Citation
Managing Expectations

Material Information

Title:
Managing Expectations Creating a Community Based Stormwater Pond Nutrient Management Program
Creator:
Nealis, Charles Patric
Place of Publication:
[Gainesville, Fla.]
Florida
Publisher:
University of Florida
Publication Date:
Language:
english
Physical Description:
1 online resource (180 p.)

Thesis/Dissertation Information

Degree:
Doctorate ( Ph.D.)
Degree Grantor:
University of Florida
Degree Disciplines:
Soil and Water Science
Committee Chair:
CLARK,MARK W
Committee Co-Chair:
HOCHMUTH,GEORGE J,II
Committee Members:
MONAGHAN,PAUL F
FRANK,KATHRYN I
Graduation Date:
12/18/2015

Subjects

Subjects / Keywords:
Bodies of water ( jstor )
Chlorophylls ( jstor )
Environmental protection ( jstor )
Lakes ( jstor )
Nitrogen ( jstor )
Nutrients ( jstor )
Phosphorus ( jstor )
Ponds ( jstor )
Stormwater ( jstor )
Water quality ( jstor )
Soil and Water Science -- Dissertations, Academic -- UF
algae -- chlorophyll-a -- development -- fertilizer -- management -- nitrogen -- nutrients -- phosphorus -- policy -- quality -- runoff -- stormwater -- turfgrass -- urban -- water
Tampa Bay ( local )
Genre:
bibliography ( marcgt )
theses ( marcgt )
government publication (state, provincial, terriorial, dependent) ( marcgt )
born-digital ( sobekcm )
Electronic Thesis or Dissertation
Soil and Water Science thesis, Ph.D.

Notes

Abstract:
Degradation of surface waters is a critical concern in the state of Florida. Regulatory frameworks and best management practices (BMPs) exist to protect the designated uses of natural surface waters and reduce the impact of runoff from upstream activity. Stormwater ponds (SWPs) are an increasingly popular BMP in residential developments and are assumed to remove at least 80% of the nutrient load from the contributing watershed to meet regulatory requirements. Residential SWPs also generate a property value premium by creating waterfront property with social expectations related to aesthetics and recreational value. The management of SWPs to meet social expectations often includes the removal of biological responses to increased nutrient concentrations, resulting in a reduction of the nutrient removal efficiencies and failure to meet regulatory requirements. In this study, a method was developed to quantify social expectations of SWPs and define numeric nutrient criteria required to meet social demands and regulatory criteria. Nutrient and chlorophyll-a water column concentrations in SWPs within a southwest Florida community were sampled and significant nutrient-response relationships were established for clear and colored systems. The SWP nutrient-response relationships were compared to those established for the Florida numeric nutrient criteria for natural lakes and found to be weaker but significantly different. To quantify social expectation criteria, a web-based survey was created to identify thresholds of impairment based on water column chlorophyll-a concentrations. Results indicated mean community-based thresholds range from 20-30 ug/l. Preferred thresholds were found to increase with frequency of use for recreational activities and respondents who correctly identified the role of algae in SWPs had significantly greater thresholds than those who did not. Age, seasonality of residence, sex and presence of children in the household were also found to have a significant impact on preferred thresholds. Based on the identified community-based thresholds and nutrient-response relationships, SWP numeric nutrient criteria were established and the potential impacts were estimated. The findings and methods identified in this study indicate the significant potential to effectively meet regulatory requirements and social expectations of SWPs, improving management practices and reducing downstream impacts of runoff from residential development. ( en )
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Bibliography:
Includes bibliographical references.
Source of Description:
Description based on online resource; title from PDF title page.
Source of Description:
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Thesis:
Thesis (Ph.D.)--University of Florida, 2015.
Local:
Adviser: CLARK,MARK W.
Local:
Co-adviser: HOCHMUTH,GEORGE J,II.
Electronic Access:
RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2016-12-31
Statement of Responsibility:
by Charles Patric Nealis.

Record Information

Source Institution:
UFRGP
Rights Management:
Applicable rights reserved.
Embargo Date:
12/31/2016
Classification:
LD1780 2015 ( lcc )

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MANAGING EXPECTATIONS: CREATING A COMMUNITY BASED STORMWATER P OND NUTRIENT MANAGEMENT PROGRAM By CHARLES PATRICK NEALIS A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2015

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2015 Charles Patrick Nealis

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To Mr. Larry McFall; for inspiring my passion for science, love of teaching, and appreciation of Fleetwood Mac and B&B , and to my daughter, Evelyn, whom I hope to inspire the same appreciation of science

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4 ACKNOWLEDGMENTS This research was made possible through essential funding from the Tampa Bay Environmental Fund and the University of Florida Water Institute. Additional support was provided from Lakewood Ranch and the University of Florida Soil and Water Science Departme nt. The financial, physical and technical contributions were essential for the success of this research project. I would like to thank the community of Lakewood Ranch, Florida, for allowing me to conduct my research in their back yards. Additionally, I’d like to thank Ryan Heise for his continued support and guidance working in Lakewood Ranch and his willingness to explore new options for creating a more environmentally friendly development. I had additional incredible support from interested community mem bers, Mike, Tracy, and Emily Ott and I am extremely grateful for your contributions. I’d also like to thank those who helped me sample in the field. It was an arduous task, but without the help of Jackson Nealis, Katie Nealis, Kaylie Nealis, Adrian Hughes, Shannon Duffy, Ben Hughes, Grant Weinkam, Wesley Henson, Mary Beth Litrico, and Brenhan Street, I would have been stuck rowing circles a stormwater pond and talking to myself for days. I also would like to thank my advisors and committee members, Dr. Mar k Clark, Dr. Paul Monaghan, Dr. George Hochmuth, and Dr. Kathryn Frank. Dr. Clark has been a pillar of support through my academic journey, providing knowledge, technical advice and enjoyable conversation ever since he took a chance on me and offered me an opportunity to work on my PhD at the University of Florida. I’m eternally thankful for the mentor he became. Additionally, Dr. Monaghan has been a constant presence and beacon of insight into the social needs of physical science. His work inspired this pr oject and his continuing support has been irreplaceable. Dr. Hochmuth and Dr. Frank have

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5 provided outstanding support and knowledge throughout my studies, and their classes have served as inspirations for a true interdisciplinary research project. Thank you all. I would also like to acknowledge the tremendous help provided by Mike Sisk and James Coley. Mike continuously provided support and advice from day one and was an incredible help through any challenge. James provided irreplaceable help with statisti cal analysis and review. This work would not have been completed if not for both of their assistance. Finally, I would like offer my greatest thanks to my friends and family. Without the inspirational support, love and encouragement from my wife, daughter, brothers, parents, extended family and friends I wouldn’t be have made it through with my sanity intact . My wife, Jennifer, has been my inspiration of strength, positivity and perseverance, no matter what I face. Thank you Jenn, Evelyn, Mom, Dad, Jackson, Jake, Rose, Ben, Nick, Kiley, Grant, Brian, Dennis, Mary Beth, Soko, Chris and Dom for everything .

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6 TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................. 4 LIST OF TABLES ............................................................................................................ 8 LIST OF FIGURES .......................................................................................................... 9 WORKING DEFINITIONS ............................................................................................. 11 ABSTRACT ................................................................................................................... 12 CHAPTER 1 WATERFRONT WARS AND THE NEED FOR INTERVENTION ........................... 14 The Growing Conflict .............................................................................................. 14 The Impact of Nutrients on Surface Water Resources ............................................ 16 Increase of Nutrients in Surface Waters and Urban Land Use ......................... 17 Role of Nutrients in Surface Water Impairment ................................................ 20 Algae .......................................................................................................... 20 Nutrients ..................................................................................................... 22 Urban surface waters ................................................................................. 25 Regulatory Framework Protecting Water Resources .............................................. 26 Clean Water Act ............................................................................................... 27 Florida’s Stormwater Management ................................................................... 28 Water Quality Standards .................................................................................. 30 Local Ordinances and Restrictions ................................................................... 33 Reducing NonPoint Source Nutrient Pollution Using Stormwater Ponds ............... 35 Regulatory Requirements ................................................................................. 36 Social Expectations .......................................................................................... 41 Location Description ............................................................................................... 42 Research Objectives and Hypotheses .................................................................... 44 2 NUTRIENT ALGAL RESPONSE RELATIONSHIPS IN STORMWATER PONDS . 50 Introduction ............................................................................................................. 50 Methods .................................................................................................................. 52 Results and Discussion ........................................................................................... 54 Conclusion .............................................................................................................. 58 3 IDENTIFYING SIGNIFICANT FACTORS INFLUENCING STORMWATER POND NUTRIENT AND ALGAE CONCENTRATIONS .......................................... 68 Introduction ............................................................................................................. 68 Methods .................................................................................................................. 72

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7 Results and Discussion ........................................................................................... 74 Conclusion .............................................................................................................. 82 4 CREATING A COMMUNITY BASED CHLOROPHYLL A THRESHOLD FOR STORMWATER PONDS ........................................................................................ 89 Introduction ............................................................................................................. 89 Methods .................................................................................................................. 91 Results and Discussion ........................................................................................... 94 Identi fied Mean Treatment Thresholds ............................................................. 94 Impact of Pond Use on Mean Treatment Threshold ......................................... 96 Knowledge and Educational Influence on Mean Treatment Threshold ............ 99 Demographic Drivers of Mean Treatment Threshold ...................................... 103 Conclusion ............................................................................................................ 105 5 METHODS FOR IDENTIFYING AND QUANTIFYING IMPACT OF NUMERIC THRESHOLD IN STORMWATER PONDS ........................................................... 115 Introduction ........................................................................................................... 115 Methods ................................................................................................................ 117 Nutrient Management Threshold .................................................................... 117 Nutrient Assimilation Potential ........................................................................ 118 Results and Discussion ......................................................................................... 119 Nutrient Management Threshold .................................................................... 119 Nutrient Assimilation Potential ........................................................................ 121 Conclusion ............................................................................................................ 122 6 CONCLUSION ...................................................................................................... 1 30 Findings ................................................................................................................ 130 Future Research Implications ............................................................................... 135 APPENDIX : COMMUNITY BASED STORMWATER POND MANAGEMENT SURVEY ............................................................................................................... 139 LIST OF REFERENCES ............................................................................................. 161 BIOGRAPHICAL SKETCH .......................................................................................... 180

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8 LIST OF TABLES Table page 1 1 EPA Approved Numeric Criteria for Florida’s Lakes ........................................... 49 2 1 Mean, median, standard error, and minimum and maximum values for total phosphorus, total nitrogen and chlorophyll a concentrations in stormwater ponds com pared to Numeric Nutrient Criteria ..................................................... 60 2 2 Empirical models and summary statistics describing the association of monthly average nutrient and chlorophyll concentrations using data from stormwater ponds in a southwest Florida community and Florida Lakes ............ 61 3 1 Management and landscaping variables evaluated for significance as predictors of total phosphorus, total nitrogen and chlorophyll a concentrations in stormwater ponds. .......................................................................................... 83 3 2 Empirical models and summary statistics describing the association of nutrient and chlorophyll concentrations using significant management and landscaping predictors from stormwater ponds in southwest Florida ................. 85 3 3 Summary statistics for significant predictor variables of total phosphorus, total nitrogen and chlorophyll a stormwater po nd models in southwest Florida .. 86 4 1 Demographic survey questions and responses with no significant difference in mean treat ment threshold between responses ............................................. 107 5 1 Empirical models and summary statistics describing the association of monthly average nutrient and chlorophyll concentrations and median percent algal assimilated phosphorus or nitrogen using data from stormwater ponds .. 124 5 2 Quadratic models and summary statistics describing the association of monthly average nutrient and chlorophyll concentrations and algal assimilated phosphorus or nitrogen associated with the identified threshold ... 124 5 3 Florida’s Numeric Nutrient Criteria and the stormwater pond nutr ient management criteria established for a residential community in southwest Florida. ............................................................................................................. 125 5 4 Summary statistics describing the estimated assimilated algal phosphorus (AAP) and assimilated algal nitrogen (AAN) for clear and colored stormwater ponds for a residential community in southwest Florida. .................................. 125

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9 LIST OF FIGURES Figure page 1 1 Stormwater pond interactions and drivers .......................................................... 49 2 1 Location of 36 stormwater ponds sampled ......................................................... 62 2 2 Regression analysis between annual geometric mean chlorophyll a concentration and annual geometric TP concentration in clear Florida lakes clear stormwater ponds in southwest Florida ...................................................... 63 2 3 Regression analysis between annual geometric mean chlorophyll a concentration and annual geometric TP concentr ation in colored Florida lakes compared to colored st ormwater ponds in southwest FL ......................... 64 2 4 Regression analysis between annual geometric mean chlorophyll a concentration and annual geometric TP concentration in West Central Peninsular Region colored, Florida lakes compared to colored stormwater ponds located in the same region ....................................................................... 65 2 5 Regression analysis between annual geometric mean chlorophyll a concentration and annual geometric TN concentration in clear Florida lakes compared to clear stormwater ponds in southwest FL ....................................... 66 2 6 Regression analysis between annual geometric mean chlorophyll a concentration and annual geometric TN concentration in colored Florida lakes compared to colored st ormwater ponds in southwest FL .......................... 67 3 1 Variables identified as significant predictors of phosphorus, nitrogen and chlorophyll a concentrations in stormwater ponds .............................................. 88 4 1 Series of ten photos depicting water column chlorophyll a concentrations increas ing in increments of five from 5 gL1 to 50 gL1 over a sandy bottom including submerged aquatic vegetation. .............................................. 108 4 2 Series of ten photos depicting water column chlorophyll a concentrations increasing in increments of five from 5 gL1 to 50 gL1 over a sandy bottom. ............................................................................................................. 108 4 3 Comparison of mean chlorophyll a concentration (gL1) response of four survey treatments ............................................................................................. 109 4 4 Comparison of mean treatment threshold based on pond use ......................... 110 4 5 Comparison of mean treatment threshold associated with know ledge of stormwater pond origin ..................................................................................... 111

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10 4 6 Comparison of mean treatment threshold associated with stormwat er pond education and awareness ................................................................................. 112 4 7 Mean treatment threshold associated with resident perceptions of alg ae function in stormwater ponds ............................................................................ 113 4 8 Comparison of mean treatment threshold associat ed with demographic information ........................................................................................................ 114 5 1 Models displaying treatment threshold and numeric phosphorus values with associated algal phosphorus assimilation values. ............................................ 126 5 2 Models displaying treatment threshold and numeric nitrogen values with associated algal nitrogen assimilation values. .................................................. 127 5 3 Estimated algal assimilated phosphorus (AAP g m3) in stormwater ponds at chlorophyll a concentrations from 5 to 30 g L1. .............................................. 128 5 4 Estimate d algal assimilated nitrogen (AAN, g m3) in stormwater ponds at chlorophyll a concentrations from 5 to 30 g L1. .............................................. 129 6 1 Variables identified as significant predictors of phosphorus, nitrogen and chlorophyll a concentrations in stormwater ponds ............................................ 138

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11 WORKING DEFINITIONS Designated Use State of Florida policy defined u ses of a water body with specific protective criteria for water quality. Impaired Waters that do not meet protective water quality standards for the designated use (United States Environmental Protection Agency, 2013) . Non point source Any source of water pollution not legally defined as point source in the Clean Water Act, including but not limited to runoff from land caused by precipitation and/or irrigation, atmospheric deposition, drainage, and seepage (Davis & McCuen, 2005; United States Environmental Protection Agency, 2012) . Point s ource “Any discernible, confined and discrete conveyance, including but not limited to any pipe, ditch, channel, tunnel, conduit, well, discrete fissure, container, rolling stock, concentrated animal feeding operation, or vessel or other floating craft, from which pollutants are or may be discharged. This term does not include agricultural stormwater discharges and return flows from irrigated agriculture.” (33 U.S.C. 1251 et seq., p. 214) Stormwater Storm water, snow melt, and surface water runoff and drainage (40 C.F.R. 122.26(b)(13)) . Total Maximum Daily Load (TMDL) The Total Maximum Daily Load (TMDL) Program, instituted by the United States Environmental Protection Agency (EPA), requires a state to identify its impaired water bodies, develop a total maximum daily load necessary to eliminate the impairment in each water body, and then enact each plan throughout the state (United States Environmental Protection Agenc y, 2013)

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12 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy MANAGING EXPECTATIONS: CREATING A COMMUNITY BASED STORMWATER POND NUTRIENT MANAGEMENT PROGRAM By Charles Patrick Nealis December 2015 Chair: Mark Clark Major: Soil and Water Science Degradation of surface waters is a critical concern in the state of Florida. Regulatory frameworks and best management practices (BMPs) exist to protect the designated uses of natural surface waters and reduce the impact of runoff from upstream activity. S tormwater ponds (SWPs) are an increasingly popular BMP in residential developments and are assumed to remove at least 80% of the nutrient load from the contributing watershed to meet regulatory requirements. Residential SWPs also generate a property value premium by creating “waterfront” property with social expectations related to aesthetics and recreational value. The management of SWPs to meet social expectations often includes the removal of biological responses to increased nutrient concentrations, res ulting in a reduction of the nutrient removal efficiencies and failure to meet regulatory requirements. In this study, a method was developed to quantify social expectations of SWPs and define numeric nutrient criteria required to meet social demands and r egulatory criteria. Nutrient and chlorophyll a water column concentrations in SWPs within a southwest Florida community were sampled and significant nutrient response relationships were established for clear and colored systems. The SWP nutrient response r elationships were compared to those

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13 established for Florida’s numeric nutrient criteria for natural lakes and found to be weaker but significantly different. To quantify social expectation criteria, a webbased survey was created to identify thresholds of impairment based on water column chlorophyll a concentrations. Results indicated mean community based thresholds range from 2030 g l1. Preferred thresholds were found to increase with frequency of use for recreational activities and respondents who corr ectly identified the role of algae in SWPs had significantly greater thresholds than those who did not. Age, seasonality of residence, sex and presence of children in the household were also found to have a significant impact on preferred thresholds. Based on the identified community based thresholds and nutrient response relationships, SWP numeric nutrient criteria were established and the potential impacts were estimated. The findings and methods identified in this study indicate the significant potential to effectively meet regulatory requirements and social expectations of SWPs, improving management practices and reducing downstream impacts of runoff from residential development.

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14 CHAPTER 1 WATERFRONT WARS AND THE NEED FOR INTERVENTION The Growing Conflict Florida’s climate , location and natural attractions have long been a powerful draw for visitors and transplant residents . The attraction has led to Florida recently becoming the t hird most populous state in the United States with a population of 19.9 million people, increasing at over 800 new residents per day (United States Census Bureau, 2014) . Florida continues to be a popular tourist destination as well , hosting a record high 94.7 million visitors in 2013 (Jackovics, 2014) . Growth has come with a cost , greatly straining the state’s natural resources as an estimated 10,000 acres per year are converted to residential, industrial, commercial and infrastruct ural development to meet the demands of an increasing population (Francesconi & Stein, 2008) . Accordingly, overall freshwater use has increased and public water use has become the largest consumer, surpassing agriculture in 2010 and demanding 2.3 billion gallons per day and expected to escalate significantly with increased population growth and demand (Florida Department of Environmental Protection, 2014) . As water use and land development have increased, an increasing number of Florida’s fresh and salt water resources have been negatively impacted by nutrient runoff f rom activities in the watershed. Identifying and preventing pollution from the many nonpoint source s has been extremely difficult and protective policies and practices have been implemented on a variety of scales and with varying success. National, state and local regulatory programs attempt to identify and control polluted runoff while new practices are impl emented in design and management of current and future development, creating an amalgam of protective policies in an attempt to ensure

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15 environmental integrity and prevent further degradation. Urban s tormwater runoff is a major source of nutrient pollutants to surface water bodies in Florida (Livingston & McCarron, 1992; Roach, et al., 2008) and s tormwater management provides one promising avenue for effectively addressing nonpoint source pollution (Roy, et al., 2008) . Unfortunately, numerous gaps often exist between policy planning , understanding and management when individuals and communities make decisions regarding nutrient reduction, resulting in conflict between individual expectations, regulatory requirements and environmental protection. The dispute between the protection of Florida’s surface water quality and the protection of individual s’ property values, aesthetics and expectations has created a “Waterfront War ” between residents and often unintentional environmental impacts . Stormwater ponds represent the epicenter of the struggle to balance development and the environment . The interactions and drivers of stormwater pond function are summarized in Figure 1 1 and described in the following sections of this chapter . Originally, s tormwater ponds were utilized as a regulated stormwater management strategy designed and assumed to protect natural ecosystems by mitigating the impact of activities within the watershed on downstream water quantity and quality (Anderson, Watt, & Marsalek, 2002; Roy, et al., 2008) . Currently, however, stormwater ponds are increasingly integrated into low relief areas of developments as landscape features (Collins, et al., 2010; Schueler T. , 1997) and maintained for their aesthetic, recreational and economic value to community stakeholders (DeLorenzo, Thompson, Cooper, Moore, & Fulton, 2012; Serrano & DeLorenzo, 2008) . The intended

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16 design and function of stormwater ponds to protect downstream, natural systems by reducing runoff pollution rarely coincide with stakeholder expectations as communities manage the stormwater ponds for aesthetic values . In addition, evaluation of conventional stormwater pond design criteria indicate that nutrient load reduction expectations are not being met and that source controls, pretreatment strategies and alternativ e pond management strategies are needed (Harper & Baker, 2007) . As more natural surface water bodies are impaired by nutrients, identifying opportunities to improve effectiveness of existing infrastructure and adoption of new practices will be required. Creating a management regime to better address the dual function of stormwater ponds as a nutrient reduction strategy and aesthetic, community asset is essential to identifying compatible practices and ensuring the adoption and e ffectiveness of more environmentally friendly and sustainable ideals. The Impact of Nutrients on Surface Water Resources Freshwater resource degraded by humaninduced eutrophication in the United States has led to annual economic losses in recreational water use, property value, endangered and threatened species recovery and drinking water estimated at more than 2.2 billion dollars (Dodds, et al., 2009) . Nutrie nt loss from anthropogenic activities contribute greatly to freshwater resource degradation as 90% of the rivers in 12 of the 14 ecoregions in the United States contain excess phosphorous (3 times higher ) and nitrogen (5.5 times higher ) compared to established reference levels (Dodds, et al., 2009) . Florida, a state long known for and dependent upon its water resources, currently faces severe resource degradation due to w ater scarcity, water quality degradation and natural ecosystem loss (Mustafa, Smucker, Ginn, Johns, & Connely, 2010) .

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17 Florida’s natural resources have long been affected by the growing demand of anthropogenic activity within the state. Florida has experienced substantial losses of natural habitat to human activity and development since 1935, losing 22% of the natural forest cover and 51% of the natural marsh area while increasing agricultural areas 60% and urban areas 632% (Mustafa, Smucker, Ginn, Johns, & Connely, 2010) . Florida’s remaining natural areas , including hundreds of miles of coastline and rivers, continue to be increasingly impacted by nutrient loading from further population growth and development. Increase of Nutrients in Surface Waters and Urban Land Use Development in urban and suburban areas of Florida has led to increased nonpoint source runoff and nutrient loading to surface water resources (Dauer, Weosnerg, & Rannasinghe, 2000; Osborne & Wiley, 1988) . Development and conversion of lands to urban and residential areas reduces infiltration and increases the overland transport of nitrogen and phosphorus to surface waters (Paul & Meyer, 2001; Walsh, Fletcher, & Ladson, 2005) . These nutrients are the primary cause of water quality impairment in Florida (United States Environmental Protection Agency, 2014) and upland, nonpoint sources representing the primary contributor of phosph orus to freshwater systems (Sharpley, et al., 1994; Daniel, Sharpley, Edwards, Wedepohl, & Lemunyon, 1994) . The process of converting natural and agricultural landscapes to urban and residential areas has had a signif icant impact on nutrient loading to downstream environments. Construction and runoff associated with development can produce high sediment loads in urban watersheds, carrying a multitude of potential pollutants into surface water bodies (Schueler & Simpson, 2004) . Runoff and sediment nutrient

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18 concentrations are closely related to land use and management (Graves, Wan, & Fike, 2004) and c onversion of agricultural land to res idential land use can result in the mobilization of large amounts of legacy soil phosphorus (Daniel, Sharpley, Edwards, Wedepohl, & Lemunyon, 1994; Sharpley, et al., 1994) . Following the conversion into residential la nd use, the application of additional landscape fertilizer can further increases the potential phosphorus runoff to aquatic systems like ponds, streams and lakes (Fluck, Fonyo, & Flaig, 1992; United States Environmental Pro tection Agency, 1996) . In addition to applied nutrient loss, dissolved losses of soil phosphorus can be extremely high once the soil phosphorus absorption capacity is exceeded (Sims, Simard, & Joern, 1998) . Unfortunately f or reasons of awareness, n egative environmental impacts resulting from phosphorus application and accumulation in soils may not be expressed in downstream freshwater systems for many years (ReedAnderson, Carpenter, & Lathrop, 2000) . W ater quality problems and changes in aquatic ecosystem productivity may appear abruptly once an assimilation threshold in the system is surpassed (Heckrath, Brookes, Poulton, & Goulding, 1995) . Conversely, s oil phosphor us accumulation and subsequent release can also cause lags between management actions to control resulting water quality issues and achieving desired results (Stigliani, et al., 1991) . Residential landscape preferences and mana gement further increase nonpoint source pollution to downstream water bodies once the landscape has been converted. Intensely managed turfgrass lawns are a dominating feature in residential landscapes and have been promoted and perceived as a source of individual and social good for nearly 200 years (Downing A. , 1844; Fein, 1972; Schroeder F. , 1993) as the present

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19 idea of a perfect, ordered, and monoculture lawn is constantly marketed through numerous media i magery outlets (Bormann & Balmori, 1993) . Although turfgrass has been criticized by many for its negative environmental impact, the management decisions and resident actions associated with turfrass, not the turfgrass itself, m ay be the defining cul prit of downstream degradation. Mismanagement of turfgrass can have tremendous negative impacts on the environment . Studies have shown bet ween 50 and 75% of households apply fertilizer to their lawn (Carrico, Fraser, & Bazuin, 2013; Fissore, et al., 2011; Law, Band, & Grove, 2004; Robbins, Polderman, & Birkenholtz, 2001; United States Environmental Protection Agency, 2004) and the hig h density and frequency of fertilizer applications by individuals within an urban watershed will collectively contribute to increased nutrient concentrations in urban surface water bodies (Serrano & DeLorenzo, 2008) . R esidents personally caring for their lawn rarely receive training regarding application, storage, handling and disposal of turfgrass chemicals, or education on the environmental impacts of their use and decisions (Carrico, Fraser, & Bazuin, 2013) . Fertilizing turfgrass lawns at rates exceeding plant and soil requirements can lead to greater nutrient loss and negative downstream environmental impacts (Fissore, et al., 2011; Law, Band, & G rove, 2004; Trenholm, Unruh, & Sartain, 2012; Soldat & Petrovic, 2008) . Additionally, improper use of turfgrass fertilizer can lead to further loss of soil nutrients, acidification of soils and surface water, accelerated loss of biodiversity, contaminated resources and the release of nitrous oxide (Vitousek, et al., 1997) . Improper irrigation compounds nutrient runoff in residential areas , carrying nutrients and other pollutants to downstream water bodies (Kjelgren, Farag, Neale, Endter Wada,

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20 & Kurtzman, 2002) and stressing water resources through consumption and pollution (Martin C. , 2001; Baker, Wilson, Fulton, & Horgan, 2008; Yabiku, Casagrande, & Farley Metzger, 2008; Milesi, et al., 2005) . Typically, r unoff from turfgrass landscaping contains approximately 0 .5 2.0 mg phosphorous and 3.05.0 mg nitrogen per liter (Barten & Jahnke, 1997; Easton & Petrovic, 2004; Shuman, 2004; Waschbusch, Selbig, & Bannerman, 1999) and is often distributed to stormwater ponds or natural waterbodies via stormwater conveyance structures included during development. A large volume of r unoff contai ning nutrient concentrations of this level is capable of causing eutrophication in any receiving water body, natural or created (Baker, Wilson, Fulton, & Horgan, 2008) . Role of Nutrients in Surface Water Impairment Excess enrichment of phosphorus and nitrogen in surface waters leads to degradation through eutrophication, or the increasing supply of organic matter to the system (Carpenter, et al., 1998) . Degradation, identified as a change in int egrity of the natural system, species or use (Postel & Carpenter, 1997) , leads to impairment of the water body if it is found to be unsuitable for the assigned designated use (Florida Administrative Code) . C hanges in benthic invertebrates, vascular plants, fish, periphyton, and phytoplankton biomass/community structure are indicators of ecological imbalance or impairment caused by increases in nutrient concentrations (Havens & Schelske, 2001; Livingston R. , 2001; Kennish, 1999) . Algae Increased algal growth is one of the most recognizable and adverse effects of eutrophication in Florida surface waters. Phytoplankton communities may shift to bl oom forming nuisance algae when water bodies are enriched with a limiting nutrient (Smith,

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21 1990) and t he decomposition of the algae can cause oxygen depletion in the water column, resulting in fish kills and nuisance complaints regarding aesthetics and odor (Carpenter, et al., 1998; Smith, 1998) . Some a lgal bloo ms can also produce toxins (Lawton & Codd, 1991) , eliminate native plants, and drastically diminish the biodiversity of an aquatic ecosystem (Smith, 1998) . Chlorophyll a is often used as a measure of the algal standing crop (Dillon & Rigler, 1974) and is one of the most visible indicators of eutrophication in a surface water body (Havens, 2003) . In Florida, an algal bloom refers to chlorophyll a concentrations greater than 40 gL1 (Walker & Havens, 1995; Havens & Walker, 2002) , a level also identified as a “ severe nuisance” in other states (McGhee, 1983) . Concentrations of c hl orophyll a do not have to reach algal bloom levels to be considered problematic as chlorophyll a concentrations greater than 20 gL1 have been associated with nuisance or unwanted conditions (Heis kary & Walker, 1988; Florida Department of Environmental Protection , 2012) . Managing and controlling algal blooms can be difficult as a lag often exists between nutrient dose and algal response in aquatic systems , both in the near and long term . Alga l mass within an aquatic system is not immediately respondent to nutrient enrichment as the algae requires time to uptake and incorporate nutrients into additional biomass under influence of other environmental conditions (United St ates Environmental Protection Agency, 2010) . It is also extremely difficult to predict the immediate and prolonged impact of management decisions reducing loads of nitrogen and phosphorus to an aquatic ecosystem in an attempt to control eutrophication (Jacoby & Frazer, 2009) . Noticeable impairment of aquatic systems may appear long

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22 after phosphorous accumulation in upstream soils, sediments and aquatic systems are elevated enough to continue contributing phosphorus to the system for an extended future amount of time (Bennett, Carpenter, & Caraco, 2001) . Nutrient runoff into lakes is highly influenced by climate (Florida Department of Environmental Protection , 2012) , but there are no consistent seasonal or wet and dry period patterns in algal and chlorophyll a response to total nitrogen (TN) and total phosphorous (TP) in Florida (United States Environmental Protection Agency, 2010) . I ncreasing trends of nutrient and chlorophyll a concentrations within the system are the result of increasing external and/or internal loads of nutrients to the surface water body, turnover time, and temperature and are exacerbated when loading exceeds inte rnal, biological assimilation processes and downstream export (Florida Department of Environmental Protection , 2012) . Nutrients The major nutrients required by aquatic organisms include carbon, oxygen, hydrogen, nitrogen and phosphorus (Wetzel, 2001) . Nitrogen and phosphorus most often affect the primary productivity in freshwater systems, with one nutrient in excess and the other considered limiting since its lack of availability inhibits increased growth (Suplee, Watson, Varghese, & Cleland, 2008) . The relationship of nitrogen to phosphorus, or N:P ratio, most often determines the limiting nutrient controlling algal growth in in freshwater lakes . S ystems with an N:P ra tio less than 7:1 are considered nitrogen limited, systems with an N:P ratio greater than 20:1 are considered phosphorus limited and systems with an N:P ration between 7:1 and 20:1 are considered colimited (Guildford & Hecky, 2000) . Excess supply of limiting nutrients can cause increased algal and/or macrophyte growth beyond the capacity of natural grazer control, leading to

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23 undesirable and detrimental water quality including decreased water clarity and dissolved oxygen levels (Florida Department of Environmental Protection , 2012) . Controlling or preventing eutrophication in freshwater systems usually focuses on decreasing phosphorus inputs as it is often considered the limiting nutrient , but several studies suggest nitrogen must be controlled as well (Schindler, et al., 2008; Conley, et al., 2009) , especially when considering downstream impacts of freshwater to saltwater systems (Paerl, 2009) . Algal response to increased phosphorus concentrations can be reduced by alternative nutrient limitation (Canfield, 1983) and an over abundance of available phosphorus can lead to nitrogen limitation in f reshwater systems (Schindler, 1971) . The constraint on algal production by the synergistic interaction between nitrogen and phosphorus, known as colimitation, occurs often in freshwater lakes (Harpole, et al., 2011; Maberly, King, Dent, Jones, & Gibson, 2002) so it is important to reduce both nitrogen and phosphorus runoff to prevent eutrophication unless there is a clear driver and defined limiting nutrient (Con ley, et al., 2009) . The role of nitrogen in freshwater systems is often overlooked. Sole focus on r educing nitrogen input to a water body does not reduce algal biomass within the water body (Smith & Schindler, 2009; Schindler, et al., 2008) , but nitrogen concentration in runoff from residential land uses is a significant concern. Reducing nitrogen runoff is important as nitrogen control within lakes can be expensive and unnecessary due to the presence of nitrogen fixing cyanobacteria (Schindler & Hecky, 2009) that can bloom when phosphorus is abundant and nitrogen becomes the limiting nutrient (Conley, et al., 2009) . Additionally, r esults from a study by Paerl et al (2004) , suggest both nitrogen and phosphorus reductions may be needed in freshwater systems when the freshwater

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24 system is connected to estuarine/marine systems where nitrogen is the limiting nutrient . Nitrogen in the i norganic form is the most soluble and readily assimilated form of nitrogen and runoff from resid ential land use has a greater fraction of inorganic nitrogen (18%) than runoff from other urban land uses (11%) (Gra ves, Wan, & Fike, 2004) . Nitrogen has a positive, predictive relationship with chlorophyll a in freshwater lakes and protective criteria have been established for nitrogen concentrations (Florida Department of Environmental Pr otection , 2012) . A lgal p roduction in most freshwater ponds and lakes , however, depends on phosphorus input as phosphorus is usually the limiting nutrient (Schindler, 1977; Schindler, 1974) . T otal phosphorus (TP) concentration is an indicator of trophic state in natural , freshwater lake systems (Dillon, 1975) and can be used as an indicator of algal population densities measured by the chlorophyll a concentration (Jones & Bachmann, 1976) . The relationship between chlorophyll a and TP is significantly positive in Florida (Canfield, 1983; Mazumder & Havens, 1998) , but caution must be practiced in predicting algal response as chlorophyll a per unit TP can be reduced by zooplankton grazing (Mazumder, 1994) , abiotic turbidity (Phlips, et al., 1997) and nitrogen limitation (Canfield, 1983) . Water color may also suppress the TP /chlorophyll a relationship as color reduces light penetration in the water column (Havens, 2003) . Additionally, not all phosphorus in a freshwater system is available to contribute to algal growth. Only dissolved inorganic phosphorus is considered immediately bioavailable while organic and particulate forms must usually undergo transformations to inorganic forms before becoming bioavailable (Reddy, Kadlec, Flaig, & Gale, 1999) . Available phosphorus can also become unavailable in aquatic systems through com plexation with dissolved

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25 organic material (Jackson & Hecky, 1980) , precipitation and assimilation into particulate matter by plants (Reddy & DeLaune, 2008) . Urban surface waters Lakes in urban and developed residential settings tend to receive higher nutrient loads from stormwater runoff than lakes in non urban settings (Schueler & Simpson, 2004) . Upland residential fertilizer application, activity and erosion can be considerable contributors of phosphorus and nitrogen to lake systems (Carpenter, et al., 1998; Law, Band, & Grove, 2004; Gaddis, Vladich, & Voinov, 2007; Groffman, Law, Belt, Band, & Fisher, 2004; Strynchuk, Royal, & England, 1999) . Soil particles eroded into lakes or ponds are also an important contributor of phosphorus (Daniel, Sharpley, Edwards, Wedepohl, & Lemunyon, 1994; Sharpley, et al., 1994) , especially during large rain events (Pionke, Gburek, Sharpley, & Zollweg, 1997) . Overall surface water runoff from all activities in residential land use areas has been reported to have a typical TP concentration ranging from 0 .22 to 0.52 mg L1 and total nitrogen ( TN ) concentrations ranging from 1.61 to 2.32 mg L1 (Graves, Wan, & Fike, 2004; Harper & Baker, 2007) . External nutrient loading is not the only source of phosphorus within lakes and ponds ; however , w hen reducing external phosphorus loading does not reduce eutrophication it is often due to internal loading from sediments in the lake or pond (Schindler & Hecky, 2009) . In addition to release from the sediment, urban lakes have several other unique internal phosphorus sources, including waterfowl and recreation activity (Schueler & Simpson, 2004) . Many of the current nutrient reduction strategies and regulations focus on reducing nonpoint source pollution, or stormwater runoff, from u rban sources through design and assumed compliance. The inclusion of stormwater ponds and other nutrient

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26 sinks in the landscape design can help reduce nutrient runoff from reaching natural aquatic systems (Novotny & Olem , 1994; Soranno, Hubler, Carpenter, & Lathrop, 1996) but the actual nutrient removal efficiencies do not currently meet regulatory requirements (Harper & Baker, 2007) . Incorporating more efficient nutrient application and better landscape management practices in upland systems can reduce downstream eutrophication (Bennett, Carpenter, & Caraco, 2001) and may also help improve design removal efficiencies . New strategies incorporating both source control and treatment practices must be researched, developed and implemented to better meet regulatory requirements and downstream protection. Regulatory Framework Protecting Water Resources Improving water quality protective practices requires a clear understanding of the current regulatory framework protecting water resources. Water resource management in t he United States is often handled independently by different agencies and stakeholders in response to a problematic pollutant, polluter or sensitive landscape feature following public outcry stemming from the failure of a water resource to meet a certain perceived societal need or expectation that has never been fully vetted with a comprehensive set of social values (Sabatier, et al., 2005) . The resulting strategies are often controversial, limited in scope and focused on physical manipulation as a solution to water resource problems as opposed to source control and preventative strategies (Gleick, 20 00) . Over time, policy and associated regulations have integrated more collaborative approaches to address water resources issues and engage stakeholders to improve program success. The scale of regulation and management, from federal law to community codes and covenants, are all important in establishing an effective foundation protecting water resources.

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27 Clean Water Act The Federal Clean Water Act, established in 1972, is the foundation for supporting the protection of water quality in Florida. The Federal Clean Water Act requires states adopt water quality criteria to protect the designated uses of surface waters based on sound scientific rationale and federal, state, municipal and industrial entities to investigate, develop and enact programs protecting water bodies and preventing, reducing or eliminating pollution (33 U.S.C. 1251 et seq.) . The Clean Water Act provided greater clar ity and enforcement than prior regulations by requiring permits for point sources discharging pollutants into water bodies through the National Pollutant Discharge Elimination System (NPDES) , protecting water quality, wildlife and recreational use of navigable waters (33 U.S.C. 1251 et seq.; Davis & McCuen, 2005) . Runoff from activities within urban areas, including nutrients and contaminants from landscaping and impervious surfaces, is considered nonpoint source pollution and is not as easily identified or controlled as point sources. Multi ple phases of the NPDES have been implemented to reduce stormwater impact on natural water bodies. Phase I of the NPDES required stormwater permits for ten categories of industrial activities, construction discharge on five or more acres of land, and munic ipal separate storm sewers (MS4s) discharge in medium and large urban areas of 100,000 or more individuals (United States Environmental Protection Agency, 2014b) . Phase II expanded the stormwater permit requirement to smaller construction site operators, MS4s in smaller urban areas , and MS4s outside of urban areas designated by the permitting authority to obtain NPDES coverage (United States Environmental Protection Agency, 2014b) . Under Phase II of the NPDES and section 402(p)(3)B) of the Clean Water Act, stormwater pollutants must be reduced to the

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28 maximum extent possible (33 U.S.C. 1251 et seq.) . A Stormwater Management Plan including six minimum control measures is required by Phase II applicants, identifying public education and outreach, public participation and involvement, illicit discharge detection and elimination, construction site runoff control, post construction runoff control and pollution prevention p rocedures (United States Environmental Protection Agency, 2014b) . Florida’s Stormwater Management In conjunction with the Clean Water Act and efforts to manage flooding , Florida has implemented numerous measures to better manage and protect water quality. Regulatory requirements and roles have evolved over several decades to improve the management of stormwater runoff and implement ation of protective practices in the wat ershed. The Water Resources Act of 1972 established a plan for regulating Florida’s water resources and created five regional water management districts drawn on hydrologic boundaries, localizing water management (Christaldi, 1996) . The act directed the Florida Department of Environmental Protection (FDEP) to delegate much of its authority to the water management districts , giving them the power to manage regional water resources and develop rules, procedures and policy for wat er resources within the district (Christaldi, 1996) . The Water Resources Act allowed for local administration of state rules and regulations, creating statelevel and regionally specific implementation of planning and policy de cisions (Christaldi, 1996) . Florida statute also required FDEP to protect water quality and FDEP delegated the authority to do so to the five Florida water management districts (WMDs) (73.403. 469) . The WMDs utilize environmental resource permits protective of Florida’s water

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29 qu ality standards to exercise their authority . N ew and existing development s contributing to violations of the water quality standards must provide reasonable, documen ted assurance discharges will not violate state water quality standards to be issued a permit (Rupert & Ankerson, 2008) . No additional permits causing or contributing to a water quality violation can be approved by the WMD if a waterbody is currently in violation of state water quality standards (Rupert & Ankerson, 2008) . WMDs and FDEP also have the responsibility to manage and assign nutrient loads to sources as part of the Total Maximum Daily Load ( TMDL ) process. FDEP has authority over the TMDL program following the 1999 passage of the Florida Water Restoration Act (Hue ber, 2010) and is able to establish Basin Management Action Plans ( BMAPs ), or basin specific strategies for reducing waterborne pollutants. Planning and implementation of these plans are shared by FDEP and the water management districts (Hueber, 2010) . The enforceable regulatory scheme of BMAP obligations of nonpoint sources was important as it created an enforcement mechanism where no prior option existed, but could be strengthened in respect to identifying violators and ensuring compliance. BMAP program success and pollutant reduction can be improved through involvement and cooperation of stakeholders in the development and implementation of the program (Hueber, 2010) . Specifically including BM Ps in Conditions, Covenants and Restrictions of homeowners associations (HOAs) and delegating enforcement rights to local governments and WMDs could improve compliance and enforcement (Rupert & Ankerson, 2008) .

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30 Water Quality S tandards Florida was the first state in the country to adopt a rule dictating a specified level of stormwater pollutant load reduction. Florida’s performance standard required all new developments following the 1972 Water Resources Act to reduce post development stormwater pollutant loading of total suspended solids (TSS) by at least 80% (Florida Department of Environmental Protection, 2011) . The 80% level of treatment was chosen to create equal treatment req uirements for point and nonpoint sources and set a realistic goal as the cost of stormwater treatment increases tremendously with additional treatment above 80% (Florida Department of Environmental Protection, 2011) . The State Water Resource Implementation Rule amended the expectation of stormwater treatment in 1990 beyond TSS to include removal of 80% of all post development stormwater pollutants causing or contributing to water quality standard violations, including nitrogen and phosphorus (Florida Department of Environmental Protection, 2011) . Stormwater infrastructure design criteria and WMD permitting rules necessary to meet the updated treatment requirement , however, have never been revised acco rdingly despite the updated state and federal water quality regulation. The stormwater rule relies upon a minimum level of treatment goal, a design criteria for achieving established goals, a rebuttable presumption stormwater systems following the design criteria will not harm water resources , and a periodic review and update of the design criteria to ensure continual improvement and success (Florida Department of Environmental Protection, 2011) . The goal of resource preservati on, stormwater treatment, and pollution load reduction is established and legitimized in the Water Resource Implementation Rule, chapter 6240 of the Florida Administrative Code (Harper & Baker, 2007; Florida Administrative Code ) .

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31 The Surface Water Quality Standards and minimum water quality levels necessary to protect present and future most beneficial uses of waters are defined and surface waters are classified in section 62302 of the Florida Administrative Code (Harper & Baker, 2007; Florida Administrative Code ) . Water quality classifications are listed in decreasing order of required protection from Class I to Class V, with Class I, II and III surface waters including water quality criteria with recreational use considered (Florida Administrative Code) . Recreational use includes any activities providing value as a resource for outdoor recreational activities, including fishing, boati ng and nature observation (Florida Administrative Code) . The designated uses of Florida’s surface waters are: Class I Potable Water Supplies Class II Shellfish Propagation or Harvesting Class III Fish Consumption; Recreation, Propagation and Maintenance of a Healthy, WellBalanced Population of Fish and Wildlife Class III Limited Fish Consumption; Recreation or Limited Recreation; and/or Propagation and Maintenance of a Limited Population of Fish and Wildlife Class IV Agricultural Water Supplies Class V Navigation, Utility and Industrial Use (Florida Administrative Code) Florida established a Narrative Nutrient Criteria in 1974 to protect the designated use s of Class I and III surface waters (Obreza, et al., 2011; Florida Department of Environmental Protection, 2015) . The Narrative Nutrient Criteria identified impaired surface waters, or those waters not providing their designated use, based on changes in aquatic species compositi ons due to increased nutrients (Florida Administrative Code) . Surface waters would be identified as impaired if there was a detectable change in the composition of aquatic species populations due to increased nutrients.

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32 Recently, however, t he United States Environmental Protection Agency (EPA) determined Florida’s narrative criteria was not protective of water quality and numeric stan dards were necessary to meet Clean Water Act requirements (Obreza, et al., 2011) . The EPA published numeric nutrient criteria (NNC) establishing numeric water quality criteria for nutrients and response variables, including chlorophyll a , interpreting narrative criteria for Class I and I II surface waters based upon FDEP research and recommendations (Florida Department of Environmental Protection , 2012) . The EPA defined the NNC (Table 11) for an individual system based on several variables influencing the rel ationship between chlorophyll a concentration and the TP or TN concentration. Chlorophylla values of 6 gL1 PCU), low alkalinity lakes and 20 g L1 for colored (>40 PCU) high alkalinity lakes were chosen as thresholds protective of designated uses b ased on EPA guidance and the Impaired Waters Rule Technical Advisory Committee’s review and revision of the Trophic State Index used in 1998 303(b) report (Florida Depar tment of Environmental Protection , 2012) . The NNC was designed to protect aquatic life, water quality, public health and recreational uses of Florida waters from wastewater, urban stormwater runoff, and excess fertilizer pollution from anthropogenic activities within the watershed (Florida Department of Environmental Protection , 2012) . Additionally, maintaining the numeric criteria for an individual water body ensures attainment and maintenance of water quality standards for downstream waters (Obreza, et al., 2011) . Consistent with their development, Florida’s numeric nutrient standards are expressed as annual geometric

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33 means based on regular monitoring and cannot be exceeded more than once in a three year period. Even though the NNC established statewide standards, nutrient response concentrations and relationships in Florida are regionally diverse. Lakes located in the West Central Peninsula Nutrient Watershed Region (WCPNWR) have been identified as being potentially impacted by natural sources of phosphorous and variations in the stressor response variables have been noted. Colored lake systems in this region have a region specific maximum TP limit of 0 .49 mg L1 to pr otect downstream flowing waters (United States Environmental Protection Agency, 2010) . The increased TP threshold is due to the lack of a strong relationship between TP and chlorophyll a (r2=0.028; p =0.315) , as evaluated through a least squares regression analysis. Clear lake systems in the WCPNWR, however, showed a strong and statistically significant rela tionship between chlorophyll a and TP (r2=0.45; p <0 .001) as well as TN (r2=0.66; p <0.001) , and do not have a region specific limit (United States Environmental Protection Agency, 2010) . Local Ordinances and Restrictions Ordinances, restrictions and policies implemented at the local level can also contribute to water quality protection and maintenance of regional or statewide requirements. Local Florida governments can regulate stormwater as long as the regulatory program is not in conflict with state or federal laws (Rupert & Ankerson, 2008) . Local stormwater regulations, monitoring and control can provide an avenue for improving stormwater management by implementing zoning and planning initiatives pr otective of water resources and providing infrastructure and community services to reduce runoff pollution (Livingston E. , 1995) .

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34 For source control, c ounty wide fertilizer ordinances restricting residential fertilizer use during the rainy season are common practice in several Florida counties (Hochmuth, Nell, Unruh, Trenholm, & Sartain, 2012) . Most county fertilizer ordinances restrict application of nitrogen and phosphorus between June 1st and September 30th, with additional restrictions of application during a severe weather warning or watch (Manatee County, 2011; Hochmuth, Nell, Unruh, Trenholm, & Sartain, 2012) . Additionally, fertilizer ordinances c an suggest nutrient application rates, identify areas where fertilizer application is restricted, and recommend low maintenance or buffer zones to aid in reducing nutrient runoff (Manatee County, 2011; Hochmuth, Nell, Unruh, Trenholm, & Sartain, 2012) . Homeowners associations (HOAs) and Community Development Districts (CDDs) also represent local entities capable of regulating stormwater management. HOAs are generally responsible for operating and maintaining the stormw ater management system as they usually own and maintain the infrastructure and common areas within a development or community (Rupert & Ankerson, 2008) . Additionally, HOAs often are the operation and maintenance permit holder f or the stormwater system in new residential developments and incorporate covenants, conditions and restrictions (CCRs) to ensure the financial, legal and administrative capability of the HOA to maintain the stormwater system in perpetuity (Rupert & Ankerson, 2008) . Local governments can enforce CCRs only if it properly imposes the related CCRs on a development upon approval of a local stormwater permit, development of regional impact or planned unit development proposal and cann ot enforce private CCRs unrelated to the local government’s regulatory authority (Rupert & Ankerson, 2008) .

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35 Either way, HOAs are often depended upon to monitor and enforce CCRs because local governments commonly lack the resour ces to do so, but the local government can serve as a n important backstop should the HOA fail in their duties to enforce operation and management conditions (Rupert & Ankerson, 2008) . CDDs represent another important organization with many of the same powers as a local government, including the ability to levy and assess taxes and special assessments within the district (Rupert & Ankerson, 2008) . Unlike HOAs, th ey lack the statutory authority to enforce CCRs unless the CDD holds the rights to easements containing stormwater elements and language preventing adjacent property owners from damaging or interfering with stormwater control elements within the easement (Rupert & Ankerson, 2008) . The CDDs assessment and taxing power can provide incentive to better manage current stormwater issues as well as the means to collect money necessary to maintain the operations and management of the st ormwater structures (Rupert & Ankerson, 2008) . Reducing NonPoint Source Nutrient Pollution Using Stormwater Ponds Stormwater management is an important component of water quality protection in Florida, especially with the rece nt and projected growth of urban and residential areas. Effective stormwater management can serve several functions, from pollution reduction, erosion control, and water storage to aesthetic and recreational enhancement (Livingston & McCarron, 1992) . Stormwater runoff flows and nutrient concentrations are highly variable and difficult to predict (Davis & McCuen, 2005) and it is challenging to effectively design and implement a stormwater management system fitting of the social and regulatory needs (Schueler T. , 1995) . Stormwater pollution management can include structural or nonstructural controls managed and maintained at the state or local

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36 level . Structural controls are physical practices employed to manage water volume and peak discharge rate or contain or restrict stormwater flow to allow for treatment through settling, filtration, chemical treatment or biological uptake (Livingston & McCar ron, 1992) . Nonstructural controls include land use planning, resource protection, education, restrictions and/or practices implemented to prevent runoff pollution (Livingston & McCarron, 1992) . The primary goal of urban stormwater management and stormwater pond construction has historically been water volume control and flood prevention (Davis & McCuen, 2005; Livingston & McCarron, 1992) but stormwater ponds ar e also recognized for their benefit in protect ing downstream ecosystems by mitigating the impact of activities within the watershed on water quality and quantity (Anderson, Watt, & Marsalek, 2002; Roy, et al., 2008) . S tormwater ponds have been increasingly integrated into developments and community design as landscape features (Collins, et al., 2010) , especially in low relief areas like Florida where it is difficult to separate the high groundw ater table from the stormwater (Schueler T. , 1997) . Managing ponds to meet regulatory requirements and social expectations has led to difficulty in adequately maintaining and enhancing stormwater pond performance, but a par adigm shi ft focused on meeting requirements and expectations simultaneously may offer a sensible and effective solution. Regulatory Requirements Although regulatory enforcement of the Stormwater Rule requirements has been lax, the EPA’s TMDL program and Phase II of the Municipal Stormwater Sewer System Program and NPDES permit for stormwater discharge have heightened recent focus on nonpoint source runoff quality from urban landscapes (Baker, Wilson, Fulton, &

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37 Horgan, 2008) . A renewed focus on identifying, quantifying and reducing nutrient loads from residential communities is imminent with the increasing quantity and severity of impaired natural water bodies. The design and management of stormwater ponds should be conducive of nutrient removal processes through physical (sedimentation), chemical (precipitation and adsorption), and biological (uptake) mechanisms, and stormwater ponds built to the state criteria are assumed to meet the required nutrient removal efficien cies (Harper & Baker, 2007) . As designed and managed , however, the efficiency of stormwater ponds in reducing stormwater flow and retaining nutrients may be less than what is expected by permit (Harper & Baker, 2007) . The nature of the techniques used for treating stormwater and the internal design geometry of a stormwater pond are two very important factors influencing stormwater pond performance (Scheuler, 1994) . Stormw ater ponds are generally categorized as detention or retention ponds. R etention ponds discharge through infiltration and groundwater transport and drain completely within twenty four to seventy two hours (Vandiver & Hernandez, 2009; Livingston & McCarron, 1992) . Infiltration utilizes the natural nutrient removal capacities of soil and vegetation as water moves through the soil profile, before it reaches groundwater or surface water (Ferguson, 1990) . As stormwater moves through the soil profile phosphorus and other contaminants tend to accumulate in the upper soil layers, depending on organic matter content and soil particle size, while nitrogen is reduced to N2 gas in the anaerobic soil layers (Brady & Weil, 2008) . Detention ponds , or “wet” stormwater ponds, with a permanent volume of water gradually discharge downstream through a designated overflow structure (Vandiver &

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38 Hernandez, 2009; Livingston & McCarron, 1992) . Stormwater detention pond performance is usually assessed through total suspended solids levels and removal (Olding, Steele, & Nemeth, 2004; Gharabaghi, et al., 2006) , neglecting the role of biogeochemical processes and fate of dissolved contaminants including nutrients (Anderson, Watt, & Marsalek, 2002; Olding, Steele, & Nemeth, 2004; Collins, et al., 2010; Downing J. , 2010) . Stormwater pond biogeochemical characteristics are relatively unknown, but they appear to be extremely productive and able to support complex microbial communities and food webs (Chiandet & Xenopoulos, 2010; Sommaruga, 1995; Sanchez, et al., 2011) . Williams et al. (2013) report water chemistry and phytoplankton biomass in stormwater ponds tend to be more variable t han natural, unimpacted systems (Chiandet & Xenopoulos, 2010) , and more closely resembl e eutrophic lakes (Sommaruga, 1995; Sanchez, et al., 2011) and restored and natural wetlands in anthro pogenically impacted watersheds (Stewart & Downing, 2008; Hossler, et al., 2011) . The existing microbial food webs and biogeochemical cycles are dependent on water residence time within the stormwater pond and the external chemical input quantity and quality (Sommaruga, 1995; Van Meter, Swan, & Snodgrass, 2011) . Internal cycling drives processes within the stormwater pond during dry periods while rainfall can provide external in puts of nutrients from the watershed, influencing the water column characteristics and turnover time within the pond (Olding, Steele, & Nemeth, 2004; Chiandet & Xenopoulos, 2010) . Terrestrial connections to stormwater ponds may be best reflected during periods of high rainfall and associated runoff (Williams, Frost, & Xenopoulos, 2013) .

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39 Stormwater ponds are required by permit to mitigate for increased rates of runoff volume and elevated poll utants associated with development. Structurally, wet stormwater ponds must detain water for a minimum of 14 days, contain a littoral zone of at least 30% of the pond area, and be no deeper than 10 feet below the control elevation ( Livingston E. , McCarron, Cox, & Sanzone, 1988) . Stormwater ponds are typically built to provide a 2448 hour lag phase during a rain event, allowing total suspended solids to settle before entering downstream water bodies (Olding, Steele, & Nemeth, 2004; Gharabaghi, et al., 2006) . Sediment accumulation can be rapid (Downing, et al., 2008) and must be mitigated through periodic dredging to maintain permitted storage capacity (Anderson, Watt, & Marsalek, 2002) . Pollutants in the stormwater pond system are removed from the water column through biological uptake and/or sediment deposition (Novotny, 1995) . The state Stormwater Rul e, Chapter 1725 Florida Administrative Code, requires stormwater systems to treat the first flush of stormwater and remove at least 80% of the annual average pollutant load, with an increased treatment to 95% of the load if water is being discharged to Outstanding Florida Waters (Livingston & McCarron, 1992) . A study by Harper and Baker (2007) , however, demonstrated stormwater ponds are not meeting the required removal efficiencies for TN and TP as currently designed and fail to meet the 80% to 95% removal efficiencies required by the Florida Administrative Code. To meet the required removal efficiencies, Harper and Baker (2007) suggest increasing retent ion time and adding upstream mitigation to stormwater management plans to form a treatment train reducing the overall load reaching natural water bodies.

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40 Stormwater ponds that receive excess loading of nitrogen and phosphorus can become eutrophic and exper ience algal blooms and excessive aquatic vegetation growth. Vegetation type and coverage can increase the nutrient removal efficacy of stormwater ponds (Mallin, Ensign, Wheeler, & Mayes, 2002) and represent an important nutrient removal pathway within the pond (Harper & Baker, 2007) . Littoral and pond bank v egetation can also increase soil stabilization on the slopes around stormwater ponds and decreases overland runoff velocity and associated soil e rosion (Livingston & McCarron, 1992; Arendt, 1996) and improve soil development and infiltration rates while utilizing nutrients moving through the soil (Brady & Weil, 2008) . Additionally , e xtensive aquatic plant coverage may reduce the potential of undesirable phytoplankton blooms (Richard & Small, 1984) . Unfortunately, eutrophication can also impair the aesthetic value and recreational use of the stormwater pond. Eutrophication results in decreased water clarity, altered water column color, unwanted odor, and changes in ecological community composition (Vitousek, et al., 1997; Xavier, Vale, & Vasconcelos, 2007; Dokulil, Martin, & Teubner, 2003) . Eutrophication occurs naturally in lake systems and is often noted as a consequence of the aging of a lake basin as they become less deep and more biologically productive over time (Rodhe, 1969) . U rban stormwater ponds can have extremely high rates of internal nutrient processing (Downin g, et al., 2008; Tranvik, et al., 2009; Downing J. , 2010; Williams, Frost, & Xenopoulos, 2013) and may be subject to accelerated eutrophication and aging due to the increased supply of nutrients and sediments from the surrounding watershed and anthropogenic activities. Increased plant and algae biomass within the stormwater pond leads to increa sed organic

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41 sediment production, decreased storage volume and decreased dissolved oxygen from the increased microbial degradation of organic matter (Wetzel, 2001) . To maintain volume requirements, stormwater ponds may need to be dredged periodically. Social Expectations Stormwater ponds in urban and residential settings are often marketed to meet aesthetic and recreational expectations in addition to regulatory requirements . Stormwater ponds are prominent landscape features in many communities and offer aesthetic, recreational and economic value similar to natural lakes (DeLorenzo, Thompson, Cooper, Moore, & Fulton, 2012; Serrano & DeLorenzo, 2008) . Unlike natural lakes, however, there are no water quality standards established for pond uses and expectations are highly variable between homeowners. Often, m aintaining the social expectations of stormwater ponds is implemented by suppressing the biological responses to increased nutrient loads instead of managing excess nutrients in the watershed. Killing algae growth in the pond may achieve homeowner expectations of the pond aesthetics but m ay compound the stormwater pond’s ability to meet the required TN and TP removal efficiencies by eliminating an important biological nutrient removal mechanism within the pond (Harper & Baker, 2007) . Stormwater ponds in resi dential and urban developments are often used for recreational activiti es like fishing and boating by residents in the community (Serrano & DeLorenzo, 2008) . In natural lake systems, user water quality preference varies based o n their use of the system (Ditton & Goodale, 1973; Parsons & Kealy, 1992) and users are willing to pay for management strategies protective of their desired use (Bockstael, McConnell, & Strand, 1989) . Residents in communities with stormwater ponds mirror this willingness to pay and often employ lake management companies to chemically

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42 treat algal blooms and remove nuisance vegetation resulting from nutrient loading and eutrophic conditions. Eutrophication causes unwanted changes that negatively affect aesthetic and recreational uses of surface water bodies (Vitousek, et al., 1997; Xavier, Vale, & Vasconcelos, 2007; Dokulil, Martin, & Teubner, 2003) and reduce the property value of waterfront homes (Steinnes, 1992) . Nutrient loading to aquatic systems has an enormous economic price and includes d eclines in lakefront property value, fishing and recreation loss, cost of biodiversity loss, and cost of water purification (Dodds, et al., 2009) . Stormwater ponds are designed and regulated to be nutrient sinks reduc ing the impact of nutrient loading on downstream systems, but maintaining social expectations of stormwater ponds shifts the concerns and costs of nutrient loading in natural systems upstream to the stormwater pond. Unfortunately, chemical interventions eliminating biological responses to increased nutrients artificially maintains stormwat er pond expectations and allows nutrients to bypass removal mechanisms in the stormwater pond and enter downstream systems. To maintain regulatory nutrient reduction requirements and social expectations of stormwater ponds, better management criteria must be developed to identify thresholds of impairment and reduce upstream nutrient loads. Location Description The Tampa Bay area is one of the fastest growing coastal urban centers in Florida and population growth is leading to increased fresh water demand, development and sprawl (Dorsey, 2010) . Urban land use in the Tampa Bay watershed has more than tripled since 1991 and accounts for approximately 27% of the total land area as more than two million people now reside within the watershed (Xiang, Crane, & Su, 2007) .

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43 Coastal states are dramatically impacted by nonpoint source pollution from stormwater runoff with more than sixty percent of rivers, estuaries and bays moderately to severely degraded (National Research Council, 2000) . U rban areas are significant contributors to nonpoint source pollution (United States Environmental Protection Agency, 2009) and r esidential areas within the Tampa Bay watershed are the primary source of nitrogen pollution reaching Tampa Bay (Tampa Bay Estuary Program, 2006) . Elevated nitrogen levels in Tampa Bay, along with other nutrients and pollutants , can lead to loss of seagrass beds, algal blooms and other negative environmental impacts (Tampa Bay Estuary Program, 2006) . Landscaping practices and decisions have led to many of the nutrient loading and water supply issues the Tampa Bay watershed experiences. Irrigation of lawns and gardens accounts for more than 80% of the domestic water use in Florida (Johns, et al., 2007) and lawns are maintained through extensive labor and chemical inputs. Tu rfgrass lawns are extremely popular in the Tampa Bay watershed as a recent study indicated nearly 70% of residents reported 25% or more of their property is completely covered in turfgrass (Mustafa, Smucker, Ginn, Johns, & Connely, 2010) . Despite the environmental concerns present in the watershed, residents tend to be largely unaware of the impact their landscaping decisions and runoff have on natural systems (Nielson & Smith, 2005) . Piped water, specifically in the form of irrigation and stormwater management, causes disconnect between people and the local environment (Malone, 1999; Hillman, Brierley, & Fryirs, 2008) . This study was conducted in a large residential community within the Tampa Bay watershed and West Central Peninsula Nutrient Watershed Region (Florida

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44 Administrative Code, 2013) . The community covers over 8,500 acres and has a growing population of over 15,000 residents. The demographics of the community vary greatly and range from working class, young families to affluent, retired, part time residents. Formerly a cattle ranch, the community now includes thousands of homes, over 300 stormwater ponds, multiple park s, several natural areas, and two golf courses. Stormwater ponds are an impor tant component of the community beyond water storage and treatment capacities as they provide aesthetic, recreational and economic value to residents and homeowners. Although many homeowners paid premiums to have waterfront property on these stormwater ponds, many were unaware they were not natural water bodies and do not understand their role in treating non point source nutrient runoff. Landscaping in the community is done by con tracted lawn maintenance companies or homeowners and there are strong expectations for lawns and landscaping to be regularly maintained to meet aesthetic standards. Stormwater ponds and common areas are managed by a single director of operations. Runoff f rom the community eventually deposits into the Braden River which contributes to the Manatee River and, ultimately, Tampa Bay. The Braden River designated use is potable water supply and it is impaired for fecal coliforms, chlorophyll A, and dissolved oxygen (United States Environmental Protection Agency, 2013) . A TMDL for fecal coliforms was established in 2009 and the Braden River was impaired for nutrients, fecal coliform, total suspended solids and dissolved oxygen in the re porting year 2002. Research Objective s and Hypotheses Perceived value and community ownership of stormwater is necessary to identify solutions to improve water quality (Winz, Brierley, & Trowsdale, 2011) , therefore

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45 stormwater ponds in residential areas represent a n ideal focal point to evaluate strategies that address both social and regulatory objectives. This research investigated the use of a community selected chlorophyll a nutrient threshold to help align the social and regulatory expectations of stormwater ponds. Following the FDEP Numeric Nutrient Criteria model for natural lakes, chlorophyll a thresholds were established based on visual preferences deemed protective of desired aesthetic and recreational uses and then used to identify nutrient criterion to maintain or improve the water condition (Florida Department of Environmental Protection , 2012) . Establishing stormwater pond water quality goals and numeric nutri ent criteria that could be used by community pond managers would help guide upstream nutrient management programs, maintain the social and regulatory functions of stormwater ponds , and help protect the designated uses of natural, downstream waterbodies . Em powering and entrusting community members to self regulate landscaping decisions in accordance with community aesthetic expectations may be the best opportunity to minimize impact on natural systems . Since residents value stormwater ponds like natural lake systems, utilizing similar management strategies to protect designated uses could allow stormwater ponds to better meet regulatory requirements and aesthetic expectations with minimal use of algaecides and herbicides . Developing acceptable nutrient criter ia for stormwater ponds would provide a framework for better management of nonpoint source pollution and stormwater while ensuring better protection for downstream water bodies. Understanding the physicochemical environmental and biogeochemical mechanisms controlling the quality and clarity of water within and released from stormwater ponds could improve the management,

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46 performance and sustainability of the system (Williams, Frost, & Xenopoulos, 2013) . Additionally, creating a c ommunity based nutrient management criteria based on social expectations could provide site specific goals meeting local, state and federal regulations strengthened by stakeholder involvement. To create a community based stormwater pond management program to meet regulatory requirements and aesthetic preference, several objectives must be met. The following chapters present investigations of 1) the nutrient response relationships in Florida stormwater ponds, 2) the identification of chlorophyll a thresholds for stormwater ponds , 3) the evaluation of significant predictors of nutrient enrichm ent in stormwater pond systems and 4) the identification of community based nutrient management thresholds and potential impacts. Establishing the relationships between TN , TP and chlorophyll a concentration is essential in defining water column nutrient criteria and the nutrient response relationships in stormwater ponds . This part of the investigation is summarized in Chapter 2. Objectives and hypothesis for Chapter 2 were: Object ive 2 1: Develop nutrient response models for stormwater ponds using TP , TN and chlorophyll a concentrations . Hypothesis 21: Chlorophyll a response to nutrients in stormwater ponds are significantly different than the chlorophyll a response to TN and TP in natural Florida lakes . Identifying c ommunity based expectations and acceptable thresholds based on chlorophyll a concentrations were necessary to identify nutrient concentration criteria protective of resident preference. Results o f this investigation are provided in C hapter 3. The objectives and hypotheses for C hapter 3 were :

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47 Objective 31 : Identify community based expectations and thresholds of impairment in stormwater ponds based on water column chlorophyll a concentrations. Hypo thesis 3 1: Community based expectations and thresholds of impairment identified for stormwater ponds will be lower than the numeric nutrient criteria established for natural lake systems in Florida (20 gL1 chl a ) . Objective 32: Determine if educational information on the role o f algae in stormwater ponds has an effect on community based expectations and thresholds of impairment chosen in a webbased survey. Hypothesis 32 A : E ducational treatment regarding the benefit and role of algae in a stormwater pond will increase community based treatment thresholds. Hypothesis 32B : The presence of aquatic vegetation will reduce community based treatment thresholds. Objec tive 3 3: Dete rmine if pond use, educat ion regarding stormwater ponds and demographic background have significant effects on preferred chlorophyll a treatment threshold. Hypothesis 33A: If individuals use ponds frequently for recreational activities, then they will hav e a higher chlorophyll a treatment threshold than individuals who do not. Hypothesis 33B: If residents are educated regarding the benefit and function of water column algae growth, then they will have a higher chlorophyll a t reatment threshold than those who are not . Hypothesis 33C: There will be a significant difference in chlorophyll a treatment thresholds according to demographic identity. In Chapter 4, s everal management variables were evaluated as predictors of stormwater pond TN , TP , and chloroph yll a concentration to identify potential management targets for reducing undesirable conditions and identifying pondspecific treatment thresholds. The objective for Chapter 4 was: Objective 41: Identify potential drivers of stormwater pond nutrient enri chment and develop pondspecific TN , TP and chlorophyll a concentration models. After identifying nutrient response relationships and chlorophyll a treatment thresholds, a community based numeric nutrient criteria can be established to guide

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48 management dec isions. Chapter 5 utilized nutrient response relationships established in Chapter 2 and treatment thresholds identified in Chapter 3 to establish nutrient thresholds for several potential chlorophyll a treatment levels. The objecti ves and hypotheses for Ch apter 5 were : Objective 51: Establish community based stormwater pond nutrient criteria for TN and TP in clear and colored stormwater ponds based on community identified chlorophyll a treatment thresholds. Hypothesis 51 : Higher chlorophyll a treatment thresholds will result in increasingly greater nutrient removal potential in stormwater ponds. In conclusion ( Chapter 6), the results are summarized within the context of t he current regulatory requirements and social expectations of stormwater ponds in Fl orida .

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49 Table 1 1. EPA Approved Numeric Criteria for Florida’s Lakes (United States Environmental Protection Agency, 2010) . Lake Type Color/Alkalinity Response Chla g/L Stressor Nutrient mg /L Lower Threshold Upper Threshold Clear, Low Alkalinity 6 6 TP TN .01 .51 .03 .09 Clear, High Alkalinity 20 20 TP TN .03 1.05 .09 1.93 Colored 20 20 TP TN .05 .1.27 .16 2.23 Color is distinguished by the amount of dissolved organic matter, free from turbidity, and reported in Platinum Cobalt Units (PCU). Clear lakes have values less than or equal to 40 PCU and colored lakes have values greater than 40 PCU. Alkalinity is deter mined by concentration of CaCO3. Alkaline lakes have greater than 20mg/L CaCO3 and acid lakes have values less than or equal to 20mg/L CaCO3. Figure 11. Stormwater pond interactions and drivers

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50 CHAPTER 2 NUTRIENT ALGAL RESPONSE RELATIONSHIPS IN STORMWATER PONDS Introduction The development of a quantitative and predictive ecological nutrient response relationship is essential to establishing adequate watershed management practices (Dillon & Rigler, 1974) . Nutrient response relationships are commonly used by regulatory agencies and lake managers to implement eutrophication control measures , and n itrogen and phosphorus are widely recognized predictive d rivers of chlorophyll a response in freshwater lake systems (Sakamoto, 1966; Dillon & Rigler, 1974; Brown, Hoyer, Bachmann, & Canfield, 2000; Florida Department of Environmental Protection , 2012) . To establish the relationships, l ake water column nutrient concentrations are measured directly or estimated with nutrient loading models and then compared in an associated regression models to relate to algae chlorophyll a concentrations (Hoyer, Frazer, Notestein, & Canfield, 2002) . Chlorophyll a concentrations can , in turn, be used to determine how much the nutrient of concern needs to be controlled to achieve or maintain a desired algal concentration (Hoyer, Frazer, Notestein, & Canfield, 2002; Florida Department of Environmental Protection , 2012) . This nutrient response approach to address eutrophication in freshwater lake systems has been successfully implemented in several locations, including Florida (Cooke, Welch, Peterson, & Newroth, 1993; Hoyer, Frazer, Notestein, & Canfield, 2002; Florida Department of Environmental Protection , 2012) , but no similar relationship has ever been established or applied to stormwater pond systems. E utrophication in stormwater pond systems is a recent problem that has arisen with the increased implementation of wet stormwater ponds as landscape features and

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51 recreational amenities in re sidential communities (DeLorenzo, Thompson, Cooper, Moore, & Fulton, 2012; Serrano & DeLorenzo, 2008) . In Florida, stormwater pond systems are regulated stormwater management features expected to treat nutrient runoff and protect natural downstream systems by removing at least 80% of the annual ave rage pollutant load (Livingston & McCarron, 1992) . Stormwater pond design and management supports nutrient removal through physical (sedimentation), chemical (precipitation and adsorption), and biological (uptake) mechanisms, and stormwater ponds built to the state criteria are assumed to meet the required nutrient removal efficiencies (Harper & Baker, 2007) . However, a recent study by Harper and Baker (2007) revealed stormwater ponds built and managed to state standards fail ed to meet the required total nitrogen (TN) and total phosphorus (TP) removal efficiencies. T he principal role of stormwater ponds for quantity and quality mitigation systems of runoff from urban development has become secondary to aesthetic and recreational expectations of water quality standards and management decisions to use herbicides and algaecides to achieve expectations further compounds the inefficiencies of nutrient removal . To meet nutrient removal efficiencies, Harper and Baker (2007) suggest adding upstream source control and mitigation to stormwater management plans forming a treatment train to help reduce the overall load reaching natural water bodies. E stablishing the nutrient response relationships between TN , TP and chlorophyll a in stormwater ponds would allow managers to e stablish quantitative relationships betw een nutrients and algal response and more effectively identify water quality goals , including acceptable nutrient concentration targets and specific upstream nutrient reduction strategies .

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52 Nutrient response relationships are well established for natural Florida lakes, but a pplying those relationships to stormwater ponds may not be appropriate. Prior studies demonstrated empirical models developed from natural lakes were not applicable for built aquatic systems (Smith, 1990; Gloss, Reynolds, Mayer, & Kidd, 1981; Higgins, Poppe, & Iwanski, 1981) and primary productivity appear ed lower in artificial systems than in natural lakes (Soballe, Kimmel, Kennedy, & Gaugush , 1992; Cooke & Carlson, 1989; Jones & Bachmann, 1976) . The major objective of this work was to develop nutrient response models for TP , TN and chlorophyll a concentrations in Florida stormwater ponds . Additionally, the established stormwater pond models was compare d to the Florida lake nutrient response models used to develop the Numeric Nutrient Criteria in the state of Florida. Methods Urban development in the Tampa Bay watershed, Florida, currently accounts for at least 27% of the total land area (Xiang, Crane, & Su, 2007) and is considered a significant contributor to nonpoint source pollution reaching Tampa Bay (Tampa Bay Estuary Program, 2006; United States Environmental Protection Ag ency, 2009) . This study was conducted in a large, residential community located with in the Tampa Bay watershed that covers approximately 8,500 acres with a population of more than 15,000 residents. Wet stormwater ponds are an important feature in the community as over 300 ponds provide water storage, water treatment, aesthetic, recreational and economic value to residents and homeowners. Stormwater pond management decisions are made by a single community pond manager based on resident preferences and algaecide and herbicide applications to control algal growth are applied by a contracted pond management company.

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53 A simple, rando mized sample (n=36) of the 307 stormwater ponds in the residential community located in southwest Florida was selected (Ary, Jacobs, & Razavieh, 2002) and water column TP concentration , TN concentration, color and chlorophyll a concentration were measured at three predetermined locations within each pond monthly during May, July, August and October, 2013 (Figure 2 1) . Water samples were taken by hand at a depth of 0.60 m and preserved in accordance with EPA protocol (United States Environmental Protection Agency, 1979) in 20 ml PTFE acid washed bottles and stored on wet ice. Water samples collected for TP were syringe filtered through 0.45m disk filter and H2SO4 was added to ensure pH below 2.0. Wate r samples collected for TKN and NOxN were preserved with H2SO4 to ensure pH below 2.0. Color and chlorophyll a concentrations were measured at a depth of 0.60 m using a WET Labs E CO Triplet w optical instrument. The WET Labs ECO Triplet w measured chlorophyll a concentration (g L1) and color ( platinum cobalt units, PCU) every 30 seconds for 3 minutes and mean values were calculated for each sampling station. Water samples were analy zed for n u t rients by the University of Florida Analytical Research Lab following EPA Method 365.1 for TP and EPA Methods 351.2 (TKN) and 353.2 (NOxN) to determine TN. Following the 4 months of sampling, a representative subset of 12 ponds was selected from the randomized sample for continued sampling for an additional 8 months. The representative sample consisted of 4 phosphorus limited ponds with consistently low water column TP concentrations, 4 phosphorus limited ponds with consistently high water column TP concentrations and 4 nitrogen limited ponds. Phosphorus limi ted ponds were defined as ponds with an N:P ratio greater than 20:1

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54 and nitrogen limited ponds were def ined as ponds with an N:P ratio less than or equal to 20:1 (Guildford & Hecky, 2000) . For the study data analysis, mean color, TP, TN and chlorophyll a concentrations were determined for each pond by averaging the values measured at each of the three site s within the pond for each sampling date, similar to Hoyer et al (2002) . Computations and comparisons were performed using the JMP Pro 11 statistical software package (SAS Institute, 2009) and mean values are reported with the standard error . For analysis and comparison of nutrient response relationships, stormwater ponds were categorized into clear and colored (>40 PCU) systems similar to state Numeric Nutrient Criteria classification (Florida Department of E nvironmental Protection , 2012) to account for the possible influence of color on the chlorophyll a and nutrient relationships (Hoyer & Jones, 1983; Brown, Hoyer, Bachmann, & Canfield, 2000) . Data for nutrient response were log transformed to normalize data and accommodate heterogeneity of variance (Cleveland, 1984; Ott & Longnecker, 2001; Snedecor & Cochran, 1967) . Stormwater pond nutrient response linear regressions were then compared to the established , statewide colored and clear lake nutrient response regressions utilizing a fixedeffects test of a l east squares model to evaluate for significant difference between the two indicator variable models and slopes . Results and Discussion The 36 stormwater ponds sampled for this project were distributed throughout the residential community and ranged in size and surrounding land use. All of the stormwater ponds were constructed after 1992 and were 5 acres or smaller in size . Total phosphorus concentrations averaged 0.03 0.003 mgL1 for clear stormwater ponds and 0.05 0.005 mgL1 for colored stormwater ponds (Table 21). The average

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55 TP concentration of colored stormwater ponds was higher than the average of 0.039 mgL1 reported for natural Florida lakes (Brown, Hoyer, Bachmann, & Canfield, 2000) , and equal to the lower threshold of 0.05 mgL1 identified by the Numeric Nutrient Criteria for colored Florida l akes (United States Environmental Protection Agency, 2010) . The average TP for clear stormwater ponds (0.03 mgL1) was equal to the Numeric Nutrient Criteria lower threshold for clear, high alkalinity lakes (United States Environmental Protection Agency, 2010) . Total nitrogen concentrations averaged 0.91 0.04 mgL1 for clear stormwater ponds and 1.29 0.04 mgL1 for colored stormwater ponds, both higher than the values reported TN concentration of 0.69 mgL1 for all natural Florida lakes (Brown, Hoyer, Bachmann, & Canfield, 2000) . The average TN concentration of colored stormwater ponds exceeded the Numeric Nutrient Criteria lower threshold for total nitrogen of 1.27 mgL1 in natural, colored lakes, but the average TN concentration of clear stormwater ponds did not exceed the Numeric Nutrient Criteria for clear, high alkalinity lakes of 1.05 mgL1 (United States Environmental Protection Agency, 2010) . The average chlorophyll a concentrations of clear and colored stormwater ponds were 5.55 0.49 gL1 and 9.12 0.44 gL1, respectively . N either value exceeded the 23.0 gL1 a verage chlorophyll a concentrations reported for all Florida lakes (Brown, Hoyer, Bachmann, & Canfield, 2000) . The stormwater ponds also did not exceed the 20 gL1 impairment threshold identified by the Numeric Nutrient Criteria for colored and clear, high alkalinity lakes with the designated use of fishing, recreation and maintenance of a healthy fish and wildlife population (United States Environmental Protection Agency, 2010) .

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56 The relationship between nutrients and chlorophyll a concentrations in stormwater ponds is much weaker than those established in natural Florida lakes (Table 2 2). Total phosphorus alone accounted for 25% of the variance in chlorophyll a concentrations in clear stormwater ponds and 27% of the variance in chlorophyll a concentrations in col ored stormwater ponds, compared to a much more robust 68% in clear lakes and 58% in colored lakes (Florida Department of Environmental Protection , 2012) . The relationship between TP and chlorophyll a in clear and colored stor mwater ponds was plotted, respect ively , against the TP chlorophyll a relationship established in setting Florida’s Numeric Nutrient Standard (Florida Department of Environmental Protection , 2012) for clear (Figure 22) and colored (Figure 23) lakes. The chlorophyll a response to increases in TP concentration appears to be greater in clear and colored lake systems than in clear and colored stormwater ponds and a fixedeffects test revealed significant difference in the TP chlorophyll a interaction and slopes of clear lakes and clear stormwater ponds (F1,1=7.504, p <0.05) and of colored lakes and colored stormwater ponds ( F1,1=4.763, p <0.05). Interestingly , t he community is also located in a region with noted external influences on the nutrient response relationships in natural lakes and streams (Florida Department of Environmental Protection , 2012) . Prior evaluation by the Florida Department of Environmental Protection (FDEP) of natural lakes i n the West Central Peninsula R egion (WCPR) revealed the relationship between TP and chlorophyll a was weak (R2=0.028, p=0.315) , suggesting other factors influence the nutrient algal response relationship in this area (2012) . Total phosphorus chlorophyll a relationships for colored lakes in this area were evaluated and an alternative model was developed,

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57 leading F DEP to cap the upper TP threshold of the Numeric Nutrient Criteria for colored lakes at the regional stream threshold of 0 .49mg/L. W hen data collected for colored stormwater ponds were compared to natural lakes located in the WCPR (Table 22) , the TP chlorophyll a relationship was found to be stronger in stormwater ponds than in lakes, wi th TP accounting for 27% of the variance in chlorophyll a in stormwater ponds and only for 3% of the variance in chlorophyll a in lakes (Florida Department of Environmental Protection , 2012) . The chlorophyll a response to TP concentrations in colored stormwater ponds was plotted against the chlorophyll a response to TP in colored lakes in the WCPR (Figure 2 4) . A fixed effects test of least squares model revealed the TP chlorophyll a interaction and slopes of colored lakes and colored stormwater ponds were not significantly different (F1,1=0.701, p =0.404), even though nearly all the stormwater pond data were less than TP concentrations found in the natural colored lakes in the WCPR . Furthermore, a fixed effects test least squares model for mean response difference at zero indicates there is no significant difference (F1,1=0.001, p =0.978) in the intercept between colored stormwater ponds and colored lakes in this region. Total nitrogen accounted for 5% of the variance in chlorophyll a in clear stormwater ponds and 7% in colored stormwater ponds, much less than the 77% and 65% variance in chlorophyll a related to TN concentrations in clear and colored lak es , respectively (Florida Department of Environmental Protection , 2012) . Thus, the TN chlorophyll a stormwater pond models (Table 22) are much less robust than those for natural Florida lakes . Additionally, t he relationships between TN and chlorophyll a in clear and colored stormwater pon ds were plotted, respect ivel y, against the TN -

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58 chlorophyll a relationship established in setting Florida’s Numeric Nutrient Standard (Florida Department of Environmental Protection , 2012) for clear (Figure 25 ) and colored (Figure 2 6 ) lakes. As seen in the TP chlorophyll a relationships, t he chlorophyll a response to increases in TN concentration appears to be greater in clear and colored lake systems than in clear and colored stormwater ponds . A fixed effects test revealed significant difference in the TN chlorophyll a interaction and slopes of clear la kes and clear stormwater ponds (F1,1=13.800, p <0.005) and of colored lakes and colored stormwater ponds (F1,1=11.268, p <0.005). Conclusion This study developed nutrient response models for TP , TN and chlorophyll a concentrations in Florida stormwater ponds by sampling a random selection of stormwater ponds in southwestern Florida for several months. These models may help guide stormwater pond managers to better design and impl ement nutrient reduction strategies preventing unwanted algal responses by identifying target nutrient thresholds. Phosphorus is normally the primary limiting nutrient in Florida lakes (Canfield, 1983; Brown, Hoyer, Bachmann, & Canfield, 2000) , and t he data presented suggest TP often has a greater influence on the chlorophyll a concentration within stormwater ponds than TN and is the primary limiting nutrient . Total phosphorus concentrations account for 25% and 27% o f the variance in chlorophyll a concentrations in clear and colored stormwater ponds, respectively . Total nitrogen concentrations account for only 5% and 7% of the variance in chlorophyll a concentrations in clear and colored stormwater ponds, respectively. Although the TP chlorophyll a relationships in stormwater ponds are not as robust as those established for natural lake systems, they are more robust than

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59 relationships found in a prior study of built reservoirs in the southeastern United States (Reckhow, 1988; Canfield & Bachmann, 1981) . T he models developed for TP / TN chlorophyll a relationships in clear and colored stormwater ponds were also found to be significantly different from those developed for Florida lakes. The chlorophyll a responses to increases in TP and TN concentrations are less in stormwater pond systems than the response occurring in natural lake systems, suggesting the poor suitability of the Florida lake models for use in stormwater ponds. There is one exception, however, as the region specific TP model for colored lakes in the WCPR was not significantly different than the TP model for colored stormwater ponds. This finding suggests there is an external influence on TP chlorophyll a relationships for lake and stormwater pond surface water bodies in this region that should be further investiga ted . The models developed in this investigation provide a more accurate description of the nutrient response relationships in stormwater ponds and could be used more suitably to provide quantitative guidance for managing aesthetic and permitted demands in stormwater ponds where no such guidance currently exists. The relatively weak nutrient chlorophyll a relationships , however, suggest there are other variables contributing to the variance of chlorophyll a concentrations that should be investigated to impr ove the eutrophication models for stormwater ponds . Alternative variables impacting chlorophyll a concentration in stormwater ponds, including detention time, pond design and management strategies , should be investigated and considered to better explain and predict nutrient response relationships in stormwater ponds.

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60 Table 21. Mean, median, standard error, and minimum and maximum values for total phosphorus, total nitrogen and chlorophyll a concentrations in stormwater ponds compared to Numeric Nutrient Criteria (NNC) lower threshold values (United Stat es Environmental Protection Agency, 2010) and natural Florida (FL) lake values (Brown, Hoyer, Bachmann, & Canfield, 2000) Pond Color Variable Mean Median S.E. Min. Max. NNC FL Clear n=87 TP (mg L 1 ) 0.03 0.02 0.003 0.01 0.14 0.03 0.04 TN (mg L 1 ) 0.91 0.87 0.04 0.4 2.24 1.05 0.69 Chl a ( g L 1 ) 5.55 4.14 0.49 0.18 26.03 20.0 23.0 Colored (>40 PCU) n=120 TP (mg L 1 ) 0.05 0.03 0.005 0.01 0.29 0.05 0.04 TN (mg L 1 ) 1.29 1.21 0.04 0.66 3.48 1.27 0.69 Chl a ( g L 1 ) 9.12 8.95 0.44 1.41 30.68 20.0 23.0 TP, total phosphorus, TN, total nitrogen, Chl a, Chlorophyll a, PCU, platinum cobalt units, S.E., standard error, NNC, Numeric Nutrient Criteria, FL, natural Florida lake values.

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61 Table 2 2. Empirical models and summary statistics describing the association of monthly average nutrient and chlorophyll concentrations using data from stormwater ponds in a southwest Florida community and Florida Freshwater Lakes (Florida Department of Environmental Protection , 2012) . Model Color p r 2 Southwest FL Stormwater ponds LnCHL = 0.520LnTP + 3.459 Clear <0.001 0.245 LnCHL = 0.423LnTN + 1.528 Clear <0.05 0.051 LnCHL = 0.368LnTP + 3.284 Colored <0.001 0.269 LnCHL = 0.486LnTN + 1.959 Colored <.01 0.066 FDEP (2012) for Florida freshwater lakes LnCHL = 1.136LnTP + 6.370 Clear <0.001 0.677 LnCHL = 1.729LnTN + 2.482 Clear <0.001 0.769 LnCHL = 1.128LnTP + 5.729 Colored <0.001 0.581 LnCHL = 1.965LnTN + 1.995 Colored <0.001 0.645 LnCHL = 0.594LnTP + 3.942 Colored, WCPR =0.351 0.028 CHL, chlorophyll a (gL1), TP, total phosphorus (mgL1), TN, total nitrogen (mgLcolored (>40PCU). WCPR, West Central Peninsula Region.

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62 Figure 21 . Location of 36 stormwater ponds sampled between May 2013 and June 2014. The yellow pins indicate the initial 24 stormwater ponds sampled during the first 4 sampling dates and the red pins indicate the subset of ponds sampled all 12 dates.

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63 Figure 22. Regression analysis between annual geometric mean chlorophyll a concentration and annual geometric TP concentration in clear Florida lakes (black d ata points, upper left equation (Fl orida Department of Environmental Protection , 2012) ) compared to regression analysis between monthly mean pond chlorophyll a concentration and monthly mean TP concentration in clear stormwater ponds in southwest Florida (blue data points, lower right equation). The two lines represent the linear regressions for each data set. Fixed effects test of least squares model shows significant difference in TP Chlorophyll a interaction and slopes of clear lakes and clear stormwater ponds (F1,1=7.504, p <0.05).

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64 Figure 23. Regression analysis between annual geometric mean chlorophyll a concentration and annual geometric TP concentration in colored Florida lakes (black data points, upper left equation (Florida Department of Environmental Protection , 2012) ) compared to regression analysis between monthly mean pond chlorophyll a concentration and monthly mean TP concentration in colored stormwater ponds in southwest FL (blue data points, lower right equation). The two lines represe nt the linear regressions for each data set. Fixed effects test of least squares model shows significant difference in TP Chlorophyll a interaction and slopes of colored lakes and colored stormwater ponds (F1,1=4.763, p <0.05).

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65 Figure 24. Regression analysis between annual geometric mean chlorophyll a concentration and annual geometric TP concentration in West Central Peninsular Region colored, Florida lakes (black data points, upper left equation (Florida Department of Enviro nmental Protection , 2012) ) compared to regression analysis between monthly mean pond chlorophyll a concentration and monthly mean TP concentration in colored stormwater ponds located in the same region (blue data points, lower right equation). The tw o lines represent the linear regressions for each data set. Fixed effects test of least squares model shows TP Chlorophyll a interaction and slope of colored lakes and colored stormwater ponds are not significantly different (F1,1=0.701, p =0.404).

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66 Fig ure 25. Regression analysis between annual geometric mean chlorophyll a concentration and annual geometric TN concentration in clear Florida lakes (black data points, upper left equation (Florida Department of Environmental Prote ction , 2012) ) compared to regression analysis between monthly mean pond chlorophyll a concentration and monthly mean TN concentration in clear stormwater ponds in southwest FL (blue data points, lower right equation). The two lines represent the linear regressions for each data set. Fixed effects test of least squares model shows significant difference in TN Chlorophyll a interaction and slopes of clear lakes and clear storm water ponds (F1,1=13.800, p <0.005).

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67 Figure 26. Regression analysis between annual geometric mean chlorophyll a concentration and annual geometric TN concentration in colored Florida lakes (black data points, upper left equation (Florida Department of Environmental Protection , 2012) ) compared to regression analysis between monthly mean pond chlorophyll a concentration and monthly mean TN concentration in colored stormwater ponds in southwest FL (blue data points, lower ri ght equation). The two lines represent the linear regressions for each data set. Fixed effects test of least squares model shows significant difference in TN Chlorophyll a interaction and slopes of colored lakes and colored stormwater ponds (F1,1=11.268, p <0.005).

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68 CHAPTER 3 IDENTIFYING SIGNIFICANT FACTORS INFLUENCING STORMWATER POND NUTRIENT AND ALGAE CONCENTRATIONS Introduction Nutrient algae response relationships are commonly used to predict unwanted algal blooms, control eutrophication and manage natural lake systems. Nitrogen and phosphorus are recognized drivers of algal biomass, as measured by chlorophyll a concentration, in freshwater lake systems (Sakamoto, 1966; Dillon & Rigler, 1974; Brown, Hoyer, Bachmann, & Canfield, 2000; Florida Department of Environmental Protection , 2012) and the relationships between total phosphorus (TP), total nitrogen (TN) and chlorophyll a concentrations can be used to create regression models approxim ating algal response concentrations based on quantifiable nutrient concentrations (Hoyer, Frazer, Notestein, & Canfield, 2002) . Nealis et al. (2016) , established nutrient chlorophyll a relati onships for stormwater ponds, but recognized the nutrient response relationships were significantly different from natural lake systems and additional variables were likely influencing the algal response to increasing nutrient concentrations. Water qualit y expectations of stormwater pond users are similar to natural, freshwater lakes (Nealis, Monaghan, Clark, Hochmuth, & Frank, 2016) , but current stormwater pond management practices may influence TN, TP and chlorophyll a co ncentrations within ponds and compound pond failure to meet the required nutrient removal efficiencies (Harper & Baker, 2007) . Currently, stormwater pond managers focus on several variables that may have a significant impact on the nutrient response relationships within stormwater ponds.

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69 Within the pond, algae, emergent vegetation and submerged aquatic vegetation are often controlled through various chemical treatments to meet aesthetic preferences. Application of algaecides and herbicides drastically reduce algal populations, artificially suppressing chlorophyll a concentration response to water column nutrient concentrations. Chemical applications may eliminate important biological nutrient removal pathways (Harper & Baker, 2007; Brenner, et al., 2006; deBashan & Bashan, 2004; Reddy, Kadlec, Flaig, & Gale, 1999; Graves, Wan, & Fike, 2004) , specifically the assimilative capacity of algae in the water column, reducing the overall nutrient removal efficiencies of the stormwater pond. Algae, specifically, has the ability to assimilate nitrogen and phosphorus (Wetzel, 2001) , store excess, “luxury” phosphorus (Kuhl, 1974; Powell, Shilton, Pratt, & Chisti, 2008) , and sequester nutrients as algae particles settle within the pond. The management of emergent and submerged vegetation within and surrounding stormwater ponds is also an important variabl e to consider. Vegetated wetland areas, as are found on some littoral shelves or pond edges, can have a high assim ilative capacity for nutrients while the denitrification processes within the wetland area can reduce nitrate nitrite N concentrations in r unoff (Graves, Wan, & Fike, Water quality characteristics of storm water from major land uses in South Florida, 2004; Hammer & Bastian, 1989) , but they do not necessarily increase the nutrient removal efficiencies compared to nonvegetated littoral areas (DB Environmental, Inc., 2005) . Vegetated littoral shelves can contribute nutrients to the water column from decomposing plant tissue (Graves, Wan, & Fike, Water quality characteristics of storm water from major land uses in South Florida, 2004) , especially when vegetation is managed with

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70 herbicidal treatments (DB Environmental, Inc., 2005) . Littoral shelf vegetation may, however, contribute to reducing chlorophyll a concentrations by outcompeting algae for light and nutrients (DB Environmental, Inc., 2005; van Donk & van de Bund, 2002) , producing allelopathic substances (Jasser, 1995; Wium Anderson, Christophersen, & Houen, 1982) , and supporting communities grazing zooplankton communities (van Donk & van de Bund, 2002) . Stormwater pond structural design may also influence nutrient and chlorophyll a concentrations. Littoral shelves are the shallow area at the edge of a stormwater pond, usually no deeper than approximately 1 meter below the design overflow, where sunlight may penetrate the water column and reach the soil surface (Southwest Florida Water Management District, 2010) . The shallow areas provided by littoral shelves have the ability to reduce water column nutrient concentrations by increasing the area of contact between the water column, soil, and vegetation (Baldwin, Simpson, & Weammert, 2009; DB Environmental, Inc., 2005) and increase the settling of suspended particles by decreasing the velocity of incoming runoff (Brix, 1993 ; Schueler T. , 1992) . Management decisions surrounding stormwater ponds may also impact stormwater pond nutrient and chlorophyll a concentrations. Landscaping decisions (Linde & Watschke, 1997; Easton & Petr ovic, 2004; Shuman, 2004) and land use (Brown & Vivas, 2005; Mallin, Ensign, Wheeler, & Mayes, 2002; Mallin, Johnson, & Ensign, 2009) adjacent to the stormwater pond may influence nutrient loads to the pond and reduce water quality. Increased land use intensity and impervious surface cover have been linked to increases in runoff volume, erosion and nutrient loading (Carey, et al., 2011; Schiff & Benoit, 2007; Brown & Vivas, 2005) . Soil erosion surrounding

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71 stormwater ponds is another important variable as shoreline erosion can be prevented through several design and landscaping practices. Er oded soil particles and organic matter can be significant contributor s of nitrogen and phosphorus to a stormwater pond (Daniel, Sharpley, Edwards, Wedepohl, & Lemunyon, 1994; Sharpley, et al., 1994; Quinton, Govers , Van Oost, & Bardgett, 2010) and further increase water column nutrient concentrations. Landscape maintenance decisions may also impact nutrient loading to stormwater ponds. R unoff from managed turfgrass landscaping has been reported to contain 0 .5 2.0 mg phosphorous and 3.05.0 mg nitrogen per liter (Barten & Jahnke, 1997; Easton & Petrovic, 2004; Shuman, 2004; Waschbusch, Selbig, & Bannerman, 1999) and runoff containing these nutrient concentr ations are capable of causing eutrophication in surface water bodies receiving the runoff in large volumes (Baker, Wilson, Fulton, & Horgan, 2008) . Local regulations restricting residential fertilizer application have been implemented in several areas in an attempt to reduce nonpoint source nutrient runoff, but the effect of the ordinances on stormwater pond water column nutrient concentrations is currently unknown. Grass clippings are an additional byproduct of turfgrass m anagement and, if mismanaged, can enter a stormwater pond through direct input from maintenance of adjacent shorelines, overland flow from surrounding areas, or from transport via impervious surfaces and stormwater systems. Grass clippings contain a 1.5 to 3.5% nitrogen concentration and a 0.15 to 0.5% phosphorus concentration by dry weight (Sartain, 2001) and can supply additional nitrogen and phosphorus to the water column as they decompose (Bedan & Cla usen, 2009) . Most of the nutrients associated with

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72 grass clippings will leach into the water column within 22 days of immersion, with a majority of the phosphorus and a third of the TKN released within the first day of immersion (England, 2001; Strynchuk, Royal, & England, 1999) . Leached nutrients enter the water column and can potentially stimulate increased algal growth. The influence of the aforementioned management variables must be evaluated to identify other factors potentially influencing the TP, TN and chlorophyll a concentrations in stormwater ponds. Identifying and measuring variables that significantly impact nutrient and algal concentrations within stormwater ponds will provide better guidance for stormw ater pond management criteria. The careful evaluation and consideration of individual stormwater pond characteristics may provide a more accurate understanding of nutrient response relationships (Havens, 2003) . Identifying l andscaping and management variables with significant impacts on water column nutrients and algae could also provide future guidance and recommendations for reducing nutrients and algae in stormwater ponds. In this paper, the impact of pond design, management and landscaping decisions on stormwater pond nutrient and chlorophyll a concentrations were evaluated to identify significant predictive variables of TP, TN and chlorophyll a concentrations within stormw ater ponds. Significant predictor variables were then used to develop pond specific TN , TP and chlorophyll a concentration models for clear and colored stormwater ponds. Methods This study was conducted in a large, residential community located within the Tampa Bay watershed. Wet stormwater ponds are an important feature in the community as over 300 ponds provide water storage, water treatment, aesthetic,

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73 recreational and economic value to community members. A single community pond manager is tasked with making all stormwater pond management decisions and a single pond management company is contracted to implement the community pond manager’s decisions, including chemical and mechanical interventions applied to the stormwater ponds. Landscape management surr ounding the stormwater ponds may be conducted by a community contracted company, individual private contractor, or private homeowner. Nealis et al. (2016) , sampled 36 stormwater ponds in a large, residential community in southwest Florida and measured water column TP concentration, TN concentration, color and chlorophyll a concentration at three predetermined locations within each pond monthly for 4 months. A representative subsample of 12 ponds was then selected from the 36 original ponds and sampled for an additional 8 months. This data were used to establish nutrient response relationships for TP and TN in clear and colored stormwater ponds (Nealis, Clark, Monaghan, Hochmuth, & Frank, 2016) . The nutrient response relationships established for TP and TN in stormwater ponds provide an estimate for quantifying the nutrient removal capacity within a stormwater pond, but low coefficients of determination for each model suggest there are other f actors influencing nutrient and response dynamics (Nealis, Clark, Monaghan, Hochmuth, & Frank, 2016) . Concurrent with the previous study, additional variables were measured at each stormwater pond sample site during each of the 12 sampling events, including field assessments of landscaping and management decisions. The variables and methods used to quantify the variables are described in Table 31.

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74 Visual evaluation of land use adjacent to stormwater ponds was conducted on site and spatial analysis of land use within 100 meter buffer of the stormwater ponds was conducted using ArcGIS Desktop (ESRI, 2011) and landscape disturbance gradients identified in the Landscape Development Intensity index (Brown & Vivas, 2005) . These variables were evaluated for their significance as predictors of TP, TN and chlorophyll a concentrations in clear and colored storm water ponds reported by Nealis et al. ( 2016) , using a statistical software (SAS Institute, 2009) stepwise regression fit model, mixed option, with the probability to enter and leave set at 0.15. Once the significant variables were identified, a fit least squares model procedure was conducted to identify variable coefficients and the model equation. Results and Discussion The stepwise regression fit model identified significant predictive variables for TP, TN and chlorophyll a concentrations in clear and colored ponds and a fit least squares model was used to determine variable coefficients, model equations and the coefficient of determination for each model. Predictive models evaluating the impact of different management and landscaping variables for clear and colored stormwater ponds are presented in Table 32 with summary statistics for each significant variable presented in Table 33. Residential fertilizer application, chlorophyll a concentration, subaquatic vegetation coverage, bank erosion, and the nutrient limitation of the stormwater pond were found to be significant predictor variables of phosphorus concentrations in clear stormwater ponds ( p <0.001, r2 =0.76). Chlorophyll a concentration, area of stormwater pond in proportion to surrounding 100 meters, pr esence of grass clippings, percent of pond area in littoral shelf, pond area, and nutrient limitation of the stormwater pond were

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75 found to be significant predictor variables of phosphorus concentrations in colored stormwater ponds ( p <0.001, r2 =0.82). Resi dential fertilizer application, presence of artificial aeration, percent of surrounding land area in low intensity transportation and low intensity commercial use, chlorophyll a concentration, filamentous algae coverage, presence of bank erosion, percent o f pond area in littoral shelf, and percent of littoral shelf area planted in emergent aquatic vegetation were found to be significant predictor variables of nitrogen concentration in clear stormwater ponds ( p <0.001, r2 =0.49). Residential fertilizer applic ation, presence of aeration, percent of surrounding land area in low intensity transportation and in highdensity residential use, percent of surrounding land area in natural lands or wetlands, presence of grass clippings, percent of pond area in littoral shelf and percent of adjacent land use in natural areas were found to be significant predictor variables of nitrogen concentration in colored stormwater ponds ( p <0.001, r2 =0.31). Evidence of chemical treatment, percent of surrounding land area in low inte nsity recreational and low intensity commercial land use, percent coverage of submerged aquatic vegetation, presence of grass clippings, percent of pond area in littoral shelf, percent of adjacent residential land use, nutrient limitation and TP concentrat ion were found to be significant predictor variables of chlorophyll a concentration in clear stormwater ponds ( p <0.001, r2 =0.51). Percent of surrounding land area in highdensity residential use, percent of surrounding land in natural lands or wetlands, percent of pond area in littoral shelf, percent of shoreline with shoreline plantings, percent of adjacent residential land use, percent of adjacent natural area, and nutrient limitation were found to be significant predictor variables of chlorophyll a conc entration in colored stormwater ponds ( p <0.001, r2 =0.51).

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76 Only two variables, littoral shelf coverage of pond area and the presence of grass clippings, were identified as significant drivers of TP, TN and chlorophyll a concentrations in clear and colored stormwater ponds (Figure 3 1). Ponds in this study had littoral shelf coverage ranging from 0 to 60%, with a median coverage of 15%. Littoral shelf coverage was negatively correlated with TP concentration in colored stormwater ponds, positively correlated with TN concentrations in clear ponds, negatively correlated with TN concentrations in colored ponds, and positively correlated with chlorophyll a concentrations in clear and colored ponds. Grass clippings were present in 73% of the ponds when sampled and the presence of grass clippings was inversely correlated with TP and TN concentrations and positively correlated with chlorophyll a concentrations within stormwater ponds. Results suggest littoral shelf coverage is an important driver of nutrient and chlor ophyll concentrations. Littoral shelves may provide some of the nutrient removal benefits of w etlands as runoff enters a stormwater pond, assimilat ing nutrients and leading to low concentr ations of TP and inorganic N (Graves, Wan, & Fike, Water quality characteristics of storm water from major land uses in South Florida, 2004) . The shallow areas in littoral shelves increase the area of contact between the water column, soil, and vegetation, and increase the potential of nutrient assimilation (Baldwin, Simpson, & Weammert, 2009; DB Environmental, Inc., 2005) . These shallow areas also reduce the velocity of incoming runoff and may allow suspended particles and the associated nutrients to settle out of the water column (Brix, 1993; Schueler T. , 1992) . Moreover, denitrification processes within the wetlandlike area can lead to additional nitrogen removal and low nitratenitrite N concentrations in wetland runoff (Graves,

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77 Wan, & Fike, Water quality characteristics of storm water from major land uses in South Florida, 2004; Hammer & Bastian, 1989) . Additional to nutrient mitigation, emergent littoral shelf vegetation has been found to reduce chlorophyll a concentrations by outcompeting algae for light and nutrients (DB Environmental, Inc., 2005; van Donk & van de Bund, 2002) , producing allelopathic substances (Jasser, 1995; Wium Anderson, Christophersen, & Houen, 1982) , and supporting algae grazing communities (van Donk & van de Bund, 2002) . Consequently, emergent and vegetative coverage of littoral shelves and pond sh oreline were identified as significant drivers of nutrient and chlorophyll a concentrations in stormwater ponds. Planted littoral shelves were found to be a significant predictor of TN concentration in clear stormwater ponds, with TN concentrations inversely correlated with plant coverage. Shoreline plantings coverage was a significant predictor of algae growth and was inversely correlated with chlorophyll a concentrations. Submerged aquatic vegetation was found to be a significant predictor of TP and chlor ophyll a concentrations in clear stormwater ponds, with TP and chlorophyll a concentrations inversely correlated with submerged aquatic vegetation coverage. Prior research indicates increased phosphorus levels in the water column are not directly linked to the increased growth of submerged aquatic vegetation as they obtain most of their phos phorus from the sediments (Cooke, Welch, Peterson, & Newroth, 1993) , but s ubmerged aquatic vegetation is able to alter the physicochemical e nvironment of water, resulting in chemical precipitation (Reddy, Kadlec, Flaig, & Gale, 1999) .

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78 Results also suggest grass clippings are an important driver of nutrient and chlorophyll concentrations in stormwater ponds. The pr esence of grass clippings was a significant predictor of TP concentration in colored stormwater ponds, TN concentrations in clear and colored ponds, and chlorophyll a concentrations in clear ponds. Although grass clippings provide additional nutrients to t he water column as they decompose (Bedan & Clausen, 2009) , the presence of grass clippings was negatively correlated with TP and TN concentrations but positively correlated with chlorophyll a concentrations within stormwater po nds. These correlations could potentially be explained by the presence and growth of epiphytic or filamentous algae on subsurface grass clippings, but the presence of grass clippings and water column nutrient concentrations should be further investigated t o identify the dynamics of grass clipping nutrient fate. Several other variables were identified as significant drivers of TN, TP and/or chlorophyll a concentrations. Residential fertilizer application was a significant predictor of both TN and TP concentr ations in the stormwater ponds. Residential application of nitrogen and phosphorus fertilizer was assumed to cease during the months of the Manatee County fertilizer ordinance, from June 1st to September 30th (Manatee County, 2011) , and the presence of this fertilizer restriction was inversely correlated with TP concentrations in clear stormwater ponds and TN concentrations in both clear and colored ponds. Even though regulatory controls are considered generally ineffective in managing nonpoint source pollutants from stormwater with no clear point of origin (Taylor & Wong, 2002) , fertilizer restrictions may have a positive impact on immediately receiving waters by reducing the nutrient loads to the landscape. Removing or limiting

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79 external loading of nutrients to the watershed may thus reduce the runoff into stormwater ponds. Chlo rophyll a concentration was a significant predictor of nutrient concentrations, positively correlated with TP concentrations in clear and colored stormwater ponds and TN concentration in clear ponds. The modeling results align with previous studies as nitr ogen and phosphorus are recognized as drivers of chlorophyll a concentrations in freshwater lake systems (Sakamoto, 1966; Dillon & Rigler, 1974; Brown, Hoyer, Bachmann, & Canfield, 2000; Florida Depart ment of Environmental Protection , 2012) and stormwater ponds (Nealis, Clark, Monaghan, Hochmuth, & Frank, 2016) . Interestingly, filamentous algae coverage was identified as a significant predictors of TN in clear storm water ponds and was negatively correlated with increases in TN concentrations. Filamentous algae is a recognized aesthetic concern in stormwater ponds and its growth, nutrient response and aesthetic impact in stormwater ponds should be further researched. The presence of bank erosion surrounding the stormwater pond was also a significant predictor of TP and TN concentrations in clear stormwater ponds and was inversely correlated with water column nutrient concentration. The models’ suggested relationship is contrary to expectations as eroded soil particles and organic matter can be important contributor s of nitrogen and phosphorus to the aquatic system (Daniel, Sharpley, Edwards, Wedepohl, & Lemunyon, 1994; Sharpley, et al., 1994; Quinton, Govers, Van Oost, & Bardgett, 2010) , especially during large rain events causing major erosion and runoff (Pionke, Gburek, Sharpley, & Zollweg, 1997) . Shoreline erosion may contribute additional org anic matter and soil particles to the stormwater pond littoral

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80 areas, supporting denitrification and providing additional sorption sites, but additional research should be conducted to identify a possible explanation. The limiting nutrient status of the s tormwater pond was a significant predictor of phosphorus and chlorophyll a concentrations in clear and colored ponds. Phosphorous is usually identified as the limiting nutrient in freshwater systems and driver of algal p roduction (Schindler, 1977; Schindler, 1974; Canfield, 1983; Mazumder & Havens, 1998) . Chlorophyll a response to increasing TP concentrations in freshwater lakes can be reduced by nutrient limitation (Canfield, 1983) , so stormwater ponds in this study were categorized as nitrogen limited (N:P<7:1), phosphorus limited (N:P>20:1) or colimited (7:1
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81 suggest the opposite, with the exception of low intensity transportation land use. The percent land use i n natural area/wetland were positively correlated with TN and chlorophyll a concentrations in stormwater ponds while the percent land in low intensity commercial use and percent land use in high density residential use were inversely correlated with TN and chlorophyll a concentrations. As expected, the percent of the surrounding 100 meter buffer in low intensity transportation, or paved roads, was positively correlated with TN concentrations in clear and colored stormwater ponds. Since the contributing landscape surrounding the stormwater ponds is designed to direct runoff flows to specific stormwater ponds, the landscape use in the 100 meters surrounding the pond may have less impact on the nutrient concentrations within the pond than the adjacent land use as runoff may be directed to other stormwater ponds. The percent adjacent natural area was a significant predictor of TN and chlorophyll a concentrations in colored stormwater ponds and the inverse correlation suggests the low impact of this land use. Evid ence of chemical treatment to the pond, either visual or recorded, was a significant predictor of algal growth, inversely correlated with chlorophyll a concentrations in clear stormwater ponds. The negative impact of chemical treatment on chlorophyll a concentrations suggests anthropogenic intervention suppresses algal response to nutrient concentrations within stormwater ponds, supporting claims made by Nealis et al. (2016) . This evidence is important to consider when identifying nutrient response relationships and establishing nutrient management thresholds for stormwater ponds as the actual response in untreated ponds may be different than those without chemical intervention.

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82 Several other measured variables were signi ficant predictors of individual algae and nutrient concentrations and warrant further investigation. Stormwater pond area and the proportion of the stormwater pond area in relation to the surrounding 100 meter contributing area were identified as significa nt predictors of TP in colored systems. Additionally, the use of artificial aeration was a significant predictors of TN in clear or colored stormwater ponds, with both positive and negative impact on water column TN concentration. Aeration can impact nutri ent release by increasing the oxidation of organic sediments and removing anaerobic areas necessary for denitrification, but further research should be conducted to evaluate the impact of aeration devices on water column nutrient concentrations. Further i nvestigation of all the bivariate relationships between identified individual significant predictor variables and nutrient or chlorophyll concentrations is necessary. However, recognizing the importance of these identified variables as drivers in stormwate r pond systems offers an improved prediction of TN, TP and chlorophyll a concentrations within clear and colored stormwater ponds. Conclusion This study evaluated the impact of management and landscaping decisions on stormwater pond nutrient and chlorophy lla concentrations to identify significant predictor variables of TP, TN and chlorophyll a water column concentrations within clear and colored stormwater ponds. Using the significant predictor variables, models were developed to provide more accurate, si te specific nutrient and water column algae predictions to aid and improve management of stormwater pond function, use and aesthetics.

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83 Table 3 1 . Management and landscaping variables evaluated for significance as predictors of total phosphorus, total nitrogen and chlorophyll a concentrations in stormwater ponds. Variable Description Chemical treatment CT Presence of chemical treatment was determined at each site by blue water column coloring, indicating dye for clarity and/or algae treatment, or if chemical treatment was performed and recorded by the pond management company within 6 weeks prior to the sampling date. Pond management company records were not always consistent with visual evidence of treatment. Presence of treatment was coded with “1” and absence of treatment was coded with “0.” Residential landscape fertilizer application RF Residential fertilizer application of fertilizer containing nitrogen and/or phosphorus was assumed to cease during the months of the Manatee County fertilizer ordinance, from June 1st to September 30th (Manatee County, 2011) . Sampling events during the ordinance were coded with “1”. Fertilizer application was assumed to occur during the remaining, non restriction months and sampling events were coded with a “0.” Aeration AE The presence of aeration devices within the stormwater pond was c oded with “1” and absence of aeration was coded with “0.” Aeration devices included subsurface and surface aerators. Chlorophyll a concentration CHL Concentration of chlorophyll a (gL 1 ) were measured at a depth 0.60 m using the WET Labs ECO Triplet optical instrument. The WET Labs ECO Triplet w measured chlorophyll a concentration every 30 seconds for 3 minutes and mean values were calculated for each sampling station This variable was not included in the evaluation of chlorophyll a concentrations predictor variables. Natural land/open water land use NL Percent coverage of land in open water, upland, or wetland with very low manipulations within 100 meters of the stormwater pond (Brown & Vivas, 2005) . Land use coverage was evaluated with GIS software. Recreational/open land low intensity RL Percent coverage of land in areas maintained as natural areas and undeveloped land with natural within 100 meters of the stormwater pond (Brown & Vivas, 2005) . Land use coverage was evaluated with GIS software. Recreational/open land medium intensity RM Percent coverage of land in areas with grassy lawns, land that has been cleared and pr epared for construction, and humancreated water bodies (stormwater ponds) within 100 meters of the stormwater pond (Brown & Vivas, 2005) . Land use coverage was evaluated with GIS software. Recreational/open land high intensity RH Percent coverage of land used for recreation fields and golf courses within 100 meters of the stormwater pond (Brown & Vivas, 2005) . Land use coverage was evaluated with GIS software. Single family residential h igh density HD Percent coverage of land in areas used for residential units with a density of more than 20 units/ha within 100 meters of the stormwater pond (Brown & Vivas, 2005) . Land use coverage was evaluated with GIS software. All residential property in the community was included in this category. Commercial low intensity CL Percent coverage of land in areas used for commercial business within 100 meters of the stormwater pon d (Brown & Vivas, 2005) . Land use coverage was evaluated with GIS software. Transportation low intensity TL Percent coverage of land in driveways and paved roads with no more than 2 lanes within 100 meters of the stormwater pond (Brown & Vivas, 2005) . Land use coverage was evaluated with GIS software.

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84 Table 31. Continued Variable Description Transportation high intensity TH Percent coverage of land in paved roads with more than 2 lanes, including the shoulder, within 100 meters of the stormwater pond (Brown & Vivas, 2005) . Land use coverage was evaluated with GIS software. Stormwater pond SW Are a of stormwater pond of interest in proportion to surrounding 100 meters. Land use coverage was evaluated with GIS software. Floating filamentous algae coverage FA Percen t coverage of shoreline water in floating filamentous algae. Shoreline water was defi ned as the 2 meters extending into the stormwater pond from the water’s edge. Coverage was visually estimated on site. Submerged aquatic vegetation SAV Percent coverage of the visible sub surface sediment by submerged aquatic vegetation. Visible subsurf ace sediment was defined as the 3 meters extending into the stormwater pond from the water’s edge. Coverage was visually estimated on site. Bank erosion BE The presence of surrounding bank erosion was documented and coded with “1” if there was any evidence of soil erosion within five meters of the stormwater pond perimeter. The absence of erosion was coded with “0.” Grass clippings GC The presence of grass clippings within the stormwater pond was documented and coded with “1” if clippings were identified on the pond surface or settled to the pond sediment. The absence of grass clippings was coded with “0.” Littoral shelf coverage LS The percent coverage of total stormwater pond area consisting of littoral shelf. This value w as determined using “as built” development documents and on site visual evaluation. Littoral shelf plantings LP The percent of the littoral shelf planted in emergent vegetation was visually evaluated during each sampling event. Shoreline plantings SP The percent of the stormwater pond shoreline edge planted with vegetation other than turfgrass. Shoreline edge was defined as 1 upland meter from the water’s edge. Shoreline plantings were evaluated during each sampling event. Adjacent homes HO The percen t of the area immediately surrounding the stormwater pond in residential homes, lawns and driveways. Evaluated visually on site. Adjacent golf course GO The percent of the area immediately surrounding the stormwater pond in use as a golf course. Evaluated visually on site. Adjacent natural area NA The percent of the area immediately surrounding the stormwater pond preserved as a natural area. Evaluated visually on site. Adjacent roads RO The percent of the area immediately surrounding the stormwater pond s in use as paved roadway. Evaluated visually on site. Pond size PS The total area of the pond as defined by community development and pond management documents. Nutrient Limitation LM Using corresponding TN and TP concentrations (Nealis, Clark, Monaghan, Hochmuth, & Frank, 2016) , ponds were categorized as nitrogen limited (N:P<7:1), phosphorus limited (N:P>20:1) and colimited (7:1
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85 Table 3 2. Empirical models and summary statistics describing the association of monthly average nutrient and chlorophyll concentrations using significant management and landscaping predictors from stormwa ter ponds in southwest Florida (Nealis, Clark, Monaghan, Hochmuth, & Frank, 2016) . Variable Pond Model n F p > F r 2 Phosphorus (mgL1) Clear TP =0.075 0.005RF +0.001CHL 0.010SAV 0.009BE + LM (0.068 IF N Limited, 0.021 IF Co Limited, 0.047 IF P Limited) 87 42.92 <0.001 0.76 Colored TP =0.109 0.116SW +0.001CHL 0.016GC 0.041LS +0.004PS +LM (0.079 IF N Limited, 0.016 IF CoLimited, 0.063 IF P Limited) 120 71.03 <0.001 0.82 Nitrogen (mgL1) Clear TN =1.06 0.19RF +0.63AE +1.28TL – 2.76CL +0.01CHL – 2.65FA – 0.24BE +0.56LS – 0.18LP 87 8.08 <0.001 0.49 Colored TN =1.02 0.15RF 0.25AE +5.27TL 1.63HD +2.88NL 0.18GC 0.57LS 1.42NA 120 6.25 <0.001 0.31 Chlorophyll a ( g L1) Clear CHL = 2.90 1.62CT +27.41RL 39.24CL 2.62SAV +2.33GC +12.46LS +6.31HO +1.07LM +50.40TP 87 8.87 <0.001 0.51 Colored CHL =10.48 26.29HD +20.38NL +7.81LS 4.45SP +6.71HO 8.28NA 2.07LM 120 7.54 <0.001 0.32 Coefficient abbrevi ations are identified in Table 33.

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86 Table 3 3. Summary statistics for significant predictor variables of total phosphorus, total nitrogen and chlorophyll a stormwater pond models in southwest Florida Model Variable Estimate SE t ratio >|t| Phosphorus, Clear Residential Fertilizer RF 0.005 0.003 1.56 =0.12 (mgL 1 ) Chlorophyll a CHL 0.001 0.001 2.88 <0.01 Sub. Aquatic Veg. SAV 0.010 0.004 2.81 <0.01 Bank Erosion BE 0.009 0.004 2.41 <0.05 N Limited LM 0.068 0.006 11.32 <0.001 Co Limited LM 0.021 0.004 5.78 <0.001 P Limited LM 0.047 ---Phosphorus, Colored Stormwater Pond SW 0.116 0.043 2.71 <0.01 (mgL 1 ) Chlorophyll a CHL 0.001 0.001 2.95 <0.01 Grass Clippings GC 0.016 0.005 3.41 <0.001 Littoral Shelf LS 0.041 0.015 2.72 <0.01 Pond Size PS 0.004 0.003 1.54 =0.13 N Limited LM 0.079 0.005 14.46 <0.001 Co Limited LM 0.016 0.004 3.81 <0.001 P Limited LM 0.063 ---Nitrogen, Clear Residential Fertilizer RF 0.188 0.07 2.73 <0.01 (mgL 1 ) Aeration AE 0.625 0.21 2.97 <0.01 Transportation, L.I. TL 1.278 0.63 2.02 <0.05 Commercial, L.I. CL 2.759 1.09 2.54 <0.05 Chlorophyll a CHL 0.014 0.01 2.06 <0.05 Filamentous Algae FA 2.651 0.67 3.96 <0.001 Bank Erosion BE 0.237 0.09 2.70 <0.01 Littoral Shelf LS 0.563 0.37 1.53 =0.13 Littoral Shelf Planted LP 0.191 0.83 2.28 <0.05 Nitrogen, Colored Residential fertilizer RF 0.147 0.08 1.86 <0.10 (mgL 1 ) Aeration AE 0.248 0.12 2.07 <0.05 Transportation, L.I. TL 5.269 1.16 4.55 <0.001 Residential, H.D. HD 1.625 0.81 2.02 <0.05 Natural/Wetland NL 2.882 0.78 3.69 <0.001 Grass Clippings GC 0.176 0.10 1.83 <0.10 Littoral Shelf LS 0.573 0.26 2.23 <0.05 Adj. Natural Area NA 1.425 0.38 3.75 <0.001 Chlorophyll a, Clear Chemical Treatment CT 1.625 0.86 1.54 =0.13 ( g L 1 ) Recreational, L.I. RL 27.405 5.51 4.97 <0.001 Commercial, L.I. CL 39.235 13.80 2.84 <0.01 Sub. Aquatic Veg. SAV 2.619 1.06 2.47 <0.05 Grass Clippings GC 2.330 0.89 2.61 <0.05 Littoral Shelf LS 12.464 4.51 2.76 <0.01 Adj. Homes HO 6.312 2.06 3.06 <0.01 Nutrient Limitation LM 1.071 0.63 1.69 <0.10 Total Phosphorus TP 50.400 20.32 2.48 <0.05

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87 Table 33. Continued Model Variable Estimate SE t ratio >|t| Chlorophyll a, Residential, H.D. HD 26.295 10.25 2.57 <0.05 Colored Natural/Wetland NL 20.382 8.66 2.35 <0.05 ( g L 1 ) Littoral Shelf LS 7.807 3.14 2.48 <0.05 Shoreline Plantings SP 4.445 1.83 2.43 <0.05 Adj. Homes HO 6.713 3.39 1.98 <0.10 Adj. Natural Area NA 8.281 4.73 1.75 <0.10 Nutrient Limitation LM 2.069 0.46 4.46 <0.001 Descriptions of variables located in Table 33.

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88 Figure 31. Variables identified as significant predictors of phosphorus, nitrogen and chlorophyll a concentrations in stormwater ponds. Arrows indicate positive, negative or both positive and negative variable coefficients.

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89 CHAPTER 4 CREATING A COMMUNITY BASED CHLOROPHYLL A THRESHOLD FOR STORMWATER PONDS Introduction Nutrient response relationships are commonly utilized by researchers and water resource managers to develop standards and criteria protecting water quality. Relationships between water column nutrient concentrations and the response variable are measured directly or estimated and regression models are established to estimate response variable concentrations based on quantifiable nutrient concentrations (Hoyer, Frazer, Notestein, & Canfield, 2002) . The desired use of a water body should then be identified to determine how water quality is defined (Hoyer, Brown, & Canfield, 2004) . Once water quality is defined, a management criteria can be established identifying nutrient or response variable concentration thresholds protective of desired conditions, dependent on use or water body type. Designated uses and n utrient response relationships were used in this manner to establish protective criteria for natural, freshwater lakes in Florida. T he United States Environmental Protection Agency (EP A ) published numeric nutrient criteria (NNC) establishing numeric water quality criteria for nutrients and response variables, specifically chlorophyll a , interpreting narrative criteria for Class I and III surface waters based upon Florida Department of Environmental Protection ( FDEP ) research and recommendations (Florida Department of Environmental Protection , 2012) . The an nual geometric mean chlorophyll a conc entration was chosen by FDEP as the biological response variable to relate total nitrogen (TN) and total phosphorus (TP) concentration because of the strong, predictable correlation (Florida Department of Environmental Protection , 2012) . A chlorophyll a value of 20g L1 was selected for colored (>40

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90 platinum cobalt units , PCU) lakes in Florida based on several lines of evidence, including user perception and protection of designated use (Florida Department of Environmental Protection , 2012) . Although stormwater ponds are increasingly treated and valued as freshwater lakes in Florida, they do not fall under the same protective criteria as natural lakes. Stormwater ponds in Florida are increasingly utilized in developments for purposes o ther than their permitted requirement of removing at least 80% of the annual average pollutant load (Livingston & McCarron, 1992) . Residents v alue stormwater ponds as landscape features, providing recreational and economic value to their residential communities (DeLorenzo, Thompson, Cooper, Moore, & Fulton, 2012; Serrano & DeLorenzo, 2008) , but unlike natural lakes, water quality standards and designated uses within stormwater ponds are not protected or defined. Use and aesthetic expectations of stormwater ponds appear to be similar to natural, freshwater lakes, but the maintenance for aesthetic expectations may impact stormwater pond treatment function and increase the likelihood that these ponds will fail to meet required TN and TP removal efficiencies (Harper & Baker, 2007) . Currently, aesthetic expectations of stormwater ponds are often maintained through biological response suppression. Algal blooms in stormwater ponds due to high water column nutrient concentrations are typically controlled through chemical treatments to meet aesthetic and recreational demands, temporarily removing the biological uptake nutrient removal pathway (Harper & Baker, 2007) . I dentifying a biological endpoint similar to the NNC would provide clear guidance to improve management and maintenance of ponds nutrient concentr ations to identify quantifiable

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91 nutrient goals protective of both pond use expectations and downstream, natural water bodies. The stormwater pond regulatory requirements of nutrient removal and social expectations of aesthetics and attaining use objectives would no longer have to be mutually exclusive. Identifying the designated uses of stormwater ponds and establishing a biological endpoint protective of those uses and preferences is essential for improving stormwater pond management and ensuring maintenance of the permitted function. Surveys of lake users regarding lake use, water quality and water chemistry have been conducted (Heiskary & Walker, 1988; Smeltzer & Heiskary, 1990; Hoyer, Brown, & Canfield, 2004) and have contributed to establishing the biological response threshold of impairment for the NNC protecting natural Florida lakes (Florida Department of Environmental Protection , 2012) . In this study, a survey was conducted to determine a community based chlorophyll a threshold, or biological endpoint, for stormwater ponds in a large, southwest Florida community . Additionally, t he impact of education on chlorophyll a threshold and/or the presence of submerged aquatic veg etation on participant identified thresholds was evaluated. Finally, t he influences of pond use, knowledge of stormwater pond function and demographic background on preferred threshold were determined. Methods This study was conducted in a large community within the Tampa Bay watershed, covering 8,500 acres with a growing population of over 15,000 residents. The community includes thousands of homes, over 300 stormwater ponds , multiple parks, several natural areas, and two golf courses. Stormwater ponds are an important component of the community as they provide aesthetic, recreational and economic value to residents and homeowners. M any homeowners paid premiums to have

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92 waterfront property on stormwater ponds, but most ponds in the community are easily visible and accessible to all residents. An internet based (Qualtrics, 2015) survey evaluating stormwater pond use, knowledge and perceptions was distributed via email to a purposive sample ( Ary, Jacobs, & Razavieh, 2002) of residents on the commu nity email listserv and conducted between October 23, 2014 and November 7, 2014 in accordance with established protocol (Dillman, 2007) . The survey included questions regarding pond use, stormwater pond knowledge, demographic information, and one question to identify the acceptable biological endpoint , or “treatment threshold,” for managing stormwater ponds . To identify the acceptable biological endpoint , participants were randomly assigned one of four treatments examining the impact of prequestion education and chlorophyll a concentration presentation. For the prequestion education treatment, p articipants were randomly assigned either a question preface providing education regarding algae and nutrient enrichment or a question preface with no educational information. The educational statement was: Algae can be found in most natural lakes and ponds in Florida. Algae blooms can occur when large amounts of nutrients enter a water body. These nutrients come from all parts of the land that drain to the pond, even if the land may be located some distance away. Activities within this area, including fertilizer use, can provide nutrients to the pond if they are not managed appropriately. Algae growth in stormwater ponds, as well as natural lakes, helps to take up nutrients in runoff and protects downstream natural resources by acting as a filter. When the nutrient supply to the pond is reduced, algae blooms can become less freq uent and less intense. The educational component explained the response of algae to water column nutrients, the natural occurrence of algal blooms in some Florida lakes, and the role of algae and

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93 sub merged aquatic vegetation in reducing water column nutrient concentrations. For the chlorophyll a concentration presentation, s urvey participants were also randomly assigned one of two series of ten images depicting chlorophyll a concentrations increasing in incr ements of five from 5 g L1 to 50 g L1 in a water column over a sandy bottom . Participants were asked to identify the chlorophyll a concentration at which water quality became unacceptable, or the “treatment threshold. ” One of the two series of images i ncluded sub merged aquatic vegetation over the sandy bottom to provide a focal item for clarity perspective (Figure 4 1) and the other series of photos contained no item atop the sandy bottom (Figure 4 2) . To create the series of images, a 0.50 m diameter, 1.00m tall clear, acrylic cylinder with a sandcovered bottom was used to create a 0.75 m water column of varyi ng chlorophyll a concentrations , increasing in increments of five from 5 g L1 to 50 g L1. An initial chlorophyll a concentration of 50 g L1 was confirmed using the WET Labs ECO Triplet w optical instrument and a dilution factor was used to create decreasing chlorophyll a concentrations. P hotographs were taken of the water column from 0.20 m above the water surface with a digital camera under similar combined natural and artificial lighting . Statistical computations were performed using the JMP statistical package (SAS Institute, 2009) by University of Florida Department of Statistics Statistical Consulting . A comp arison of means was used to examine the difference between the mean identified threshold for each treatment and that for natural, Florida lakes. Pairwise comparison and Tukey Kramer groupin) were conducted for each treatment to evaluate differences in mean identified thresholds for each treatment groups and assess impact of image selection and pre question education on response.

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94 Additionally, the GLIMMIX procedure (SAS Institute, 2005) was conducted to fit general linearized mixed models to the treatment data to compare resident identified chlorophyll a thresholds for different pond uses and demographic categories utilizing the Tukey Kramer Grouping for Treatment Least Squares Means ( =0 .1 0 ) . Results and Discussion The internet based survey was distributed to 3,848 residents and received 712 responses for a response rate of 18.5%. The low response rate may suggest the influence of a nonresponse bias on the resulting data. Of the 712 responses, 578 were complete for a completion rate of 81% . Data processing refined the raw survey data, coding and categorizing free response questions and removing unrecognizable responses. Identified Mean Treatment T hresholds One survey item asked the parti cipant, “ From completely clear to water colored green from algae, how green does your pond (or pond in your neighborhood) get before you think it needs treatment?” The responses were designed to depict a gradient in water column chlorophyll a concentrations, from a 5 gL1 to 50 gL1 and determine the biological endpoint , or treatment threshold, at which conditions became unacceptable. There were four potential treatments applied at random to the survey item for each participant; (1) the photos in the item had no sub merged aquatic vegetation in the water column and the question had no educational component (NN) , (2) the photos in the item had no sub merged aquatic vegetation in the water column and the question was prefaced with an algae educational component (NE) , (3) the photos in the item contained sub merged aquatic vegetation in the water column and the question had no educational component (VN), and ( 4 ) the photos in the item contained

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95 sub merged aquatic vegetation in the water column and the question was prefaced with an algae educational component (VE) . A c omparison of least squares means was conducted to determine if the chlorophyll a concentration treatment threshold for stormwater ponds was significantly different than Florida’s numeric nutrient criteria (NNC) threshold of 20 gL1 for natural lakes . A pairwise comparison of least square means using the Tukey Kramer treatment groups (Figure 4 3) . The mean identified treatment thresholds for stormwater ponds are similar to previous findings establishing chlorophyll a concentration values protective of recreational and aesthetic values between 20 and 30 gL1 (Hoyer, Brown, & Canfield, 2004; Glass, 2006) but greater than the 20 gL1 criteria established to protect natural Florida lakes (United States Environmental Protection Agency, 2010) . The community based treatment threshold could be coupled with associated nutrient data to develop a stormwater pond numeric criteria similar to the NNC to creat e management criteria protective of the desired water quality. The comparison of survey treatment groups revealed the impact of presentation when identifying the treatment threshold. Respondents asked to identify treatment threshold when provided with no prior education and no aquatic vegetation in the photo indicated thresholds significantly greater than individuals provided with photos containing aquatic vegetation, regardless of the inclusion of prequestion algae education al information. Respondents asked to identify preferred treatment threshold when provided with education and no aquatic vegetation in the photo i ndicated a

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96 significantly higher treatment threshold than individuals provided a photo with aquatic vegetation and education. Results suggest the presence of aquatic vegetation in the survey images reduces the preferred treatment threshold. Additionally, pr e question education regarding algae and nutrients does not have a significant effect on preferred treatment threshold . Even though the preference for submerged aquatic vegetation can vary among lake users (Richardson, 2008) , r esearch by Kaplan et al. (1972) suggest more complex natural scenes presented in images are preferred by individuals . The sub merged aquatic vegetation becomes more difficult to see in the series of images presented in the survey as the chlorophyll a concentration increases, whereas no natural item provides perspective as the chlorophyll a concentration increases in the other series of images. An increase in algae and decrease in water clarity have been identified as indicators of poor water quality (David, 1971; Moser, 1984) , especially when the waters are used for recreational purposes (Hoyer, Brown, & Canfield, 2004) , and the increase may be more evident when sub merged aquatic vegetation provides a preferred focal point for comparison. Additionally, t he educational treatment provided prequestion did not have a signific ant effect on the treatment threshold and did not change respondent perspective. The lack of impact is not unexpected, especially considering the question queried participants regarding personal pond preference and research has demonstrated individuals are less environmentally conscious concerning issues immediately related to their personal lives and material ambitions (Rickinson, 2001) . Impact of Pond Use on Mean Treatment Threshold One survey item asked participants how frequently over the prior year they used their stormwater pond for several specific uses, including birdwatching, fishing, watching

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97 the sun set/rise, relaxing, walking and picnicking . Respondents indicated the frequency on a sevenpoint scale ranging from never to daily. Stormwater pond use responses were reduced to three categories for statistical analysis; (1) never, (2) occasional, and (3) frequent. “Occasional” was defined as less than once a month but not as often as once a week and “frequent” was defi ned as at least once a week. A GLIMMIX procedure (SAS Institute, 2005) was conducted to fit general linearized mixed models to the four sets of treatment data (NN, NE, VN, VE) associated with each individual’s response to effectively compare mean resident identified treatment thresholds for different stormwater pond uses and frequency of use (Figure 4 4) utilizing the Tukey Kramer Grouping for Treatment Least Squares Means ( =0.1 0 ) . The comparison between use frequency trea tment threshold means for “birdwatching” revealed no significant difference between the use categories of frequent (n=355, M=24.4gL1, S E=0.65 ), occasional (n=150, M=23.3gL1, S E = 1.00 ) and never (n=102, M=21.5gL1, S E = 1.35 ) . The comparison between us e frequency treatment threshold means for “fishing” revealed no significant difference between the use categories of frequent (n=32, M=26.1gL1, SE=2.25 ), oc casional (n=101, M=24.5 gL1, SE=1.20 ) a nd never (n=462, M=23.6gL1, SE=0.60 ). The comparison between use frequency treatment threshold means for “watching sunset/rise” revealed no significant difference between the use categories of frequent (n=302, M=24. 2 gL1, SE=0.70 ), occasional (n=144, M=23.6 gL1, SE=1.05 ) and never (n=158, M= 23.2 gL1, S E=1.05 ). The comparison between use frequency treatment threshold means for “relaxing” revealed frequent users (n= 394 , M=24. 8 gL1, SE=0. 60) had significantly higher treatment thresholds than both occasional ( t (507)= 2.09, p <0.10; n= 99,

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98 M=2 2.0 gL1, SE=1 . 25 ) and non users ( t (507)= 2.51, p <0.05; n= 109 , M= 22. 3 gL1, SE=1.30 ). The comparison between use frequency mean treatment threshold for “walking” revealed no significant difference between the use categories of frequent (n=254, M=24.8gL1, SE=0.7 5), o ccasional (n=137, M=22.5 gL1, SE=1.05 ), a nd never (n=214, M=23.2 gL1, SE=0.90 ). The comparison between use frequency mean treatment threshold for “picnicking” revealed no significant difference between use categories of frequent (n= 14, M= 22.3gL1, S E= 3.4 0 ) , occasional (n= 76, M= 26.1gL1, SE=1.35 ), and never (n= 513, M= 23.4 gL1, SE=0.55 ). Additionally, a Tukey Kramer HSD was conducted to evaluate the differences between mean treatment thresholds identified by frequent users for each stormwater pond use category and found there was no significant difference. Stormwater ponds in residential and urban developments are valued for their recreational uses (Serrano & DeLorenzo, 2008) . In natural lake systems, user water quality preference varies based on the use of the system (Ditton & Goodale, 1973; Parsons & Kealy, 1992) , but the data collected suggests the re is no significant difference between water quality preference of di fferent uses when comparing the treatment thresholds of frequent users. However, frequency of use appears to increase the tolerance of higher chlorophyll a concentration values for most uses, significantly so for the use “relaxing.” Prior research indicate s i ncreased frequency of use increases the tolerance of higher chlorophyll a concentrations (Smeltzer & Heiskary, 1990; Hoyer, Brown, & Canfield, 2004) because individuals become accustomed to higher concentrations of chlorophyll a . Acceptable water quality for recreation is relative to users’ experiences (Smeltzer & Heiskary, 1990) and perceptions may be more sensitive

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99 to changes in water quality parameters from established or expected conditions (Michael, Boyle, & Bouchard, 2000) than specific levels . T he variation of identified treatment thresholds within each stormwater pond use and frequency of use has been demonstrated in a similar study on natural Florida lakes (Hoyer, Brown, & Canfield, 2004) and exhibits the variety in individual user preference. Establishing designated uses for stormwater ponds may provide a strategy for developing defensible criteria for protecting recreatio nal uses, aesthetic demands and regulatory nutrient load requirements of stormwater ponds. Results from this study provide identifiable treatment thresholds dependent on use and frequency of use, establishing chlorophyll a concentrations associated with im pairment. Knowledge and Educational Influence on Mean Treatment Threshold Several survey items asked participants questions evaluating their knowledge of stormwater ponds. A GLIMMIX procedure (SAS Institute, 2005) was conducted to fit general linearized mixed models to the four sets of treatment data (NN, NE, VN, VE) associated with each individual’s response to effectively compare mean resident identified treatment thresholds for participant responses to the knowledge and educ ation questions utilizing the Tukey Kramer Grouping for Treatment Least Squares Means ( =0.1 0 ) . One survey question asked participants (n=518) if the pond or lake in their community was natural or created (Figure 4 5) . All water bodies in the residential community are created stormwater ponds. No significant difference between response variables , however respondents who indicated “ natural ” had a lower mean treatment threshold (n=30, M=19.8gL1, SE=2.15) than respondents indicating

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100 “ created” (n=380, M= 23.6gL1, S E =0.60 ) and “I do not know” ( n=108, 24.7gL1, S E =1.10 ). Three survey questions queried participants regarding prior education or awareness of stormwater ponds (Figure 4 6) . The first question asked participants (n=524) if they had received any prior education regarding stormwater ponds. No respondents who indicated they had received prior education had slightly higher mean treatment thresholds (n= 210, M=24.2gL1, SE= 0.80) than respondents indicating they had not received prior education (n=314, M=23.4gL1, SE=0.65). The second question asked participants (n=522) if they were provided with any stormwater pond information by the real estate company when looking to buy or rent their home . Respondents who indicated they had been provided with stormwater pond information by the real estate company had a significantly higher, t (514)=1.70, p <0.10 , mean treatment threshold (n=27, M=27.5gL1, SE=2.45) than respondents who indicated they had not been provided with stormwater pond information (n=495, M=23.55gL1, SE=0.50). The third question asked participants (n=521) if they were provided with any stormwater pond information or presentation when moving into their community. No significant difference received stormwater pond information or presentation when moving into the community had slightly higher mean treatment thresholds (n=80, M=24.6gL1, SE=1.30) than respondents indicating they had not received stormwater pond information or presentation (n=441, M=23.6gL1, SE=0.55).

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101 One survey question asked participants to identify the function of alg ae in stormwater ponds (Figure 4 7). Respondents who identified “ filter and uptake nutrients and pollutants” as the function of algae had a mean treatment threshold significantly higher (n=139, M=27.6gL1, SE=0.96) than respondents who identified algae function as “grow out of control and look swampy” ( t (502)=4.45, p <0.001; n=165, M=21.8gL1, SE=0.87) , , “decrease property value” ( t (502)=3.29, p <0.01; n=48, M=21.4gL1, SE=1.62), , “smell bad” (t (502)=2.03, p <0.05; n=23, M=22.3gL1, SE=2.39) , , and “I don’t know” ( t (502)=3.23, p <0.01; n=147, M=23.3gL1, SE=0.92). There were no significant differences found between any of the other responses. Establishing treatment thresholds for stormwater ponds would create quantified management criteria to improve recreation, aesthetic and nutrient removal functions of stormwater ponds. Currently, qualitative aesthetic and recreational demands drive stormwater pond management in residential areas . B iological responses, like algal blooms, are suppressed with chemical treatments whenever t here are complaints. Removing or limiting the biological response eliminates an important removal pathway for nutrients and jeopardizes the regulated function of stormwater ponds as treatment basins (Harper & Baker, 2007) . The current management regime and understanding of pond roles must be altered to improve pond function. Establishing a community identified treatment threshold may help, but i t is widely recognizing changing the knowledge, opinions, and behaviors of homeowner s regarding management decisions is a significant challenge (Hostetler & Noiseux, 2010; Youngentob & Hostetler, 2005; Askew & McGuirk, 2004; Dunlap & Jones, 2003) . The challenge is compounded by the lack of knowledge

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102 regarding stormwater pond function. A notable percentage (27%, n=138) of the participants were unaware the water bodies in their community were built stormwater ponds. The lack of awareness coincides wit h the absence of prior education regarding stormwater ponds as 60% (n=314) of respondents claim they had received no prior general stormwater pond education and 85% (n=441) claim they had received no community specific stormwater pond education or informat ion. Prior education regarding stormwater ponds should provide individuals with better understanding of stormwater pond function and design and did result in the acceptance of slightly higher mean treatment thresholds. I nformation and education provided by real estate agencies was found to have a significant impact on resident identified treatment thresholds. Even though only 5% (n=27) of respondents indicated they were provided with stormwater pond information by the real estate company when they were pur chasing their home , they identified a significantly higher treatment threshold than the 95% (n=495) of respondents who indicated they had received no such information. Individuals purchasing homes on or near stormwater ponds managed for aesthetic and recreational demands may perceive these as natural systems and fail to understand their role in treating runoff. People prefer landscapes they perceive as natural (Dearden, 1987; Herzog, 1989; K aplan & Kaplan, 1981; Knopf, 1987; Nassauer, 1995) , even if they are not. Even though t he biological response to increased nutrients occurs in natural lakes, the desire to manage and suppress the response is not surprising as the presence of a ctual natural ecosystems and processes in urban setting s have been linked to perceived lack of care (Bos & Mol, 1979; Gobster & Hull, 2000; Misgav, 2000; Nassauer, 2004; Nassauer,

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103 1993; Wi lliams & Cary, 2002) . Increasing the awareness and understanding of the nutrient removal function of algae in stormwater ponds may increase the acceptable treatment threshold identified by a community. As demonstrated in this study, respondents who were aware of the function of algae in stormwater ponds had a significantly higher mean treatment threshold than all other respondents. Demographic Drivers of Mean Treatment Threshold Several demographic questions were included in the survey to evaluate inf luences on stormwater pond treatment threshold selection. A GLIMMIX procedure (SAS Institute, 2005) was conducted to fit general linearized mixed models to the four sets of treatment data (NN, NE, VN, VE) associated with each individual’s response to effectively compare mean resident identified treatment thresholds for demographic questions utilizing the Tukey Kramer Grouping for Treatment Least Squares Means ( =0.1 0 ) to identify significant differences. Responses revealed several significant differences in mean treatment thresholds between demographic groups (Figure 4 7). Seasonal resident respondents had a significantly lower mean treatment threshold (n=123; M=22.1g L1, SE= 1.03 ) , t (510)=1.87, p <0.10, than year round resi dent respondents (n=395, M=24.3g L1, SE=0.57). Male respondents had a significantly lower mean treatment threshold (n=331, M=22.5g L1, SE= 0.6 2) , t (510)= 3.62, p <0.001, than female respondents (n=187, M= 26.2g L1, SE=0.82). Respondents with children y ounger than 18 years old living in their residence had a significantly higher mean treatment threshold (n=73, M=26.4g L1, SE=1.33) , t (510)=2.11, p <0.05, than respondents without young children (n=445, M=23.4g L1, SE= 0.5 4) . Respondents who were older than 64 years had a significantly lower mean treatment threshold (n=278, 21.7g L1, SE=0.67) , t (480)=2.98, p <0.01,

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104 than respondents who were between 54 and 64 years old (n=126, 25.3g L1, SE=1 . 00) and significantly lower , t (48 0)=4.89, p <0.001, than respondents who were younger than 54 years old (n=88, 28.5g L1, SE= 1.21). Several additional demographic responses did not reveal any significant differences in m ean treatment threshold (Table 41) . Understanding demographic driver s of preferred treatment thresholds provides additional guidance improving stormwater pond management by identifying specific populations with significantly different preferences. Traditionally, lake use has defined water quality criteria in natural system s for users (Ditton & Goodale, 1973; Smeltzer & Heiskary, 1990; Parsons & Kealy, 1992; Hoyer, Brown, & Canfield, 2004) and regulators (Florida Department of Environmental Protection , 2012) , but id entifying populations that may be unaccepting of management criteria and adopted treatment thresholds provides opportunity for focused education and outreach to improve acceptance and implementation of water quality goals. The influence of gender and parental status demonstrated in this study (Figure 4 7) is supported by prior environmental studies. Women have been found to be more concerned about environmental quality issues than men (McStay & Dunlap, 1983; Zelezny, Chua, & Aldrich, 2000; Hunter, Hatch, & Johnson, 2004; McCright, 2010) and the significantly greater treatment threshold identified by female participants may reflect this concern. Additionally, parents of young children have demonstrated greater environmental concern and commitment to environmental protection than individuals without young children (Dupont, 2004; Teal & Loomis, 2000; Hamilton, 1985) . The parental eff ect even influences the male gender effect, increasing environmental concern and value (Wilson, Daly, Gordon, & Pratt, 1996) .

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105 The influence of age on preferred treatment threshold is significant (Figure 47) and could be the r esult of several factors that should be further investigated to improve understanding of this demographic difference . The negative correlation between age and willingness to contribute to future environmental protection is well supported (Samdahl & Robertson, 1989; Whitehead, 1991; Carlsson & JohanssonStenman, 2000) but recent data has revealed age is positively correlated with environmental concern (Liu, Vedlitz, & Shi, 2014) . A l arge percentage of respondents greater than 64 years in age (24%) are seasonal residents and half (51%) have lived in Florida for 10 years or less, so their prior experiences and reference conditions may be influencing their current preferred treatment thr eshold (Hoyer, Brown, & Canfield, 2004) . The impact of participant residence time is further demonstrated in the significant difference in treatment thresholds identified by all seasonal and year round residence (Figure 47), supporting the findings of Hoyer, Brown and Canfield (2004) that suggest lake users are more tolerant of eutrophic conditions if they are consistently exposed to more eutrophic conditions. Perception of water qualit y is relative to experience and exposure. Conclusion Establishing designated uses and management criteria similar to natural Florida lakes (Florida Department of Environmental Protection , 2012) could provide a framework for p rotecting aesthetic, recreational and permitted treatment functions of stormwater ponds. This study presented an approach for identifying a treatment threshold for stormwater ponds at which the stormwater pond i s considered unsuitable for desired use s as d efined by the community . Nearly all of the mean treatment thresholds identified for stormwater ponds in this study were significantly higher than the 20gL 1 chlorophyll a concentration of Florida’s NNC (Florida Department of

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106 Environmental Protection , 20 12) but were similar to prior studies establishing chlorophyll a concentration values protective of recreational and aesthetic values (Hoyer, Brown, & Canfield, 2004; Glass, 2006) . Survey image presentation does have a n influence on respondent identified chlorophyll a treatment threshold as the presence of submerged aquatic vegetation did significantly reduce the preferred chlorophyll a treatment threshold. Prequestion education regarding the role of algae in stormwater ponds did not have an effect on the participant identified treatment threshold. This study also identified the impact of designated uses, educational influences, and demographic drivers of treatment thresholds that must be considered to successfully implement a management criteria for stormwater ponds. The frequency of use for the identif ied stormwater pond recreational uses had some positive correlation with treatment thresholds, but the treatment threshold identified by frequent users of ponds for “relaxing” was the only use found to be significantly higher than less frequent users. Kn ow ledge of the actual function and role of algae in a stormwater ponds, as well as prior education of the role of stormwater ponds provided by real estate agencies , resulted in significantly higher chlorophyll a treatment thresholds . Finally, several demographic factors were found to be predictors of significant treatment threshold differences, including year round residency, gender , parental status, and age.

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107 Table 4 1. Demographic survey questions and responses with no significant difference in mean treatment threshold between responses (Tukey Kramer HSD, 10.1 15 22.9 1.05 >15 18.6 3.50 How many years lived in Florida? (n=510)

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108 Figure 41. Series of ten photos depicting water column chlorophyll a concentrations increasing in increments of five from 5 g L1 to 50 g L1 over a sandy bottom including submerged aquatic vegetation. Figure 42 . Series of ten photos depicting water column chlorophyll a concentrations increasing in increments of five from 5 g L1 to 50 g L1 over a sandy bottom.

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109 Figure 43 . Comparis on of mean chlorophyll a concentration (gL1) response of four survey treatments. The mean treatment threshold for each survey treatment was compared to the Numeric Nutr i ent Criteria at 20 g L1 (represented by the red line) and found to be significantl y grea ter for treatments NN, NE, and VN (*** = p <0.001, * = p <0.05). A pairwise comparison of least square means using the Tukey Kramer HSD, =0.05, revealed significant differences between survey treatment groups indicated by letters A, B and C. A *** AB *** BC * C 15 20 25 30 No education, no vegetation in photo (NN) Education, no vegetation in photo (NE) No education, vegetation in photo (VN) Education, vegetation in photo (VE)Treatment threshold chlorophyll a (gL1)Treatment

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110 Figure 44. Comparison of mean treatment threshold based on pond use. A Tukey threshold for “frequent” use of pond for each desi r ed use and no significant diff erence was found. For each desir ed use, a Tukey Kramer Grouping for Treatment Least Squares Means ( =0.1 0 ) was conducted to compare mean treatment thresholds and no significant difference was found between use frequencies for birdwatching, fishing, watching sunset/rise, walking or picnic , however, respondents who frequently used the stormwater pond for relaxing had a significantly higher treatment threshold than respondents using the stormwater pond for relaxing occasionally (p<0.05) and never (p<0.05). The Numeric Nutrient Criteria (NNC) chlorophyll a concentration threshold of 20 g L1 for natural lake systems is included for reference and visual comparison (horizontal red line). a aiaiiaiiiaivava aiaiibiiiaivava aiaiibiiiaivav15 20 25 30 Birdwatching Fishing Watching Sunset/rise Relaxing Walking PicnicTreatment threshold Chlorophyll a (ugL1)Desired use Frequently Occasionally Never A A A A A A

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111 Figure 45. Comparison of mean treatment threshold associated with knowledge of stormwater pond origin. A Tukey compare the mean treatment threshold between each response and no significant difference was found between the three responses to stormwater pond origin. The red horizontal line representing the NNC at 20gL1 is included for visual comparison. A A A 15 20 25 30 Natural Created I don't knowTreatment threshold chlorophyll a ( gL1)Stormwater pond origin

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112 Figure 46. Comparison of mean treatment threshold associated with stormwater pond education and awareness. A Tukey compare the mean treatment threshold between positive and negative responses to receiving each form of stormwater pond education. No significant difference ( =0.10) was found between individuals who did and did not receive education in the form of prior education or a presentation or information provided prior to m oving to the community. Individuals who received stormwater pond educational information from the real estate company prior to purchasing or renting their home (M=27.5gL1, SE=2.45) had significantly higher (p<0.10) mean treatment threshold than those who were not provided with information from the real estate company (M=23.55gL1, SE=0.50). The red horizontal line representing the NNC at 20gL1 is included for visual comparison. A A AiAiiAii15 20 25 30 Yes No Yes No Yes No Prior education Real estate information Presentation or information prior to movingTreatment threshold chlorophyll a (gL1)Survey itemBi

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113 Figure 47 . Mean treatment threshold associated with resident perceptions of algae function in stormwater ponds. A Tukey to compare the mean treatment threshold associated with the selected algae functions in stormwater ponds. Partic ipants who identified algae function as “filter and uptake nutrients and pollutants” had treatment threshold (M=27.6 gL1, SE=0.96) significantly greater (p<0.001) than participants who identified algae function as “grow out of control and look swampy” (M=21.8gL1, SE=0.87), “decrease property values” (21.4gL1, SE=1.62), “smell bad” (M=22.3gL1, SE=2.39) and “I don’t know” (M=23.3gL1, SE=0.92). The red horizontal line representing the NNC at 20gL1 is included for visual comparison. A B B B B 15 20 25 30 Filter and uptake nutrients and pollutants Grow out of control and look swampy Decrease property values Smell bad I don’t knowTreatment Threshold Chl a (ug/L)Algae function

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114 Figure 4 8 . Comparison of mean treatment threshold associated with demographic information. A Tukey Kramer ( =0.10) comparison of least square means for each survey item revealed significant differences between mean treatment thresholds associated with demographic information. The red horizontal line representing the NNC at 20gL1 is included for visual comparison. A B AiBiAiiBiiAiiiAiiiBiii15 20 25 30 Seasonal Year round Male Female Children No children < 54 years 54-64 years > 64 years Seasonal or year round resident Sex Children under 18 AgeTreatment threshold chlorophyll a (gL1)Survey item

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115 CHAPTER 5 METHODS FOR IDENTIFYING AND QUANTIFYING IMPACT OF NUMERIC THRESHOLD IN STORMWATER PONDS Introduction N utrient response relationships are commonly used by lake managers and regulatory agencies to predict unwanted algal blooms and implement measures to control eutrophication. Chlorophyll a concentration is a highly visible indicator of eutrophication (Havens, 2003) and is often used as a measure of the algal standing crop (Dillon & Rigler, 1974) . Nitrogen and phosphorus are recognized drivers of chlorophyll a response in freshwater lake systems (Sakamoto, 1966; Dillon & Rigler, 1974; Brown, Hoyer, Bachmann, & Canfield, 2000; Florida Department of Environmental Protection , 2012) and the r elationships between total phosphorus (TP), total n itrogen (TN) and chlorophyll a concentrations can be used to create regression models approximating algal response concentrations based on quantifiable nutrient concentrations (Hoyer, Frazer, Notestein, & Canfield, 2002) . The state of Florida adopted numeric nutrient criteria (NNC) to establish protective numeric water quality criteria for nutrients and chlorophyll a in Class I and III surface waters (Florida Department of Environmental Protection , 2012) . A chlorophyll a value of 20 gL1 was deemed protective of the designated uses of colored (>40 (Florida Department of Environmental Protection , 2012) and corresponding nutrient values were established for TP and TN . To establish the NNC values , FDEP decided to define a range of 50% probability that a given TN or TP level will elicit the chlorophylla response given the regression equa tions calculated for the clear and colored lake

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116 systems when establishing the numeric nutrient criteria (Florida Department of Environmental Protection , 2012) . Stormwater ponds in Florida are increasingly utilized in develop ments for aesthetic and recreational purposes (DeLorenzo, Thompson, Cooper, Moore, & Fulton, 2012; Serrano & DeLorenzo, 2008) , but their desired uses and water quality thresholds are not defined or protected by the sam e regulations and criteria protecting natural lakes , even though water quality expectations of stormwater pond users are similar to natural, freshwater lakes (Nealis, Monaghan, Clark, Hochmuth, & Frank, 2016) . Currently, t he only regulatory water quality requirement stormwater ponds must meet is the removal of at least 80% of the annual average pollutant load (Livingston & McCarron, 1992) . Establishing a nutrient management threshold utilizing stormwater pond user expectations and nutrient response relationships would provide the framework for identifying quantifiable watershed nutrient management goals and strategies to protect stormwater pond uses and expectations. A stormwater pond nutrient m anagement criteria and successful management regime could increase the likelihood that stormwater ponds meet regulatory nutrient removal requirements and minimize the impact of nonpoint source pollution on downstream water bodies. A survey conducted by Nealis et al. (2016) , found mean chlorophyll a concentrations thresholds for a variety of stormwater pond uses and aesthetic preferences ranged from approximately 20 to 25 g L1 chlorophyll a while a previous study revealed the actual mean stormwater pond chlorophyll a concentration in the same community was 5.55 0.49 g L1 (SE) for clear systems and 9.12 0.44 g L1 for colored systems (Nealis, Clark, Monaghan, Hochmuth, & Frank, 2016) . It is believed

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117 that low algal responses to nutrients within the ponds are a result of algaecide applications to meet present aesthetic preferences. However, there appears to be a discrepancy between the community’s acceptable threshold and the threshold at which pond managers are treating the ponds. Managing stormwater ponds for the increased chlorophyll a concentration could potentially increase the stormwater ponds’ biological nutrient uptake and removal of nitrogen and phosphorus, assuming algal assim ilated nutrients could potentially increase the stormwater ponds’ removal of nitrogen and phosphorus, algal assimilated nutrients remain within the stormwater pond and chlorophyll a concentrations remain constant. In this paper, a method is proposed for i dentifying and quantifying threshold nutrient levels in stormwater ponds . The proposed method used established nutrient chlorophyll a response relationships (Nealis, Clark, Monaghan, Hochmuth, & Frank, 2016) to create stormwater pond nutrient criteria . These values were then used to determine the maximum assimilative potential of nutrients if chlorophyll a levels were allowed to increase above current management levels. Methods Nutrient Management Threshold N utrient response rel ationships in clear and colored stormwater ponds in a Southwest Florida community were used to identify TP and TN concentrations associated with chlorophyll a thresholds identified by residents as protective of aesthetic and recreational uses (Nealis, Monaghan, Clark, Hochmuth, & Frank, 2016) . The inverse equations of the nutrient response relationships established by Nealis et al. (2016) , were calculated to determine the nutrient management criteria for TP and TN (mgL1) in clear and colored stormwater ponds based on community defined

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118 chlorophyll a concentration thresholds (gL1). Although not as stringent as the range of values offered by the NNC, this mean intercept of the nutrient response relationships was chosen to simplify management strategies and provide a single defensible management target to improve current management strategies. After establishing nutrient management threshol d values, the estimated percent of TP and TN assimilated into algal biomass were calculated to quantify the estimated impact different chlorophyll a management thresholds would have on algal nutrient assimilation potential within clear and colored stormwat er ponds. Nutrient Assimilation Potential To estimate the fraction of TP likely assimilated in algal biomass , TP was divided by orthophosphatephosphorus to identify percentage of TP in inorganic form. The remaining portion of TP was assumed to be in particulate organic form and associated with assimilated algal phosphorus (AAP) . For each sample, t he AAP was calculated and then divided by TP to identify the percentage of TP assimilated into organic form. To estimate the assimilated nitrogen values, a mmonium nitrogen (NH3N) and nitratenitrogen ( NOxN) were subtracted from TN to identify the mass of nitrogen assumed to be in organic form and associated with assimilated algal nitrogen (AAN). For each sample, the AAN was calculated and then divided by T N to identify the percentage of TN assimilated into organic form. The median AAP and AAN percentages for PCU) and colored (>40 PCU) stormwater ponds were calculated because of the nonnormal, skewed distribution of data. Separate values were cal culated for clear and colored stormwater ponds to account for the influence of color on nutrient response relationships (Hoyer & Jones, 1983; Brown, Hoyer, Bachmann, & Canfield, 2000) . TP and TN values were multipli ed by the median AAP and AAN percentages for each lake

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119 type to determine the associated absolute AAP and AAN values for clear and colored stormwater ponds . AAP and AAN values for potential chlorophyll a concentration thresholds ranging from 5 30 gL1 in clear and colored stormwater ponds were determined by multiplying the associated nutrient management threshold criteria for TP and TN by the corresponding median percent of the nutrient in organic form . Best fit curves and equations were then created fo r the AAP and AAN relationships using statistical software (SAS Institute, 2009) . I ndividual empirical models were used to calculate TP and TN values for clear and colored stormwater ponds at chlorophyll a thresholds ranging fr om 5 to 30 g L1. Associated AAP and AAN values for clear and colored stormwater ponds were calculated from the nutrient response values using the associated percent algal assimilated nitrogen and phosphorus. Results and Discussion Nutrient Management Thr eshold The inverse equations of the nutrient response relationships established by Nealis et al. (2016) , were calculated to create the empirical nutrient management criteria models for TP and TN (mgL1) (Table 5 1). A least squares regression analysis revealed statistically significant ( p< 0.001) yet weak relationships between TP and chlorophyll a in clear ( r2=0.23) and colored ( r2=0.26) stormwater ponds. The regression analysis revealed statistically significant but even weaker relationships between TN and chlorophyll a in clear ( p <0.05, r2=0.05) and colored ( p <0.01, r2=0.07) stormwater ponds. Statistically significant ( p <0.001) quadratic best fit models for clear and colored stormwater ponds were calculated for the r esulting nutrient management criteria (Tables 5 1 & 5 2).

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120 The stormwater pond nutrient management criteria for clear and colored systems established at 20 g L1 chlorophyll a are much different than the state of Florida’s NNC for natural lakes (Table 5 3). The acceptable range for TP in natural clear lake systems is 0.03 to 0.09 mgL1 and the clear stormwater pond TP threshold relating to a chlorophyll a concentration less than 20 g L1 is 0.41 mgL1. The acceptable statewide range for TP in a natur al colored lake system is 0.05 to 0.16, but the limit for lakes in the West Central Nutrient Watershed Region (WCNWR) is set at 0.49 mgL1. The community in this study is located in the WCNWR and the colored stormwater pond TP threshold is a comparable 0. 46 mgL1. The acceptable range for TN in natural clear lake systems is 1.05 to 1.91 mgL1 and the clear stormwater pond TN threshold is 32.1 mgL1. The acceptable range for TN in natural colored lake systems is 1.272.23 mgL1 and the colored stormwater pond TN threshold is 8.45 mgL1. (Florida Department of Environmental Protection , 2012) The TN thresholds for clear and colored stormwater ponds are much greater than those established for natural lake systems and further support the importance of investigating the influence of stormwater pond management and chemical interventions on algal response relationships to nutrients as reported in Nealis et al (2016) . Utilizing the more protect ive NNC for establishing a nutrient management criteria for nitrogen in stormwater ponds may be suggested to ensure protection of both stormwater pond aesthetic demands and natural downstream waterbodies. Stormwater ponds and the contributing watersheds ar e heavily managed and several other environmental drivers, including algaecide applications within the stormwater ponds, may impact nutrient response relationships (Nealis et al., 2016). Therefore, it is

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121 recommended the nutrient criteria most protective of natural downstream systems be selected for managing stormwater ponds. Utilizing the most protective criteria inherently protects the desired aesthetic and recreational uses of stormwater ponds while ensuring downstream ecosystems will not be negatively im pacted. Nutrient Assimilation Potential The median AAP portion of TP was 81% (n=86) in clear stormwater ponds and 76% (n=118) in colored stormwater ponds (Table 54) . The median AAN portion of TN was 80% (n=87) in clear stormwater ponds and 85% (n=120) in colored stormwater ponds. The estimated AAP and AAN associated with a range of chlorophyll a thresholds for clear and colored stormwater ponds were determined using the developed quadratic models ( Figures 51 & 5 2) . The AAP and AAN values were then converted to gm3 to quantify the potential assimilative capacity of phosphorus (Figure 5 3) and nitrogen ( Figure 54) by stormwater ponds at chlorophyll a th r esholds ranging from 5 to 30 g L1. Utilizing the estimated AAP and AAN, the potential increases in nutrient assimilative capacity associated with increasing chlorophyll a treatment thresholds from present stormwater pond chlorophyll a concentrations to the community identified treatment thresholds were evaluated (Figure 5 3 & Figure 54) . A t the current stormwater pond mean chlorophyll a concentrations, clear systems maintained at 5 g L1 chlorophyll a potentially remove 0.023 gm3 phosphorus and 0.970 gm3 nitrogen. Colored stormwater ponds maintained at 10 g L1 chlorophyll a potentially remove 0.053 gm3 phosphorus and1.725 gm3 nitrogen. If the chlorophyll a management threshold were increased to survey defined acceptable levels of 20 or 25 g L1 for clear and colored

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122 stormwater ponds , an inc reased removal o f phosphorus and nitrogen in clear and colored stormwater ponds could be achieved. A 20 g L1 chlorophyll a threshold potentially results in the removal of 0.332 gm3 phosphorus in clear systems (1,343% increase) , 0.347 gm3 phosphorus in colored system s (555% increase) , 25 . 71 gm3 nitrogen in clear systems (2,551% increase) , and 7.18 gm3 nitrogen in colored systems (316% increase) . A 25 g L1 chlorophyll a threshold potentially results in the removal of 0.510 gm3 phosphorus in clear systems (2,117% increase) , 0.636 gm3 phosphorus in colored systems (1,100% increase) , 43 . 6 gm3 nitrogen in clear systems (4,388% increase) , and 11.4 gm3 nitrogen in colored systems (584% increase) . Considering a stormwater pond of average size ( 0 .40 hectar es, 2 meter average depth) contains a volume of 8000 m3 and has several complete volume turnovers per year, and knowing there are several hundred stormwater ponds within the community, the effect of increasing community wide chlorophyll a thresholds on nut rient removal and downstream loading could be significant . Conclusion This study identified a method for ascertaining and quantifying nutrient management criteria in clear and colored stormwater ponds using established nutrient response relationships and community based chlorophyll a tolerance thresholds. The phosphorus nutrient management criteria values established for clear and colored stormwater ponds were greater than those for natural lake systems, but were comparable to the NNC for natural colored l akes in the WCNWR. The nitrogen nutrient management criteria values established for clear and colored stormwater ponds were much greater than those established for natural lake systems and suggest the impact of other management variables on algal responses .

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123 Furthermore, the potential assimilation of nitrogen and phosphorus at various nutrient management criteria levels were calculated to estimate the environmental impact of various community identified management thresholds. Increasing the nutrient management criteria from current levels to community identified management thresholds results in a great increase in the potential assimilation of nitrogen and phosphorus by stormwater pond algae. An increase in the chlorophyll a concentrations in clear and colored stormwater ponds from the current standards to the community identified acceptable chlorophyll a concentration of 20 g L1 would result in a 1,343% increase in the removal phosphorus in clear systems, 555% increase in the removal of phosphorus i n colored systems , 2,551% increase in the removal of nitrogen in clear systems, and 316% increase in the removal of nitrogen in colored systems , assuming all algal particles settle within the pond and there is permanent sediment stability . It is recommende d stormwater pond managers select the most conservative nutrient management criteria when comparing the stormwater pond management criteria to the NNC in order to protect both stormwater ponds and natural, downstream systems.

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124 Table 51 . Empirical models and summary statistics describing the association of monthly average nutrient and chlorophyll concentrations and median percent algal assimilated phosphorus or nitrogen using data from stormwater ponds in southwest Florida (Neal is, Clark, Monaghan, Hochmuth, & Frank, 2016) . Nutrient Pond Model n F p > F r 2 Phosphorus Clear LnCHL= 0.520LnTP + 3.459 86 27.19 <0.001 0.25 (mgL 1 ) LnTP= 1.923LnCHL 6.652 86 25.55 <0.001 0.23 Colored LnCHL= 0.368LnTP + 3.284 120 43.32 < 0.001 0.27 LnTP= 2.717LnCHL 8.924 120 40.39 <0.001 0.26 Nitrogen Clear LnCHL= 0.423LnTN + 1.528 86 4.53 <0.05 0.05 (mgL 1 ) LnTN= 2.364LnCHL – 3.612 86 4.53 <0.05 0.05 Colored LnCHL= 0.486LnTN + 1.959 120 8.30 <0.01 0.07 LnTN= 2.058LnCHL – 4.031 120 8.30 <0.01 0.07 CHL, chlorophyll a ( g L-1), TP, total phosphorus ( m g L-1), TN, total nitrogen ( m g L-1), clear ( 40 PCU), colored (>40PCU) . Table 5 2 . Quadratic models and summary statistics describing the association of monthly average nutrient and chlorophyll concentrations and median percent algal assimilated phosphorus or nitrogen associated with the identified threshold using data from stormwater ponds in southwest Florida (Nealis, Clark, Monaghan, Hochmuth, & Frank, 2016) . Model Color p r 2 Nutrient Response Relationships TP = 0.0009(CHL 17.625) 2 + 0.0348CHL 0.2913 Clear <0.001 0.99 TN = 0.1221(CHL 17.625) 2 + 3.3919CHL 35.9322 Clear <0.001 0.99 TP = 0.0024(CHL 17.625) 2 + 0.0572CHL 0.6862 Colored <0.001 0.99 TN = 0.0227(CHL – 17.625) 2 + 0.7667CHL 6.9959 Colored <0.001 0.99 Estimated Algal Assimilated Nutrient AAP = 0.0007(CHL 17.625) 2 + 0.0282CHL 0.2359 Clear <0.001 0.99 AAN = 0.0977 (CHL 17.625) 2 + 2. 7135 CHL – 2 8 . 7458 Clear <0.001 0.99 AAP = 0.0018(CHL 17.625) 2 + 0.0435CHL 0.5215 Colored <0.001 0.99 AAN = 0.0193(CHL 17.625) 2 + 0.6517CHL 5.9465 Colored <0.001 0.99 CHL, chlorophyll a ( g L-1), TP, total phosphorus ( m g L-1), TN, total nitrogen ( m g L-1), clear ( 40 PCU), colored (>40PCU), AAP/N, percent algal assimilated phosphorus or nitrogen.

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125 Table 53 . Florida’s Numeric Nutrient Criteria and the stormwater pond nutrient management criteria established for a residential community in southwest Florida. Nutrient Color Statewide Range Stormwater Pond WCNWR Nitrogen Clear 1.05 – 1.91 32.1 (mg L 1 ) Colored 1.27 – 2.23 8.45 Phosphorus Clear 0.03 0.09 0.41 (mg L 1 ) Colored 0.05 0.16 0.46 0.49 Clear 40 PCU, Colored >40 PCU. NNC values established by Florida Department of Environmental Protection (United States Environmental Protection Agency, 2010) . TP, total phosphorus, TN, total nitrogen, Chl a, Chlorophyll a, PCU, platinum cobalt units, S.E., s tandard error, NNC, Numeric Nutrient Criteria, WCNWR, West Central Nutrient Watershed Region. Table 54 . Summary statistics describing the estimated assimilated algal phosphorus (AAP) and assimilated algal nitrogen (AAN) for clear and colored stormwater ponds for a residential community in southwest Florida. Nutrient Color n Median Mean SD Range AAP Clear 86 0.807 0.786 0.193 0.297 – 1.00 Colored 118 0.757 0.714 0.242 0.246 – 1.00 AAN Clear 87 0.799 0.747 0.148 0.158 – 0.944 Colored 120 0.849 0.820 0.112 0.282 – 0.968 Clear 40 PCU, Colored >40 PCU.

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126 Figure 51 . Models displaying treatment threshold and numeric phosphorus values based on nutrient response relationships defined in Chapter 2 for clear and colored stormwater ponds with associated algal phosphorus assimilation values.

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127 Figure 52. Models displaying treatment threshold and numeric nitrogen values based on nutrient response relationships defined in Chapter 2 for clear and colored stormwater ponds with associated algal nitrogen assimilation values.

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128 Figure 53 . Estimated algal assimilated phosphorus (AAP g m3) in stormwater ponds at chlorophyll a concentrations from 5 to 30 g L1.

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129 Figure 54. Estimated algal assimilated nitrogen (AAN, g m3) in stormwater ponds at chlorophyll a concentrations from 5 to 30 g L1.

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130 CHAPTER 6 CONCLUSION Findings Stormwater ponds are an increasingly important landscape feature in Florida developments. The original and regulatory intent of including stormwater ponds in residential developments wa s to protect surface water quality by mitigating urban or residential runoff volume and reducing pollutants, including nitrogen and phosphorus (Livingston & McCarron, 1992; Harper & Baker, 2007) . Nutrients are removed through numerous pathways in stormwater ponds, including biological assimilation by plants and algae (Harper & Baker, 2007) . Stormwa ter ponds are required to remove 8095% of the total nitrogen (TN) and total phosphorus (TP) in runoff, but a study by Harper and Baker (2007) revealed stormwater ponds fail to meet the permitted removal efficiencies and recommended increased retention time and upstream pretreatment . Recently, stormwater ponds have become recognized by communities for their a esthetic and recreational value. Developers have increasingly incorporated stormwater ponds into community design to maximize waterfront properties and property value premiums. As such, water quality within stormwater ponds has become a concern of residents using the stormwater ponds , but, unlike natural water bodies in Florida, no water quality criteria exist for sto rmwater ponds. Managing social expectations of stormwater ponds does not take into consideration regulatory intent and therefore may be conducted at the expense of meeting regulatory requirements. Algal response to increased water column nutrients is commo n as there is a well documented positive relationship between nutrients and algal biomass as measured by chlorophyll a concentrations (Dillon & Rigler, 1974; Brown, Hoyer, Bachmann, &

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131 Canfield, 2000; H oyer, Frazer, Notestein, & Canfield, 2002; Florida Department of Environmental Protection , 2012) . N utrient response relationships are helpful in guiding management practices and were used to establish Florida’s Numeric Nutrient Criteria (NNC) protect ing designated uses of natural lakes . The NNC aids in identifying management strategies and nutrient loading targets by identifying unacceptable ch lorophyll a concentrations and associated preventative nutrient thresholds . In stormwater ponds, nutrient response relationships, unacceptable chlorophyll a concentrations, and preventative nutrient thresholds are all unknown. Instead of protective criteria, algal blooms and other biological responses triggered by high nutrient loads in stormwater ponds are often suppressed chemically to maintain resident expectations. Artificial management of the biological response to increased nutrients then eliminates an important nutrient removal pathway within the pond and potentially reduces the required pond nutrient removal efficiency. This study proposed developing a community based stormwater pond nutrient criteria to create a stormwater pond management program effectively meeting both regulatory and community demands. Identifying nutrient concentrations resulting in problematic algal blooms shifts protective standards reserved for natural systems by the NNC to the stormwater pond and identifies targets for upland nutrient management and nutrient runoff reduction. To develop the criteria, nutrient response rel ationships in stormwater ponds were evaluated and compared to the relationships in natural lake systems. Furthermore, variables significantly predicting TP, TN, and chlorophyll a concentrations were identified to isolate targets for reducing stormwater pond nutrient enrichment and creating a sitespecific model of nutrient criteria. Finally , c hlorophyll a

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132 concentrations associated with impairment were identified by residents and related to numeric nutrient thresholds to create the stormwater pond nutrient c riteria. The evaluation of nutrient chlorophyll a relationships in stormwater ponds reve aled statistically significant positive relationships between TP and chlorophyll a concentrations in clear and colored systems and TN and chlorophyll a concentrations in clear and colored systems , but the relationships were much weaker the nutrient response relationships found in natural lakes. When compared to natural lakes, t he chlorophyll a response to TP and TN concentrations was greater in natural lakes than stormw ater ponds and there was a significant difference in the nutrient response interaction and slopes in both clear and colored systems. However, there was no significant difference in the TP chlorophyll a interaction of colored lakes and colored stormwater po nds in the specific West Central Peninsular Region. Numerous management and landscaping variables were evaluated for their significance as predictors of TP, TN and chlorophyll a concentrations in stormwater ponds and sitespecific models were developed. Si gnificant predictor variables influencing water column TP, TN and chlorophyll a concentrations were summarized and categorized (Figure 61) and the presence of grass clippings and littoral shelf coverage of the stormwater pond area were identified as the t wo significan t predictor variables influencing all three concentrations. Fertilizer restrictions, chlorophyll a concentrations and the presence of bank erosion were the three variables found to be significant predictors of nutrient concentrations. The TP, TN and chlorophyll a concentration models associated with the significant predictors were more robust than

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133 the nutrient response models for TN and TP in stormwater ponds and may offer a better alternative for establishing stormwater pond nutrient criteria at a site specific level. A web based survey was then used to identify a community based chlorophyll a threshold of impairment , referred to as “treatment threshold, ” by having participants identify the point of impairment in a series of photos with increasing chlorophyll a water column concentrations. Each p articipant was given one of four survey based treatments evaluating the impact of prequestion educational information and image presentation on preferred treatment threshold. Mean thresholds of i mpairment from the four different treatments were greater than the NNC of 20 gL1 and ranged from 21 to 2 6 gL1, but only three of the treatments were significantly greater than the NNC. Education was found to have no significant impact on treatment threshold, but inclusion of a visual focal point in the images did have a significantly negative impact on the identified threshold. Several additional questions were included in the survey to identify significant predictors of preferred chlorophyll a treat ment thresholds in stormwater ponds. I ncreased frequency of stormwater pond use for different recreational activities had a positive correlation with identified thresholds of impairment. Additionally, some forms of prior knowledge of stormwater pond functi on had a significant effect on the identified treatment threshold . P articipants who identified algae function in stormwater ponds as a nutrient removal pathway had a significantly greater treatment threshold than respondents who identified other algal roles and i ndividuals who received stormwater pond educational information from the real estate company prior to purchasing or renting their home had a significantly higher mean treatment threshold than those who were not provided with information from the real estate company . Finally, a ge, presence

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134 of children in the household, sex and seasonality of residence were identified as demographic categories with significant differences in treatment thresholds amongst groups. Finally, p otential community based stormw ater pond nitrogen and phosphorus criteria were then identified for clear and colored stormwater ponds based on the established nutrient response relationships and survey identified thresholds of impairment. The TN and TP concentration thresholds were higher than those identified for natural Florida lakes, with exception of the NNC established for TP in colored lakes of the WCPR region which was comparable to the colored stormwater pond TP criteria. Additionally, a lgal nitrogen and phosphorus assimilation v alues were estimated and the potential algal nutrient removal associated with each treatment threshold was calculated to reveal the potential environmental impact of varying stormwater nutrient criteria. Results indicated that managing ponds at the community identified chlorophyll a concentration threshold of 20 g L1 instead of the current concentrations of 5 and 10 g L1 would increase the potential TP and TN removal from stormwater ponds in clear and colored stormwater ponds significantly. In co nclusion, the integration of a community based stormwater pond nutrient management program would facilitate the objectives of both regulatory and social requirements . As demonstrated in this study, establishing a community based chlorophyll a treatment thr eshold and the associated protective nutrient concentration clearly defines the management and intervention criteria necessary to maintain the desired aesthetic and recreational use of stormwater ponds. Identifying a specific protective nutrient concentrat ion will identify specific landscape management targets

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135 and promote more efficient nutrient management in contributing, upland systems. Protecting the community identified designated use of a stormwater pond through improved nutrient management shifts nutr ient removal requirement s upstream from stormwater ponds and inserts another protective standard between the natural environment and human development. Thus, protecting stormwater ponds as aesthetic and recreational commodities will inherently protect down stream natural waters and satisfy the regulatory requirements of these built systems while maintaining social expectations . Future Research Implications Nutrient response relationships in stormwater ponds and the quantitative implications of user preferences and management on stormwater pond nutrient removal performance had not been studied in great detail prior to this investigation. Each chapter of this study revealed important and pertinent results that could be applied to current management strategies to improve stormwater pond management, however, numerous additional opportunities for research arose with each finding. The nutrient response relationships identified in Chapter 2 were found to be significantly different than nutrient response relationships in natural lake systems, but the relationship between TN/TP and chlorophyll a concentrations were much weaker in stormwater pond systems. Current stormwater pond management strategies may contribute to the weaker relationship since stormwater pond syst ems are heavily managed for aesthetics, and algae concentrations are treated with various chemic al compounds. Additionally, the nutrient response relationships within the stormwater ponds were not significantly different than the nutrient response relationships in natural lakes located in this region which may indicate the influence of naturally occurring

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136 phosphorus deposits. Therefore, the dynamics of nutrient interactions and both internal and external influences of nutrient response relationships warrant further investigation to determine why nutrient chlorophyll a response relationships in stormwater ponds differ from that of natural systems. Chapter 3 identified significant management variables influencing the nutrient response relationships in stormwater ponds and developed models for TN, TP and chlorophyll a for clear and colored stormwater ponds. These models should be further validated in the same community as well as other regional and statewide stormwater ponds. Additionally, independent management variables influencing nutrient and algal concentrations should be further tested to better quantif y their impact on nutrient concentrations in stormwater ponds. Validating and improving the understanding of the impact of various management decisions has great implications in BMP recommendation and homeowner adoption. Chapter 4 identified resident preferred chlorophyll a management thresholds and provided usable evidence to support management decisions. Although prequestion education had no effect on preferred chlorophyll a concentration, another survey item demonstrated the influence of algae function knowledge on preferred chlorophyll a values. There should be a further investigation into effective education regarding the role of algae in stormwater ponds and the best manner of information delivery. Additionally, the presence of a focal point (submerged aquatic vegetation) in images presented regarding water column algae concentration did seem to have an impact on desired chlorophyll a concentrations. Additional studies should focus on the impact of other focal points, both submerged and emergent, on water column algae preference.

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137 Finally, water column algae concentration is not the only natural response variable managed in stormwater ponds so similar studies focusing on identifying thresholds for filamentous algae, submerged aquatic vegetation, emergent vegetation, water color, shoreline plantings, etc., should be conducted. Lastly, in Chapter 5, the community based chlorophyll a threshold and nutrient response relationships were used to set the stormwater pond nutrient management values for clear and c olored stormwater ponds and the estimated algae assimilated nutrients were used to predict the impact of increasing management thresholds on potential nutrient removal. Additional studies should be conducted to identify the actual nutrient assimilation by the water column algae, algae settling rates, sediment stability, and overall short term and long term retention percentage of nutrients assimilated by algae within stormwater ponds.

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138 Figure 61. Variables identified as significant predictors of phosp horus, nitrogen and chlorophyll a concentrations in stormwater ponds. Arrows indicate positive, negative or both positive and negative variable coefficients

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139 APPENDIX A COMMUNITY BASED STORMWATER POND MANAGEMENT SURVEY

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180 BIOGRAPHICAL SKETCH Charlie Nealis grew up on a frozen tundra in a house constructed entirely of dinosaur bones. He attended grade school with various woodland creatures and was only accepted as one when he defeated a oneeyed grizzly bear named Gerald the Terrible in hand to paw combat. After being crowned king of the wilderness, Charlie earned his B.S. in f ood and r esource e conomics at the Univers ity of Florida with a minor in a gronomy. Following his bachelor ’ s, Charlie earned his M.S. in agricultural education and c ommunication from the University of Florida. After working as a research assistant in communi ty based social marketing of environmentally friendly landscaping practices at the University of Florida and a biology teacher at Deltona High School, Charlie returned to the University of Florida as a Water Institute Graduat e Fellow and earned his PhD in soil and water s cience.