# Site

- Specific Information in Support of Establishing Numeric Nutrient

Criteria for the Springs Coast

Florida Department of Environmental Protection Tallahassee, FL 32399

August 20, 2010Draft ii August 2010 

### Table of Contents

Executive Summary

............................................................................................................... 1 Geographic and Physical Description

..................................................................................... 4 Sources of Nutrients

.............................................................................................................. 8 Ground Water, Springs, and Spring

- fed Rivers

................................................................................. 8 Wetlands and Wildlife

.................................................................................................................. 10 Atmospheri c Deposition

................................................................................................................ 10 Offshore Spring Vents

................................................................................................................... 13
Coastal Currents

........................................................................................................................... 15 

### Biological Summa ry
............................................................................................................. 16

Submersed Aquatic Vegetation and Species Composition

.............................................................. 16 Epiphyte Loads on Seagrass

.......................................................................................................... 29 Phytoplankton Species Composition

.............................................................................................. 29 Macroalgal Species Composition and Biomass (Including Calcareous Forms)

.................................. 30 Depth to Seagrass Targets

............................................................................................................ 30 Presence and Frequency of Harm ful Algal Blooms

......................................................................... 30 Coral or Hardbottom Community Structure and Areal Extent

......................................................... 31 Shellfish Production and Frequency/Duration of Bed Closures

........................................................ 34 Quantification of Landings from Commercial/Recreational Fisheries

.............................................. 35 Existing Local Biological Indices

.................................................................................................... 37 Hypoxia

................................................................................................ ....................................... 37 

### Water Quality Studies

......................................................................................................... 37 Anclote River Estuary Studies 1970s

.............................................................................................. 38 MML Study of Selected Rivers, 1984

– 85

........................................................................................ 38 Project COAST, 1997

– Present

........................................................................................................ 41 MML Intensive Study of the Chassahowitzka NWR, 1996

– 2001

...................................................... 52 Random Sampling by IMAP through the FWRI

............................................................................... 60 

### Waters on the 303(d) List

..................................................................................................... 61 Proposed Numeric Nutrient Criteria

..................................................................................... 63 References 68 Appendix A. Water Quality Data Plots from Entire Record of Project COAST Data

................ 72 Appendix B. Annual Geometric Mean Chlorophyll a (Uncorrected) and TN from Project COAST

............................................................................................................. 80 Appendix C. Relationship between Salinity and Annual Geometric Mean TN per Site in 8 Coastal Areas of Project COAST.

....................................................................... 93Draft iii August 2010 

### Appendix D. Data Comparisons between Providers

............................................................. 97Draft iv August 2010 

### List of Tables

Table 1a. Checklist of nutrient enrichment symptoms in the Springs Coast

................................................ 2 Table 1b. Checklist of additional factors in the Springs Coast

..................................................................... 3 Table 2. Land use in selected springsheds depicted in Figure 3 (SWFWMD 2007 land use)

........................ 9 Table 3. Land use in the Pithlachascotee and Anclote River watersheds (SWFWMD 2004 and 2007 l and use).

............................................................................................................................ 9 Table 4. Annual load estimates for TP and TN for two spring

- fed rivers along the Springs Coast. Estimates were calculated based on annual mean nutrient concentrations from bimonthly sampling at 1 SWFWMD site on each river (site as indicated in table) and mean annual discharge at USGS gauge stations (SWFWMD).

................................................... 9 Table 5. Estimates of seagrass coverage along the Springs Coast to approximately 15 miles offshore, from the interpretation of 2007 digital imagery (SWFWMD; Kolasa 2010). Shown are acres and percent of total area comprised by various bottom habitats within 4 regions.

....................................................................................................................... 16 Table 6. Comparison of seagrass acreage estimated for the Springs Coast in 1985 and 2007 (from Kolasa and Craw 2009).

.................................................................................................. 17 Table 7. Summary of observations of seagrass species at 188 sampling locations in the Big Bend and Springs Coast regions. The depths represent the maximum depth at which each species was observed. The depths listed in the 1974

– 1980 column were determined from the depths measured in the 2000 study (from Hal e et al. 2004).

.................................... 22 Table 8. Regional Braun

- Blanquet statistics by sampling for the entire coastal study area in the MML study of the Chassahowitzka NWR (30 stations) (Table 5 in Toutant et al. 2004).

......... 24 Table 9. Macroalgal species occurrence in St. Martins Mar sh, 1998

– 2009, sampled by Aquatic Preserve staff. Shown is the number of sampling quadrats in which that species was present, of 100 total quadrats sampled per year. The sampling program and methods are described in the section on SAV and species composi tion.

.................................. 31 Table 10. Summary water clarity data for estuarine sites sampled off three Springs Coast rivers by MML, 1984

– 85. Values presented at mean/standard deviation (from Dixon 1986).

......... 39 Table 11. Annual geometric mean TN and chlorophyll a (uncorrected) from the 1984

– 85 MML study of the Weeki Wachee and Crystal Rivers.

....................................................................... 39 Table 12. Summary of data analysis for coastal areas of Citrus and Hernando Counties combined (33 stations) and Pasco County (39 stations), 1997

– 2006.

...................................................... 49 Table 13. Summary of data analysis for Pasco County stations grouped by salinity, 1997

– 2006. “salinity<25” represents 13 stations, “salinity 25

- 30” represents 19 stations, and “salinity>30” represents 7 stations.

.......................................................................................... 50 Table 14. Sample sizes for sites and years for FDEP’s analysis of the MML study of the Chassahowitzka NWR.

.............................................................................................................. 56 Table 15. Summary of data analysis for coastal areas of the Chassahowitzka NWR, 1997

–

2004 (12 stations). The first table contains only station years with at least 4 samples; the second table contains all station years (range 1 to 6 samples per station year; mean 3.6 samples per station year). Data collected and analyzed by MML.

.................................... 59 Table 16. Summary of data analysis for coastal areas of the Chassahowitzka NWR, 1997

–

2004, with stations divided by mean salinity (5 stations < 20 ppt; 7 stations > 20 ppt). EachDraft v August 2010 salinity category contains tables for which only station years with at least 4 samples were included, and tables for which all station years were included (range 1 to 6 samples per station year; mean 3.6 samples per station year). Data collected and analyzed by MML.

..................................................................................................................... 60 Table 17. Mean values by area and year for IMAP sampling in the region of the Crystal River Estuary (data from FDEP IWR Run 40). Samples for chlorophyll a were depth integrated; others were surface grabs.

.................................................................................... 61 Table 18. Waterbody IDs within the marine portions of the Springs Coast region that are listed on the 303(d) list of impaired wa ters.

........................................................................................... 61 Table 19. Mean and standard deviations of site annual geometric means, summarized by subregion and salinity range. Note that fewer than ten sites are reported for some subregions because freshwater sites were not included. N = sample size, SD = standard deviation

.................................................................................................................... 63 Table 20. Proposed numeric nutrient criteria for all segments of Springs Coast, including TP, TN, and chlorophyll a. For compliance purposes, the long term geometric mean shall not exceed the long term limit nor shall the average of all stations in a segment exceed the network average more than twice in a 5 year period. The last column shows the value which single station shall not exceed, by segment, more than twice in a 5 year period.

................................................................................................ ....................................... 66



### List of Figures

Figure 1. Map of the Springs Coast, showing managed areas (areas that are discussed are labeled) and mapped seagrass coverage (2007, limited to 15 miles offshore).

......................... 5 Figure 2. Springs Coast coastal WBIDs contained within USGS HUC 35.

.................................................... 7 Figure 3. Aquatic features of the Springs Coast, including major waterways, springs, delineated springsheds, and coastal bathymetry. Note the very shallow nature of the nearshore area. Major springsheds delineated by the SWFWMD.

........................................................... 11 Figure 4. Aquifer vulnerability in spring areas (Figure 16 in Harrington et al. 2010)

................................ 12 Figure 5. Atmospheric deposition of inorganic N (nitrate and ammonium nitrogen) by quarter at the Chassahowitzka NWR (NADP FL05) (from Dixon and Estevez 2001)

.................................. 13 Figure 6. Locations of potential offshore springs in the northern half of the SWFWMD (from DeWitt 2003)

............................................................................................................................ 14 Figure 7. The average surface CDOM absorption over the West Florida Shelf for the period from June 1 to July 17, 1998, shows the southward dispersal of the Suwannee River plume. At right, a time series (May 5 to July 29, 1998) for locations along a transect through the river plume shows the variability in the modeled surface CDOM normalized by the highest value modeled for that location during the perio d (red). Similarly, 7

- day composite Sea

- viewing Wide Field

- of

- view Sensor (SeaWiFS) chlorophyll a values for the corresponding pixel locations are presented (black) as values normalized by the highest value observed during that period. Values were interpolated when cloud cover obscured retrieval (from Jolliff et al. 2003).

.................................................................... 15 Figure 8. Comparisons of 1985 and 2007 submersed aquatic vegetation (SAV) coverages for a) Crystal River region, b) Weeki Wachee region, c) Aripeka region, and d) AncloteDraft vi August 2010 region. 1985 coverage by Continental Shelf Associates (1985). 2007 coverage by Avineon Inc. and provided by SWFWMD. Dense Seagrass = 75

- 100% c over, Sparse

Medium Seagrass = 10

- 75% cover, and Patchy Seagrass polygons are areas with discontinuous patches of seagrass > 10% cover.

...................................................................... 21 Figure 9. Locations along the Springs Coast where Thalassia testudinum was present in the 1985 study, but replaced by Syringodium filiforme (S) or Halodule wrightii (H) or both species in the 2000 study. Dotted lines delineat e the 6

- meter (m) and 9

- m isobaths (from Hale et al. 2004).

............................................................................................................. 23 Figure 10. Medians and quartiles of salinity of 12 routinely sampled coastal stations in the MML study of the Chassahowitzka NWR (Figure 9 in Dixon and Estevez 2001).

............................... 25 Figure 11. Mean density for vascular SAV species by year, in the MML study of the Chassahowitzka NWR (Figure 5 in Toutant et al. 2004).

......................................................... 25 Figure 12. Mean density for rhizophytic algal species by year, in the MML study of the Chassahowitzka NWR (Figure 6 in Toutant et al. 2004).

.......................................................... 26 Figu re 13. Fixed monitoring sites in St. Martins Marsh Aquatic Preserve.

................................................ 27 Figure 14. Frequency of occurrence of seagrass species in St. Martins Marsh Aquatic Preserve, 1997

–

2009.

............................................................................................................................... 28 Figure 15. Average total seagrass coverage at St. Martins Marsh Aquatic Preserv e, 2002

– 09. AVG B&B represents the average Braun

- Blanquet ranking assigned at each of 100 sampling quadrats per year. Ranks are abundance codes ranging from1 to 5.

...................... 28 Figure 16. Average epiphyte ranking in St. Martins Marsh Aquatic Preserve, 2004

– 09. Shown are average epiphyte rankings of 100 sampled quadrats. Possible epiphyte ranks range from 1 to 4. The sampling is described in the section on submersed aquatic vegetation and species composition.

........................................................................................ 29 Figure 17. Phytoplankton concentrations by major group and by sampling, from the 1996

– 2001 MML study of the Chassahowitzka NWR (Figure 33 in Dixon and Estevez 2001).

................... 30 Figure 18. Hardbottom habitat in St. Martins Marsh Aquatic Preserve (photo from St. Martins Marsh Aquatic Preserve staff).

................................................................................................ . 32 Figure 19. Location and size of coral beds and coral reefs off the coast of a) Citrus County and b) Hernando County, generated from 2007 aerial photos (map courtesy of SWFWMD).

............ 34 Figure 20. Commercial blue crab harvest (pounds per trip) per year in Citrus, Hernando, and Pasco Counties, for the period of survey record (1995

– 2008) (from FWCC).

........................... 35 Figure 21. Commercial bait and food shrimp harvest (pounds per trip) per year in Citrus, Hernando, and Pasco Counties, for the period of survey record (1995

– 2008) (from FWCC).

................................................................................................ ...................................... 36 Figure 22. Commercial landings (pounds per trip) of grouper and mullet per year in Citrus, Hernando, and Pasco Counties, for the period of survey record (1995

– 2008) (from FWCC).

................................................................................................ ...................................... 36 Figure 23. Total commercial finfish harvest (pounds per trip) per year in Citrus, Hernando, and Pasco Counties, for the period of survey record (1995

– 2008) (from FWCC).

........................... 37 Figure 24. TN data for one site in the Weeki Wachee Estuary and one site in the Crystal River Estuary, 1984

– 85, from the MML study.

.................................................................................. 40 Figure 25. Salinity as a predictor of TN for one site in the Weeki Wachee estuary and one site in the Crystal River Estuary, 1984

– 85, from MML study.

............................................................. 40Draft vii August 2010 Figure 26. Project COAST sampling stations. Forty stations along the coast of Citrus and Hernando Counties have been sampled monthly from 1997 to the present, with 10 stations each in the Weeki Wachee, Chassahowitzka, Homosassa, and Crystal River systems. Forty station s along the coast of Pasco County have been sampled monthly from 2000 to the present, with 10 stations each in the Aripeka, Hudson, Pithlachascotee, and Anclote River regions. Colored station markers represent the mean annual geometric mean of each statio n for 1996

– 2006, calculated by FDEP.

............... 42 Figure 27. Relationship between log 10 - transformed monthly mean chlorophyll and TN and TP concentrations from all estuarine systems along the Citrus, Hernando, and Pasco County coasts (from Jacoby et al. 2009a).

................................................................................ 43 Figure 28. Trend analysis based on correlation of site data with time. Wet months were identified as June, July, August, and September (from Jacoby et al. 2009a).

........................... 44 Figure 29. Trend analysis based on correlation of site data with time. Transitional months were identified as December, January, February, and March (from Jacoby et al. 2009a).

............... 44 Figure 30. Trend analysis based on correlation of site data with time. Dry months were identified as April, May, October, and November (from Jacoby et al. 2009a).

........................ 45 Figure 31. Trend analysis based on correlation of site data with time. Wet months were identified as June, July, August, and September (from Jacoby et al. 2009b).

........................... 45 Figure 32. Trend analysis based on correlation of site data with time. Transitional months were id entified as December, January, February, and March (from Jacoby et al. 2009b).

............... 46 Figure 33. Trend analysis based on correlation of site data with time. Dry months were identified as April, May, October, and November (from Jacoby et al. 2009b).

........................ 46 Figure 34. Geometric mean TN concentrations per station for the Weeki Wachee River and coastal sites. Sites 1 and 2 are in the river, Site 3 is at the river mouth, and Sites 4 through 10 are in the coastal area.

.......................................................................................... 51 Figure 35. Location of the Weeki Wachee River and coastal sites in Project COAST.

................................ 52 Figure 36. Sampling stations in the Chassahowitzka NWR in the 1996

– 2001 MML study (from Dixon and Estevez 2001).

.......................................................................................................... 53 Figure 37. DO (means and quartiles) for stations along the riverine transect. Stations 24, 26, and 44 are in the coastal areas (from Dixon and Estevez 2001).

............................................. 54 Figure 38. Mean TN, IN, and organic nitrogen (ON) along the riverine transect, illustrating the generally conservative net behavior downstream of Station R1.7; salinity 3.5 practical salinity units (PSU) (Figu re 28 in Dixon and Estevez 2001).

...................................................... 55 Figure 39. Water quality sampling sites from the MML study of the Chassahowitzka River and

co ast, used in FDEP’s data analysis.

......................................................................................... 56 Figure 40. Mean annual salinity is positively related to annual geometric mean TN. Salinity was depressed at all stations during 1998, a year of particularly high rainfall.

.............................. 57 Figure 41. Annual geometric mean corrected chlorophyll a at Chassahowitzka River sites (R4.0

– R0.0) and Bay sites (40C

- 3) collected by MML. Very high chlorophyll a levels were measured at the bay sites in 1998 (El Niño event); stable levels in the river indicate that the increase was due to input from coastal waters.

......................................................... 57 Figure D

- 1. TP concentrations in the Weeki Wachee River, 1997

– 2009, sampled by FDEP and Project COAST.

.......................................................................................................................... 97Draft viii August 2010 Figure D

- 2. Comparison of available data for Homosassa Head Springs, sampled by FDEP and Project COAST.

.......................................................................................................................... 98 Figure D

- 3. Comparison of COAST TN data and FDEP Trend Variability NO 2+3 data from the Weeki Wachee River. Most TKN values from the FDEP data were nondetect, and thus FDEP NO 2+3 and Project COAST TN data were compared.

................................................................ . 98 Figure D

- 4. Comparison of salinity values at sites that are located close to one another in the Chassahowitzka Estuary, from the COAST and Mote Marine Lab (MML) sampling programs.

................................................................................................ .................................. 99 Figure D

- 5. Comparison of total phosphorus values at sites that are located close to one another in the Chassahowitzka Estuary, from the COAST and Mote Marine Lab (MML) sampling programs. The minimum detection limit (MDL) for the MML lab was 50 μg/L; non

- detects were plotted as 25 μg/L.

............................................................................. 99 Figure D

- 6. Comparison of chlorophyll a values at sites that are located close to one another in the Chassahowitzka Estuary, from the COAST and Mote Marine Lab (MML) sampling
programs.

................................................................................................ ................................ 100 Figure D

- 7. Comparison of total nitrogen values at sites that are located close to one another in the Chassahowitzka Estuary, from the COAST and Mote Marine Lab (MML) sampling
programs.

................................................................................................ ................................ 101 Figure D

- 8. Comparison of total phosphorus values at sites that are located close to one another in the Suwannee Estuary, from the COAST and Suwannee River Water Management District (SRWMD) sampling programs.

................................................................................... 102 Figure D

- 9. Comparison of total nitrogen values at sites that are located close to one another in the Suwannee Estuary, from the COAST and Suwannee River Water Management District (SRWMD) sampling programs.

................................................................................... 103Draft 1 August 2010 

### Executive Summary
This report was prepared by the Florida Department of Environmental Protection (FDEP), in cooperation with local scientists, to support the development of numeric nutrient criteria for the Springs Coast. The primary purpose of the proposed numeric nutrien t criteria is to protect healthy, well

- balanced natural populations of flora and fauna from the effects of excess nutrient enrichment.

The Springs Coast of Florida, encompassing the coastal areas of Citrus, Hernando, and Pasco Counties, is a low

- energy c oastline that functions like an estuary, despite the lack of physical barriers and enclosures. The region is characterized by extensive tidal marshes and swamps, with much of the coastline in conservation land, and a wide continuous seagrass bed that exte nds 15

- 30 miles offshore in some areas due to the very shallow and clear water of this coastline. Marine habitats in the area include extensive seagrass beds, patches of limestone hardbottom habitat that support macroalgal and coral communities, oyster re efs, and some mangrove areas. Submersed aquatic vegetation (SAV), which includes seagrass and macroalgae, is the most nutrient

- sensitive biological endpoint in the Springs Coast, and SAV mapping conducted in 1985, 1999, and 2007 suggests that SAV acreage and the location of the deep edge has not been degraded during that interval.
Although nitrogen (N) levels have been increasing and/or there has been ecological imbalance in recent decades in some inland spring runs in Springs Coast watersheds (Kings Bay , Homosassa, Weeki Wachee), N levels have been stable in the coastal area since the 1980s. The increased loading in freshwater systems has not been sufficient to exceed the capacity of the river and estuary to use those nutrients, and thus nutrient concentrations in the estuary have not increased. Total phosphorus (TP) concentrations have been stable or declining during that period. Nutrient limitation studies have shown that algal growth is either limited by phosphorus (P) or co

- limited by N and P in th is region. Therefore, limits for N and P are warranted. Biological data from the region suggest that the designated aquatic life use is currently being fully supported, and so the nutrient regime of the recent record ( the past 15 years) is protective of that use.

Contributors

Dr. Kellie Dixon (Mote Marine Laboratory ; Dr. Thomas K. Frazer and Dr. Chuck Jacoby (University of Florida ); Chris Zajac, Keith Kolasa, Dr. Gary Williams, Veronica Craw (Southwest Florida Water Management District) ; Melissa Charbonneau (Big Bend Seagrasses and St. Martin Marsh Aquatic Preserves) ; Nia Wellendorf (FDEP)Draft 2 August 2010 Table 1a. Checklist of nutrient enrichment symptoms in the Springs Coast

- = Empty cell/no data ; N/A = Not available Response V ariable Observed H istorically

or C urrently? Explanation Source

Low dissolved oxygen ( DO ) (hypoxia/anoxia) No None of the segments with waterbody identification numbers ( WBIDs ) within this region are listed for DO, and no reports of hypoxia or anoxia were found. F lorida 303(d) list

Reduced clarity No Plots of annual geometric mean Secchi depth from 6 to 10 years of Project COAST data show no trend

. Project COAST data from STORET Increased chlorophyll

a concentrations Yes, limited in space and time No trend is visually apparent in the data overall (Appendix B). An increasing trend in chlorophyll a was detected for wet season months at some Cryst al and Homosassa Estuary sites only , in trend analyses conducted by Jacoby et al. Jacoby et al. 2009a; Project COAST data from STORET

Phytoplankton blooms (nuisance or toxic) Yes There was a sustained bloom in 1998 following large amounts of rainfall and water from the Suwannee River extending south along the Springs Coast. This bloom was not toxic, but temporar il y increase d chlorophyll a levels. Dixon and Estevez 2001

Problematic epiphyte growth No Epiphyte rank data from St. Martins Marsh Aquatic P reserve indicate no problematic growth and no change over the sampling period from 2004 to 2009. Analysis provided by M. Charbonneau Problematic macroalgal growth No An attendee at FDEP’s February 23, 2010 public meeting shared an anecdotal account of seeing more red algae (macroalgae) nearshore; however
, that account has not been verified with data. -

S ubmerged aquatic vegetation (S AV ) community changes or loss Yes The 2000 study by J

. Hale and colleagues found some areas near the deep edge off Citrus and Hernando Counties in which Halodule or Syringodiu m had replaced Thalassia , but no cause was identified. Subsequent studies of the 1998 El Niño event suggest that the colored plume from the Suwannee R iver could have shaded those areas and caused temporary community shifts. FDEP does not think that this is an example of anthropogenic degradation caused by nutrients. Community changes were also observed along the coast of the Chassahowitzka National Wildlife Refuge (NWR)
, but those changes were attributed to an increase in fresh water in 1998 and resultant low salinity. Hale et al. 2004; J. Hale, personal communication; Toutant et al. 2004; Jolliff et al. 2003

Emergent or shoreline vegetation community changes or loss No No such reports were found in the literature. Much of the shoreline is protected as conservation land. -

Coral/hardbottom community changes or loss Unknown No information on change or loss was found in the literature. There is currently a map of hardbottom communities along the Springs Coast (Figure 18) , but no historical reference exists for comparison. -

Impacts to benthic community N/A No additional information was found other than the benthic communities listed above. -

Fish kills No - -Draft 3 August 2010 Table 1b. Checklist of additional factors in the Springs Coast

- = Empty cell/no data Nutrient Factors Observed? Explanation Source Increased nutrient loading or concentrations Yes There has been increased loading of N from some spring rivers, but loading estimates through time are not available. Trend analyses by Jacoby et al. (2009) detected some some increases in TN and TP during the wet months off the coast of Citrus County. See Appendix B for annual means. Harrington et al. 2010; Jacoby et al. 200 9a , 200 9b

Difference between nearshore and offshore levels Yes In the northern Springs Coast, nutrient levels are often higher offshore due to external sources and relatively small freshwater inputs from coastal rivers. In the southern Springs Coast, there is an expected gradient of nutrient concentrations as terrestrial river water is diluted by lower

nutrient Gulf water. Appendix B; Figure 25

Mitigating factors that could preven t nutrient expression No - -

Other significant
stressors to biological communities No - -

Natural high

nutrient episodes (e.g., seasonal or event driven) Yes During periods of extreme high rainfall (e.g., the El Niño event in 1998), water from the Suwannee River has been shown to travel along the Springs Coast and could reduce water clarity. -Draft 4 August 2010 

### Geog raphic and Physical Description
( Adapted from http://www.protectingourwater.org/ and Wolfe 1990)

The Springs Coast watershed includes coastal areas off Citrus, Hernando, and Pasco Counties, from Crystal River south to the Anclote River (Figure 1)

. It is bound on the east by the Brooksville Ridge, a sandy remnant of previous higher sea levels that is characterized by porous limestone geology, with wetlands in low

- lying areas and scattered sinkhole lakes. The whole region is contained in U.S. Geological Survey ( USGS) Hydrologic Unit Code (HUC) 35, Crystal River to St. Petersburg , and is divided into many waterbody IDs (WBIDs) for assessment by FDEP (Figure 2)

. Major cities and towns in the watershed include Port Richey, New Port Richey, Weeki Wachee, Brooksville, and Crystal River.

Much of the shoreline is preserved by local, state, or federal entities. From north to south, protected lands include the Marjorie Carr Cross Florida Greenway Trail State Recreation and Conservation Area, Crystal River Preserve State Park, St. Martins Marsh Aquatic Preserve, Chassahowitzka N ational Wildlife Re fuge
, Weeki W achee Preserve, Werner

- Boyce Salt Springs State Park, and Anclote Key Preserve State Park (Figure 1)

. Consequently, much of the coast contains intact salt marshes and mangrove forests that provide a buffer between uplands and the estuarine waters.

The six major rivers in the watershed

— Crystal, Homosassa, Chassahowitzka, Weeki Wachee, Anclote, and Pithl achascotee

— their springs, and their associated coastal aquatic resources are dominant features. The watershed contains four major spring complexes, which occur because of the region's karst geology. A spring complex is a group of springs, often spread ou t over several square miles. The springs are recharged mainly by rainfall.

The coastline has very low relief, so the nearshore areas are very shallow with low wave energy. The coast contains numerous tidal creeks and salt marshes, as well as isolated islands fringed with
mangroves. There are very few natural sandy beaches. Most of the region functions like an estuary, with its shallow waters, abundant freshwater flows, and low

- energy shoreline. Seagrass beds cover almost the entire nearshore area where depths are sufficient, and extensive oyster reefs are also present. Vast salt marshes up to ten miles wide provide a buffer between the upland land uses and the estuaries.

In the Springs Coast region , the nearshore estuarine area provides essential habitat for numerous fish and wildlife species, including nursery and juvenile habitats for many recreational and commercial fish species. The commercial seafood harvests on Florida's west coast consist of at least 95 % estuary

dependent species.

Conservation lands include the following:

**•** The Crystal River NWR comprises 20 islands and several small parcels of land. Six hundred million gallons of fresh water flow daily from more than 30 natural springs in the refuge. The springs are a natural warmwater refuge for the endangered West Indian manatee and provide critical habitat for the Crystal River herd, which makes up about 25 % of the United State s 's manatee population.Draft 5 August 2010 Figur e 1. Map of the Springs Coast, showing managed areas (areas that are discussed are labeled) and mapped seagrass coverage (2007, limited to 15 miles offshore).Draft 6 August 2010 **•** The 23, 000

- acre St. Martins Marsh Aquatic Preserve, established in 1969, is the southern terminus for migratory waterfowl of the Atlantic and Mississippi flyways. St. Martins Marsh provides stopover and wintering areas for many migratory species. DeWitt (2003) describes this preserve as “a nearly pristine area of extensive needle rush islands, sea grass meadows, and mangrove keys.”

**•** The Chassahowitzka NWR , established in 1931, comprises 31,000 acres of shallow saltwater bays, estuaries, brackish marshes, and tidal streams, with a fringe of hardwood swamps. It is accessible only by boat. This NWR is the site of a whooping crane reintroduction program that has been ongoing since 2000.

**•** Weeki Wachee Preserve contains the southernmost coastal hardwood hammock in western Florida.

**•** Starkey Wilderness Park, an 8,069

- acre tract, encompasses a portion of the headwaters of the Anclote River and a stretch of the Pithlachascotee River.

**•** Anclote Key Preserve State Park is a barrier island at the southern end of this region

. Just to the east of Anclote Key lies Anclote Anchorage, a shallow area containing

s eagrass beds that provides breeding habitat for numerous marine species. The Anclote N WR encompasses the waters between Anclote Key and the mainland.

A comprehensive description of the geology, hydrology, and ecology of the Springs Coast can be found in An Ecological Characterization of the Florida Springs Coast: Pithlachascotee to Waccasassa Rivers (Wolfe 1990).Draft 7 August 2010 Figure 2. Springs Coast c oastal WBIDs c ontained within USGS HUC 35.Draft 8 August 2010 

### Sources of Nutrients

Ground W ater, Springs , and Spring

- fed Rivers The coasts of Citrus and Hernando Counties receive the majority of their freshwater input from ground water through the major spring

- fed rivers and from diffuse ground water seeps from the karst landscape. Springs and spring runs carry ground water captured within the spring group’s springshed (Figure 3). The karst geology of this region makes the ground water very vulnerable to contamination from fertilizers, animal waste, and wastewater (Harrington et al. 2010). The landuse in the springsheds for area springs contain 23% to 45% urbanization, 9% to 25% agriculture, and 23% to 41% forest (Table 2 ). It is notable that the percent age of wetlands in the springsheds ranges from 11 % to 18%, which is low compared with neighboring watersheds to the north. The karst landscape is one reason for the low percentage of wetlands and the higher percentage of upland forests; soils are very well drained
, and thus the water goes from land into ground water. That groundwater resurfaces as spring boils and within coastal marshes. Table 3 lists the l and use distributions for the watersheds of the major rivers of Pasco County.

In 2010, the Florida Springs Initiative reported on nutrient levels in Florida’s major springs and ground water (via wells) and the causes of eleva ted nitrate levels at selected sites (Harrington et al. 2010). They reported the following median nitrate concentrations (mg/L) from 2001 to 2006 for regularly monitored spring boils along the Springs Coast: Tarpon Hole Spring (0.185) and Hunter Spring ( 0.39) of Kings Bay, Homosassa Springs #1,2,3 (0.5

- 0.54), Chassahowitzka Main and #1 (0.53 and 0.575), and Weeki Wachee Main (0.765).

Those nitrate levels are moderate compared with springs statewide, but almost all exceed the proposed nitrate criterion f or clear streams and springs of 0.35 mg/L, and all are an order of magnitude greater than estimated background conditions. Orthophosphate concentrations in these spring boils are among the lowest statewide (Harrington et al. 2010). In their report, Harri ngton et al. (2010) reported N isotope studies indicating that the most significant sources of nitrate to Weeki Wachee Springs is inorganic fertilizer from residential lawns and golf courses, as well as septic tanks. Table 4 contains annual N and P loadin g estimates from the Homosassa and Weeki Wachee Rivers. These estimates are derived from water quality and flow estimates within the spring runs rather than at the spring boil.

The only major freshwater inputs into the Pasco County coastal area are the A nclote and the Pithlachascotee Rivers, which originate in swamps and not springs. The shallow coastal area is not as wide as in the northern Springs Coast; seagrass beds extend approximately 15 miles offshore rather than the 30

- mile extent in the northern areas (K. Kolasa, personal communication, SWFWMD).

There are approximately 140 active wastewater treatment facilities in the vicinity of the Crystal, Homosassa, Chassahowitzka, Weeki Wachee, and Aripeka Spring Complexes ( FDEP website www.protecingourwat er.com, 2010). Most of these do not discharge to surface waters, but rather discharge into percolation ponds or are discharged via land application. T he soils in this region are porous and the ground water is highly vulnerable to contamination from land activities , so any land

based wastewater disposal system potentially contributes nutrients to the ground water and ultimately the springs and coastal areas (Figure 4 ; Harrington et al. 2010; Kuhnman and DeHaven 2008 ). The

c oastal areas of Hernando and Pasco Counties are similarly vulnerable to ground water contamination (Harrington et al. 2010).Draft 9 August 2010 Table 2. Land u se in s elected s pringsheds depicted in Figure 3 (SWFWMD 2007 l and u se ) Springshed Springshed Area ( square kilometers [km 2 ]) Urban and Built

Up Agriculture Upland Non

forested Upland Forests Water Wetlands Barren Land Transpo r ta

tion , Comm uni

cations, and Utilities

K ings Bay 671 45.0% 10.7% 1.4% 27.4% 2.7% 11.2% 0.2% 1.4%
H omosassa 734 22.8% 14.9% 1.3% 40.8% 1.8% 17.5% 0.3% 0.5%
Chassahowitzka 439 35.6% 13.7% 1.1% 31.3% 0.8% 15.5% 0.1% 1.9%
W eeki Wachee 719 30.9% 24.9% 2.5% 24.4% 1.3% 13.7% 0.2% 2.0%
A ripeka 110 44.6% 9.6% 1.0% 23.0% 1.7% 16.6% 0.2% 3.3%

Table 3

. Land u se in the Pithlachascotee and Anclote River w atersheds (SWFWMD 2004 and 2007 l and

u se). Land Use Anclote

2004 Land Use Pithlachascotee

2007 Land Use Urban 28.47% 22.76%

Citrus, orchards, nurseries 0.76% 1.74%

Pasture, rangeland, and other agriculture 24.69% 25.91%

Uplands 15.23% 28.37%

Wetlands 24.40% 17.07%

Water 5.74% 2.08%

Other 0.71% 2.06%

Table 4. Annual load estimates for TP and TN for two spring

- fed rivers along the Springs Coast. Estimates were calculated based on annual mean nutrient concentrations from bimonthly sampling at 1 SWFWMD site on each river (site as indicated in table) and mean an nual discharge at USGS gauge stations (SWFWMD).

Parameter Homosassa River Weeki Wachee River USGS gauge USGS 02310700 HOMOSASSA R AT HOMOSASSA FL USGS 02310525 WEEKI WACHEE RIVER Mean annual flow (cfs) 243 140

SWFWMD station Site HV

- 3 10/05

- 8/09 WEEKI WACHEE RIVER WW5 2/06

– 2/09 Mean annual TN concentration (mg/L) 0.45 0.72

Mean annual TP concentration (mg/L) 0.027 0.011

Annual TN load 97,761 90,117Draft 10 August 2010 (kg/yr) Annual TP load (kg/yr) 5,866 1,377

cfs = Cubic feet per second mg/L = Milligrams per liter kg/yr = Kilograms per year

Wetlands and Wildlife Citrus and Hernando Counties are developed along U.S. Highway 19 and along the rivers. There are, however, large areas of undeveloped salt marsh, river habitat, and low

- lying island s on the western edge of the counties towards the Gulf of Mexico. The 23,000

- acre St. Martins Marsh Aquatic Preserve, the 32,000

- acre Crystal River Preserve State Park, and the 31,000

- acre Chassahowitzka NWR are large areas that support abundant wildlife and wetland flora. The West Indian (Florida) manatee
, an endangered species , inhabits the area year

- round. Bird communities are also present in the salt marshes. Migratory waterfowl and other more permanent bird residents are found in significant numbers throughout the area. Abundant wildlife along the shoreline has the potential to increase nutrients in nearshore waters
, especially following rainfall and during coastal flood events. In addition, migratory waterfowl populations are seasonal and can be found in the uplands and marshes
, and sometimes roosting on exposed sandbars and oyster reefs. The concentration and loading of organic N into an estuary is positively correlated with the percentage of wetlands in the watershed ( F DEP stream studies ). However, coastal wetlands can also uptake land

- derived N before it reaches coastal waters (Valiela and Cole 2002).

Atmospheric Deposition Dixon and Estevez ( 2001) reported on the atmospheric deposition of inorganic nitrogen (IN) in rainfall, as measured by the National Atmospheric Deposition Program (NADP) at Chassahowitzka Site FL05 (Figure 5). They reported that the atmospheric deposition of IN directly to the waters of the Chassahowitzka NWR is nearly double that contributed by riverine flow

.Draft 11 August 2010 Figure 3. Aquatic features of the Springs Coast, including major waterways, springs , delineated springsheds, and coastal bathymetry. Note the very shallow nat ure of the nearshore area. Major springsheds delineated by the SWFWMD.Draft 12 August 2010 Figure 4. Aquifer vulnerability in spring areas ( Figure 16 in Harrington et al. 2010)Draft 13 August 2010 Figure 5. Atmospheric deposition of inorganic N (nitrate and ammonium nitrogen) by quarter at the Chassahowitzka N WR (NADP FL05) (from Dixon and Estevez 2001)

Offshore Spring Vents Spring vents have been identified offshore of Citrus, He rnando, and Pasco Counties (Figure 6 ). DeWitt (2003) did not observe flow at the vents in Hernando and Pasco Counties. Flow was detected at the Maya Spring vent in Citrus County in April 2002, but high salinities and temperatures from the vent during subsequent deployments of YSI sondes suggested that very little ground water discharge is occurring at this site (DeWitt 2003). DeWitt (2003) reported a number of other sinkholes offshore (30 to 50 miles) but indicated that ground water discharge was unlikely from most of these sinks.Draft 14 August 2010 Figure 6. Locations of potential offshore springs in the northern half of the SWFWMD (from DeWitt 2003)Draft 15 August 2010 Coastal Currents Various currents within the Gulf of Mexico occasionally bring waters from the rivers to the north through the Springs Coast region. One such event occurred in 1998, when it was documented by ecologists (Dixon and Estevez 2001) and oceanographers (Jolliff et al. 2003 ; Weisberg et al. 2004) that the plume of colored dissolved organic matter (CDOM) from the Suwannee River extended past the nearsh ore areas of the Springs Coast (Figure 7). Jolliff et al. (2003) determined that the 1998 plume was from the Suwannee River, but other rivers may contribute as well ( the Withlacoochee and Waccasassa are also colored rivers north of the Springs Coast).

F

igure 7. The average surface CDOM absorption over the West Florida Shelf for the period from June 1 to July 17, 1998, shows the southward dispersal of the Suwannee River plume. At right, a time series ( May 5 to July 29, 1998) for locations along a transe ct through the river plume shows the variability in the modeled surface CDOM normalized by the highest value modeled for that location during the period (red). Similarly, 7

- day composite Sea

- viewing Wide Field

- of

- view Sensor ( SeaWiFS ) chlorophyll

a values for the corresponding pixel locations are presented (black) as values normalized by the highest value observed during that period. Values were interpolated when cloud cover obscured retrieval (from Jolliff et al. 2003 ).Draft 16 August 2010 

### Biological Summary

Subm ersed A quatic V egetation and S pe cies Composition

SAV , including seagrasses and associated macroalgae, is the marine aquatic community most sensitive to nutrient enrichment and potential resultant light reduction along the Springs Coast. The SAV community along this coastline is vast and valuable, providing habitat for fish, manatees, sea turtles, and other wildlife. Zieman and Zieman (1989) provide a comprehensive review of the character and value of the seagrass communities off the west coast of Florida, including the Springs Coast. They summarize the functions of seagrass communities as ( 1) high production and growth, ( 2) food and feeding pathways, ( 3) shelter, ( 4) habitat stabilization, and ( 5) nutrient effects (holding detritus onsite, hosting nitroge n- fixing organisms, and pumping nutrients from sediment to water).

Estimates of Submersed Aquatic Vegetation Coverage Thalassia testudinum, Syringodium filiforme, Halodule wrightii , and Halophila spp. comprise the vascular component of the SAV community in this region. Kolasa and Craw (2009) interpreted aerial photos to determine seagrass coverage for the project area (Table 5 ; Figure 8 ). Seagrass cover was found within 379,016 acres of 494,404 total acres mapped, or 77% of the total project area

. In general, dense seagrass comprised 272,772 acres , or 63% of the 431,323 acres of submerged bottom mapped. Seagrass within the sparse- to

- medium classification comprised 87,393 acres (20%), patchy seagrass comprised 18,851 acres (4%), and bare substrate comprised 52,305 acres (12%). Dense seagrass was the dominant seagrass cover type within all 4 segments, with the Aripeka and Weeki Wachee segment s containing the largest area and percentage of dense seagrass (68% and 73%, respectively). In contrast, the Anclote and Homosassa segment s contained larger areas of nonvegetated or bare substra te (24% and 21%, respectively).

Table 5. Estimates of seagrass coverage along the Springs Coast to approximate ly 15 miles offshore, from the interpretation of 2007 digital imagery (SWFWMD; Kolasa 2010). Shown are acres and percent of total area comprised by various bottom habitats within 4 regions. Habitat Type Anclote to Pithlachascotee (acres [%]) Aripeka to He rnando Beach (acres [%]) Weeki Wachee to Chassahowitzka (acres [%]) Homossasa to Crystal River (acres [%]) All Regions (acres [%])

Dense seagrass 36,221 (59%) 76,855 (68%) 100,825 (73%) 58,870 (50%) 272,772 (63%) Patchy seagrass 5,903 (10%) 4,138 (3%) 4401 (4%) 4,408 (4%) 18,851 (4%) Sparse to

m edium seagrass 4,201 (7%) 17,461 (25%) 36701 (17%) 29,026 (25%)) 87,393 (20%)

Other

–
o pen w ater, t idal f lats, s hoals (nonvegetated) 14,575 (24%) 7,091 (4%) 5,759 (7%) 24,881 (21%) 52,305 ( 12%)

Total a rea of

s ubmerged b ottom 60,902 ( 100% ) 105,547 ( 100% ) 147,688 ( 100% ) 117,186 ( 100% ) 431,323 ( 100% )

D ense seagrass beds extend well beyond the western boundary ( 15 miles offs hore ) of this project’s study area. These offshore dense beds are primarily located within the shallow offshore zones of theDraft 17 August 2010 Aripeka and Weeki Wachee segments, where water depth increases at a gradual rate of 1 foot per mile. The shallow depth (less than 20 f ee t), good water clarity, and adequate light pe netration support seagrass growth in these offshore waters (Zieman and Zieman 1989).

The mapping of SAV by photo interpretation of aerial surveys was also conducted for the Springs Coast in 1985 (Continental Shelf Associates 1985) and 1999. Comparison in coverage between years is difficult due to different mapping techniques and different image resolution. The most comparable years were 1985 and 2007, and Table 6 contains the comparison between those mapping efforts for the entire mapping region (from K olasa and Craw 2009). The acreages are comparable, though the 2007 mapping shows a higher percent age of unvegetated area. However, the detail of line work and number of polygons were so different between the 2 years (e.g., the majority of dense seagrass was represented by 2 polygons totaling 288,000 acres in 1985, compared with 1,900 polygons of dense seagrass in the 2007 effort) that the authors do not conclude that there has been any loss in seagrass (Kolasa and Craw 2009). Their analysis does not include a comparison of acreage for each region, but v isual examination of 1985 and 2007 coverages in the four regions of their study indicate few areas of potential loss (Figure 8). An area of “patchy seagrass” just east of Crystal River is present in 1985, but the 2007 map is devoid of seagrass in that area of roughly 6 miles by 1.5 miles (Figure 8a). Two isolated circle areas in the northern nearshore portion of the Aripeka region were mapped in 1985 but not in 2007 (Figure 8c).

The recent efforts to map SAV in this region using digital imagery from 2007 showed that the deep edge of dense SAV coverage in Pasco County , at 11

- 13 feet deep, has not been reduced (Kolasa and Craw 2009 ; Figures 8c, 8d ), which suggests that water clarity in that area has not bee n degraded. The deep edge extends too far out into the Gulf in Citrus and Hernando Counties (about 30 miles) for this study (to 15 miles offshore) to make any judgment about that portion of the coast.

Table 6. Comparison of seagrass acreage estimated for the Springs Coast in 1985 and 2007 (from Kolasa and Craw 2009).Draft 18 August 2010Draft 19 August 2010Draft 20 August 2010Draft 21 August 2010 Figure 8. Comparisons of 1985 and 2007 submersed aquatic vegetation (SAV) coverages for a) Crystal River region, b) Weeki Wachee region, c) Aripeka region, and d) Anclote region. 1985 coverage by Continental Shelf Associates (1985). 2007 coverage by Avineon Inc. and provided by SWFWMD. Dense Seagrass = 75

- 100% cover, Sparse

- Medium Seagrass = 10

- 75% cover, and Patchy Seagrass polygons are areas with discontinuous patches of seagrass > 10% cover.
2000 Field Survey Results
Field SAV surveys of species composition were conducted from 1974 to 1980 ( Iverson and Bittaker 1986) and repeated in 2000 (Hale et al. 2004 ; Table 7) in the Springs Coast and along the Big Bend Coast. T here was some apparent replacement of T. testudinum with S. filiforme or H. wrightii at some deep sites between 1980 and 2000 ( Figure 9 ; Hale et al. 2004). Hale et al. (2004) reported that there may have been a shift in species composition and maybe even a loss of seagrass at the deep edge, and hypothesized that those changes may have been due to increased light limitation and nutrients from rivers in the region. They note that effects are more likely fr om highly colored northern rivers (e.g., Suwannee) rather than small spring

- fed rivers along the adjacent coast, but no water quality data were available at that distance from shore to confirm their hypothesis. They acknowledge the limitations of their co mparison, including the fact that they only sampled each survey point once during one year, whereas Iverson and Bittaker visited each site six times and considered a species present if it was detected one time. Despite these limitations, the authors think that they may have detected some change in distribution, but that further sampling would be necessary to confirm their findings (J

. Hale,Draft 22 August 2010 personal communication, May 14, 2010 ). The results of the 2007 mapping described previous;y , in which the deep edge in Pasco County had not changed, do not refute these authors’ conclusions of
seagrass loss because they did not detect any change in Pasco County (Hale et al. 2004); most of their observed loss or change was in the areas far offshore of Citrus and Hernando Counties, beyond the reach of the 2007 mapping by SWFWMD.

The replacement of T. testudinum with S. filiforme or H. wrightii is consistent with the hypothesis that some kind of stress occurred, likely light limitation, and the latter two species were able to recolonize the area first because of their life history ( see the discussion in Hale et al. 2004 ). However, it is not clear if the increased light limitation was due to increased color, turbidity, or chlorophyll a in the water column, and if that increased limitation was part of a downward trend or sporadic event. The 2000 sampling event followed closely behind a period of high flow from October 1997 to June 1998 , an El Niño event, in which the freshwater discharge from the Suwannee River was nearly three times the long

- term average (Carlson et al. 2010) and it was shown that the Suwannee River plume of CDOM extended south over the Springs Coast (Jolliff et al. 2003; Figure 7).

Quinlan (2003) found that the light extinction coefficient in the estuarine areas (reef and nearshore) of the Suwannee River was most strongly correlated with tripton (nonalgal suspended solids), followed by CDOM and chlorophyll a . Only during very low

- flow periods was light extinction highly correla ted with chlorophyll a . These results indicate that phytoplankton biomass is not the major contributor to water clarity reductions in the Suwannee River but
, rather , from the organic materials from swamp source waters in the Suwannee River watershed . Dr. T. Frazer (University of Florida) has measured light extinction coefficient in the nearshore region of the Springs Coast for 13 years, and he has found that it is poorly correlated with chlorophyll a ( T. Frazer, personal communication at public meeting in Crystal River 2/23/10 ). However, the Florida Wildlife Research Institute (FWRI) of the Florida Fish and Wildlife Conservation Commission (FWCC) have preliminary results of a 5

- year water clarity and SAV study in the region north of the Suwannee River tha t suggest that chlorophyll and turbidity explain the variation in water clarity greater than color (Paul Carlson, personal communication 7/31/10). FDEP has not obtain ed light extinction data with which to perform independent analyses.

Table 7

. Summary of observations of seagrass species at 188 sampling locations in the Big Bend and Springs Coast regions

. The depths represent the maximum depth at which each species was observed. The depths listed in the 1974

– 1980 column were determined from the depths measured in the 2000 study (from Hale et al. 2004).Draft 23 August 2010 Figure 9 . Locations along the Springs Coast where Thalassia testudinum was present in the 1985 study, but replaced by Syringodium filiforme (S) or Halodule wrightii (H) or both species in the 2000 study. Dotted lines delineate the 6

- meter (m) and 9

- m isobaths (from Hale et al. 2004).

Mote Marine Laboratory Studies in the Chassahowitzka NWR Mote Marine Laboratory (MML) studied water chemistry, sediment, and SAV throughout the boundaries of the Chassahowitzka NWR from 1996 to 2004. The purpose of the study was to establish the baseline condition for the community amid growing concerns over freshwater reductions and increased nitrate concentrations in the springs. Dixon and Estevez (1998 ) describe Chassahowitzka Bay as “a large, shallow (<2m), exposed mosaic of saltmarsh, seagrass beds, and algal assemblages growing on an extensive karstified limestone shelf.” Their studies showed a diverse SAV community, dominated by attached macroalga and Thalassia testudinum in the nearshore areas of Chassahowitzka Bay (see Table 8, from Toutant et al. 2004). Dixon and Estevez (1998) characterized the system as healthy.

High rainfall in 1998 ( an El Niño event) followed by an extensive algal bloom allo wed MML to study the effects of reduced salinity and water clarity on the SAV community (Toutant et al. 2004). The chlorophyll a concentration in 1998 was greater than 20 micrograms per liter (μg/L) at some stations for 6 months from May to October 1998, where levels were typically well below 5 μg/L (see Figure 41 in the section on water quality studies). There were high surface water flows during this time, and the salinity was less than 20 parts per thousand (ppt) for that 6

- month period at stations whe re it typically ranges from about 25 to 30 ppt (Figure 10 ). Toutant et al. (2004) estimated that the bloom dominated at least 50 km of the coastline and hypothesized that the excess nutrients originated from large rivers to the north (Withlacoochee and Su wannee), although excess fresh water originated all along the coast. SAV responses shown in Toutant et al. (2004) demonstrate that the SAV community is very dynamic alongDraft 24 August 2010 this coastline and is driven by salinity as well as light (Figures 10 and 11 ). Acet abularia crenulata and Caulerpa paspaloides were the two most abundant rhizophytic algae at the beginning of the study (1996), were reduced during 1998, and rebounded by 2000 (Figure 12 ). These algae are not tolerant of fresh water; their abundance was likely reduced due to the decrease in salinity rather than algal blooms (Toutant et al. 2004).

Table 8

. Regional Braun

- Blanquet statistics by sampling for the entire coastal study area in the M ML study of the Chassahowitzka NWR (30 stations) (Table 5 in Toutant et al. 2004)

.

OBS = N umber of quadrats in which species was observed FREQ = frequency ABUN = abundance DENS = densityDraft 25 August 2010 Figure 10

. Medians and quartiles of salinity of 12 routinely sampled coastal stations in the M ML study of the Chassahowitzka NWR (Figure 9 in Dixon and Estevez 2001).

Figure 11

. Mean density for vascular SAV species by year, in the M ML study of the Chassahowitzka NWR (Figure 5 in Toutant et al. 2004)

.

Note: O nly a subset of sites was surveyed i n 1998

.Draft 26 August 2010 Figure 12

. Mean density for rhizophytic algal species by year, in the M ML study of the Chassahowitzka NWR (Figure 6 in Toutant et al. 2004)

.

Note: O nly a subset of sites was surveyed in 1998.

S

AV in St. Martin’s Marsh Aquatic Preserve ( text and figures provided by Big Bend Seagrass and St. Martins Marsh Aquatic Preserve staff )

Aerial surveys are the most commonly used tool for estimating seagrass locations, acres, and broad scale changes over time. However, additional localized change s to sea grass species such as abundance and health are difficult to capture using traditional mapping methodologies. The St. Martins Marsh Aquatic Preserve’s seagrass monitoring program began in 1997 , in the region between the Chassahowitzka and Homosassa Rivers in Citrus County

. Sampling is conducted within a 25

- mile grid consisting of 25 fixed sites that are 1 mile apart (Figure 13 ). At each site , 4 replicate quadrats are randomly thrown for a total of 100. Coverage estimates of seagrass, rooted macro algae, and drift algae are made using Braun

- Blanquet sampling methods. This involves identifying the percent coverage of all seagrass and algae species represented within a 1 square meter ( m 2 ) “quadrat.” The preserve uses the following coverage abundance codes: 1 = <5% cover; 2 = 5 %- 25% cover; 3 = 25 %- 50% cover; 4 = 50 %- 75% cover; 5 = 75 %- 100% cover (Figure 15 )

. The type of data collected has been adjusted throughout the study period, but the site locations ha ve remained the same. The p reserve contin ues to collect data on indicators that prove to be the most accessible and comparable
, including seagrass and macroalgae abundance, seagrass species composition, canopy height, epiphyte density ( 1 = clean, 2 = light, 3 = moderate, 4 =heavy ) , water quality measurements (DO, pH, temperature, salinity, turbidity, color, photosynthetic active radiationDraft 27 August 2010 (PAR), sediment type/grain size, and the presence of other organisms present in the bed, such as bay scallops and sea urchins. The monitoring program pr ovides information to resource managers to assess the status of this resource in and near the preserve, and is not representative of the entire Springs Coast.

This area of Florida is extremely shallow and is characterized by exposed karst features , resul ting in a mosaic of seagrass and hardbottom habitats. The domina nt species within the hardbottom habitat are Siderastrea radians ( shallow

- water starlet coral ) and Spheciospongia vesparium ( loggerhead sponge ) ( see Table 9 and Figure 18 in later sections)

. The domina nt seagrasses species within the project location are Thalassia testudinum and Syringodium filiform (Figure 14)

. In 2002, the p reserve began to assess total sea grass coverage, total macroalgal coverage, and total SAV coverage (Figure 15 ). Total

sea grass coverage has ranged between 3.02 and 4.13 on the Braun

- Blanquet scale of 1 to 5 (approximately 25

- 55 percent cover SAV)

. Total epiphyte coverage density has been stable throu ghout the study period (Figure 16 ). The project area has a very d iverse array of rooted macroalgae
, and a total of 19 species occ ur within the study area (Table 8 ). The domina nt macroalgal species within the study

area are Penicillus capitatus and Caulerpa prolifera.

Figure 13. Fixed m onitoring s ites in St. Martins Marsh Aquatic Preserve.Draft 28 August 2010 Figure 14 . Frequency of occurrence of seagrass species in St. Martins Marsh Aquatic Preserve , 1997

– 2009.

Figure 15 . Average t otal seag rass c overage at St. Martins Marsh Aquatic Preserve , 2002

– 09. AVG B&B represents the aver age Braun

- Blanquet ranking assigned at each of 100 sampling quadrats per year. Ranks are abundance codes ranging from 1 to 5.Draft 29 August 2010 Figure 16 . Average e piphyte r anking in St. Martins Marsh Aquatic Preserve , 2004

– 09. Shown are average epiphyte rankings of 100 sampled quadrats. Possible epiphyte ranks range from 1 to 4. The sampling is described in the section on submersed aquatic vegetation and species composition

.

Epiphyte Loads on Seagrass None of the studies reviewed mentioned problematic ephiphyte growth on seagrass

.
Ph ytoplankton Species Composition Roger Johansson conducted a year

- long study of water quality and primary productivity in three regions of the Anclote River estuary from 1973

- 1974 (Johansson 1975). The three regions he studies were the Anclote River (3 sites in tidal portions), Anclote A nchorage (5 sites between the river mouth and Anclote Key) and the Gulf of Mexico (3 sites on the seaward side of Anclote Key). Phytoplankton and benthic algae were collected at one site within each region. Phytoplankton were dominated by diatoms at all times of year, and they observed a bloom of the dinoflagellate Ceratium hircus in January. Diatoms were the only phytoplankton group of any importance in terms of biomass during the course of the study (Johansson 1975).

Mote Marine Lab studied phytoplankt on in the Chassahowitzka N WR . In the 1996

– 2001 study, the phytoplankton community was dominated at all times by diatoms (Figure 17 ). The community experienced a large algal bloom during the 1998 El Niño event. Diatoms were still dominant then, but dinof lagellates were also very abundant.Draft 30 August 2010 Figure 17

. Phytoplankton concentrations by major group and by sampling, from the 1996

–

2001 MML study of the Chassahowitzka N WR (Figure 33 in Dixon and Estevez 2001)

.

Macroalgal S pecies C omposition and B ioma ss (Including Calcareous Forms) Table 9 lists the types of macroalgal species found in St. Martin’s Marsh from 1998 to 2009.

Depth to Seagrass Targets

No seagrass depth targets have been established

. Based on the 2007 mapping effort by the SWFMWD, dense beds occur up to 13 feet deep off Pasco County, the only area for which their mapping reached the deep edge. In

Presence and Fr equency of Harmful Algal Blooms

No harmful algal blooms (HABs) have been documen ted for the area

.Draft 31 August 2010 Table 9. Macroalgal species occurrence in St. Martins Marsh , 1998

–

2009, sampled by Aquatic Preserve staff. Shown is the number of sampling quadrats in which that species was present, of 100 total quadrats sampled per year. The s ampling program and methods are described in the section on SAV and species composition

. Macroalgal Species 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Acetabularia crenulata 15 5 4 15 9 10 3 5 2 5 1 4

Avrainvillea levis 2 1 2 0 3 0 0 0 0 0 0 0 Anadyomene stellata 3 1 0 9 5 1 2 1 1 1 0 0 Caulerpa ashmeadii 7 11 4 11 11 16 7 10 7 7 4 4 Caulerpa cupressoides 2 3 6 3 2 3 1 2 4 4 0 3

Caulerpa langinosa 0 0 0 3 2 0 0 0 0 2 4 0 Caulerpa mexicana 0 0 0 0 0 0 0 0 0 0 4 0 Caulerpa paspaloides 0 2 0 3 1 7 1 5 5 0 6 4 Caulerpa prolifera 67 52 48 62 54 71 19 51 32 22 17 41 Drift algae 40 74 57 40 22 39 25 35 45 29 7 8 Digenia simplex 7 3 2 10 5 3 3 7 2 1 1 6
Halimeda incrassata 30 44 33 48 42 44 33 33 26 22 18 30 Penicillus capitatus 57 61 63 63 63 46 52 52 47 39 16 41 Penicillus dumetosus 4 35 32 32 37 28 26 26 40 53 48 48
Padina vickersiae 4 0 0 0 0 0 0 0 0 0 0 0 Rhipocephalus phoenix 3 6 7 6 9 2 5 2 3 5 0 0

Sargassum sp. 1 4 2 15 6 0 3 5 0 0 3 8 Udotea flabellum 21 21 25 38 31 27 15 21 30 26 15 4 Unknown algae 0 0 0 0 0 2 0 0 3 0 0 0

Coral or H ard bottom C ommunity S tructure and A real E xtent
Dense areas of coral are found around the St

. Martins Marsh A quatic P reserve within water as shallow

as 4 to 6 feet (Figure 18 )

. These coral beds are flat areas of exposed limerock containing dense growth of small coral isolates. Only 1 to 2 species inhabit the shallow beds around the St. Martins Keys, primarily Siderastrea radians (l esser s tarlet) and Siderastrea siderea ( m assive s tarlet). In addition
, scattered coral is fo und growing on much of the hardbottom within 1 mile of the coastli ne. Again , these are primarily Siderastrea radians (lesser s tarlet) and Siderastrea siderea (massive s tarlet) ; however, other corals that are oc casionally seen include Solenastrea hyades (k nobby s tar) and Stephanocoenia intersepta (b lushing star ) . Sponges such as the loggerhead sponge ( Spheciospongia vespari ) are also very common within 1 mile of the coastline, especially between the St. Martins Keys and Chassahowitzka River. They support a more diverse coral and sponge community than the flat

- bottom coral beds.

Within 6 to 8 miles of the coastline, there are a number of shallow reef systems and rock outcroppings that support up to 10 species o f coral. These reefs are located in 12 to 15 feet of water and have 2 - to 6

- foot relief. In addition to the 4 species listed above, common corals inhabiting these systems include Stephanocoenia intersepta (b lushing s tar)
, Cladocora arbuscula ( tube ), Manicina areolata (r ose)
, Oculin aDraft 32 August 2010 robusta (r obust i vory t ree) , and Solenastrea bournoni (s mooth s tar) (description from K. Kolasa, SWFWMD).

Unfortunately, little historical information is available on the reef systems for the Springs Coast. Continental S helf Associates completed some work in 1985 at the same time the seagrass mapping was completed; however, no maps were generated. The 2007 seagrass imagery has provided the first images of these systems that are sufficiently detailed for reef mapping. Fi gure 19 shows the l ocation and size of coral beds and coral reefs off the Springs Coast, generated from 2007 aerial photos

.

Figure 18 . Hardbottom h abitat in St. Martins Marsh Aquatic Preserve (photo from St. Martins Marsh Aquatic Preserve staff ).Draft 33 August 2010 a.)Draft 34 August 2010 b.)

Figure 19

. Location and size of coral beds and coral reefs off the coast of a) Citrus County and b) Hernando County , generated from 2007 aerial photos (map courtesy of SWFWMD).

Shellfish P roduction and F requency /

Duration of Bed Closures Citrus County is the only portion of the Springs Coast that is part of a Shellfish Harvesting Area monitored by the Florida Division of Aquaculture, and it is not a major shellfishing area compared with other regions

. For the winter season, 64,472 acres are Conditi onally Approved (<14 MPN/100 ml fecal coliforms) for shellfish harvesting, 4,004 acres are Conditionally Restricted (<88 MPN/100 ml fecal coliforms) , and 7,380 acres are Prohibited. Closure in the winter season is dependent upon rainfall and associated fe cal coliform concentrations (see discussion on relevance of fecal coliforms to nutrient criteria development later in this report) . For the Spring/Fall season, 66,608 acres are Approved, 1,867 acres are Restricted, and 7,380 acres are Prohibited. Closure during the Spring/Fall season occurs during emergency conditions such as red tides, hurricanes, and sewage spills. The prohibited areas are in the Crystal River and along the marshy coastline. Approved areas are the open water portions of Citrus County waters (Kuhman and DeHaven 2008). From 1995 through 2006, the annual reported commercial landings of shellfish in Citrus County averaged 546 pounds, with an annual dockside value of $1,289. This area accounted for 0 .03 % of shellfish landings in Florida and .03 % of shellfish value in Florida (Kuhman and DeHaven 2008)

.Draft 35 August 2010 The Florida Fish and Wildlife Conservation Commission (FWCC) conducts annual scallop surveys to monitor the status of representative scallop populations i n Florida and to assess changes in population abundance that may occur in response to management and restoration efforts instituted by the s tate since 1994. FWCC (2009) describe d the results of 2008 bay scallop surveys in coastal areas of the Homosas sa, H ernando, and Anclote segments . These surveys measure d adult abundance and recruitment, and also report ed on restoration efforts, at 20 sites within each area. For the 3 areas within the Springs Coast, adult abundance and recruitment indicated improving trends and good condition (FWCC 2009). No active restoration efforts were reported for this area, though the statewide harvesting regulations apply. A dult abundance declined in the Homosassa and Hernando study areas in 2009 (FWCC 2010), but that decline i s likely due to increases in fresh water (S

. Geiger, FWCC, personal communication).

Quantification of L andings from C ommerci al

/

Recreational Fisheries
Data from the FWCC fish landings data by county illustrate that the Springs Coast region supports a range of fisheries (Figures 20 through 23 ). Changes in the fisheries cannot be attributed to nutrient effects; however, the presence of stable fisheries , especially shellfish, suggests healthy habitat conditions.

Figure 20

. Commercial blue crab harvest (pou nds per trip) per year in Citrus, Hernando, and Pasco Counties, for the period of survey record (1995

– 2008) (from F WCC ). 0 50 100 150 200 250 300 350 400 450

Blue Crabs

- Citrus Blue Crabs

- Hernando Blue Crabs

- Pasco 

## Commercial Blue Crab Harvest (pounds/trip)

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008Draft 36 August 2010 Figure 21

. Commercial bait and food shrimp harvest (pounds per trip) per year in Citrus, Hernando, and Pasco Counties, for the period of survey record (1995

– 2008) (from F WCC ).

Figure 22. Commercial landings (pounds per trip) of grouper and mullet per year in Citrus, Hernando, and Pasco Counties, for the period of survey record (1995

– 2008) (from F WCC ). 0 200 400 600 800 1000 1200

Shrimp, Bait

- Citrus Shrimp, Bait

- Hernando Shrimp, Bait

- Pasco Shrimp, Food

- Citrus Shrimp, Food

- Hernando Shrimp, Food

- Pasco 

### Commercial Shrimp Harvest (pounds/trip)

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

0 200 400 600 800 1000 1200 1400 1600

Grouper, Total

- Citrus Grouper, Total

- Hernando Grouper, Total

- Pasco Mullet, Total

- Citrus Mullet, Total

- Hernando Mullet, Total

- Pasco 

### Commercial Landings (pounds/trip) of Grouper and Mullet

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008Draft 37 August 2010 Figure 23

. Total commercial finfish harvest (pounds per trip) per year in Citrus, Hernando, and Pasco Counties, for the period of survey record (1995

– 2008) (from F WCC ).

Ex isting Local B iological I ndices

No local biological indices have been established.

Hypoxia

No hypoxic episodes are known to have occurred

. 

### Water Quality Studies
This section discusses the following studies :

**•** Anclote River Estuary studies 1970s ;

**•** M ML study of selected rivers in the Springs Coast area , 1984

– 85 ;

**•** Project COAST, 1997

–

present ;

**•** MML i ntensi ve s tudy of the Chassahowitzka N WR , 1996

– 2001 ; and

**•** Random sampling of the Springs Coast, 2000

– 04, by the I nshore Marine M onitoring and Assessment Program ( IMAP ) through the Fish and Wildlife Research Institute ( FWRI). 0 200 400 600 800 1000 1200 1400 1600 1800 2000

Finfish, Total

- Citrus Finfish, Total

- Hernando Finfish, Total

- Pasco 

### Commercial Total Finfish Harvest (pounds/trip)

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008Draft 38 August 2010 Anclote River Estuary Studies 1970s Roger Johansson conducted a year

- long study of water quality and primary productivity in three regions of the Anclote River estuary from 1973

- 1974 (Johansson 1975). The three regions he studies were the Anclote River (3 sites in tidal portions), Anclote A nchorage (5 sites between the river mouth and Anclote Key) and the Gulf of Mexico (3 sites on the seaward side of Anclote Key). He measured salinity, temperature, turbidity, orthophosphate, nitrate, ammonia, silica, primary productivity, chlorophyll a , an d phaeopigments monthly at each site.

Mean water chemistry values over the period of the study at the river sites were 0.079

- 0.154 mg/L orthophosphate, 0.015

- 0.045 mg/L ammonia, and 0.052

- 0.105 mg/L nitrate. Mean values for the Anchorage sites were 0.04 5- 0.054 mg/L orthophosphate, 0.003

- 0.004 mg/L ammonia, and 0.009

- 0.036 mg/L nitrate. Mean values for the Gulf of Mexico sites were 0.048

- 0.057 mg/L orthophosphate, 0.002

- 0.005 mg/L ammonia, and 0.008

- 0.027 mg/L nitrate.

Mean uncorrected chlorophyll a over the period of the study at the river sites ranged from 7.86

- 11.5 mg/m 3 (phaeopigments range 3.76

- 4.6 mg/m 3 ), and monthly averages of all sites ranged from a low of 3.75 mg/m 3 (phaeopigments 0.17 mg/m 3 ) in December to a high of 21.33 mg/m 3 (phaeopigments 8 .67 mg/m 3 ) in September. Mean uncorrected chlorophyll a over the period of the study at the Anchorage sites ranged from 4.55

- 7.0 mg/m 3 (phaeopigments range 2.29

- 4.08 mg/m 3 ), and monthly averages of all sites ranged from a low of 1.7 mg/m 3 (phaeopigments 1 .53 mg/m 3 ) in March to a high of 10.91 mg/m 3 (phaeopigments 5.29 mg/m 3 ) in August. Mean uncorrected chlorophyll a over the period of the study at the Gulf of Mexico sites ranged from 4.22

- 5.96 mg/m 3 (phaeopigments range 2.91

- 3.58 mg/m 3 ), and monthly averages of all sites ranged from a low of 1.88 mg/m 3 (phaeopigments 0.8 mg/m 3 ) in November to a high of 17.33 mg/m 3 (phaeopigments 7.53 mg/m 3 ) in August.

MML Study of Selected Rivers, 1984 –85

M ML conducted a 2- year study of water quality at river and estuary stations of the Waccasassa, Withlacoochee, Crystal, Weeki Wachee, and Aripeka Rivers , under contract with the SWFWMD for determining minimum flows and levels (MFL s)

. Except for the Aripeka sites, those data are in LEGACY STORET and in the Impaired Sur face Waters Rule ( IWR ) database. Data are reported and analyzed in Dixon (1986). The systems discussed here are Crystal River, Weeki Wachee, and Aripeka.

Metered parameters (salinity, pH, DO , and temperature) were recorded at 10 sites in the Crystal and Weeki Wachee systems, with water chemistry (nutrients, turbidity, color, total suspended solids ( TSS )
, chlorophyll a, phaeophytin a , and transparency) sampled at 5 stations

. Only five sites were monitored for Aripeka because it i s a much smaller system. The Crystal and Weeki Wachee River stations were sampled in 1984 and 1985, but Aripeka was only sampled in 1984.

Water clarity was generally very good offshore from these spring

- fed rivers , with 20% of surface light reaching as deep as 3.8 m (Table 10 ). Dixon ( 1986 ) conducted a correlation analysis to determine which light attenuation factor contributed most to the light extinction coefficient, and they found color to be most important for Weeki Wachee, color and turbidity for Crystal River, and chlorophyll a for Aripeka. Chlorophyll a values (uncorrected) were fairly low, at 3.3

- 3.6 μg/L on average for Crystal River estuary 1.4 μg/L for Weeki Wachee, and 2.5 μg/L for Aripeka. Average dissolved oxygen (DO) levels were high,

ev en on the bottom (Table 10), and minimum bottom DO concentrations were typically greater than 5 mg/L for these sites (Dixon 1986). Note that their analyses included sites along each river reach , not just in the estuary, and so these results must be viewed with caution in the current context.Draft 39 August 2010 Table 10

. Summary water clarity data for estuarine sites sampled off three Springs Coast r ivers by M ML , 1984

– 85. Values presented at mean/standard deviation (from Dixon 1986 ).

PCU = Platinum cobalt unit NTU = Nephelometric turbidity unit

m g/m 3 = milligrams per cubic meter

Parameter Crystal River Crystal River Weeki Wachee Weeki Wachee Aripeka
River mile 0.00

- 3.48

- 0.15

- 3.62

- 0.4 Color (PCU) 10/4 9/5 15/5 7/3 15/3
TSS

– Surface (mg/L) 5/2 7/3 3/1 5/4 3/1
TSS

– Mid (mg/L) 6/2 8/3 3/1 5/3 3/1
TSS

– Bottom (mg/L) 7/2 9/3 4/2 6/3 11/25 Turbidity (NTU) 3.6/1.7 2.9/1.2 1.1/0.3 1.0/0.3

--- Chlorophyll a , uncorrected (mg/m 3 ) 3.6/3.3 3.3/1.9 1.4/0.7 1.4/0.9 2.5/1.9

Extinction coefficient (m -1 ) 0.81/0.27 0.51/0.36 0.69/0.28 0.49/0.25 0.69/0.22

Depth receiving 20% light (m) 2.2 3.7 2.6 3.8 2.6

Bottom dissolved oxygen (mg/L) 7.7/1.5 7.3/1.1 8.0/1.8 7.7/1.1 8.0/1.4

F DEP Analysis of 1984 –85 M ML S tudy Two years of data at one site off Crystal River and one site off the Weeki Wachee River along the Springs Coast were available in Legacy STORET (Figures 24 and 25 )

. These were normal or low

- normal rainfall years (Dixon 1986). TN was calculated by adding total Kjeldahl nitrogen ( TKN ) and nitrate+nitrite ( NO 2+3 ) . Table 11 contains sample sizes and the results of those analyses. Phaeophytin a was analyzed but is not available in STORET

. Annual geometric m ean total nitrogen ranged from 0.472 mg/L to 0.504 mg/L at Crystal River and was 0.611 mg/L for both years at Weeki Wachee (Table 11; Figure 24 )

. There was not much relationship between total nitrogen and salinity (Figure 25 ). Annual geometric mean chlorophyll a (uncorrected) ranged from 0.62 to 3.19 μg/ L. Total phosphorus data were not analyzed due to uncertainty of data comparability (Appendix D)

.
Table 11

. Annual geometric mean TN and chlorophyll a (uncorrected) from the 1984

– 85 MML study of the Weeki Wachee and Crystal Rivers. Site Year Sample Size Annual Geometric Mean TN (mg/L) Annual Geometric Mean Chlorophyll a (uncorrected) Crystal River

- 10 1984 10 0.504 3.19 Crystal River

- 10 1985 6 0.472 2.04 Weeki Wachee

- 10 1984 12 0.611 1.78 Weeki Wachee

- 10 1985 6 0.611 0.62Draft 40 August 2010 Figure 24. TN data for one site in the Weeki Wachee Estuary and one site in the Crystal River Estuary , 1984

– 85, from the M ML study.

Figure 25. Salinity as a predictor of TN for one site in the Weeki Wachee estuary and one site in the Crystal River Estuary , 1984

– 85, from M ML study.Draft 41 August 2010 Project COAST, 1997

– Present Forty sites off the coast of Citrus and Hernando Counties have been sampled monthly since 1997, and 40 stations off the coast of Pasco County have been sampled monthly since 2000, as part of P roject COAST , which is led by Principal Investigator Dr. Tom Frazer of the University of Florida and funded in cooperation with the SWFWMD (Figure 26 ). Th e project measures TN, TP , chlorophyll a , light extinction coefficient, Secchi depth , color, salinity, DO , and temperature at 10 sites within each of 8 river systems/areas along the coast. Water quality analyses are conducted at the University of Florida
, Institute of Food and Agricultural Sciences (IFAS) School of Forest Resources and Conservation (SFRC) by the L akeWatch P rogram. At the time of this writing, data are available in STORET through 2006, and several reports of the results are available (Frazer et al. 1998 ; Frazer et al. 2002 ; Frazer et al. 2005 ; Frazer et al. 2006 ; Jacoby et al. 2009a ; Jacoby et al. 2009b). This is the most extensive and comprehensive dataset available for th e region.

Appendix A summarizes the Project COAST data as mean concentrations for all estuary stations for each coastal segment. The results of F DEP analyses will be presented later in this report. Below is a summary of Dr. Frazer (and colleagues) interpretation of the data.

The following text is excerpted from Jacoby et al. ( 2009a ) and accompanies Figures 2 7-33:

Chlorophyll concentrations are correlated with concentrations of total phosphorus and total nitrogen (Figure 27 ). The stronger empirical relationship between chlorophyll and total phosphorus pointed to phosphorus as a major driver of changes in chlorophyl l. Across all stations in all systems, mean concentrations of total nitrogen, total phosphorus and chlorophyll increased in response to an El Niño event, which generated significant rainfall during 1998 (Appendix A). These changes decreased water clarity as shown by a reduction in the proportion of times a Secchi disc remained visible throughout the water column. The systems recovered, with “typical” values recorded after 6

– 8 months. Overall, these results illustrated how natural variation can confound identification of anthropogenic impacts, and they pointed to the value of sustained sampling. Trends were examined by correlating indicators with time. Total nitrogen concentrations increased significantly in the Crystal and Homosassa systems, especially during wet months (Figures 28– 30 ). Significant increases in total phosphorus concentrations were not as widespread. As expected, chlorophyll concentrations in these systems increased in response to increased nutrients. In contrast, decreases in nutrient and chlorophyll concentrations were prevalent in the Chassahowitzka and Weeki Wachee systems. Further insights into causal relationships await collation of data on human activities and completion of diagnostic studies of key biological processes.

Data suggest that phosphorus is limiting along the Pasco County portion of the Springs Coast as well (Figure 27 ; Jacoby et al. 2009b). The analyses described above were conducted for Pasco County sites as for northern sites, in which data were divided into

seaso ns and correlations over time were run to determine temporal trends over the period 2000

- 2008. Results showed no increase in TN, TP, or chlorophyll a concentrations over time in the coastal areas of Pasco County; concentrations actually declined in some

c ases (Figures 31–33 ; Jacoby et al. 2009b).

Nutrient limitation studies conducted by Dr. Frazer on monthly samples collected during 2000

– 01 showed that the Weeki Wachee, Chassahowitzka, and Homosassa coastal systems were limited by P in 79 % , 40 % , and 51 % of samples ; limited by N in 0 % , 4 % , and 0 % of samples ; and co

- limited by N and P in 6% , 40 % , and 32 % of samples, respectively. For the Crystal River coastal area, 29 % of samples wereDraft 42 August 2010 limited by N and 29 % by P , and 29 % were co

- limited. The remaining samp les were undetermined. These results are important to support the theory of P

- limitation in this region, as strong relationships between TP and chlorophyll a are not sufficient evidence to indicate P

- limitation (Lewis and Wurtsbaugh 2008).

Figure 2 6. Project COAST sampling stations. Forty stations along the coast of Citrus and Hernando Counties have been sampled monthly from 1997 to the present, with 10 stations each in the Weeki Wachee, Chassahowitzka, Homosassa, and Crystal River systems

. Forty stations along the coast of Pasco County have been sampled monthly from 2000 to the present, with 10 stations each in the Aripeka, Hudson, Pithlachascotee, and Anclote River region s . Colored station markers represent the mean annual geometric mean of each station for 1996

– 2006 , calculated by FDEP.

Notes: Maps made by N

. Wellendorf with data pulled from Florida STORET in March 2010. This figure includes r iver /s tream sites and 1 year of data (1996) that were not included in subsequent F DEP analyses. 

### Total Nitrogen Geometric Mean Total Phosphorus Geometric Mean Chlorophyll a (uncorrected) 

### Geometric Mean

Crystal River

Homosassa

Chassahowitzka

Weeki Wachee
Aripeka

Hudson

Pithlachascotee

AncloteDraft 43 August 2010 Figure 27. Relationship between log 10 - transformed monthly mean chlorophyll and TN and TP concentrations from all estuarine systems along the Citrus, Hernando, and Pasco County coasts ( f

rom Jacoby et al. 2009a).

Note: T hese figures include data from the Withlacoochee River, which is not considered part of the Springs Coast for the current effort. Correlation coefficient = 0.84 p < 0.001

- 1.0 0.0 1.0 2.0

0.0 0.5 1.0 1.5 2.0 2.5log10[Chlorophyll (μg L-1)]

Log 10 [Total phosphorus (μgL

- 1 )] Correlation coefficient = 0.46 p < 0.001

- 1.0 0.0 1.0 2.0

2.0 2.5 3.0 3.5log10[Chlorophyll (μg L-1)]

Log 10 [Total nitrogen (μgL

- 1 )]Draft 44 August 2010 Figure 28

. Trend analysis based on correlation of site data with time. Wet months were identified as June, July, August, and September (f rom Jacoby et al. 2 009a )

.

Figure 29

. Trend analysis based on correlation of site data with time. Transitional months were identified as December, January, February, and March (f rom Jacoby et al. 2009a )

. Nitrogen Phosphorus Chlorophyll

= significant positive correlation = significant negative correlation 

## Temporal correlations with TN, TP and Chlorophyll

- Wet Months

-

= significant positive correlation = significant negative correlation 

## Temporal correlations with TN, TP and Chlorophyll

- Transitional Months

-

Nitrogen Phosphorus ChlorophyllDraft 45 August 2010 Figure 30

. Trend analysis based on correlation of site data with time. Dry months were identified as April, May, October, and November (f rom Jacoby et al. 2009a )

.

Figure 31

. Trend analysis based on correlation of site data with time. Wet months were identified as June, July, August, and September (f rom Jacoby et al. 2009 b)

. Nitrogen Phosphorus Chlorophyll

= significant positive correlation = significant negative correlation 

### Temporal correlations with TN, TP and Chlorophyll

- Dry Months

-

= significant positive correlation = significant negative correlation 

## Temporal correlations with TN, TP and Chlorophyll

- Wet Months

-

Nitrogen Phosphorus ChlorophyllDraft 46 August 2010 Figure 32

. Trend analysis based on correlation of site data with time. Transitional months were identified as December, January, February, and March (f rom Jacoby et al. 2009 b)

.

Figure 33

. Trend analysis based on correlation of site data with time. Dry months were identified as April, May, October, and Novembe r (f rom Jacoby et al. 2009 b)

. 

### = significant positive correlation = significant negative correlation 

## Temporal correlations with TN, TP and Chlorophyll

- Transitional Months

-

Nitrogen Phosphorus Chlorophyll

= significant positive correlation = significant negative correlation 

## Temporal correlations with TN, TP and Chlorophyll

- Dry Months

-

Nitrogen Phosphorus ChlorophyllDraft 47 August 2010 FDEP Analysis of COAST Data

F DEP notes the following details about sample analysis methods used b y Project COAST that require additional scrutiny before using the results of the data to support the development of water quality standards.

Chlorophyll a from Project COAST is reported without correction for phaeophytin. F DEP will propose water quality criteria for corrected chlorophyll a , and thus the uncorrected chlorophyll a data are expected to yield higher numbers than what F DEP will consider appropriate for the criteria. Project COAST reported corrected chlorophyll a data and phaeophytin concentrations for a few recent years of the project. This report contains comparisons of the corrected and uncorrected chlorophyll a data to inform the use of uncorrected values (the majority of the data record). The corrected and uncorrected values are highly correlated.

The method used by COAST for determining TN in water samples is not an EPA

- approved method, nor is it an approved method in F DEP’s Standard Operating Procedures ( SOPs ) . Bachmann and Canfield (1996) describe this method and provide data that show that the method produces results comparable to EPA

approved methods for TN in fresh water.

Water samples are frozen before analysis, an approach that also does not conform to F DEP SOPs. However, Bachmann and Canfield (1 996) and Canfield et al. (2002) demonstrate that TN results are not significantly affected by freezing. Also, the Project COAST samples are not held frozen for very long before analysis
, compared with citizen

- collected samples described by Canfield et al. (2002), which may be held for three months before analysis.

TP samples are also frozen, rather than acidified, before analysis. Canfield et al. (2002) showed that this preservation method did not significantly affect the analytical results.

Due to th ese inconsistencies between Project COAST lab analyses and F DEP SOPs and EPA guidance, several analyses were conducted in which the water chemistry results from Project COAST were compared with the results from concurrent sampling by other entities that used labs certified by the National Environmental Laboratory Accreditation Conference ( NELAC ) and NELAC

- approved methods. The results of these analyse s suggest that it is appropriate to use the long

- term Project COAST datasets, in conjunction with other d ata sources, to support proposed numeric nutrient criteria (see Appendix D for comparisons)

. Data were pulled from Florida STORET in April 2010 , but only included data through 2006. Stations designated as r iver /s tream in STORET (by data generators) and one additional station that is predominantly fresh were not included in this analysis (Chassahowitzka

- 1,

- 2,

- 10 ; Crystal -4; Homosassa5; Pithlachascotee -1; and Weeki Wachee

- 1,

- 2). Data from 1996 were not included due to small sample size, and so the dat a used included 1997 to 2006 (with no data available for 2005). For each station, annual geometric mean TN, TP, and c hlorophyll a were calculated.

The initial approach taken for pooling stations was to separate Pasco County sites from the northern Springs Coast, based on a recommendation by Dr. Tom Frazer. The annual geometric mean was calculated for each station

- year, and then the distribution of those geometric means was described for each of the two large regions (Table 12). The long

- term mean of the annual geometric means was calculated, and then a theoretical curve was fitted using a log normal distribution function to estimate the 75 th and 90 th percentile of the data. The long term means for TN were nearly identical (380 μg/L) forDraft 48 August 2010 the two r egions, long term mean TP was higher for the northern region (12.1 μg/L) than for Pasco County (9.2 μg/L) but both were low, and the long term mean chlorophyll a (uncorrected) was very low for both regions (< 2 μg/L; Table 12). Appendix B contains plots o f annual geometric mean s over time for each site

.
The a nnual geometric mean TN for each station was then plotted against average salinity for each year to determine if FDEP should pursue salinity

- dependent criteria

. Appendix C contains figures of salin ity versus TN for all systems. In general, salinity had a weaker influence on TN in the northern systems of Crystal River, Homosassa, Chassahowitzka, and Weeki Wachee The relationships are weak and in some

cases are positive, with increasing N as salinity increases. Positive relationships suggest that there are nonlocal inputs of nutrients to these coastal areas, and this is most likely due to transport from the rivers to the north. The relationship was strongest for 1998, in which the influence of the Suwannee River and possibly the Withlacoochee River on this region has been documented (Dixon and Estevez 2001; Jolliff et al. 2003). There was a relationship between salinity and TN some years at Weeki Wachee, but it was not consistent. At Crystal River, TN peak s at midrange salinities, suggest ing that something besides salinity is influencing TN concentrations there. Annual geometric means for each station are shown pictorially in Figure 26, and show a clear gradient of TN along the Pasco County coast, but not along the coasts of Citrus and Hernando Counties. Therefore, all sites in the Crystal, Homosassa, Chassahowitzka, and Weeki Wachee systems were not broken out into different salnity regimes

. For the Pasco County stations, TN and salinity shifted somewhat from year to year, but there was a consistent ly negative relationship between salinity and TN in that region , indicat ing that the river systems along that part of the coast are controlling the coastal nutrient regime (Figure 2 6; Appendix C)

. Pasco County s ites were pooled for 1 analysis, and then divided into 3 groups based on mean annual salinity over the course of the dataset: less than 25 ppt, 25 to 30 ppt, and greater than 30 ppt (Table 13 )

. Pasco County sites were of h igher salinity overall, probably because the farthest sites are farther from shore than the northern Project COAST sites, and possibly also because the coast has a slightly higher gradient off Pasco County ; thus the farthest sites are in deeper water. Lon g term geometric mean TN was higher for the sites < 25 ppt (417 μg/L) than for sites of 25

- 30 ppt (466 μg/L) or > 30 ppt (456 μg/L; Table 13). Long term mean TP and Chlorophyll a (uncorrected) were higher for the sites >30 ppt than for lower salinities, but that is probably due to the fact that most sites > 30 ppt are in the Anclote estuary, and higher nutrients there may be from anthropogenic origin. The tidal reaches of the An clote River are on the 303(d) list for mean chlor ophyll a values > 11 μg/L from 1999

- 2002 , but a TMDL has not been established

. Annual geometric mean TP and chlorophyll a are greater for the Anclote Estuary than the other coastal areas of Pasco County (Figure 26), and that could be due to na tural facto rs such as a larger watershed with swamp drainage or less mixing with the Gulf due to barrier island, or due to anthropogenic input.Draft 49 August 2010 Table 12. Summary of data analysis for coastal areas of Citrus and Hernando Counties combined (33 stations) and Pasco County (39 stations), 1997

–

2006.

LN = N atural logarithm GM = G eometric mean C.I. = C onfidence interval Note: The l ong

- term region annual geometric mean and 90 th percentile of site annual geometric means within the region are shown in bold.

Log Normal Distibution Empirical Percentile Log Normal Distibution Empirical Percentile Log Normal Distibution Empirical Percentile Mean LN 5.94 2.50 0.49 Std. Dev. LN 0.27 0.45 0.74 N 293 293 299 95% C.I. 0.03 0.05 0.08 Long-term GM 380.05 394.82 12.12 13.45 1.63 2.15 Lower 95% C.I. 368.39 11.52 1.50 Upper 95% C.I. 392.07 12.76 1.78 75th Percentile 456.26 444.12 16.37 18.23 2.69 3.06 90th Percentile 537.85 530.43 21.46 22.91 4.21 4.58

Log Normal Distibution Empirical Percentile Log Normal Distibution Empirical Percentile Log Normal Distibution Empirical Percentile Mean LN 5.94 2.22 0.01 Std. Dev. LN 0.18 0.42 0.63 N 234 234 234 95% C.I. 0.02 0.05 0.08 Long-term GM 380.31 386.38 9.19 10.14 1.01 1.25 Lower 95% C.I. 371.76 8.70 0.93 Upper 95% C.I. 389.07 9.71 1.10 75th Percentile 428.45 423.89 12.24 12.53 1.55 1.61 90th Percentile 476.97 486.61 15.83 15.58 2.28 2.34 CHLOROPHYLL A (uncorrected; μg/L) TOTAL NITROGEN (μg/L) TOTAL PHOSPHORUS (μg/L) CHLOROPHYLL A (uncorrected; μg/L) CITRUS & HERNANDO COUNTIES

PASCO COUNTY TOTAL NITROGEN (μg/L) TOTAL PHOSPHORUS (μg/L)Draft 50 August 2010 Table 13

. Summary of data analysis for Pasco County stations grouped by salinity, 1997

–

2006. “s alinity <25” represents 13 stations, “salinity 25

- 30” represents 19 stations, and “salinity>30” represents 7 stations.

LN = N atural logarithm GM = G eometric mean C.I. = C onfidence interval Note: The l ong

- term region annual geometric mean and the 90 th percentile of site annual geometric means within the region are shown in bold.

Log Normal Distibution Empirical Percentile Log Normal Distibution Empirical Percentile Log Normal Distibution Empirical Percentile Mean LN 6.03 2.18 0.05 Std. Dev. LN 0.17 0.44 0.60 N 78 78 78 95% C.I. 0.04 0.10 0.14 Long-term GM 417.12 423.31 8.84 9.93 1.05 1.28 Lower 95% C.I. 401.39 8.00 0.92 Upper 95% C.I. 433.48 9.77 1.20 75th Percentile 467.98 467.06 11.92 10.43 1.58 1.49 90th Percentile 519.04 534.99 15.60 15.01 2.27 2.14

Log Normal Distibution Empirical Percentile Log Normal Distibution Empirical Percentile Log Normal Distibution Empirical Percentile Mean LN 5.90 2.09 -0.25 Std. Dev. LN 0.16 0.37 0.57 N 114 114 114 95% C.I. 0.03 0.07 0.11 Long-term GM 365.63 370.56 8.07 8.72 0.78 0.95 Lower 95% C.I. 354.71 7.53 0.70 Upper 95% C.I. 376.88 8.64 0.87 75th Percentile 408.22 409.46 10.36 9.74 1.15 1.05 90th Percentile 450.79 460.55 12.97 13.40 1.62 1.53

Log Normal Distibution Empirical Percentile Log Normal Distibution Empirical Percentile Log Normal Distibution Empirical Percentile Mean LN 5.88 2.65 0.65 Std. Dev. LN 0.16 0.19 0.32 N 42 42 42 95% C.I. 0.05 0.06 0.10 Long-term GM 356.49 360.71 14.10 14.35 1.92 2.01 Lower 95% C.I. 339.55 13.30 1.73 Upper 95% C.I. 374.27 14.96 2.12 75th Percentile 396.10 403.48 16.03 15.48 2.38 2.34 90th Percentile 435.51 433.13 17.98 17.71 2.89 2.82 PASCO COUNTY salinity >30 ppt TOTAL NITROGEN (μg/L) TOTAL PHOSPHORUS (μg/L) CHLOROPHYLL A (uncorrected; μg/L) PASCO COUNTY salinity < 25 ppt TOTAL NITROGEN (μg/L) TOTAL PHOSPHORUS (μg/L) CHLOROPHYLL A (uncorrected; μg/L)

PASCO COUNTY

salinity 25-30 ppt TOTAL NITROGEN (μg/L) TOTAL PHOSPHORUS (μg/L) CHLOROPHYLL A (uncorrected; μg/L)Draft 51 August 2010 Portions of the Project COAST dataset provide an opportunity to compare trends over time in the freshwater sources and the receiving coastal waters. Figure 34 compares the annual geometric mean TN through the period collected by Project COAST for the Weeki Wachee River (Sites 1 and 2, with Site 3 influenced by the riv er and Gulf; Figure 3 5 ) and coastal areas (Sites 4 through 10; Figure 35 ).

As previously mentioned, TN (specifically nitrate) has increased in recent years in the Weeki Wachee river due to anthropogenic factors (Harrington et al. 2010), and that trend is evident at Sites 1 and 2 (Figure 34 ). However, the coastal sites do not follow the same pattern. The year 1998 was very wet, and TN concentrations at the coastal sites were significantly higher in 1998 than during other study years; however, concentrations at the river sites did not increase as dramatically. These data suggest that the increased loading in the freshwater systems has not been sufficient to exceed the capacity of the river and estuary to use those nutrients, and thus the nutrient concentrations in the estuary have not increased. No further increase is anticipated due to the proposed nitrate criteria that will apply to these spring runs (<0.35 mg/L).

Figure 34. Geometric mean TN concentrations per station for the Weeki Wachee River a nd coastal sites. Sites 1 and 2 are in the river, Site 3 is at the river mouth, and Sites 4 through 10 are in the coastal area. 0 100 200 300 400 500 600 700 800 900

1997 1998 1999 2000 2001 2002 2003 2004 2006Total Nitrogen (μg/L) 

## Geometric Mean TN Concentration for Weeki Wachee Stations, COAST

Weeki Wachee

- 1

Weeki Wachee

- 2

Weeki Wachee

- 3

Weeki Wachee

- 4

Weeki Wachee

- 5

Weeki Wachee

- 6

Weeki Wachee

- 7

Weeki Wachee

- 8

Weeki Wachee

- 9

Weeki Wachee

- 10Draft 52 August 2010 Figure 35. Location of the Weeki Wachee River and coastal sites in Project COAST.

MML Intensive Study of the Chassahowitzka NWR , 1996

– 200 1 MML measured water chemistry and SAV within the boundaries of the Chassahowitzka NWR from 1996
to 2004 . The purpose of the study was to establish a baseline condition for the refuge , but MML was als o able to document changes due to a major storm year. The study included a network of 30 coastal stations and eight riverine stations within the refuge (Figure 36 ), some sampled approximately 30 times during the study (3 to 5 times per year) and some only sampled a few times. MML collected water quality data and conducted SAV surveys. The results are available in M ML reports (Dixon and Estevez 1998; Dixon and Estevez 2001 ; Toutant et al. 2004), and are summarized here ( additional data analyses are provid ed in a later section) . Water quality analyses included N species, TP, orthophosphate, chlorophyll a (corrected), and other water quality and clarity measurements. Analyses were conducted using EPA - and F DEP

- approved methods at a NELAC

- certified lab. MML also conducted studies of the invertebrate community along the length of the Chassahowitzka River, including some estuary areas (Leverone 2006).

Dixon and Estevez ( 1998 ) reported on the first 2 years of the study , and Dixon and Estevez (2001) reported through 2001

. They reported that the waters of Chassahowitska Bay are very well mixed and shallow, with strong tidal currents. Only 5% of observations at coastal stations were below 4 5 mg/L ;Draft 53 August 2010 these were in the early morning at several stations, mainly in the northern part of the refuge (Figure 37 )

. The long term mean at coastal stations was 6.8 mg/L (Dixon and Estevez 2001)

.

Figure 36

. Sampling stations in the Chassahowitzka N WR in the 1996

– 2001 MML st udy (from Dixon and Estevez 2001).Draft 54 August 2010 Figure 37

. DO (means and quartiles) for stations along the riverine transect. Stations 24, 26, and 44 are in the coastal areas (from Dixon and Estevez 2001)

.

Nitrate+nitrite concentrations in the Chassahowitzka River had increased in the years prior to this sampling program, but nearly all of that N is assimilated by algae before it reaches the coastal sites
, rather than being converted to another form of nitrogen (Figure 38 ; Dixon and Estevez 2001 ) . TN concentrations increase with salinity and distance offshore, which is co ntrary to the expected pattern. Dixon and Estevez (2001) postulate that the Withlacoochee and/or Suwannee Rivers to the north generate a plume of high -n utrient water that travels over the offshore areas of the Springs Coast. They cited observations that peak flows in the Weeki Wachee River occurred between August 1997 and March 1998, but bloom conditions within that estuary did not become established unt il May

– June 1998, implying a nutrient source other than the Weeki Wachee River (Dixon and Estevez 2001).Draft 55 August 2010 Figure 38

. Mean TN, IN, and organic nitrogen (ON) along the riverine transect , illustrating the generally conservative net behavior downstream of Station R1 .7; salinity 3.5 practical salinity units (PSU) (F igure 28 in Dixon and Estevez 2001)

.

FDEP Analysis of MML Study Data Statistical Analysis

– MML graciously provided FDEP with the full dataset from its 1996

– 2004 study of the springs, rivers, and coastal area of the Chassahowitzka NWR. Most of the following analyses focused on the coastal sites (Figure 39 ). Comparisons of TP data from this study and available TP data from similar sites during the same periods revealed some discrepancies between t he MML data and other sources. The MML results were consistently higher than results from the FDEP Tallahassee lab for the spring head or the LakeWatch lab for coastal stations (Appendix Figure D

- 5) . Analytical methods differ between the organizations, a nd further investigation will be necessary to determine the cause of the difference. Due to the longer time span and broader spatial coverage of the Project COAST data, this report does not include MML TP data.

Sites sampled varied from year to year durin g the MML study, with some sites sampled for the duration of the study and other sites only sampled during one or two years. For the purposes of numeric nutrient criteria development, only data from sites sampled each year were included, and 1996 data wer e not included due to the small sample size that year. Table 1 4 lists the sample sizes for each site/year used. The years included were 1997 to 2004, and the sites included were 3, 4, 7, 18, 21, 23, 24, 26, 28, 30, 40C, and 44 (Figure 39 ). TN was calcul ated by adding the results for nitrate+nitrite ( NO 2+3 –N) and total Kjeldahl nitrogen ( TKN ) . If the result was below detection, then half the detection limit was used in the TN calculation.Draft 56 August 2010 Figure 39 . Water quality sampling sites from the MML study of the Chassahowitzka R iver and coast, used in FDEP ’s data analysis.

Table 14

. Sample sizes for sites and years for FDEP ’s analysis of the M ML study of the Chassahowitzka NWR. Station 1996 1997 1998 1999 2000 2001 2002 2003 2004 18 1 3 4 5 4 4 4 3 2 21 1 3 3 5 4 4 4 3 2 23 1 2 5 5 4 4 4 3 2 24 2 3 4 5 4 4 4 3 2 26 1 2 4 5 5 4 4 3 2 28 1 2 4 5 4 4 4 3 2 3 1 2 4 5 4 4 4 3 2 30 1 2 4 5 4 4 4 3 2 4 1 2 5 5 4 4 4 3 2 40C 1 2 4 5 4 4 4 3 2 44 1 6 5 4 4 4 3 2
7 1 2 4 5 4 4 4 3 2Draft 57 August 2010 Figure 40

. Mean annual salinity is positively related to annual geometric mean TN . Salinity was depressed at all stations during 1998, a year of particularly high rainfall.

Figure 41

. Annual geometric mean corrected chlorophyll a at Chassahowitzka River sites (R4.0

– R0.0) and Bay sites (40C

- 3) collected by M ML . Very high chlorophyll a levels were measured at the b ay sites in 1998 (El Niño event); stable levels in the river indicate that the increase was due to input from coastal waters. 0 200 400 600 800 1000 1200

0 5 10 15 20 25 30 35Annual Geometric Mean TN (μg/L)

Annual Mean Salinity (ppt) 

### Annual Mean Salinity vs. Annual Geometric Mean Total Nitrogen for 12 MML Chassahowitzka Estuary Sites

1997

1998

1999

2000

2001

2002

2003

2004

0 5 10 15 20 25 30R4.0R3.0R2.5R2.0R1.7R1.3R1.0R0.040C4430282624232118743 Annual Geometric Mean Chlorophyll a (corrected, μg/L), Chassahowitzka River (R0.0

- 4.0) and Bay (3

- 40C) Sites, by MML

1997

1998

1999

2000

2001

2002

2003

2004Draft 58 August 2010 Data were analyzed as described above for Project COAST data. There was a positive relationship between salinity and TN within years, though it was not consistent (Figure 40 ). This positive relationship for many years indicates that there is a frequent s ource of N to this estuary that is not related to the Chassahowitzka or Homosassa River discharge. T he annual geometric mean for each station and year was calculated
, and then the stations were pooled to describe the distribution of annual geometric

means overall (Table 15 ). Stations were also separated into two salinity groups, with stations that had average salinity over the life of the project of less than 20 ppt in one group, and stations with average salinity greater than 20 ppt into a second group ( Table 16 ). This division was exploratory, and results further indicate that N concentrations are generally higher in higher salinity areas, due to nutrient

sources outside of the watershed

. Note that chlorophyll a values are lower at high salinity, which may support Dr. Frazer’s conclusion that this part of the coast is phosphorus

- limited.

As noted in Toutant et al. (2004) and all of the Project COAST reports (Frazer, Jacoby refs

. ), 1998 was an El Ni ñ o year with very high rainfall and higher nutrients and chlorophyll values in general. In the MML Chassahowitzka NWR study, the chlorophyll levels were nearly an order of magnitude higher in the coastal areas in 1998 than during other years, but were comparable among all years in the rivers that deliver fresh water to that part of the coast (Figure 41 ). This discrepancy suggests that the higher chlorophyll a in 1998 was due to far

- field effects from rivers to the north, carried by a southerly current; this conclusion was reached by investigators through experience and modeling (Dixon and Estevez 2001 ; Jolliff et al. 2003 ; Weisberg et al. 2004).Draft 59 August 2010 Table 15

. Summary of data analysis for coastal areas of the Chassahowitzka NWR, 1997

–

2004 (12 stations). The first table contains only station years with at least 4 samples; the second table contains all station years (range 1 to 6 samples per station year ; mean 3.6 samples per station year). Data collected and analyzed by M ML

.

LN = N atural logarithm GM = G eometric mean C.I. = C onfidence interval Note: Long

- term region annual geometric mean and the 90 th percentile of site annual geometric means within the region are shown in bold.

Log Normal Distibution Empirical Percentile Log Normal Distibution Empirical Percentile Mean LN 6.21 0.27 Std. Dev. LN 0.31 1.04 N 60 59 95% C.I. 0.08 0.27 Long-term GM 495.75 522.51 1.32 2.51 Lower 95% C.I. 457.07 1.00 Upper 95% C.I. 537.71 1.72 75th Percentile 612.89 597.73 2.65 1.92 90th Percentile 741.81 802.97 4.96 8.54

Log Normal Distibution Empirical Percentile Log Normal Distibution Empirical Percentile Mean LN 6.21 0.18 Std. Dev. LN 0.31 0.96 N 86 96 95% C.I. 0.07 0.19 Long-term GM 498.47 516.08 1.19 2.22 Lower 95% C.I. 466.27 0.98 Upper 95% C.I. 532.90 1.45 75th Percentile 615.01 596.78 2.27 1.51 90th Percentile 743.02 781.24 4.06 6.71



### Chassahowitzka NWR (min 4 samples/yr) TOTAL NITROGEN (μg/L) CHLOROPHYLL A (Corrected; μg/L)



### Chassahowitzka NWR (all years) TOTAL NITROGEN (μg/L) CHLOROPHYLL A (Corrected; μg/L)Draft 60 August 2010 Table 16. Summary of data analysis for coastal areas of the Chassahowitzka NWR, 1997

–

2004, with stations divided by mean salinity ( 5 stations < 20 ppt ; 7 stations > 20 ppt). Each salinity category contains tables for which only station years with at least 4 samples were included, and tables for which all station years were included (range 1 to 6 samples per station year ; mean 3.6 sam ples per station year). Data collected and analyzed by M ML

.

LN = N atural logarithm GM = G eometric mean C.I. = C onfidence interval Note: Long

- term region annual geometric mean and the 90 th percentile of site annual geometric means within the region are shown in bold.

Random S ampling by IMAP through the F WRI Florida’s IMAP was a probabilistic sampling program for Florida’s marine waters that sampled the whole state from 2000 to 2004. Th e program was conducted by the FWRI in cooperation with the EPA ’s Gulf Breeze office. The Crystal River Estuary ( west- central coast ) was t he only area of the Springs Coast included in th e program.

Table 17 contains summary water quality data as reported in F DEP’s IWR database Run 40 (2010). Although the IMAP reports indicate that TN was analyzed, the IWR database only contained nitrate+nitrite data

. IMAP reports do not include a qualitative assessment of t he study findings, but simply a report of some of the quantitative results. Nutrient and chlorophyll a concentrations were low and similar to other data sources. Log Normal Distibution Empirical Percentile Log Normal Distibution Empirical Percentile Log Normal Distibution Empirical Percentile Log Normal Distibution Empirical Percentile Mean LN 6.11 0.70 6.08 0.59 Std. Dev. LN 0.25 0.85 0.25 0.72 N 25 25 40 40 95% C.I. 0.10 0.35 0.08 0.23 Long-term GM 449.40 464.44 2.01 3.12 435.86 449.78 1.81 2.56 Lower 95% C.I. 404.67 1.41 402.41 1.44 Upper 95% C.I. 499.09 2.86 472.09 2.28 75th Percentile 533.40 478.63 3.58 2.13 515.81 507.16 2.95 2.15 90th Percentile 622.34 665.54 6.02 9.10 600.23 654.83 4.57 7.17

Log Normal Distibution Empirical Percentile Log Normal Distibution Empirical Percentile Log Normal Distibution Empirical Percentile Log Normal Distibution Empirical Percentile Mean LN 6.28 -0.04 6.28 -0.12 Std. Dev. LN 0.34 1.06 0.32 1.00 N 35 34 56 56 95% C.I. 0.12 0.37 0.09 0.27 Long-term GM 531.76 414.93 0.96 2.05 534.42 563.43 0.89 1.97 Lower 95% C.I. 473.55 0.67 490.24 0.68 Upper 95% C.I. 597.13 1.39 582.58 1.16 75th Percentile 667.70 476.64 1.97 0.87 664.14 644.53 1.74 0.89 90th Percentile 819.53 662.93 3.73 7.13 807.61 857.15 3.18 6.23 TOTAL NITROGEN (μg/L) CHLOROPHYLL A (Corrected; μg/L)

TOTAL NITROGEN (μg/L) CHLOROPHYLL A Chassahowitzka NWR (min 4 samples/yr)
Salinity < 20 ppt (5 sites) Chassahowitzka NWR (all years)

Salinity > 20 ppt (7 sites) TOTAL NITROGEN (μg/L) CHLOROPHYLL A (Corrected; μg/L)

Chassahowitzka NWR (min 4 samples/yr) TOTAL NITROGEN (μg/L) CHLOROPHYLL A Chassahowitzka NWR (all years)Draft 61 August 2010 Table 17 . Mean values by area and year for IMAP sampling in the region of the Crystal Ri ver Estuary (data from F DEP IWR Run 40). Samples for chlorophyll a were depth integrated ; others were surface grabs. Geographic Area Year N Chlorophyll a (corrected, μg/L) Color (PCU) Nitrate + Nitrite (mg/L) TP (mg/L) Salinity (ppt)

Crystal River Estuary 2003 8 2.09 15 0.002 0.019 20.3



### W aters on the 303(d) L ist
Only one marine area within the Springs Coast were listed for nutrients, chlorophyll a , or DO , and that area was the tidal portion of the Anclote River

. The chlorophyll a impairment is based on a nnual average chlorophyll a values exceeding 11 ug/l in 1999, 2001, and 2002 ( values of 13.48, 14.89, and 12.26 ug/l, respectively ) . Nitrogen was determined to be the limiting nutrient based on a median TN/TP ratio of 8.2 (74 valu es). Verified period total nitrogen median = 0.77 mg/L (74 values), total phosphorus = 0.1 (87 values), and BOD median = 2 mg/l (82 values) for the assessed tidal WBID 1440A

. Other areas are listed for mercury or for bacteria (Table 18). Mercury impairment is not related to nutrients, and it is possible to have bacteria impairments without nutrient pollution sources (see discussion below).

Table 18. Waterbody IDs within the marine portions of the Springs Coast region that are listed on the 303(d) list of impaired waters.
Basin Group Name Planning Unit Waterbody ID (WBID) Water Segment Name Parameters Assessed (IWR) Concentration Causing Impairment

Springs Coast Anclote River / Coastal Pinellas County 8044C ROBERT K REES PARK BEACH Bacteria Beach advisories > 21 days/yr

Springs Coast Anclote River / Coastal Pinellas County 8045A GULF HARBORS BEACH Bacteria Beach advisories > 21 days/yr
Springs Coast Crystal River / Kings Bay Planning Unit 8039A FORT ISLAND GULF BEACH Bacteria Beach advisories > 21 days/yr Springs Coast Middle Coastal 1409B OELSNER PARK BEACH Bacteria Beach advisories > 21 days/yr Springs Coast Middle Coastal 8042A PINE ISLAND BEACH Bacteria Beach advisories > 21 days/yr Springs Coast Middle Coastal 8044A ROBERT J STRICKLAND BEACH Bacteria Beach advisories > 21 days/yr

Springs Coast Middle Coastal 8044B BRASHER PARK BEACH Bacteria Beach advisories > 21 days/yr Springs Coast Middle Coastal 8044D ENERGY AND MARINE CENTER Bacteria Beach advisories > 21 days/yr Springs Coast Anclote River / Coastal Pinellas County 1440A ANCLOTE RIVER BAYOU COMPLEX (SPRING BAYOU) Dissolved Oxygen < 4.0 mg/L

Springs Coast Anclote River / Coastal Pinellas County 1440 ANCLOTE RIVER TIDAL Mercury (in fish tissue) Exceeds DoH threshold ( > 0.43 mg/kg) Springs Coast Anclote River / Coastal Pinellas County 1440A ANCLOTE RIVER BAYOU COMPLEX (SPRING BAYOU) Nutrients (chla) Median TN = 0.77 mg/LDraft 62 August 2010 The use of fecal coliform as indicator s of the presence of human pathogens has been under scrutiny in Florida for the past decade. One of the priorities of the Gulf of Mexico Alliance (GOMA) is the need to improve microbial source tracking (MST) and pathogen

- detection met hods for use under Gulf of Mexico conditions (GOMA 2009). The GOMA Pathogens Workgroup recently submitted comments regarding the status of EPA recreational water quality criteria (GOMA 2009). It expressed concern that the EPA recreational criteria were d erived in places that do not represent Gulf of Mexico conditions, and that the use of fecal indicators was not appropriate for waters primarily influenced by animal sources. Areas in the Gulf of Mexico for which the group thought the EPA criteria might no t be appropriate included low

population

- density coastal areas, areas of heavy rainfall, subtropical latitudes, and areas where waters contain a large amount of organic detritus and/or CDOM ( GOMA 2009).

Boehm et al. (2009) express similar concern about the current and proposed recreational criteria, and specifically call attention to the need for further research and revision in tropical waters and waters adversely impacted by urban runoff and animal feces. This is not to say that fecal coliform and
ente rococci bacteria cannot indicate human sources or cannot co

- occur with nutrient inputs, but that there is ample evidence to caution against assuming that the presence of these bacteria automatically indicates the presence of anthropogenic nutrients.

The fo llowing text is taken from a review conducted by Dr. V.J

. Harwood of the University of South Florida (USF) as part of a n MST project she is conducting for FDEP:

The main groups of indicator bacteria for recreational water quality assessment in use today include fecal coliforms, or a specific member of that group, Escherichia coli, in fresh water and the genus Enterococcus in both fresh and estuarine/marine waters. However, in order for the indicator concept to work optimally there are many assumptions th at must hold true. One of the most important assumptions is that indicator bacteria must co

- occur with human pathogens when pathogens are present and pose a human health risk. Unfortunately, recent research has indicated that this assumption is often false by showing that the presence of indicator bacteria do not always correlate well with the presence of pathogens such as Salmonella
, Campylobacter
, Cryptosporidium
, Giardia , or enteric viruses (Anderson et al. 2005, Bonadonna et al. 2002, Harwood et al. 2005, Lemarchand and Lebaron 2003, Lund 1996, Rees et al. 1998). One important reason for the lack of correlation between traditional fecal indicator bacteria and pathogens is that the indicator bacteria are not specific to humans, nor to other hosts known to shed human pathogens in their feces, but are present in the intestines of all warm

- blooded animals and some cold

- blooded animals (Souza et al. 1999). Because not all animals are equally likely to carry human pathogens, contamination from all sources does not represent an equal health risk. Thus, some sources of fecal contamination in water are of greater concern than others. Furthermore, there is increasing evidence of naturalized or environmentally adapted strains indicator bacteria (both coliforms and enterococci) that are capable of persisting in a culturable form for extended periods, or even growing, in a wide variety of environmental matrices, including terrestrial soils, aquatic sediments, and attached to aquatic vegetation (Byappanahalli and Fujioka 1998, Byappanahalli et al. 2003, Ishii et al. 2006, Jeng et al. 2005, Ksoll et al. 2007, Solo

- Gabriele et al. 2000, Topp et al. 2003, Whitman et al. 2003). If indicator bacteria are persisting in environmental matrices their reintroduction into the water column, such as might occur during storms or highDraft 63 August 2010 recreational activity, may lead to false positive indications regarding contamination and public health risk. As a result of these two confounding factors, it is now clear that simply measuring concentrations of waterborne indicator bacteria do not offer detailed enough information to properly determine health risks associated with recreational water use. Furthermore, this practice does not allow specific sources of contamination to be identified or targeted for remediation of water quality.



### Proposed Numeric Nutrient Criteria
The data and syntheses presented here show that the biological communities along the Springs Coast are meeting the designated aquatic life use. Some positive correlations with time were found for TN, TP, and chlorophyll a in coastal Citrus county during the wet months (Jacoby et al. 2009a, 2009b), but the coastal ecosystem has not shown detrimental effects and those trends are not apparent in the data overall . Additionally, increased nitrate in some spring

- fed rivers has not influenced the nutrient regime of the coastal area overall. It is possible that there has been some seagrass loss off the coast of Crystal River. The Anclote River Estuary is on the 303(d) list for chlorophyll a and dissolved oxygen and the coastal area adjacent to the Anclote has higher TP and chlorophyll a than coastal areas just north of it off the Pithlachascotee River. I t has not been determined whether or not those values are highe r due to anthropogenic activity

. Chlorophyll a values measured in the Anclote Estuary by the COAST program from 2000

- 2006 are comparable to those measured in the estuary a rea in 1973

- 74 (Johansson 1975)

. [Feedback from the public welcome] FDEP r ecommend s numeric nutrient criteria that will maintain the existing long

- term nutrient regime and not allow increases, as determined by the available data , but excluding data from areas that have potentially been identified as nutrient enriched

. The magn itude of nutrients is fairly consistent along this coast (Table 19 ), from the Crystal River to the Anclote River , but nutrients and chlorophyll a vary with salinity and the sources of the nutrients differ between the northern and southern areas of the region. Criteria could either be derived for each river system individually, or developed collectively for the whole region, taking salinity into account. To tal phosphorus and chlorophyll a are generally higher in waters of lower salinity (Table 19), but total nitrogen levels do not decrease as much at higher salinities, likely due to nitrogen coming from larger rivers to the north (Suwannee, Withlacoochee).

[FDEP is seeking input on appropriate regionalization or separation by salinity along the Springs Coast

. Below we propose criteria based on mean annual site salinity. ]

Table 19. Mean and standard deviations of site annual geometric means, summarized by subregion and salinity range. Note that fewer than ten sites are reported for some subregions because freshwater sites were not included. N = sample size, SD = standard deviation

N Mean Chlorophyll **a** ,

uncorrected SD Chlorophyll **a** ,

uncorrected Mean Total Nitrogen SD Total Nitrogen Mean Total Phosphorus SD Total Phosphorus Means by Subregion Crystal 9 2.74 1.03 322 79.71 18.99 5.08 Homosassa 9 1.65 1.12 401 74.23 11.93 3.95 Chassahowitzka 7 1.96 1.18 379 8.72 11.63 3.92 Weeki Wachee 7 0.96 0.10 420 17.74 8.32 0.53 Aripeka 10 0.71 0.18 386 25.23 6.75 0.46 Hudson 10 0.74 0.23 368 39.33 7.03 0.86 Pithlachascotee 9 1.44 0.97 413 48.10 11.91 6.05Draft 64 August 2010 Anclote 10 2.04 0.65 379 38.19 14.77 2.81 Means by Salinity Category < 20 ppt 17 2.48 1.25 369 64.52 15.76 6.77 20

- 25 ppt 26 1.24 0.65 407 59.20 9.93 3.57 25

- 32 ppt 28 1.19 0.76 368 31.01 10.17 4.01

Methodology

For consistent application and for providing an appropriate level of protection, water quality criteria need to include magnitude, frequency, and duration components. The magnitude is a measure of how much of a pollutant may be present in the water without an unacceptable adverse effect. Duration is a measure of how long the pollutant may be above the magnitude, and frequency relates to how often the magnitude may be exceeded without adverse effects. It is preferred to derive the magnitude component of a criterion through a cause

- effect relationship (such as those measured through toxicity testing). The magnitude would then be set at a level that would protect a majority of the sensitive aquatic organisms inhabiting the system. Absent a demonstrated ca use

- effect relationship, the magnitude may be set at a level designed to maintain the current data distribution, accounting for natural temporal variability, when the current conditions are protective of the designated uses of the waterbody. Since a crite rion derived based on the existing data distribution has no direct link to any observed cause and effect relationship, it is assumed that maintaining the current data distribution will preserve the uses associated with that distribution.

The frequency an d duration components of the criteria are best established as additional descriptors of the reference condition data distribution. Specifically, these components should be part of a statistical test designed to determine whether the long

- term distribution of data has shifted upward ( or in some cases, downward) from the reference distribution. This test would then be used to determine whether future monitoring data are consistent with the magnitude (long

- term average) defined by the reference dataset. It is critical to account for the natural variability surrounding the magnitude expression and to control for statistical errors.

The derivation of the magnitude, frequency and duration components of the numeric nutrient criteria for Springs Coast is descr ibed briefly below. More details concerning the statistical approaches used can be found in the document “Overview of FDEP Approaches for Nutrient Criteria Development in Marine Waters” (FDEP 2010).

Magnitude

The magnitude component can be set at a variety of values based on the frequency and duration that will be used to determine compliance. For the “healthy existing conditions” approach, FDEP established the magnitude at: a) an adjusted long

- term central t endency (geometric mean) of the distribution, expressed as a long

- term geometric mean never to be exceeded; and b) an annual geometric mean, not to be exceeded more than two times over a five - year period. The long

- term average condition was adjusted to a level that represents an insignificant increase from the baseline. Allowing for an insignificant increase accounts for uncertainty in the estimate of the mean and partially addresses theDraft 65 August 2010 fact that the reference based approach fails to identify a threshol d of imbalance, and thus is highly prone to excessive Type I error. For the purpose of antidegradation evaluations, EPA has established that a ten percent change in a water quality parameter represents an insignificant departure from the historical condit ion, known as a de minimus change (US Sixth Circuit Court 2008). Therefore, the long

term geometric mean limit was derived to allow for up to a ten percent increase in the long

- term geometric mean, which was calculated as the geometric mean of the annual geometric means of the long

- term dataset for each segment of the waterbody.

Because it is not always practical to assess compliance with the criteria on the same long

- term basis, FDEP also developed criteria expressed as an annual geometric mean so that estuaries could be assessed on an annual basis. It should be noted that the duration and frequency components of the criteria must be linked to the response timeframe of the sensitive endpoint. Short

- term averaging periods (e.g., 1 to 30 days) might be app ropriate for nutrient criteria where a sufficiently robust cause

- effect relationship has demonstrated that a eutrophic response occurs over such timeframes. If however, such a short

term response cannot be demonstrated, or there is no indicati on of use im pairment, longer averaging periods should be used.

Since the duration and frequency components of the criteria must be consistent with the derivation of the magnitude component, the long

- term geometric mean target cannot simply be applied as an annual

m ean. Doing so would result in an unacceptability high Type I failure rate (identifying a healthy system as being impaired) since approximately 50 percent of the individual yearly means are expected to be above the long

- term mean. Therefore, the long

- term target must be adjusted to allow for the application to a shorter duration with an acceptable Type I error rate of no more than a 10 percent.

An annual criterion with an approximate 10 percent Type I error rate for a given frequency was derived by appropr iately accounting for the annual variability above the mean. This annual target concentration was derived as an upper percentile of the distribution of the annual geometric mean concentrations. Previous proposals by EPA have utilized three

- year assessmen t periods to express the duration nutrient criteria components. Although it is possible to construct a test that achieves the 10 percent Type I error rate target over a 3

- year period, a slightly longer period (5 years) will provide better control for Typ e II error and will more fully capture climatic cycles ( e.g ., el nino, la nina), which tend to be longer than three years in Florida (and may actually be on a multi

- decadal scale). Furthermore, a five year period is more consistent with both the State’s five year 303(d) assessment and NPDES permit renewal cycles.

Given a five year a ssessment period, FDEP derived criteria expressed as an annual geometric mean by using the 75 th percentile of the annual geometric means from the long

- term dataset. FDEP demons trated that setting the criteria at this percentile results in a magnitude that, when expressed as an annual geometric mean not to be exceeded more than twice during a five

- year period, will achieve the targeted 10 percent error rate

. The magnitude compon ent of the criteria (not to be exceeded more than twice in a 5 year period) was established to allow for two separate assessments:

**•** As an annual geometric mean for a network of stations in a specified segment of the waterbody; andDraft 66 August 2010 **•** As an annual geometric mean for a single station in a given segment.

The two expressions of magnitude differ in the handling of within

- segment spatial variability. The network average magnitude was calculated based on the distribution of spatially averaged annual geometric mean s, while the single site magnitude was calculated using the distribution of station annual geometric means. Use of the network average magnitude is appropriate for assessing overall segment
status. However, a network average is only representative of ov erall segment status if it is relatively homogeneous. I f the segment is not well mixed, is very large, or contains localized nutrient sources, then there is a potential that isolated areas of enrichment may be masked in the network spatial
average. There fore, the single station annual geometric mean has the benefit of assessing localized enrichment patterns. DEP has not decided whether both expressions of magnitude are needed in all cases, and we are seeking additional feedback from local experts and sta keholders.

Summary of the Proposed Criteria

FDEP proposes three sets of potential criteria: a) a long

- term geometric mean concentration; b) an annual geometric mean of values from a network of stations over a given area, not to be exceeded more than twice in a five

- year period; and c) a n annual geometric mean of values from a single location, not to be exceeded more than twice in a five

- year period. Data from Crystal and Anclote river estuaries were not included in the calculations for proposed criteria.

The proposed long

- term targets for the protection of a healthy, well

- balanced aquatic community in Springs Coast, as well the annual limits for each segment, are provided in Table 20

. Appropriate salinity zone is determined for a station based on the an nual mean salinity.

Table 20 . Proposed numeric nutrient criteria for all segments of Springs Coast, including TP, TN, and chlorophyll a. For compliance purposes, the long term geometric mean shall not exceed the long term limit nor shall the average of all stations in a segment exceed the network average more than twice in a 5 year period. The last column shows the value which single station shall not exceed, by segment, more than twice in a 5 year period. 

## TP (μg/L) Network Average Assessed as a Single Site GM Salinity Zone LT_GM LT_Limit 2:5 Annual Limit 2:5 Annual Limit
<20 15.8 17.3 20.1 24.3
20

- 25 9.7 10.6 13.0 14.1
>25 8.6 9.4 12.0 12.6 

## TN (μg/L) Network Average Assessed as a Single Site GM Salinity Zone LT_GM LT_Limit 2:5 Annual Limit 2:5 Annual Limit
<20 381 419 468 500
20

- 25 432 476 550 586
>25 368 404 456 466 

## Chlorophyll a (μg/L)Draft 67 August 2010 Network Average Assessed as a Single Site GM Salinity Zone LT_GM LT_Limit 2:5 Annual Limit 2:5 Annual Limit
<20 2.4 2.6 3.5 4.2
20

- 25 1.1 1.2 2.0 2.1
>25 0.8 0.9 1.4 1.5Draft 68 August 2010 

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### Appendix A. Water Quality Data Plots from Entire Record of Project COAST Data
(from Frazer and Jacoby 2010 )

0 200 400 600 800 1000 1200

Mar

- 96 Aug

- 97 Dec

- 98 May

- 00 Sep

- 01 Jan

- 03 Jun

- 04 Oct

- 05 Mar

- 07 Jul

- 08TN (ug/L) Crystal Monthly Average Total Nitrogen (TN) 1996 through 2008 Estuarine Stations

0 10 20 30 40 50 60 70 80

Mar

- 96 Aug

- 97 Dec

- 98 May

- 00 Sep

- 01 Jan

- 03 Jun

- 04 Oct

- 05 Mar

- 07 Jul

- 08TP (ug/L) Crystal Monthly Average Total Phosphorus (TP) 1996 through 2008 Estuarine Stations

0 5 10 15 20 25

Mar

- 96 Aug

- 97 Dec

- 98 May

- 00 Sep

- 01 Jan

- 03 Jun

- 04 Oct

- 05 Mar

- 07 Jul

- 08CHL-a (ug/L) Crystal Average Chlorophyll

- a (CHL

- a) 1996 through 2008 Estuarine StationsDraft 73 August 2010 0 200 400 600 800 1000 1200 1400 1600

Mar

- 96 Aug

- 97 Dec

- 98 May

- 00 Sep

- 01 Jan

- 03 Jun

- 04 Oct

- 05 Mar

- 07 Jul

- 08TN (ug/L) Chassahowitzka Monthly Average Total Nitrogen (TN) 1997 through 2008 Estuarine Stations

0 5 10 15 20 25 30 35 40 45

Mar

- 96 Aug

- 97 Dec

- 98 May

- 00 Sep

- 01 Jan

- 03 Jun

- 04 Oct

- 05 Mar

- 07 Jul

- 08TP (ug/L) Chassahowitzka Monthly Average Total Phosphorus (TP) 1997 through 2008 Estuarine Stations

0 5 10 15 20 25

Mar

- 96 Aug

- 97 Dec

- 98 May

- 00 Sep

- 01 Jan

- 03 Jun

- 04 Oct

- 05 Mar

- 07 Jul

- 08CHL-a (ug/L) Chassahowitzka Average Chlorophyll

- a (CHL

- a) 1997 through 2008 Estuarine StationsDraft 74 August 2010 0 200 400 600 800 1000 1200

Mar

- 96 Aug

- 97 Dec

- 98 May

- 00 Sep

- 01 Jan

- 03 Jun

- 04 Oct

- 05 Mar

- 07 Jul

- 08TN (ug/L) Weeki Wachee Monthly Average Total Nitrogen (TN) 1997 through 2008 Estuarine Stations

0 5 10 15 20 25 30

Mar

- 96 Aug

- 97 Dec

- 98 May

- 00 Sep

- 01 Jan

- 03 Jun

- 04 Oct

- 05 Mar

- 07 Jul

- 08TP (ug/L) Weeki Wachee Monthly Average Total Phosphorus (TP) 1997 through 2008 Estuarine Stations

0 2 4 6 8 10 12

Mar

- 96 Aug

- 97 Dec

- 98 May

- 00 Sep

- 01 Jan

- 03 Jun

- 04 Oct

- 05 Mar

- 07 Jul

- 08CHL-a (ug/L) Weeki Wachee Average Chlorophyll

- a (CHL

- a) 1997 through 2008 Estuarine StationsDraft 75 August 2010 0 200 400 600 800 1000 1200

Mar

- 96 Aug

- 97 Dec

- 98 May

- 00 Sep

- 01 Jan

- 03 Jun

- 04 Oct

- 05 Mar

- 07 Jul

- 08TN (ug/L) Homosassa Monthly Average Total Nitrogen (TN) 1996 through 2008 Estuarine Stations

0 10 20 30 40 50 60

Mar

- 96 Aug

- 97 Dec

- 98 May

- 00 Sep

- 01 Jan

- 03 Jun

- 04 Oct

- 05 Mar

- 07 Jul

- 08TP (ug/L) Homosassa Monthly Average Total Phosphorus (TP) 1996 through 2008 Estuarine Stations

0 5 10 15 20 25

Mar

- 96 Aug

- 97 Dec

- 98 May

- 00 Sep

- 01 Jan

- 03 Jun

- 04 Oct

- 05 Mar

- 07 Jul

- 08CHL-a (ug/L) Homosassa Average Chlorophyll

- a (CHL

- a) 1996 through 2008 Estuarine StationsDraft 76 August 2010 0 100 200 300 400 500 600 700 800

May

- 99 Oct

- 00 Feb

- 02 Jun

- 03 Nov

- 04 Mar

- 06 Aug

- 07 Dec

- 08TN (ug/L) Aripeka Monthly Average Total Nitrogen (TN) 2000 through 2008 Estuarine Stations

0 2 4 6 8 10 12 14 16 18

May

- 99 Oct

- 00 Feb

- 02 Jun

- 03 Nov

- 04 Mar

- 06 Aug

- 07 Dec

- 08TP (ug/L) Aripeka Monthly Average Total Phosphorus (TP) 2000 through 2008 Estuarine Stations

0 1 2 3 4 5 6 7

May

- 99 Oct

- 00 Feb

- 02 Jun

- 03 Nov

- 04 Mar

- 06 Aug

- 07 Dec

- 08CHL-a (ug/L) Aripeka Average Chlorophyll

- a (CHL

- a) 2000 through 2008 Estuarine StationsDraft 77 August 2010 0 100 200 300 400 500 600 700 800

May

- 99 Oct

- 00 Feb

- 02 Jun

- 03 Nov

- 04 Mar

- 06 Aug

- 07 Dec

- 08TN (ug/L) Hudson Monthly Average Total Nitrogen (TN) 2000 through 2008 Estuarine Stations

0 5 10 15 20 25

May

- 99 Oct

- 00 Feb

- 02 Jun

- 03 Nov

- 04 Mar

- 06 Aug

- 07 Dec

- 08TP (ug/L) Hudson Monthly Average Total Phosphorus (TP) 2000 through 2008 Estuarine Stations

0 1 2 3 4 5 6 7 8 9 10

May

- 99 Oct

- 00 Feb

- 02 Jun

- 03 Nov

- 04 Mar

- 06 Aug

- 07 Dec

- 08CHL-a (ug/L) Hudson Average Chlorophyll

- a (CHL

- a) 2000 through 2008 Estuarine StationsDraft 78 August 2010 0 100 200 300 400 500 600 700 800 900 1000

May

- 99 Oct

- 00 Feb

- 02 Jun

- 03 Nov

- 04 Mar

- 06 Aug

- 07 Dec

- 08TN (ug/L) Pithlachascotee Monthly Average Total Nitrogen (TN) 2000 through 2008 Estuarine Stations

0 5 10 15 20 25 30 35 40

May

- 99 Oct

- 00 Feb

- 02 Jun

- 03 Nov

- 04 Mar

- 06 Aug

- 07 Dec

- 08TP (ug/L) Pithlachascotee Monthly Average Total Phosphorus (TP) 2000 through 2008 Estuarine Stations

0 2 4 6 8 10 12 14 16 18 20

May

- 99 Oct

- 00 Feb

- 02 Jun

- 03 Nov

- 04 Mar

- 06 Aug

- 07 Dec

- 08CHL-a (ug/L) Pithlachascotee Average Chlorophyll

- a (CHL

- a) 2000 through 2008 Estuarine StationsDraft 79 August 2010 0 100 200 300 400 500 600 700 800

May

- 99 Oct

- 00 Feb

- 02 Jun

- 03 Nov

- 04 Mar

- 06 Aug

- 07 Dec

- 08TN (ug/L) Anclote Monthly Average Total Nitrogen (TN) 2000 through 2008 Estuarine Stations

0 5 10 15 20 25 30 35 40

May

- 99 Oct

- 00 Feb

- 02 Jun

- 03 Nov

- 04 Mar

- 06 Aug

- 07 Dec

- 08TP (ug/L) Anclote Monthly Average Total Phosphorus (TP) 2000 through 2008 Estuarine Stations

0 2 4 6 8 10 12

May

- 99 Oct

- 00 Feb

- 02 Jun

- 03 Nov

- 04 Mar

- 06 Aug

- 07 Dec

- 08CHL-a (ug/L) Anclote Average Chlorophyll

- a (CHL

- a) 2000 through 2008 Estuarine StationsDraft 80 August 2010 

### Appendix B. Annual Geometric M ean Chlorophyll a ( Uncorrected ) and TN from Project COAST

Data are from Project COAST and include all sites. Freshwater sites removed from the statistical analyses are Chassahowitzka

- 1,

- 2,

- 10 ; Crystal

4; Homosassa -5; Pithlachascotee -1 ; and Weeki Wachee

- 1, -2.Draft 81 August 2010Draft 82 August 2010Draft 83 August 2010Draft 84 August 2010Draft 85 August 2010Draft 86 August 2010Draft 87 August 2010Draft 88 August 2010Draft 89 August 2010Draft 90 August 2010Draft 91 August 2010Draft 92 August 2010Draft 93 August 2010 

### Appendix C . Relationship b etween S alinity and A nnual G eometric M ean TN per S ite in 8 C oastal A reas of Project COAST.

Notes: Plots do not include freshwater sites. Data pulled from STORET and analyzed by N

. Wellendorf, F DEP.

0 100 200 300 400 500 600 700 800

0 5 10 15 20 25 30Annual Geometric Mean TN (mg/L)

Mean Annual Salinity 

## Crystal River Bay Salinity vs. TN (9 sites)

1997

1998

1999

2000

2001

2002

2003

2004

2006

0 100 200 300 400 500 600 700

0 5 10 15 20 25 30Annual Geometric Mean TN (mg/L)

Mean Annual Salinity 

## Chassahowitzka (COAST) Salinity vs. TN (7 sites)

1997

1998

1999

2000

2001

2002

2003

2004

2006Draft 94 August 2010 0 100 200 300 400 500 600 700 800 900 1000

0 5 10 15 20 25 30 35Annual Geometric Mean TN (mg/L)

Mean Annual Salinity 

## Homosassa Salinity vs. TN 

# (9 sites)

1997

1998

1999

2000

2001

2002

2003

2004

2006

0 100 200 300 400 500 600 700 800 900

0 5 10 15 20 25 30Annual Geometric Mean TN (mg/L)

Mean Annual Salinity 

## Weeki Wachee Salinity vs. TN 

# (8 sites)

1997

1998

1999

2000

2001

2002

2003

2004

2006Draft 95 August 2010 0 100 200 300 400 500 600

10 15 20 25 30 35Annual Geometric Mean TN (mg/L)

Mean Annual Salinity 

# Aripeka Salinity vs. TN (10 sites)

2000

2001

2002

2003

2004

2006

0 100 200 300 400 500 600 700

10 15 20 25 30 35Annual Geometric Mean TN (mg/L)

Mean Annual Salinity 

# Hudson Salinity vs. TN (10 sites)

2000

2001

2002

2003

2004

2006Draft 96 August 2010 0 100 200 300 400 500 600 700

0 5 10 15 20 25 30 35Annual Geometric Mean TN (mg/L)

Mean Annual Salinity 

# Pithlachascotee Salinity vs. TN (9 sites)

2000

2001

2002

2003

2004

2006

0 100 200 300 400 500 600

20 25 30 35 40Annual Geometric Mean TN (mg/L)

Mean Annual Salinity 

# Anclote

- Salinity vs. TN (10 sites)

2000

2001

2002

2003

2004

2006Draft 97 August 2010 

### Appendix D

. Data Comparisons between Providers

F DEP and SWFWMD Springs Studies

F DEP and SWFWMD have sampling programs that regularly monitor some springs and spring runs. S ome of these data were plotted as an estimate of trends in loading to the estuarine system over time, and as a way to compare data that were collected and analyzed using different methods but from roughly the same sites.

Figure D-1 . T P concentrations in the Weeki Wachee River , 1997

–

2009, sampled by F DEP and Project COAST. 0 0.005

0.01 0.015

0.02 0.025

0.0310/28/19953/11/19977/24/199812/6/19994/19/20019/1/20021/14/20045/28/200510/10/20062/22/20087/6/200911/18/2010Total Phosphorus (mg/L) 

## TP

- Weeki Wachee @ Brooksville TV site vs. COAST sites upstream and downstream w/in 1 mile

TV site

- TP

COAST WW1

- TP

COAST WW2

- TPDraft 98 August 2010 Figure D-2. Comparison of available data for Homosassa Head Spring s , sampled by F DEP and Project COAST.

Figure D- 3. Comparison of COAST TN data and FDEP Trend Variability NO 2+3 data from the Weeki Wachee River. M ost TKN values from the F DEP data were nondetect, and thus FDEP NO 2+3 and Project COAST TN data were compared

.Draft 99 August 2010 Figure D

- 4. Comparison of salinity values at sites that are located close to one another in the Chassahowitzka Estuary, from the COAST and Mote Marine Lab (MML) sampling programs.

Figure D -5

. Comparison of total phosphorus values at sites that are located close to one another in the Chassahowitzka Estuary, from the COAST and Mote Marine Lab (MML) sampling programs. The minimum detection limit (MDL) for the MML lab was 50 μg/L; non

- detects we re plotted as 25 μg/L.Draft 100 August 2010 Figure D

- 6. Comparison of chlorophyll a values at sites that are located close to one another in the Chassahowitzka Estuary, from the COAST and Mote Marine Lab (MML) sampling programs.Draft 101 August 2010 Figure D

- 7. Comparison of total nitrogen values at sites that are located close to one another in the Chassahowitzka Estuary, from the COAST and Mote Marine Lab (MML) sampling programs.Draft 102 August 2010 Figure D

- 8. Comparison of total phosphorus values at sites that are located close to one another in the S uwannee Estuary, from the COAST and Suwannee River Water Management District (SRWMD) sampling programs.Draft 103 August 2010 Figure D

- 9. Comparison of total nitrogen values at sites that are located close to one another in the Suwannee Estuary, from the COAST and Suwannee River Water Management District (SRWMD) sampling programs.