# Site

- Specific Information in Support of Establishing Numeric Nutrient Criteria in Apalachicola Bay

Division of Environmental Assessment and Restoration Standards and Assessment Section Florida Department of Environmental Protection Tallahassee, FL 32399

August 13, 2010Draft ii August 2010 

### Table of Contents

Executive Summary

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

..................................................................................... 3 Sources and Fates of Nutrients

.............................................................................................. 4 Summary of Nutrient Studies by Dr. Robert J. Livingston (FSU)

......................................................... 6 

### Biological Summary

............................................................................................................. 10

SAV

................................................................................................ .............................................. 10 Phytoplankton

.............................................................................................................................. 12 Oysters (Crassostrea virginica) (from Livingston 2010)

................................................................... 13 Infaunal Macroinvertebrates (from Livingston 2010)

..................................................................... 13 Penaeid Shrimp (from Livingston 2010)

......................................................................................... 13 Callinectes Sapidus (from Livingston 2010)

.................................................................................... 14 Fishes (from Livingston 2010)

........................................................................................................ 14 Presence and Frequency of Harmful Algal Blooms (HABs)

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

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

.............................................. 16
Fish Kills

................................................................................................ ....................................... 16 

### Water Quality Studies

......................................................................................................... 17 ANERR Monitoring

....................................................................................................................... 17 Water Quality St udies by Paula Viveros (UF) and ANERR

............................................................... 20 Water Quality Studies by Dr. Robert J. Livingston (FSU), 1972

– 2008

............................................... 30 

### Nutrient Loading Models

..................................................................................................... 31 Waters on the 303(d) List

..................................................................................................... 41 Impair ment for Bacteria Not Necessarily Indicative of Anthropogenic Impact

................................ 44 

### Numeric Nutrient Criteria Recommendations

...................................................................... 45 References

.......................................................................................................................... 50 Appendix A: Nutrients in Apalachicola River

- Bay System

..................................................... 56 Appendix B: Fish Landings by County and Year for all Florida Counties except Walt on
......... 57 Appendix C: Apalachicola River Nutrient Loadings

............................................................... 58 Appendix D: Fish Kills Associated with K. brevis in Franklin County, 2001

– June 21, 2010

...... 59Draft iii August 2010 

### List of Tables

Table 1. Checklist of nutrient enrichment symptoms for Apalachicola Bay

................................................. 2 Table 2. Summary of the physical characteristics of Apalachicola Bay.

...................................................... 4 Table 3. Nutrient concentrations in the Apalachicol a River, Mile 11 (from Frick et al. 1996).

.................. 10 Table 4. East Bay SAV species list (from Fahrny et al. 2006).

..................................................................... 12 Table 5. Apalachicola Bay red tide tracking (FDACS).

................................................................................ 15 Table 6. Mean nutrient measurements in Apalachicola Bay as determined by various researchers over time (Wanat 2010).

........................................................................................................... 20 Table 7. Mean DIN concentration for different areas of Apalachicola Bay, in summer and winter, from Paula Viveros, UF (Wanat 2010).

..................................................................................... 21 Table 8. Mean TDN concentration for different areas of Apalachicola Bay, in summer and winter, from Paula Viveros, UF (Wanat 2010).

..................................................................................... 21 Table 9. Mean SRP concentration for different areas of Apalachicola Bay, in summer and winter, from Paula Viveros, UF (Wanat 2010).

..................................................................................... 22 Table 10. Mean total dissolved phosphorus (TDP) concentration for different areas of Apalachicola Bay, in summer and winter, from Paula Viveros, UF (Wanat 2010).

.................. 22 Table 11. Mean salinity for different areas of Apalachicola Bay, in summer and winter, from Paula Viveros, UF (Wanat 2010 ).

.............................................................................................. 23 Table 12. Mean chlorophyll a concentration for different areas of Apalachicola Bay, in summer and winter, from Paula Viveros, UF (Wanat 2010).

.................................................................. 24 Table 13. Concentration flow regression equations for the Lake Seminole and Sumatra stations (Hydroqual).

.............................................................................................................................. 32 Table 14. Upper distribution of Apalachicola River statistical nutrient loads (after Hydroqual 2010).

................................................................................................ ........................................ 32 Table 15. Impaired waters in the Apalachicola Bay Basin

......................................................................... 41 Table 16. Proposed numeric nutrient criteria for all segments of Apalachicola Bay, including TP, TN , and Chlorophyll a.

. .............................................................................................................. 49Draft iv August 2010 

### List of Figures

Figure 1. Satellite photo of Apalachicola Bay, with labeled sections (from Wanat 2010).

.......................... 3 Figure 2. Map of the Apalachicola

– Chattahoochee

– Flint River Basin. Each separate basin is depicted by a different shade of green (from Wanat 2010).

...................................................... 5 Figure 3. Nitrite

- nitrate and orthophosphate loading in the Apalachicola, Choctawhatchee, Perdido, and Escamb ia Rivers (Livingston 2010).

....................................................................... 8 Figure 4. Livingston’s model of the Apalachicola Bay system, showing key features that result in

ex tremely high primary and secondary productivity.

................................................................ . 9 Figure 5. Percent SAV coverage in East Bay and ANERR monitoring sites, June 200 5 (Edmiston 2008).

................................................................................................ ........................................ 11 Figure 6. ANERR long

- term monitoring locations throughout Apalachicola Bay (Wanat 2010).

.............. 17 Figure 7. Cat Point (Gray) and Dry Bar (Blue) daily average salinity, 1993

– 2008 (solid lines are 90

- day moving average data; dashed lines are linear trend lines) (Wanat 2010).

.................. 18 Figure 8. Areal extent of salinity zones in Apalachicola Bay under various flow regimes. Map at left shows salinity contours in the bay when river flow is between 15,000 and 35,000 cfs. Map at right shows salinity contours in the bay when river flow is below 15,000 cfs (Wanat 2010).

..................................................................................................................... 18 Figure 9. DO (mg/L) at the three data logger locations, from 2008 ANERR data (Wanat 2010).

............. 19 Figure 10. Turbidity at the three data logger locations, from 2008 ANERR data (Wanat 2010).

.............. 19 Figure 11. pH at the three data logger locations, from 2008 ANERR data (Wanat 2010).

........................ 20 Figure 12. Chlorophyll a compared with river flow for four stations in the bay, 2002

– 09, from Paula Viveros, UF (Wanat 2010).

.............................................................................................. 23 Figure 13. Phytoplankton composition, June 2008, by biovolume (μm 3 mL -1 ); stars show station locations on map below; data from Paula Viveros, UF (Wanat 2010).

.................................... 24 Figure 14. Phytoplankton composition, July 2008, by biovolume (μm 3 mL -1 ); stars show station locations on map below; data from Paula Viveros, UF (Wanat 2010).

.................................... 25 Figure 15. Phytoplankton composition, August 2008, by biovolume (μm 3 mL -1 ); stars show station locations on map below; data from Paula Viveros, UF (Wanat 2010).

........................ 25 Figure 16. Map of Apalachicola Bay, showing station locations; stars show certain stations from figures above; data from Paula Viveros, UF (Wanat 2010).

..................................................... 26 Figure 17. Phytoplankton composition, September 2008, by biovolume (μm 3 mL -1 ); stars show station locations on map below; data from Paula Viveros, UF (Wanat 2010).

........................ 26 Figure 18. Phytoplankton composition, October 2008, by biovolume (μm 3 mL -1 ); stars show station l ocations on map below; data from Paula Viveros, UF (Wanat 2010).

........................ 27 Figure 19. Phytoplankton composition, November 2008, by biovolume (μm 3 mL -1 ); stars show station locations on map below; data from Paula Viveros, UF (Wanat 2010).

........................ 27 Figure 20. Map of Apalachicola Bay; stars show station locations from figures above; data from Paula Viveros, UF (Wanat 2010).

.............................................................................................. 28 Figure 21. Phytoplankton species composition, December 2008, by biovolume (μm 3 mL -1 ); stars show station locations on map below; data from Paula Viveros, UF (Wanat 2010).

............... 28 Figure 22. Phytoplankton composition by biovolume (μm 3 mL -1 ), January 2008; stars show station locations on map below; data from Paula Viveros, UF (Wanat 2010).

........................ 29Draft v August 2010 Figure 23. Phytoplankton composition by biovolume (μm 3 mL -1 ), February 2008; stars show station locations on map below; data from Paula Viveros, UF (Wanat 2010).

........................ 29 Figure 24. Map of Apalachicola Bay, showing station locations; stars show certain stations from figures above; data from Paula Viveros, UF (Wanat 2010).

..................................................... 30 Figure 25. Apalachicola Bay system, showing the locations of long

- term sampling stations (1972

– 84).

................................................................................................ ................................ . 31 Figure 26. Station map of the Apalachicola River, from Lake Seminole to the Gulf coast (HydroQual).

............................................................................................................................. 33 Figure 27. Flow compared with TN and TP concentrations for the Apalachicola River at Lake Seminole; data from Florida STORET and USGS 0235800 (HydroQual).

................................... 34 Figure 28. Flow compared with TN and TP concentrations for the Apalachicola River near Sumatra, data from USGS

- 2359170 (HydroQual).

.................................................................... 35 Figure 29. TN and TP concentrations versus flow for the Apalachicola River at Lake Seminole and near Sumatra (post

- 1990) (HydroQual).

................................................................................... 36 Figure 30. TN and TP compared with flow for the Apalachicola River at Lake Seminole; data from Florida STORET and USGS 02358000. Graphs show data points, load based on regression analysis, annual geometric mean (HydroQual).

...................................................... 37 Figure 31. TN and TP compared with flow for the Apalachicola River near Sumatra; data from USGS- 2359170. Graphs show data points, load based on regression analysis, annual geometric mean (HydroQual).

.................................................................................................. 38 Figure 32. Annual geometric mean for TN and TP concentrations for the Apalachicola River at Lake Seminole and near Sumatra (HydroQual).

....................................................................... 39 Figure 33. Probability of annual geometric mean estimated unfiltered nutrient loads for the Apalachicola River at Lake Seminole and near Sumatra (HydroQual).

..................................... 401 Draft August 2010 

### Executive Summary

This report was prepared by t he Florida Department of Environmental Protection (FDEP), in cooperation with local scientists, to support the development of numeric nutrient criteria for Apalachicola Bay. 1

Except for water withdrawal issues occurring far upstream of the bay , the Apalachicola system remains relatively free of human impacts. The Apalachicola River and Bay system is located in one of the least populated areas along the Gulf coast. The Apalachicola Estuary , which is dominated by freshwater inputs from the river, is a shallow
, lagoon

- and

- barrier

- island complex oriented along an east

- west axis

. Important habitats include Spartina/Juncus marshes, unconsolidated soft

- sediment areas, and significant oyster reefs. The Apalachicola Estuary has been described as one of the most productive estuarine systems in the northern hemisphere . This bay is known for its oyster bars and oyster production, producing 90% of Florida’s and 10% of the nation’s oyster harvest (Edmiston 2008). The primary purpose of the proposed numeric nutrient criteria is to protect health y, well

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

The main source of nutrients in Apalachicola Bay is the Apalachicola River, which dominates water quality in the bay and rep resents the chief source of freshwater input. Unlike most estuaries around the state, the critical issue in the Apalachicola has been significant, long

- term reductions of river flow and associated reductions of loading of nutrients and organic matter. Periods of high nutrient and organic matter loading have been associated with relatively high and beneficial secondary production in this system. Reductions in freshwater flow and nutrients have been associated with adverse effects on the fisheries of the Apalachicola system (Livingston 2010).

Since it is characterized as an alluvial system, maintaining phytoplankton biomass and secondary production of fish and oysters is the main concern in Apalachicola Bay. Phytoplankton is the main source of carbon in t he bay (Chanton and Lewis 2002), but Wilson et al. (2009) suggest that benthic production is also important. The bay’s food webs are driven by in situ productivity and
, consequently, the bay depends on the input of “new “nutrients to the system. It is fo r this reason that reductions of river flow (and coincidentally, nutrients) have, on occasion, adversely affected this system in the past (although recovery has been observed when flow and nutrients return). The Apalachicola Estuary is characterized by ab undant phytoplankton production, which serves as the basis of a robust food web, yielding a high abundance of oysters, blue crabs, and commercially important fishes.

Maintaining the existing and historic al healthy conditions is the recommended approach for developing nutrient criteria for Apalachicola Bay. The greatest concern for the b ay is potential reductions in nutrient loads from the river due to reduct ions in river discharge that w ould result in significant impacts to the food web

. The data provide d here demonstrate that the nutrient and chlorophyll concentrations provide for the overall health of the bay (Table 1) . In fact, maintaining phytoplankton production is critical for protecting the bay’s robust food web.

1 Contributors to this report included Dr. Robert J. Livingston (Florida State University [FSU]), Jennifer Wanat and Lauren Levi (FDEP’s Office of Coastal and Aquatic Managed Areas [CAMA]), Jennifer Cherrier (Florida Agricultural and Mechanical University), Paula Viveros (University of Florida [UF]), Dr. Edward Phlips (UF), Dan Tonsmeire (Apalachicola River Keepers), Graham Lewis (Northwest Florida Water Mana gement District [NWFWMD]), Andrew Thuman and Thomas Gallagher (Hydroqual) and Randy Snipes (FDEP).2 Draft August 2010 Table 1. Checklist of nutrient enrichment symptoms for Apalachicola Bay

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

or Currently? Explanation Source

Low dissolved oxygen ( DO ) (hypoxia/anoxia) Yes Hypoxia in the bay is normally not evident; however, low DO levels (< 4 milligrams per liter [ mg/ L] ) have been noted in

some areas. In East Bay, most hypoxic events that occur last less than 4 hours. The low DO episodes are not linked to nutrients and ar e not associated with adverse biological
responses

. Sanger et al. 2002 ; Wanat 2010 ; Edmiston 2008

Reduced clarity No Color ranges from 0 to over 300 platinum cobalt units ( PCU s) at individual stations but is generally in the 20 to 160 range, with lower values near the G ulf

. High color levels, which are a natural condition associated with swamp runoff, generally occur at the river mouth and in the upper areas of East Bay. Edmiston 2008 ; Wanat 2010 ; Livingston 2010

Increased chlorophyll a concentrations No Unlike most estuaries around the state, Apalachicola Bay is an alluvial system and has high primary and secondary productivity, supporting a multimillion

- dollar fishery. Research has shown that elevated chlorophyll a values near the mouth and in East B ay are beneficial and help the system maintain its healthy condition. Livingston 2010

Phytoplankton blooms (nuisance or toxic) Yes Occasional red tide events, which originate offshore and are transported to the bay by currents, affect the system. These events are not related to nutrients from the Apalachicola Bay system. The b ay was last closed for shellfish harvesting due to red tides in 2005 and 2006. Livingston 2010 ; Florida Department of Agriculture and Consumer Services ( FDACS )

Problematic epiphyte growth No N o evidence of epiphyte growth. Due to natural high color and turbidity, submerged aquatic vegetation ( SAV ) is naturally rare in the system, except for oligohaline and fringing areas. -

Problematic macroalgal growth No There is no evidence of adverse macroalgal growth.

-

SAV community changes or loss Yes During periods of low river discharge and unusually high salinities in upper East Bay, reductions of fresh/brackish SAV ha ve occurred. A 2005 hurricane also affected t he fresh/brackish SAV. Note that none of these changes are associated with nutrients. Edmiston 2008 ; Fahrny et al. 2006

Emergent or shoreline vegetation community changes or loss No - -

Coral/hardbottom community changes or loss N/A This habitat type does not typically occur. -

Impacts to benthic community No Variability in benthic communities is associated with freshwater flow. -

Fish kills Yes Episodic fish kills occur due to Karenia brevis blooms moving in from offshore , not related to nutrients in Apalachicola Bay

. The last reported fish kill was on November 8, 2005
, at East Florida Fish and Wildlife Conservation Commission (FWCC) Fish and Wildlife3 Draft August 2010 Point. Research Institute ( FWRI )


### Geographic and Physical Description

Apalachicola Bay is a dynamic, highly productive estuary l ocated in the Florida P anhandle. The bay is a bar

- built, subtropical estuary characterized by large quantities of freshwater inflows from the Apalachicola River. The bay is divided into four major parts: St. George Sound, Apalachicola Bay, East Bay, and St. Vincent Sound (Figure 1). Apalachicola Bay is de signated as an Outstanding Florida Water (OFW), a Class II shellfish harvesting waterbody, a National Es tuarine Research Reserve (NERR)
, a U.S. Environmental Protection Agency ( EPA ) Gulf of Mexico Ecological Management Sit e, and a United Nations Educational, Scientific and Cultural Organization ( UNESCO ) Biosphere Reserve . Portions of the bay are also designated as an Area of Critical State Concer n. Table 2 lists the physical characteristics of the bay
, such as size, volume, watershed area, and depth.

Figure 1. Satellite photo of Apalachicola Bay, with label ed sections ( from Wanat 2010)

. 

## Tate’s Hell

East Bay

St. Vincent Island St. George Island

Sike’s Cut 

## Apalachicola River

Indian Pass



## Little St. George Island West Pass 

### Dog Island East Pass4 Draft August 2010 Table 2

. Summary of the physical characteristics of Apalachicola Bay.
Data Values Source

Estuarine surface area (square kilometers [km 2 ]) 593 km 2 Smith 2003; NOAA

Watershed area (km 2 ) 51,000 Murrell and Caffrey 2005

Land use Primarily forested, pine flatwoods, and bottomland hardwoods Murrell and Caffrey 2005

Mean depth (meters [m]) 2.3 m ANERR

Volume (cubic meters [m 3 ]) 1,074,990,400 m 3 Smith 2003; NOAA

Tidal range (m) 0.58m Smith 2003; NOAA

Tidal freshwater inflow (1,000 cubic meters per day [1,000 m 3 d -1 ]) 64,000 m 3 d - 1 Smith 2003; NOAA

Mean water residence time days) 6 days Murrell and Caffrey 2005

Salinity and salinity zones (practical salinity units) Average salinity: 19 psu Smith 2003; NOAA



### Sources and Fates of Nutrients

The main source of the nutrients in Apalachicola Bay is the Apalachicola River
, the primary source of fresh water entering the bay and the largest river in the state. The Apalachicola River is one part of the Apalachicola

– Chattahoochee – Flint River system, whose basin is located in mainly three states (Figure 2). The Apalachicola R iver provides 83% of the tota l nitrogen (T N) and 78% of the total phosphorus ( T P) found in the bay ( Edmiston 2008 ).

The Apalachicola River dominates water quality in the bay system. As such, the river and the nutrients it delivers represent a major source of coastal productivity in the region (Livingston 1983, 1984; Livingston et al. 1997, 1999, 2000, 2002, and 2005). Because of the protective measures taken in the Apalachicola River floodplain, nutrient loading from sources in Florida is not of concern. In fact, a significant pro blem for the Apalachicola is long

- term reductions of river flow and associated reductions of the loading of nutrients and organic matter. High loading of nutrients and organic matter is associated with relatively high secondary production in this system. Periods of reduced water delivery are associated with reduction s in the fisheries of the Apalachicola system

. Nutrient s, as the foundation for the estua ry’s productivity, are transported to the estuary both in the form of detritus and as compound s dissol ved in the water column (Livingston 1984 b ). N itrogen ( N) is limiting in summer and during periods of lower river flow, while phosphorus ( P) is limiting in winter, when water levels are typically higher

. Phytoplankton productivity is most frequently limite d by N availability, less of ten by P availability (Iverson et al. 1997)

.5 Draft August 2010 Figure 2 . Map of the Apalachicola

– Chattahoochee

– Flint River Basin. E ach separate basin is depicted by a different shade of green ( from Wanat 2010)

.6 Draft August 2010 Point sources that contribute nutrients to the river and bay include municipal wastewater treatment facilities (WWTFs), industrial wastewater facilities, and combined sewer overflows (Frick et al

. 1996 ). There are a total of 15 facilities in the Apalachicola River P lanning U nit : 6 domestic and 8 industrial
waste water facilities
, and 1 concrete batch plant. The major domestic facilities are the city of Blountstown (design fl ow Q = 1.5 million gallons per day [ MGD ] ), the city of Chattahoochee (Q= 0.5 MGD ), Florida State Hospital (Q = 1.3 MGD ), and the town of Sneads (Q = 0.495 MGD ). The only major industrial facility is the Gulf Power Scholz Steam Plant (Q = 129.6 MGD ) (FDEP 2002). The only major surface water discharge facility in the Apalachicola Bay P lanning U nit is the city of Apalachicola sewage treatment plant (des ign fl ow [Q] = 1.0 MGD) , which discharges to a wetland, Huckleberry Creek, the Gulf Intracoastal Waterway (GIWW) , and then the Apalachicola River

.

There are 6 small domestic wastewater plants with nonsurface discharge s , the largest being Eastpoint Water and Sewer District (Q = 0.1650 MGD ). There is only 1 industrial plant: Couch Ready Mix

— Eastpoint (FDEP 2002). These provide de minimis loads to the bay.

N onpoint sources that contrib ute nutrients to the bay include animal manure, fertilizer, runoff from agricultural areas, r unoff from urban and suburban areas, septic systems, atmospheric deposition, and the decomposition of organic matter (Frick et al. 1996). Apalachicola Bay nutrient concentrations are primarily influenced by river flow, local rainfall, tidal interactions, residence time, flux from benthic sediments, and the resuspension of sediments (Lewis 2003).

Summary of Nutrient Studies by Dr. Robert J. Livingston (FSU) Nutrients adhere to the particulate organic matter (detritus) that eventually falls into the sediments of the shallow Apalachicola system. This nutrient

- rich organic matter is colonized by microbial components to form the basis of important detrital food webs (Federle et al. 1983; White 1983; White et al. 1977, 1979a, 1979b). Infaunal (living in or on sediments) , detritus

- feeding macroinvertebrate assemblages that live in the sediments of the bay are dominated by various species of worms and
crustaceans , including Mediomastus ambiseta, Hobsonia florida
, Grandidierella bonnieroides
, and Streblospio benedicti (Livingston 1984 b ). The infauna form the food base for sciaenid fishes (Atlantic croaker [ Micropogonias undulates ]
, spot [ Le iostomus xanthurus ]
, and sea trout [ Cynoscion spp. ] ) that dominate the estuarine fish populations. Shallow depths and extremely high bottom productivity explain why the Apalachicola E stuary is a primary nursery area along the Gulf coast for blue crabs ( Ca llinectes sapidus ) and white shrimp ( Litopenaeus setiferus ). These species form the basis of highly lucrative fisheries in the region.

The outer bay, having higher salinities than the upper parts of the Apalachicola E stuary , is dominated by species such as silver perch ( Bairdiella chrysoura ), pigfish ( Orthopristis chrysoptera ), least squid ( Lolliguncula brevis ), pink shrimp ( Farfantepenaeus duorarum ), brown shrimp ( Farfantepenaeus
aztecus ), and various important game fishes.

Litter fall in the Apalachicola floodplain (800 grams per square meter [ gm -2 ] ) is higher than that noted in many tropical systems and almost all warm temp erate systems (Elder and Cairns 1982). T he se authors found that the annual deposition of litter fall in the bottomland hardwood forests of the Apalachicola River floodplain appro ximates 360,000 metric tons

. Seasonal river flooding transfer s detritus from the wetlands to a ssociated aquatic areas (Cairns 1981; Elder and Cairns 1982.

Livingston et al. (1974) indicated that, in additio n to providing particulate organics that fuel the bay system, river input determine s nutrient loading to the estuary. Nutrient loading in the Apalachicola7 Draft August 2010 River as it enters the bay is relatively high compared with that in other alluvial rivers along the northeast Gulf coast of Florida (Figure 3 ) (Livingston 2010). Of the 214,000 metric tons (mt) of carbon, 21,400 mt of N , and 1,650 mt of P that is delivered to the estuary over a given year, over half is transferred during the winter

- spring flood peaks (M attraw and Elder 1984 ). Studies conducted in the bay (Livingston 1976, 1981a, 1983, 1984, 2000, 2002) corroborate the timing of these flow events with the delivery of nutrients and dissolved and particulate organic matter as an important factor in the main tenance of the estuarine primary production (autochthonous and allochthonous). There are direct links between the estuarine food webs and fr eshwater discharges (Livingston 1981a, 1983, 1984). Particulate organic carbon delivered to the estuary follow s seasonal and interannual fluctuations that are closely associa ted with river flow ( R 2 = 0.738 ) (Livingston 1991). During summer and fall months, there is no direct correlation of river flow and detritus movement into the bay. By winter, there is a signi ficant relationship between microdetrital loading and river flow peaks.

P hytoplankton productivity is a major determinant of secondary prod uction in many coastal systems. Boynton et al. (1982) reported that the Apalachicola sys tem has high phytoplankton p roductivity compared with other river

- dominated estuaries, embayments, lagoons, and fjords around the world. Nixon (1988) showed that t he Apalachicola Bay system ranks high in overall primary production compared with other such systems. Up to 50% of the phytoplankton productivity of the Apalachicola E stuary is explained by Apalachicola River flow (Myers 1977 ; Myers and Iverson 1977, 1981).

In the Apalachicola system, orthophosphate availability limit s phytoplankton during both low - and high

salinity winter periods and during the summer at stations with low salinity (Iverson et al. 1997). Conversely, N is limiting during summer periods of moderate to high salinity in the Apalachicola E stuary. Flow rates affect the development of nutrient limitation in t he estuary. Nutrient limitation is highest during low

- flow summer periods.

The physiography of the Apalachicola E stuary is an important factor in the high primary productivity of the system. The bay is relatively shallow, and wind action frequently resu spends inorganic nutrients ( regenerated in the sediments ) and mixes them into the euphotic zone, producing periodic peak s of phytoplankton production (Livingston et al. 1974; Iverson et al. 1997). In deeper estuaries, nutrients can be sequestered in the sediments
, and thus can be unavailable for phytoplankton production. Shallow

w ater depth is thus an important factor in the natural productivity of the Apalachicola E stuary.

Recent studies have further documented the influence of the Apalachicola River on nutrient and organic carbon loading to the bay. Chanton and Lewis (1999) found that, despite inputs of large quantities of terrestrial organic matter, net heterotrophy in the Apalachicola Bay system was not dominant relative to net autotrophy
, during a 3- year period. Chanton and Lewis (2002), using carbon ( **δ** 13 C) and sulfur ( **δ** 34 S) isotope data, noted clear distinctions between benthic and water column feeding types. They found that the estuary depend s on river flows to provide floodplain detritus during high

- flow periods, and dissolved nutrients for estuarine primary productivity (plants) during low er flows. Floodplain detritus is significant in the important East Bay nursery area, thus showing that peak flows are important in washing such detritus into the estuary. Winter/spring periods of high river flow and macrodetritus d elivery to the bay (Livingston 1981a) are coincident with increased infaunal abundance ( McLane 1980). Four out of the five dominant infaunal species at river

- dominated stations ar e detritus feeders. The transformation of nutrient

- rich particulate organic matter from periodic river

- based influxes of dissolved and particulate organic matter coincide s with abundance peaks of the detritus

- based (infaunal) food8 Draft August 2010 Figure 3

. Nitrite

- nitrate and orthophosphate loading in the Apalachicola, Choctawhatchee, Perdido , and Escambia Rivers (Livingston 2010).9 Draft August 2010 webs of the Apalachicola system (Livingston and Loucks 1978 ; White et al. 1979a, 1979b; Livingston 1984 b ). A mechanism for the direct connection of increased infaunal abundance was described by Livingston (1983, 1984 b), in which microbial activity at the surface of the detritus (Federle et al. 1983) l eads to microbial successions (Morrison et al. 1977) that then provide food f or a variety of detritivorous organisms (White et al. 1979a, 1979b; Livingston 1984 b ). Mortazavi et al. (2000a) found that phytoplankton productivity in river

- dominated parts of the Apalachicola Es tuary is limited by P in the winter (during periods of low salinity) and N during summer periods of high salinity. The d issolved

o rganic n itrogen (DON) input is balanced by export fr om the estuary. Mortazavi et al. (2000b) determined temporal couplings of nutrient loading with primary production in the estuary. Around 75% of such productivity occurs from May through November, with primary control due to grazing. Mortazavi et al. (2000c) provided detailed accounts of the N budgets of the bay. These studies indicated that phytoplankton productivity is an importa nt component of estuarine food webs along the Gulf coast, and that a combination of river

- derived o rganic matter and autochthonous organic carbon provide s the resources for consumers in river

- dominated estuaries of the Gulf coast. Figure 4 presents a conc eptual model of Apalachicola Bay’s trophodynamics.

Figure 4. Livingston ’s m odel of the Ap alachicola Bay system, showing key features that result in extremely high primary and secondary productivity.10 Draft August 2010 It should be noted that nutrient concentrations in the river fluctuate little over time, but riverine water flow determines the loading of nutrient delivery to the bay (Table 3). The Apalachicola River illustrates the relationship between concentration and river flow (Table 3 ). Minimum and maximum values are actually 10 th and 90 th percentile values based on the number of samples for each parameter. A n a nalysis of seasonal data shows a wide range of values in both dissolved nitrate and total phosphorus (TP) concentrations throughout the year, probab ly related to river flow differences. Further trend analysis show s little change in most nutrients over time in the lower river
, except an increase in dissolved nitrate and a decrease in TP

.

Table 3

. N utrient concentrations in the Apalachicola River , Mil e 11 ( from Frick et al. 1996 )

. Parameter Number of Samples Minimum Maximum Median

River flow (cubic feet per second [cfs]) 101 11,000 50,000 24,000 TN (mg/L) 63 0.47 0.98 0.71 Total inorganic N (TIN) (mg/L) 83 0.22 0.47 0.32 Total organic N (TON) (mg/L) 55 0.17 0.68 0.35 Dissolved ammonia (mg/L) 84 0.02 0.09 0.03 Dissolved nitrate (mg/L) 98 0.17 0.42 0.27 TP (mg/L) 101 0.02 0.09 0.05

Other nutrient sampling done in the Apalachicola River around the same time includes nutrient

c oncentrations in the l ower Apalachicola River ( Fulmer 1997 ; Mortazavi et al. 2000a, 2000b, ) ; the results for 1994 to 1997 are as follows:

Nitrate = 0.180 to 0.480 mg/L; Mean dissolved inorganic nitrogen (DIN) = 0.350 mg/L; Mean dissolved organic nitrogen (DON) = 0.183 mg/L; Phosphate (soluble reactive phosphate [ SRP ] ) = 0.001 to 0.016 mg/L; and Monthly average SRP = 0.0057 +/ - 4.1 mg/L.



### Biological Summary

S

AV

S AV is generally a minor component of the habitats in Apalachicola Bay. The surveys of submerged vegetation listed by Livingston (1980) and CSA (1985) show significant differences in acreages

. These differences are probably caused by mapping methods, calculation techniques, change in species ( Myriophyllum ), or the absence of data from easte rn St. Geo rge Sound (CSA 1985). Apalachicola National Estuarine Research Reserve (ANERR) s urveys show that the central eastern side of East Bay contains more submerged vegetation than previously reported, primarily the low

- salinity taxa, Ruppia and Vallisneria (Fahrny et al. 2006).

The Apalachicola River and Bay Basin went through an extended drought from 1999 to 2002 that resulted in record low flows for much of that period, including the absence of normal winter floods for several years. During this period, unusually high salinities were noted in upper East Bay from ANERR’s System

- Wide Monitoring Program (SWMP) data loggers (Figure 6). At the same time
, staff began to11 Draft August 2010 detect, qualitatively, the disappearance of the fresh/brackish SAV normally se en in East Bay and the lower river. New studies (Fahrny et al. 2006) have documented a wider distribution of SAV in East Bay than was previously reported (Figure 5). In addition, more species have been documented than were found in the past (Table 4 ), ei ther due to a more detailed survey or a change in the SAV community over time. Unfortunately, after the most detailed SAV map for East Bay was created in 2005, Hurricane Dennis, w ith a storm surge of 2.5 m, significantly impacted the area. All the SAV in East Bay was eliminated and did not reappear that summer. The ANERR is documenting its recovery since the storm.

The fresh and brackish water submerged species also provide habitat and nursery areas for numerous organisms. Dominant organisms associate d with these vegetation beds include polychaetes, amphipods, chironomid larvae, snails, amphipods, mysids, crabs and shrimp, rainwater killifish, pipefish, silv ersides, and gobies (Livingston 1984 c ). Because of its position located between upland and
unveg etated bay bottom habitats, submerged vegetation links dissimilar ecosystems. It act s much like salt marshes in this respect and is important to the productivity of estuarine systems because it function s as a nursery area , providing food and reducing predation pressure through habitat complexity.

Figure 5

. P ercent SAV coverage in East Bay and ANERR monitoring sites, June 2005 (Edmiston 2008).12 Draft August 2010 Table 4 . East Bay SAV species list (from Fahrny et al. 2006). Species Name Common Name Native/Invasive Ceratophyllum demersum Coontail Native Chara spp Muskgrass Native Hydrilla verticillata Hydrilla Invasive Myriophyllum aquaticum Parrot feather Invasive Myriophyllum spicatum Eurasian watermilfoil Invasive Najas guadalupensis Southern naiad Native Najas minor Spiny naiad Native Potamogeton pusillus Slender pondweed Native Ruppia maritima Widgeon grass Native Stuckenia pectinata Sago pondweed Native Vallisneria americana Tapegrass Native Zannichellia palustris Horned pondweed Native

Phytoplankton Phytoplankton is the ma in source of carbon in the bay, fueling the productive food web (Chanton and Lewis 2002). Wilson et al. (2009) suggest that benthic production is also important. In either case, food webs are driven by in situ product ivity and therefore depend on the input of “new” nutrients to the system. Compared with other estuaries in the Gulf of Mexico, phytoplankton productiv ity is high in Apalachicola Bay (Putland 2005).

In 2008, a phytoplankton species composition study was performed throughout the bay by Paula Viveros and Dr. Ed Phlips from UF , along with ANERR staff. This study showed that diatoms dominated the community, with some dinoflagellate peaks and moderate cyanobacteria biomass during the summer of 2008. A shift occurred in the fall of 2008, and while diatoms still dominated, cyanobacteria and dinoflagellates became less important. In the winter of 2008, diatoms still dominated
, with some dinoflagellate peaks but few cyanobacteria. The most common diatom was Tha lassiosira sp., the main dinoflagellate found was Protoperidinium sp., and the main cyanobacterium observed was Pseudosolenia calcaravis

. Salinity
, defined by freshwater inflow from the Apalachicola Rive r, is considered to be the single most important det ermination of the distribut ion of organisms in the estuary ( Livingston 1983).

Phytoplankton S pecies C omposition Phytoplankton species composition in Apalachicola Bay was dominated by diatoms during the summer of 2008, with some dinoflagellate peaks and moderate cyanobacteria biomass. In the fall of 2008, the bay was mostly diatom dominated, with reduced cyanobacteria and dinoflagellate densities. In the winter of 2009, the bay was mostly diatom dominated, with some dinoflagellate peaks and few cyanobact eria ( see Figures 13 through 24).

The Apalachicola E stuary is characterized predominately by euryhaline species ( those adapted to varying salinities) that can thrive in the extreme salinity variations of the bay. The actual distribution of the key estuari ne species is based on microhabitat organization s that are ultimately based on various conditions

r elated to river flow processes. The river continuum extends into the estuary as the freshwater and estuarine habitats overlap in their usage by juvenile forms of various types.13 Draft August 2010 Oysters (Crassostrea virginica) (from Livingston 2010) Oyster bars represent an important habitat in the Apalachicola E stuary , providing cover and food for diverse assemblages (Livingston 1984 b ). Th ese include bryozoans, flatwor ms, annelids, gastropod and pelecypod mollusks, arthropod crustaceans
, and fishes. Research on the extensive Apalachicola oyster ( Crassostrea virginica ) reefs goes back to the work of Sw ift (1896) and Danglade (1917). The Apalachicola E stuary has account ed for about 90% of Florida's commercial oyster fis hery (Whitfield and Beaumariage 1977) and about 10% of the oyster production in the U nited States

. Conditions in the Apalachicola Bay system are highly advantageous for oyster propagation and growth (Men zel 1981; Menzel a nd Nichy 1958; Menzel et al. 1966; Livingston 1984 b), with reefs covering about 7% (4,350 hect ares [ha] ) of bay bottom (Livingston 1984 b ). The g rowth rates of oysters in this region are among the most rapid of those recorded (Ingle and Da wson 1952, 1953)
, with harvestable oysters taken in 18 months. The abundant phytoplankton food source, which is a consequence of riverine nutrient inputs, accounts for this high growth rate.

Appendix A contains more oyster information, including the dist ribution of oyster larvae, spat fall, new growth, percent mortality, location of study sites, and effects due to salinity.

Infaunal M acroinvertebrates (from Livingston 2010) In terms of frequency of occurrence, the infaunal macroinvertebrate assemblages in East Bay are dominated by species such as Mediomastus ambiseta ( below

- surface deposit feeder and detritivorous omnivore), Hobsonia florida (above

- surface deposit feeder and detritivorous omnivore), Grandidierella bonnieroides (grazer/scaven ger and general omnivore), Streblospio benedicti (above

- surface deposit feeder and detritivorous omnivore), and Parandalia americana (primary carnivore). Larger species of infaunal macroinvertebrates include the plankton

- feeding herbivores Mactra fragili s and Rangia
cuneata

. Dominant epibenthic (living above sediments) macroinvertebrates in East Bay over the period of study include the palaemonetid shrimp ( Palaemonetes spp., detritivorous omnivores), xanthid crabs ( Rhithropanopeus harrisi , a sensitive pr imary carnivore), blue crabs ( Callinectes sapidus
, primary carnivores at less than 30 millimeters [ mm ] ; secondary carnivores at more than 30 mm), and penaeid shrimp ( L. setiferus, F. duorarum and F. aztecus
, which are primary carnivores at less than 25 mm and secondary carnivores at more than 25 mm). Most of these invertebrate species are browsers, grazers, or seize

- and

- bite predators.

Penaeid S hrimp (from Livingston 2010) The numerically dominant invertebrates of the Apalachicola system include white shrimp and blue crabs that, when combined , represent ed about 70% of the total numbers taken over a 14

- year study period. The white shrimp, Litopenaeus setiferus , is the numeri cally dominant penaeid species in the Apalachicola system. White shrimp enter the bay during spring months, and are caught in otter trawls during the summer and fall months. Young

- of

- the

- year white shrimp ( less than 25mm) are first noted in East Bay duri ng the early summer months
, and they remain in the East Bay area throughout the

summer. The second trophic unit of this species is concentrated in East Bay during the summer and fall months. The largest white shrimp trophic unit is located mainly just west of the river mouth and in parts of East Bay. White shrimp are largely absent in the bay by mid - to late November through December.

White shrimp represent the most commercially valuable population in the Apalachicola E stuary , and are distributed in ar eas most affected by river flows. This distribution is compatible with the importance of freshwater inflows and the resulting productivity that accompanies such flows. The low numbers14 Draft August 2010 associated with drought conditions are compatible with the known aspec ts of white shrimp life history patterns.

Pink shrimp ( Farfantepenaeus duorarum ) and brown shrimp ( Farfantepenaeus aztecus ) occur in lower numbers than the white shrimp. Pink shrimp are usually associated with higher salinities than white shrimp, and young of the year also are most abundant during early fall in East Bay. This appears to be related to food availability in areas receiving freshwater flow. Young brown shrimp are most abundant during late spring, with the primary pattern of distribution just west of the river mouth and in East Bay

areas. Once again, both species favor areas receiving direct freshwater runoff from the river.

Callinectes S apidus (from Livingston 2010) The blue crab ( Callinectes sapidus ) is another commercially important species in the Apalachicola system. Young

- of

- the

- year blue crabs appear in the bay during the winter months and are largely concentrated in East Bay and along the main river channel of the bay. Secondary increases of t his trophic unit occur during late summer to fall months in the upper bay. The next trophic stage appears in the bay during February
, with secondary peaks during the summer months. This trophic stage is centered in East Bay. The largest blue crab trophic unit is found in the highest numbers during the summer months in East Bay. In all three blue crab trophic stages, the East Bay nursery area appears to be the favorite habitat. Spatial

- temporal blue crab distribution appears to be associated with the

re lationship of the individual trophic units to freshwater inputs from the river.

The long

- term trends of invertebrate distribution indicate that invertebrate numbers are associated with river flow
, even though such manifestations of habitat preference vary by species and by trophic unit within each species. High invertebrate numbers during the drought of 1980 to 1981 were due in large part to blue crab predominance. Each species has a very different set of habitat needs through out its ontological development, with major differences in the spatial/temporal patterns of habitat use.

The one unifying feature that affects such distributions appears to be increased concentrations of invertebrate populations in areas associated with the entry of fresh water into the upper bay. These areas are notable for relatively high organic carbon and nutrient loading and associated productivity. Trophic unit distribution displays a broad spectrum of diverse phase interactions with river input to the bay over seasonal and interannual periods. Feeding habit changes are related to habitat

- oriented differences in available food.

Fishes (from Livingston 2010) Dominant fishes in East Bay include the plankton

- feeding primary carnivore Anchoa mitchilli (bay anchovy) and benthic

- feeding primary carnivores such as spot ( Leiostomus xanthurus ), hogchokers ( Trinectes maculatus ), young Atlantic croakers ( Micropogonias undulates less than 70 mm) and silver perch ( Bairdiella chrysoura 21 to 60 mm). Secondary carnivores among the dominant fishes include larger croakers ( more than 70 mm), Gulf flounder ( Paralichthys albigutta )
, and sand seatrout ( Cynoscion arenarius ). Tertiary carnivores in East Bay include the larger spotted seatrout ( C. nebulosus ), southern flounder ( P. lethostig ma ), largemouth bass ( Micropterus salmoides ) and gar ( Lepisosteus spp). Escept for the bay anchovies, all of the above species live near the sediment

- water interface
, with most of the trophic organization of the bay dependent on interactions among bottom

- living infaunal and epibenthic (living above sediments) macroinvertebrates and fishes. The primary fish dominants, representing about 80% of total fish numbers taken over the sampling period, include bay anchovies, seatrout, spot, and Atlantic croaker. A ppendix A provides complete information on each fish species.15 Draft August 2010 Presence and F requency of H armful A lgal B looms (HABs) Occasional red tide events, which originate offshore and are transported to the bay by currents, affect the system. These events are not related to nutrients from the Apalachicola Bay system. The last closure of parts of the bay due to red tide was in 2005 and 2006. Area 1611 East was closed from September 2, 2005, to January 26, 20 06, for a total of 145 days (FDACS) (Table 5 ). Most rece ntly, K. brevis was found at 2 locations, at Pickalene Bar and Green Point in Wakulla County on April 27, 2010. Fewer than 1
, 000 cells were present at each site, and since the cells were found in such small quantities
, no adverse effects were observed. These data are routinely collected by FDACS

.

Table 5 . Apalachicola Bay red tide tracking (FDACS)

.

Shellfish Production and Frequency/Duration of Bed Closures During the period of low river flows from 1999 to 2002 , there was a collapse of oystering in the Eastern reefs from Cat Point to East Hole. In 2002, a field assessment by FDEP demonstrated that the reduced oyster productivity in eastern bay reefs was accompanied by large numbers of predators that included oyster drills, crown conchs, and sea urc hins (G. S. Gunter, pers

. comm .). With t he return of higher river16 Draft August 2010 flows during 2003, there was a marked increase in oyster abundance observed at Cat Point and East Hole, accompanied by a reduction in oyster predators (G. S. Gunter, pers

. comm .).

During the 2002 collapse of the eastern oyster reefs, commercial oystering continued in northern sections of western bars
, such as Dry Bar and upper St. Vincent Bar (G. S. Gunter, pers

. comm .). The above observations during the 1999 to 2002 period of low river flows represented the field verification of model predictions made by Livingston et al. (2000). The model predicted that ongoing reductions of Apalachicola River flow, which are related, in part, to reservoir and other water management practices in Alabama and Georgia, would accentuate the adverse effects of natural droughts. Over prolonged periods, the resilience of the bay to such events would be systematically reduced, which would then lead to more permanent reductions in secondary production bio mass (organisms such as oysters, shrimp, blue crabs
, and sciaenid fishes) that depends on the interannual cycling of natural river flows into the bay.

The most recent period of low river flow (2007 to 2009) followed a similar pattern to that described for the 1999 to 2002 drought. S alinities in East Bay reached unprecedented high levels ( greater than 30 parts per thousand [ ppt ]), adversely affecting the highly productive eastern oyster bars through a combination of predation and disease (L. Edmiston, J. Wa nat, and G. Lewis, p ers

. c omm .). Cat Point, the leading oyster

- producing reef in the bay, was particularly affected by excess predators during the recent drought. During the period of increased salinity , o yster catches were largely restricted to less productive bars in the western parts of the bay

. These observations further verified the Livingston et al. (2000) oyster model. For additional information on oysters, see Appendix A.

Quantification of L andings from C ommercial /R ecreational F isheries Stratified Random Sampling The Florida Fish and Wildlife Conservation Commission (FWCC) collected a total of 249,676 fishes (174 taxa) and selected invertebrates (17 taxa) from 840 Apalachicola Bay simple random samples ( SRS ) in 2008 ( FWCC 2008 ). Anchoa m itchilli (n=99,209) was the most numerous taxon collected, representing 39.7% of the total catch. Lagodon rhomboides (n=19,916), Micropogonias undulatus (n=16,958), and Litopenaeus setiferus (n=11,410) were the next most abundant taxa collected, accountin g for an additional 19.3% of the total catch. Thirty

- three s elected t axa (n=56,220) composed 22.5% of the total catch. Micropogonias undulatus (n=16,958), L. setiferus (n=11,410), and Leiostomus xanthurus (n=9,142) were the most abundant selected t axa, representing 15.0% of the annual catch. Collections in 2008 included 5 species new to the Apalachicola Bay Fisheries Independent Monitoring ( FIM ) Program collection, including Albula vulpes (bonefish), Ctenopharyngodon idella (grass carp), Microgobius carr i (Seminole goby), Parablennius marmoreus (seaweed blenny), and Sicyonia parri (a rock shrimp) (FWCC 2008).

The FIM Program’s 2008 Annual Data Summary Report contains additional information on landings.

Fish Kills Appendix D lists reported fish kills in relation to the K. brevis bloom in Franklin County, from 2001 to June 21, 2010
, from the FWRI fish kill database. Most of the sampling is done by members of the public, who call the FWRI hotline to report seeing dead fish

.17 Draft August 2010 

### Water Quality Studies

A NERR Monitoring ANERR has a System

- Wide Monitoring Program to monitor n utrients and has been collecting data since 2002. The program includes spatial sampling at 11 sites around the bay
, including a river site and an offshore site outsi de Sike’s Cut, and temporal sampling at East Bay over a diel cycle (approximately 25 hours) (Figure 6)

. ANERR measure s nitrate, nitrite, ammonium, SRP , and chlorophyll a

. Nutrient concentrations in the river do not fluctuate greatly, and nutrient loading to the bay is controlled by the river flow. Other factors influencing nutrient concentrations are rainfall, tidal interactions, flux from sediments, and sediment resuspe nsion. Nitrate concentrations in the system range from 0.003 to 0.400 mg/L and average 0.193 mg/L. Phosphate concentrations range from 0.001 to 0.016 mg/L and average 0.007 mg/L

. Chloro phyll a values in the system range .2 to 32.2 mg/L and average 5.9 mg /L.

Figures 7 through 11 show ANERR data for salinity, turbidity, pH, and DO

. The salinity data were collected over a longer period
, from 1993 to 2008 (Figures 7 and 8 )

. DO (Figure 9), t urbidity (Figure 10), and pH (Figure 11) are from 2008 data. Table 6 lists m ean nutrient measurements in Apalachicola Bay as determined by various researchers over time

.

Figure 6. ANERR long

- term monitori ng locations throughout Apalachicola B ay (Wanat 2010).18 Draft August 2010 Figure 7. Cat Point (Gray) and Dry Bar (Blue) daily average salinity, 1993

– 2008 ( solid lines are 90

- day moving average data ; dashed lines are linear trend lines) (Wanat 2010).

Figure 8. Areal extent of salinity zones in Apalachicola Bay under various flow regimes. Map at left shows salinity con tours in the bay when river flow is between 15,000 and 35,000 cfs. Map at right shows salinity contours in the bay when river flow is below 15,000 cfs (Wanat 2010).19 Draft August 2010 Figure 9. DO (mg/ L ) at the three data logger locations , from 2008 ANERR data (Wanat 2 010).

Figure 10. Turbidity at the three data logger locations , from 2008 ANERR data (Wanat 2010).20 Draft August 2010 Figure 11. pH at the three data logger locations , from 2008 ANERR data (Wanat 2010).

Table 6

. Mean n utrient measurements in Apalachicola Bay as determined by various researchers over time (Wanat 2010). Summarized by Lewis 2003

. Studies Nitrate (NO 3 ) (mg/L) Nitrogen Ammonia (NH 4 ) (mg/L) Phosphate (PO 4 ) (mg/L) Chlorophyll a (mg/L)

Estabrook (1972

– 73) 0.091 0.017 0.006 6.5 Mortazavi (1993

– 96) 0.119 0.020 0.003 4.8 NWFWMD (2000

– 02) 0.059 0.016 0.008 4.6

Water Quality Studies by Paula Viveros (U F ) and A NERR UF and ANERR are studying the relationship between Apalachicola R iver discharge and a number of variables in the bay (correlative sampling), including salinity, chlorophyll, and nutrient concentrations (Tables 7 through 12 ; Figures 12 through 24) . They found an inverse relationship between salinity and discharge, and an inverse relationship between river discha rge and chlorophyll a ( i.e., as discharge increase s , chlorophyll a decrease s ). Chlorophyll a values were higher in summer. They found that as river discharge increases, N increases, but P remains approximately the same. The phytoplankton community in t he bay is dominated by diatoms
, with higher biovolume in summer . In winter, there are much lower diatom volumes and some increases in dinoflagellates. Preliminary information on nutrient limitation analyses indicates that P is the limiting nutrient for algae in the river, while the bay and coastal area are colimited by N and P.21 Draft August 2010 Table 7

. Mean DIN c oncentration for different areas of Apalachicola Bay, in summer and winter , from Paula Viveros, U F (Wanat 2010)

.

Table 8

. Mean TDN c oncentration for diff erent areas of Apalachicola Bay, in summer and winter , from Paula Viveros, UF (Wanat 2010). Mean DIN Concentration - μ g L -1

Summer Winter

River (231) 388 472

North Bay E. Bay Bridge (171) 223 342 E. Bay Bottom (191) 88 123

East Bay Cat Point (221) 125 160

West Bay West Pass (131) 64 146 Dry Bar (141) 82 171

Central Bay Mid Bay (161) 121 238 Nick's Hole (211) 73 149

South Bay Pilot's Cove (151) 55 120

Offshore (201) 46 41

Mean Total Dissolved Nitrogen Concentration - μ g L -1

Summer Winter

River (231) 460 625

North Bay E. Bay Bridge (171) 316 471 E. Bay Bottom (191) 314 357

East Bay Cat Point (221) 300 283

West Bay West Pass (131) 196 260 Dry Bar (141) 217 292

Central Bay Mid Bay (161) 233 401 Nick's Hole (211) 206 265

South Bay Pilot's Cove (151) 174 220

Offshore (201) 146 14422 Draft August 2010 Table 9 . Mean S RP c oncentration for different areas of Apalachicola Bay, in summer and winter , from Paula Viveros, UF (Wanat 2010).

Table 10

. Mean t otal d issolved p hosphorus (TDP) c oncentration for different areas of Apalachicola Bay, in summer and winter , from Paula Viveros, UF (Wanat 2010). Mean Soluble Reactive Phosphorus Concentration - μ g L -1

Summer Winter

River (231) 8 12

North Bay E. Bay Bridge (171) 5 9 E. Bay Bottom (191) 5 8

East Bay Cat Point (221) 5 5

West Bay West Pass (131) 3 3 Dry Bar (141) 4 4

Central Bay Mid Bay (161) 4 4 Nick's Hole (211) 4 4

South Bay Pilot's Cove (151) 4 3

Offshore (201) 3 2

Mean Total Dissolved Phosphorus Concentration - μ g L -1

Summer Winter

River (231) 13 18

North Bay E. Bay Bridge (171) 12 12 E. Bay Bottom (191) 15 15

East Bay Cat Point (221) 16 13

West Bay West Pass (131) 15 13 Dry Bar (141) 13 11

Central Bay Mid Bay (161) 15 11 Nick's Hole (211) 12 12

South Bay Pilot's Cove (151) 16 13

Offshore (201) 21 1423 Draft August 2010 Table 11

. Mean s alinity for different areas of Apalachicola Bay, in summer and winter , from Paula Viveros, UF (Wanat 2010).

Figure 12. Chlorophyll a compared with river flow for four stations in the bay , 2002

– 09 , from Paula Viveros, UF (Wanat 2010). Mean Salinity - psu

Summer Winter

River (231) 0 0

North Bay E. Bay Bridge (171) 14 8 E. Bay Bottom (191) 13 10

East Bay Cat Point (221) 27 19

West Bay West Pass (131) 30 20 Dry Bar (141) 25 17

Central Bay Mid Bay (161) 24 15 Nick's Hole (211) 27 18

South Bay Pilot's Cove (151) 30 22

Offshore (201) 34 3324 Draft August 2010 Table 12

. Mean c hlorophyll a c oncentration for different areas of Apalachicola Bay, in summer and winter , from Paula Viveros, UF (Wanat 2010).

Figure 13. Phytoplankton composition , June 2008 , by biovolume ( μm 3 mL -1 ); stars show station location s on map below; data from Paula Viveros, UF (Wanat 2010). Mean Chlorophyll a Concentration - μ g L -1

Summer Winter

River (231) 5 2

North Bay E. Bay Bridge (171) 8 4 E. Bay Bottom (191) 13 11

East Bay Cat Point (221) 7 4

West Bay West Pass (131) 6 4 Dry Bar (141) 9 4

Central Bay Mid Bay (161) 7 5 Nick's Hole (211) 6 4

South Bay Pilot's Cove (151) 5 4

Offshore (201) 4 3



## JUNE25 Draft August 2010 Figure 14. Phytoplankton c omposition , July 2008 , by biovolume ( μm 3 mL -1 ); stars show station location s on map below ; data from Paula Viveros , UF (Wanat 2010).

Figure 15. Phytoplankton c omposition , August 2008 , by biovolume ( μm 3 mL -1 ); stars show station location s on map below ; data from Paula Vivero s , UF (Wanat 2010). 

## JULY

AUGUST26 Draft August 2010 Figure 16. Map of Apalachicola Bay, showing station location s; stars show certain stations from figures above ; data from Paula Viveros , UF (Wanat 2010).



## Phytoplankton Composition Fall 2008 by biovolume, μm 3 

## ml -1

Figure 17. Phytoplankton c omposition , September 2008 , by biovolume ( μm 3 mL -1 ); stars show station location s on map below ; data from Paula Viveros , UF (Wanat 2010). 

## September27 Draft August 2010 Figure 18. Phytoplankton c omposition , October 2008 , by biovolume ( μm 3 mL -1 ); stars show station location s on map below ; data from Paula Viveros , UF (Wanat 2010).

Figure 19. Phytoplankton c omposition , November 2008 , by biovolume ( μm 3 mL -1 ); stars show station location s on map below ; data from Paula Viveros , UF (Wanat 2010). 

## October

November28 Draft August 2010 Figure 20. Map of Apalachicola Bay ; stars show station locations from figures above ; data from Paula Viveros , UF (Wanat 2010).

Figure 21. Phytoplankton species c omposition , December 2008, by biovolume ( μm 3 mL -1 ); stars show station location s on map below ; data from Paula Viveros , UF (Wanat 2010). 

## December29 Draft August 2010 Figure 22. Phytoplankton c omposition by biovolume ( μm 3 mL -1 ), January 2008 ; stars show station location s on map below ; data from Paula Viveros , UF (Wanat 2010).

Figure 23. Phytoplankton composition by biovolume ( μm 3 mL -1 ), February 2008 ; stars show station location s on map below ; data from Paula Viveros , UF (Wanat 2010). 

## January

February30 Draft August 2010 Figure 24. Map of Apalachicola Bay, showing station locations ; stars show certain stations from figures above ; data from Paula Viveros , UF (Wanat 2010).

Water Quality Studies by Dr. Robert J. Livingston (F SU ), 1972

– 2008 Dr. Livingston conducted research on the bay from 1972 to 2008 (see Figure 25 for station locations). During this time, he collected data on r iver flow, rainfall , s alinity, temperature, DO , oxygen anomaly, pH, Secchi depth
, and nutrients ( ammonia [ NH 3 ]
, n itrite nitrogen [ NO 2 ] , NO3, TIN, TN, PO4, and TP ). Other water quality factors measured included National Council for Air and Stream Improvement ( NCASI )

co lor, turbidity, chlorophyll a , w ater/sediment/organism pollutants (metals, pesticides) , S AV (quadrat s and mapping) , i nfaunal macroinvertebrates (cores) , epibenthic i nvertebrates (seines, trawls) , f ishes (seines and trawls) , and food web transformations (based on the stomach contents of fishes and invertebrates)

. The Livingston team also carried out p hysical model ing
, o yster model ing , and n utrient loading calculations.

The a quatic habitats of the Apalachicola River floodplain depend on river flows in terms of frequency and duration of inundation and saturation. Floodplain vegetation is closely associa ted with the extent and timing of river flows and flooding. Seasonal flow changes are important to the life cycles of many terrestrial and aquatic species along the river. Since 80 % to 85% of the fishes use the floodplain as a food source, wetlands inund ation is a critical part of the life history of these species. The river dominates the Apalachicola Bay system as a source of fresh water, nutrients, and organic matter. Together with local rainfall and wind events, the river is closely associated with the estuarine salinity regime and coastal productivity (Livingston 1983, 1984, 2000, 2005; Livingston et al. 1997, 1999, 2000).

Nutrient

- induced phytoplankton productivity is an important component of estuarine food webs along the Gulf coast, and especially in the Apalachicola River. The alluvial river also provides river

- derived nutrients and organic matter that fuel planktonic and detrital food webs. The combination of these sources of autochthonous and allochthonous organic carbon provides the resource s for consumers in the Apalachicola Estuary. Reduced river flows and flooding will diminish this loading
, leading to a collapse of useful productivity in receiving coastal areas. There is evidence that recent extended periods of low river flow have already adversely affected organic carbon loading to the bay (Livingston 2010).31 Draft August 2010 Figure 25. Apalachicola Bay system , showing the location s of long

- term sampling stations (1972

– 84).



### Nutrient Loading Models

Existing TN , TP , and flow data were analyzed and, considering flow to be an explanatory variable, long

term nutrient loads were estimated by Hydroqual (2010)

. A nalyses were performed to assist in the development of TN and TP loads for the Apalachicola River to support nutrient criteria dev elopment in Apalachicola Bay.

Available water quality and flow data were obtained from the following sources: U.S. Geological Survey (USGS) for flow and water quality; and Florida STORET for water quality. Figure 26 shows t he locations where river data w ere available
, with the stations at the Lake Seminole outlet ( Florida STORET at U.S. H ighway 90 and USGS Gau ge #02358000) and Sumatra (USGS Gau ge #02359170) containing the most data. These two stations (Lake Seminole and Sumatra) were used to complete the river loading analyses. The data were used to develop concentration relationships to flow
, so that the daily flow record could be used to develop long

- term estimates of river concentrations and loads for TN and TP. Ultimately, annual geometric mean load s were developed to be used in developing protective loads to Apalachicola Bay.

Figures 27 and 28 present t he data obtained for flow, TN
, and TP at Lake Seminole and Sumatra from 1975 to 2009
, along with the 2010 proposed EPA in

- stream protective values (IPV) for TN (0.824 mg/L) and TP (0.043 mg/L) as horizontal dashed lines. The flow values range from about 5,000 to 200,000 cfs,32 Draft August 2010 the TN values range from about 0.3 to 1.5 mg/L, and the TP values range from about 0.01 to 0.1 mg/L. These data were used to develop concentration relationships to flow using the data from 1990 to 2009 (Figure 29 ). This period was chosen since pre

- 1990 TN data at Lake Seminole appeared less reliable and more variable than the post

- 1990 data. Although strong correlations betwee n concentration and flow were not observed, generally increasing trends in concentration were observed with increasing flow. Log

- log regressions were completed on the data
, and Table 13 and Figure 31 present the resulting equations.

Table 13 . Concentrati on flow regression equations for the Lake Seminole and Sumatra station s (Hydroqual)

. Location/Source TN Equation TP Equation

Lake Seminole 0.244Q 0.116 0.0038Q 0.223

Sumatra 0.675Q 0.005 0.0008Q 0.379

Figures 30 and 31 present the calculated daily loads based on the concentration

- flow regression equations and the daily flows at Lake Seminole and Sumatra from 1975 to 2009. The solid blue horizontal lines in each panel represent annual geometric means of flow, TN load
, and TP load. In general, the calcul ated TN and TP loads compare well with the observed loads.

Since the concentration

- flow relationships are not very strong (little variation with flow), much of the load variation to Apalachicola Bay is due to the hydrology of the river. In order to incor porate the hydrology (flow) variation into developing nutrient criteria or protective nutrient loads, probability distributions of TN and TP loads were developed. Figure s 32 and 33 present log probability distributions of calculated annual geometric means for TN and TP loads for the period from 1975 to 2009 at Lake Seminole
, and from 1978 to 2009 at Sumatra. Table 1 4 shows t he upper distribution of the nutrient loads at two stations in the Apalachicola River. Nutrient criteria structured to maintain this distribution of loads over time would assure that the necessary water flow and beneficial nutrient inputs needed to sustain the system would be delivered. For more information on the modeling, see Appendix C

.

Table 14

. Upper distribution of Apalach icola River statistical nutrient loads ( after Hydroqual 2010 ).

- = Empty cell/no data

- Lake Seminole Sumatra TN load (lbs/day) 67%

- 81,633 95%

- 116,509 99%

- 130,085 Max imum

- 130,112 67%

- 93,582 95%

- 116,971 99%

- 118,274 Max imum

- 118,301 TP load (lbs/day) 67%

- 3,639 95%

- 5,375 99%

- 6,064 Max imum

- 6,065 67%

- 4,755 95%

- 6,459 99%

- 6,558 Max imum

- 6,56033 Draft August 2010 Figure 26

. Station map of the Apalachicola River, from Lake Seminole to the Gulf coast (HydroQual).34 Draft August 2010 Figure 27

. Flow compared with TN and TP c oncentrations for the Apalachicola River at Lake Seminole ; data from Florida STORET and USGS 0235800 (HydroQual).35 Draft August 2010 Figure 28. Flow compared with TN and TP c oncentrations for the Apalachicola River near Sumatra, data from USGS

- 2359170 (HydroQual).36 Draft August 2010 Figure 29. TN and TP c oncentrations versus flow for the Apalachicola River at Lake Seminole and near Sumatra ( post

- 1990) (HydroQual).37 Draft August 2010 Figure 30. TN and TP compared with flow for the Apalachicola River at Lake Seminole; data from Florida STORET and USGS 02358000. Graphs show data points, load based on regression analysis, annual geometric mean (HydroQual).38 Draft August 2010 Figure 31. TN and TP compared with f low for the Apalachicola River near Sumatra ; data from USGS

2359170. Graphs show data points, load based on regression analysis , annual geometric mean (HydroQual).39 Draft August 2010 Figure 32. Annual geometric mean for TN and TP c oncentrations for the Apalachicola River at Lake Seminole and near Sumatra (HydroQual).40 Draft August 2010 Figure 33

. Probability of a nnual g eometric m ean e stimated u nfiltered n utrien t l oads for the Apalachicola River at Lake Seminole and near Sumatra (HydroQual).41 Draft August 2010 

### Waters on the 303(d) List

T able 15 contains t he Group 2 V erified 303(d) L ist for the Apalachicola Bay Basin , including several coastal waterbodies within the Apalachicola Bay region

.

Table 15 . Impaired waters in the Apalachicola Bay Basin

- = Empty cell/no data N/A = Not Available

1 II = Class II; IIIM = Class III Marine Planning Unit WBID Waterbody Segment Water

body Type Water

body Class 1 Parameters Assessed Using the Impaired Surface Waters Rule (IWR) Concentration of Criteria or Threshold Not Met Priority for TMDL Development Projected Year for TMDL Development

Apalachicola Bay 1266 St. George Sound Estuary 2 Mercury (based on fish consumption advisory) Exceeds Florida Department of Health (FDOH) threshold (>0.3 milligrams per kilogram [mg/kg]) High N/A

Apalachicola Bay 1266 St. George Sound Estuary 2 Bacteria (in shellfish) Exceeds Shellfish Evaluation and Assessment Section (SEAS) threshold Medium 2008

Apalachicola Bay 1274 Apalachicola Bay Estuary 2 Bacteria (in shellfish) Exceeds SEAS threshold Medium 2008

Apalachicola Bay 1274 Apalachicola Bay Estuary 2 Fecal Coliforms ≤14 Most probable number per 100 milliliters (MPN/100mL) Low 2003

Apalachicola Bay 1274 Apalachicola Bay Estuary 2 Mercury (based on fish consumption advisory) Exceeds FDOH threshold (>0.3 mg/kg) High N/A

Apalachicola Bay 1288 Money Bayou Estuary 3M Bacteria (in shellfish) Exceeds SEAS threshold Medium 2008

Apalachicola Bay 1288 Money Bayou Estuary 3M Mercury (based on fish consumption advisory) Exceeds FDOH threshold (>0.3 mg/kg) High N/A

Apalachicola Bay 1289 Direct Runoff to Bay Estuary 3M Bacteria (in shellfish) Exceeds SEAS threshold Low N/A

Apalachicola Bay 1289 Direct Runoff to Bay Estuary 3M Mercury (based on fish consumption Exceeds FDOH threshold (>0.3 mg/kg) High N/A42 Draft August 2010 Planning Unit WBID Waterbody Segment Water

body Type Water

body Class 1 Parameters Assessed Using the Impaired Surface Waters Rule (IWR) Concentration of Criteria or Threshold Not Met Priority for TMDL Development Projected Year for TMDL Development

advisory) Apalachicola Bay 1291 Indian Lagoon Estuary 3M Bacteria (in shellfish) Exceeds SEAS threshold Low N/A

Apalachicola Bay 1291 Indian Lagoon Estuary 3M Mercury (based on fish consumption advisory) Exceeds FDOH threshold (>0.3 mg/kg) High N/A

Apalachicola Bay 1292 Direct Runoff to Bay Estuary 2 Bacteria (in shellfish) Exceeds SEAS threshold Low N/A

Apalachicola Bay 1292 Direct Runoff to Bay Estuary 2 Mercury (based on fish consumption advisory) Exceeds FDOH threshold (>0.3 mg/kg) High N/A

Apalachicola Bay 8018 Gulf of Mexico (Franklin County, Gulf County) Coastal 3M Mercury (based on fish consumption advisory) Exceeds FDOH threshold (>0.3 mg/kg) High N/A

Apalachicola Bay 8020 Gulf of Mexico (Franklin County, St. George Island) Coastal 3M Mercury (based on fish consumption advisory) Exceeds FDOH threshold (>0.3 mg/kg) High N/A

Apalachicola Bay 8021 Gulf of Mexico (Franklin County, St. George Island) Coastal 3M Mercury (based on fish consumption advisory) Exceeds FDOH threshold (>0.3 mg/kg) High N/A

Apalachicola Bay 8022 Gulf of Mexico (Franklin County, Dog Island) Coastal 3M Mercury (based on fish consumption advisory) Exceeds FDOH threshold (>0.3 mg/kg) High N/A

Apalachicola Bay 8023 Gulf of Mexico (Franklin County, Dog Island) Coastal 3M Mercury (based on fish consumption advisory) Exceeds FDOH threshold (>0.3 mg/kg) High N/A

Apalachicola Bay 1266A Carrabelle Beach Beach 3M Bacteria (Beach Advisories) ≥21 days of beach advisories High N/A43 Draft August 2010 Planning Unit WBID Waterbody Segment Water

body Type Water

body Class 1 Parameters Assessed Using the Impaired Surface Waters Rule (IWR) Concentration of Criteria or Threshold Not Met Priority for TMDL Development Projected Year for TMDL Development

Apalachicola Bay 1274A East Bay Estuary 2 Fecal Coliforms ≤14MPN/100 mL Low 2008

Apalachicola Bay 1274A East Bay Estuary 2 Bacteria (in shellfish) Exceeds SEAS threshold Medium 2008

Apalachicola Bay 1274A East Bay Estuary 2 Mercury (based on fish consumption advisory) Exceeds FDOH threshold (>0.3 mg/kg) High N/A

Apalachicola Bay 1274B Apalachicola Bay Estuary 2 Mercury (based on fish consumption advisory) Exceeds FDOH threshold (>0.3 mg/kg) High N/A

Apalachicola Bay 1274B Apalachicola Bay Estuary 2 Bacteria (in shellfish) Exceeds SEAS threshold Medium 2008

Apalachicola Bay 1274C Direct Runoff to Bay Coastal 2 Bacteria (in shellfish) Exceeds SEAS threshold Low N/A

Apalachicola Bay 1274C Direct Runoff to Bay Coastal 2 Mercury (based on fish consumption advisory) Exceeds FDOH threshold (>0.3 mg/kg) High N/A

Apalachicola Bay 8020A St. George Island 11 th
St. W Beach 3M Bacteria (beach advisories) ≥21 days of beach advisories High N/A

Apalachicola Bay 8021A St. George Island Franklin Blvd. Beach 3M Bacteria (beach advisories) ≥21 days of beach advisories High N/A

Apalachicola Bay 8021B St. George Island 11 th
St. E Beach 3M Bacteria (beach advisories) ≥21 days of beach advisories High N/A

Apalachicola Bay 8022A St. George Island State Park Beach 3M Bacteria (beach advisories) ≥21 days of beach advisories High N/A

Apalachicola Bay 8019 Gulf of Mexico (Franklin County) Coastal 3M Mercury (based on fish consumption advisory) Exceeds FDOH threshold (>0.3 mg/kg) High N/A

New River 1256 Alligator Harbor Estuary 3M Mercury (based on fish consumption advisory) Exceeds FDOH threshold (>0.3 mg/kg) High N/A

New River 1278 East Bayou Estuary 3M Mercury (based on fish Exceeds FDOH threshold Low N/A44 Draft August 2010 Planning Unit WBID Waterbody Segment Water

body Type Water

body Class 1 Parameters Assessed Using the Impaired Surface Waters Rule (IWR) Concentration of Criteria or Threshold Not Met Priority for TMDL Development Projected Year for TMDL Development

consumption advisory) (>0.3 mg/kg)

New River 1279 West Bayou Estuary 3M Mercury (based on fish consumption advisory) Exceeds FDOH threshold (>0.3 mg/kg) - N/A

New River 1279 West Bayou Estuary 3M Bacteria (in shellfish) Exceeds SEAS threshold - N/A

New River 1283 Blounts Bay Estuary 3M Bacteria (in shellfish) Exceeds SEAS threshold - N/A

Impairment for Bacteria Not N ecessarily I ndicative of A nthropogenic I mpact The use of fecal coliforms as an indicator 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 methods for use under Gulf of Mexico conditions (GOMA 2009). The GOMA Pathogens Workgroup rece ntly submitted comments regarding the status of EPA recreational water quality criteria (GOMA 2009). It expressed concern that the EPA recreational criteria were derived 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 natural animal sources. Areas in the Gulf of Mexico for which the workgroup thought the EPA criteria might not 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 material and/or colored dissolved organic
matter (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 enterococci bacteria cannot indicate hum an 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 following text is from a review conduc ted by Dr. V. Jody Harwood of the University of South Florida as part of a microbial source tracking project she is conducting for F DEP:

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 that 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 this45 Draft August 2010 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 Leba ron 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, or 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 high recreational activity, may lead to false positive indications regarding contamination and public h ealth 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.



### Numeric Nutrient Criteria Recommendations

The well

- developed scientific database for the Apalachicola River and Bay system indicates that nutrients delivered to the bay from the Apalachicola River are integral to the welfare of this highly productive system. Reductions of nutrient inputs due to decrease d river flow are accompanied by adverse changes in the ove rall secondary production of the estuary. There is currently no need for any reduction of nutrient loading to the bay from the river. Any attempt to restrict nutrients would be counterproductive to the key fisheries of the bay and would only add to the s tress caused by recent increases in drought effects.

For Apalachicola Bay
, maintaining the upper distribution of the nutrient loads associated with healthy conditions is the numeric nutrient goal. Table 14 provides a quantitative basis for selecting nut rient loads from the Apalachicola River that would protect the trophic functioning of the bay. Nutrient criteria structured to maintain this distribution of loads over time would ensure that the necessary water flow and beneficial nutrient inputs needed to sustain the system would be delivered.

Pr oposed Numeric Nutrient Criteria

Methodology46 Draft August 2010 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 Apalachicola Bay is de scribed 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 tendency (geometric mean) of the distributi on, 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 in crease from the baseline. Allowing for an insignificant increase accounts for uncertainty in the estimate of the mean and partially addresses the fact that the reference based approach fails to identify a threshold of imbalance, and thus is highly prone t o 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 condition, known as a de minimus change (US Sixt h 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 f or each segment of the waterbody.47 Draft August 2010 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 bas is. 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 appropriate for nutrient criteria where a suf ficiently 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 impairment, 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

mean. Doing so would result in an unaccept ability 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 appropriately accounting for the annual variabili ty 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 assessment 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 Type II error and will more fully capture cli matic 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 demonstrated that setting the criteria at this p ercentile 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 component of the criteria (not to be exceeded mo re 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; and

**•** 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 means, while the single site magnitude was cal culated 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 overall segment status if it is relatively h omogeneous. I f the segment is not well mixed, is very large, or contains localized nutrient sources,48 Draft August 2010 then there is a potential that isolated areas of enrichment may be masked in the network spatial

average. Therefore, 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 stakeholders.

Summary of the Proposed Criteri a
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 g eometric mean of values from a single location, not to be exceeded more than twice in a five

- year period.

The proposed long

- term criteria for the protection of a healthy, well

- balanced aquatic community in Apalachicola Bay, as well the annual limits for ea ch segment, are provided in Table 16. Due to the importance of providing a minimum nutrient load (and flow) to maintain the health of the bay, FDEP is evaluating the need to establish a minimum nutrient load for Apalachicola Bay, and is seeking input on

t his concept.49 Draft August 2010 Table 16. Proposed numeric nutrient criteria for all segments of Apalachicola Bay, 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, mor e than twice in a 5 year period.



### TP (ug/L)

Segment Existing Long Term Geometric Mean Maximum Allowed Long Term Geometric Mean Annual Geometric Mean for a Network of Stations (2 of 5 year exceedance rate) Annual Geometric Mean for a Single Site (2 of 5 year exceedance rate)

Apalachicola Bay 0.042 0.046 0.073 0.077 East Bay 0.041 0.045 0.064 0.071 St George Sound 0.023 0.025 0.051 0.054
St. Vincent Sound 0.043 0.047 0.074 0.074 Bay Wide 0.041 0.046 0.070 0.077



### TN (ug/L)

Segment Existing Long Term Geometric Mean Maximum Allowed Long Term Geometric Mean Annual Geometric Mean for a Network of Stations (2 of 5 year exceedance rate) Annual Geometric Mean for a Single Site (2 of 5 year exceedance rate)

Apalachicola Bay 0.69 0.76 1.00 1.03 East Bay 0.68 0.74 0.85 0.89 St George Sound 0.45 0.50 0.57 0.59
St. Vincent Sound 0.64 0.70 0.75 0.75 Bay Wide 0.68 0.75 0.95 1.00



### Chlorophyll a (ug/L)

Segment Existing Long Term Geometric Mean Maximum Allowed Long Term Geometric Mean Annual Geometric Mean for a Network of Stations (2 of 5 year exceedance rate) Annual Geometric Mean for a Single Site (2 of 5 year exceedance rate)

Apalachicola Bay 5.14 5.65 11.08 12.75 East Bay 4.14 4.55 7.36 8.80 St George Sound 1.78 1.96 3.70 4.10
St. Vincent Sound 8.20 9.02 25.33 25.33 Bay Wide 5.42 5.97 10.45 12.9150 Draft August 2010 

### References

Anderson, K. L., J. E. Whitlock, V. J. Harwood, and K. 2005. Persistence and differential survival of fecal indicator bacteria in subtropical waters and sediments. Appl

. Environ

. Microb

. 71:3041

– 3048. Boehm, A.B., N.J. Ashbold, J.M. Colford, Jr., L.E. Dunbar, L.E. Fleming, M.A. Gold, J.A. Hansel, P.R. Hunter, A.M. Ichida, C.D. McGee, J.A. Soller, and S.B. Weisberg. 2009. A sea change ahead for recreational water quality criteria. Journal of Water and Health 07.1: 9

– 20. Bonadonna, L., R. Briancesco, M. Ottaviani, and E. Veschetti. 2002. Occurrence of Cryptosporidium oocysts in sewage effluents and correlation with microbial, chemical and physical water variables. Environ

. Monit

. Assess

. 75:241

– 252.51 Draft August 2010 Boynton, W. R., W. M. Kemp, and C. W. Keefe. 1982. Comparative analysis of nutrients and other factors influencing estuarine phytoplankton production. In : V. S. Kennedy (Ed.), Estuarine comparisons (New York: Academic Press, pp. 69

- 90)

. Byappanahalli, M. N., and R. S. Fujioka. 1998. Evidence that tropical soil environment can support the growth of Escherichia coli

. Water Sci

. Technol

. 38:171

– 174. Byappanahalli, M. N., D. A. Shively, M. B. Nevers, M. J. Sadowsky, and R. L. Whitm an. 2003. Growth and survival of Escherichia coli and enterococci populations in the macro

- alga Cladophora ( Chlorophyta ). Fems Microbiol

. Ecol

. 46:203

– 211.
Cairns, D. J. 1981. Detrital production and nutrient release in a southeastern flood

- plain fore st. M. S. Thesis
, Florida State University
, Tallahassee, FL

. Chanton, J.
, and F. G. Lewis. 1999. Plankton and dissolved inorganic carbon isotopic composition in a river

- dominated estuary: Apalachicola Bay, Florida. Estuaries 22: 575

- 583.

——— . 2002. Examination of coupling between primary and secondary production in a river

dominated estuary: Apalachicola Bay, Florida, U. S. A. Limnol. Oceanogr. 47: 683

- 697. Continental Shelf Associates, Inc(CSA). 1985. Apalachicola Bay Study: Submerged vegetation assessment of the Apalachicola Bay System. Prepared for the U.S. Army Corps of Engineers. Mobile District, Sea Grant Publication No. MASGP 84 020. Danglade, E. 1917. Conditions and extent of the water level oyster beds and barren bottoms in the vicinity of Apalachicola, Florida. Appendix V, Reports of the U.S. Commissioner of Fishes for 1916, Bureau of fishes Document No. 841. 75 pp.
Edmiston, H. L. 2008. A river meets the bay: A characterization of the Apalachicola River and Bay system. Apalachicola National Estuarine Research Reserve (ANERR).
Elder, J. F.
, and D. J. Cairns. 1982. Production and decomposition of forest litter fall on the Apalachicola River floodplain, Florida. U.S. Geological Survey Water

- Supply Paper 2196.

Elder and Cairns

. 1982 . Production and decomposition of forest litter fall on the Apalachicola River floodplain, Florida. U. S. Geological Survey Water

- Supply Paper 2196

Fahrny et al. 2006. Submerged Aquatic Vegetation Monitoring in Apalachicola Bay, Florida. Unpublished report to NOAA. Apalachicola National Estuarine Research Reserve. 24 pp.

Federle et al. 1983. Modification of estuarine sedimentary microbiota by exclusion of epibenthic predators. Journal of Experimental Marine Biological Ecology 73: 81

- 94.
Florida Department of Environmental Protection. 2002. Basin status report: Apalachicola

– Chipola. Tallahassee, FL: Division of Water Resource Management.

Florida Fish and Wildlife Conservation Commission. 2008. Fisheries

- Independent Monitoring Program 2008 a nnual d ata s ummary r eport.

Fric k, E.A.
, G.R. Buell , and E.E. Hopkins

. 1996

. Nutrient sources and analysis of nutrient water

- qualit y data, Apalachicola

- Chattahoo chee

- Flint River basin, Georgia, Alabama, and Florida, 1972

– 90

. U.S. Geological Survey Water

- Resou rce Investigations Report 96

- 4101. Atlanta, GA

. Federle, T. W. , R. J. Livingston, D. A. Meeter, and D. C. White. 1983. Modification of estuarine sedimentary microbiota by exclusion of epibenthic predators. J

. Exp

. Mar

. Biol

. Ecol

. 73: 81

- 94.52 Draft August 2010 Frick et al. 1996

. Nutrient sources and analysis of nutrient water

- quality data, Apalachicola

Chattahoo chee

- Flint River basin, Georgia, Alabama, and Florida, 1972

- 90. USG S Water

Resource Investigations Report, 96

- 4101, Atlanta, GA

. Fulmer, J.M. 1997. Nutrient e nrichment and nutrient input to Apalachicola Bay, Florida. MS Thesis, Florida state University. Tallahassee, FL. 58 pages. Gulf of Mexico Alliance (GOMA). 2009. Comments regarding pending EPA Clean Water Act, recreational water quality criteria. Prepar ed for the EPA stakeholders workshop, October 6

– 7, 2009, Chicago, IL.
Harwood, V. J., A. D. Levine, T. M. Scott, V. Chivukula, J. Lukasik, S. R. Farrah, and J. B. Rose. 2005. Validity of the indicator organism paradigm for pathogen reduction in reclaim ed water and public health protection. Appl

. Environ

. Microb

. 71:3163

– 3170. HydroQual Inc. June 23, 2010. Apalachicola R iver nutrient loadings. Technical memorandum prepared for the Florida Department of Environmental Protection, Tallahassee, FL

. Ingle and Dawson

. 1952

. Growth of the American Oyster Crassostrea virginica (Gmelin) in Florida Waters. Bull. Mar. Sci. Gulf and Caribbean 2:393

- 404.

——— . 1953 . A survey of Apalachicola Bay, Technical Series No. 10. State of Florida Board of Conservation 38 pp. Ishii, S., W. B. Ksoll, R. E. Hicks, and M. J. Sadowsky. 2006. Presence and growth of naturalized Escherichia coli in temperate soils from Lake Superior watersheds. Appl

. Environ

. Microb

. 72:612

– 621.

Iverson , R. L., W. Landing, B. Mortazav i, and J. Fulmer. 1997. Nutrient transport and primary productivity in the Apalachicola River and Bay. In: F. G. Lewis (Ed.), Apalachicola River and Bay freshwater needs a ssessment. Report to the ACF/ACT Comprehensive Study. Havana, FL: Northwest Florida Water Management District. Unpublished r eport

. Jeng, H. W. C., A. J. England, and H. B. Bradford. 2005. Indicator organisms associated with stormwater suspended particles and estuarine sediment. J. Environ

. Sci

. Heal

. A 40:779

– 791.

Ks oll, W. B., S. Ishii, M. J. Sadowsky, and R. E. Hicks. 2007. Presence and sources of fecal coliform bacteria in epilithic periphyton communities of Lake Superior. Appl

. Environ

. Microb

. 73:3771

– 3778. Lemarchand, K., and P. Lebaron. 2003. Occurrence of Salmonella spp. and Cryptosporidium spp. in a French coastal watershed: Relationship with fecal indicators. Fems Microbiol

. Lett

. 218:203

– 209. Lewis, F.G., 2003. Presentation from Seminar for Apalachicola National Estuarine Research Reserve, March 2003.
Livingston, R. J. 1976. Dynamics of organochlorine pesticides in estuarine systems and their effects on estuarine biota. Invited paper

. Proc eedings of the Third International Estuarine Research Federation Conference, Galveston Texas, October, 1975. Estuarine Processes I., 507

- 522.
Livingston , R.J. 1980 . Critical Habitat Assessment of the Apalachicola Estuary and Associated Coastal Areas. Fi nal Report, Coastal Plains Regional Commission, Tallahassee, Florida.53 Draft August 2010 ——— . 1981a. River

- derived input of detritus into the Apalachicola E stuary

. In : R. D. Cross and D. L

. Williams (Eds.), Proceedings of the national symposium on freshwater inflow to estuaries (Washington, DC: U.S . Fish and Wildlife Service, pp. 320

- 332 ).

——— . 1983 . Resource Atlas for the Apalachicola Estuary. Report Number 55. Florida Sea Grant.

——— . 1984 a

. Long

- term effects of dredging and open

- water disposal on the Apalachicola Bay system. Final r eport . Washington, DC: National Oceanic and Atmospheric Administration.

——— . 1984 b

. The ecology of the Apalachicola Bay system: An estuarine profile. U.S. Fish and Wildlife Service FWS/PBS 82/05.

——— . 1984 c

. Field characterization study of a Gulf coastal seagrass system. Unpublished report for the U. S

. Environmental Protection Agency.

——— . 1991a. The rivers of Florida. New York: Springer

- Verlag.

——— . 2000. Eutrophication processes in coastal systems: Origin and succession of plankton blooms and effects on secondary production. Boca Raton, FL: CRC Press.

——— . 2002. Trophic organization in coastal systems. Boca Raton, FL: CRC Press.

——— . 2008 a

. Importance of river flow to the Apalachicola River

- Bay system. Florida Department of Environmental Protection.

——— . 2008b. Water quality and seagrass survey in the Carrabelle River and St. George Sound. Unpublished report for the Apalachicola River K eepers and c ity of Carrabelle.

——— . 2010. Nutrients in Apalachicola River

- Bay system

. U npublished report for the Florida Department of Environmental Protection , Tallahassee, FL

. Livingston, R. J.
, and O. L Loucks. 1978. Productivity, trophic interactions, and fo od

- web relationships in wetlands and associated systems. In : P. E. Greeson, J. R. Clark, and J. E. Clark (Eds.), Wetland functions and values: The state of our understanding (Lake Buena Vista, FL: American Water Resources Association , pp. 101

- 119 ). Livingston, R. J., R. L. Iverson, R. H. Estabrook, V. E. Keys, and J. Taylor, Jr. 1974. Major features of the Apalachicola Bay system: Physiography, biota, and resource management. Florida Scientist 4: 245

- 271.
Livingston, R. J., X. Niu, F. G. Lewis, and G. C. Woodsum. 1997. Freshwater input to a Gulf estuary: Long

- term control of trophic organization. Ecol. Appl. 7: 277

- 299. Livingston, R. J., Howell, R. L., Niu, X., Lewis, F. G. and Woodsum, G. C. 1999. Recovery of oyster reefs ( Crassostrea vi rginica ) in a G ulf estuary following disturbance by two hurricanes. B . Mar. Sci.
, Gulf and Caribbean 64, 75

- 94.
Livingston, R. J., F. G

. Lewis, III, G

. C. Woodsum, X

. Niu, R. L. Howell, IV, and G. L. Ray et al. 2000. Coupling of physical and biological models: response of oyster population dynamics to freshwater input in a shallow Gulf estuary. Est. Coast. Shelf Sci.50: 655

- 672. Livingston et al. 200 5. Restoration of Aquatic Systems. CRC Press, Inc. Boca Raton, Florid a, 424 pp. Lund, V. 1996. Evaluation of E

- coli as an indicator for the presence of Campylobacter jejuni and Yersinia enterocolitica in chlorinated and untreated oligotrophic lake water. Water Res

. 30:1528

– 1534.
Mattraw, H. C.
, and J. F. Elder. 198 4

. Nutrient and detritus transport in the Apalachicola River, Florida. U. S. Geological Survey Water

- Supply Paper 2196

- C.54 Draft August 2010 McLane, B. G. 1980. An investigation of the infauna of East Bay

- Apalachicola Bay. M. S. t hesis
, Florida State University, Tallahassee
, FL. Menzel and Nichy

. 1958

. Studies of the distribution and feeding habits of some oyster predators in Alligator Harbor, Florida. Bulletin of Marine Science Gulf and Caribbean 8: 125

- 145.

Menzel et al. 1966 . Oyster abundance in Apalachicola Bay, Florida in relation to biotic associations influenced by salinity and other factors. Gulf Research Reports 2: 73

- 96. Menzel R.W. 1983. Genetics and the potential for oyster production in Apalachicola Bay. Apalachicola Oyster Industry: Conference Proceedings. S. Andree, editor. Florida Sea Grant Program 57:22

- 26. Morrison et al. 1977. Evidence of microfloral succession of allochthonous plant litter in Apalachicola Bay, Florida, U. S. A. Marine Biology 41:229

- 240. Mortazavi, B., R. L. Iverson, W. M. Landing, and W . Huang

. 2000a. Phosphorus budget of Apalachicola Bay: A river

- dominated estuary in the n ortheastern Gulf of Mexico. Mar

. Ecol .- Prog

. Ser

. 198: 33

- 42. Mortazavi, B., R. L. Iverson, W. M. Landing, F. G. Lewis, and W. Huang

. 2000b. Control of phytoplankton production and biomass in a river

- dominated estuary: Apal achicola Bay, Florida USA. Mar

. Ecol .- Prog

. Ser

. 198: 19

- 31.
Mortazavi, B., R. L. Iverson, and W. Huang

. 2000c

. Dissolved organic nitrogen and nitrate in Apalachicola Bay, Flori da: S patial distrib utions and monthly budgets. Mar

. Ecol .- Prog

. Ser

. 214: 79

- 91. Mortazavi et al. 2001. Dissolved organic nitrogen and nitrate in Apalachicola Bay, Florida, USA: spatial distributions and monthly budgets. Marine Ecology Progress Series 21 4:79

- 91.

Murrell M. C.
, and Caffrey
, J. M. 2005. High cyanobacterial abundance in three northeastern Gulf of Mexico estuaries

. Gulf and Caribbean Research Vol. 17, 95

- 106
, 97.
Myers, V. B. 1977. Nutrient limitation of phytoplankton productivity in north Florida coastal systems: Technical considerations; spatial patterns; and wind mixing effects. Ph. D. d issertation
, Florida State University
, Tallahassee, FL

. Myers, V. B.
, and R. J. Iverson. 1977. Aspects of nutrient limitation of phytoplankton productivity in the Apalachicola Bay system. In : R. J. Livingston (Ed.), Proceedings of the conference on the Apalachicola drainage system (St. Petersburg, FL: Florida Department of Natural Resources, Marine Resources Publication 26 , pp. 67

- 74)

.

——— . 1 981. Phosphorus and nitrogen limited phytoplankton productivity in Northeastern Gulf of Mexico coastal estuaries. In : B J. Nielson and L. E. Cronin (Eds.), Estuaries and nutrients (Clifton, NJ: Humana Press, pp. 569

- 582 ).
Nixon, S. W. 1988. Physical energy inputs and the comparative ecology of lake and marine ecosystems. Limnol. Oceanogr. 33: 1005

- 1025.

Putland , J. 2005. Ecology of Phytoplankton, Acartia Tonsa, and Micro Zooplankton in Apalachicola Bay, FL. Florida State University

- Department of Oceanography. Rees, G., K. Pond, K. Johal, S. Pedley, and A. Rickards. 1998. Microbiological analysis of selected coastal bathing waters in the UK, Greece, Italy and Spain. Water Res

. 32:2335

– 2340.
Smith, S.V. 2003. Preliminary NOAA estuarine typology database

.55 Draft August 2010 Solo

- Gabriele, H. M., M. A. Wolfert, T. R. Desmarais, and C. J. Palmer. 2000. Sources of Escherichia coli in a coastal subtropical environment. Appl

. Environ

. Microb

. 66:230

– 237. Swift, F. 1896. Report of a survey of the oyster region of S t. Vincent Sound, Apalachicola Bay, and St. George Sound, Florida. U.S. Commission of Fish and Fisheries. Report of the U.S. Commission for 1896. Appendix 4, pp. 187

- 221. Topp, E., M. Welsh, Y. C. Tien, A. Dang, G. Lazarovits, K. Conn, and H. Zhu. 2003. Strain

- dependent variability in growth and survival of Escherichia coli in agricultural soil. F ems Microbiol

. Ecol

. 44:303

– 308.
Wanat, J. 2010. Estuarine nutrient criteria: Apalachicola Bay b ackground Information. Presentation for February 11, 2010
, public meeting on numeric nutrient criteria development, Apalachicola.
White, D. C. 1983. Analysis of microorganisms in terms of quantity and activity in natural environments : Microbes in their natural environments. Society for General Microbiology Sy mposium 34: 37

- 66. White, D. C., R. J. Bobbie, S. J. Morrison, D.K. Oesterhof, C. W. Taylor, and D. A. Meeter. 1977. Determination of microbial activity of lipid biosynthesis. Limnol. Oceanogr. 22: 1089

- 1099. White, D. C., R. J. Livingston, R. J. Bobbie, and J. S. Nickels. 1979a. Effects of surface composition, water column chemistry, and time of exposure on the composition of the detrital microflora and associated macrofauna in Apalachicola Bay, Florida. In : R. J. Livingston ( Ed .), Ecological
proces ses in coastal and marine systems (New York: Plenum Press , pp. 83

- 116). White, D. C., W. M. Davis, J. S. Nickels, J. D. King, and R. J. Bobbie. 1979b. Determination of the sedimentary microbial biomass by extractable lipid phosphate. Oecologia 40: 51

- 62.

Whitfield , W.K., Jr., and Beaumariage , D.S. 1977 . Shellfish management in Apalachicola Bay: Past, present, and future. Proceedings of the Conference on the Apalachicola Drainage System. Eds. R. J. Livingston and E. A. Joyce, Jr. Florida Department of Natural Resources Mar. Res. Publ. 26: 130

- 140. Whitman, R. L., D. A. Shively, H. Pawlik, M. B. Nevers, and M. N. Byappanahalli. 2003. Occurrence of Escherichia coli and enterococci in Cladophora ( Chlorophyta ) in nearshore water and beach sand of Lake Michigan. Appl

. Environ

. Microb

. 69:4714

– 4719.56 Draft August 2010 

### Appendix A: Nutrients in Apalachicola River

- Bay System

Report written by Dr. Robert J. Livingston
, retired FSU professor
, for FDEP

. The report is found under the name Appen dix A for Apalachicola Bay Report .doc

Livingston, R.J. 2010. Nutrients in Apalachicola River

- Bay system. U npublished report for the Florida Department of Environmental Protection. . This report outlines the various research done by Dr. Livingston from 1970 to 2008 ; it includes a physical description of the Apalachicola Bay and River system, nutrients in the Apalachicola system , dominant species found in the Apalachicola system , the trophic organization of the bay, recent drought trends and bay productivity, and conclusions.57 Draft August 2010 

### Appendix B: Fish Landings by County and Year for all Florida Counties except Walton

An Excel spreadsheet that shows pounds caught and trips made per Florida county for each year from 1998 to 2008 , except for Walton County . T he only county that was used in preparing this report was Franklin County because it encompasses all of Apalachicola Bay. This spreadsheet covers finfish, invertebrates, and shrimp, and also provides a grand total for landings

. The Excel file is found under the

name Appendix B for Apalachicola Bay Report .xlsx

.58 Draft August 2010 

### Appendix C: Apalachicola River Nutrient Loadings

This memorandum summarizes the analyses performed by HydroQual Inc. to assist in the development of TN and TP loads for the Apalachicola River , i n order to support nutrient criteria development in Apalachicola Bay. While these analyses may not result in specific nutrient criteria values, the objective is to present an approach and corresponding results that can be used for the development of final values. Existing TN, TP
, and flow data were analyzed and, considering flow to be an explanatory variable, long

term nutrient loads were estimated. In addition, Apalachicola Bay water quality data from ANERR ’s System Wide Moni toring Program were analyzed.

HydroQual Inc. June 23, 2010. Apalachicola River nutrient loadings. Technical memorandum prepared for the Florida Department of Environmental Protection, Tallahassee, FL

.59 Draft August 2010 

### Appendix D: Fish Kills Associated with K. brevis in Franklin County , 2001

– June 21, 20 10

Source: FWRI f ish kill database Note: Specimen count is the number of specimen s found dead. Most of the sampling is carried out by members of the public, who call the FWRI fish kill hotline to report the dead fish

.

Report Number *Date Reported City *Count
y Call Categor
y *Probabl

e Cause Waterbody Name Specime n Count Comment

100901 10/9/2001 St George Island Frankli

n Fish Kill Red Tide St George Island 40 Pompano, Trout
112401 11/24/200 1 St George Island Frankli

n Fish Kill Red Tide St George Island 99 Species Unknown – Also reporting respiratory irritation. 112501 11/25/200 1 St George Island Frankli

n Fish Kill Red Tide St George Island 200 Mullet

– Beach at 10 th
St. West on St. George Island
112501 11/25/200 1 St George Island Frankli

n Fish Kill Red Tide St George Island 100 Mullet

112601 11/26/200 1 St George Island Frankli

n Fish Kill Red Tide St George Island 200 Mullet

112601 11/26/200 1 Panama City Frankli

n Fish Kill Red Tide St. Andrews State Park 200 Mullet

112601 11/26/200 1 St George Island Frankli

n Fish Kill Red Tide St George Island 50 Whiting

– Also reporting respiratory irritation. 112701 11/27/200 1 St George Island Frankli

n Fish Kill Red Tide St George Island 50 Mullet, Catfish

– Also reporting respiratory irritation. 112801 11/28/200 1 St George Island Frankli

n Fish Kill Red Tide St George Island 80 Catfish, Mullet
091602 9/16/2002 Apalachicol

a Frankli

n Fish Kill Red Tide Gulf City Canal 100 Mullet – Near chemical plant, all along canal. Gulf City Canal
091902 9/19/2002 Apalachicol

a Frankli

n Fish Kill Red Tide St. Joseph Bay 200 Lizardfish, Pigfish, Pinfish, Gafftopsail, Catfish

– Most decomposed60 Draft August 2010 , mouth gaping, no lesions, gasping

. 091903 9/19/2003 Apalachicol

a Frankli

n Fish Kill Red Tide St George Island 100s Bonnethead Shark, Needlefish, Hardhead Catfish – 1⁄2

m ile w est of Lighthouse

. 092003 9/20/2003 Apalachicol

a Frankli

n Fish Kill Red Tide St George Island 100s Flounder, Croaker, Whiting, Baitfish

– Odor of red tide
, respiratory irritation. 092003 9/20/2003 Apalachicol

a Frankli

n Fish Kill Red Tide St George Island 20 Flounder, Ladyfish

– Was on St. George Island State Park 09/20/03. Saw several dozen small flounder and ladyfish washed ashore. Were dead but intact (not decomposed ). Family and I started coughing.
092103 9/21/2003 Apalachicol

a Frankli

n Fish Kill Red Tide St George Island 5 Remora

– I previously submitted a report and gave "pilot fish" as one of the dead fish species seen. That

was incorrect, it

was Remoras.61 Draft August 2010 There were 5 of them and they were all approximatel
y 12 inches long.
092103 9/21/2003 Apalachicol

a Frankli

n Fish Kill Red Tide St Josephs Island 100 Flounder, Species Unknown

– I was at St. George Island today and stunned at the dead fish and eels on the beach. I have gone there for years and

never seen anything like this. They

were continuing to wash in. There were

even Pilot Fish.
092303 9/23/2003 St George Island Frankli

n Fish Kill Red Tide St George Island Beach Unknow n Count Croaker, Pinfish, Unidentified Species

– Has

someone reported the fish kill yet?

– Yes 041204 4/12/2004 East Point Frankli

n Fish Kill Red Tide St Joe Bay 12 Spot, Catfish, Spider Crab

– F DEP is heading over there to do
some counts and collect a few specimens. 041604 4/16/2004 East Point Frankli

n Fish Kill Red Tide St Joseph Bay 9 Red Drum, Shad

–This kill already reported by F DEP. 082505 8/25/2005 Carrabelle Frankli

n Fish Kill Red Tide Dog Island 100s Snapper, Red Drum, Black62 Draft August 2010 Grouper, Pinfish, Grunt

– Due south of Dog Island 4 miles to 11 miles out.
082905 8/29/2005 Carrabelle Frankli

n Fish Kill Red Tide Carrabelle to B Tower 200 Hog Snapper, Grunt, Grouper

– Also east of Dog Island.
083005 8/30/2005 Alligator Point Frankli

n Fish Kill Red Tide Bald Point State Park 100s Grouper, Horned Fish, Baitfish

– Has 72 dead fish

– sending
water sample. Ocklocknee River

– at mouth.
083005 8/30/2005 East Point Frankli

n Fish Kill Red Tide St Joseph Bay Unknow n Count Shark, Grouper, Species Unknown

– Reporting respiratory irritation. 083005 8/30/2005 St George Island Frankli

n Fish Kill Red Tide St George Island Unknow n Count Trout, Whiting, Puffer, Catfish, Eel, Redfish – Casa Del Mar to St George Island Plantation.
083005 8/30/2005 St George Island Frankli

n Fish Kill Red Tide St George Island 1000s Grouper, Redfish, Trout, Snapper, Grunt, Eel, Catfish

– East Side Gorrie Drive. 0909010 5 9/1/2005 St George Island Frankli

n Fish Kill Red Tide St George Island 20

- 100 Puffer, Grouper, Catfish, Species Unknown

– Bad smell.63 Draft August 2010

090405 9/4/2005 St George Island Frankli

n Fish Kill Red Tide St George Island 1000s Eel, Flounder, Catfish

– Do not call

– tourist

– gone. Reporting eye and respiratory irritation. 090405 9/4/2005 St George Island Frankli

n Fish Kill Red Tide 1 1⁄2 Mi. State Park Entrance 1000s Shark, Eel, Dolphin

090505 9/5/2005 East Point Frankli

n Fish Kill Red Tide St George Island Plantation 100 Species Unknown

– The dead fish

were seen on the bay side of St. George Island Plantation (w est end).
090505 9/5/2005 St George Island Frankli

n Fish Kill Red Tide St George Island Unknow n Count Species Unknown

– There are many large fish.
090605 9/6/2005 East Point Frankli

n Fish Kill Red Tide Little St George Island 3 Tiger Shark

– We found the sharks washed up on the beach of Little St. George Island. The 3

were approximatel y 6 to 8 feet in length and partially decomposed . There has been an ongoing red tide event on the island, but the sharks were

more decomposed than anything64 Draft August 2010 else.
090705 9/7/2005 East Point Frankli

n Fish Kill Red Tide St George Island Bay 20

- 100 Eel, Snapper, Grouper

– Reporting respiratory irritation also.
091705 9/17/2005 Apalachicol

a Frankli

n Fish Kill Red Tide Crooked Island Sound 5547 Mullet, Red Drum, Sheepshead, Stingray, Trout, Jack Crevalle

– Unbelievable number of dead and dying fish,
many, many thousands. Other species included menhaden, scaled sardine, southern stargazer, sharksucker, flounder, spanish mackerel, king mackerel.
091805 9/18/2005 St George Island Frankli

n Fish Kill Red Tide Nick's Hole 1000s Species Unknown

– Fish are from small to medium size.
092605 9/26/2005 Carrabelle Frankli

n Fish Kill Red Tide Carrabelle Beach 1000s Redfish, Hammerhea d Shark, Croaker, Puffer

– 3 miles south of Carrabelle. Ho Hum Travel Park.
092605 9/26/2005 Carrabelle Frankli

n Fish Kill Red Tide Carrabelle Beach 1000s Redfish, Sheepshead, Toadfish, Hammerhea65 Draft August 2010 d Shark, Baitfish, Stingray, Baitfish
092605 9/26/2005 St George Island Frankli

n Fish Kill Red Tide St George Island 86 Mullet, Catfish, Batfish

– Many dead fish there were on the beach. The smell was awful. Rough surf from Hurricane Rita helped wash much off the beach and the red tide was so strong. 092605 9/26/2005 St Teresa Beach Frankli

n Fish Kill Red Tide Alligator Point & FSU Marine Lab Unknow n Count Bonnethead Shark, Stingray, Flounder, Pigfish
092805 9/28/2005 St George Island Frankli

n Fish Kill Red Tide Park Entrance 1000s Flounder, Catfish, Red Grouper

– Flounder are small.
092805 9/28/2005 Carrabelle Frankli

n Fish Kill Red Tide St George Sound 2002 Stingray, Grunt

– The fish were washed up along the bank. Probably between 4 to 6 per foot of the shoreline. This Saturday, this was along the shore at my home.
092905 9/29/2005 Carrabelle Frankli

n Fish Kill Red Tide Carrabelle Beach 100s Red Drum, Mullet, Shark, Stingray,66 Draft August 2010 Species Unknown

– Reporting respiratory irritation. 092905 9/29/2005 Carrabelle Frankli

n Fish Kill Red Tide Carrabelle Beach 306 Mullet, Red Drum, Shark

– Went to beach myself and observed the dead fish. Can see dead fish all the way down the beach as far as you

can see. 100105 10/1/2005 Carrabelle Frankli

n Fish Kill Red Tide St George Sound 20

- 100 Pinfish, Hammerhea d Shark

– Willing to take water samples.
100205 10/2/2005 Carrabelle Frankli

n Fish Kill Red Tide St George Sound 100s Shark, Stingray, Pinfish, Red Drum, Mullet

– A lot of sharks, but few rays.
100505 10/5/2005 Lanark Frankli

n Fish Kill Red Tide Dog Island 1000s Stingray, Shark, Species Unknown

– Would like us to collect samples.
100505 10/5/2005 Carrabelle Frankli

n Fish Kill Red Tide St George Sound Unknow n Count Pinfish, Anchovy, Shark, Toadfish, Croaker, Gulf Flounder
100705 10/7/2005 St George Island Frankli

n Fish Kill Red Tide Plantation Airstrip 1015 Mullet, Trout

– Small inlet from the bay near our house full of dead mullet and a few other67 Draft August 2010 species. 100705 10/7/2005 St George Island Frankli

n Fish Kill Red Tide Resort Vacation Properties Unknow n Count Species

u nknown

– I
am not sure of how many or what kind.
101005 10/10/200 5 St George Island Frankli

n Fish Kill Red Tide Randolf Tray Canal 100s Mullet, Pinfish

– Dead fish are mostly Pinfish. West of bridge.
101005 10/10/200 5 Apalachicol

a Frankli

n Fish Kill Red Tide Alligator Bay 1000 Alewi v es
– Noticed a red tide smell to the air. 110805 11/8/2005 East Point Frankli

n Fish Kill Red Tide West Pass

– Apalachicol

a 25 Gar