St. Lucie River Estuary: Evidence of Impairment 

July, 2002 

G. Graves, M. Thompson, and D. Fike 

Southeast District Water Quality Section 

Florida Department of Environmental Protection 

Port Saint Lucie 
Table of Contents

Executive Summary 3

Introduction 4 

Existing Documentation of St. Lucie Impairment 5 

 Sediment 7

 

 Seagrasses 9

 Oysters 10

 Nutrient enrichment/algal blooms 11 

 Fish 13

 Benthic Macroinvertebrates 15 

Benthic Community Impairment Verification Study 17 

Methods 17 

Results 20

Discussion 26

Conclusions 28

 

References 29

2 
Executive Summary

Anthropogenic impacts to the Saint Lucie Estuary (SLE) have impaired its function as an important 

estuarine ecosystem and resource. Stream channelization, wetland drainage and conversion, 

construction of drainage canal systems, urbanization and agriculture activity have so completely 

modified the watershed that it can no longer function as a healthy ecosystem. Studies document the 

loss of oyster and seagrass populations, fish abnormalities, increased sedimentation rates, high 

nutrient loadings, adverse fluctuations in normal estuarine salinity regimes, and impacts to 

invertebrate populations. Under the Impaired Waters Rule adopted by Florida as the methodology for 

placing waters of the state on the EPA required 303(d) list, portions of the SLE may escape 

classification as “impaired” unless a case can be presented which identifies an imbalance of flora and 

fauna. Once a waterbody is listed as impaired, a process of developing basin-specific water quality 

criteria and source-loading allocations (Total Maximum Daily Loads-TMDL) can begin. This 

document is intended to assure that the SLE is included in the TMDL program by presenting previous 

studies which have shown impairment in the SLE and by providing new research which verifies an 

imbalance in flora and fauna. 

Over the last forty years sedimentation in the SLE has increased to a rate two and a half times that of

the pre-settlement era. Thick muck deposits have accumulated throughout the estuary and have had 

detrimental impacts on benthic communities. These sediments are also contaminated with pesticides 

and metals at levels that may be toxic to indigenous organisms. Research indicates that turbidity and 

algal blooms have contributed to the near elimination of once abundant seagrasses from the SLE. 

Few oyster beds now exist in the SLE, and existing beds show high mortality. Studies have 

suggested that salinity fluctuations and sediment smothering caused by freshwater canal discharges 

are to blame for the elimination of once abundant oyster stocks. Freshwater discharges have also 

been correlated to outbreaks of fish abnormalities in the SLE. Construction of major canal systems 

which discharge to the SLE have increased phosphorus inputs by 100 percent, and nitrogen inputs by 

200 percent. This increased nutrient loading may be a factor in seagrass disappearance, occurrence of 

abnormal fish, a shift from macrophyte-dominated primary production to phytoplankton-dominated 

production, occurrence of hypoxia/anoxia, occurrence of harmful algal blooms, and other detrimental 

environmental changes. 

In an effort to verify the impairment which previous studies have identified, twenty-one benthic 

invertebrate samples were taken along an upstream-downstream gradient in the SLE and its receiving 

body, the Indian River Lagoon (IRL). These samples were analyzed using multivariate statistical 

methods and an Estuarine Index of Biotic Integrity (IBI) was calculated for each sample. The 

analyses show a distinct difference between sites in the SLE and sites in the IRL. The IBI scores 

showed that the majority of the SLE sites could be categorized as “degraded”, while no sites in the 

IRL were degraded. Historical water quality data analyzed for this study showed that nutrient (total 

nitrogen and total phosphorus) levels were significantly higher in the SLE than in the IRL. These 

SLE nutrient concentrations were much higher than the mean for Florida estuaries, and significantly 

higher than EPA guidelines for nutrient concentrations in rivers and streams (it is anticipated that 

concentration guidelines for estuaries will be lower than guidelines for rivers and streams). Water 

quality data also showed the upper SLE had numerous violations of the water quality criteria for 

copper, and will likely meet the definition of “impaired” once data sufficiency requirements have 

been satisfied. Based on the weight of evidence presented within this document, the SLE should be 

included on the Florida list of verified impaired waters (303(d) list). 

 

3 
Introduction 

River-estuarine and coastal systems are among the most productive ecosystems on earth (Livingston 

2001). Most of Florida’s communities are highly dependent on their natural resources, especially 

those related to natural water bodies, whether freshwater or estuarine systems. However, the 

remaining ecosystems in south Florida no longer exhibit the ecological functions, species richness, 

and spatial extent that defined the pre-drainage systems (USACOE 1999). Many wetlands that once 

acted as natural filters and retention areas have been impaired by over-drainage or lost altogether by 

conversion. Urban and agricultural development utilized an intricate and highly efficient system of 

drainage canals and ditches to rapidly discharge pollutant-laden runoff into the region’s waterbodies; 

these discharges affect normal salinity regimes in downstream estuaries. 

Nearly all of the natural waterbodies in south Florida have been modified through channelization and 

dredging. Dredge spoil banks created next to canals and channelized streams such as the North Fork 

of the St. Lucie River, are easily eroded and become a source of turbidity. The banks also isolate 

oxbows and floodplain wetlands, thereby decreasing the storage and filtering capacities of the natural 

system. 

Excessive human-induced nutrient concentrations and loading in southern Florida waterbodies have 

led to a variety of negative impacts to the ecosystem. These impacts include imbalances in aquatic 

vegetation and animal communities, algal blooms, fish kills, depressed levels of dissolved oxygen 

(DO) and other signs of degraded ecosystem function and declining ecological productivity. 

The Indian River Lagoon and its tributaries (e. g., the St. Lucie Estuary) “are a resource in peril, 

having been severely impacted by human activities for over a hundred years” [United States Army

Corps of Engineers (USACOE) and the South Florida Water Management District (SFWMD) 2001]. 

To address this situation, the Water Resources Development Act legislation was enacted in 1996 and 

2000, the Comprehensive Everglades Restoration Plan (CERP) Design Agreement was executed in 

2000, and Florida legislation in 2001 recognized that restoration of water quality was an integral and 

essential function of CERP. 

The Florida Department of Environmental Protection (FDEP) has been given the task of conducting 

Total Maximum Daily Load (TMDL) analyses in compliance with Section 303(d) of the Clean Water 

Act. States are required to identify waterbodies that fail to meet state surface water quality standards 

and place them on the 303(d) list. After the state has completed the United States Environmental 

Protection Agency (USEPA) approved TMDL analysis, waterbodies can then be removed from the 

303(d) list when a waterbody meets water quality standards, or when it is determined that other 

pollution control programs will result in attainment of water quality standards (Florida Statute 62-

302.600). The purpose of the TMDL program is to identify the causes and solutions to water quality 

impairment in water bodies and to establish an upper limit or ceiling on the specific amount of 

pollutant(s) which the water body can incorporate and still meet standards. 

To insure that the TMDL listing process was consistent and scientifically based, the Florida 

Environmental Regulatory Commission officially adopted Chapter 62-303 of the Florida 

Administrative Code (FAC) titled “Identification of Impaired Surface Waters” in May 2002. The 

following text from the Impaired Waters Rule (IWR) introduces its scope and intent: 

“This chapter establishes a methodology to identify surface waters of the state that will be 

included on the state’s planning list of waters that will be assessed pursuant to subsections 

403.067(2) and (3), Florida Statutes (F.S.). It also establishes a methodology to identify 

4 
impaired waters that will be included on the state’s verified list of impaired waters, for which 

the Department will calculate Total Maximum Daily Loads (TMDLs), pursuant to subsection 

403.067(4), F.S., and which will be submitted to the United States Environmental Protection 

Agency pursuant to paragraph 303(d)(1) of the Clean Water Act (CWA).” 

The FDEP Watershed Assessment Group has divided the St. Lucie Estuary (SLE) and the Indian 

River Lagoon (IRL) into waterbody segments for evaluation under the IWR (Table 1). Portions of 

the SLE have been placed on the planning list for nutrients (303(d) listing) and dissolved oxygen 

(IWR listing), while other portions are currently not included on the list even though long-term

monitoring of nutrient concentrations has documented elevated concentrations (FDEP 2001). 

Table 1: Waterbody segments (WBID's) included in the SLE and South IRL. 

Planning Unit WBID Waterbody Segment Name IWR Impairment 

Coastal 3193 Lower St. Lucie Estuary None 

5003A South Indian River Lagoon None 

North St. Lucie 3194B North Fork St. Lucie Estuary Dissolved Oxygen, Nutrients 

South St. Lucie 3210 South Fork St. Lucie Estuary None 

A waterbody can be placed on the verified impaired list “for other information” if an imbalance in 

flora and fauna can be documented. The IWR contains specific provisions regarding placement of 

waterbodies on the verified list for impairment under these circumstances. Specifically the IWR 

states in subsection 62-303.450(2): 

“If the water was listed on the planning list for nutrient enrichment based on other information 

indicating an imbalance in flora or fauna, as provided in Rule 62-303.305(1), the Department 

shall verify the imbalance before placing the water on the verified list for impairment due to 

nutrients and shall provide documentation supporting the imbalance in flora or fauna.” 

(italics inserted) 

This report was composed to meet the Department’s obligation to provide documentation supporting 

an imbalance in flora or fauna in the SLE. A weight of evidence approach will be used to establish 

that impairment, as evidenced by this imbalance, does exist in the SLE. The evidence presented in 

this report is divided into two parts: 

(1) A summary of information from previous studies and reports which documented or related 

to SLE biological imbalance, water quality impairment, and/or sediment contamination, and 

(2) New research which documents SLE biological impairment pursuant to the requirements 

and guidelines of the IWR. 

Existing Documentation of St. Lucie Impairment

The SLE (Figure 1) is one of the largest estuarine systems on the east coast of Florida and once 

provided vital habitat for substantial populations of fish and invertebrates that have biological and 

economic importance. The North Fork of the St. Lucie Estuary has been designated by the State of 

Florida as an aquatic preserve (Figure 1), whose management objectives are to maintain and improve 

existing resources such as seagrasses, mangroves, aquatic plants, birds, and fish (FDEP 2002b). 

However, the potential of the SLE to function as a productive ecosystem has been adversely affected 

5 
by many anthropogenic watershed and shoreline activities (Haunert and Konyha 2001). 

St. Lucie Inlet

Figure 1. The St. Lucie Estuary with Significant Features. 

The Indian River Surface Water Improvement and Management (SWIM) Plan was issued in 

compliance with the Florida Surface Water Improvement and Management Act (Florida Statutes 

Chapter 373.451-373.4595) in 1989 and then revised and updated in 1993. The SLE was identified 

as a priority for water and sediment quality improvement within the IRL watershed. Major 

environmental concerns within the SLE have been identified as adverse salinity fluctuations, 

accumulation of sediments and toxins, poor water quality, and loss of seagrass and shellfish resources 

(St. Johns River Water Management District and South Florida Water Management District 1994). 

The SWIM Plan Water and Sediment Quality Program identified five main objectives that must be 

achieved for protection and enhancement of water quality within the IRL and SLE: 

1. Management of freshwater inputs to minimize their negative impacts on a natural salinity regime. 

2. Assessment of sediment loadings and deposition rates relative to muck and turbidity problems, 

and reduction of suspended matter loadings to levels which will assure the overall health of the 

watershed. 

3. Reduction of excessive point and nonpoint source loadings of nutrients to a level which will 

promote a macrophyte-based (i.e., an ecosystem based on seagrasses rather than on plankton) 

system while slowing the rate of eutrophication. 

4. Elimination or significant reduction in releases of toxic substances from point and nonpoint 

sources. 

5. Reduction of anthropogenic loadings of fecal and total coliforms bacteria to shellfish harvesting 

areas. 

The SWIM Plan provided a good summary of the history of problems in the SLE but progress toward 

realizing the goals of the plan has been slow. Bringing the SLE into the TMDL development process 

by listing it as impaired will provide a new mandate for improvement of this vital estuarine resource. 

The following sections discuss water quality problems that have contributed to the collapse of the 

formerly healthy SLE ecosystem. 

6 
Sediment 

Several major basin modifications have increased sediment deposition rates in the SLE. In 1892, the 

St. Lucie Inlet was opened and maintained, transforming the former normally freshwater system to 

estuarine. The North St. Lucie River Water Management District completed an extensive drainage 

system in the watershed of the North Fork of the St. Lucie River basin in 1924. The St. Lucie canal 

(or C-44 canal), that connected the estuary to Lake Okeechobee, was also completed in 1924. The C23 and C-24 canals were completed in the early 1960s; these canals routed additional agricultural and 

urban runoff into the SLE. Schrader (1984) concluded that the average rate of sedimentation in the 

SLE has increased in the last 40 years, and that the major source of sediment was terrigenous material 

transported to the estuary as suspended load. Schropp et al. (1994) also concluded that the SLE 

sedimentation rate had increased in comparison to pre-development sediment deposition rates. Due 

to the increase in the amount of freshwater entering the St. Lucie Estuary, muck has been 

accumulating at a rate 2.5 times faster than historic or normal levels (USACOE and SFWMD 2001). 

Areas where muck has accumulated have become unfavorable environments for the survival of 

normal estuarine communities, and these sediments have caused water quality problems due to 

resuspension (USACOE and SFWMD 2001). The fine organic material which covers much of the St. 

Lucie Estuary bottom is known locally as “St. Lucie ooze”. Resuspension of these sediments releases 

nutrients to the water column, reduces light penetration, and depletes oxygen content in overlying 

waters (Traxler 2002). Letters to the editors of local newspapers and recollections by long time area 

residents, describe the SLE as very productive with good water clarity and a sandy bottom throughout 

much of its extent in the 1930’s and 1940’s. Some suggested that catastrophic loads of sediment 

carried from the C-44 canal (during water releases from Lake Okeechobee) into the estuary during 

storm events of that era coated the estuary with thick deposits and reduced its productivity (Stuart 

News 1992). 

Muck sediments have been presumed to originate from human activities and have been shown to 

have detrimental impacts on benthic biological communities and the overlying water column (Taylor 

Engineering 1994; Schropp 1994). High levels of organic materials and elevated concentrations of 

copper have been documented in the central portion of the north fork of the estuary (organic materials 

represented as “ignition loss”; Haunert 1988; Table 2). Exceptionally high levels of pesticides have 

been documented in the sediments of the St. Lucie Estuary, and normal half-lives appear to be 

extended, presumably due to the highly organic and anoxic conditions caused by the ooze (FDEP 

1995-2000 unpublished data 2002b). 

Monitoring studies conducted by the FDEP Southeast District Water Quality Section and SFWMD 

have found concentrations of some heavy metals and pesticides in SLE sediments to be above 

threshold effects levels (TELs) which are used as guidelines for evaluating sediment quality (Haunert 

1988; Thompson et al. 2001; Table 3). Studies have also suggested that the SLE sediment may 

exhibit toxicity to decomposer communities, has a high organic content and is very resistant to 

microbial degradation (Thompson et al. 2001). 

7 
Table 2: Heavy Metals in SLE Ooze. Survey of heavy metals in sediments of the St. Lucie Estuary 

(Haunert 1988). Numbers in blue exceed the TEL (threshold effects level), and in red exceed the ERL (effects range low) as per MacDonald et al. (1996). 

Site Ag As Cd Cu Hg Ni Pb Zn Ignition 

Loss 

Mean 

Phi 

1.3 0.04 36 1.2 229 4.3 21 62 235 59.81 6.05

2.2 0.23 28 0.8 75 1.0 17 46 43 12.85 6.15

6.4 0.25 23 0.5 8 0.2 8 17 3 23.67 3.12

8.3 0.05 33 0.8 15 0.4 17 39 4 21.94 4.84

10.3 0.24 27 0.3 13 0.5 27 40 54 14.87 6.93

11.1 0.20 2 0.0 2 0.1 4 1 2 28.96 1.27

11.2 0.09 46 1.0 37 0.7 27 54 27 28.21 7.55

11.3 0.23 32 0.7 15 0.6 23 43 59 22.13 7.30

12.2 0.04 32 0.7 23 0.5 19 49 27 27.85 5.01

12.3 0.04 45 0.9 22 0.4 16 55 43 14.55 4.76

13.2 0.22 13 0.4 6 0.4 22 12 20 14.16 2.86

14.2 0.24 32 0.7 29 0.5 38 35 65 48.94 6.03

15.3 0.21 3 0.0 1 0.0 4 0 2 27.58 1.28

18.4 0.24 23 0.4 15 0.2 13 24 38 15.41 4.23

19.2 0.94 30 0.9 22 0.5 34 31 66 22.97 5.87

21.1 0.22 30 0.5 28 0.3 21 39 62 30.66 5.24

24.1 0.24 24 0.9 15 0.2 26 25 58 33.65 5.61

26.1 0.25 12 0.3 13 0.1 30 17 34 69.27 2.80

31.2 0.24 28 0.6 17 0.2 23 42 61 21.27 6.14

32.1 0.04 30 0.8 29 0.4 29 40 63 23.53 4.55

35.2 0.20 27 0.8 20 0.6 37 41 71 41.16 7.07

36.2 0.05 45 1.1 32 7.8 23 59 55 63.54 8.07

37.2 0.04 45 0.9 59 0.7 29 56 100 33.36 7.75

40.1 0.04 31 0.8 36 0.4 14 31 34 20.93 5.29

42.1 0.05 25 0.7 27 8.5 9 22 15 47.34 3.74

44.1 0.04 43 0.8 60 0.4 19 42 69 34.02 6.14

c24.1 0.05 63 1.3 88 4.9 32 45 182 19.07 7.22

c24.3 0.05 46 0.8 172 2.5 21 42 219 28.63 7.21

s49 0.24 28 0.8 83 1.3 25 30 183 20.94 6.89

s50 0.24 27 0.4 77 1.0 50 44 139 9.61 4.22

s80 0.30 31 0.5 18 0.0 19 22 46 2.57 1.42

Table 3: SLE sediment monitoring data from Florida DEP Southeast District. Values exceeding 

threshold effects level (TEL) shown in blue. Values exceeding probable effects level (PEL) shown in 

red. 

Site Storet Date Hg As Cd Cr Cu Pb Mn Ni Zn DDE

TEL 0.13 7.24 0.68 52.30 18.70 30.20 15.90 124.00 2.07

PEL

NEST 28010037 9/14/00 0.15 5.90 2.10 32.10 71.60 26.60 244.00 7.30 110.00 4.7

SEST 28010229 9/14/00 0.20 5.40 2.20 25.60 46.40 25.60 231.00 7.70 85.00 9.5

NEST 28010037 7/25/00 0.19 5.30 0.78 38.30 70.40 28.00 238.00 8.60 110.00 7.4

SEST 28010229 7/25/00 0.24 4.80 0.83 36.40 41.10 25.00 222.00 9.70 82.00 12

NEST 28010037 4/20/00 0.16 6.80 0.60 32.80 93.10 27.00 264.00 9.60 110.00

SEST 28010229 4/20/00 0.20 5.10 0.49 27.10 44.10 26.00 249.00 9.80 85.00 8.6

NEST 28010037 11/23/99 0.24 9.40 0.48 40.00 68.30 83.10 197.00 12.50 94.00 6.4

SEST 28010229 11/23/99 0.17 13.00 0.33 28.00 103.00 246.00 9.40 130.00 11

NEST 28010037 8/25/99 0.18 3.71 0.43 27.50 38.40 30.50 223.00 7.12 106.00 7.6

SEST 28010229 8/25/99 0.26 2.65 0.44 23.30 20.70 26.70 196.00 6.01 76.10 10

NEST 28010037 6/28/99 3.00 0.35 39.30 23.60 28.50 234.00 9.08 63.00

SEST 28010229 6/28/99 0.25 2.10 0.45 37.40 15.20 28.20 195.00 7.43 35.80 7.4

NEST 28010037 9/30/98 5.00 87.80 4.8

SEST 28010229 9/30/98 4.00 34.20 4.9

Mean 0.20 5.44 0.79 32.32 55.71 38.18 228.25 8.69 90.58 7.86

Stdev 0.04 2.85 0.65 5.89 31.56 26.02 22.56 1.72 25.30 2.44

Min 0.15 2.10 0.33 23.30 15.20 25.00 195.00 6.01 35.80 4.70

Max 0.26 13.00 2.20 40.00 103.00 264.00 12.50 130.00 9.50

0.70 41.60 4.21 160.00 108.00 112.00 42.80 271.00 374

125.00

125.00

8 
It is of concern that these contaminated SLE sediments could be transported to and result in 

degradation of the Indian River Lagoon (Haunert 1988). McRae et al. (1998) analyzed EMAPEstuaries Carolinian Province Base Monitoring benthic data collected at 19 stations in Florida using 

multivariate statistical methods (BIO-ENV procedure). The study attributed dramatically different 

infaunal community structure at a sample site located at the mouth of the SLE in the IRL to elevated 

metals and organics concentrations in the sediments. 

Seagrasses 

Submerged aquatic vegetation (SAV) is probably the most productive habitat within the IRL 

(Gissendanner 1985; Dawes et al. 1995). SAV converts sunlight energy into food for fish, sea turtles, 

manatees, invertebrates, and other species. It provides habitat and nursery areas for many aquatic 

organisms. Seagrasses provide oxygen, act as substrate for epiphytic algae which are used by higher 

trophic levels, and reduce turbidity by stabilizing sediments and removing nutrients from the water 

column that might otherwise cause harmful algal blooms (Wood et al. 1969; Odum 1974; 

Gissendanner 1985). 

Reductions in water transparency caused by dredging, nutrient loading, stormwater runoff, and other 

anthropogenic activities upset the natural process of water column filtration by seagrasses, and 

therefore the stability and function of established and developing seagrass meadows. Reduced light 

penetration also restricts growth and coverage of SAV, eventually leading to the loss of beneficial 

functions. With that loss comes decreased bottom and shoreline stability, decrease macroepifaunal 

and infaunal abundance, and increased turbidity (Kenworthy and Haunert 1991). 

Relatively large and dense seagrass beds within the SLE were documented in the 1940s and 1950s, 

but have been sporadic since (URS Greiner Woodward-Clyde 1999). Current SAV resources in the 

SLE are restricted to narrow bands along the lower estuary downstream of the Sewells Point Bridge 

(Highway A1A, Stuart; Figure 2). Only the low-salinity tolerant seagrasses Najas and Ruppia were 

found in the upper estuary. A SAV survey conducted in the SLE by URS Greiner Woodward-Clyde 

(1999) revealed very little submerged aquatic vegetation. The SAV found during the survey was so 

sparse that only point locations (not beds) could be mapped. Low densities of SAV cover, mainly 

shoal grass (Halodule wrightii), were found in the lower estuary. No SAV was documented in the 

middle estuary or the North Fork, and only small patches were found in the South Fork. The 

endangered Johnson’s seagrass (Halophila johnsonii) was found near the mouth of the lower estuary. 

 

Figure 2: Range of submerged aquatic vegetation in the SLE as of 1997. Taken from URS survey. 

9 
High turbidities due to sediment resuspension and freshwater inflow limit light penetration and 

reduce the potential for sea grass colonization in the SLE (Schropp et al. 1994). Modeling indicates 

that some species of SAV should be well established in the shallow zones with sandy or mucky sand 

substrates throughout most of the estuary (URS Greiner Woodward-Clyde 1999). However, the 

easily re-suspended sediments of the St. Lucie Estuary have covered habitats and caused turbidity, 

limiting or preventing growth (USACOE and SFWMD 2001). Contrary to the State of Florida’s 

SWIM Plan goals for the SLE, the estuary has become a plankton-dominated system with limited 

seagrass and macroalgae (Chamberlain and Hayward 1996; USACOE and SFWMD 2001). Plankton 

dominated communities are subject to decreased photic zones, algal blooms, decreased dissolved 

oxygen, wide swings in dissolved oxygen concentrations, and a shift in ecosystem structure and 

function. Studies in a Texas estuary have shown long-term declines in seagrass cover due to algae 

blooms (Onuf 1996). 

Oysters 

Oysters are a valuable commercial fishery in Florida (Comp and Seaman 1988). Their high filtration 

capacity facilitates removal of particulates and plankton from overlying waters (Woodward-Clyde 

1998). Filtering activities of large masses of oysters can change the assemblage of plankton 

communities, reduce bacterioplankton and sea nettles, and reduce turbidity of an entire estuary, 

benefiting seagrass due to enhanced light penetration (Chesapeake Bay Program 1991). Larval, 

juvenile, and adult oysters are an important food source for many estuarine predators (Stanley and 

Sellers 1986; Woodward-Clyde 1994; 1998). 

Perhaps the most important role the oyster plays in estuaries is as a builder of habitats. Oysters are 

known as a “keystone” species in Western Atlantic ecosystems (Stanley and Sellers 1986). 

According to Woodward-Clyde (1998), the “American oyster tends to provide the greatest volume of 

hard substrate found in temperate and tropical estuaries of the western Atlantic. Under natural 

conditions, oyster reefs can be very large, and provide extensive attachment area for oyster spat and 

numerous associated species such as mussels, tunicates, bryozoans, and barnacles." Numerous 

species of molluscs, crustaceans, annelid worms, and other organisms hide in and amongst the 

elaborate hard structure of the typical natural oyster reef (Stanley and Sellers 1986; Woodward-Clyde 

1994; 1998). 

In 1959, oyster populations were described as abundant in the system (URS Greiner WoodwardClyde 1999). The SLE no longer supports permanent or extensive populations of oysters and 

seagrasses (Chamberlain and Hayward 1996). Together with documented declines in seagrass 

abundance over the last 30 years, oyster populations have become virtually nonexistent (Janicki et al. 

1996). In 1997, 27 oyster beds were mapped, but less than five percent of the oysters in 24 of the 

beds were alive (Figure 3). Percent cover of live oysters in the remaining three beds ranged from 5 - 

40% (Becky Robbins, SFWMD, personal communication 2002). 

Extended periods of salinity below 12 parts per thousand (ppt) can be fatal to oysters, or inhibit 

feeding, growth, and reproduction (Chesapeake Bay Program 1991; Stanley and Sellers 1986). 

Increased freshwater inputs from agricultural and urban drainage canal systems have probably been a 

major factor in the decline of the oyster in the SLE. Storm events and freshwater releases from

drainage canals can lower the salinity of the SLE to less than 5 ppt in 24 hours (Haunert and 

Startzman 1985). Releases from the C-44 canal can occur over an extended period of weeks to 

months (Haunert and Startzman 1980; FDEP Southeast District Water Quality Section personal 

observations). Even though oysters have developed efficient mechanisms for tolerating heavy 

10 
sediment loads and low salinities often found in estuaries, oysters can be overwhelmed and buried by 

heavy sedimentation, dying from suffocation (Chesapeake Bay program 1991). Substrates with a 

high proportion of sand can cause oyster mortality due to abrasion and valve injury. Shifting sandy 

substrate also destroys young spat. The sediment load released into the SLE from the major canal 

systems is largely sand. 

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Figure 3: Range of the eastern oyster, Crassostrea virginica, in the SLE as of 1997. Taken from

URS survey (URS Greiner Woodward-Clyde 1999).

Nutrient enrichment/algal blooms 

The addition of large nutrient loads (nitrogen and phosphorus) to estuarine waters fosters progressive 

organic enrichment and eutrophication, primarily due to accelerated phytoplankton production and 

biomass accumulation, followed by changes in the estuarine food web and periodic hypoxia and 

anoxia (Livingston 2001). Depletion of DO in bottom waters is typically caused by bacterial 

decomposition of accumulated phytoplankton and aquatic vegetation. Accelerated phytoplankton 

growth increases turbidity and light attenuation while decreasing production of submerged aquatic 

vegetation. Increased nutrient loading has also been associated with outbreaks of harmful algal 

blooms (HAB), suspected of killing fish, marine mammals and in some instances possibly affecting 

human health (Burkholder and Glasgow 1997; Moe et al. 2001; Landsberg and Steidinger 1998). 

Construction of the C-23, C-24, C-44, and other canals has resulted in a 100% increase in phosphorus 

load and a 200% increase in nitrogen load (USACOE and SFWMD 2001). Nutrient enrichment in 

the SLE has resulted in a shift from a seagrass-dominated to a phytoplankton-dominated system

(Chamberlain and Hayward 1996). Increased nutrient loads have caused higher primary production, 

resulting in unhealthy DO levels in the estuary (Janicki et al. 1996). Estimates of nutrients and solids 

loading to the estuary based upon flow data and average concentrations (1980–1990) from the C-23, 

C-24, and C-44 canals indicated that more than 3600 metric tons of suspended solids, 910 metric tons 

of nitrogen and 91 metric tons of phosphorus enter the estuary annually (Graves and Strom 1992). 

Because estimates did not reflect peak flow pulses, when loadings were much higher due to higher 

concentrations, actual transport to the estuary is believed much higher. For example, Haunert and 

Startzman (1980) calculated that 3.86-5.66 tons/day of suspended solids were delivered to the SLE 

during discharge events that they monitored. 

11 

Populations of phytoplankton are often assessed by measuring the amount of chlorophyll a (chla) in 

water samples. The occurrence of large episodic phytoplankton blooms, often exceeding 50 mg/m3
chla, anoxic and hypoxic events, and nutrient concentrations well above the average for Florida 

estuaries, suggests that nutrient loading to the SLE is excessive (Doering 1996). However, Doering 

(1996) examined four years of water quality, freshwater discharge, and tidal influence data from the 

SLE, and found that only 20-30 percent of the variability in chla could be explained by multiple 

regression against secchi depth, NH4, DIP, N02+3, flow rate and salinity. This relative inability to 

correlate chlorophyll to any large degree with nutrient concentration indicates that other factors 

(turbidity, light availability, grazing, stratification, flow dynamics, etc.) may dominate the processes 

governing phytoplankton biomass dynamics. Chamberlain and Hayward (1996) reported a median 

chla value of 9.2 mg/m3

, which placed it at just over the 50th percentile for Florida estuaries 

(Friedemann and Hand 1989). Highest chla values were associated with low to intermediate flows, 

lower nutrient concentrations, and low color values. This inverse relationship between chla and 

discharge suggest that chla (as a surrogate for phytoplankton production) is more responsive to light 

limitation (due to turbidity, sediment resuspension, color, or other factors) than elevated nutrient 

concentrations associated with increased freshwater inflows. This idea was supported by the chla 

model proposed by Chamberlain and Hayward (1996), and the existence of a similar condition in 

Charlotte harbor (Montgomery et al. 1991; McPherson et al. 1990). 

The chla production rate in the SLE was found to be less than the residence time of the estuarine 

water mass, indicating that the chla response to nutrient concentration may be mediated by a wash out 

effect during higher flows (Chamberlain and Hayward 1996). This suggests that utilizing chla as an 

indicator for assessing nutrient status in the SLE may be inappropriate, and that the complexities 

involved result in a tendency to under-estimate the actual estuarine nutrient enrichment condition. 

Scientific studies now link increased nutrient loadings to estuarine blooms of harmful algae such as 

Pfiesteria and Karenia (e.g., Burkholder and Glasgow 1997). Blooms of harmful algae have in turn 

been linked to fish lesions, fish kills, marine mammal deaths, and health concerns in humans 

(Burkholder and Glasgow 1997; Moe et al. 2001; Landsberg and Steidinger 1998). Initial surveys 

conducted by Florida Marine Research Institute (FMRI) showed Pfiesteria and other harmful algae 

were present within both the IRL and SLE at low densities (Landsberg 2001). Thus, nutrient 

enrichment may increase the likelihood of blooms of harmful algae within the SLE and IRL. 

A potential ramification of a high water volume turnover rate from the SLE is the impact discharges 

of nutrient-laden stormwater from the SLE have on nearshore reef ecosystems. Recent studies have 

shown that nutrients from stormwater may cause ecologically disruptive macroalgal blooms on coral 

reefs (Lapointe and Barile 2001). 

Fish 

There is a clear relationship between structural complexity of seagrass beds (particularly blade 

density) and fish abundance (e.g., Stoner 1983). Oyster beds also provide habitat and support 

increased fish abundance in a similar way (Woodward-Clyde 1998). The near elimination of oyster 

beds and seagrasses from the SLE has had an effect on the abundance of fish and other aquatic 

organisms. An evaluation of the SLE by Haunert and Startzman (1985) revealed that the fish 

community exhibited low diversity and was dominated by lower trophic level fish, especially bay 

anchovies. In contrast, the IRL supported diverse populations of estuarine benthic organisms and fish 

(Haunert and Startzman 1985). 

In a comparison between SLE and the Loxahatchee River Estuary, Browder (2002) reported that the 

highest overall prevalence of abnormal fish was in the SLE, based on the collection and examination 

of 3,906 fish of varying species. The report also suggested that the prevalence of fish abnormalities 

12 
is higher in the upper and middle SLE than in the Inlet area or the Jupiter Inlet area. The most 

common type of abnormality identified in the SLE was lesions, including fin erosion, spots or patches 

of inflamed or blood-congested skin, and ulcers (Figure 4). Evaluations conducted in 1998 by the 

Florida Fish & Wildlife Conservation Commission (FFWCC) found that, although both the St. Lucie 

and Caloosahatchee Estuaries experienced high levels of freshwater influx, the number of lesioned 

fish reported in the SLE was substantially higher than the number of lesioned fish reported in the 

Caloosahatchee. Increased public awareness of the condition on the east coast likely prompted 

increased reporting of abnormal fish from the southwest Florida coast near Ft. Myers, but still only 

eleven reports of lesioned fish from that region were ever received (FFWCC 2001) versus numerous 

and at times almost constant reports of lesioned fish in the SLE. 

Figure 4: Striped mullet, Mugil cephalus, from the SLE, exhibiting lesions. 

An FFWCC Fisheries Independent Monitoring (FIM) monitoring program was developed in the late 

1980’s to provide projections of juvenile and adult marine and estuarine fish populations in selected 

estuaries in Florida (Apalachicola Bay, Cedar Key, Tampa Bay, Florida Keys, Tequesta, the Indian 

River Lagoon, and the St. Johns River near Jacksonville). The St. Lucie Estuary was added to the 

FIM sampling program in April 1998. The FIM program (using non-selective gear and randomly 

selected sampling points within an estuary) now provides a statistically valid, synoptic view of fish 

health in those estuaries. 

Between April 1998 and December 2001, 941,459 marine and estuarine fish greater than 75mm in 

length were examined statewide for abnormalities by FIM staff using criteria developed by FFWCC 

researchers (including categories such as bloody lesions, fin rot, skin erosion, ulcer, tumor, skeletal 

deformities, parasites, and other). Abnormalities were found in 1016 fish or 0.11% of those 

examined (FFWWC unpublished data). Of the 74,080 fish examined at the Tequesta/SLE station 377 

or 0.51% were abnormal. Selected abnormal specimens were transported within 24 hours to the fish 

health lab in St. Petersburg for confirmation and additional evaluations. In 1998 the number of 

lesioned fish collected from the other estuaries was dramatically lower than the number collected 

from the SLE. That year 75 percent of the abnormal fish collected statewide came from the 

Tequesta/SLE station (Table 4). The highest incidence of lesions in the SLE was found in striped 

mullet, Mugil cephalus.

 

Table 4: Results of an FFWCC/FMRI/FIM study of fish with abnormalities. The number of fish 

with abnormalities is shown along with total number of fish inspected (in parentheses).

Monitoring Year Statewide Tequesta/St. Lucie Estuary 

1998 (April- December only) 396 (0.23%, n=170,690) 295 (0.95%, n=30,874) 

13 
1999 132 (0.05%, n=270,632) 42 (0.66%, n=6,368) 

2000 295 (0.11%, n=261,285) 31 (0.16%, n=19,534) 

2001 193 (0.08 %, n=238,852) 9 (0.05 %, n=17,304) 

Fish with lesions have been reported from numerous locations around the globe, in particular Asia, 

and in the last decade from the mid-Atlantic seaboard. A low-salinity tolerant pathogenic fungus, 

Aphanomyces invadans, has been associated with these lesions and with ulcerative mycosis (UM). 

The Florida lesions are very similar in appearance to fish with UM elsewhere and are typically found 

in low salinity environments. The majority of the skin lesions in Florida fish are bloody ulcers with 

raised irregular margins and deeply penetrating fungal hyphae in the surrounding muscle tissue. 

Recently, FWC researchers in collaboration with the University of North Carolina, identified 

Aphanomyces invadans from fish lesions in Florida using DNA technology. Increased observation 

and collection of fish with lesions in the SLE is closely correlated to large freshwater influxes and the 

subsequent lowering of salinity in the middle and upper estuary. 

Harmful algal blooms have been linked to the occurrence of abnormalities in fish. Because excessive 

nutrient loadings have been associated with increasing the probability of harmful algal blooms, there 

is evidence that nutrient inputs may be a factor influencing the incidence of fish abnormalities 

(Burkholder and Glasgow 1997). 

There is some evidence that sublethal exposure of fishes to copper may impair reproductive success 

and suppress growth and feeding (Eisler 1997) which may in turn cause fish to become more 

susceptible to bacterial and fungal infections. Of the twelve estuarine water column samples 

collected from the SLE during 1999-2000, eight (67%) exceeded the maximum criteria for copper in 

Class III marine waters (62.302 FAC), which may list the estuary as verified impaired per 62.303 

FAC for copper. The developing fish embryo or larva is generally considered the most sensitive 

stage in the life history, being particularly sensitive to all kinds of low-level environmental changes 

(Westernhagen 1988). Kingsford and Gray (1996) argued that it should not be assumed that 

pollutants simply disperse from a point source, but have been shown to concentrate along fronts, such 

as haloclines or thermoclines. Fish larvae do not drift about, but accumulate along these fronts where 

zooplankton concentration is often an order of magnitude greater than in the surrounding water. 

Thus, fish larvae feeding on plankton can be exposed to pollutants for longer periods than expected 

from simple diffusion and transport models. Many pollutants, especially metals and pesticides, cause 

mortality and chronic deformity in larvae, and can cause major deleterious effects with less than 24 

hours of exposure (Kingsford and Gray 1996). This has important implications because it suggests 

larvae may develop deformities with limited exposure to pollutants. Although larvae may not be 

killed immediately in plumes, they may suffer irreversible damage (Kingsford and Gray 1996). 

Scale disorientation (SD) which could not be explained by physical injury has been correlated with 

areas of increased sediment contamination. Areas of SD can appear spontaneously in normal juvenile 

and adult fish, and does not require prior scale loss (Corrales et al. 2000). Significant difference 

between regions having different levels of sediment contamination suggest environmental factors 

may be important in development of SD (Corrales et al. 2000). Sediment contaminants have also 

been implicated in severe viral outbreaks in marine mammals and liver lesions in bottom fish (Wilson 

et al. 2000; Stehr et al. 1998; Chang et al. 1998). Scale disorientation is common among St. Lucie 

Estuary fish (Browder 2001; 2002).

14 
Benthic Macroinvertebrates 

Salinity and bottom substrate are important environmental factors that affect fish and benthic 

communities (Haunert and Startzman 1985). When water column stratification is strong and vertical 

mixing reduced, bottom water hypoxia may persist for months. As a result, opportunistic species 

commonly dominate benthic communities in impacted waters (Kennish 1999). 

In addition to impacts from watershed modifications, the shoreline and benthic community has been 

negatively impacted by human activities. Shorelines and inter-tidal areas of the estuary that were 

once populated by mangroves and other detritus exporting vegetation now support very little 

vegetation. In many areas, seawalls and docks have replaced mangroves and seagrass (USACOE and 

SFWMD 2001). Unconsolidated sediments have accumulated in the estuary and are frequently resuspended by wave energy (Haunert 1988). This process has degraded habitat for bottom dwelling 

organisms, shaded out benthic vegetation, and has added to water quality problems (Haunert and 

Konyha 2001). 

Physical and chemical characteristics of estuarine bottom sediments affect the types of plants and 

animals that can live there. Substrate instability selects for the relatively few species that can 

colonize the fine sediments that dominate the bottom of the SLE (Schropp et al. 1994). 

Nutrient enrichment of estuarine waters can enhance eutrophication, accelerating phytoplankton 

production and biomass accumulation, which may lead to periodic hypoxia and anoxia (Livingston 

2001). Depletion of DO in bottom waters is typically caused by bacterial decomposition of 

accumulated phytoplankton and aquatic vegetation. Accelerated phytoplankton growth increases 

turbidity and light attenuation. These changes may drastically change the benthic community 

structure. 

Rudolph (1990) reported that the macroinvertebrate community at all stations in the North Fork of the 

St. Lucie River was composed of tolerant organisms indicative of a physically stressed environment. 

The report was based upon the types of organisms present, low diversity, and low Florida biotic index 

values. Schropp et al. (1994) reported that stress-tolerant opportunistic species dominated the North 

Fork benthos. Graves and Strom (1995) also reported that the North Fork SLR benthic 

macroinvertebrate assemblage was highly stressed, with a significantly lower diversity as compared 

to the more natural, historic South Fork of the St. Lucie River. The differences were attributed to 

periodic exposure of macroinvertebrates to a variety of pesticides in the North Fork, some at 

concentrations sufficient to cause documented fish kills. Statistical analysis of benthic 

macroinvertebrate data in the North Fork showed clear violations of state water quality standards 

based upon narrative biological criteria (Graves and Strom 1995). 

15 
Benthic Community Impairment Verification Study

Methods

Seven sites were selected in the St. Lucie Estuary and Indian River Lagoon from established water 

quality monitoring locations described in the Comprehensive South Florida Water Quality 

Monitoring Plan (Graves and Fike 2002; Figure 5). Boundaries were drawn midway between sites 

such that the study area was divided into seven subregions. Within each of these subregions, three 

sample sites were randomly chosen that met the following criteria: 

1. Water at least 3 feet deep on low tide, 

2. The site was not located in a dredged channel or basin. 

3. The site was at least 200 feet from shore (Figure 5). 

Figure 5: Benthic Macroinvertebrate Sampling Locations in the St. Lucie Estuary and the Indian 

River Lagoon. Core stations are circled in red; related sampling locations are given in yellow. 

During the week of February 11, 2002, a grab sample of benthic substrate was taken using a petite 

ponar dredge (surface area = 0.024 m2

) from each of the 21 designated sampling sites. The portion of 

the sediment retained on a Tyler series #30 (0.6-mm aperture) sieve was transferred into a sample 

bottle and preserved with a ten-percent buffered formalin solution containing rose-bengal dye. 

Temperature, dissolved oxygen, conductivity, and pH measurements were taken at top, mid, and 

bottom depths at the time of sampling with a Hydrolab® multi-parameter unit. Time of sampling, 

secchi depth, and the nature of the bottom substrate was also recorded. 

In the laboratory, samples were passed through a Tyler series # 30 sieve. Coarser materials were 

retained in a 2.0 aperture sieve and examined in a white enamel pan for organisms. Finer material 

was examined under a dissecting microscope until all macroinvertebrates were removed. The 

specimens were preserved in 80 percent ethanol containing glycerin. The organisms collected were 

16 
identified using standard marine identification references to the lowest practicable taxon. Examples 

of all identified species were retained as labeled voucher specimens, and all organisms were saved. 

Species abundance data was entered into the FDEP centralized biological database system (SBIO). 

Monthly water quality monitoring data (1991-2001) for stations used in this survey was obtained 

from the South Florida Water Management District DBHYDRO water quality database. Parameters 

monitored by SFWMD at these stations included: 

 

1. Chlorophyll 7. Color 

 2. Pheophytin 8. Depth 

 3. Dissolved oxygen 9. Salinity 

 4. pH 10. TSS 

5. Nutrients (all forms of N and P) 11. Turbidity 

 6. Temperature 

 

Mean water quality values were calculated and tabulated for each parameter at each of the seven 

water quality monitoring sites. These mean values served as input to the statistical correlation 

programs used in this study. The results of water quality monitoring for metals within the SLE were 

reviewed and summarized within this document. 

Multivariate statistical analysis were performed using Primer software developed by Plymouth 

Marine Laboratory specifically for use in evaluating marine biological data (Carr 1994; Clarke and 

Warwick 1994). Primer facilitates spatial analysis of relationships between environmental and 

biological data. Primer programs used in this evaluation included: 

1. CLUSTER: Performs hierarchical agglomerative clustering of data. 

2. DIVERSE: Calculates a suite of biological indices. 

3. SIMPER: Analyzes which species are most responsible for differences between sites by 

examining the contribution of each species to the Bray-Curtis dissimilarity between sample 

groups (Clarke 1993). 

4. NMDS: A non-metric multi-dimensional scaling (NMDS) program which produces an 

ordination of sites allowing analysis of similarities and between-site differences in biological 

data (Kruskal and Wish 1978). 

5. BIOENV: A nonparametric statistical program that selects environmental variables which 

best explain community patterns by maximizing a rank correlation between respective 

similarity matrices (Clarke and Ainsworth 1993). 

The Primer program DIVERSE was used to calculate the following metrics for each of the 21 

samples (sites): 

1. Species richness 

2. Number of individuals 

3. Margalef’s index (# species-1)/(log #individuals) 

4. Shannon-Weaver index of diversity. 

 5. Evenness 

The FDEP SBIO database system was used to obtain the composition of each biological sample 

according to functional feeding groups (shredders, filter-collectors, grazers, predators, deposit 

feeders). Species abundance data for each sample was analyzed using the NMDS program and a twodimensional plot of similarity was developed. The SIMPER program identified which species had 

17 
the greatest impact in determining differences between samples in the NMDS ordination. The 

BIOENV program was used to examine correlations of similarities in the distribution of

macroinvertebrate data with water quality data. This program suggests which water quality 

parameters had the highest probability of affecting the distribution of macroinvertebrate data. 

A Benthic Index of Biotic Integrity (IBI) was calculated for each of the 21 sample sites using 

methods developed by Van Dolah et al. (1999) specifically for estuarine waters of the southeastern 

USA. The following metrics were calculated from the original species abundance data to obtain an 

IBI score at each site: 

1. Mean abundance per 0.04 square meters 

2. Mean taxa per 0.04 square meters 

3. 100 – the percent of two dominant taxa 

4. The percent of sensitive taxa (i. e., Ampeliscidae, Haustoriidae, Tellinidae, Lucinidae, 

Hesionidae, Cirratulidae, Cyathura spp.). 

Scoring criteria for these four metrics were developed based on the distribution of values at nondegraded and degraded reference sites (Van Dolah et al. 1999). A score of 1 is given if the value falls 

within the lower 10th percentile of corresponding reference values. A score of 3 is given if the metric 

value obtained falls between the 10th and 50th percentile. A score of 5 is assigned if the value is 

greater than the 50th percentile value. Scores are assigned separately to each metric for each of four 

habitat types using the 10th and 50th percentile threshold values (Table 5). An IBI score is calculated 

by assigning a score for each metric and averaging the individual scores. An IBI score less than three 

suggests the presence of a degraded (e. g., a community for which some level of stress is apparent) 

benthic assemblage (Van Dolah et al. 1999). 

Table 5: Scoring guidelines for metrics in the IBI calculation (modified from Van Dolah et al. 1999). 

Oligohaline-Mesohaline All 

Latitudes 

Metric Polyhaline-Euryhaline Southern 

10th 50th 10th 50th 

Mean abundance 

per 0.04 m2 

53.5 93.0 112.5 301.0

Mean number taxa 

per 0.04 m2

7.0 8.5 26.5 35.0

100- percent of two 

dominant taxa 

9.62 25.45 52.89 61.19

Percent pollution 

sensitive taxa* 

0.61 5.04 0.71 2.22

*Ampeliscidae, Huastoriidae, Tellinidae, Lucinidae, Hesionidae, Cirratulidae, Cyathura spp. 

The Minitab Statistical Software package (Minitab 1997) was used to perform all between sample 

comparisons and correlations not otherwise noted. Nonparametric methods were used exclusively in 

this study. An ∝ = 0.05 level of significance was used in all statistical tests. 

18 
Results

A total of 145 unique macroinvertebrate taxa were identified in the twenty-one samples examined for 

this study (The raw macroinvertebrate data is available from the FDEP Southeast District Water 

Quality Section). The Primer NMDS non-metric multidimensional scaling program used to evaluate 

this biological data, based on similarities, showed two obvious groupings (Figure 6). Eight iterations 

were used in the program and an acceptable stress level (0.12) was obtained. This stress level 

suggests that the two-dimensional representation of the data corresponds to a good ordination, and 

that the interpretation of the results will not be misleading (similar samples are shown in close 

proximity and dissimilar sites are a greater distance apart). The IRL samples and lower SLE sites 

were grouped together, while the middle and upper estuary samples comprised a separate grouping. 

While the plots demonstrate similar assemblage characteristics within these groups, they also 

demonstrate the dissimilarity between samples from the IRL group and samples from the upper 

estuary group (represented by the relative distance in Figure 6 between the upper estuary and the IRL 

sampling sites). 

-2

-1

0

1

2

-1 -0.5 0 0.5 1 1.5

IRL 17C

IRL 17B

SE02A

SE02C SE02B

IRL25C

SEO1B

SE01C

IRL25A

SE01A

IRL25B SEO3B

HR1A

HR1B

SE03A

SE08B SE08C

HR1C

IRL17A

SE03C

SE08A

IRL and Lower SLE Stations

Upper SLE Stations

Figure 6: NMDS two-dimensional ordination of species abundance data for the SLE/IRL showing 

grouping of similar data. 

The program SIMPER was used to evaluate which species were most responsible for the differences 

between samples. The bivalve Mulinia lateralis and the polychaete Mediomastus californiensis were 

the two species most responsible for differences between samples (Table 6). Hydrobiidae gastropods, 

the polychaetes Polydora aggregata, Glycinde solitaria, and Streblospio benedicti, and the bivalve 

Mytilopsis leucophaeata also influenced the differences in species distribution between samples. The 

upper SLE samples contained relatively higher densities of Mulinia lateralis, Hydrobiidae, and 

Mytilopsis leucophaeata. The Indian River samples contained relatively higher densities of the 

polychaetes Mediomastus californiensis and Polydora aggregata. The polychaetes Glycinde solitaria

and Streblospio benedicti appeared to be more abundant in both the lower SLE and the Indian River 

sites. 

19 
Table 6: Species most responsible for separation of sites by species abundance data. 

Mulinia 

lateralis 

(29%) 

Mediomastus 

californiensis 

(17%) 

Hydrobiidae 

(9%) 

Polydora 

aggregata 

(5%) 

Mytilopsis 

leucophaeata 

(3.4%) 

Glycinde 

solitaria 

(2.9%) 

Streblospio 

benedicti 

(2.8%) 

Acteocina 

canaliculata 

(2.8%) 

HR1A 48 0 19 0 4 0 0 2

HR1B 20 0 11 0 3 1 0 1

HR1C 10 0 4 0 4 0 0 0

SE08A 4 0 1 0 0 0 0 0

SE08B 124 0 18 0 0 0 1 0

SE08C 128 0 93 0 96 0 0 0

SE03A 16 0 32 2 88 0 0 1

SE03B 0 0 0 0 0 0 1 4

SE03C 5 0 0 0 0 0 0 0

SE02B 0 1 0 0 0 0 0 0

SE02C 0 11 0 0 0 6 12 0

SEO2A 0 1 0 0 0 0 0 0

SE01A 0 8 0 0 0 14 1 0

SE01B 0 7 0 10 0 3 73 0

SE01C 0 47 0 46 0 0 83 0

IRL25A 7 31 0 76 0 5 10 4

IRL25B 0 39 1 21 0 2 0 5

IRL25C 0 43 1 4 0 4 3 3

IRL17A 0 2 0 1 0 0 0 0

IRL17B 5 38 0 28 0 1 4 3

IRL17C 0 17 1 10 0 4 0 2

In general, the Shannon-Weaver diversity index, species richness, and abundance were lower in 

samples from the upper and middle SLE (sampling areas SE03 and SE02) and increased in samples 

from downstream estuary sites (Table 7). The Mann-Whitney test (u = 45, p = 0.018) showed a 

significantly greater mean Shannon-Weaver diversity index value for pooled Indian River sample 

data when compared to pooled data from upper and mid-SLE samples. The Mann-Whitney test also 

revealed significantly greater mean species richness (u = 45, p = 0.0009) and evenness values (u = 58, 

p = 0.05) for the Indian River samples compared to samples from the SLE sites. Evenness, an 

inverse measure of dominance among species (more evenness equals less dominance), was 

significantly greater for the IRL sites compared to the SLE sites. 

Table 7: Metrics for describing benthic macroinvertebrate samples from the SLE. Indices calculated 

from data pooled by sampling area. 

Sampling 

Area 

Distance from 

Ocean Inlet (miles) 

Species 

Richness Abundance 

Margalef’s 

Index 

Shannon 

Weaver 

diversity Evenness 

IRL17 1.7 - 5.8 66 387 10.9 3.24 0.773 

IRL25 5.8 - 9.5 74 662 11.2 3.15 0.732 

SE01 1.5 – 3.8 58 2150 7.43 1.89 0.464 

SE02 3.8 – 6.6 30 95 6.37 2.97 0.872 

SE03 6.6 – 9.5 19 262 3.23 1.72 0.584 

SE08 9.5 – 11.5 14 506 2.09 1.38 0.521 

HR1 10.1 – 13.2 15 154 2.78 1.65 0.608 

Classifying species into functional feeding groups is sometimes used to help evaluate environmental 

conditions. In this study, the filter/suspension-feeders functional feeding group made up a 

significantly (Mann-Whitney test, p=0.0157) higher proportion of the total species abundance in 

samples from upper SLE sites, while the predator/carnivore feeding (Mann-Whitney test, p=0.03) and 

20 
subsurface-gatherer/deposit feeder (Mann-Whitney, p=0.009) groups were significantly more 

prevalent at the Indian River sites (Table 8). No additional significant differences based on feeding 

groups were found. 

Table 8: Functional feeding groups for each site.

Florida 

Index 

species 

% 

Brow/

graz 

% Filt/ 

susp 

% Epi 

gath/ 

dep 

% 

Paras

% Plnt 

piercer 

% 

Pred 

% 

Scav 

% Peri

Scrap 

% 

Shred 

(fw) 

% 

Subgath

/dep % Unknown 

HR1A 0.0 0.6 65.5 24.1 0.0 0.0 4.6 0.6 2.3 0.0 0.0 2.3

HR1B 0.0 0.0 64.6 28.1 0.0 0.0 4.9 0.0 2.4 0.0 0.0 0.0

HR1C 0.0 0.0 57.7 17.3 0.0 0.0 17.3 0.0 0.0 0.0 0.0 7.7

SE08A 0.0 0.0 66.7 16.7 0.0 0.0 16.7 0.0 0.0 0.0 0.0 0.0

SE08B 0.0 0.0 80.8 12.7 0.0 0.0 3.3 0.0 2.6 0.7 0.0 0.0

SE08C 0.0 0.6 70.2 27.5 0.0 0.0 0.6 0.6 0.3 0.3 0.0 0.0

SE03A 0.0 0.0 83.9 14.5 0.0 0.0 0.8 0.0 0.4 0.0 0.0 0.4

SE03B 0.0 3.6 3.6 7.1 0.0 0.0 42.9 3.6 28.6 3.6 0.0 7.1

SE03C 0.0 0.0 83.3 0.0 0.0 0.0 0.0 0.0 16.7 0.0 0.0 0.0

SEO2A 0.0 0.0 0.0 0.0 0.0 0.0 20.0 0.0 0.0 0.0 80.0 0.0

SE02B 0.0 29.0 13.2 7.9 0.0 0.0 15.8 29.0 0.0 0.0 5.3 0.0

SE02C 0.0 1.4 24.7 10.6 0.0 0.0 26.8 5.6 0.0 0.0 28.2 2.8

SE01A 0.0 0.7 3.7 1.0 0.0 0.0 10.7 0.7 0.0 0.0 83.3 0.0

SE01B 0.0 27.1 20.8 13.9 0.0 0.0 4.3 28.1 1.0 0.0 2.6 2.3

SE01C 0.0 7.5 8.3 4.0 0.0 0.0 2.4 8.2 0.3 0.0 3.1 66.3

IRL25A 0.0 0.6 20.8 17.4 0.0 0.0 27.2 1.2 3.1 0.0 27.7 2.1

IRL25B 0.0 0.5 17.7 7.6 0.0 0.0 31.1 0.5 2.9 0.0 35.8 3.9

IRL25C 0.0 0.8 11.8 11.5 0.0 0.0 14.2 1.2 3.4 0.0 51.7 5.5

IRL17A 0.0 2.8 30.6 2.8 0.0 0.0 27.8 2.8 0.0 0.0 11.1 22.2

IRL17B 1.0 0.5 25.4 9.7 0.0 0.0 26.6 1.8 4.3 0.0 21.9 10.0

IRL17C 1.0 0.0 31.6 5.9 0.0 0.0 37.4 0.4 1.5 0.0 17.7 5.6

21 
The Benthic Index of Biotic Integrity (IBI; Van Dolah et al. 1999) calculated from this 

macroinvertebrate data showed a higher incidence of degraded sites located in the upper and middle 

SLE (Table 9). Five of the nine (56%) SLE stations located upstream of the Roosevelt (U. S. 

Highway 1) Bridge were classified as degraded (mean score less than three) using the IBI 

methodology. Three of the six SLE sites (50%) located in the middle to lower estuary (from the SLE 

mouth to the Roosevelt Bridge) were classified as degraded, and no sites (0%) in the Indian River 

Lagoon were classified as degraded. 

Table 9: Estuarine Benthic Index of Biotic Integrity (IBI) scores for sites sampled in this study. 

Site Classification 

Mean 

Abund

* Score 

Mean 

Taxa* Score 

100 – 

% 2 Dom

Scor

e 

% 

Sensitive** Score 

Total

Score*** 

Mean 

Scor

e 

HR1 A Mesohaline 145.29 5 10 5 23 3 0 1 14 3.5 

HR1 B Mesohaline 68.47 3 8 3 24.3 3 0 1 10 2.5

HR1 C Mesohaline 43.42 1 9 5 46.1 5 0 1 12 3

SE08 

A Mesohaline 10.02 1 3 1 16.5 3 0 1 6 1.5

SE08 

B Mesohaline 257.18 5 6 1 7.8 1 0 1 8 2

SE08 

C Mesohaline 577.82 5 12 5 35.3 5 0 1 16 4

SE03 

A Mesohaline 404.14 5 11 5 25.6 5 0 1 16 4

SE03 

B Mesohaline 23.38 1 8 3 50 5 0 1 10 2.5

SE03 

C Mesohaline 10.02 1 2 1 0 1 0 1 4 1

SE02 

A Mesohaline 8.35 1 4 1 40 5 0 1 8 2

SE02 

B Mesohaline 31.73 1 6 1 57.9 5 0 1 8 2

SE02 

C Mesohaline 118.57 5 22 5 67.5 5 11.26 5 20 5

SE01 

A 

Polyhaline - 

South 250.5 3 11 1 12.7 1 1.3 3 8 2

SE01 

B 

Polyhaline - 

South 506.01 5 21 1 33.7 1 42.6 5 12 3

SE01 

C 

Polyhaline - 

South 

2833.9

9 5 36 5 22.2 1 12.4 5 16 4

IRL 17 

A 

Polyhaline - 

South 30.06 1 43 5 66.7 5 16.6 5 16 4

IRL 17 

B 

Polyhaline - 

South 389.11 5 32 3 71.7 5 2.5 5 18 4.5

IRL 17 

C 

Polyhaline - 

South 227.12 3 34 3 66.2 5 2.2 3 14 3.5

IRL 25 

A 

Polyhaline - 

South 552.77 5 12 1 62.8 5 0 1 12 3

IRL 25 

B 

Polyhaline - 

South 340.68 5 46 5 42.6 1 0.5 1 12 3

IRL 25 

C 

Polyhaline - 

South 212.09 3 31 3 58.3 3 3.1 5 14 3.5

*Per 0.04m2 

**Sensitive taxa: Ampeliscidae, Haustoriidae, Tellinidae, Lucinidae, Hesionidae, Cirratulidae, Cyathura spp. 

***Total score = mean abundance score + mean taxa score + (100 - % 2 dominant species) score + % sensitive score. 

A summary of water quality data from the seven SFWMD monitoring stations used in this study is 

given in Table 10. Stations HR1, SE08, SE03, and SE02 are classified as mesohaline (salinity greater 

than 5 and less than 18 ppt) using mean salinity values. Sites SE01, IRL17, and IRL25 are classified 

as polyhaline (salinity greater than 18 ppt and less than 30 ppt). Mean chlorophyll-a concentrations 

were higher for sites that were further upstream in the estuary. Color was significantly greater for the 

SLE sites compared to the IRL sites. Mean total suspended solids (TSS) values were higher for the 

IRL than for the SLE stations. Mean nutrient concentrations were higher for sites that were further 

upstream in the estuary. Review of water quality monitoring data for metals in the SLE showed that 

the North Fork of the SLE (WBID 3194B) had 7 water quality criteria violations out of 13 known 

samples taken since 1996. The South Fork of the SLE (WBID 3210) had 4 violations out of 15 

samples collected since 1996. 

22 
Table 10: Mean water quality values for SFWMD monitoring stations used in this study. SAL DEP CHLA COL DO TSS TUR NH4 NO2 NO3 TN OP TP 

HR1 9.5 3.2 13.1 69.9 6.6 8.6 4.3 0.06 0.01 0.08 1.2

2 0.17 0.21

SE 08 7.1 1.0 11.6 69.7 6.7 

16.

5 11.0 0.06 0.01 0.11

1.2

2 0.13 0.19

SE 03 12.4 6.2 11.4 64.2 6.1 14.9 7.3 0.07 0.01 0.09 1.10 0.14 0.18

SE 02 

16.

7 3.2 9.3 52.6 6.2

15.

9 6.1 0.06 0.01 0.07

0.9

9 0.11 0.15

SE 01 23.7 5.0 8.0 41.1 6.2 19.2 6.1 0.07 0.01 0.06 0.88 0.08 0.12

IRL17 30.4 2.0 5.3 15.9 6.3 31.1 6.1 0.01 0.00 0.01 0.74 0.03 0.06

IRL25 

28.

5 1.2 7.2 13.9 7.2

27.

2 7.2 0.01 0.00 0.00

0.8

3 0.02 0.06

Substrate types were subjectively described during sampling events. Substrates in the upper and mid 

SLE were muck while IRL sites were primarily sandy (Table 11). 

Table 11: Sediment types at study sample sites.

Sample Site Substrate Classification 

HR1A Muck

HR1B Muck

HR1C Muck

SE08A Muck

SE08B Muck w/shellhash

SE08C Muck w/shellhash and detritus 

SE03A Muck w/shellhash

SE03B Muck

SE03C Muck

SE02A Muck w/shellhash

SE02B Muck

SE02C Muddy Sand

SE01A Clay/Muck

SE01B Muddy Sand

SE01C Sand w/detritus and shellhash 

IRL17A Sand

IRL17B Muddy Sand

IRL17C Muddy Sand w/shellhash 

IRL25A Muddy Sand

IRL25B Mud

IRL25C Muddy Sand

 

Results from the rank-correlation statistical program BIOENV indicated that the water quality 

parameters with the most significant correlations to macroinvertebrate community data distribution 

were color, TSS, and Total Phosphorous (TP). The differences in mean water quality values for these 

parameters correlated with differences in the pooled biological data (Figure 7). 

23 
MDS of Pooled Biological Data

SE08 SE03 HR1

SE02 SE01 IRL17 IRL25

Mean TSS Values at Study Sites

16 15 8

16 19

31

27

Mean Total Phophorus Values for Sample Sites

0.188 0.182 0.208

0.148 0.119 0.061 0.063

Mean Color Values for Sample Stations

70 64 70

53 41 16 14

Figure 7: Correlation of water quality data with biological data showing similarities in grouped 

stations for the three most highly correlated parameters. Sites with similar biological data are circled. 

Succeeding graphs show mean water quality values for those sites. Sites that were similar 

biologically were also similar for these mean water quality values. 

24 
Discussion

In this study, nonparametric multivariate statistical analysis has shown that benthic macroinvertebrate 

community samples taken from the Indian River Lagoon were distinctly different from the benthic 

samples taken from the upper and middle St. Lucie Estuary. Many natural and anthropogenic factors 

likely played a role in producing these differences between sites. Salinity regime, substrate 

characteristics, flow regime, tidal range, depth and vegetation are natural factors that may partially 

explain the differences in the community structure. Water quality, sediment toxicity, dredging, and 

the alteration of flow and salinity regime by human activities are also likely to influence the 

differences between sites. The upper and middle SLE serve as a settling basin for suspended matter 

transported downstream through the canals and streams draining agricultural and urban areas in the 

watershed. Its close proximity to agricultural and urban pollutant sources, greater residence time, and 

lesser tidal influence would seem to make the SLE more susceptible to the influences of suspended 

and dissolved pollutants such as nutrients than the IRL. The IRL in the area of the SLE receives no 

direct discharges from agricultural canals, has greater ocean flushing, and is far enough downstream

of the upper SLE that much the sediment-based pollutant load to the SLE has already been captured. 

Thus, pollutant impacts to the IRL are likely to be not as severe as impacts to the SLE. 

Macroinvertebrate communities (as biological indicators of ecosystem health) may be useful as good 

integrators of total system stress (Kennish 1999). Multivariate analysis of the benthic 

macroinvertebrate samples collected in this study differentiated between samples collected from the 

SLE and those collected from IRL (Figure 6). These differences are substantially attributable to 

impaired water quality and habitat. It has been shown that in general, species richness, abundance 

and the Shannon-Weaver Index of Diversity decrease at pollution-impacted sites (Barbour et al. 

1996). Significantly lower species richness and Shannon-Weaver diversity index values were seen at 

the upper and mid-SLE sites when compared to the IRL. Species evenness (equitability) has been 

shown to decrease with increasing pollution impact (USEPA 1990). The SLE sites had significantly 

lower evenness and diversity index values than the IRL sites. 

The use of functional feeding groups has been discounted for use as biological indices in 

bioassessment due to highly variable responses (Barbour et al. 1996; Rawer-Jost et al. 2000). For this 

reason inference regarding the relationships of feeding groups among sites will not be attempted in 

this study. 

Median total phosphorus values for the SLE were more than twice the statewide estuarine median 

(Friedemann and Hand 1989; FDEP 2001), while all forms of nitrogen were elevated above statewide 

estuarine medians. The IRL medians for nitrogen and phosphorus were below statewide medians 

(FDEP 2001). Mean TP and TN values for the C23, C24 and C44 canals which discharge into the 

SLE are much greater than applicable USEPA nutrient guidelines for streams (USEPA 2002; Table 

12). These canals can be shown to be impaired for nutrients under the IWR using Chla as an 

indicator (FDEP 2002b). The primary inflows into the SLE are these nutrient-impaired waters 

(SFWMD 2001). 

25 
Table 12: Mean nutrient and Chla concentrations in canals discharging to the SLE (FDEP 

unpublished data 2002b) 

Waterbody Chla TP TN 

C24 48.29 0.27 1.35

C23 54.29 0.36 1.46

C44 21.0 0.31 1.32

USEPA Guidance 0.04 0.90

Florida IWR 20.00 

Primer’s BIOENV program was used to objectively evaluate relationships between water quality and 

macroinvertebrate data. This multivariate analysis implicated TP concentration as a causal factor 

linking observed differences in biological data to water quality. Elevated levels of TP are associated 

with nutrient enrichment, and the upper and middle SLE sites had significantly higher concentrations 

of TP than the IRL sites. 

The waterbody segments which make up the upper SLE were found to have a high proportion of 

copper criteria violations. The rate at which violations occur will most likely require the upper 

estuary to be listed as impaired due to copper concentrations under the IWR once the data sufficiency 

requirements have been met. High concentrations of copper in the water column and sediments may 

have an affect on the benthic and aquatic community, and may be a factor reflected in low IBI scores 

and differences between the upper SLE and the IRL. The design of this study did not allow the 

correlation of copper data to biological data. 

Fish and mammal disease events have been correlated with harmful algal blooms along the Atlantic 

Coast. Intense blooms have now been associated with eutrophic conditions, and especially with high 

nitrogen concentrations. Though harmful algal species are commonly present in low abundance in 

coastal estuaries, it has been hypothesized that nutrient loadings may play a role in promoting a shift 

in the phytoplankton community, producing a harmful algal bloom. Mean concentrations of TP and 

TKN in the upper SLE are at or above concentrations which were correlated to fish and invertebrate 

effects due to HAB’s in the Neuse River (Burkholder and Glasgow 1997). The fish lesion event, 

which occurred in the SLE in 1998, was associated with large freshwater releases from drainage 

canals. The waters of the drainage canals discharging into the SLE are especially high in nutrients 

(Table 12). Though one-time sampling by FMRI found low concentrations of harmful algal species 

in the SLE and IRL, current knowledge suggests a real potential for harmful algal blooms is present 

in the SLE due to high nutrient loadings. 

Studies have found the presence of submerged aquatic vegetation within the SLE has been drastically 

reduced over the past 50 years. Nutrient loadings promote algal blooms that decrease water clarity 

and decrease the extent of the photic zone, limiting light penetration, and thus the depth at which 

seagrasses can survive. 

Substrates sampled from the upper and middle SLE sites were all muck-based, while the IRL 

substrates were primarily sandy with some muddy component. The presence of thick ooze at all sites 

is itself an indicator of impact. Historical accounts document the SLE as naturally having a sandysediment bottom (Schropp et al. 1994). Any role which substrate type plays in differentiating the 

biological samples in this study also supports the idea that the differences are due to anthropogenic 

impact. 

26 
The Benthic Index of Biological Integrity (IBI) as presented by Van Dolah et al. (1999) was derived 

especially for estuarine systems of the southeastern United States. Benthic data from the St. Lucie 

Estuary was used in development of this index. The IBI is a multimetric index using the metrics 

found to be most sensitive and consistent for identifying impacted estuarine sites. This index was 

developed using a large macroinvertebrate dataset collected from southeastern United States estuarine 

stations, and the development of the index was based on a multivariate analysis of site water quality, 

sediment quality, and benthic biotic assemblages. It used known degraded and non-degraded sites 

(with verification and an analysis of Type I and II error rates). Thus this index may serve as the 

single best biological tool available for assessing impairment of sites within the SLE or IRL. The IBI 

analyses performed for this study showed a majority of the upper and middle SLE sites should be 

classified as degraded, while no IRL sites are classified as degraded. When this information is 

combined with the multidimensional scaling ordination results and water quality data, a case can be 

made for the inference that differences in the shown groupings may likely be due to pollution impacts 

and habitat degradation. The IRL samples were grouped separately from the upper and middle-SLE 

samples, and water quality analyses suggest that the IRL is a less impacted system compared to the 

SLE. This is not to imply that the IRL is pristine; it has been shown to have suffered some water 

quality impairment (Sigua et al. 2000). Results obtained in this study show that half of the IRL 

samples had IBI scores only slightly above “degraded”. Any inference in this paper that the IRL is 

not affected by impairment is not intended. However, it can be inferred that the SLE shows a 

significantly greater level of impact than the Indian River Lagoon. 

Conclusions

This assessment of the benthic biological community in the SLE indicates that the macroinvertebrate 

community is stressed and does not represent the assemblage that a healthy ecosystem should 

support. The new data presented herein corroborates both the set of pre-existing data and the findings 

of other researchers who have studied of the St. Lucie Estuary. The loss of general ecosystem

function, as evidenced by drastically diminished distribution of seagrass and oysters, fish community 

imbalance and lesions, sediment and water column contamination by heavy metals (especially 

copper) and pesticides, excessive algal blooms, and failure to support a healthy and well-balanced 

benthic macroinvertebrate community, is proof that the St. Lucie Estuary fully satisfies the legal 

criteria of an impaired waterbody as stipulated in 62-303.450(2) FAC. Using the weight of evidence 

argument presented in this document, the St. Lucie Estuary (WBIDs 3210, 3194B, 3193) should be 

classified as impaired due to excessive nutrient inputs which have resulted in an imbalance in flora 

and fauna, a violation of water quality criteria per 62-302 FAC. Both phosphorus and nitrogen 

concentrations are high relative to other estuarine systems and relative to suggested guidelines. 

Copper concentrations in the water column of the estuary have exceeded applicable Class III marine 

water quality standard in 67% of samples collected and analyzed utilizing the MIBK copper protocol. 

The SLE is a complex estuarine ecosystem adversely impacted by a variety of human related factors. 

As a result, the impairment of this severely degraded system is readily apparent from an examination 

of any of a number of key ecological factors. Accordingly, the SLE should be added to the list of 

waterbodies that are verified as impaired so that a TMDL plan can be formulated and other critical 

restoration efforts can proceed unimpeded. 

27 
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