findings are similar to others in this same system within seagrass beds and in carbonate systems elsewhere. Phosphate flux magnitude was least in the cent ral and southeastern sites, which have the lowest available dissolved P concentrations in the water column and also the lowest P supply based upon Fourqurean et al. (1992) Phosphate flux in the western bay was greater in magnitude. This region of the b ay has the highest P supply from both surface (Fourqurean et al. 1992) and groundwater sources (Price, 2005) and greater dissolved P concentration in the water column. Florida Bay sediment, and the associated BMA community, acts as both a source and a sin k of phosphorus in this system. Soluble reactive phosphate flux was quite low, at the limits of detection no matter the location. In the afternoons, SRP flux was only out of the sediment, although mornings were variable. This was the only significant di fference in time of day that was noted. There was no difference in flux between light and dark treatments, perhaps because dark conditions were simulated during daylight hours ignoring any diel cues (Serodio et al. 2005) in the BMA community that may affe ct P flux if it is, indeed, mediated by the BMA. Dissolved organic phosphate was the dominant component of TDP in most of Florida Bay. This is in contrast to most systems, but in character for a bay with high

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164 autochthonous production and little inorgani c P input that comes from diverse sources (Gulf of Mexico, C111 canal, etc) The relative contribution of organic P to the total dissolved pool varied across my three sites according to the total available P, with the highest DOP in the central bay, and lo west in the southeast bay. Total dissolved nitrogen flux from the sediment was also variable temporally and spatially across the bay. In all experiments, TDN was much more abundant than TDP. The total dissolved benthic nutrient fluxes I measured could account for 100% of the nitrogen need and 6 41% of the phosphorus need of the water column during non bloom conditions. However, this calculation ignores community composition and preferen tial uptake of nutrient species by phytoplankton. Based upon my ave rage measured flux rates (positive) and the areas of Florida Bay that can be considered BMA habitat, ~1600 metric tons of P would enter the system from the sediment each year. Actual flux rates, as shown in this dissertation, vary into and out of the sedi ment which would balance any net loss of P from the sediment presumed from my extrapolation bay wide. This would probably be much larger if the nuances of anoxia and hypoxia of the sediments were better understood. The semi diurnal pulses in sediment P fl ux, driven by anoxia, that have been reported by other researchers would probably occur more frequently in Florida Bay. However, sediment P flux would be an important source of P to the Florida Bay system. Only by more widespread in situ measurements of benthic nutrient flux will the potential for BMA to act as a nutrient source or sink be better understood. Benthic microalgal chlorophyll a standing stock I was surprised that chlorophyll a standing stock was similar among the three locations I measured, despite differences in sediment grain size, tidal range and nutrient supply. Seasonal changes were apparent in western Florida Bay, with a spring and fall increase in chlorophyll a standing stock The lowest concentrations were in the wintertime, coincid ent with peaks in water column chlorophyll a standing stock which probably shaded the BMA community or if winter storms resuspended BMA into the water column This relationship between benthic and pelagic chlorophyll a is an important consideration in li ght limitation of BMA and macrophytes. While seasonal

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165 trends in chlorophyll a standing stock w ere not as clear at the other two locations, greater sediment chlorophyll a standing stock was associated with spring/summer at the central site. My measurements of chlorophyll a standing stock are similar to others from Florida Bay, but are generally less than those in temperate systems. Pigments in the sediment are primarily phaeopigment, the dead and decomposing macrophytes and microalgae both contributing to this signature. Despite this, the areal contribution of ~700 kg Chl a day 1 from BMA in otherwise unvegetated bottom is significant in Florida Bay. Benthic microalgal chlorophyll a standing stock, using a method that removes chlorophyllide a interference s, should be a component of ecosystem monitoring. Mesocosms as a tool to measure limiting nutrients in benthic microalgae I investigated two methods of evaluating potential nutrient limitation in BMA: dissolved nutrient availability in the water column a nd sediment nutrient addition bioassays. Dissolved nutrient availability was more representative of potential limiting nutrients in central Florida Bay where dissolved P is nearly always less abundant than N and most limiting. Despite removing the pela gic phytoplankton community it quickly reformed. The water column community responded more quickly to nutrient additions to the sediment than the BMA community did in the summer experiment. This water column community was at first P limited and then shifted to N limited, as more P wa s added to the sediment and presumeably made available to the water column by benthic flux. However, P flux to the water column was not detectable at a level significantly different among treatments in these mesocosms from central Florida Bay either in th e summer or the winter. The BMA community was always P limited in central Florida Bay. Total dissolved nutrient availability was not indicative of the potential for nutrient limitation in western Florida Bay. Total dissolved nitrogen and NH 4 were abund ant in comparison to P. Although measureable NO 3 was absent, all forms of P were present in low but measureable amounts. Nutrients seemed to not be affecting western Florida Bay BMA chlorophyll a concentrations so much as some other untested constituent, like light or temperature, in the winter experiment. Nitrogen addition treatments suffered less

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166 chlorophyll a loss than P addition treatments, which may support N limitation as a cofactor. Bioassays using natural populations of BMA would be an important tool to include in monitoring programs and would better predict nutrient limitation of the BMA community than dissolved nutrient availability. Nutrient preferences in both pelagic and benthic microalgae discount the exclusive use of dissolved nutrient ava ilability in determining potential nutrient limitation of a system. The results of my benthic nutrient flux measurements indicate the sediment and the associated BMA can be both source and sink for dissolved nutrients in the system. Radiolabelled tracers of P flux through benthic microalgae The use of 33 P was useful in tracing P flux trends from the sediment to the water column. Fickian diffusion across a killed BMA layer took between 1 and 5 hours to complete equilibrium The trend of BMA enhancing P f lux to the water column beyond simple Fickian diffusion was clear in live versus killed treatments although the mechanism is unknown. P flux from the sediment occurred almost immediately and there was sometimes subsequent loss of P to either the vessel w alls or the sediment/BMA complex There were differences among light and dark treatments suggesting that light dependent reactions somehow affect 33 P flux. The magnitude of P flux was different among the two field locations, but was consistent with disso lved P concentration at the sites as measured during the sediment flux studies (i.e., more 33 P flux in the western site than in the central location ) This method posed a hindrance to drawing conclusions on BMA mediation of P flux from the sediment due t o the lack of a total P measurement in the sediment and water column pools. However, the positive trend in the total dissolved P pools between the sediment and the water column, which I did measure, supports BMA influence on P flux from the sediment. Me asuring primary production in benthic microalgae My measurements of primary production, using dissolved O 2 evolution and PAM fluorometry indicate that BMA are a source of primary production to the Florida Bay

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167 system, although far less than seagrass. Area l production estimates range from ~400 and 800 metric tons of C day 1 based upon O 2 evolution and PAM fluorometry, respectively. These results are similar to BMA production estimates from other parts of the world, but less than muddy sediment in Florida Bay. Those areas of Florida Bay with BMA habitat would be net autotrophic based upon my measurements, however, I may have underestimated respiration. Both methods were measured during sunlight hours, which would not take in to account diel changes in pro duction and respiration due to physiological differences. Based upon PAM fluorometry results, BMA in the western and central Florida Bay are low light adapted. Peak production (ETR) occurred between 200 and 500 Einsteins m 2 s 1 or about 20% of surfa ce irradiance. However, diel differences were found in production, with either photoinhibition or downregulation of ETR (in response to high light) occurring in the mid day at all locations. The southeastern site, although only sampled a few times, appea red not to reach maximum photosynthetic efficiency, even when exposed to high light, suggesting BMA were adapted to high light conditions or some other factor was limiting ETR at this location. PAM fluorometry was much easier and provided much more information on the BMA photosynthetic capacity than O 2 evolution measurements. The ability to avoid problems with migration and photoadaptation that are associated with traditional light curves and its portability and lack of preparation make PAM very att ractive for field use. The newness of the technology, difficulty interpreting the information from the instrument, and the potential for species specific differences currently hinder the widespread use of PAM fluorometry as a means of measuring production Comparisons with traditional, long used 14 C and O 2 evolution methods are only now being undertaken, so this method will probably not be useful for making ecosystem management decisions for several more years. Everglades r estoration e fforts If Everglades restoration were to be completed there would be changes to the Florida Bay system as a result. With an increase in freshwater would come the delivery of more nutrients, lowered salinity, and decreased residence time within the mud basins.

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168 The decreased residence time might result in greater exports of production out of the Florida Bay system. Monitoring of the microphytobenthos would enable managers to evaluate the consequences of those changes upon the benthic community production, biomass and sediment nutrient flux. Such changes might be anticipated to include uptake of the nutrients by the BMA and perhaps a shift away from net autotrophy to net heterotrophy in more basins. However, if the water column biomass were to increase as a result of increased nutrient flux, there might ultimately be decreased BMA production as a result of light limitation. This could ultimately end with a complete decoupling of the benthic pelagic interchange of production and nutrient exchange in favor of phytopl ankton dominated system. Future work In the relatively short period of time that Florida Bay has been investigated, researchers have developed a better understanding of the oceanographic processes. As with any problem or question, the investigation leads us to more questions. My own future questions that have evolved from my work include co nducting more sediment mesocosm bioassays in the bay. I would also like to develop a better tracer of nutrients through the sediment porewater/BMA/water column pools. Those BMA living in the hypersaline lakes within some of the mangrove islands in Florida Bay have not been investigated for biomass, production to higher trophic levels living within the pools, or community structure. These could be the most extreme BMA environments found in Florida Bay. Most interesting to me is the influence of wave and tidal pumping and sediment microtopography on the concentration or advection of nutrient porewaters and probably BMA patchiness. This final topic would perhaps be the most applicable, and potentially fundable, aspect of the coastal nutrification problem I would like to pursue.

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169 Literature Cited Admiraal, W. 1977. Experiments with mixed populations of benthic estuarine diatoms in laboratory microecosystems. Botanica M arina 20: 479 485. Aller, R.C., Y.Y. Aller and P.F. Kemp. 2001. Effects of particle and solute transport on rates and extent of remineralization in bioturbated sediments. pP 315 333 In : Organism Sediment Interactions. Eds J. Y. Aller, S.A. Woodin, a nd R.C. Aller. University of South Carolina Press. Amspoker, M. C., and C. D. McIntire. 1978. Distribution of intertidal diatoms associated with sediments in Yaquina estuary, Oregon. Journal of Phycology 14: 387 395. Baillie, P. W. and B. L. Welsh. 1980 The effect of tidal resuspension on the distribution of intertidal epipelic algae in an estuary. Estuarine and Coastal Marine Science 10: 165 180. Beer, S. and M. Bjork. 2000. Measuring rates of photosynthesis of two tropical seagrasses by pulse amplit ude modulated (PAM) fluorometry. Aquatic Botany 66:69 76. Brand, L.E, and M.S. Ferro. 2001. Nutrient ratios and the eutrophication of Florida Bay. Abstract In 2001 Florida Bay Science Conference, April 23 26, 2001, Key Largo, FL. Butler, M.J. IV, J.H. Hunt, W.F. Herrnkind, T. Matthews, M. Childress, R.Bertelsen, W. Sharp, J.M. Field, and H. Marshall. 1995. Cascading disturbances in Florida Bay, USA: cyanobacteria blooms, sponge mortality, and implications for juvenile spiny lobster Panulirus argus Marine Ecology Progress Series 129: 119 125 Cahoon, L. B. 1992. Total chlorophyll in Onslow Bay, North Carolina: field observations vs. predictions of a total chlorophyll algorithm. Journal of the Elisha Mitchell Scientific Society 108: 91 101. Cahoon, L. B., and J. E. Cooke. 1992. Benthic microalgal production in Onslow Bay, North Carolina, USA. Marine Ecology Progress Series 84: 185 196. Cahoon, L.B. 1999. The role of benthic microalgae in neritic ecosystems. Oceanography and Ma rine Biology Annual Review. 37:47 86.

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170 Cahoon. L.B. 2006. Upscaling primary production estimates: Regional and global scale estimates of microphytobenthos production. Pp 99 108. In : Functioning of microphytobenthos in estuaries. J.C. Kromkamp, J.F.C. De Brouwer, G. F. Blanchard, R.M. Forster, and V. Creach (eds) Royal Netherlands Academy of Arts and Science. Caraco, N. 1988. What is the mechanism behind the seasonal switch between N and P limitation in estuaries? Canadian Journal of Fisheries and Aqu atic Sciences 45: 381 382 Caraco, N.F. J. J. Cole, and G. E. Likens. 1992. New and recycled primary production in an oligotrophic lake: Insights for summer phosphorus dynamics Limnol ogy and Oceanogr aphy. 37(3), 1992, 590 602 Carlson, P. R., Jr., Durako, M. J., Barber, T. R., Yarbro, L. A., deLama, Y., and Hedin, B. 1990. Catastrophic mortality of the seagrass Thalassia testudinum in Florida Bay. Annual project report. St. Petersburg, Florida: Florida Department of Natural Res ources. Charphy Roubaud C.J. and A. Sournia. 1990. The comparative estimation of phytoplanktonic microphytobenthic production in the oceans. Marine Microbial Food Webs 4:31 51 Charpy, L., and C. J. Charpy Roubaud. 1990. A model of the relationship bet ween light and primary production in an atoll lagoon. Journal of the Marine Biological Association of the United Kingdom 70: 357 369. Colijn, F. a. G. van Buurt. 1975. Influence of light and temperature on the photosynthetic rate of marine benthic diatoms. Marine Biology 31: 209 214. Colijn, F., and V. N. de Jonge. 1984. Primary production of the microphytobenthos in the Ems Dollard estuary. Marine Ecology Progress Series 14: 185 196. Cooke, J. E., 1991. The effects of ultraviolet radiation B on the diato m Nitschia closterium M. Sc. Thesis. University of North Carolina, Wilmington. Cornwell, J.C., M. Owens and W.M. Kemp. 2001 Nitrogen cycling in Florida Bay sediments. Abstract I n : 2001 Florida Bay Conference, Key Largo FL, Spring 2001 Darrow, B.P., J.J Walsh, G.A. Vargo, R.T. Masserini jr., K.A. Fanning, and J.Z. Zhang. 2003 A simulation study of the growth of benthic microalgae following the decline of a surface phytoplankton bloom. Cont inental Shel f Res earch 23: 1265 1283 de Jonge, V. N. 1985. The occurrence of epipsammic diatom populations: A result of interaction between physical sorting of sediment and certain properties of diatom species. Estuarine Coastal and Shelf Science 21:607 622.

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171 D'Elia, C. F., J. G. Sanders, and W. R. Boynton. 1986. Nutrient enrichment studies in a coastal plain estuary: phytoplankton growth in large scale continuous cultures. Can adian J ournal of Fish eries and Aquat ic Sci ences 43: 397 406 Durako, M. and J. Zieman 2007. Chapter 7: Seagrass Ecology. Pp 92 109. I n: Florida Bay Science Program: A Synthesis of Research on FloridaBay. Hunt J. H., Nuttle, W. (eds.), Fish Wildlife Res. Inst. Tech Rept. TR 11, 148 pp. Elser, J. J., M. M. Elser, N. A. MacKay, and S. R. Carpenter. 1988. Zooplankton mediated transitions between N and P limited algal growth. Limno logy and Oceanogr aphy 33:1 14 Fe nchel, T. and L. H. Kofoed 1976. Evidence for Exploitative Interspecific Competition in Mud Snails (Hydrobiidae) Oikos 27(3): 367 376 Forster, R.M. and J.C. Kromkamp. 2006. Estimating benthic primary production: scaling up from point measurements to the whole estuary. Pp 108 120. In : Functioning of microphytobenthos in estuaries. J.C. Kromkamp, J.F.C. De Brouwer, G. F. Blanchard, R .M. Forster, and V. Creach (eds). Royal Netherlands Academy of Arts and Science. Fourqurean, J. W., Jones, R. D., and Zieman, J. C. 1993. Processes influencing water column nutrient characteristics and phosphorus limitation of phytoplankton biomass i n Florida Bay, Florida, USA: inferences from spatial distributions. Estuarine, Coastal and Shelf Science 36:295 314. Fourqurean, J. W., Zieman, J. C., and Powell, G. V. N. 1992. Phosphorus limitation of primary production in Florida Bay: evidence from C:N:P ratios of the dominant seagrass Thalassia testudinum Limnology and Oceanography 37(1):162 171. Gordon, L. I., Jennings, J. C. Jr., Ross, A. A., and Krest, J. M. 1993. A suggested Protocol For Continuous Flow Automated Analysis of Seawater Nutri ents. In: WOCE Operations Manual. WHP office Report 90 1, WOCE report 77 No. 68/91. 1 52. Grant, J. and G. Gust. 1987. Prediction of coastal stabilization from photopigment content of mats of purple sulfur bacteria. Nature 330: 244 246. Halley, R. B, E.J Prager, R.P Stumpf, K. K. Yaters and C. H. Holmes, 1999. Sea level rise and the future of Florida Bay in the next century. Abstract In Proceedings of the South Florida Restoration Science Forum, May 17 19, 1999, Boca Raton, FL. Hancke, K., T.B. Hancke, L. M. Olsen, G. Johnsen, R.N. Glud, 2008. Temperature effects on microalgal photosynthesis light responses measured by O 2 production, pulse amplitude modulated fluorescence, and 14 C assimilation. Journal of Phycology 44(2): 501 514.

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172 Harrison, W. D., D. Musgrave and W.S. Reeburgh. 1983. A wave induced transport process in marine sediments. Journal of Geophysical Research 88(c12): 7617 7622. Heil, C.A. K. Chaston, S. Costanza, B. Longstaff, and W.C. Dennison. 2004. Benthic microalgae in coral reef sediments of the southern Great Barrier Reef, Australia. Coral Reefs 23:336 343. Hoare, A M. D J. Hollander, C A. Heil S Murasko, P M. Glibert, M Revilla, and J Alexander. 2005. Isotopic fingerprinting of nutrient sources and biological sinks in Florida Bay: A geochemical tool for evaluating ecosystem response to changing nutrient inputs Abstract in 2005 Florida Bay and Adjacent Marine Systems Science Conference, Duck Key, FL Howarth, R. W. 1988. Nu trient limitation of net primary production in marine ecosystems. Ann ual Rev iew of Ecol ogy 19: 89 110 Huettel, M. and G. Gust. 1992. Impact of bioroughness on interfacial solute exchange in permeable sediments. Marine Ecology Progress Series 89:253 26 7. Jensen, HS, KJ McGlathery, R Marino & RW Howarth. 1998. Forms and availability of sediment phosphorus in carbonate sand of Bermuda seagrass beds. Limnology and. Oceanography 43(5), 799 810 Jurado, J. and G.L. Hitchcock. 2001. Development of a silica budget for northwestern Florida Bay. Abstract in 2001 Florida Bay Science Conference, April 23 26, 2001, Key Largo, FL. Keizer, P. D., B. T. Hargrave, and J. Gordon, D. C. 1989. Sediment water exchange of dissolved nutrien ts at an intertidal site in the upper reaches of the Bay of Fundy. Estuaries 12: 1 12. Kelble, C.R., Ortner, P.B., Hitchcock, G.L. and Boyer, J.N. 2005 Attenuation of photosynthetically available radiation (PAR) in Florida Bay: Potential for light limitation of primary producers. E stuaries 28(4):560 571. Kirchstein, J.D., J.P. Zehr, H. Paerl. 1993. Determination of Nitrogen Fixation Potential in the marine environment: application of the polymerase chain reaction. Marine Ecology Progress Series, 95:305 309. Koch, M. S. Schopmeye r. C. Khyhn Hansen, O. Nielsen, C. Madden. 2005. A conceptual model for seagrass die off in Florida Bay based upon mesocosm and field experiments. Abstract in : Florida Bay and Adjacent Marine Systems Science Conference, Dec. 11 14, 2005, Duck Key, FL

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182 Appendices

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183 Appendix A ANOVA F test results from the mesocosm experiments by date. Central TDP ( M) SRP ( M) TDN ( M) NO 3 +NO 2 ( M) NO 2 ( M) NH 4 ( M) SIL ( M) PO 4 ( M) Benthic Chl a Water Chl a 8/4/2002 0.113 0.011* 0.641 0.51 0.52 0.801 0.477 0.558 0.215 ND 8/5/2002 0.619 0.444 0.643 0.778 0.789 0.565 0.87 0.785 0.311 0.398 8/6/2002 0.126 0.004** 0.16 0.013* 0.11 0.002** 0.148 0.388 0.477 0.297 8/7/2002 0.251 0.003** 0.004 ** 0.344 0.636 0.0003*** 0.256 0.317 0.032* 0.139 8/8/2002 0.796 0.022* 0.008** 0.005** 0.008** 0.002** 0.256 0.455 0.09+ 0.1456 8/9/2002 ND 0.133 0.0002*** 0.39 0.427 0.175 0.42 0.728 0.193 0.866 8/10/2002 ND 0.003** ND ND ND ND ND ND 0.328 0.065+ 8/11/2002 ND ND ND ND ND ND ND ND NV 0.013 8/12/2002 ND ND ND ND ND ND ND ND NV 0.065 Western 1/25/2003 0.32 0.135 0.934 0.288 0.475 0.961 0.741 0.365 2.3 x 10 9*** 0.586 1/26/2003 3.18 x 10 5*** 1.16 x 10 8*** ND ND ND ND ND ND 3.83 x 10 15*** 0.102+ 1/27/2003 4.42 x 10 5*** 8.38 x 10 8*** ND ND ND ND ND ND 3.98 x 10 8*** 0.399 1/28/2003 0.000145*** 3.27 x 10 8*** ND ND ND ND ND ND 4.58 x 10 13*** 0.345 1/29/2003 0.02** 1.87 x 10 8*** ND ND ND ND ND ND NV 0.71 1/30/2003 ND 1.31 x 10 7*** 0.068+ 0.028* 0.776 0.998 0.85 0.001*** NV 0.55 Central 1/25/2003 0.206 0.116 0.849 0.525 0.128 0.826 0.433 0.378 0.083+ 0.848 1/26/2003 0.221 0.034* ND ND ND ND ND ND 3.08 x 10 9*** 0.669 1/27/2003 0.291 0.202 ND ND ND ND ND ND 7.27 x 10 7*** 0.099+ 1/28/2003 0.667 0.067+ ND ND ND ND ND ND NV 0.166 1/29/2003 0.382 0.246 ND ND ND ND ND ND NV 0.328 1/30/2003 ND 0.29 0.091+ 0.432 0.389 0.578 0.689 0.256 NV 0.108+ +p=0.1 *p=0.05 **p=0.01 ***p=0.001 NV =no value determined, too few replicates, ND = not determined

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184 Appendix B ANOVA f test results from the 33 P flux experiments by time. August 2003 initial T1 T2 T3 T4 T5 T6 T7 T8 T9 Sandy Key 0. 09+ 0. 11+ 0. 16 0. 12+ 0.249 0.164 0.0 1 3 0. 05 3 0. 05 7 0. 04 4 May 2004 Sandy Key 0.522 0. 08 7 + 0. 08+ 8 0.195 0. 08 7 + 0.198 ND ND ND ND End Key 0.599 0. 05 7 + 0. 0 47 0. 0 84 + 0. 0 69 + 0. 0 96 + ND ND ND ND +p=0.1, *p=0.05

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185 A ppendix C (from Cahoon and Cooke, 1992). Net Benthic Primary Production = (([DO] t2 [DO] t1 x V x 12)/(PQ x H x A) [DO] t2 is the concentration of dissolved oxygen in mmol/liter at the end of the incubation. [DO] t1 is the concentration of dissolved oxygen in mmol/liter at the start of the incubation. V is the volume of the chamber in liters. 12 is the atomic weight of carbon. A P hotosynthetic Q uotient of 1.2 is used to represent 1. 2 moles of O 2 evolved per mole of carbon fixed. H is the hours of incubation. A is the area of sediment enclosed beneath the chamber in square meters. Sediment Respiration = (([DO] t2 [DO] t1 x V x 12 x RQ)/(H x A) A R espiratory Q uotient of 1.0 is used to represent 1.0 moles of carbon respired per 1 mole of O 2 consumed. Gross Benthic Production = Net Benthic Primary Production + Sediment Respiration

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About the Author Merrie Beth Neely is a native of Slippery Rock, PA. She received her Bachelor of Science degree from the University of Tampa, where she was an honors program She received her Masters of Science degree from the University of South Florida. She is a proud member of Kappa Delta Sorority since 1989 and has been a local and national volunteer with that organization since 1993. She is also a proud member and former officer of the St. Petersburg Alumnae Panhellenic Association si nce 1995. She has worked for Pinellas County, the University of South Florida and the State of Florida during her professional career.


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Benthic microalge and nutrient flux in Florida Bay, USA
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ABSTRACT: The objective of this study was to address the relationship between benthic microalgal communities and the phosphate nutrient dynamics of Florida Bay sediments and how they relate to benthic and water column primary production. In situ phosphate (P) flux between the sediment and the water column was measured in three regions of Florida Bay. Differences in the ratio of inorganic to organic phosphate flux were found between the three regions in relation to the amount of phosphate measured in the water column. Based upon the average sediment flux in my study, more than 1600 metric tons of P would be supplied by the sediment per year in Florida Bay. Based upon my measurements, dissolved nutrient flux from the sediment can be an important contribution to pelagic phytoplankton blooms in Florida Bay, accounting for 6.5 41% of demand and TDN accounts for 100% of the N demand.My findings were similar to others for both benthic nutrient flux and benthic microalgal chlorophyll a concentration. Benthic microalgae in Florida Bay contribute 700 kg Chl a per day to the system. Mesocosm experiments demonstrated that benthic microalgae and water column phytoplankton can respond differently to changes in nutrient availability. The dissolved nutrient in least supply in the water column does not necessarily correspond to the limiting nutrient for benthic microalgae. P acted as a tracer between sediment and water column dissolved P pools. The presence of benthic microalgae enhanced the transport of P to the water column as compared to simple Fickian diffusion. This was supported by the positive flux of dissolved P from the sediment to the water column pools in control treatments with a living benthic microalgal layer. Primary production by benthic microalgae were measured using dissolved O evolution and PAM fluorometry.Primary production for BMA habitat in Florida Bay was between 400 and 800 tons of C per day, based upon O production and PAM fluorometry, respectively.
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590
Co-advisor: Gabriel A. Vargo, Ph.D.
Co-advisor: Kent A. Fanning, Ph.D.
653
Phosphorus
Nitrogen
Chlorophyll
Mesocosm
Microphytobenthos
690
Dissertations, Academic
z USF
x Marine Science
Doctoral.
773
t USF Electronic Theses and Dissertations.
4 856
u http://digital.lib.usf.edu/?e14.2649