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Evaluating dissolved oxygen regimes along a gradient of human disturbance for lotic systems in west-central Florida

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Title:
Evaluating dissolved oxygen regimes along a gradient of human disturbance for lotic systems in west-central Florida
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Book
Language:
English
Creator:
Hammond, Daniel G
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University of South Florida
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Tampa, Fla
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Subjects / Keywords:
LDI
Nutrients
Diel variation
TMDL
SCI
Dissertations, Academic -- Geography -- Masters -- USF   ( lcsh )
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non-fiction   ( marcgt )

Notes

Abstract:
ABSTRACT: Land uses dominated by human activity can have a significant effect on ecological processes. In Florida, oxygen depletion is the most common impairment in lake, stream, and coastal water bodies. The continual growth and development in Florida, along with a conversion to more human intense land uses warrants study and discussion on impacts to dissolved oxygen regimes along a gradient of human disturbance. This research study is designed to identify observable trends in dissolved oxygen regimes along a gradient of increasing human intensity. Twenty-six stations in the Tampa Bay area were selected to represent lotic systems in west-central Florida. Data was collected quarterly, during four-day deployments, using a deployable data sonde. Grab samples for nutrients and chlorophyll-a provided antecedent data to explain observed trends. Physical components of streams, such as channelization were also taken into account. Biological integrity of streams was assessed to identify if altered dissolved oxygen regimes as a result of human land use significantly affect the health of the systems. Analysis included the use of Spearman rank order correlations to identify patterns. Dissolved oxygen regimes were correlated with the Landscape Development Intensity Index (LDI). Nutrients, primary productivity, and physical alteration to the streambed play a significant role in understanding how land use affects dissolved oxygen regimes. Results indicate the intensity of human land use has a significant effect on dissolved oxygen regimes and has significant policy implications for Florida's Total Maximum Daily Load (TMDL) program. Diel variation in oxygen measurements may be a more appropriate indicator of impairment and stream biological integrity.
Thesis:
Thesis (M.S.)--University of South Florida, 2009.
Bibliography:
Includes bibliographical references.
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Mode of access: World Wide Web.
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System requirements: World Wide Web browser and PDF reader.
Statement of Responsibility:
by Daniel G. Hammond.
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Title from PDF of title page.
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Document formatted into pages; contains 101 pages.

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oclc - 557252230
usfldc doi - E14-SFE0003007
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ABSTRACT: Land uses dominated by human activity can have a significant effect on ecological processes. In Florida, oxygen depletion is the most common impairment in lake, stream, and coastal water bodies. The continual growth and development in Florida, along with a conversion to more human intense land uses warrants study and discussion on impacts to dissolved oxygen regimes along a gradient of human disturbance. This research study is designed to identify observable trends in dissolved oxygen regimes along a gradient of increasing human intensity. Twenty-six stations in the Tampa Bay area were selected to represent lotic systems in west-central Florida. Data was collected quarterly, during four-day deployments, using a deployable data sonde. Grab samples for nutrients and chlorophyll-a provided antecedent data to explain observed trends. Physical components of streams, such as channelization were also taken into account. Biological integrity of streams was assessed to identify if altered dissolved oxygen regimes as a result of human land use significantly affect the health of the systems. Analysis included the use of Spearman rank order correlations to identify patterns. Dissolved oxygen regimes were correlated with the Landscape Development Intensity Index (LDI). Nutrients, primary productivity, and physical alteration to the streambed play a significant role in understanding how land use affects dissolved oxygen regimes. Results indicate the intensity of human land use has a significant effect on dissolved oxygen regimes and has significant policy implications for Florida's Total Maximum Daily Load (TMDL) program. Diel variation in oxygen measurements may be a more appropriate indicator of impairment and stream biological integrity.
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Evaluating Dissolved Oxygen Regimes Along a Gradient of Human Disturbance for Lotic Systems in West-Central Florida by Daniel G. Hammond A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science Department of Geography College of Arts and Sciences University of South Florida Major Professor: Graham Tobin, Ph.D. Philip Reeder, Ph.D. Kamal Alsharif, Ph.D. Date of Approval: July 17, 2009 Keywords: LDI, nutrients, diel variation, TMDL, SCI Copyright 2009, Daniel G. Hammond

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ACKNOWLEDGEMENTS I would like to thank Dr. Graham Tobin for taking me on as a graduate student and providing input and directi on to make this research possi ble. I would also like to thank Dr. Philip Reeder and Dr. Kamal Alsharif for their support, comments, and ideas during this process. Thank you to Dr. D ouglas Durbin and Ms. Kristan Robbins of ENTRIX Inc. (fka Biological Research Associates) for providing ideas, comments, statistical support, and the flex ibility necessary to complete this project. In addition, I would like to thank Dr. Gary Payne of th e Florida Department of Environmental Protection for allowing me to use data for this research effort. Fi nally, I would like to thank my wife, Kimberly, for her unyielding support and motivation without which this project would never have been completed.

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i TABLE OF CONTENTS LIST OF TABLES..............................................................................................................ii LIST OF FIGURES...........................................................................................................iii ABSTRACT....................................................................................................................... iv INTRODUCTION..............................................................................................................6 Research Design......................................................................................................8 LITERATURE REVIEW.................................................................................................13 MATERIALS AND METHODS......................................................................................18 Site Selection........................................................................................................18 Landscape Development Inte nsity Index (LDI)...................................................21 Dissolved Oxygen, Nutrient, and Chlorophylla Data Acquisition......................23 Stream Condition Index (SCI)..............................................................................26 Data Analyses.......................................................................................................29 DESCRIPTIVE RESULTS...............................................................................................30 Landscape Development Inte nsity Index (LDI)...................................................32 Dissolved Oxygen.................................................................................................33 Nutrients and Chlorophylla .................................................................................37 Stream Condition Index (SCI)..............................................................................39 ANALYSIS AND DISCUSSION.....................................................................................41 Dissolved Oxygen, Nutrients, and Chlorophylla .................................................41 The Role of Stream Morphology..........................................................................50 Biological Integrity of Streams.............................................................................58 POLICY IMPLICATIONS...............................................................................................67 CONCLUSIONS...............................................................................................................74 LITERATURE CITED.....................................................................................................82 BIBLIOGRAPHY.............................................................................................................88 APPENDIX A: Landscape Development Intensity Index Raw Data...............................90

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ii LIST OF TABLES Table 1. Station names and loca tions, west-central Florida.........................................20 Table 2. Equations for calculating SCI metrics for peninsular Florida (range from zero to ten).............................................................................................28 Table 3. Aquatic life use categories for SCI scores, peninsular Florida......................29 Table 4. Quarterly data collection pe riods, west-central Florida, 2005 – 2006...........31 Table 5. Landscape Development Intens ity Index scores, calculated from 2005 GIS land use coverages for west-central Florida...........................................32 Table 6. Overall quarterl y range and mean dissolved oxygen concentrations, west-central Florida, 2005 – 2006.................................................................34 Table 7. Mean dissolved oxygen saturati on percent, mean oxygen deficit, and percentage of dissolved oxygen valu es below Florida’s water quality standard (5.0 mg/L), west -central Florida, 2005 – 2006................................36 Table 8. Mean and range values for nutrients and chlorophylla west-central Florida, 2005 – 2006......................................................................................38 Table 9. Stream Condition Index scores and aquatic life use categories, westcentral Florida, 2005 – 2006..........................................................................40 Table 10. Spearman correlations for dissolved oxygen, LDI, nutrients, and chlorophylla concentrations, west-central Florida, 2005 – 2006.................41 Table 11. Breakdown of LDI scores fo r channelized and non-channelized streams, west-central Florida, 2005 – 2006...................................................52 Table 12. Spearman rank order correl ations for dissolved oxygen, LDI, nutrients, and chlorophylla concentrations in non-channelized and channelized streams, westcentral Florida, 2005 – 2006...............................54 Table 13. Overall, channelized and non-channelized Spearman rank order correlations for dissolved oxygen, LDI, and biological integrity, west-central Florida, 2005 – 2006.................................................................60

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iii LIST OF FIGURES Figure 1. Basic flow diagram indicati ng general knowledge on how intensity of human land uses affect stream ecosystems....................................................10 Figure 2. Monitoring station locations..........................................................................19 Figure 3. Typical sonde deployment st ructure and positioning in stream.....................24 Figure 4. Mean dissolved oxygen range (DOR) for each deployment and LDI score over all quarters....................................................................................43 Figure 5. Mean dissolved oxygen (DOM) values for each deployment and LDI score over all quarters....................................................................................45 Figure 6. Mean dissolved oxygen (DOM) and nitrate+nitrite values for each deployment over all quarters..........................................................................48 Figure 7. Mean dissolved oxygen concentrations (DOM) and LDI scores for non-channelized and channelized st reams over all quarters in westcentral Florida................................................................................................53 Figure 8. LDI and overall SCI scores cal culated from summer and winter data collection efforts............................................................................................62 Figure 9. Mean dissolved oxygen (DOM) and SCI scores calculated from summer and winter data collection efforts.....................................................63 Figure 10. Dissolved oxygen deficit (DOD) calculated at the minimum oxygen concentration for each day of the 4-day deployment, during summer and winter data collection efforts...................................................................65 Figure 11. Percent of dissolved oxygen va lues collected from all stations, over all quarters observed above the 5.0 mg /L state water quality standard by hour of the day..........................................................................................71 Figure 12. Percent of dissolved oxygen values collected from the reference stations, over all quarters observe d above the 5.0 mg/L state water quality standard by hour of the day................................................................73

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iv EVALUATING DISSOLVED OXYGEN REGIMES ALONG A GRADIENT OF HUMAN DISTURBANCE FOR LOTIC SYSTEMS IN WEST-CENTRAL FLORIDA Daniel G. Hammond ABSTRACT Land uses dominated by human activity can have a significant effect on ecological processes. In Florida, oxygen de pletion is the most common impairment in lake, stream, and coastal water bodies. Th e continual growth and development in Florida, along with a conversion to more human intense land uses warrants study and discussion on impacts to dissolved oxygen regimes along a gradient of human disturbance. This research study is designe d to identify observable trends in dissolved oxygen regimes along a gradient of increasing human intensity. Twenty-six stations in the Tampa Bay area were selected to represent lotic systems in west-central Florida. Data was collected quarterly, during four-day deployments, using a deployable data sonde. Grab samples for nutrients and chlorophylla provided antecedent data to explain observed trends. Physical components of streams, such as channelization were also taken into account. Biological integrity of streams was assessed to identify if altered dissolved oxyge n regimes as a result of human land use significantly affect the health of the system s. Analysis included the use of Spearman rank order correlations to identify patterns.

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v Dissolved oxygen regimes were correlated with the Landscape Development Intensity Index (LDI). Nutrients, primar y productivity, and physical alteration to the streambed play a significant role in understa nding how land use affects dissolved oxygen regimes. Results indicate the intensity of human land use has a significant effect on dissolved oxygen regimes and has significant policy implications for Florida’s Total Maximum Daily Load (TMDL) program. Diel variation in oxygen measurements may be a more appropriate indicator of impairme nt and stream biol ogical integrity.

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6 INTRODUCTION Land uses dominated by human activity ar e known to have significant effects on natural communities and ecological processe s within those communities (Brown and Vivas 2005). This relationship has been well documented in the lite rature (Brown and Vivas 2005, Allan et al. 1997, Beaulac & R eckhow 1982, Crosbie & Chow-Fraser 1999, Tsegaye et al. 2006, Ehrenfeld 1983, Richards et al. 1996, and Roth et al. 1996, among others). Similar results are presented from studies conducted in a variety of landscapes showing degradation in ecological community structure with intense human dominated land uses. In the United States, non-point source r unoff from intense human land use is the main source of lake, stream, and coastal water degradation (Tsegaye et al. 2006, Carpenter et al. 1998, USEPA 1996 & 2001). According to the U.S. Environmental Protection Agency (1996 & 2001) approximate ly 35 percent of ri ver reaches in the United States violate water quality standards as a result of tempor al land use/land cover changes. In Florida, this same pattern is il lustrated as a result of continuing urban sprawl and intense agriculture activities that increase the human influence on Florida’s natural communities. Water resources in Florida are diverse, supporting a wide array of plant and animal habitats as well as human uses such as food crops, industry, tourism, and recreation (FDEP 2008).

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7 The Florida Department of Environmenta l Protection (FDEP) is charged with assessing Florida’s aquatic res ources to determine which wate rbodies are impaired and in need of restoration. Accordi ng to the FDEP (2008) Integrat ed Water Quality Assessment for Florida, there are currently 931 river and st ream segments listed as impaired for some constituent throughout Florida. The mo st common impairment observed is oxygen depletion (248 waterbody segments), totali ng over 2,000 miles of impaired rivers and streams out of the approximate 20,000 mile s accessed (FDEP 2008). Dissolved oxygen (DO) is the main focus of this research proj ect as it is one of the main parameters of concern in Florida and is wide ly recognized as a ge neral indicator of aquatic health. Adequate dissolved oxygen concentrations are an essential part of any healthy aquatic system. Many processe s can affect the amount of DO in a system at any given time. For example, respiration, metabolism, re-aeration potential, sunlight, and nutrient loading among others can cause significant fl uctuations in DO concentrations on a daily or even hourly basis. Many studies have described links between oxygen depletion and anthropogenic impacts such as urbanization (Walsh et al. 2005, Wang et al. 2003, Paul and Meyer 2001, Meyer et al. 2005). Oxygen depletion in aquatic systems has been linked to increased nutrient loading from agriculture and urban stormwater runoff, impervious land cover, and pollution (B oeder & Chang 2008, MacPerson et al 2007, Mallin et al. 2006, and NRC 2000). It is important to understand the eff ect human dominated land uses have on dissolved oxygen regimes in aquatic communitie s, especially with the abundance of river reaches impaired for oxygen depletion in Florida and the knowledge that adequate oxygen concentrations are esse ntial for healthy aquatic systems and normal ecological

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8 functions. This project was initiated to identify correlations between DO regimes in lotic (flowing) systems and incr easing intensity of human land uses in the surrounding watershed. Research focuses on lotic system s throughout west-central Florida located in varying landscapes of human disturbance. The purpose is to determine what effect increasing intensity of human land use has on the DO regime of the stream system, and, in turn, what affect the altered system has on the ecological health of the stream. Growth and development in Florida, along with conversion to more human intense land uses warrants study and discussion on impacts to dissolved oxygen regimes along a gradient of human disturbance. This information is critical in und erstanding the human impact on natural communities and assisting environmental managers and urban planners in developing strategies to mitigate those impacts. Research Design This study design was based around the gene ral idea that increasing intensity of human land uses has an effect on the ecological processes of natural communities. Furthermore, adverse impacts to stream ecosystems as a result of urbanization and agricultural land uses are well documented (See Literature Review section). Dissolved oxygen is used in this project as a general indicator of the ove rall health of a waterbody. Adequate and sufficient dissolved oxygen regime s are critical to the health of biological communities in aquatic ecosystems as well as necessary for physical processes, including the breakdown of organic material. Figure 1 presents a basic flow diagra m indicating general knowledge on the effects of intense human land uses on dissolv ed oxygen in stream ecosystems. As the

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9 figure indicates, increasing hu man activity in a watershed can alter the chemical and physical properties of a stream system l eading to depletion of oxygen and decreased stream biological integrity. However, the hypothesis tested during this project revolves around the idea that human activity in a wa tershed may have the opposite effect on dissolved oxygen regimes than that depicted in Figure 1. Increasing intensity of human land use in a watershed results in increas ed DO regimes compared to those in less disturbed stream reaches likely as a result of increased nutrient inputs and therefore increased primary production. This hypothesi s is tested by identifying correlations between land use, nutrients, chlorophylla DO, and biological in tegrity of the stream. Antecedent variables are expected to play an important role in understanding the effect of increasing human intensity of la nd use on dissolved oxygen regimes. Nutrient levels are known to affect concentrations of dissolved oxygen in waterbodies and are evaluated as a part of this project. Increased nutrient lo ading to a system can cause increased primary production, resulting in larg e diel variations in DO concentrations. This information is included to help identify correlations between intensity of land use, nutrient inputs, and resulting DO. A critical component of this study is the accurate determination of a gradient of human disturbance. Brown and Vivas ( 2003 & 2005) present a Landscape Development Intensity Index (LDI); a land use based index of potential human disturbance. The index reflects non-renewable energy flow through a sy stem and is based on the principle that ecological processes are impacted by the inte nsity of human dominated land uses (FDEP 2006). This method of evaluating intensity of human land use is broad enough to accurately reflect the wide range of huma n activities that can affect a waterbody.

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10 Figure 1. Basic flow diagram indicating gene ral knowledge on how intensity of human land uses affect stream ecosystems. This diagram is meant to be specif ic to factors affecting disso lved oxygen concentrations and does not include all possible effects to streams.

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11 It is important to note the LDI does not directly account for physical or chemical disturbance to a stream system. However by using non-renewable energy flow, the index reflects a gradient of human activity in a watershed that is expected to result in corresponding physical and chemical alterations to the aquatic system, thereby resulting in altered DO regimes. The LDI is an accep ted and viable index of human disturbance and is used in this project to represent la nd uses of increasing hu man intensity that are likely to have some effect on streams and aquatic ecosystems. Another important aspect of this stud y is to identify correlations between DO regimes and the overall health of the aqua tic ecosystem. In this study, in-stream biological data are used to eval uate the biological integrity of the systems. The Stream Condition Index (SCI) was developed by the FD EP as an index of biological integrity using in-stream and riparian habitat c onditions and stream macroinvertebrate assemblages. Previous studies have linked increasing LDI to decreasing SCI scores (Fore 2004 & 2007). The same framework is employed in this study, and includes DO, to identify stream effects as a result of incr easing human intensity of land use and altered DO regimes. This study identifies correlations between DO regimes and increasing intensity of human land uses. Altered DO regimes as a re sult of increasing human disturbance have significant effects on the overall health of aquatic systems. The research questions addressed during this study are: Is there a significant correlation betw een dissolved oxygen regimes and increasing human disturbance in westcentral Florida streams?

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12 Do nutrient and chlorophylla data correlate to explain shifts in DO as a result of increasing human disturbance? Do altered dissolved oxygen regimes result in corresponding changes in biological integrity of stream systems? This information can be valuable when refi ning Florida’s dissolve d oxygen criterion to determine when DO has been altered by the effects of human land uses, and therefore assist FDEP in focusing its Total Maximum Daily Load (TMDL) development efforts on abating the causes of those alterations.

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13 LITERATURE REVIEW This chapter provides a review of available literature pertaining to the effects of human disturbance on dissolved oxygen and stre am integrity as it relates to the current research presented in this study. Dissolve d oxygen has long been used as a primary indication of water quality sta ndards and is an important i ndicator of general water body health (Wang et al. 2003 and Alexander & Stefan 1983). The presence of adequate concentrations of DO in surface waters is cri tical to the health and survival of aquatic ecosystems (Boeder & Chang 2008). Florida state regulations (62-32.530, F.A.C.) set a dissolved oxygen standard for freshwater sy stems of 5.0 mg/L. The American Fisheries Society (1979) concurs that a minimum value of 5.0 mg/L is necessary to maintain a healthy lotic ecosystem. Understanding the dynamics of DO is complex involving chemical, physical, and biological processes. Re-aeration potential, photosynthesis, and respiration have been identified in the liter ature as three primary factors affecting DO (Odum 1956, Schurr & Ruchti 1977, Parkhill & Gulliver 1999, and Wang et al. 2003). In healthy lotic systems, DO fluctuates near saturation varying w ith temperature and metabolism (Wang et al. 2003). However, oxygen concentrations depressed below saturation can indicate a wa ter quality concern, such as increased nutrient inputs (Wilcock 1986 and Wang et al. 2003). The Na tional Research Counc il (2000), Mallin et al. (2006), and MacPerson et al (2007), among others, report the catalyst for increased oxygen demand is often the result of incr eased nutrient loading. Low oxygen

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14 concentrations have been linked to impai red development, maturation, and increased mortality of fish as well as macroinverteb rate habitat degrada tion (Rounds & Doyle 1997, Cox 2003, and Boeder & Chang 2008). Many studies have been devoted to unde rstanding the dynamics of DO in stream systems (Odum 1956, O’Conner & Di Toro 1970, Kelly et al. 1974, Gulliver & Stephan 1984, Butcher & Covington 1995, Chaudhury et al. 1998, and Wang et al. 2003). Some of these studies have been based on models ranging from simple (Chapra & Di Toro 1991) to very complex, requiring a significant nu mber of input parameters (Hornberger & Kelly 1972 and Edwards et al. 1978). Most modeling efforts for DO have evolved from the basic Sag equation pioneered by Street er and Phelps (1925), which has been extensively used as a tool in stream pollution (Berkun & Aras 2007). The Sag curve shows that oxygen demand in a stream is incr eased at the point where some pollutant is introduced and oxygen is replen ished at some point downs tream indicating recovery (Streeter and Phelps 1925). While DO modeling efforts have been used to characterize stream conditions, metabolism, respiration, and photosynthesis, as well as to estimate the effects of pollutant loading, no modeling stud ies have been uncovered that attempt to evaluate DO along a human disturbance gradient. The evaluation of DO in urbanizing landscap es has garnered more attention in recent years. Brilly et al. (2006) describe the complexity in characterizing the impact urbanization has on stream systems. They conclude the heavily modified concrete channel of an urbanized stream had a signi ficant effect on the dissolved oxygen regime with oversaturation due to excessive algae gr owth. Wang et al. (2003) found that streams in an urban landscape had lo wer rates of metabolism than those in an agricultural

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15 landscape. Colangelo (2007) studied DO in the Kissimmee River, Florida showing increased DO concentrations in the post-rest oration period compared to pre-restoration, which included a series of impounded reservoirs and water control st ructures. Boeder & Chang (2008) shows that urban streams and associated land cover changes affect the volume and timing of runoff, causing water qua lity impacts that can lead to low DO concentrations. As human populations congregate in urba n areas, ecological studies on the effects of urbanization on stream ecosystems are incr easing. Meyer et al. (2005) and Walsh et al. (2005) describe an “urban stream syndrom e” that documents the ways in which urban streams are ecologically degraded. Paul a nd Meyer (2001) state ur banization is second only to agriculture as the majo r cause of stream impairment. Walsh et al. (2005) provide a thorough review of current literature pert aining to the urban stream syndrome and indicate directions for future research to al leviate its effects. Symptoms of the syndrome include a flashier hydrograph, elevated concentrations of nutrients and contaminants, altered channel morphology and stability, and reduced biotic richness with increased dominance of tolerant species (Paul and Meyer 2001, Meyer et al. 2005, Walsh et al. 2005). Reduced baseflow from an increase in impervious area is described as another symptom, usually compounding water chemistr y problems, such as increasing diel variation in dissolved oxygen (Walsh et al. 2005 ). In addition, stormwater impacts have been identified as the catalys t for correlations between st ream condition and catchment imperviousness (Walsh et al. 2005, Paul and Meyer 2001). The LDI has been accepted as a viable index of human disturbance and is included as a metric calculated for the human disturbance gradient (HDG) (Fore et al.

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16 2007). The HDG calculates disturbance based on five metrics including water quality, energy flow (LDI), and stream macroinvertebra te biologic integrity (Fore et al. 2007). The HDG uses ammonia to summarize water qual ity as it may be a general indicator of urbanization and agriculture (Fore et al. 2007). This study uses dissolved oxygen to summarize water quality as it is an indicator of general aquati c health and is affected by measures of disturbance used in other metrics, such as nutrients. Mack (2006) states that the LDI uses quantified land use percentages and therefore has many advantages over more quali tative human disturbance gradients. Mack (2006) showed the LDI was positively correlat ed with a human disturbance gradient (Ohio Rapid Assessment Method for Wetlands) and an Index of Biotic Integrity (IBI) for a large wetland data set in Ohio. However, according to Novotny (2005), an acceptable IBI should not rely on a single stressor such as percent imperviousness because it may not represent a true cause-effect proximate re lationship. Percent im pervious surface has been shown to be a relatively good indicator of surface water pollution in watersheds, although this correlation breaks down in agri cultural watersheds where imperviousness may be relatively unimportant (Brown and Vi vas 2005). The LDI, then, is a continuous index and differs from other measures of land use intensity because it scales the intensity of activity based on non-renewable energy use, a characteristic common to all human dominated land uses (Brown and Vivas 2005). The Landscape Development Intensity Index has also been shown to be an effective predictor of stre am macroinvertebrate biologi cal integrity (FDEP 2006). A strong correlation has been demonstrated between the LDI and the Stream Condition Index (SCI) by Fore (2004). In this study, the SCI is used to evaluate biologic integrity

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17 of the systems and is correlated with the LDI scores to determine if the same pattern observed by Fore (2004) is observed in the lotic systems used here. Literature has shown shifts in disso lved oxygen regimes to have significant effects on the biological integr ity of stream systems. Availability of oxygen has been recognized as a factor in the compositi on of freshwater communities affecting distribution of many species (Hynes 1960, Giller and Malmqvist 1998, Dodds 2002, and Connolly et al. 2004). Hynes (1960), Pearson and Penridge (1987) and Connolly et al. (2004) show that anthropogenic impacts can cause decreased oxygen conditions resulting in changes to community structure and in ma ny cases a loss of dive rsity. Walton et al (2007) also show that urban land use has a ne gative association with biological integrity of streams. Jacobsen (2008) concluded that oxygen saturation was the best predictor of stream macroinvertebrate richness. Ava ilable literature has shown dissolved oxygen concentration and saturation to be significantl y linked to the biological integrity of stream macroinvertebrate assemblages. This study builds on the current base of knowledge by attempting to link in-stream effects of alte red DO regimes along a gradient of human disturbance. The goal of this study is to build on the current base of knowledge by using empirical data to identify direct correl ations between dissolved oxygen and rates of human disturbance. This study includes mo re data points over a longer period of time then previous studies and includes a measure of stream biological integrity to further identify the potential impacts of altered dissolved oxygen regimes.

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18 MATERIALS AND METHODS This chapter describes the methods used to evaluate dissolved oxygen regimes against a gradient of human disturbance in west-central Florida st reams. The methods used to identify rates of disturbance and s ubsequent biological in tegrity of the subject streams is also provided. Site Selection This study focuses on west-central Florid a and specifically the Tampa Bay area. The FDEP has selected approximately 350 water bodies, including streams, rivers, canals, lakes, and estuaries, throughout Florid a for inclusion in a statewide water quality survey to collect data on dissolved oxygen a nd nutrient concentrations for the purpose of revising state water quality sta ndards. Twenty-six waterbodies from the statewide dataset represent the lotic systems of the Tampa Bay area and west-central Florida located throughout Hillsborough, Pinellas, Manatee, Pol k, and Pasco counties (Figure 2). These 26 stations make up the dataset used for this study and include all the lotic systems that were included in the statewide data set for west-central Florida. These lotic systems vary in size from low velocity streams to large rivers. Monitoring stations are located along all of the major Tampa Bay tributaries, as well as many smaller tributaries feeding the larger syst ems. Station names, IDs, and coordinates are presented in Table 1. The dataset incl udes inland and coastal streams and provides a

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19 Figure 2. Monitoring Station Locations.

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20 good representation of the divers ity of lotic systems throughout west-central Florida and the Tampa Bay area. The stations are located in varying landscapes ranging from rural to agricultural to urban settings. Table 1. Station names and loca tions, west-central Florida. Station ID Station Name Latitude Longitude HIL-1 Mango Creek 27.97777472 -82.3463173 HIL-2 Brushy Creek 28.06589772 -82.55529783 HIL-3 Sweetwater Creek 28.04307258 -82.51181536 HIL-4 Sweetwater Creek 28.00033 -82.56456 HIL-5 Hillsborough River 28.15111311 -82.22626586 HIL-6 Hollomans Branch 28.09380971 -82.24892382 HIL-7 Delaney Creek 27.92374602 -82.37205405 HIL-8 Delaney Creek 27.92948 -82.31095 HIL-9 Fishhawk Creek 27.82192873 -82.20348711 HIL-10 Alafia River 27.79151012 -82.20949805 HIL-11 Little Manatee Rive r 27.6630995 82.30080073 MAN-1 Manatee River 27.59203278 -82.08192905 MAN-2 Wares Creek 27.468325 -82.570529 MAN-3 Williams Creek 27.455666 -82.485258 PAS-1 Anclote River 28.21324018 -82.67836345 PAS-2 Withlacoochee River South 28.35262888 -82.12632803 PAS-3 Pithlachascottee Rive r 28.32950795 -82.53628406 PAS-4 Pithlachascottee Rive r 28.24018407 -82.67372628 PAS-5 Anclote River 28.21465233 -82.66573936 PIN-1 Surlew Creek 28.04018 -82.74659 PIN-2 Long Branch 27.91507435 -82.72460915 PIN-3 Long Branch 27.91315148 -82.7410334 POL-1 Itchepackesassa Creek 28.04214604 -82.01752026 POL-2 Banana L Mid Stream 27.98848007 -81.92082793 POL-3 Tiger Creek 27.81206389 -81.44429611 POL-4 Livingston Creek 27.70860793 -81.44644802

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21 Landscape Development Intensity Index (LDI) This section presents the method for determining the gradient of human disturbance used in this study. For each st ream reach, the LDI was calculated for an area that includes the station loca tion, a 100 meter buffer on either side of the stream, and 10 km of the upstream drainage basin (zone of calculation). Brown and Vivas (2003 & 2005) and Fore (2004 & 2007) have determined this technique to adequately represent the stream reach and state that increasing bu ffers and upstream distances does not provide more significant results. Land uses and pe rcent area occupied by each land use in the zone of calculation for each station were determined using 2005 Geographic Information System (GIS) land use coverage maps. Land uses were identified using the standard Florida Land Use and Cover Classification Sy stem (FLUCCS). Land uses that fall into the FLUCCS code categories of lakes and reservoirs were not included in the LDI calculation. This was done to prevent skewing the LDI calculation as these land uses do not represent a direct source of anthropogeni c load to the stream (Dr. Gary Payne, personal communication). In addition, the stream itself was not included in the calculation (Dr. Gary Payne, personal communication). As previously described, the LDI is a land use based index of potential human disturbance with values calculated spatially based on coefficients applied to land uses within watersheds, according to Brown and Vivas (2005). Coefficients are quantified using emergy use per unit area per time. Emer gy is energy that has been corrected for different qualities and is expr essed in units of solar emergy joule (sej) (Brown and Vivas 2005). The units for quantifying the intensity of human activity are therefore sej/ha*yr-1

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22 (empower density) (Brown & Vivas 2005 and FDEP 2006). Brown and Vivas (2003 and 2005) collected energy consumption data from billing records and literature sources for non-renewable energy sources such as electricit y, fuels, fertilizers, pesticides, and water (public supply and irrigation) (FDEP, 2006). Since this index was designed to specifically measure human disturbance, only non-renewable energy sources were included in the calculation (Brown a nd Vivas 2003 and 2005, FDEP, 2006). Empower density of natural systems is assigned a value of 0 sej/ha*yr-1. The LDI coefficients are calculated as the natural log of the empower densities on a scale from 1 to 10 (FDEP 2006). Natural lands are given an LDI coeffi cient of 1.0, while an LDI coefficient of 10.0 is associated with high intensity land uses (e.g. central busine ss district or power plant) (Brown and Vivas 2003 & 2005 and FDEP 2006). Using the land use coefficients and the percent area occupied by each land use, the LDI was calculated as follows, de scribed by Brown and Vivas (2003 & 2005): LDItotal = (LDCi %LUi) Where, LDItotal = Landscape Development Intensity Index for the area of influence %LUi = percent of total area of influence in land use i LDCi = landscape development intensity coefficient for land use i In accordance with Brown and Reiss (2006), an LDI break point of less than or equal to 2.0 was used to identify minimally disturbed reference sites and an LDI of greater than 2.0 designates areas with incr easing levels of human disturbance (FDEP 2006).

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23 Dissolved Oxygen, Nutrient, and Chlorophylla Data Acquisition This section describes the field methodol ogies employed for data collection of dissolved oxygen, nutrient, and chlorophylla constituents necessary to complete this study. Dissolved oxygen, nutri ent, and chlorophylla data were collected in each of the 26 lotic systems on a quarterl y basis for one year between March 2005 and January 2006. During each quarter, a YSI 6600 multi-parameter data sonde was deployed in the stream and programmed to record field measurements in 15 minute interval s over a four day (96 hour) period. The sonde recorded temperatur e (C) and dissolved oxygen in mg/L as well as percent saturation. Each quarter the YSI data sondes were deployed in the same location at approximately midstream and mid-depth in str eams and rivers with a total water depth of one meter or less and at midstream and a depth of one-half meter below the water surface in systems with a total water depth of more than one meter (Figure 3). Sondes were deployed with probes facing upstream and encased in PVC tubes with multiple one inch holes drilled in the tube to allow sufficient water flow over the probes. The PVC tubes were painted in camouflage fo r security and provided safety for the YSI from debris floating downstream (Figure 3). Data sondes were properly calibrated and verified according to manufacturer’s and FDEP protocols for temperature (DEP SOP 001/01 FT 1400) (acceptance criteria +/0.2 C) and dissolved oxygen (DEP SOP 001/01 FT 1500) (acceptance criteria +/ 0.3 mg/L) before and after each 96 hour deployment period. Following each deployment, dissolved oxygen data were uploaded from the YSI data sonde using EcoWatch version 3.15.00 (E coWatch) software and entered into a Microsoft Access database.

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24 Figure 3. Typical sonde deployment st ructure and positioning in stream.

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25 For each deployment period at each station th e overall minimum, maximum, and mean dissolved oxygen (DOM) values were calculated. In addition, the minimum and maximum DO values measured each day of th e four day deployment were averaged to obtain average daily minimum and maximum con centrations. The average daily range of DO measurements (DOR) was determined by subtracti ng the average daily maximum from the average daily minimum concentra tions for each quarterly deployment. The mean DO deficit (DOD) concentration was calculated for each station and each quarter using the following formula: DOD = (DOM/DOSAT) – DOM Where, DOD = mean DO deficit in mg/L DOM = mean DO concentration over the four day deployment period DOSAT = mean DO percent saturation ove r the four day deployment period The above formula was designed for this st udy and is only accurate for use in this study. This is because the YSI 6600 data sonde internally compensates for temperature when calculating the percent saturation and the conversion from percent saturation and temperature to a solubility in mg/L is carried out using formulae available in Standard Methods for the Examination of Water and Wastewater (ed. 1989) (YSI 2002). This allows the above calculation to accurately dete rmine the mean dissolved oxygen value, at any given time, if the percent saturation we re 100 percent. Then by subtracting the observed mean oxygen concentration, the m ean oxygen deficit can be derived. In addition to the above calculations, the percent of DO values that exceeded Florida’s Class III fresh water dissolved oxygen standard ( shall not be less than 5.0 mg/L ) in all measurements collected over the four day de ployment period for each quarter was also determined (DO% < 5).

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26 During data sonde retrieval, water qual ity grab samples were collected for nitrate+nitrite, total Kjelda hl nitrogen, and chlorophylla (corrected for phaeophytin) each quarter. Samples were collected at the same depth as the sonde deployment. All samples were properly preserved in the fiel d according to FDEP protocols. Samples collected for chlorophylla analysis were filtered through a GF/C glass fiber filter (DEP SOP BB-29) within 24 hours of collection and immediately frozen with dry ice for transport to the laboratory. All field sampling was conducted accordi ng to the FDEP Standard Operating Protocols (SOP) listed below. All laborat ory analyses were c onducted by a certified laboratory accredited by the National E nvironmental Laboratory Accreditation Conference (NELAC). FC 1000 Cleaning/Decontamination FS 2100 – Surface Water Sampling FD 1000 – Documentation FS 2000 – General Aqueous Sampling FQ 1000 – Field Quality Control FT 1000-1600 – General Field Testing and FS 1000 – General Sampling Measurement Stream Condition Index (SCI) In order to measure and determine the potential effects of human land use on dissolved oxygen regimes, a measure of str eam integrity is included in this study. Methodologies for collecting the stream biologi cal integrity data ar e presented here. Biological assessment data were collected during the second and fourth deployment periods at each site to evaluate seasonal di fferences. At each of the 26 stations, a Stream Habitat Assessment (FDEP-SOP-001/01 Form FD 9000-6) and a Physical/Chemical Characterization Field Sheet (FDEP SOP-001/01 Form FD 90003) were completed. The

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27 habitat assessment is comprised of a variet y of physical criteria that are independently evaluated on a numerical scale, and the component values are summed to provide a quantitative rating for a stream segment that is presumed to be proportional to the quality of the stream for native macroinvertebrates. The Physical/Chemical Characterization also provides for the delineation of various mi crohabitats in the stream into categories to ensure that sampling of such microhabitats is conducted in gene ral proportion to their abundance. Macroinvertebrate sampling was performed according to the Stream Condition Index (SCI) protocol developed by FD EP (FDEP-SOP-001/01 FS 7420) by personnel with training and experience with the SCI w ho have successfully passed FDEP audits for the protocol. The SCI is a standardized macroinvertebrate sampling methodology that accounts for the various microhabitats avai lable (e.g., leaf packs, snags, aquatic vegetation, roots/undercut banks) within a 100 -m segment of stream. Utilizing this methodology, twenty 0.5-m D-frame dip net sweeps were performed within a 100-m segment of the stream. The number and quality of benthic macroinvertebrate microhabitats present during the sampling event determines the number of sweeps performed within each microhabitat type. Macroinvertebrate samples are preserved in the field using 99 percent Isopropyl alcohol. The amount of alcohol used is dependent on the amount of organic material and site water present in the sample necessary to achieve a 90 percent final concentration of alcohol. Consistent with FDEP protocols, each benthic macroinvertebrate sample was sort ed in the laboratory and taxonomically analyzed according to FDEP SOP-001/01 LT 7200. Macroinvertebrate identifications were made to the lowest po ssible taxonomic category.

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28 Data from each invertebrate sample we re used to calculate the various SCI metrics and resulting overall SCI values per the methodology for the Florida Peninsula (Table 2). For each equation in Table 2, “X” equals the number representing the count or percentage listed in the co rresponding row of the left column. For calculated values greater than ten, the score is set to ten; for va lues calculated less than zero, the score is set to zero. Table 2. Equations for calcula ting SCI metrics for peninsular Florida (range from zero to ten). SCI Metric Peninsula Score Total Taxa 10(X-16)/25 Ephemeropteran Taxa 10X/5 Trichopteran Taxa 10X/7 Percent Collector-Filterer Taxa 10(X-1)/39 Long-lived Taxa 10X/4 Clinger Taxa 10X/8 Percent Dominant Taxon 10-(10[(X-10)/44]) Percent Tanytarsini 10[ln(X+1)/3.3] Sensitive Taxa 10X/9 Percent Very Tolerant Taxa 10-(10[ln(X+1)/4.1]) It is important to note that in the fa ll of 2006, FDEP revised the SCI protocol by changing the range of individua l macroinvertebrates required for sample analysis from 100-120 to 140-160, requiring the SC I to be determined as the average of two replicate samples, and updating the aquatic life use cat egories that describe the resulting SCI scores. The data acquisition effort for this study was conducted prior to the FDEP revisions to the protocol. However, the re sulting SCI scores were evaluated using the revised aquatic life use categor ies (Table 3) to employ the most accurate and up to date information for evaluating the biological inte grity of the stream systems in this study.

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29 Every effort was made to conduct the biologi cal monitoring during re trieval of the data sonde. If this was not possible, the mon itoring was conducted with in two weeks after retrieval of the sonde followi ng a successful deployment. Table 3. Aquatic life use categories for SCI scores, peninsular Florida. SCI Category SCI Range Typical Descript ion for Range Category 1 (Exceptional) 71-100 Higher diversity of taxa than for Category 2, particularly for Ephemeroptera and Trichoptera; several more clinger and sensitive taxa than found in Category 2; high proportion for Tanytarsini; few individuals in the dominant taxon; very tolerant individuals make up a very small percentage of the assemblage. Category 2 (Healthy) 35-70 Diverse assemblage with 30 different species found on average; several different taxa each of Ephemeroptera, Trichoptera, and long-lived and, on average, 5 unique clinger and 6 sensitive taxa routinely found; small increase in dominance by a single taxon relative to Category 1; very tolerant taxa represent a small percentage of individuals, but noticeably increased from Category 1. Category 3 (Impaired) 0-34 Notable loss of taxonomic diversity ; Ephemeroptera, Trichoptera, longlived, clinger, and sensitive taxa uncommon or rare; half the number of filterers than expected; assemblage dominated by a tolerant taxon, very tolerant individuals represent a large portion or the individuals collected. Adapted from Fore (2004). Data Analyses Non-parametric Spearman rank order correla tion analyses were used in this study to identify relationships among the dissolved oxygen, nutrient, LDI, and SCI data. Nonparametric statistics were used because the data do not meet the assumptions of parametric analyses (i.e. normal distributio n). Analyses were run using STATISTICA version 7.1 (StatSoft, Inc 2005) software. Da ta was lumped together to provide an overall analysis as well as separated by quart er at each station to determine any seasonal differences.

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30 DESCRIPTIVE RESULTS This chapter presents the results of the raw data collection effort for all variables used in this study. The data collection effort for this project was conducted between March 2005 and January 2006. Tabl e 4 shows station IDs and da tes of data collection. Logistical issues forced the data collecti on to begin approximately 2 months late and resulted in the following quarterly breakdow n; Quarter 1 – March-April, Quarter 2 – May–July, Quarter 3 – August–October, and Quarter 4 – November–January. During Quarter 1 data sonde malfunctions prevented collection of dissolved oxygen data from stations HIL-6 and POL-4. During Quarter 2, deployment of the data sonde at stations HIL-6 and HIL-11 occurred the first week of August, but were still included in the Quarter 2 data set. Also in Quarter 2, a sonde malfunction at HIL-7 midway through deployment resulted in only two days of useable dissolved oxygen data.

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31 Table 4. Quarterly data collection pe riods, west-central Florida, 2005 – 2006. Data Collection Periods Station ID Quarter 1 Quarter 2 Quarter 3 Quarter 4 HIL-1 3/18/05 3/22/05 6/2/05 6/6/05 8/25/05 8/29/05 12/2/05 12/6/05 HIL-2 3/25/05 3/29/05 6/9/05 6/13/05 9/2/05 9/6/05 11/17/05 11/21/05 HIL-3 3/11/05 3/15/05 6/2/05 6/6/05 9/2/05 9/6/05 12/1/05 12/5/05 HIL-4 3/3/05 3/7/05 5/19/05 5/23/05 8/18/05 8/22/05 11/17/05 11/21/05 HIL-5 3/3/05 3/7/05 5/19/05 5/23/05 8/18/05 8/22/05 11/1/05 11/15/05 HIL-6 --8/1/05 8/5/05 10/14/05 10/18/05 12/16/05 12/20/05 HIL-7 3/18/05 3/22/05 5/27/05 5/29/05 9/2/05 9/6/05 12/2/05 12/6/05 HIL-8 3/18/05 3/22/05 5/27/05 5/31/05 9/2/05 9/6/05 12/2/05 12/6/05 HIL-9 3/4/05 3/8/05 5/20/05 5/24/05 9/2/05 9/6/05 11/18/05 11/22/05 HIL-10 3/4/05 3/8/05 5/20/05 5/24/05 9/2/05 9/6/05 11/18/05 11/22/05 HIL-11 4/22/05 4/26/05 8/1/05 8/5/05 9/30/05 10/4/05 1/6/06 1/10/06 MAN-1 4/7/05 4/11/05 6/9/05 6/13/05 9/15/05 9/19/05 1/6/06 1/10/06 MAN-2 3/11/05 3/15/05 5/27/05 5/31/05 9/2/05 9/6/05 1/5/06 1/9/06 MAN-3 3/11/05 3/15/05 5/27/05 5/31/05 9/2/05 9/6/05 1/5/06 1/9/06 PAS-1 4/8/05 4/12/05 6/10/05 6/14/05 9/8/05 9/12/05 12/2/05 12/6/05 PAS-2 3/24/05 3/28/05 6/9/05 6/13/05 8/18/05 8/22/05 11/11/05 11/15/05 PAS-3 4/8/05 4/12/05 6/3/05 6/7/05 9/8/05 9/12/05 12/8/05 12/12/05 PAS-4 4/8/05 4/12/05 6/10/05 6/14/05 9/8/05 9/12/05 12/2/05 12/6/05 PAS-5 4/8/05 4/12/05 6/10/05 6/14/05 9/8/05 9/12/05 12/2/05 12/6/05 PIN-1 3/10/05 3/14/05 5/19/05 5/23/05 8/18/05 8/22/05 11/11/05 11/15/05 PIN-2 3/11/05 3/15/05 5/27/05 5/31/05 8/19/05 8/23/05 11/17/05 11/21/05 PIN-3 3/10/05 3/14/05 5/27/05 5/31/05 8/19/05 8/23/05 11/17/05 11/21/05 POL-1 3/4/05 3/8/05 5/20/05 5/24/05 8/18/05 8/22/05 11/10/05 11/14/05 POL-2 3/4/05 3/8/05 5/20/05 5/24/05 8/19/05 8/23/05 11/10/05 11/14/05 POL-3 4/7/05 4/11/05 7/7/05 7/11/05 9/23/05 9/27/05 12/16/05 12/20/05 POL-4 --7/1/05 7/5/05 9/23/05 9/27/05 12/16/05 12/20/05

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32 Landscape Development Intensity Index (LDI) This section shows the results of the LD I calculation effort conducted for the 26 stations in this study. LDI scores were cal culated using 2005 GIS la nd use coverages and are presented in Table 5. Appendix A show s the raw data for each station used to calculate the index. Table 5. Landscape Development Intensit y Index scores, calculated from 2005 GIS land use coverages for west-central Florida. Station ID Stream Name LDI Score HIL-1 Mango Creek 4.15 HIL-2 Brushy Creek 5.35 HIL-3 Sweetwater Creek 6.72 HIL-4 Sweetwater Creek Tributary 7.22 HIL-5 Hillsborough River 2.59 HIL-6 Hollomans Branch 4.00 HIL-7 Delaney Creek 4.84 HIL-8 Delaney Creek 1.38 HIL-9 Fishhawk Creek 2.91 HIL-10 Alafia River 2.68 HIL-11 Little Manatee River 2.07 MAN-1 Manatee River 1.42 MAN-2 Wares Creek 7.73 MAN-3 Williams Creek 3.46 PAS-1 Anclote River 2.09 PAS-2 Withlacoochee River South 2.05 PAS-3 Pithlachascottee River 1.45 PAS-4 Pithlachascottee River 1.84 PAS-5 Anclote River 1.70 PIN-1 Surlew Creek 7.61 PIN-2 Long Branch 6.83 PIN-3 Long Branch 8.60 POL-1 Itchepackesassa Creek 5.20 POL-2 Banana L Mid Stream 7.18 POL-3 Tiger Creek 1.23 POL-4 Livingston Creek 2.29

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33 The overall LDI scores ranged from 1.23 to 8.60 across the 26 stations. Six stations (HIL-8, MAN-1, PAS-3, PAS-4, PAS-5, and POL-3) have LDI scores less than 2.0 and are reference stations indicative of areas with minimal levels of human disturbance, according to Brown and Reiss (2006) The scores are well distributed along the LDI scale with 13 stations having a LD I score between 2.0 and 6.0, and another seven scores greater than 6.0. The 11 Hillsborough County stations were wi de ranging with LDI scores between 1.38 and 7.22. All of the West-Central Florida co unties included in this study had at least one reference station (LDI < 2.0), with the ex ception of Pinellas C ounty. Pinellas County is the most densely populated county in Fl orida (Pinellas County Government, 2009) and therefore it is not surprising th at LDI scores from stations in this county indicate more intense levels of human activity. Dissolved Oxygen The results of the dissolved oxygen data co llection effort are presented in this section. Table 6 presents the quarterly ra nge and mean dissolved oxygen concentrations (DOM) collected over each deploym ent at all stations. Eight een of the 26 stations had overall mean dissolved oxygen concentrations (mg/L) that fell below Florida’s Class III state water quality standard (5.0 mg/L) during at least one quarter. Twenty-two stations had DO concentrations that exceeded the standard at some time during the deployment during at least one quarter. DO concentrati ons at two stations (PAS-2 and PAS-4) exceeded the state water quality standard in all measurements, during all quarters.

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34 Table 6. Overall quarterly range and mean dissolved oxyg en concentrations, westcentral Florida, 2005 – 2006. Dissolved Oxygen (mg/L) Quarter 1 Quarter 2 Quarter 3 Quarter 4 Station ID DOM (mg/L) Range DOM (mg/L) Range DOM (mg/L) Range DOM (mg/L) Range HIL-1 6.4 5.5 8.0 4.2 3.5 6. 7 3.7 2.9 6.5 7.5 6.0 8.5 HIL-2 6.8 6.3 7.3 6.0 4.4 6. 6 5.8 5.2 6.7 6.6 5.6 8.0 HIL-3 5.5 4.3 7.2 3.7 2.9 5. 1 5.1 3.7 6.4 6.4 5.4 7.6 HIL-4 3.0 1.9 8.6 0.5 -0.1 1.7 0.8 0.2 5.4 2.7 0.4 4.7 HIL-5 7.4 7.0 7.7 6.5 6.3 6. 9 5.8 5.5 6.1 6.4 6.2 6.5 HIL-6 ----5.2 4.9 6.2 6. 3 5.8 7.3 7.6 6.9 8.9 HIL-7 7.3 6.1 9.6 9.2 1.2 17. 1 3.9 2.8 5.8 8.5 5.8 12.1 HIL-8 3.9 2.0 6.4 2.3 0.7 4. 7 1.6 0.9 4.5 5.5 4.2 6.6 HIL-9 8.0 7.1 9.0 6.2 6.0 6. 5 5.9 5.7 6.2 7.3 6.6 8.0 HIL-10 8.5 8.0 9.2 6.9 6.0 8. 2 6.2 5.7 6.9 7.9 7.0 9.1 HIL-11 8.3 7.9 8.7 6.5 6.4 6. 6 7.0 6.9 7.4 9.1 3.1 11.2 MAN-1 2.2 1.5 3.3 1.2 0.5 2. 2 0.6 0.1 2.1 3.6 2.4 5.5 MAN-2 5.8 3.4 9.7 5.8 0.6 12. 9 4.0 1.0 10.0 7.1 4.2 10.8 MAN-3 9.3 7.4 10.9 5.1 3.4 6. 0 6.6 4.9 8.7 8.2 7.3 9.1 PAS-1 4.9 4.6 5.2 5.0 4.6 5. 6 5.4 5.1 6.0 4.8 3.9 5.4 PAS-2 3.2 2.8 3.9 3.1 2.2 4. 7 1.6 1.4 2.1 2.7 2.6 2.9 PAS-3 5.5 5.1 6.0 5.1 4.5 6. 0 3.4 3.0 4.0 5.6 4.7 7.1 PAS-4 4.0 3.7 4.4 4.3 3.7 4. 8 4.0 3.6 4.4 4.2 3.6 4.6 PAS-5 4.8 4.4 5.3 5.1 4.7 5. 6 5.4 5.2 5.8 4.1 3.4 4.6 PIN-1 8.0 7.3 9.1 6.6 6.2 7. 6 6.6 6.0 7.0 7.2 6.8 7.9 PIN-2 4.1 0.1 12.2 1.5 0.1 5. 4 0.7 0.2 2.7 1.0 0.3 3.6 PIN-3 3.5 1.1 6.0 0.8 0.1 4. 1 0.9 0.3 3.8 0.7 0.1 2.9 POL-1 6.7 4.7 8.9 4.2 3.1 5. 8 4.2 2.0 6.8 6.9 5.6 9.1 POL-2 9.2 7.1 11.8 3.6 0.2 10. 1 4.9 1.1 10.5 6.8 3.7 12.3 POL-3 5.2 4.9 5.6 1.9 1.7 2. 8 2.8 2.6 3.0 6.0 5.4 6.8 POL-4 ----2.7 2.4 3.3 3. 5 3.2 4.1 7.2 5.9 9.8 As expected, DO concentrations were ge nerally higher during Quarters 1 and 4 when lower water temperatures allow for more oxygen absorption. During Quarters 1 and 4 the number of stations with mean DO concentrations below the standard was nine and eight, respectively. Quar ters 2 and 3 had 13 and 15 st ations, respectively, with concentrations below the 5.0 mg/L standard.

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35 The mean DO saturation percent (DOSAT), the mean oxygen deficit (DOD), and the percentage of DO values that fell below the water quality standard (DO% < 5) for each quarter are presented in Table 7. The m ean saturation percent ranged from 5.9 to 119.7 percent across all stations and quarters. Saturation percentages above 100 percent indicate supersaturated cond itions, usually resulting from algae blooms at the time of monitoring. Both the minimum and maxi mum saturation percent occurred during Quarter 2. Two stations (POL-2; Quarter 1 a nd HIL-7; Quarter 2) had mean saturation percents above 100 percent likely indicating the presence of an algae bloom at the time of sampling. The mean oxygen deficit ranged from 1.5 to 8.4 mg/L across all stations and quarters. Two stations (POL-2; Quarter 1 and HIL-7; Quarter 2) had negative oxygen deficits and coincide with the super-saturati on conditions at the same stations, during the same sampling events. The mean oxygen defi cit across quarters was very similar ranging from 3.3 mg/L (Quarter 1) to 3.8 mg/L (Qua rter 3), indicating no significant seasonal difference. Also listed in Table 7 is the percentage of DO values that exceeded the state water quality standard during each quarter. Only four stations (HIL-5, HIL-9, HIL-10, and PIN-1) did not exceed the standard in a ny measurements during any quarter, none of which were characterized as reference stations by the LDI scores. The mean percentage of DO values below the standard during Quarters 1 and 4 was 36.1 and 33.5 percent, respectively. Quarters 2 and 3 had a mean of 57.1 and 55.4 percent of values below the standard, respectively. This pattern is expected showing warmer summer temperatures somewhat increase the likelihood dissolve d oxygen may fall below the standard.

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36 Table 7. Mean dissolved oxygen saturation percent, mean oxygen deficit, and percen tage of dissolved oxygen values below Florida’s water quality standard (5.0 mg/L), west-central Florida, 2005 – 2006. Dissolved Oxygen (mg/L) Quarter 1 Quarter 2 Quarter 3 Quarter 4 Station ID DOSAT (%) DOD (mg/L) DO % < 5 (%) DOSAT (%) DOD (mg/L) DO % < 5 (%) DOSAT (%) DOD (mg/L) DO % < 5 (%) DOSAT (%) DOD (mg/L) DO % < 5 (%) HIL-1 69.38 2.84 0.00 51.58 3.97 95.01 48.08 4.04 97.36 76.55 2.29 0.00 HIL-2 79.04 1.79 0.00 74.25 2.07 10.39 73.47 2.09 0.00 74.99 2.21 0.00 HIL-3 59.21 3.80 28.72 45.14 4.46 98.96 66.31 2.59 60.31 64.92 3.46 0.00 HIL-4 30.40 6.93 92.82 5.89 7.62 100.00 10.48 6.79 99.74 29.46 6.37 100.00 HIL-5 79.56 1.90 0.00 77.94 1.84 0.00 71.89 2.27 0.00 72.93 2.38 0.00 HIL-6 ------67.09 2.57 5.87 74.65 2.15 0.00 76.96 2.29 0.00 HIL-7 79.25 1.91 0.00 119.65 -1.51 33.20 50.31 3.90 93.80 87.44 1.23 0.00 HIL-8 42.01 5.32 82.06 29.06 5.49 100.00 20.39 6.20 100.00 56.44 4.26 14.36 HIL-9 81.80 1.79 0.00 74.64 2.12 0.00 73.85 2.10 0.00 80.25 1.78 0.00 HIL-10 89.39 1.01 0.00 84.75 1.23 0.00 78.55 1.69 0.00 88.23 1.05 0.00 HIL-11 90.92 0.83 0.00 82.36 1.39 0.00 86.35 1.11 0.00 86.08 1.48 7.63 MAN-1 25.03 6.47 100.00 14.54 6.77 100.00 7.19 7.21 100.00 34.73 6.77 88.54 MAN-2 65.78 3.02 50.13 76.30 1.82 46.35 52.08 3.66 64.14 72.49 2.68 11.86 MAN-3 97.15 0.27 0.00 61.78 3.18 30.57 80.26 1.61 0.80 79.97 2.06 0.00 PAS-1 55.03 3.97 79.95 61.30 3.17 52.91 65.54 2.82 0.00 50.74 4.63 78.40 PAS-2 36.28 5.65 100.00 37.26 5.20 100.00 20.61 6.22 100.00 30.36 6.30 100.00 PAS-3 60.47 3.59 0.00 60.08 3.37 33.77 41.60 4.79 100.00 57.20 4.22 26.75 PAS-4 45.99 4.76 100.00 51.59 4.00 100.00 48.23 4.26 100.00 45.11 5.13 100.00 PAS-5 54.90 3.97 68.78 62.27 3.09 47.49 66.54 2.74 0.00 43.61 5.25 100.00 PIN-1 87.72 1.13 0.00 81.88 1.47 0.00 85.86 1.08 0.00 84.80 1.30 0.00 PIN-2 46.68 4.73 61.48 19.59 6.21 95.10 9.56 6.69 100.00 11.70 7.69 100.00 PIN-3 36.53 6.13 86.61 9.78 7.36 100.00 11.87 6.75 100.00 7.83 8.39 100.00 POL-1 69.97 2.88 5.46 52.45 3.83 73.74 55.32 3.40 67.01 78.35 1.91 0.00 POL-2 100.07 -0.01 0.00 47.83 3.91 62.27 68.37 2.25 58.18 81.03 1.59 43.23 POL-3 59.50 3.51 10.08 23.96 5.93 100.00 34.65 5.21 100.00 62.24 3.62 0.00 POL-4 ------34.62 5.09 100.00 44.39 4.40 100.00 76.21 2.23 0.00

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37 Nutrients and Chlorophylla In this study nutrient and chlorophylla data are used as antecedent variables, included to help explain the observed rela tionships between dissolved oxygen regimes and LDI scores, representing th e gradient of human disturbance. Table 8 presents the range and mean nutrient and chlorophylla data collected at all stations. Nitrate+Nitrite (N+N) ranged from 0.002 to 1.28 mg/L across all 26 stations with a mean of 0.25 mg/L. Total Kjeldahl nitr ogen (TKN), the sum of organic nitrogen and ammonia, ranged from 0.47 to 1.76 mg/L, with a mean of 1.01 mg/L at all stations. Total nitrogen (sum of nitrate+nitr ite and TKN) at all stations, with the exception of station HIL-5, was dominated by TKN, indicating a predominance of organic nitrogen over other forms. Total nitrogen (TN) ranged from 0.58 to 2.05 mg/L with a mean of 1.30 mg/L at all stations. In the quarterly samples co llected during this assessment, mean total phosphorus (TP) ranged from 0.06 to 0.78 mg/L with a mean of 0.27 mg/L. Mean chlorophylla concentrations (corrected for phaeo phytin) ranged from a low of 0.28 to a high of 19.08 g/L during thus study, with a mean of 2.9 g/L.

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38 Table 8. Mean and range values for nutrients and chlorophylla west-central Florida, 2005 – 2006. Nitrate+Nitrite (mg/L) Total Kjeldahl Nitrogen (mg/L) Total Nitrogen (mg/L) Total Phosphorus (mg/L) Chlorophylla (g/L) Station ID Mean Range Mean Range Mean Range Mean Range Mean Range HIL-1 0.15 0.04 0.33 1.23 0.98 1.46 1.35 1.1 1.77 0.27 0.17 0.37 8.26 0.05 16.0 HIL-2 0.38 0.08 0.57 0.85 0.75 1.02 1.19 0.92 1.38 0.15 0.09 0.21 0.76 0.05 2.0 HIL-3 0.24 0.14 0.34 1.02 0.72 1.35 1.26 0.89 1.49 0.08 0.04 0.13 1.65 1.1 2.7 HIL-4 0.01 0.002 0.02 1.29 0.47 2.14 1.50 1.08 2.14 0.22 0.04 0.37 2.83 0.5 7.5 HIL-5 1.28 0.97 1.5 0.47 0.29 0.76 1.74 1.36 1.93 0.16 0.11 0.23 0.33 0.05 1.1 HIL-6 0.90 0.3 1.23 1.12 0.8 1.44 2.01 1.74 2.34 0.39 0.24 0.64 3.03 1.1 6.9 HIL-7 0.06 0.01 0.1 0.89 0.58 1.22 0.98 0.66 1.26 0.23 0.14 0.36 1.25 0.5 2.1 HIL-8 0.02 0.002 0.03 1.27 0.56 2.64 1.46 0.63 2.67 0.23 0.09 0.55 3.53 1.3 6.4 HIL-9 0.28 0.21 0.36 0.74 0.57 1.04 1.05 0.92 1.25 0.66 0.49 0.8 1.21 0.05 2.1 HIL-10 0.06 0.04 0.07 0.68 0.52 0.84 0.77 0.58 0.91 0.44 0.32 0.61 3.48 0.5 7.5 HIL-11 0.59 0.19 0.95 0.62 0.4 0.82 1.33 1.04 1.71 0.45 0.29 0.57 0.81 0.05 1.6 MAN-1 0.002 0.002 0.002 1.38 1. 15 1.56 1.43 1.38 1.56 0.35 0.22 0.52 1.84 0.05 5.3 MAN-2 0.22 0.17 0.3 0.75 0. 52 1.14 1.01 0.7 1.44 0.22 0.13 0.38 1.73 0.5 4.3 MAN-3 0.50 0.11 1.56 1.24 0. 72 1.79 1.87 0.83 3.35 0.78 0.59 0.94 0.98 0.5 1.2 PAS-1 0.08 0.02 0.13 0.63 0. 22 0.87 0.70 0.31 0.89 0.06 0.05 0.06 0.28 0.05 0.5 PAS-2 0.02 0.002 0.03 1.60 1. 21 1.99 1.71 1.39 1.99 0.09 0.06 0.16 0.91 0.05 2.0 PAS-3 0.02 0.002 0.05 1.48 0. 84 2.27 1.65 1.21 2.27 0.09 0.04 0.13 1.28 0.5 2.1 PAS-4 0.06 0.04 0.08 0.68 0. 58 0.84 0.58 0.04 0.88 0.06 0.05 0.06 0.41 0.05 0.6 PAS-5 0.08 0.02 0.13 0.74 0. 3 0.99 0.80 0.41 1.01 0.07 0.05 0.09 0.31 0.05 1.1 PIN-1 0.56 0.14 1.58 0.76 0.56 0.93 1.41 0.76 2.51 0.49 0.31 0.72 0.68 0.5 1.2 PIN-2 0.05 0.002 0.18 0.78 0. 62 0.87 0.84 0.62 1.02 0.14 0.1 0.21 2.70 0.7 5.3 PIN-3 0.05 0.01 0.12 1.76 0.8 4.32 2.05 0.9 4.33 0.35 0.18 0.82 3.40 1.6 4.8 POL-1 0.45 0.17 0.63 1.20 1.03 1.49 1.69 1.29 2.12 0.46 0.37 0.59 7.75 4.3 10.7 POL-2 0.09 0.02 0.23 1.26 0.92 1.7 1.25 1.0 1.49 0.35 0.23 0.52 19.08 5.0 39.2 POL-3 0.08 0.02 0.16 0.76 0.52 0.94 0.85 0.68 0.96 0.09 0.04 0.16 0.93 0.5 1.1 POL-4 0.21 0.08 0.31 0.99 0.84 1.17 1.20 0.99 1.48 0.12 0.08 0.18 5.95 3.2 8.5

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39 Stream Condition Index (SCI) Macroinvertebrate assemblages are quantified using the Stream Condition Index (SCI) to assess the biological integrity of th e stream reaches in this study. SCI scores were calculated for each stream reach tw ice during the sampling period (2005-2006) and results are presented in Table 9. Macroinve rtebrate samples were collected once during the summer months (Quarter 2) and once dur ing the winter months (Quarter 4). At station PIN-3, only the SCI conducted during Quarter 2 resulted in useable data. During the summer of 2005 SCI scores ra nged from a low of six (POL-1) to a high of 61 (HIL-5). Eighteen of the 26 stations assessed during the summer are categorized as “impaired” according to Fore et al. (2007). The remaining eight stations were categorized as “healthy.” SCI scores calculated during the winter months (Quarter 4) ranged from 11 (POL-1) to 71 (HIL-5) with the high and low scores occurring at the same stations as the summer scores. Fifteen stations fall in the “impaired” category, with another nine categorized as “h ealthy,” and one station rated as “exceptional” (Fore et al. 2007). Twelve of the stations in this study had SCI scores that fell in the “impaired” category during both of the assessments conducted.

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40 Table 9. Stream Condition Index scores and aquatic life use categories, west-central Florida, 2005 – 2006. Stream Condition Index Summer (Quarter 2) Winter (Quarter 4) Station ID Score Aquatic Life Use Category* Score Aquatic Life Use Category* HIL-1 16 impaired 13 impaired HIL-2 28 impaired 35 healthy HIL-3 44 healthy 34 impaired HIL-4 10 impaired 25 impaired HIL-5 61 healthy 71 exceptional HIL-6 41 healthy 34 impaired HIL-7 31 impaired 26 impaired HIL-8 19 impaired 24 impaired HIL-9 47 healthy 52 healthy HIL-10 41 healthy 46 healthy HIL-11 53 healthy 46 healthy MAN-1 19 impaired 35 healthy MAN-2 33 impaired 22 impaired MAN-3 23 impaired 32 impaired PAS-1 30 impaired 40 healthy PAS-2 11 impaired 18 impaired PAS-3 23 impaired 36 healthy PAS-4 50 healthy 44 healthy PAS-5 29 impaired 31 impaired PIN-1 26 impaired 18 impaired PIN-2 12 impaired 14 impaired PIN-3 7 impaired ----POL-1 6 impaired 11 impaired POL-2 11 impaired 29 impaired POL-3 39 healthy 30 impaired POL-4 25 impaired 53 healthy Source (Fore et al. 2007)

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41 ANALYSIS AND DISCUSSION This chapter provides the analyses of th e data collection effort for this study. Relationships between intensity of hum an land use, dissolved oxygen, nutrients, chlorophylla and stream biological in tegrity are discussed. Co rrelation analyses were successful in indentifying these relationships and provide insight in to causative factors affecting dissolved oxygen regimes in the subject streams. Dissolved Oxygen, Nutrients, and Chlorophylla Correlation analysis serves to identify relationships between the variables and better understand how intensity of human land uses affects dissolved oxygen regimes in streams. Table 10 presents the Spearman ra nk order correlation values calculated for LDI, dissolved oxygen, and nutrien t concentrations over the ye ar long study. Significant correlations (p < 0.05) are in bold. Table 10. Spearman correlations for dissolv ed oxygen, LDI, nutrients, and chlorophylla concentrations, west-central Florida, 2005 – 2006. Parameter LDI TKN N+N TN TP Chlorophylla LDI 0.04 0.24 0.09 0.32 0.28 DOM 0.11 -0.33 0.58 -0.01 0.28 -0.15 DOR 0.54 0.24 -0.08 0.08 0.29 0.56 DOD -0.16 0.27 -0.6 -0.03 -0.38 0.09 DO% < 5 -0.14 0.28 -0.6 -0.07 -0.29 0.17 Bold values indicate significant correlations (p < 0.05)

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42 As the table shows, mean DO range wa s the only measure of dissolved oxygen significantly correlated (Spearman r = 0.54, p < 0.001) with the LDI scores when evaluated over all quarters. Diel variation in dissolved oxygen increased with increasing intensity of human land use in the surrounding watershed (Figure 4). This is not surprising as other studies have linked in creased diel varia tion in streams to anthropogenic sources such as increased imperv ious area (Walsh et al. 2005). Catchment imperviousness has been linked to reduced ba seflow and flashier hydrographs leading to increased diel variation in urban settings (Meyer et al. 2005 and Wa lsh et al. 2005). Land uses with higher LDI scores can be expect ed to experience higher amounts of catchment imperviousness as well as greater effect s of point and non-point source runoff. Monitoring stations with LDI scores < 2 (reference streams) showed diel variations generally less than 2.0 mg/L during all qua rters, indicating relatively stable oxygen concentrations throughout the da y and night (see Figure 4). The other measures of dissolved oxygen in this study (mean concentration, mean deficit, and percent of exceedances) did not correlate with the gradient of human disturbance (LDI) when all stations were vi ewed over all quarters. As expected, mean dissolved oxygen values tend to be lower duri ng the warmer months (quarters 2 and 3) at all stations, although viewing the measures of dissolved oxygen on a quarterly basis did not produce any significant result s with respect to LDI scores.

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43 12345678910 LDI Score 0 2 4 6 8 10 12 14 16 DOR (mg/L) Spearman r = 0.54, p < 0.001 Figure 4. Mean dissolved oxygen range (DOR) for each deployment and LDI score over all quarters. Mean dissolved oxygen (DOM) calculated over each four day deployment generally exceeded Florida’s fresh water qual ity standard (5.0 mg/L) at the reference stations in this study (HIL-8, MAN-1, PA S-3, PAS-4, PAS-5, and POL-3) during most quarters (Figure 5). These stations, as dete rmined by the LDI score, are those in areas with the least non-renewable energy consump tion and exhibit natural conditions with little to no impact from human activities (Brown and Vivas 2 005). The majority of the reference streams are dominated by hea vy canopy cover (PAS-3, PAS-4, PAS-5, and POL-3) and reduced sunlight penetration can lead to reduced photosynthesis in the aquatic system causing lower overall dissolv ed oxygen values compared to more open systems (Roy et al. 2005). The data support this claim showing a significant positive

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44 correlation between LDI score and chlorophylla concentrations (see Table 10). Another of the reference stations (MAN-1), has an open canopy, but is located immediately downstream of a large groundwater fed wetland system which serves as the stream’s headwaters. Groundwater wetland systems t ypically have low dissolved oxygen and this most likely explains the low ove rall mean oxygen concentration recorded at this reference station. These data indicate the natural sy stems identified in th is study, through the use of the LDI scores, may be characterized as impacted for dissolved oxygen even though human activity and influence in these catch ments is expected to be very low. Mean dissolved oxygen values calculated from monitoring stations with high LDI scores (LDI scores 6 – 9) also exceeded th e state standard on the majority of occasions (see Figure 5). Land uses repr esented by these LDI scores te nd to indicate high intensity agriculture, medium to high de nsity residential, low intens ity commercial, and industrial (Brown and Vivas 2005). While these stations typically exhibit le ss canopy cover than the reference stations, the overall low oxygen concentratio ns (below the standard) observed during most quarters is likely the re sult of physical alterations to stream channels, such as channelization (described below), in areas of more intense human land use.

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45 12345678910 LDI Score 0 1 2 3 4 5 6 7 8 9 10 DOM (mg/L) Spearman r = 0.11, p > 0.05 Figure 5. Mean dissolved oxygen (DOM) values for each deployment and LDI score over all quarters. Monitoring stations represented by LDI sc ores along the middle of the gradient (LDI scores 2 – 6) generally had higher mean oxygen values during all quarters than the reference or high human intensity stations. The land uses in this category tend to be dominated by agriculture incl uding pasture, citrus and row crops (Brown and Vivas 2005). The stream systems located in agriculture dominated areas tend to have little to no canopy cover and receive direct sunlight allo wing for increased photosynthesis compared to more shaded systems leading to increased overall DO. In addition, these streams are subject to increased gr oundwater inputs from irrigation which may be clearer allowing for less light attenuation.

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46 An evaluation of nutrient concentrations wa s included in this study to determine if nutrients could help explain sh ifts in dissolved oxygen regi mes as a result of increasing human disturbance. As prev iously mentioned, many studies have linked excess nutrients to anthropogenic sources and urban land uses, as well as depletion of oxygen in aquatic systems (Mallin et al 2006, MacPerson et al 2007, National Research Council 2000, Wang et al 2003, and Wilcock 1986). In this st udy the LDI scores were not significantly correlated with TKN (organic nitrogen and a mmonia) or total nitr ogen (see Table 10). Significant positive correlations (p < 0.05) we re observed between LDI and inorganic nitrogen (N+N) (Spearman r = 0.24, p = 0.01) and TP (Spearman r = 0.32, p = 0.001). Although only a weak correlation was observed in this data set, the findings coincide with previous studies showing increased nut rient concentrations in watersheds of increasing intensity of human activity. Measures of dissolved oxygen were significantly correla ted with nutrient concentrations, with the ex ception of total nitrogen (see Table 10); suggesting nutrient concentrations play a significant role in the dissolved oxygen regime of an aquatic system. TKN was significantly correlated with measures of dissolved oxygen when viewing all deployments over al l quarters. TKN was negatively correlated with mean dissolved oxygen and positively correlated with the DO range, oxygen deficit, and the percentage of exceedances. This is not an unexpected finding as increasing organic nitrogen leads to increased demand for oxyge n and therefore reduced DO levels. The increased demand for oxygen can also expl ain the positive corre lations between oxygen deficit and TKN (Spearman r = 0.27, p = 0.006) as well as percentage of exceedances and TKN (Spearman r = 0.28, p = 0.004).

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47 Significant results were obtained by evalua ted inorganic nitrogen with measures of dissolved oxygen. When comparing all deployments over all quarters, inorganic nitrogen showed a strong positive correlati on with mean dissolved oxygen (Spearman r = 0.58, p < 0.001) (Figure 6) and strong negativ e correlations with mean oxygen deficit (Spearman r = -0.60, p < 0.001) and percentage of exceedances (Spearman r = -0.60, p < 0.001). The majority of nitrate+nitrite reported in this study was in th e form of nitrate, indicating nitrification was occurring to br eakdown toxic nitrite into nitrate. The nitrification process requires oxygen and therefore it is not surprising to find increased levels of nitrate when the availability of oxygen is also increased. The strong negative correlation between nitrate+nitrite and oxyge n deficit and percentage of exceedances further indicates the presence of adequate oxyge n allowing for the conversion of nitrite to nitrate. The presence of strong correlation betw een measures of oxygen and inorganic nitrogen does not indicate th e nitrogen is in any way causing increased oxygen, but rather, the availability of oxygen allows for th e breakdown of toxic nitrite into less toxic nitrate.

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48 0.00.20.40.60.81.01.21.41.61.8 Nitrate + Nitrite (mg/L) 0 1 2 3 4 5 6 7 8 9 10 DOM (mg/L) Spearman r = 0.58, p < 0.001 Figure 6. Mean dissolved oxygen (DOM) and nitrate+nitrite values for each deployment over all quarters. Total phosphorus (TP) was correlated with the LDI scores as well as all measures of dissolved oxygen used in this study. The mean dissolved oxygen concentration recorded over each deployment and the mean dissolved oxygen range showed a significant positive correlation with total phosphorus concentrations (Spearman r = 0.28 and 0.29, p = 0.005 and 0.003, respectively). In addition, the mean oxygen deficit and percentage of exceedances showed a significan t negative correlation with TP (Spearman r = -0.38 and -0.29, p = < 0.001 and 0.004, respectively ). The reason for these significant correlations is likely linked to primary production and is supported in the data. Chlorophylla concentrations were significantly correlated with TP concentrations (Spearman r = 0.32, p = 0.01). Phosphorus is ge nerally considered to be the limiting

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49 nutrient for phytoplankton growth in freshw ater systems (Hecky and Kilham 1988 and Mallin et al. 2004). Theref ore it is appropriate to assume that as phosphorus concentrations observed in this study increase, the ability of phytoplankton to bloom also increases. While chlorophylla concentrations were not corr elated with the overall mean oxygen values in this study, chlorophylla showed a significant positive correlation with the mean oxygen range (Spearman r = 0.56, p < 0.001). Photosynthesis during the day and respiration at night by phytoplankton comm unities results in large diel swings in dissolved oxygen. These variations can have a significant effect on the oxygen regime of a stream system and can help to explain the correlation betwee n dissolved oxygen and phosphorus observed in this study. Phosphorus and chlorophylla concentrations were also positively correlated with LDI scores (Spearman r = 0.32 and 0.28, p = 0.001 and 0.005, respectively) indicating a link between the intensity of human land use, phosphorus inputs, and subsequent increase in primary production. This relationship he lps to explain the li nk between the diel variation (DOR) observed and LDI scores. As th e intensity of land use increases phosphorus inputs to stream systems thr ough point and non-point sources such as agriculture and urban runoff also increase, resulting in increased primary production which, in turn, increases the di el range of dissolved oxygen va lues. This relationship in conjunction with the increased catchment imperviousness expected with higher LDI scores, work together to explain the obser ved relationship between LDI, nutrients, and dissolved oxygen.

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50 The Role of Stream Morphology As previously explained, the calcul ation of the LDI score is based on nonrenewable energy flow and does not directly account for physic al alterations to stream systems that may occur as a result of human act ivity in a watershed. In fact, the stream itself is not included in the LD I calculation. Previous studie s have linked altered channel morphology to degradation in water quality including dissolved oxygen (Brilly et al. 2006, Meyer et al. 2005, Paul and Meyer 2001, and Walsh et al. 2005). It is not possible for the LDI calculation to account for stream morphology other than to suggest that higher LDI scores are more likely to occur in places where the stream channel has been altered as a result of increased human activity. In order to account for differences in dissolved oxygen regimes that occur as a result of physical alterations to stream morphology, the dataset presented in this st udy was separated into non-channelized and channelized systems. Each subset of the da ta was then subjected to the same correlation analyses presented above to determine if stream morphology signi ficantly alters the relationship between dissolved oxygen a nd intensity of human land uses. Fifteen of the 26 stations fall into the non-channelized category with at least one station found in each county included in this st udy. Four of the six reference stations (LDI score < 2.0) are non-channelized and only two stations have LDI scores above 5.0 (HIL-2 – 5.35 and PIN-1 – 7.61). Non-channe lized systems tend to fall on the lower end of the LDI scale while the channelized system s tend to fall on the higher end of the scale (Table 11). Eleven of the 26 stations were channelized a nd included two of the reference stations (HIL-8 – 1.38 and MAN-1 – 1.42). MAN-1 is located in Manatee County, FL

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51 and drains a large tract of we tland area with little human activity. Although MAN-1 is a channelized stream at the station location, th e majority of the upstream basin for which the LDI was calculated encompasses wetland ar eas described as freshwater marshes and wet prairies by FLUCCS (see A ppendix A). Station HIL-8 is located along Delany Creek in Hillsborough County, FL and is included as a channelized stream because the system is altered to include a retenti on basin at the station location. However, the headwaters of Delany Creek are located just upstream of the sampling lo cation and therefore the LDI could only be calculated for a short distance of the upstream basin and only included an approximate 96,000+ square meters of area (see Appendix A). In contrast, LDI calculations in stream systems for which the entire 10km of upstream basin can be calculated encompass 2,000,000 square meters. The area of influence for which the LDI was calculated was dominated by shrub and brushland and conifer mixed hardwood. This resulted in a channelized system (HIL-8) with one of the lowest LDI scores in this project. The rest of the channelized str eams had LDI scores ranging from 4.15 (HIL-1) to 8.60 (PIN-3).

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52 Table 11. Breakdown of LDI scores for channe lized and non-channelized streams, westcentral Florida, 2005 – 2006. Non-Channelized Channelized Station ID LDI Score Station ID LDI Score HIL-2 5.35 HIL-1 4.15 HIL-5 2.59 HIL-3 6.72 HIL-6 4.00 HIL-4 7.22 HIL-9 2.91 HIL-7 4.84 HIL-10 2.68 HIL-8 1.38 HIL-11 2.07 MAN-1 1.42 MAN-3 3.46 MAN-2 7.73 PAS-1 2.09 PIN-2 6.83 PAS-2 2.05 PIN-3 8.60 PAS-3 1.45 POL-1 5.20 PAS-4 1.84 POL-2 7.18 PAS-5 1.70 PIN-1 7.61 POL-3 1.23 POL-4 2.29 This exercise illustrates significant diffe rences in the behavior of dissolved oxygen in channelized and non-channelized stre ams. In addition, it provides valuable insight into understanding the relationship between dissolved oxygen and the intensity of human land use. Figure 7 presents the m ean oxygen concentrations and LDI scores separated into channelized and non-channeli zed systems, while Table 12 provides the results of correlation analyses. As Figure 7 indicates, non-channelized streams tend to be concentrated on the lower end of the LDI scal e, representing areas of less intense land use. In contrast, the channelized systems in this study tend to concentrate on the higher end of the LDI scale, indicati ng channelized streams are more likely to be found in areas of higher intensity land use. While this result is not surprising, it is important to note as this relationship plays an important ro le in understanding how dissolved oxygen is affected by increasing intensity of human land use.

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53 12345678910 LDI Score 0 1 2 3 4 5 6 7 8 9 10 DOM (mg/L) Non-Channelized Channelized Spearman rank order correlations: Non-Channelized: r = 0.60, p < 0.001 Channelized: r = -0.15, p > 0.05 Figure 7. Mean dissolved oxygen concentrations (DOM) and LDI scores for nonchannelized and channelized streams over all quarters in west-central Florida.

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54 Table 12. Spearman rank order correlations for di ssolved oxygen, LDI, nutrients, and chlorophylla concentrations in nonchannelized and channelized streams, west-central Florida, 2005 – 2006. LDI TKN N+N TN TP Chlorophylla NonChan Chan NonChan Chan NonChan Chan NonChan Chan NonChan Chan NonChan Chan LDI -0.03 -0.19 0.61 0.16 0.27 -0.12 0.68 -0.07 0.13 0.03 DOM 0.6 -0.15 -0.34 -0.19 0.58 0.57 0.07 -0.04 0.6 -0.07 0.09 0.01 DOR 0.51 0.3 0.12 -0.25 0.24 0.26 0.16 -0.19 0.41 0.03 0.45 0.24 DOD -0.66 0.08 0.26 0.11 -0.53 -0.61 -0.05 -0.03 -0.68 -0.04 -0.1 -0.13 DO% < 5 -0.57 0.06 0.26 0.19 -0.6 -0.57 -0.13 0.01 -0.5 0.13 -0.02 -0.03 Non-Chan Non-Channelized Stream Chan Channelized Stream Bold values indicate significa nt correlations (p < 0.05)

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55 When viewing non-channelized systems, all measures of dissolved oxygen showed strong significant corr elations with LDI scores (T able 12). Mean dissolved oxygen (Figure 7) and mean dissolved oxygen ra nge showed strong positive correlations (Spearman r = 0.6 and 0.51, respectively, p < 0.001), while mean oxygen deficit and percentage of exceedances showed strong negative correlations (Spearman r = -0.66 and 0.57, respectively, p < 0.001). The same relationship was not observed in the channelized streams. As Figure 7 shows, m ean dissolved oxygen was not correlated with LDI scores for the channelized streams. Th e LDI only showed a significant correlation with mean oxygen range (Spearman r = 0.3, p = 0.04), similar to vi ewing all stations together. Two channelized systems (HIL-8 and MAN-1, described a bove) are outliers, with low LDI scores. However, with these two stations removed th e correlation between dissolved oxygen and LDI is no more significa nt than with the out liers included. This indicates a much stronger relationship is ev ident between oxygen and intensity of human land use in streams that have not been physica lly altered. In non-ch annelized systems, as land uses become more intense with huma n activity the overall concentrations of dissolved oxygen increase, fluctuate closer to the saturation level, and fewer exceedances of Florida’s state water quality standard are observed. The same relationship was observed for each quarter and no significan t seasonal differences were identified. The data indicate nutrients play an important role in understanding the relationship between dissolved oxygen a nd LDI score in the non-channelized and channelized systems. Inorganic nitrogen and total phosphorus in the non-channelized systems were positively correlated with LDI scores (Spearman r = 0.61 and 0.68, respectively, p < 0.001). Nutrient data coll ected from channelized streams were not

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56 correlated with LDI score in any case. This likely indicates the relationship between nutrients and intensity of human land use is more evident when the channel of a stream has not been altered. Measures of dissolved oxygen showed significant correlations to nutrient concentrations, especially in the non-channeli zed streams. TKN (organic nitrogen and ammonia) was correlated with mean disso lved oxygen (Spearman r = -0.34, p = 0.01) and oxygen deficit (Spearman r = 0.26, p = 0.048) in the non-channelized systems, but was not correlated in the channe lized streams. Inorganic ni trogen (N+N) showed a strong correlation with most measur es of dissolved oxygen in both the non-channelized and channelized streams (see Table 12). These resu lts are consistent with viewing all stations together. Total phosphorus showed no relationship with measures of dissolved oxygen in the channelized systems, but showed strong co rrelations in the non-channelized streams. Total phosphorus showed a strong positive correlation with mean dissolved oxygen values and mean oxygen range (Spearman r = 0.6 and 0.41, p < 0.001 and p = 0.001, respectively) while exhibiting a strong negative corre lation with mean oxygen deficit and percentage of exceedances (Spearman r = -0.68 and -0.50, p < 0.001, respectively). This relationship between dissolved oxygen and phosphor us concentrations is similar to that observed when viewing all stat ions together, although the co rrelations in non-channelized systems were much stronger. As previously described, phosphorus is typically the limiting nutrient in freshwater systems and is responsible fo r the growth and bloom of phytoplankton and other aquatic plant communities. In the non-channelized systems phosphorus

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57 concentrations were significantly positively correlated with chlorophylla concentrations (Spearman r = 0.30, p = 0.02). As a result, the chlorophylla concentrations show a strong relationship with the diel variation (DOR) in non-channelized streams (Spearman r = 0.45, p < 0.001) from the photosynthetic and respiratory functions of microbial and algal communities. This relationship helps to explain the correlation between the mean oxygen range, phosphorus, and chlorophyll observe d in this study and may also help to explain the correlation between other meas ures of oxygen and phosphorus. Research indicates as algal communities produce and consume oxygen through normal metabolic processes, they typically produce more oxyge n during photosynthesis than they consume during dark respiration resulting in a net increase in oxygen concentration (Platt 1981). An increase in algal community as a result of increased phosphorus inputs to streams could therefore help to explain the re lationship between phosphorus and dissolved oxygen observed. The sestonic chlorophylla data used in this study only partially exhibit this relationship (see Table 12), however studies have indicated sestonic chlorophyll concentrations ma y not be the appropriate method to fully explore these scenarios (Morgan et al. 2006). Morgan et al. (2006) suggest biomass of filamentous algae may be a better indicator of primar y production, and further research should be conducted to determine if this va riable provides more significan t relationships in this data set. Stream morphology has shown to be a significant factor in identifying relationships between dissolved oxygen and human land use intensity. The nonchannelized streams located thr oughout west-central Florida us ed in this project show a significant relationship between dissolved oxygen and the inte nsity of human land use.

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58 Measures of oxygen, with the exception of m ean dissolved oxygen range, seem to show improvement as the intensity of human land us e in the surrounding wa tershed increases. With increasing LDI scores the overall m ean dissolved oxygen value increases and the mean oxygen deficit and percent of exceedance s decreases. Total phosphorus seems to pay an important role in understanding this relationship. Increased primary production as a result of increased phosphorus inputs in la nd uses of more intense human activity seem to account for at least some of the relationship between dissolved oxygen and LDI scores. The same relationship was not apparent in the channelized systems. The physical alteration of channelized streams (such as straight, deep, incised channels) can have significant affects on dissolved oxygen a nd may obscure the re lationship between dissolved oxygen, nutrients, and chlorophylla Other physical factors affecting dissolved oxygen in channelized streams were not included in this study and therefore cannot be fully explored. However, the relatio nships observed here indicate that nutrient inputs as well as physical alteration of the st ream channel are signifi cant factors affecting dissolved oxygen along a gradient of human disturbance. Biological Integrity of Streams The Stream Condition Index (SCI) is an index of biological integrity using instream and riparian habitat conditions and st ream macroinvertebrate assemblages. The SCI was conducted at each station duri ng quarters two and four, allowing for characterization of summer and winter macroinvertebrate asse mblages. Fore (2004) has shown a significant negative co rrelation between th e LDI score and the SCI. In-stream biological integrity is evaluate d against the intensity of hum an land use in this study to

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59 determine if the same relationship observed by Fore (2004) is evident in this data set. The SCI is also evaluated against measures of dissolved oxygen to identify if altered oxygen regimes, as a response to intense human land use, have an effect on the biological integrity of stream systems in west-central Florida. Table 13 presents the Spearman rank or der correlations obs erved between the LDI, SCI, and measures of dissolved oxygen in this study. Stations were evaluated overall, as well as separated into channelized and non-channe lized streams. In addition to using the overall SCI score, four of the me trics used to calculate the SCI (total taxa, sensitive taxa, percent very tolerant ta xa, and percent dominant taxon) were also evaluated against the LDI score and dissolv ed oxygen. These metrics were chosen because they are expected to be more sensi tive to effects of changes in dissolved oxygen in response to intense human land use than other metrics.

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60 Table 13. Overall, channelized and non-cha nnelized Spearman rank order correlations for dissolved oxygen, LDI, and biological integrity, west-central Florida, 2005 – 2006. SCI Total Taxa Sensitive Taxa % Very Tolerant Taxa % Dominant Taxon Overall NonChan Chan Overall NonChan Chan Overall NonChan Chan Overall NonChan Chan Overall NonChan Chan LDI -0.33 -0.01 -0.17 -0.01 0.36 -0.15 -0.4 -0.05 -0.14 0.37 0.11 0.08 -0.09 -0.29 -0.16 DOM 0.41 0.37 0.4 0.16 0.17 0.2 0.2 0.24 -0.06 -0.14 -0.13 0.16 -0.26 -0.29 -0.18 DOR -0.43 -0.2 0.12 -0.11 -0.17 0.03 -0.46 -0.14 -0.11 0.46 0.19 -0.03 0.18 0.24 0.05 DOD -0.4 -0.34 -0.29 -0.17 -0.16 -0.2 -0.2 -0.22 0.08 0.15 0.09 -0.11 0.27 0.33 0.14 DO% < 5 -0.4 -0.39 -0.24 -0.15 -0.26 -0.04 -0.25 -0.28 -0.01 0.19 0.14 -0.12 0.21 0.27 0.05 Non-Chan Non-Channelized Stream Chan Channelized Stream Bold values indicate significa nt correlations (p < 0.05)

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61 SCI scores showed a significant negative correlation with the LDI (Spearman r = 0.33, p = 0.02) when viewing all stations togeth er indicating the biological integrity of stream systems is negatively affected by in creasing intensity of human land use (Figure 8). Fore (2004) reported the same relationshi p, however the strength of the correlation in her work was stronger (Spearman r = -0.60, p < 0.01). The reason for the weaker correlation observed in this study is unknown, but may be related to the much smaller data set used than reported by Fore (2004). Seasonality seemed to play a role in this relationship as well. The SCI showed a significant negative correlation with LDI (Spearman r = -0.4, p = 0.047) in samples coll ected from quarter 4 (winter) while the quarter 2 collection (summer) showed no signi ficant relationship. The LDI score also showed a significant negative co rrelation with the number of sensitive taxa (Spearman r = -0.4, p = 0.003) and a positive correlation with the percent of very tolerant taxa (Spearman r = 0.37, p = 0.008). This indicates a reduction in the most sensitive taxa and increase in tolerant macroinvertebrate speci es in stream systems located in areas of increasing human impact. These findings co incide with other studies showing reduced biological integrity in watersheds with in creased human influence (Fore 2004 and 2007). When the data set was separated into cha nnelized and non-channeliz ed streams, only the number of total taxa coll ected in non-channelized streams showed a significant correlation with LDI scores (Spearman r = 0.36, p = 0.047). The reason for the positive correlation observed is unknown, but raises in terest and it may be prudent to conduct further investigation into this relationship in the future. Seasonali ty did not significantly affect the relationships observed in th e non-channelized and channelized systems.

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62 12345678910 LDI Score 0 10 20 30 40 50 60 70 80 SCI Score Overall Spearman r = -0.33, p = 0.02 Summer Spearman r = -0.28, p > 0.05 Winter Spearman r = -0.40, p = 0.047 Summer (Quarter 2) Winter (Quarter 4) Figure 8. LDI and overall SCI scores cal culated from summer and winter data collection efforts. The data shows a significant relationship exists between the intensity of human land use and biological integrity of the stream syst ems. It is also apparent in the data that dissolved oxygen plays an important role in th e biological health of the lotic systems in west-central Florida. All measures of dissolved oxygen were significantly correlated with the SCI scores over all stations (see Ta ble 13). The mean dissolved oxygen value showed a positive correlation (Spearman r = 0.41, p = 0.003) with SCI indicating the biological health of a stream is positively affected by the amount of oxygen available to the community (Figure 9). As the diel rang e in oxygen values increased the overall SCI score as well as the number of taxa listed as sensitive decreased (Spearman r = -0.43 and -0.46, p = 0.001 and p < 0.01, respectively) while the percentage of very tolerant taxa

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63 increased (Spearman r = 0.46, p < 0.001). The mean oxygen deficit was also negatively correlated the SCI score (Spearman r = 0.40, p = 0.04) over all stations, while the percent of exceedances was negatively correlat ed with SCI over all stations and in the non-channelized streams (Spearman r = -0.40 and -0.39, p = 0.004 and p = 0.03, respectively). 012345678910 DOM (mg/L) 0 10 20 30 40 50 60 70 80 SCI Score Overall Spearman r = 0.41, p = 0.003 Summer Spearman r = 0.64, p < 0.001 Winter Spearman r = 0.18, p > 0.05 Summer (Quarter 2) Winter (Quarter 4) Figure 9. Mean dissolved oxygen (DOM) and SCI scores calculated from summer and winter data collection efforts. While the mean oxygen deficit calculated over a four day deployment is an adequate measure of oxygen when compared to the intensity of human land uses, it may not be the most ecologically significant m easure of oxygen deficit (Dr. Douglas Durbin, pers. comm.). Macroinvertebrates sensitive to oxygen levels are likely to evacuate

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64 sections of a stream during times of minimu m oxygen concentrations, and are less likely to be affected by oxygen deficit when concen trations are higher (Dr. Douglas Durbin, pers. comm.). Therefore, the oxygen deficit calculated during times of minimum oxygen concentrations (i.e. nighttime oxygen levels) is a more accurate measure of oxygen that is likely to result in affects to macroinverteb rate assemblages. Figure 10 presents the oxygen deficit calculated at the minimu m oxygen concentration over each day of deployment, for each station, during the summer and winter SCI data collection periods. The figure shows a strong negative correla tion between SCI and oxygen deficit when concentrations are at a minimum. This relationship was strong er during the summer (Spearman r = -0.55, p < 0.001) than the wint er (Spearman r = -0.38, p < 0.001) While the mean oxygen deficit calculated over the 4-day deployment period showed a negative correlation with SCI score, it is actua lly the oxygen deficit at the minimum oxygen concentration that is driving the lower SCI sc ores. These data coincide with previous studies that show adequate availability of oxygen significantly impacts the biological health of a stream community (Hyne s 1960, Giller and Malmqvist 1998, Dodds 2002, Connolly et al. 2004, Walton et al 2007, and Jacobsen 2008). The biological integrity of channeliz ed streams in this study showed no relationship with the LDI or any measure of dissolved oxygen. The lack of relationship in these systems likely means there are other fa ctors at work affecti ng biological integrity in channelized streams. Ch annelization is known to have negative affects on the habitat availability, relative abundance, and richne ss of macroinvertebrates compared to nonchannelized systems (Rohasliney and Jackson 2008, Smiley and Dibble 2008). Channelization is expected to occur more fre quently in areas of more intense human land

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65 use, which is the case in this study where the majority of channelized streams have higher LDI scores than non-channelized systems. While channelization seems to have a negative effect on the biologica l integrity of the streams (t his relationship is observed when viewing all stations toge ther), increasing the intensity of land use in systems that have already been channelized does not s eem to be significant. This shows the channelization itself is the human activity causi ng the negative effect on stream ecology. 024681012 Dissolved oxygen deficit (DOD) at daily minimum oxygen concentration (mg/L) 0 10 20 30 40 50 60 70 80 SCI Score Summer Winter Summer Spearman r = -0.55, p < 0.001 Winter Spearman r = -0.38, p < 0.001 Figure 10. Dissolved oxygen deficit (DOD) calculated at the minimum oxygen concentration for each day of the 4-day deployment, during summer and winter data collection efforts.

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66 This study shows the intensity of human land use has a negative effect on the biological integrity of streams and is consistent with pr evious studies showing the same relationship (Fore 2004 and 2007). In additi on, measures of dissolved oxygen were significantly correlated with the SCI indicating the avai lability and stability of oxygen levels also play an important role in the heal th of the streams in this study. As previously indicated in this chapter, the intensity of human land use has significant effects on measures of dissolved oxygen that are also show n to affect the biolog ical integrity of the streams. While many factors associated with human activity in a watershed can affect streams, these data show it is important to directly address diss olved oxygen as altered oxygen regimes in streams can directly affect the overall health of the system.

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67 POLICY IMPLICATIONS This research effort provides valuable in sight for assessing th e impairment status of lotic systems for dissolved oxygen in Flor ida. The Clean Water Act requires for the establishment of protective regulatory criteria known as Total Maximum Daily Loads (TMDLs). A TMDL is defined as the maxi mum amount of a pollutant the waterbody can assimilate and still meet its designated stat e water quality standards (FDEP 2008). Water bodies known to exceed water quality standa rds (as determined through Florida’s Impaired Waters Rule, Chapter 62-303, F.A.C.) are required to have a TMDL established by the State of Florida, or, if the state does not establish a TMDL in a timely manner, the US Environmental Protection Agency (EPA) will develop a TMDL instead. In Florida, oxygen depletion and elevat ed nutrient concentra tions are the most common parameters of concern in the majority of “impaired” waterbodies (FDEP 2008). Currently, the FDEP (2008) lists 248 streams and rivers as verified impaired for dissolved oxygen, with the majority of those also im paired for nutrients (nitrogen and/or phosphorus) and are slated for TMDL development. Half of the stations in this study are listed as impaired for dissolved oxygen; the othe r half either not impaired or have not yet been assessed. According to the FDEP (2009) TMDL website, 16 dissolved oxygen TMDLs have been finalized throughout the st ate. Typically, the determination of a TMDL for dissolved oxygen is completed th rough an assessment of the relationship between oxygen and nutrient concentrations. In each case, the implemented TMDL

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68 requires a reduction in overall nut rient loading to a level presum ed to be at or below the assimilative capacity of the s ubject stream; which is design ed to remove the cause of oxygen stress, thereby increasi ng oxygen concentrations to meet the state water quality standard. This methodology coincides with re search previously cited in this text indicating the link between increasing nutrient concentr ations and decreasing oxygen concentrations. While this relationship is undeniable, th e data presented from this research effort shows additional antecedent relationships may significantly obscure the effectiveness of the TMDL. Oxygen concentrations in this study s howed a positive correlation with total phosphorus and no correlation with total nitrogen. This seemed to be the result of an increase in primary production driving up th e overall concentra tion of oxygen. With lower nutrient levels, primary production is reduced and thus lower dissolved oxygen concentrations are observed. In the scenario presented by the data in this project a reduction in the nutrient inputs to the subj ect streams would essentially decrease the oxygen concentrations giving the appearance of a failed TMDL. However, as presented here, stations with lower LDI scores typica lly showed low nutrient inputs, lower oxygen concentrations, yet showed gene rally higher levels of biologica l integrity. This shows the macroinvertebrate assemblages in streams with lower human impact have the ability to adapt to naturally lower oxygen conditions. It is possible for a reduction in nutrient loading to reduce overall oxygen concentrations to a more natural state without adversely affecting the biological integrity of the st ream. A TMDL for di ssolved oxygen does not currently account for the biological integrity of the stream and solely relies on nutrient load reduction to assume oxygen levels wi ll rebound above the standard for TMDL

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69 compliance. There fore, the current me thod of assessing dissolved oxygen TMDLs can not account for the relationships observed in this study and, in some cases, may not be adequate to effectively allevi ate an impaired determination. Additionally, a dissolved oxygen TMDL does not account for physical characteristics of streams, such as channelizatio n, that can also have significant effects. In this study, the streams with the highest LDI scores tend to be channelized with variable oxygen concentrations and few discernabl e correlations, as opposed to the nonchannelized streams which were strongly corr elated with oxygen and nutrients. This variability and lack of correla tion with nutrient concentrations indicate a TMDL set for a channelized stream may not alleviate oxygen im pairment. For these systems, it will be important to address the physical as well as chemical components of the stream to successfully address impairment. The physic al effects of channelization were not included in this study and additional research will help to fully understand the TMDL implications of these systems. Diel variation (difference between daily high and low oxygen concentration) was the measure of dissolved oxygen in this study wi th the most significant correlations with other variables, such as LDI, nutrients, and stream biological integrit y. Diel variation was shown to be greatly affected by intens ity of human land use overall and in both the channelized and non-channelized streams. This measure of oxygen is presumed to be the driving force behind the correlations betw een oxygen concentra tion, nutrients, and primary production observed, as well. This research indicates dissolved oxygen range may be a more effective and appropriate indi cator of the oxygen regime in a stream than straight measurements of oxygen concentration.

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70 Current methods of data collection for assessing dissolved oxygen regimes for TMDL purposes are based on in situ measurements of oxygen concentration, collected seasonally and evaluated against Florida’s fresh water quality sta ndard. A complete description of the methodology used, includi ng sample sizes, locations, and assessments of impaired status is given in Florida’s Impaired Waters Ru le (Chapter 62-303, F.A.C.). However, this method is highly variable a nd subject to unintended human influence as well as other factors, such as those describe d in this study. TMDL data collection efforts for dissolved oxygen are conducted during th e daytime hours with no requirement to standardize or stagger the time of day the m easurements are collected. An exceedance is measured as any oxygen concentration reporte d below the 5.0 mg/L standard regardless of time of day. Once a predetermined thre shold of exceedances is reached over the course of a year of monitoring, the wate rbody is deemed impaired. However, oxygen measurements vary greatly throughout th e day depending on factors such as canopy cover, sunlight, algal community and chlorophylla concentrations, among others, and time of day the measurements are collected can play a significant role in determining the impairment status of the water body. Figure 11 shows the percentage of all di ssolved oxygen values collected at all stations during this research effort that were above the 5.0 mg/L standard for each hour of the day. As the figure indicat es, only about half of the oxygen measurements collected during the evening, nighttime, and morning hours were above the 5.0 mg/L threshold. This number climbs to approximately 60 percent for the afternoon hours (~1 to 5 pm), indicating an increased likelihood a sample collected during the afternoon in these systems will be above the standard. In contra st, a sample collected at 8 am has slightly

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71 less than 50 percent chance to be above the standard. Since samples collected for TMDL purposes are typically collected during norma l working hours (8am to 5pm), stations sampled during the morning may have an increased likelihood to be measured below the standard, and therefore increased chance of acquiring an impaired status. Also, since scheduling for this type of sampling can be logistically challenging, it is likely that stations may inadvertently be sampled at th e same time of day on many sampling trips. 123456789101112131415161718192021222324 Hour of the Day 0 10 20 30 40 50 60 70 80 90 100Percent of Oxygen Values > 5.0 mg/L Figure 11. Percent of dissolved oxygen valu es collected from all stations, over all quarters observed above the 5.0 mg/L st ate water quality standard by hour of the day. As this research indicates, the reference stations, with the lo west rate of human influence, typically had low mean oxygen concentrations (< 5 .0 mg/L) throughout the year. This is evident when displaying th e percentage of dissolv ed oxygen values above

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72 the standard at all six of the reference stat ions in this study by hour of the day (Figure 12). The same temporal pattern is observ ed with mid afternoon sample collections exhibiting the greatest percentage of values a bove the standard. However, it is interesting to note the percentage of oxygen values obser ved above the standard at the reference stations was only between ~30 and 40 percent throughout the day. This indicates there is increased opportunity to measure oxygen below the standard at the reference stations compared to stations with a higher intensity of human influence, regardless of time of day. In fact, two of the reference stations in this study are currently verified as impaired for dissolved oxygen by FDEP. These data show streams in watersheds with increased intensity of human land use, compared to the reference stations, have a greater chance to be measured above the standard. As a re sult of the inherent variability in oxygen measurements and timing of sample collections this research shows direct measurements of oxygen concentration may not be adequate to accurately determine the impairment status of streams. Diel variation was the measure of ox ygen in this study showing the most significant correlations with intensity of land use, nutrients, chlorophylla and measures of biological integrity. Measuri ng diel variation, as a measur e of the daily shift in oxygen values eliminates the potential effect of time of day on determining th e impaired status of a waterbody. In addition, diel variation is the only measure of oxygen in this study that can potentially account for the phys ical effects of channelizati on or the effect of primary production and nutrient loading on oxygen values. Future research should focus on diel variation to fully explore the complex nature of the relationships presented here. The

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73 daily range of oxygen values may be a more appropriate measure of oxygen to determine the impaired status of flowing systems. 123456789101112131415161718192021222324 Hour of the Day 0 10 20 30 40 50 60 70 80 90 100Percent of Oxygen Values > 5.0 mg/L Figure 12. Percent of dissolved oxygen values collected from the reference stations, over all quarters observed above the 5.0 mg/L state water quality standard by hour of the day.

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74 CONCLUSIONS Landscapes dominated by intense human activity are known to have significant effects on natural communities (Brown a nd Vivas 2005). Degradation of aquatic communities is known to occur as a result of urban and agricultural point and non-point sources (Tsegaye et al. 2006, Carpenter et al. 1998, USEPA 1996 & 2001). In Florida, substantial monetary funds ar e spent each year assessing Fl orida’s aquatic systems to determine anthropogenic sources of impairment and design strategies to mitigate those impacts. Oxygen depletion is the most common impairment in Florida streams, with over 2,000 miles of assessed rivers and streams lis ted as impaired for low dissolved oxygen (FDEP 2008). This study set out to evaluate dissolved oxygen in streams in west-central Florida and provide greater unde rstanding of how the intensity of human land use in the surrounding watershed affects dissolved oxygen re gimes. In addition, an index of human land use and oxygen was evaluated against a me asure of the biological integrity of the streams to identify the respons e of natural communities to altered oxygen regimes as a result of increasing human land use. Twenty-six lotic systems throughout west -central Florida (Tampa Bay basin) were used in this project and sampled quarterly for one ye ar (2005-2006). Data collection included dissolved oxygen, temperatur e, nutrients, chlorophylla and benthic macroinvertebrate assemblages (Stream Cond ition Index). The intensity of human land use was evaluated using the Landscape Devel opment Intensity Index (LDI) (Brown and

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75 Vivas 2005). Mean dissolved oxygen concentrat ion, range, deficit, and percentage of values below Florida’s fresh water dissolved oxygen standard (5.0 mg/L) were chosen to characterize the oxygen regime of each stream. Data were analyzed for relationships using Spearman rank order correlations. Through this effort significant relationship s were identified that present valuable insight into the effect of human land us es on dissolved oxygen regimes and biological communities in Florida streams. Diel variation in oxygen measurements was significantly correlated to the LDI score indi cating as land uses become more intense with human activity, the range between high and low oxygen measurements increases. This is not surprising as othe r studies have linked increased diel variation in streams to anthropogenic sources (Walsh et al. 2005). This relationship seems to be linked to nutrient and chlorophylla concentrations in the streams. The most significant relationships were seen with total phosphor us, which is understandable since phosphorus is typically the limiting nutrient in fres hwater systems (Hecky and Kilham 1988 and Mallin et al. 2004). As the intensity of hu man land use increases, the concentration of phosphorus shows a corresponding increase, as does the concentration of chlorophylla in the waterbody. This relationship has the effect of increasing the diel variation in oxygen measurements. The data show this alone has the effect of lowering the biological integrity of stream systems in west -central Florida (see Table 13). The most significant conclusions regardi ng the effect intensity of human land use has on dissolved oxygen regimes are apparent when the morphology of the stream channel is taken into account. As previously described, the LDI is a measure of the nonrenewable energy consumed by human activit ies and is therefore not capable of

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76 addressing the morphology of a stream channel. However, stream morphology is known to affect many factors of water quality in cluding dissolved oxyge n (Brilly et al. 2006, Meyer et al. 2005, Paul and Meyer 2001, and Wals h et al. 2005). The stations in this study were separated into channelized and non-channelized, then analyzed separately with considerable results. Channelized str eams can reasonably be expected to be found more frequently in landscapes of more intense human activity, as was the case in this study with the majority of channelized syst ems having higher LDI scores while most of the non-channelized stre ams were associated with lower LDI scores (see Figure 7). The effect of human land use on dissolve d oxygen seemed to come from different sources in the non-channelized and channelized systems. In the non-channelized streams all measures of dissolved oxygen were significa ntly correlated with LDI scores indicating the highest oxygen concentrati ons, lowest oxygen deficit, and fewest exceedances of the standard were found in streams with the most intense human land use. In addition, the greatest diel variation was also found with higher LDI scores. This relationship gives the overall impression of improving oxygen regime s in areas of increasing intensity of human land use as opposed to reference (nat ural) aquatic communities. However, the same relationship was not observed in the ch annelized streams, which tend to have the highest LDI scores. In the non-channelized systems, phos phorus is the key nutrient driving the relationship between dissolved oxygen and hum an land use. Phosphorus concentrations increased relative to the intensity of land us e and, interestingly, m easures of dissolved oxygen also showed improvement as phosphorus concentrations increased. This relationship seems to contradict the genera lly accepted notion that increased nutrient

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77 levels are associated with oxygen depleti on (MacPerson et al. 2007, Mallin et al. 2006, NRC 2000, Wang et al. 2003, and Wilcock 1986). This positive correlation was observed during all four quarters of da ta collection indicating the re lationship was not linked to seasonal variables. Analyzing chlorophylla concentrations shows an increase in primary producers in relation to increas ing phosphorus concentrations. The increase in primary production is linked to an increase in di el variation of oxygen measurements and subsequent increase in overall dissolved oxygen concentrations. Platt (1981) has presented studies indicating that dark re spiration by primary producers consumes less oxygen (5 – 50 percent) than is produced by photos ynthesis. This resu lts in a net increase in oxygen when diel variation increases. The complex relationships explained here indicate how intense human land use can result in increased dissolved oxygen concentrations and fewer exceedances of Florida’s oxygen criteria, as shown in this study. This was only evident in streams with natural sinuosity, and was not observed in stream systems that have been channelized. As previously described, the channelized streams in this study were mostly concentrated on the higher end of the LDI scale. The majority of quarterly mean dissolved oxygen concentrations were below th e 5.0 mg/L criteria se t for freshwaters. These systems, while typically exhibiting low overall dissolved oxygen regimes relative to the standard, did not show the same rela tionship with nutrients and chlorophyll as the non-channelized systems. It is likely these relationships still exist, however they are obscured by other physical fact ors affecting dissolved oxygen. Channelized streams tend to include straight, incised banks, greater depth, low velocity, and may include other structures such as impoundments that can ha ve significant effects on dissolved oxygen.

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78 These, and other physical characteristics of chan nelization were not incl uded in this study so their impact on the dissolved oxygen regime s of the systems could not be examined. However, the results seem to indicate that channelization has a greater effect on dissolved oxygen regimes than the variables included in th is study. Additional research in this area could help to identify which variables have the greatest effect as well as understand the relationships between the variables. Human land use affects dissolved oxygen regimes in streams to varying degrees dependent upon the physical charac teristics of the stream itself. In west-central Florida the reference streams used in this research exhibited some of the lowest overall oxygen regimes with the greatest number of exceedan ces of Florida’s fresh water standard. These streams tend to exhibit natural sinuosity with the least amount of human influence. As human influence increases in the wa tershed surrounding non-channelized streams, increased nutrient (phosphorus) inputs s eem to increase the overall oxygen regime through increased primary production. As hu man influence continues to increase and land uses surrounding the streams become more dominated by high intensity agriculture, residential, commercial, a nd industrial uses, lotic syst ems are more likely to be channelized. This physical alteration of th e stream system takes over as the dominant force affecting dissolved oxygen resu lting in lower overall regimes. Altered dissolved oxygen regimes a nd intense human land use can have significant effects on the biol ogical integrity of a stream. Fore (2004) showed how increasing LDI can result in lowered biol ogical integrity using the Stream Condition Index (SCI). The same relationship was obser ved in this research. In addition, the SCI showed a strong correlation with dissol ved oxygen. Benthic macroinvertebrate

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79 community structure increased with in creasing mean oxygen concentrations and decreased with increasing di el variation. Although the re ference stations typically exhibited lower oxygen concentratio ns (see Figure 7), they also showed more stable diel variation (see Figure 4). Incr easing intensity of human land us e results in increased diel variation of oxygen measurements and corresponds to a decrease in SCI score. Increased diel variation was linked with a loss of sensitive taxa, and an increase in the percent of tolerant taxa as well as an increase in the dominant taxon (re duced diversity). This was only observed when viewing all stations toge ther and was not evident when separating the stations into channelized a nd non-channelized systems. In this research, the diel shift in oxygen measurements showed the greatest effect on the biological integrity of the streams. Seasonal variation was observed in the relationships be tween oxygen, land use, and SCI scores as well. Biological integrity showed strong correlation with measures of oxygen during the summer, but was not correlated with the LDI scores. In contrast, the winter SCI scores showed a negative correla tion with LDI, and did not correlate with measures of dissolved oxygen. This interes ting dichotomy indicates that altered oxygen regimes as a result of intense human activity in a watershed may not be the most effective indicator of stream biological integrity. However, the data indicates oxygen does play a significant role, and these effects should be accounted for when assessing the overall health of the lotic system. The results of this research effort ma y have significant impacts for Florida’s TMDL program and for methodologies used to assess the impairment status of stream and river systems throughout the state. Curre nt TMDL evaluations do not account for the relationships observed in this study and inst ead rely solely on nutrient reduction to

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80 alleviate oxygen stress. The da ta presented here indicate a simple reduction in nutrient inputs may have no affect or may actually d ecrease overall oxygen concentrations giving the appearance of a failed TMDL for dissolved oxygen. In addition, current TMDL data collection methodologies are based on in situ measurements of oxygen concentration and are subject to unintended bias from the eff ects of photoperiod as pr eviously described. As a result of the inherent variability in oxygen measurements and timing of sample collections, this research shows in situ oxygen concentration measurements may not be adequate to accurately determine the impairme nt status of streams and rivers. Diel variation more accurately reflects the relatio nship between oxygen and the intensity of human land use and antecedent variables in cluding nutrients and primary production. Therefore, diel variation may be a more accurate predictor of oxygen impairment and TMDL efforts should focus on this measure of oxygen to determine impairment status. Additional research will be necessary to fully explore and understand the relationships presented in this study. Th e relationship between oxygen, intensity of human land use, and nutrients (phosphorus) observe d in this research seems to contradict previous studies; therefore, additional research should be co nducted to determine if the same relationship is observed in flowing syst ems on a state-wide scale or in other types of waterbodies. In addition, it will be impor tant to incorporate the effect of stream morphology on the oxygen regime of a flowing syst em to be able to fully characterize the impact of human land uses. Based on the re sults observed in this study, future research should focus on diel variation as a more appr opriate indicator of oxygen regimes in lotic systems. It will also be important to incl ude biological integrity in any assessment of impairment to determine when a system has been altered as a resu lt of human activity.

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81 Dissolved oxygen is widely considered a general indicator of aquatic health. Research presented here from lotic systems in west-central Florida indicates the intensity of human land use has a signi ficant effect on dissolved oxyge n regimes. Chemical as well as physical alterations in watersheds as a result of increased human activity have differing effects on dissolved oxygen, some wh ich may actually lead to increased overall oxygen regimes. These complex relationships mu st be fully explored and integrated into regulatory frameworks to accurately delineate between impairment as a result of human influence and natural variability for which an impaired determination is not necessary. The relationships presented here may also be useful, in conjunction wi th further research and analysis, when attempting to revise the dissolved oxygen state water quality standard to allow for greater protection of Florida’s most valuable resource.

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82 LITERATURE CITED Alexander, C.D. and H.G. Stefan. 1983. Model of Mississippi river pool dissolved oxygen. Journal of Environmental Engineering. ASCE 109(5): 1020-1036. Allan, J.D., D.L. Erickson, and J. Fay. 1997. The influence of catchment land use on stream integrity across multiple spatia l scales. Freshwat er Biology 37: 149-161. American Fisheries Society. 1979. A review of the EPA red book, quality criteria for water. American Fisheries Society, Bethesda, Maryland. Beaulac, M.N. and K.H. Reckhow. 1982. An examination of land use-nutrient export relationships. Water Res ources Bulletin 18: 1013-1024. Berkun, M. and E. Aras. 2007. Parametric evaluation of a dissolved oxygen-deficit profile. Environmental Engin eering Science 24(10): 1389-1398. Boeder, M., and H. Chang. 2008. Multi-scale analysis of oxygen demand trends in an urbanizing Oregon watershed, USA. Jour nal of Environmental Management 87: 567-581. Brilly M., S. Rusjan, and A. Vidmar. 2006. Monitoring the impact of urbanization on the Glinscica stream. Physics a nd Chemistry of the Earth 31: 1089-1096. Brown, M.T. and K.C. Reiss. 2006. Proposed breakpoint of LDI < 2.0 for determining minimally affected reference conditions for water bodies. Center for Environmental Policy, Department of Environmental Engineering Sciences, University of Florida. Technical Report Submitted to the Florida Department of Environmental Protection. Brown, M.T. and M.B. Vivas. 2003. A Landscape Development Intensity Index. Center for Environmental Policy, Department of Environmental Engineering Sciences, University of Florida. Technical Report Submitted to the Florida Department of Environmental Protection. Brown, M.T. and M.B. Vivas. 2005. Landscape Development Intensity Index. Environmental Monitoring and Assessment 101: 289-309.

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83 Butcher, J.B. and S. Covington. 1995. Dissolved oxygen analysis with temperature dependence. Journal of Environmen tal Engineering. ASCE 121(10): 756-759. Carpenter, S.R., N.F. Caraco, D.L. Correll R.W. Howarth, A.N. Sharpley, and V.H. Smith. 1998. Nonpoint pollution of surface waters with phosphorus and nitrogen. Ecological Applications 8: 559-568. Chapra, S.C. and D.M. Di Toro. 1991. Delta method for estimating primary production, respiration, and reaeration in streams. Journal of Environmental Engineering. ASCE 117(6): 641-655. Chaudhury, R.R., J.A.H. Sobrinho, R.M. Wright and M. Sreenivas. 1998. Dissolved oxygen modeling of the Blackstone River ( northeastern US). Water Resources 32(8): 2400-2412. Colangelo, D.J. 2007. Response of river me tabolism to restoration of flow in the Kissimmee River, Florida, U.S.A. Freshwater Biology 52: 459-470. Connolly, N.M., M.R. Crossland, and R.G. Pearson. 2004. Effect of low dissolved oxygen on survival, emergence, and drift of tropical stream macroinvertebrates. Journal of the North American Be nthological Society 23(2): 251-270. Cox, B.A. 2003. A review of dissolved oxyge n modeling techniques for lowland rivers. The Science of the Total Environment 314-316: 303-334. Crosbie, B. and P. Chow-Fraser. 1999. Per centage land use in the watershed determines the water and sediment quality of 22 mars hes in the Great Lakes basin. Canadian Journal of Fisheries and Aquatic Science 56: 1781-1791. Dodds, W.K. 2002. Freshwater ecology: con cepts and environmental applications. Academic Press, San Diego, California. EcoWatch for Windows. Version 3. 15.00. Copyright 1996-2000, YSI, Inc. Edwards, R.W., A.N. Duffield, and E.J. Marshall. 1978. Estimates of community metabolism of drainage channels from oxygen distributions. Proceedings of the EWRS Fifth Symposium on Aquatic Weeds. Ehrenfeld, J.G. 1983. The effects of change s in land-use on swamps of the New Jersey pine barrens. Biologica l Conservation 25: 353-375. Florida Department of Environmental Pr otection. 2006. Selection of minimally disturbed reference sites using the Landscap e Development Intensity Index (LDI). Draft prepared for the Florida Depart ment of Environmental Protection. 1 September 2006.

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84 Florida Department of Environmental Prot ection. 2008. Integrated water quality assessment for Florida: 2008 305(b) report and 303(d) list update. Bureau of Watershed Management, Division of E nvironmental Assessment and Restoration. Florida Department of Environmental Prot ection. 2009. Final TMDL Documents. http://www.dep.state.fl.us /water/tmdl/final_tmdl.htm, accessed on 20 March 2009. Florida Department of Transportation. 1999. Florida Land Use Cover and Forms Classification System. Handbook of Flor ida Department of Transportation, Surveying and Mapping Office, Thematic Mapping Section, Tallahassee, FL, 91 pp. Fore, L.S. 2004. Development and testing of biomonitoring tools for macroinvertebrates in Florida streams. Statistical Desig n, Seattle, WA. Final Report Submitted to the Florida Department of Environmental Protection. Fore, L.S., R. Frydenborg, D. Miller, T. Fric k, D. Whiting, J. Espy, and L. Wolfe. 2007. Development and testing of biomonitoring tools for macroinvertebrates in Florida streams (Stream Condition Index and Bior econ). NonPoint Source Bioassessment Program. Final Report Prepared for the Florida Department of Environmental Protection. Giller, P.S. and B. Malmqvist. 1998. The biology of streams and rivers. Oxford University Press, Oxford, UK. Grimm N.B., M.J. Grove, S.T.A. Pickett, and C.L. Redman. 2000. Integrated approaches to long-term studies of urba n ecological systems. Bioscience 50:571584. Gulliver, J. and H.G. Stephan. 1984. Stream productivity analysis with DORM-II. Development of computational model. Water Resources 18(12): 1569-1576. Hecky, R.E. and P. Kilham. 1988. Nutrient limitation of phytoplankton in freshwater and marine environments: a review of recent evidence on the effects of enrichment. Limnology and Oceanography 33: 796-822. Hornberger, G.M. and M.G. Kelly. 1972. Th e determination of primary production in a stream using an exact solution to the oxygen balance equation. Water Resources Bulletin 8(4): 795-801. Hynes, H.B. N. 1970. The biology of polluted waters. Liverpool University Press, Liverpool, UK.

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85 Jacobsen, D. 2008. Low oxygen pressure as a dr iving factor for the al titudinal decline in taxon richness of stream macroinve rtebrates. Oecologia 154: 795-807. Kelly, M.G., G.M. Hornberger, and B. J. Cosby. 1974. Continuous automated measurement of photosynthesis and re spiration in an undisturbed river community. Limnology and Oceanography 19(2): 305-312. Mack, J.J. 2006. Landscape as a predictor of wetland condition: An evaluation of the Landscape Development Index (LDI) with a large reference we tland dataset from Ohio. Environmental Monitoring and Assessment 120: 221-241. MacPherson, T.A., L.B. Cahoon, and M.A. Mallin. 2007. Water column demand and sediment oxygen flux: patterns of oxyge n depletion in tidal creeks. Hydrobiologia 586: 235-248. Mallin, M.A., M.R. McIver, S.H. Ensign, and L.B. Cahoon. 2004. Photosynthetic and heterotrophic impacts of nut rient loading to blackwat er streams. Ecological Applications 14(3): 823-838. Mallin, M.A., V.L. Johnson, S.H. Ensign, and T.A. MacPherson. 2006. Factors contributing to hypoxia in rivers, la kes and streams. Limnology and Oceanography 51: 690-701. McDonnell M.J. and S.T.A. Pickett. 1990. Ecosystem structure and function along urban-rural gradients: an unexploited opportunity for ecology. Ecology 71: 23237. Meyer J.L., J. Paul, and W.K. Taulbee. 2005. Stream ecosystem function in urbanizing landscapes. Journal of th e North American Benthological Society 24: 602-612. Morgan, A.M, T.V. Royer, M.B. David, a nd L.E. Gentry. 2006. Relationships among nutrients, chlorophyll-a, and dissolved oxygen in agricultura l streams in Illinois. Journal of Environmental Quality 35: 1110-1117. National Research Council (NRC). 2000. Cl ean coastal waters – Understanding and reducing the effects of polluti on. National Academy Press 405pp. Novotny, V., A. Bartosova, N. O’Reilly, and T. Ehlinger. 2005. Unlocking the relationship of biotic integr ity of impaired waters to anthropogenic stresses. Water Research 39: 184-198. O’Conner, D.J. and D.M. Di Toro. 1970. P hotosynthesis and oxygen balance in streams. Journal of Sanitary Engineering. ASCE 96(2): 547-571.

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86 Odum, H.T. 1956. Primary production in flowing waters. Limnology and Oceanography 1: 102-117. Parkhill, K.L. and J.S. Gulliver. 1999. M odeling the effect of light on whole-stream respiration. Ecologica l Modeling 117: 333-342. Paul, M. J., and J. L. Meyer. 2001. Streams in the urban landscape. Annual Review of Ecology and Systematics 32:333-365. Pearson, R.G. and L.K. Penridge. 1987. Th e effects of pollution by organic sugar mill effluent on the macro-invertebrates of a st ream in tropical Queensland, Australia. Journal of Environmental Management 24: 205-215. Pinellas County Government. 2009. Pi nellas County Government Facts. http://www.pinellascounty.org/fact s.htm, accessed on 17 February 2009. Platt, T. [ED.]. 1981. Physiological base s of phytoplankton ecology. Canadian Bulletin of Fisheries and Aquatic Science 210: 346p. Richards, C., L.B. Johnson, and G.E. Host. 1996. Landscape-scale influences on stream habitats and biota. Canadian Journal of Fisheries and Aquatic Science 53: 295311. Rohasliney, H. and D.C. Jackson. 2008. Lignite mining and stream channelization influences on aquatic macroinvertebra te assemblages along the Natchez Trace Parkway, Mississippi, USA. Hydrobiologia 598: 149-62. Roth, N.E., J.D. Allan, D.L. Erickson. 1996. Landscape influences on stream biotic integrity assessed at multiple spatia l scales. Landscape Ecology 11: 141-156. Rounds, S.A. and M.C. Doyle. 1997. Sediment oxygen demand in the Tualatin River Basin, Oregon, 1992-96. U.S. Geological Surv ey Water-Resources Investigations Report 97-4103: 1-19. Roy, A.H., C.L. Faust, M.C. Freeman, and J.L. Meyer. 2005. Reach-scale effects of riparian forest cover on urban stream ecosy stems. Canadian Journal of Fisheries and Aquatic Science 62: 2312-2329. Schurr, J.M. and J. Ruchti. 1977. Dynamics of O2 and CO2 exchange, photosynthesis, and respiration in rivers from time-de layed correlation with ideal sunlight. Limnology and Oceanography 22(2): 208-225. Smiley, P.C. and E.D. Dibble. 2008. Infl uence of spatial resolution on assessing channelization impacts on fish and m acroinvertebrate communities in a warmwater stream in the southeastern United States. Environmental Monitoring and Assessment 138: 17-29.

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87 StatSoft, Inc. 2005. STATISTICA (data an alysis software system), version 7.1. www.statsoft.com. Streeter H.W. and E.B. Phelps. 1925. A st udy of the pollution and na tural purification of the Ohio River. U.S. Public Health Service, Public Health Bulletin no. 146, February 1925. Tsegaye, T., D. Sheppard, K.R. Islam, A. Johnson, W. Tadesse, A. Atalay, and L. Marzen. 2006. Deveopment of chemical index as a measure of in-stream water quality in response to land-use and land cover changes. Water, Air, and Soil Pollution 174: 161-179. US Environmental Protection Agency. 1996. Environmental indicators of water quality in the United States. EPA Repor t 841-R-96-002. EPA, Washington, DC. US Environmental Protection Agency. 2001. Our built and natural environments: A technical review of the interactions between land-use, transportation, and environmental quality. EPA 231R-01-002. EPA, Washington, DC. US Environmental Protection Agency. 2002. Nitrification. Distri bution System Issue Paper. Office of Ground Water and Dr inking Water, Standards and Risk Management Division. 15 August 2002. US Geological Survey. 1999. The quality of our nation’s waters – nutrients and pesticides. USGS Circular 1225. Walsh, C. J., A.H. Roy, J.W. Feminella, P.D. Cottingham, P.M. Groffman, and R.P. Morgan. 2005. The urban stream syndr ome: current knowledge and the search for a cure. Journal of the North Amer ican Benthological Society 24(3): 706-723. Walton, B.M., M. Salling, J. Wyles, and J. Wolin. 2007. Biological integrity in urban streams: Toward resolving multiple dime nsions of urbanization. Landscape and Urban Planning 79: 110-123. Wang, H., M. Hondzo, C. Xu, V. Poole, and A. Spacie. 2003. Dissolved oxygen dynamics of streams draining an urbani zed and an agricu ltural catchment. Ecological Modell ing 160: 145-161. Wilcock, R.J. 1986. Agriculture runoff: a s ource of water pollution in New Zealand. New Zealand Agricultural Science 20: 98-103. YSI Incorporated. 2002. YSI Environmental Operations Manual. Yellow Springs, Ohio.

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88 BIBLIOGRAPHY Abdul-Aziz, O. I., B.N. Wilson, and J.S. Gulliver. 2007. An extended stochastic harmonic analysis algorithm: Applicati on for dissolved oxygen. Water Resources Research Vol. 43: W08417. Berkun, M. 2005. Effects of Ni, Cr, Hg, Cu, Zn, Al on the dissolved oxygen balance of streams. Chemosphere 59: 207-215. Cowell, B.C., A.H. Remley, and D.M. Lynch. 2004. Seasonal changes in the distribution and abundance of benthic invertebrates in six headwater streams in central Florida. Hydrobi ologia 522: 99-115. Crisman, T.L., L.J. Chapman, and C.A. Chap man. 1998. Predictors of seasonal oxygen levels in small Florida lakes: The impor tance of color. Hydrobiologia 368: 149155. Daniel, M.H.B., A.A. Montebelo, M.C. Bernar des, J.P.H.B. Ometto, P.B. De Camargo, A.V. Krusche, M.V. Ballester, R.L. Vict oria, and L.A. Martinelli. 2002. Effects of urban sewage on dissolved oxygen, di ssolved inorganic and organic carbon, and electrical conductivity of small stream s along a gradient of urbanization in the Piracicaba River Basin. Water, Ai r, and Soil Pollution 136: 189-206. Girija, T.R., C. Mahanta, and V. Chandram ouli. 2007. Water quality assessment of an untreated effluent impacted urban st ream: The Bharalu Tributary of the Brahmaputra River, India. Environm ental Monitoring and Assessment 130: 221236. Groffman, P.M., A.M. Dorsey, and P.M. Ma yer. 2005. N processing within geomorphic structures in urban streams. Journal of the North American Benthological Society 24(3): 613-625. Hamed, M.M. and M.Z. El-Beshry. 2004. Uncertainty analysis in dissolved oxygen modeling in streams. Envir onmental Management 34(2): 233-244. Kemp, M.J. and W.K. Dodds. 2001. Centimet er-scale patterns in dissolved oxygen and nitrification rates in a prairie str eam. Journal of the North American Benthological Society 20(3): 347-357.

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89 Kemp, M.J. and W.K. Dodds. 2002. Comparisons of nitrification a nd denitrification in prairie and agriculturally influenced str eams. Ecological Applications 12(4): 9981009. Lane, C.R. and M.T. Brown. 2007. Diatoms as indicators of isolated herbaceous wetland condition in Florida, USA. Ecological Indicators 7: 521-540. Morgan, R. P. and S. F. Cushman. 2 005. Urbanization effects on stream fish assemblages in Maryland, USA. Journa l of the North American Benthological Society 24(3): 643-655. Mulholland, P.J., J.N. Houser, and K.O. Maloney. 2005. Stream diurnal dissolved oxygen profiles as indicators of in-stream metabolism and disturbance effects: Fort Benning as a case study. Ec ological Indica tors 5: 243-252. Overmyer, J.P., R. Noblet, and K.L. Armbrust. 2005. Impacts of lawn-care pesticides on aquatic ecosystems in relation to property value. Environmental Pollution 137: 263-272. Reichert, P. 2001. River water quality m odel no. 1 (RWQM1): Case study II. Oxygen and nitrogen conversation processes in th e River Glatt (Switz erland). Water Science and Technology 43(5): 51-60. Ryon, M.G., A.J. Stewart, L.A. Kszos, and T.L. Phipps. 2002. Impacts on streams from the use of sufur-based compounds for dechlo rinating industrial effluents. Water, Air, and Soil Pollution 136: 255-268. Simcox, A.C. and R.C. Whittemore. 2004. E nvironmental index for assessing spatial bias in watershed sampling networks. Journal of Environmental Engineering 130(6): 622-630. Wilcock, R.J. and J.W. Nagels. 2001. Effects of aquatic macrophytes on physicochemical conditions of three contrasti ng lowland streams: a consequence of diffuse pollution from agriculture? Water and Science Technology 43(5) 163168.

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90 APPENDIX A: Landscape Developm ent Intensity Index Raw Data

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91 Appendix A Site Land Use FLUCC Code Level I FLUCC Code Level II FLUUCS Code Land Use Coeff. Total Area (m2) HIL-1 Residential, Low Density 1000 1100 1100 6.79 119134.21 HIL-1 Residential, Medium Density 1000 1200 1200 7.59 9912.87 HIL-1 Residential, High Density 1000 1300 1300 8.66 34268.28 HIL-1 Commercial and Services 1000 1400 1400 8.00 306841.24 HIL-1 Institutional 1000 1700 1700 8.07 1905.64 HIL-1 Pastures and Fields 2000 2100 2100 3.51 252280.40 HIL-1 Feeding Operations 2000 2300 2300 5.15 46963.03 HIL-1 Other Open Lands 2000 2600 2600 2.06 455459.88 HIL-1 Shrub and Brushland 3000 3200 3200 2.06 12.34 HIL-1 Mixed Rangeland 3000 3300 3300 2.06 12483.40 HIL-1 Hardwood Conifer Mixed 4000 4300 4340 1.00 119690.80 HIL-1 Lakes 5000 5200 5200 1.00 141399.70 HIL-1 Reservoirs 5000 5300 5300 4.09 57867.97 HIL-1 Wetland Hardwood Forests 6000 6100 6100 1.00 7905.01 HIL-1 Freshwater Marshes 6000 6400 6410 1.00 45386.54 HIL-1 Emergent Aquatic Ve getation 6000 6400 6440 1.00 38740.59 HIL-1 Transportation 8000 8100 8100 7.81 45207.50 HIL-2 Residential, Low Density 1000 1100 1100 6.79 175260.46 HIL-2 Residential, Medium Density 1000 1200 1200 7.59 79842.27 HIL-2 Residential, High Density 1000 1300 1300 8.66 1390843.78 HIL-2 Commercial and Services 1000 1400 1400 8.00 9826.64 HIL-2 Industrial 1000 1500 1500 8.32 3917.11 HIL-2 Institutional 1000 1700 1700 8.07 5743.99 HIL-2 Recreational 1000 1800 1800 4.09 282488.55 HIL-2 Other Open Land 1000 1900 1940 1.85 18739.88 HIL-2 Pastures and Fields 2000 2100 2100 3.51 52430.53 HIL-2 Specialty Farms 2000 2500 2500 4.06 3962.25 HIL-2 Other Open Lands 2000 2600 2600 2.06 111283.46 HIL-2 Hardwood Conifer Mixed 4000 4300 4340 1.00 73407.39 HIL-2 Streams and Waterways 5000 5100 5100 1.00 28726.40 HIL-2 Lakes 5000 5200 5200 1.00 143360.67 HIL-2 Lakes 5000 5200 5200 1.00 1892.69

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92 Appendix A (Continued) Site Land Use FLUCC Code Level I FLUCC Code Level II FLUUCS Code Land Use Coeff. Total Area (m2) HIL-2 Reservoirs 5000 5300 5300 4.09 153070.47 HIL-2 Wetland Hardwood Forests 6000 6100 6100 1.00 63992.046 HIL-2 Bottomland Hardwood Forest 6000 6100 6150 1.00 667547.82 HIL-2 Cypress 6000 6200 6210 1.00 138286.75 HIL-2 Freshwater Marshes 6000 6400 6410 1.00 34269.853 HIL-2 Wet Prairies 6000 6400 6430 1.00 14978.685 HIL-2 Emergent Aquatic Ve getation 6000 6400 6440 1.00 16987.59 HIL-2 Transportation 8000 8100 8100 7.81 20216.169 HIL-2 Utilities 8000 8300 8300 8.32 56912.633 HIL-3 Residential, Low Density 1000 1100 1100 6.79 78930.407 HIL-3 Residential, Medium Density 1000 1200 1200 7.59 890656.66 HIL-3 Residential, High Density 1000 1300 1300 8.66 732371.61 HIL-3 Commercial and Services 1000 1400 1400 8.00 72601.006 HIL-3 Institutional 1000 1700 1700 8.07 15014.416 HIL-3 Recreational 1000 1800 1800 4.09 13160.573 HIL-3 Tree Crops 2000 2200 2200 4.06 21946.072 HIL-3 Nurseries and Vineyards 2000 2400 2400 4.06 27378.881 HIL-3 Other Open Lands 2000 2600 2600 2.06 28396.57 HIL-3 Hardwood Conifer Mixed 4000 4300 4340 1.00 23881.708 HIL-3 Lakes 5000 5200 5200 1.00 1259338.1 HIL-3 Reservoirs 5000 5300 5300 4.09 92499.327 HIL-3 Wetland Hardwood Forests 6000 6100 6100 1.00 126337.74 HIL-3 Cypress 6000 6200 6210 1.00 23355.02 HIL-3 Freshwater Marshes 6000 6400 6410 1.00 25260.713 HIL-3 Wet Prairies 6000 6400 6430 1.00 8378.1596 HIL-3 Emergent Aquatic Ve getation 6000 6400 6440 1.00 156937.75 HIL-3 Transportation 8000 8100 8100 7.81 33736.33 HIL-3 Utilities 8000 8300 8300 8.32 23196.836 HIL-4 Residential, Low Density 1000 1100 1100 6.79 11822.737 HIL-4 Residential, High Density 1000 1300 1300 8.66 1613098.1 HIL-4 Commercial and Services 1000 1400 1400 8.00 408590.61 HIL-4 Industrial 1000 1500 1500 8.32 254016.34 HIL-4 Institutional 1000 1700 1700 8.07 178451.84 HIL-4 Recreational 1000 1800 1800 4.09 318860.12 HIL-4 Other Open Lands 2000 2600 2600 2.06 212258.23 HIL-4 Hardwood Conifer Mixed 4000 4300 4340 1.00 16735.22 HIL-4 Streams and Waterways 5000 5100 5100 1.00 56692.101 HIL-4 Lakes 5000 5200 5200 1.00 3955.8125

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93 Appendix A (Continued) Site Land Use FLUCC Code Level I FLUCC Code Level II FLUUCS Code Land Use Coeff. Total Area (m2) HIL-4 Reservoirs 5000 5300 5300 4.09 70194.454 HIL-4 Wetland Hardwood Forests 6000 6100 6100 1.00 111413.08 HIL-4 Mixed Wetland Hardwoods Mixed Shrubs 6000 6100 6172 1.00 13594.419 HIL-4 Freshwater Marshes 6000 6400 6410 1.00 13056.659 HIL-4 Wet Prairies 6000 6400 6430 1.00 4311.2752 HIL-4 Emergent Aquatic Ve getation 6000 6400 6440 1.00 6696.6415 HIL-4 Disturbed Lands 7000 7400 7400 4.09 322.21467 HIL-4 Transportation 8000 8100 8100 7.81 141969.9 HIL-4 Utilities 8000 8300 8300 8.32 13532.158 HIL-5 Residential, Low Density 1000 1100 1100 6.79 394098.55 HIL-5 Residential, Medium Density 1000 1200 1200 7.59 316616.89 HIL-5 Residential, High Density 1000 1300 1300 8.66 518076.75 HIL-5 Commercial and Services 1000 1400 1400 8.00 28859.891 HIL-5 Industrial 1000 1500 1500 8.32 25336.661 HIL-5 Extractive 1000 1600 1600 8.32 996969.39 HIL-5 Recreational 1000 1800 1800 4.09 327157.92 HIL-5 Other Open Land 1000 1900 1940 1.85 92877.063 HIL-5 Pastures and Fields 2000 2100 2100 3.51 2195553.5 HIL-5 Tree Crops 2000 2200 2200 4.06 11681.442 HIL-5 Specialty Farms 2000 2500 2500 4.06 196848.24 HIL-5 Other Open Lands 2000 2600 2600 2.06 208834.97 HIL-5 Shrub and Brushland 3000 3200 3200 2.06 895488.83 HIL-5 Upland Coniferous Forests 4000 4100 4100 1.00 36183.116 HIL-5 Pine Flatwoods or Mesi c Flatwoods 4000 4100 4110 1.00 443756.87 HIL-5 Hardwood Conifer Mixed 4000 4300 4340 1.00 1090666.5 HIL-5 Tree Plantations 4000 4400 4400 1.58 242459.21 HIL-5 Streams and Waterways 5000 5100 5100 1.00 31393.902 HIL-5 Lakes 5000 5200 5200 1.00 1548.3869 HIL-5 Reservoirs 5000 5300 5300 4.09 92748.65 HIL-5 Wetland Hardwood Forests 6000 6100 6100 1.00 125288.56 HIL-5 Bottomland Hardwood Forest 6000 6100 6150 1.00 5971996.8 HIL-5 Wetland Coniferous Forests 6000 6200 6200 1.00 343464.99 HIL-5 Cypress 6000 6200 6210 1.00 690591.84 HIL-5 Freshwater Marshes 6000 6400 6410 1.00 517490.07 HIL-5 Wet Prairies 6000 6400 6430 1.00 47648.132 HIL-5 Emergent Aquatic Ve getation 6000 6400 6440 1.00 27356.268 HIL-5 Transportation 8000 8100 8100 7.81 89907.839 HIL-6 Residential, Low Density 1000 1100 1100 6.79 207101.41

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94 Appendix A (Continued) Site Land Use FLUCC Code Level I FLUCC Code Level II FLUUCS Code Land Use Coeff. Total Area (m2) HIL-6 Commercial and Services 1000 1400 1400 8.00 7108.4487 HIL-6 Recreational 1000 1800 1800 4.09 319.95671 HIL-6 Pastures and Fields 2000 2100 2100 3.51 135231.46 HIL-6 Hardwood Conifer Mixed 4000 4300 4340 1.00 48884.646 HIL-6 Reservoirs 5000 5300 5300 4.09 5773.0507 HIL-6 Wetland Hardwood Forests 6000 6100 6100 1.00 4820.7962 HIL-6 Bottomland Hardwood Forest 6000 6100 6150 1.00 87996.433 HIL-6 Cypress 6000 6200 6210 1.00 14537.081 HIL-6 Freshwater Marshes 6000 6400 6410 1.00 18653.427 HIL-6 Wet Prairies 6000 6400 6430 1.00 3802.0102 HIL-6 Emergent Aquatic Ve getation 6000 6400 6440 1.00 704.04688 HIL-7 Residential, Low Density 1000 1100 1100 6.79 94573.227 HIL-7 Residential, Medium Density 1000 1200 1200 7.59 133495.37 HIL-7 Residential, High Density 1000 1300 1300 8.66 671131.69 HIL-7 Commercial and Services 1000 1400 1400 8.00 247569.83 HIL-7 Institutional 1000 1700 1700 8.07 4098.5562 HIL-7 Recreational 1000 1800 1800 4.09 13496.567 HIL-7 Other Open Land 1000 1900 1940 1.85 11759.91 HIL-7 Pastures and Fields 2000 2100 2100 3.51 407192.06 HIL-7 Specialty Farms 2000 2500 2500 4.06 227206.38 HIL-7 Other Open Lands 2000 2600 2600 2.06 465123.46 HIL-7 Shrub and Brushland 3000 3200 3200 2.06 479097.92 HIL-7 Upland Coniferous Forests 4000 4100 4100 1.00 23526.337 HIL-7 Pine Flatwoods or Mesi c Flatwoods 4000 4100 4110 1.00 179134.67 HIL-7 Hardwood Conifer Mixed 4000 4300 4340 1.00 126167.26 HIL-7 Streams and Waterways 5000 5100 5100 1.00 14013.474 HIL-7 Reservoirs 5000 5300 5300 4.09 110637.28 HIL-7 Wetland Coniferous Forests 6000 6200 6200 1.00 12162.855 HIL-7 Freshwater Marshes 6000 6400 6410 1.00 34670.047 HIL-7 Wet Prairies 6000 6400 6430 1.00 56953.816 HIL-7 Disturbed Lands 7000 7400 7400 4.09 18304.171 HIL-7 Transportation 8000 8100 8100 7.81 159869.79 HIL-7 Utilities 8000 8300 8300 8.32 218514.66 HIL-8 Shrub and Brushland 3000 3200 3200 2.06 34055.778 HIL-8 Pine Flatwoods or Mesi c Flatwoods 4000 4100 4110 1.00 16510.836 HIL-8 Hardwood Conifer Mixed 4000 4300 4340 1.00 34851.584 HIL-8 Wet Prairies 6000 6400 6430 1.00 10741.891 HIL-9 Residential, Low Density 1000 1100 1100 6.79 81838.278 HIL-9 Extractive 1000 1600 1600 8.32 579870.8

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95 Appendix A (Continued) Site Land Use FLUCC Code Level I FLUCC Code Level II FLUUCS Code Land Use Coeff. Total Area (m2) HIL-9 Other Open Land 1000 1900 1940 1.85 26114.404 HIL-9 Pastures and Fields 2000 2100 2100 3.51 877142.53 HIL-9 Row Crops 2000 2100 2140 4.63 313127.74 HIL-9 Nurseries and Vineyards 2000 2400 2400 4.06 5860.5774 HIL-9 Tropical Fish Farms 2000 2500 2550 5.15 36136.794 HIL-9 Shrub and Brushland 3000 3200 3200 2.06 123160.77 HIL-9 Pine Flatwoods or Mesi c Flatwoods 4000 4100 4110 1.00 180621.33 HIL-9 Hardwood Conifer Mixed 4000 4300 4340 1.00 225452.7 HIL-9 Reservoirs 5000 5300 5300 4.09 110597.32 HIL-9 Bottomland Hardwood Forest 6000 6100 6150 1.00 1838776.7 HIL-9 Freshwater Marshes 6000 6400 6410 1.00 83145.647 HIL-9 Wet Prairies 6000 6400 6430 1.00 2657.2139 HIL-9 Emergent Aquatic Ve getation 6000 6400 6440 1.00 4977.9042 HIL-10 Extractive 1000 1600 1600 8.32 31205.763 HIL-10 Pastures and Fields 2000 2100 2100 3.51 19.076471 HIL-10 Row Crops 2000 2100 2140 4.63 300317.51 HIL-10 Tropical Fish Farms 2000 2500 2550 5.15 36136.877 HIL-10 Shrub and Brushland 3000 3200 3200 2.06 3169.5782 HIL-10 Hardwood Conifer Mixed 4000 4300 4340 1.00 93494.231 HIL-10 Reservoirs 5000 5300 5300 4.09 1645.9179 HIL-10 Bottomland Hardwood Forest 6000 6100 6150 1.00 405017.15 HIL-10 Freshwater Marshes 6000 6400 6410 1.00 4984.1752 HIL-10 Emergent Aquatic Ve getation 6000 6400 6440 1.00 1623.0436 HIL-11 Residential, Low Density 1000 1100 1100 6.79 1575.1535 HIL-11 Other Open Land 1000 1900 1940 1.85 14527.211 HIL-11 Pastures and Fields 2000 2100 2100 3.51 3714970.5 HIL-11 Row Crops 2000 2100 2140 4.63 766952.6 HIL-11 Tree Crops 2000 2200 2200 4.06 970982.66 HIL-11 Tropical Fish Farms 2000 2500 2550 5.15 4167.1185 HIL-11 Herbaceous 3000 3100 3100 2.06 32671.283 HIL-11 Shrub and Brushland 3000 3200 3200 2.06 1590687.5 HIL-11 Mixed Rangeland 3000 3300 3300 2.06 65657.966 HIL-11 Upland Coniferous Forests 4000 4100 4100 1.00 13195.292 HIL-11 Pine Flatwoods or Mesi c Flatwoods 4000 4100 4110 1.00 890633.11 HIL-11 Upland Hardwood Forests 4000 4200 4200 1.00 7233.4841 HIL-11 Hardwood Conifer Mixed 4000 4300 4340 1.00 931002.68 HIL-11 Reservoirs 5000 5300 5300 4.09 28271.351 HIL-11 Bottomland Hardwood Forest 6000 6100 6150 1.00 6410783.4 HIL-11 Wetland Coniferous Forests 6000 6200 6200 1.00 18784.265 HIL-11 Cypress 6000 6200 6210 1.00 88718.112 HIL-11 Freshwater Marshes 6000 6400 6410 1.00 226309.52 HIL-11 Wet Prairies 6000 6400 6430 1.00 169213.24

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96 Appendix A (Continued) Site Land Use FLUCC Code Level I FLUCC Code Level II FLUUCS Code Land Use Coeff. Total Area (m2) HIL-11 Emergent Aquatic Ve getation 6000 6400 6440 1.00 8528.3823 HIL-11 Transportation 8000 8100 8100 7.81 8849.5754 MAN-1 Pastures and Fields 2000 2100 2100 3.51 6596.1826 MAN-1 Tree Crops 2000 2200 2200 4.06 13100.616 MAN-1 Shrub and Brushland 3000 3200 3200 2.06 449079.58 MAN-1 Lakes 5000 5200 5200 1.00 1298.9011 MAN-1 Reservoirs 5000 5300 5300 4.09 853.8375 MAN-1 Bottomland Hardwood Forest 6000 6100 6150 1.00 13279.696 MAN-1 Freshwater Marshes 6000 6400 6410 1.00 555069.66 MAN-1 Wet Prairies 6000 6400 6430 1.00 223147.92 MAN-2 Residential, Low Density 1000 1100 1100 6.79 2057.04 MAN-2 Residential, Medium Density 1000 1200 1200 7.59 33269.686 MAN-2 Residential, High Density 1000 1300 1300 8.66 409293.85 MAN-2 Commercial and Services 1000 1400 1400 8.00 314301.32 MAN-2 Recreational 1000 1800 1800 4.09 89725.468 MAN-2 Other Open Lands 2000 2600 2600 2.06 3776.6216 MAN-2 Streams and Waterways 5000 5100 5100 1.00 5125.6063 MAN-2 Reservoirs 5000 5300 5300 4.09 3854.0894 MAN-2 Bottomland Hardwood Forest 6000 6100 6150 1.00 17069.604 MAN-2 Transportation 8000 8100 8100 7.81 16443.235 MAN-3 Residential, Low Density 1000 1100 1100 6.79 208024.74 MAN-3 Residential, Medium Density 1000 1200 1200 7.59 8927.0862 MAN-3 Residential, High Density 1000 1300 1300 8.66 22875.597 MAN-3 Extractive 1000 1600 1600 8.32 275699.12 MAN-3 Recreational 1000 1800 1800 4.09 124420.01 MAN-3 Other Open Land 1000 1900 1940 1.85 12742.744 MAN-3 Pastures and Fields 2000 2100 2100 3.51 793419 MAN-3 Row Crops 2000 2100 2140 4.63 446156.48 MAN-3 Feeding Operations 2000 2300 2300 5.15 176251.43 MAN-3 Other Open Lands 2000 2600 2600 2.06 99171.916 MAN-3 Shrub and Brushland 3000 3200 3200 2.06 199978.84 MAN-3 Upland Coniferous Forests 4000 4100 4100 1.00 10444.616 MAN-3 Pine Flatwoods or Mesi c Flatwoods 4000 4100 4110 1.00 286928.95 MAN-3 Hardwood Conifer Mixed 4000 4300 4340 1.00 244461.95 MAN-3 Reservoirs 5000 5300 5300 4.09 37164.572 MAN-3 Bottomland Hardwood Forest 6000 6100 6150 1.00 320116.97 MAN-3 Cypress 6000 6200 6210 1.00 10049.837

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97 Appendix A (Continued) Site Land Use FLUCC Code Level I FLUCC Code Level II FLUUCS Code Land Use Coeff. Total Area (m2) MAN-3 Freshwater Marshes 6000 6400 6410 1.00 334871.06 MAN-3 Wet Prairies 6000 6400 6430 1.00 50020.913 MAN-3 Emergent Aquatic Ve getation 6000 6400 6440 1.00 773.96845 MAN-3 Transportation 8000 8100 8100 7.81 69365.49 MAN-3 Utilities 8000 8300 8300 8.32 24347.971 PAS-1 Residential, Low Density 1000 1100 1100 6.79 18873.929 PAS-1 Residential, Medium Density 1000 1200 1200 7.59 72040.837 PAS-1 Residential, High Density 1000 1300 1300 8.66 263783.53 PAS-1 Commercial and Services 1000 1400 1400 8.00 15364.252 PAS-1 Recreational 1000 1800 1800 4.09 153240.89 PAS-1 Other Open Land 1000 1900 1940 1.85 33114.96 PAS-1 Pastures and Fields 2000 2100 2100 3.51 404273.09 PAS-1 Other Open Lands 2000 2600 2600 2.06 75620.87 PAS-1 Shrub and Brushland 3000 3200 3200 2.06 11525.723 PAS-1 Upland Coniferous Forests 4000 4100 4100 1.00 693.17876 PAS-1 Pine Flatwoods or Mesi c Flatwoods 4000 4100 4110 1.00 664618.68 PAS-1 Reservoirs 5000 5300 5300 4.09 19702.82 PAS-1 Bottomland Hardwood Forest 6000 6100 6150 1.00 2166514.8 PAS-1 Wetland Coniferous Forests 6000 6200 6200 1.00 6177.9626 PAS-1 Cypress 6000 6200 6210 1.00 26375.67 PAS-1 Freshwater Marshes 6000 6400 6410 1.00 36659.585 PAS-1 Wet Prairies 6000 6400 6430 1.00 13512.952 PAS-2 Pastures and Fields 2000 2100 2100 3.51 16502.045 PAS-2 Hardwood Conifer Mixed 4000 4300 4340 1.00 6055.2146 PAS-2 Streams and Waterways 5000 5100 5100 1.00 7755.5175 PAS-2 Bottomland Hardwood Forest 6000 6100 6150 1.00 17001.945 PAS-3 Residential, Low Density 1000 1100 1100 6.79 66763.983 PAS-3 Residential, Medium Density 1000 1200 1200 7.59 39658.338 PAS-3 Commercial and Services 1000 1400 1400 8.00 55628.623 PAS-3 Recreational 1000 1800 1800 4.09 1746.6295 PAS-3 Other Open Land 1000 1900 1940 1.85 26039.509 PAS-3 Pastures and Fields 2000 2100 2100 3.51 459622.14 PAS-3 Shrub and Brushland 3000 3200 3200 2.06 75257.372 PAS-3 Upland Coniferous Forests 4000 4100 4100 1.00 19630.382 PAS-3 Pine Flatwoods or Mesi c Flatwoods 4000 4100 4110 1.00 253054.24 PAS-3 Pine Mesic Oak 4000 4100 4140 1.00 69365.055 PAS-3 Hardwood Conifer Mixed 4000 4300 4340 1.00 296771.37 PAS-3 Tree Plantations 4000 4400 4400 1.58 235.36299

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98 Appendix A (Continued) Site Land Use FLUCC Code Level I FLUCC Code Level II FLUUCS Code Land Use Coeff. Total Area (m2) PAS-3 Streams and Waterways 5000 5100 5100 1.00 30256.273 PAS-3 Lakes 5000 5200 5200 1.00 237751.58 PAS-3 Wetland Hardwood Forests 6000 6100 6100 1.00 93775.468 PAS-3 Bottomland Hardwood Forest 6000 6100 6150 1.00 797738.67 PAS-3 Wetland Coniferous Forests 6000 6200 6200 1.00 4843.1828 PAS-3 Cypress 6000 6200 6210 1.00 314267.48 PAS-3 Freshwater Marshes 6000 6400 6410 1.00 472672.44 PAS-3 Wet Prairies 6000 6400 6430 1.00 1336588.1 PAS-3 Emergent Aquatic Ve getation 6000 6400 6440 1.00 756448.75 PAS-4 Residential, Low Density 1000 1100 1100 6.79 18253.189 PAS-4 Residential, High Density 1000 1300 1300 8.66 41817.535 PAS-4 Recreational 1000 1800 1800 4.09 23269.552 PAS-4 Other Open Lands 2000 2600 2600 2.06 4791.2946 PAS-4 Upland Coniferous Forests 4000 4100 4100 1.00 8298.8856 PAS-4 Hardwood Conifer Mixed 4000 4300 4340 1.00 141706.15 PAS-4 Tree Plantations 4000 4400 4400 1.58 29701.799 PAS-4 Reservoirs 5000 5300 5300 4.09 2974.5896 PAS-4 Bottomland Hardwood Forest 6000 6100 6150 1.00 344309.86 PAS-4 Freshwater Marshes 6000 6400 6410 1.00 2312.3331 PAS-4 Wet Prairies 6000 6400 6430 1.00 2039.7336 PAS-5 Residential, High Density 1000 1300 1300 8.66 259787.58 PAS-5 Recreational 1000 1800 1800 4.09 153240.89 PAS-5 Other Open Land 1000 1900 1940 1.85 32971.232 PAS-5 Pastures and Fields 2000 2100 2100 3.51 184555.31 PAS-5 Other Open Lands 2000 2600 2600 2.06 38377.723 PAS-5 Shrub and Brushland 3000 3200 3200 2.06 100112.79 PAS-5 Upland Coniferous Forests 4000 4100 4100 1.00 693.17876 PAS-5 Pine Flatwoods or Mesi c Flatwoods 4000 4100 4110 1.00 845758.19 PAS-5 Reservoirs 5000 5300 5300 4.09 13436.965 PAS-5 Bottomland Hardwood Forest 6000 6100 6150 1.00 2445514.3 PAS-5 Wetland Coniferous Forests 6000 6200 6200 1.00 6177.9626 PAS-5 Cypress 6000 6200 6210 1.00 314204.26 PAS-5 Freshwater Marshes 6000 6400 6410 1.00 34803.354 PAS-5 Wet Prairies 6000 6400 6430 1.00 5187.3811 PIN-1 Residential, Low Density 1000 1100 1100 6.79 2984.2955 PIN-1 Residential, Medium Density 1000 1200 1200 7.59 111640.54 PIN-1 Residential, High Density 1000 1300 1300 8.66 622904.18 PIN-1 Commercial and Services 1000 1400 1400 8.00 317304.3 PIN-1 Industrial 1000 1500 1500 8.32 58228.677

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99 Appendix A (Continued) Site Land Use FLUCC Code Level I FLUCC Code Level II FLUUCS Code Land Use Coeff. Total Area (m2) PIN-1 Institutional 1000 1700 1700 8.07 20181.514 PIN-1 Recreational 1000 1800 1800 4.09 485.15483 PIN-1 Upland Coniferous Forests 4000 4100 4100 1.00 43970.217 PIN-1 Hardwood Conifer Mixed 4000 4300 4340 1.00 32863.48 PIN-1 Lakes 5000 5200 5200 1.00 17155.079 PIN-1 Reservoirs 5000 5300 5300 4.09 18289.497 PIN-1 Bottomland Hardwood Forest 6000 6100 6150 1.00 25597.411 PIN-1 Freshwater Marshes 6000 6400 6410 1.00 11434.21 PIN-1 Transportation 8000 8100 8100 7.81 49695.954 PIN-1 Utilities 8000 8300 8300 8.32 45744.383 PIN-2 Residential, Low Density 1000 1100 1100 6.79 29983.96 PIN-2 Residential, Medium Density 1000 1200 1200 7.59 29851.893 PIN-2 Residential, High Density 1000 1300 1300 8.66 341793.57 PIN-2 Commercial and Services 1000 1400 1400 8.00 138418.48 PIN-2 Industrial 1000 1500 1500 8.32 34009.784 PIN-2 Other Open Lands 2000 2600 2600 2.06 67809.102 PIN-2 Pine Flatwoods or Mesi c Flatwoods 4000 4100 4110 1.00 59517.248 PIN-2 Hardwood Conifer Mixed 4000 4300 4340 1.00 19015.797 PIN-2 Reservoirs 5000 5300 5300 4.09 26631.561 PIN-2 Wetland Hardwood Forests 6000 6100 6100 1.00 3445.4238 PIN-2 Bottomland Hardwood Forest 6000 6100 6150 1.00 20387.758 PIN-2 Freshwater Marshes 6000 6400 6410 1.00 1245.8583 PIN-2 Transportation 8000 8100 8100 7.81 55752.133 PIN-2 Utilities 8000 8300 8300 8.32 20974.459 PIN-3 Residential, High Density 1000 1300 1300 8.66 109469.69 PIN-3 Commercial and Services 1000 1400 1400 8.00 11925.313 PIN-3 Reservoirs 5000 5300 5300 4.09 5102.2832 POL-1 Residential, Low Density 1000 1100 1100 6.79 51932.521 POL-1 Residential, Medium Density 1000 1200 1200 7.59 579818.65 POL-1 Residential, High Density 1000 1300 1300 8.66 541346.1 POL-1 Commercial and Services 1000 1400 1400 8.00 66836.434 POL-1 Industrial 1000 1500 1500 8.32 151275.17 POL-1 Extractive 1000 1600 1600 8.32 317481.02 POL-1 Institutional 1000 1700 1700 8.07 40547.45 POL-1 Recreational 1000 1800 1800 4.09 341007.89 POL-1 Pastures and Fields 2000 2100 2100 3.51 519752.01 POL-1 Other Open Lands 2000 2600 2600 2.06 313034.73 POL-1 Shrub and Brushland 3000 3200 3200 2.06 2448.6147

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100 Appendix A (Continued) Site Land Use FLUCC Code Level I FLUCC Code Level II FLUUCS Code Land Use Coeff. Total Area (m2) POL-1 Mixed Rangeland 3000 3300 3300 2.06 619.22005 POL-1 Hardwood Conifer Mixed 4000 4300 4340 1.00 308837.32 POL-1 Streams and Waterways 5000 5100 5100 1.00 17039.833 POL-1 Lakes 5000 5200 5200 1.00 326422.64 POL-1 Reservoirs 5000 5300 5300 4.09 76788.566 POL-1 Wetland Hardwood Forests 6000 6100 6100 1.00 265339.35 POL-1 Bottomland Hardwood Forest 6000 6100 6150 1.00 202512.87 POL-1 Freshwater Marshes 6000 6400 6410 1.00 49374.517 POL-1 Wet Prairies 6000 6400 6430 1.00 2907.9548 POL-1 Emergent Aquatic Ve getation 6000 6400 6440 1.00 31683.677 POL-1 Transportation 8000 8100 8100 7.81 237384.47 POL-1 Utilities 8000 8300 8300 8.32 65371.213 POL-2 Residential, Low Density 1000 1100 1100 6.79 138749.49 POL-2 Residential, Medium Density 1000 1200 1200 7.59 1102147.4 POL-2 Residential, High Density 1000 1300 1300 8.66 314461.66 POL-2 Commercial and Services 1000 1400 1400 8.00 134003.82 POL-2 Extractive 1000 1600 1600 8.32 981998.43 POL-2 Institutional 1000 1700 1700 8.07 139851.48 POL-2 Recreational 1000 1800 1800 4.09 432495.44 POL-2 Pastures and Fields 2000 2100 2100 3.51 201706.78 POL-2 Lakes 5000 5200 5200 1.00 1638227 POL-2 Reservoirs 5000 5300 5300 4.09 763754.78 POL-2 Bottomland Hardwood Forest 6000 6100 6150 1.00 6831.5392 POL-2 Freshwater Marshes 6000 6400 6410 1.00 7746.6639 POL-2 Emergent Aquatic Ve getation 6000 6400 6440 1.00 26130.051 POL-2 Utilities 8000 8300 8300 8.32 82616.927 POL-3 Residential, Low Density 1000 1100 1100 6.79 6142.5118 POL-3 Other Open Land 1000 1900 1940 1.85 6965.5704 POL-3 Tree Crops 2000 2200 2200 4.06 271147.03 POL-3 Shrub and Brushland 3000 3200 3200 2.06 111807.27 POL-3 Upland Coniferous Forests 4000 4100 4100 1.00 2439.47 POL-3 Pine Flatwoods or Mesi c Flatwoods 4000 4100 4110 1.00 639745.37 POL-3 Hardwood Conifer Mixed 4000 4300 4340 1.00 135699.69 POL-3 Lakes 5000 5200 5200 1.00 1581619.6 POL-3 Bay Swamps 6000 6100 6110 1.00 1873.253 POL-3 Bottomland Hardwood Forest 6000 6100 6150 1.00 3134160.9 POL-3 Freshwater Marshes 6000 6400 6410 1.00 15775.901 POL-3 Wet Prairies 6000 6400 6430 1.00 17348.341

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101 Appendix A (Continued) Site Land Use FLUCC Code Level I FLUCC Code Level II FLUUCS Code Land Use Coeff. Total Area (m2) POL-3 Emergent Aquatic Ve getation 6000 6400 6440 1.00 2946.8974 POL-4 Residential, Low Density 1000 1100 1100 6.79 169487.3 POL-4 Residential, Medium Density 1000 1200 1200 7.59 890858.33 POL-4 Residential, High Density 1000 1300 1300 8.66 23395.488 POL-4 Commercial and Services 1000 1400 1400 8.00 8895.8554 POL-4 Industrial 1000 1500 1500 8.32 44833.447 POL-4 Institutional 1000 1700 1700 8.07 6068.2736 POL-4 Recreational 1000 1800 1800 4.09 58636.902 POL-4 Other Open Land 1000 1900 1940 1.85 50836.399 POL-4 Pastures and Fields 2000 2100 2100 3.51 834192.24 POL-4 Unimproved Pastures 2000 2100 2120 2.06 1139.5766 POL-4 Tree Crops 2000 2200 2200 4.06 662997.28 POL-4 Citrus Groves 2000 2200 2210 4.06 41961.949 POL-4 Dairies 2000 2500 2520 5.15 82226.457 POL-4 Other Open Lands 2000 2600 2600 2.06 10649.299 POL-4 Shrub and Brushland 3000 3200 3200 2.06 481196.5 POL-4 Other Shrubs and Brush 3000 3200 3290 2.06 3493.7209 POL-4 Pine Flatwoods or Mesi c Flatwoods 4000 4100 4110 1.00 623766.24 POL-4 Hardwood Conifer Mixed 4000 4300 4340 1.00 17468.857 POL-4 Hardwood Conifer Mixed 4000 4300 4340 1.00 309811.33 POL-4 Lakes 5000 5200 5200 1.00 19884528 POL-4 Reservoirs 5000 5300 5300 4.09 39310.909 POL-4 Bay Swamps 6000 6100 6110 1.00 68730.221 POL-4 Bottomland Hardwood Forest 6000 6100 6150 1.00 3872203.5 POL-4 Mixed Wetland Hardwoods Mixed Shrubs 6000 6100 6172 1.00 1309.1105 POL-4 Freshwater Marshes 6000 6400 6410 1.00 1390218 POL-4 Wet Prairies 6000 6400 6430 1.00 166761.57 POL-4 Emergent Aquatic Ve getation 6000 6400 6440 1.00 145910.79 POL-4 Utilities 8000 8300 8300 8.32 8352.4423