FINAL REPORT

Southwest Florida Water Management District Contract Number 06C00000079 Project B678 

Water quality characteristics of the nearshore Gulf coast waters adjacent to 

Citrus, Hernando and Levy Counties 

Project COAST 1997–2008 

Prepared by 

Charles A. Jacoby, Thomas K. Frazer and Darlene D. Saindon 

Program in Fisheries and Aquatic Sciences 

School of Forest Resources and Conservation 

University of Florida 

7922 NW 71st Street 

Gainesville, Florida 32653 

Submitted to 

Southwest Florida Water Management District 

2379 Broad Street 

Brooksville, Florida 34604–6899 

August 2009 

Final Report: Contract Number 06C00000079 Project B678 

Water Quality Characteristics of the Nearshore Gulf Coast Waters Adjacent to Citrus, Hernando and Levy Counties

EXECUTIVE SUMMARY Further examination of data revealed spatial 

patterns in exposure to fresh water, as indicated 

by salinity and concentrations of total nitrogen, 

total phosphorus and chlorophyll. In combination, 

these results guided pooling of data from stations 

within systems before analyses of trends. 

Florida’s coastal waters have become vulnerable 

to problems associated with increased organic 

matter. These increases arise from higher nutrient 

loads created by a larger human population and 

changes in land use. Impacts from such 

eutrophication could include algal blooms; 

lowered oxygen levels; damage to habitats; and 

loss of scallops, shrimps, blue crabs, myriad 

fishes and other ecologically and economically

important animals. In recognition of this 

threat, broad-scale sampling of water quality

along the coast of Citrus, Hernando and Levy

Counties began in 1997 (Project COAST, see 

Frazer et al. 1998). This report summarizes key

results from sampling through 2008. 

Trends were examined by correlating indicators 

with time. Total nitrogen concentrations 

increased significantly in the Withlacoochee, 

Crystal and Homosassa systems, especially

during wet months. Significant increases in total 

phosphorus concentrations were not as 

widespread. As expected, chlorophyll 

concentrations in these systems increased in 

response to increased nutrients. In contrast, 

decreases in nutrient and chlorophyll 

concentrations were prevalent in the 

Chassahowitzka and Weeki Wachee systems. 

Further insights into causal relationships await 

collation of data on human activities and 

completion of diagnostic studies of key biological 

and biogeochemical processes. 

In samples taken off Citrus, Hernando and Levy

Counties, chlorophyll concentrations increased as 

concentrations of total nitrogen and total 

phosphorus increased, with a stronger 

relationship to total phosphorus. Thus, 

concentrations of total nitrogen, total phosphorus 

and chlorophyll represent three valuable 

indicators of eutrophication. 

Overall, baseline sampling has established 

patterns in water quality off the coasts of Citrus, 

Hernando and Levy Counties. Indications of 

increasing nutrient concentrations raise concerns 

about eutrophication. Effective and efficient 

management of this threat will arise from

additional analyses and data that enhance insights 

into spatial and temporal changes and trends. For 

example, an understanding of the direction, 

magnitude and variability of links among water 

quality parameters and key forcing factors can 

guide the choice of targets for management 

actions designed to protect or restore coastal 

systems. Furthermore, an understanding of spatial 

coherence can foster optimal allocation of 

sampling effort in monitoring programs. In some

cases, the necessary level of understanding will 

require investment in collection of data that 

complements the existing baseline. Ultimately,

long-term baseline data combined with targeted 

diagnostic studies will guide the design of 

monitoring that continually evaluates and adapts 

management actions to ensure healthy coastal 

systems that deliver value to Citrus, Hernando 

and Levy Counties. 

Increased rainfall during the 1998 El Niño event 

created short-term changes in total nitrogen, total 

phosphorus, chlorophyll, and water clarity across 

all systems. However, the systems recovered from

this natural disturbance within 6–8 months. 

Another set of analyses indicated that rainfall also 

affected concentrations of nitrogen, phosphorus 

and chlorophyll at the level of months. 

Concentrations differed among wet months and 

dry months in the Homosassa and 

Chassahowitzka systems. This pattern was most 

likely related to increased rainfall during wet 

months, which resulted in an increased delivery

of fresh water containing nutrients. Less obvious 

wet–dry temporal patterns in the Withlacoochee, 

Crystal and Weeki Wachee systems probably

reflected differences in hydrological 

characteristics. Analysis of total rainfall data 

identified groups of months with relatively

consistent rainfall, which generated coherent time 

periods for use in detecting trends. 

1 
Final Report: Contract Number 06C00000079 Project B678 

Water Quality Characteristics of the Nearshore Gulf Coast Waters Adjacent to Citrus, Hernando and Levy Counties

INTRODUCTION In addition to using nutrients more efficiently, 

both epiphytic microalgae and phytoplankton 

require less light than slow-growing, benthic 

macrophytes, like seagrasses (Duarte 1995). 

Studies from around the world indicate that 

increased nutrient loading to estuarine systems 

fosters replacement of seagrasses with blooms of 

fast-growing macroalgae and phytoplankton 

(Duarte 1995, Valiela et al. 1997). Moreover, 

available information suggests that damaged 

seagrass beds require years to centuries to recover 

(Duarte 1995). 

In several springs and rivers along Florida’s 

Springs Coast, nutrient concentrations have 

increased due to agricultural practices and urban 

development within the relevant watersheds 

(Jones et al. 1997, Southwest Florida Water 

Management District 2001). When loads to these 

riverine systems exceed internal rates of 

assimilation or transformation, the rivers 

discharge surplus nutrients, especially nitrate, into 

the Gulf of Mexico (Frazer et al. 1998, Frazer et 

al. 2001a). This anthropogenic nutrient 

enrichment can fuel increased plant production 

resulting in an accumulation of organic matter, or 

eutrophication. 

Florida’s coastal systems, including Apalachee 

Bay, Tampa Bay and Florida Bay, have suffered 

substantial losses of seagrass, with declines often 

attributed to changes driven by increased nutrient 

loads (Hale et al. 2004, Handley et al. 2007). 

Along Florida’s Gulf coast, Hale et al. (2004) 

reported large-scale shifts in the depth 

distribution of turtle grass (Thalassia testudinum) 

and shoal grass (Halodule wrightii), as well as 

areas of seagrass loss near the mouths of rivers. 

They suggested that increased nutrient loading to 

coastal rivers could underlie these changes. 

In most nearshore waters, detrimental effects 

follow nutrient enrichment and eutrophication 

(Duarte 1995, Valiela et al. 1997). Seagrass beds, 

like those found off the Springs Coast, are 

particularly vulnerable to such effects. Damage to 

seagrasses raises broader concerns about the 

overall health and ecological integrity of 

Florida’s estuarine and nearshore systems (Frazer 

and Hale 2001, Mattson et al. 2007). For 

example, seagrass beds provide refuge and a 

habitat for foraging to ecologically and 

economically important animals, such as scallops, 

shrimps, blue crabs, myriad fishes, manatees and 

sea turtles (Killam et al. 1992). 

The potential negative consequences from

increased nutrient delivery to estuarine and 

coastal waters along Florida’s Springs Coast are 

recognized. In response, broad-scale sampling of 

water quality began in 1997 (Project COAST). 

The planned, long-term baseline will help water 

resource managers i) differentiate natural 

variation in water quality from persistent declines 

that arise from human activities and threaten to 

degrade coastal systems, ii) identify targets for 

diagnostic studies that optimize management 

actions, and iii) design effective and efficient 

long-term monitoring to document the success of 

management and guide responses to unforeseen 

circumstances. Consistent with these objectives, 

we provide updated results that illustrate changes 

and trends in water quality and point to analyses 

and data required to manage the risk of 

eutrophication effectively. In this report, we focus 

on links to rainfall, a driver of coastal water 

quality and an influence to address in efforts to 

differentiate natural variation and anthropogenic 

impacts. 

Seagrasses and other plants require nutrients, 

especially nitrogen and phosphorus, to support 

their growth. However, nutrient enrichment often 

results in damage to seagrasses. For example, 

seagrasses die if phytoplankton, epiphytic 

microalgae and/or benthic macroalgae shade them

too much. These fast-growing algae generally

take up nutrients more efficiently, especially in 

nutrient enriched environments (Duarte 1995). 

Although seagrasses, phytoplankton, epiphytic 

microalgae and macroalgae assimilate nutrients 

from the water column, the various types of algae 

can outcompete seagrasses for several reasons. 

For example, phytoplankton and epiphytes take 

up nutrients more rapidly, and they have greater 

contact with water and the nutrients it contains 

because they are located in the water column or 

on a host plant (Williams and Ruckelhaus 1993). 

2 
Final Report: Contract Number 06C00000079 Project B678 

Water Quality Characteristics of the Nearshore Gulf Coast Waters Adjacent to Citrus, Hernando and Levy Counties

METHODS

Earlier reports detailed sampling protocols, 

analytical procedures and characteristics of the 

five coastal rivers and their associated estuaries, 

the Weeki Wachee, Chassahowitzka, Homosassa, 

Crystal and Withlacoochee below the Inglis Dam

(Frazer et al. 1998, 2001b, 2002, 2003, 2004 

and 2006; Jacoby et al. 2008). In general, 

monthly samples were collected at 10 fixed 

stations arrayed in each of five systems along the 

Springs Coast since 1997 (Figure 1, Appendix 1). 

Water temperatures, salinities, dissolved oxygen 

concentrations and Secchi depths were recorded 

at each sampling station during each sampling 

event. Light attenuation was measured from May

1999. In addition, water samples were analyzed 

according to procedures documented in the 

program’s Quality Assurance Plan 

(CompQAP#91-01-57G) to yield concentrations 

of total nitrogen, total phosphorus, chlorophyll, 

and from May 1999, measurements of color. The 

Southwest Florida Water Management District 

has received all data in electronic format 

comprising: system names; station types (riverine 

or estuarine); station numbers; years, months, 

days, and seasons of sampling; bottom depths; 

Secchi depths; temperatures; salinities; 

concentrations of dissolved oxygen, total 

nitrogen, total phosphorus, and chlorophyll; 

measures of color; and average light attenuation 

coefficients. This report focuses on estuarine and 

coastal stations. 

This report elucidates broad-scale patterns related 

to the project’s goals. Analyses involved annual 

or monthly means, standard statistical procedures, 

and in some cases, transformations to improve 

normality and homogeneity of variance. 

Figure 1. Study area and sampling stations. 

3 
Final Report: Contract Number 06C00000079 Project B678 

Water Quality Characteristics of the Nearshore Gulf Coast Waters Adjacent to Citrus, Hernando and Levy Counties

KEY CHANGES AND TRENDS Ongoing monitoring should detect short-term

changes in water quality, or events, and 

distinguish these changes from long-term trends. 

Across all stations in all systems, mean 

concentrations of total nitrogen, total phosphorus 

and chlorophyll increased in response to an El 

Niño event, which generated significant rainfall 

during 1998 (Figures 4–6). These changes 

decreased water clarity as shown by a reduction 

in the proportion of times a Secchi disc remained 

visible throughout the water column (Figure 7). 

The systems recovered, with “typical” values 

recorded after 6–8 months. Overall, these results 

illustrated how natural variation can confound 

identification of anthropogenic impacts, and they

pointed to the value of sustained sampling. 

Chlorophyll concentrations, proxies for increased 

phytoplankton biomass, represent valuable 

indicators of increased organic matter or 

eutrophication. Chlorophyll concentrations 

remain correlated with concentrations of total 

phosphorus and total nitrogen (Figures 2 and 3). 

The stronger empirical relationship between 

chlorophyll and total phosphorus pointed to 

phosphorus as a major driver of changes in 

chlorophyll. In combination, the relationships 

supported a focus on these three parameters. 

Correlation coefficient = 0.84

p < 0.001

-1.0

0.0

1.0

2.0

0.0 0.5 1.0 1.5 2.0 2.5

log10[Chlorophyll (μg L-1)]

Log10[Total phosphorus (μgL-1)]

0

200

400

600

800

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Calendar year

Mean total nitrogen (μg L-1)

Figure 2. Relationship between log10-transformed 

monthly mean chlorophyll and total phosphorus 

concentrations from all estuarine systems. 

Figure 4. Annual mean total nitrogen concentrations 

across the five estuarine systems. 

Correlation coefficient = 0.46

p < 0.001

-1.0

0.0

1.0

2.0

2.0 2.5 3.0 3.5

log10[Chlorophyll (μg L-1)]

Log10[Total nitrogen (μgL-1)]

0

5

10

15

20

25

30

35

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Calendar year

Mean total phosphorus (μg L-1)

Figure 3. Relationship between log10-transformed 

monthly mean chlorophyll and total nitrogen 

concentrations from all estuarine systems. 

Figure 5. Annual mean total phosphorus 

concentrations across the five estuarine systems. 

4 
Final Report: Contract Number 06C00000079 Project B678 

Water Quality Characteristics of the Nearshore Gulf Coast Waters Adjacent to Citrus, Hernando and Levy Counties

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Stress = 0.1670

0

2

4

6

8

10

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Calendar year

Mean chlorophyll (μg L-1)

Figure 8. Ordination for the Withlacoochee 

comprehensive watershed management basin. 

black symbols = wet months (June–September); gray

symbols = months of variable rainfall (January, 

February, March and December); white symbols = dry 

months (April, May, October and November) 

Figure 6. Annual mean chlorophyll

concentrations across the five estuarine systems. 

0.0

0.2

0.4

0.6

0.8

1.0

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Calendar year

Secchi readings recorded as Bottom

(proportion)

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Stress = 0.1531

Figure 7. Annual means for the proportion of 

sampling events where the Secchi disk was visible at 

the bottom across the five estuarine systems. 

Figure 9. Ordination for the Springs Coast

comprehensive watershed management basin. 

black symbols = wet months (June–September); gray

symbols = months of variable rainfall (January, 

February, March and December); white symbols = dry 

months (April, May, October and November) 

Less dramatic variation in rainfall occurs among 

months, yet such variation could obscure trends. 

Two-dimensional ordinations based on total 

monthly rainfall between 1997 and 2008 for the 

Withlacoochee and Springs Coast comprehensive 

watershed management basins confirmed wellknown patterns in rainfall (Figures 8 and 9). 

Higher rainfall characterized June, July, August 

and September, wet months. The least rain fell in 

April, May, October and November, dry months. 

The transitional months, January, February

and March had variable rainfall. December 

differed from other months, probably due to high 

rainfall in 1997 and 2002 (Withlacoochee 11.92 

and 9.81 inches and Springs Coast 11.04 and 

10.19 inches). In further analyses, December was 

considered a transitional month. 

Multivariate ordinations provided evidence that 

variation in rainfall influenced concentrations of 

total nitrogen, total phosphorus and chlorophyll 

in a manner that will affect evaluations of trends 

(Figures 10–14). Stress values indicated 

reasonable representations in three dimensions, 

with axes 1 and 2 shown. Sampling events with 

similar concentrations of total nitrogen, total 

phosphorus and chlorophyll yielded clusters of 

points in the ordinations. Black symbols 

representing wet months (June–September) 

tended to separate from other months in 

ordinations for the Homosassa and 

5 
Final Report: Contract Number 06C00000079 Project B678 

Water Quality Characteristics of the Nearshore Gulf Coast Waters Adjacent to Citrus, Hernando and Levy Counties

Chassahowitzka systems. This clustering 

suggested consistency in responses to higher 

rainfall. Weaker clustering in ordinations for the 

other three systems probably reflected controlled 

flow past the Inglis Dam on the Withlacoochee 

River and differences in sizes, hydroperiods, and 

other hydrological characteristics of watersheds. 

Given these results, separate analyses examined 

trends for wet, transitional and dry months. 

-3

-2

-1

0

1

2

3

-3 -2 -1 0123

Wet months Transition months Dry months

Stress = 0.1607

-3

-2

-1

0

1

2

3

-3 -2 -1 0123

Wet months Transition months Dry months

Stress = 0.1610

Figure 12. Ordination for the Weeki Wachee system. 

black symbols = wet months (June–September); gray

symbols = months of variable rainfall (January, 

February, March and December); white symbols = dry 

months (April, May, October and November) 

Figure 10. Ordination for the Homosassa system. 

black symbols = wet months (June–September); gray

symbols = months of variable rainfall (January, 

February, March and December); white symbols = dry 

months (April, May, October and November) 

-3

-2

-1

0

1

2

3

-3 -2 -1 0123

Wet months Transition months Dry months

Stress = 0.1514

-3

-2

-1

0

1

2

3

-3 -2 -1 0123

Wet months Transition months Dry months

Stress = 0.1612

Figure 13. Ordination for the Crystal system. 

black symbols = wet months (June–September); gray

symbols = months of variable rainfall (January, 

February, March and December); white symbols = dry 

months (April, May, October and November) 

-3

-2

-1

0

1

2

3

-3 -2 -1 0123

Wet months Transition months Dry months

Stress = 0.1507

Figure 11. Ordination for the Chassahowitzka system. 

black symbols = wet months (June–September); gray

symbols = months of variable rainfall (January, 

February, March and December); white symbols = dry 

months (April, May, October and November) 

Figure 14. Ordination for the Withlacoochee system. 

black symbols = wet months (June–September); gray

symbols = months of variable rainfall (January, 

February, March and December); white symbols = dry 

months (April, May, October and November) 

6 
Final Report: Contract Number 06C00000079 Project B678 

Water Quality Characteristics of the Nearshore Gulf Coast Waters Adjacent to Citrus, Hernando and Levy Counties

Given the influence of rainfall, water quality can 

be expected to vary according to the spatial 

relationships between stations and the mouths of 

the five rivers, with the stations spanning 

gradients of freshwater influence that will affect 

evaluations of trends. Salinity represents a 

conservative marker of riverine influence, and 

multivariate ordinations based on salinity

measurements from 1999 onward highlighted one 

or more stations in each system that were most 

strongly affected by river flow, except in the 

Crystal system where the stations formed three 

groups corresponding to distance offshore 

(Figures 15–19). In analyses to identify trends, 

riverine influence, as characterized by salinity, 

should highlight groups of stations that exhibit 

coherent patterns. 

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

-2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5

Stn 1 Stn 2 Stn 3 Stn 4 Stn 6 Stn 7 Stn 8 Stn 9 Stn 10

Stress = 0.0341

Figure 17. Ordination for the Homosassa system

based on salinities. 

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

-2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5

Stn 3 Stn 4 Stn 5 Stn 6 Stn 7 Stn 8 Stn 9 Stn 10

Stress = 0.0167

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

-2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5

Stn 1 Stn 4 Stn 5 Stn 6 Stn 7 Stn 8 Stn 9 Stn 10

Stress = 0.0385

Figure 18. Ordination for the Chassahowitzka system

based on salinities. 

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

-2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5

Stn 3 Stn 4 Stn 5 Stn 6 Stn 7 Stn 8 Stn 9 Stn 10

Stress = 0.0220

Figure 19. Ordination for the Weeki Wachee system

based on salinities. 

Figure 15. Ordination for the Withlacoochee system

based on salinities. 

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

-2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5

Stn 1 Stn 2 Stn 5 Stn 6 Stn 7 Stn 8 Stn 9 Stn 10

Stress = 0.0652

Figure 16. Ordination for the Crystal system based on 

salinities. 

7 
Final Report: Contract Number 06C00000079 Project B678 

Water Quality Characteristics of the Nearshore Gulf Coast Waters Adjacent to Citrus, Hernando and Levy Counties

Concentrations of nitrogen, phosphorus and 

chlorophyll can vary independently of riverine 

influence due to inputs from other sources and 

biological and biogeochemical processing. 

Therefore, a series of multivariate ordinations 

assessed consistent differences among stations 

that might affect detection of trends. 

Ordinations based on range-standardized data 

[(value – minimum value)/range] yielded suitable 

representations in three dimensions as indicated 

by stress values (Figures 20–24). Plots showing 

the first two axes highlighted spatial patterns that 

augment the results derived from variations in 

salinity. As expected when using three parameters 

instead of one, the results are more complex than 

those based on salinity alone. Therefore, a 

combination of the two sets of data was used in a 

third set of ordinations. 

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0

Stn 1 Stn 2 Stn 3 Stn 4 Stn 6 Stn 7 Stn 8 Stn 9 Stn 10

Stress = 0.493

Figure 22. Ordination for the Homosassa system

based on concentrations of total nitrogen, total

phosphorus and chlorophyll.

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0

Stn 3 Stn 4 Stn 5 Stn 6 Stn 7 Stn 8 Stn 9 Stn 10

Stress = 0.1070

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0

Stn 1 Stn 4 Stn 5 Stn 6 Stn 7 Stn 8 Stn 9 Stn 10

Stress = 0.1106

Figure 23. Ordination for the Chassahowitzka system

based on concentrations of total nitrogen, total

phosphorus and chlorophyll.

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0

Stn 3 Stn 4 Stn 5 Stn 6 Stn 7 Stn 8 Stn 9 Stn 10

Stress = 0.1560

Figure 20. Ordination for the Withlacoochee system

based on concentrations of total nitrogen, total

phosphorus and chlorophyll.

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0

Stn 1 Stn 2 Stn 5 Stn 6 Stn 7 Stn 8 Stn 9 Stn 10

Stress = 0.0997

Figure 24. Ordination for the Weeki Wachee system

based on concentrations of total nitrogen, total

phosphorus and chlorophyll.

Figure 21. Ordination for the Crystal system based on 

concentrations of total nitrogen, total phosphorus and 

chlorophyll.

8 
Final Report: Contract Number 06C00000079 Project B678 

Water Quality Characteristics of the Nearshore Gulf Coast Waters Adjacent to Citrus, Hernando and Levy Counties

Stations were grouped according to results of 

hierarchical classification, which provided 

multivariate “distances” measuring the similarity

among the data for each station (Table 1). Plots 

showing two of the three axes in ordinations 

highlighted spatial patterns (Figures 25–29). 

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0

Stn 1 Stn 2 Stn 3 Stn 4 Stn 6 Stn 7 Stn 8 Stn 9 Stn 10

Stress = 0.0899

Group 4

Group 3

Group 2

Group 1

Table 1. Maximum multivariate distances among 

estuarine stations in groups. Wi = Withlacoochee 

system; Cr = Crystal system; Ho = Homosassa system; 

Ch = Chassahowitzka system; WW = Weeki Wachee 

system

Figure 27. Ordination for the Homosassa system

based on salinities and concentrations of total 

nitrogen, total phosphorus and chlorophyll.

Group Wi Cr Ho Ch WW

1 0.69 0.45 0.49 0.30 0.79

2 0.31 0.49 0.27 0.23 0.39

3 0.31 0.37 0.35 0.30 0.26

4 0.44 0.38 0.26

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0

Stn 3 Stn 4 Stn 5 Stn 6 Stn 7 Stn 8 Stn 9 Stn 10

Stress = 0.0683

Group 3

Group 2

Group 1

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0

Stn 1 Stn 4 Stn 5 Stn 6 Stn 7 Stn 8 Stn 9 Stn 10

Stress = 0.0690

Group 1

Group 3

Group 2

Figure 28. Ordination for the Chassahowitzka system

based on salinities and concentrations of total 

nitrogen, total phosphorus and chlorophyll.

Figure 25. Ordination for the Withlacoochee system

based on salinities and concentrations of total 

nitrogen, total phosphorus and chlorophyll.

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0

Stn 3 Stn 4 Stn 5 Stn 6 Stn 7 Stn 8 Stn 9 Stn 10

Group 4

Group 3

Group 2

Group 1

Stress = 0.0933

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0

Stn 1 Stn 2 Stn 5 Stn 6 Stn 7 Stn 8 Stn 9 Stn 10

Stress = 0.0791

Group 3

Group 4

Group 2

Group 1

Figure 29. Ordination for the Weeki Wachee system

based on salinities and concentrations of total 

nitrogen, total phosphorus and chlorophyll.

Figure 26. Ordination for the Crystal system based on 

salinities and concentrations of total nitrogen, total 

phosphorus and chlorophyll.

9 
Final Report: Contract Number 06C00000079 Project B678 

Water Quality Characteristics of the Nearshore Gulf Coast Waters Adjacent to Citrus, Hernando and Levy Counties

Correlations assessed trends in concentrations of 

total nitrogen, total phosphorus and chlorophyll 

between 1999 and 2008 for estuarine stations in 

the five coastal systems. Wet months (June, July, 

August and September), transitional months 

(January, February, March and December), and 

dry months (April, May, October and November) 

formed the basis for three sets of correlations. A 

further three sets comprised wet, transitional and 

dry “years” with months treated as replicates. 

Individual correlations in each of the six sets 

evaluated data from stations or groups of stations 

differentiated by hierarchical classification and 

ordination based on salinities and concentrations 

of the three water quality parameters (Table 2). 

This approach yielded 162 correlations for both 

months and years or 324 correlations in total. The 

patterns for correlations with months and years 

were similar, so correlations with months are 

presented. 

During wet months, concentrations of total 

nitrogen, total phosphorus and chlorophyll 

increased through time, especially at stations in 

the Withlacoochee, Crystal and Homosassa 

systems (Figures 30–32). These trends suggest 

increased transport of nutrients and stimulation of 

phytoplankton production. In fact, widespread 

increases in total nitrogen concentrations would 

be expected because highly soluble nitrate is a 

common form of nitrogen in these systems. The 

distribution of trends probably relates to human 

activities and the hydrology of watersheds, as 

determined by their sizes, contributions from

surface water and groundwater, hydroperiods, and 

other characteristics. Concentrations of total 

phosphorus decreased through time in the 

Chassahowitzka and Weeki Wachee systems. 

These decreases may be related to uptake by

phytoplankton, an explanation that is supported 

by an increase in chlorophyll at an inshore station 

near the mouth of the Weeki Wachee but not by

decreases in chlorophyll concentrations in the 

Chassahowitzka system. Table 2. Groups of estuarine stations for correlations. 

Wi = Withlacoochee system; Cr = Crystal system; 

Ho = Homosassa system; Ch = Chassahowitzka 

system; WW = Weeki Wachee system

Wi Cr Ho Ch WW

6 8 4 3, 4 3

1, 4, 5, 8, 9 9 1, 2, 6 5, 6 4 

4, 7, 10 1, 5, 6 1. 2. 6 7, 8, 9, 10 5, 7, 8 

2, 7, 10 3, 7, 9 6 6, 9, 10 

Out of 162 correlations, 49 were statistically

significant (p < 0.05), with 27 correlations 

indicating significant increases through time and 

the remaining 22 correlations indicating 

significant decreases through time. The largest, 

significant positive and negative correlation 

coefficients were 0.511 and –0.523, which meant 

that no correlation explained more than 27% of 

the variation in the appropriate data. Thus, spatial 

and temporal variation in concentrations of key

parameters remains a challenge when seeking to 

identify trends. Discussion is limited to broad 

patterns and potential causal links until 

complementary data have been collected or 

collated. 

Figure 30. Significant correlations between total 

nitrogen and wet months. 

green circle = significant positive correlation; 

red square = significant negative correlation 

10 
Final Report: Contract Number 06C00000079 Project B678 

Water Quality Characteristics of the Nearshore Gulf Coast Waters Adjacent to Citrus, Hernando and Levy Counties

In comparison to results for wet months, a greater 

proportion of significant correlations were 

negative for transitional months (Figures 33–35). 

Significant positive correlations indicated that 

concentrations of total nitrogen and/or 

chlorophyll increased at a few stations in the 

Withlacoochee, Crystal and Homosassa systems, 

whereas concentrations of total phosphorus 

remained unchanged in those systems. In 

combination with results for wet months, this 

pattern suggests increased transport of nitrogen 

resulting in stimulation of phytoplankton 

production. In general, concentrations of total 

nitrogen, total phosphorus and/or chlorophyll 

decreased through time at stations in the 

Chassahowitzka and Weeki Wachee systems. 

Further insights into causal relationships await 

auxiliary data on water management activities, 

changes in land use, and other potential 

influences on nutrient loads, as well as diagnostic 

studies to elucidate biological influences such as 

uptake and recycling of nutrients or grazing 

pressures on phytoplankton. 

Figure 31. Significant correlations between total 

phosphorus and wet months. 

green circle = significant positive correlation; 

red square = significant negative correlation 

Figure 33. Significant correlations between total 

nitrogen and transitional months. 

green circle = significant positive correlation; 

red square = significant negative correlation 

Figure 32. Significant correlations between 

chlorophyll and wet months. 

green circle = significant positive correlation; 

red square = significant negative correlation 

11 
Final Report: Contract Number 06C00000079 Project B678 

Water Quality Characteristics of the Nearshore Gulf Coast Waters Adjacent to Citrus, Hernando and Levy Counties

Results for dry months resembled results for 

transitional months (Figures 36–38). Significant 

positive correlations indicated increasing 

concentrations of total nitrogen and/or total 

phosphorus in the Withlacoochee, Crystal, 

Homosassa and Chassahowitzka systems, but 

there was no evidence of a corresponding 

increase in phytoplankton production, as 

indicated by chlorophyll concentrations. In 

contrast, concentrations of total nitrogen or total 

phosphorus decreased significantly through time 

at stations in the Homosassa, Chassahowitzka and 

Weeki Wachee systems. Auxiliary data on factors 

that could influence nutrient loads and diagnostic 

studies of biological and biogeochemical 

processing should yield further insights into the 

causes of these trends. 

Figure 34. Significant correlations between total 

phosphorus and transitional months. 

green circle = significant positive correlation; 

red square = significant negative correlation 

Figure 36. Significant correlations between total 

nitrogen and dry months. 

green circle = significant positive correlation; 

red square = significant negative correlation 

Figure 35. Significant correlations between 

chlorophyll and transitional months. 

green circle = significant positive correlation; 

red square = significant negative correlation 

12 
Final Report: Contract Number 06C00000079 Project B678 

Water Quality Characteristics of the Nearshore Gulf Coast Waters Adjacent to Citrus, Hernando and Levy Counties

CONCLUDING REMARKS

The results in this report bear on issues related to 

sustainable management of Gulf coast waters 

adjacent to Citrus, Hernando and Levy Counties. 

Three of the parameters measured in the baseline 

study are correlated, with increasing 

concentrations of total nitrogen and total 

phosphorus linked to increasing concentrations of 

chlorophyll, a metric related to eutrophication. In 

addition, the aftermath of an El Niño event 

highlighted how increased chlorophyll 

concentrations negatively affect light penetration, 

as measured with a Secchi disk. Prolonged 

decreases in light penetration can lead to loss of 

seagrasses and a variety of undesirable flow-on 

effects through these valuable coastal systems. 

Efforts to differentiate trends from short-term

changes and variation in water quality benefited 

from evaluating both the influence of rainfall and 

the extent of spatial and temporal coherence 

among sampling stations. Results for the 

Withlacoochee, Crystal and Homosassa systems 

yielded evidence of increasing nutrient loads and 

consequent increases in phytoplankton. In 

contrast, results for the Chassahowitzka and 

Weeki Wachee systems indicated decreases in 

loads of total nitrogen and total phosphorus. 

Further insights require collation of data on 

anthropogenic factors that could alter nutrient 

loads, such as changes in land use or improved 

management of stormwater, along with diagnostic 

studies to elucidate transformation of nutrients, 

grazing pressure on phytoplankton, and other 

biological and biogeochemical processes. For 

example, data on local weather conditions and 

multiple measurements of water quality within 

days would yield an improved understanding of 

key interactions and, ultimately, improved 

management of the threat of eutrophication. 

Figure 37. Significant correlations between total 

phosphorus and dry months. 

green circle = significant positive correlation; 

red square = significant negative correlation 

The understanding generated by efforts to 

elucidate spatial and temporal coherence also will 

contribute to the design of effective and efficient 

monitoring. Identifying, differentiating and 

sourcing the effects of long-term, anthropogenic 

loading and short-term responses to climate and 

weather will require a combination of highfrequency sampling at characteristic stations

Figure 38. Significant correlations between total 

chlorophyll and dry months. 

green circle = significant positive correlation; 

red square = significant negative correlation 

13 
Final Report: Contract Number 06C00000079 Project B678 

Water Quality Characteristics of the Nearshore Gulf Coast Waters Adjacent to Citrus, Hernando and Levy Counties

and less frequent sampling across an array LITERATURE CITED

of stations over decades (Enfield et al. 2001, 

Sutton and Hodson 2005). Such monitoring will 

document the success of management and guide 

responses to unforeseen circumstances. Thus, the 

baseline study and this report are delivering the 

desired results by identifying important patterns 

in water quality, providing data for more in-depth 

analyses of trends, pointing to the need for key

diagnostic studies, and laying the foundation for 

the design of long-term monitoring. 

Duarte, C.M. 1991. Seagrass depth limits. Aquatic

Botany 40: 363-377. 

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2001. The Atlantic multidecadal oscillation and its 

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28: 2077-2080. 

Frazer, T.K. and J.A. Hale. 2001. Changes in the 

abundance and distribution of submersed aquatic

vegetation along Florida’s Springs Coast: 1992–

1999. Final Report. Southwest Florida Water 

Management District (SWFWMD Contract No. 

99CON000041). 

Information in the scientific literature combined 

with this report reinforces managers’ concerns 

regarding the potential impacts of increased 

chlorophyll and decreased light availability on 

seagrasses and their associated fauna. High 

chlorophyll concentrations and resultant shading 

can cause loss of seagrasses (Duarte 1991). 

Seagrasses represent a valuable habitat that 

integrates the effects of water quality over time; 

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and design of effective management responses. 

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D.E. Canfield, F.E. Vose, W.R. Leavens,

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and D.E. Canfield, Jr. 2001a. Physical, chemical

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Clearly, there is a need for a quantitative 

understanding of nutrient loads within the region. 

The robust empirical relationship between 

chlorophyll and total phosphorus concentrations 

and results of nutrient addition assays point to 

phosphorus as a limiting nutrient across

much of the region (Frazer et al. 1998, 

2001b, 2002, 2003, 2004 and 2006, Hoyer et al. 

2002; Jacoby et al. 2008). However, estimates of 

all nutrient loads remain essential for quantifying 

responses and attributing causal links at the 

appropriate spatiotemporal scales. Data on 

nutrient loads and models of ecosystem responses 

will never obviate the need for sustained 

monitoring of water quality in a program

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quality characteristics of the nearshore Gulf coast 

waters adjacent to Citrus, Hernando and Levy 

counties. Final Report. Southwest Florida Water 

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D.E. Canfield, Jr., S.B. Blitch and C. Bedee. 2003. 

Water quality characteristics of the nearshore Gulf 

coast waters adjacent to Citrus, Hernando and 

Levy Counties – Project COAST 2002. Final 

Report. Southwest Florida Water Management

District, Brooksville, Florida.

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and J.A. Hale. 2004. Water quality characteristics 

of the nearshore Gulf coast waters adjacent to

Citrus, Hernando and Levy Counties – Project 

COAST 1997 through 2003. Annual Report.

Southwest Florida Water Management District, 

Brooksville, Florida.

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Final Report: Contract Number 06C00000079 Project B678 

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Frazer, T.K. S.K. Notestein, S.R. Keller and 

C.A. Jacoby. 2006. Water Quality Characteristics 

of the Nearshore Gulf Coast Waters Adjacent to 

Citrus, Hernando and Levy Counties – Project 

COAST 1997 – 2005. Final Report. Southwest 

Florida Water Management District, Brooksville, 

Florida. 54 pp. 

Frazer, T.K., E.J. Phlips, S.K. Notestein and C. Jett. 

2002. Nutrient limiting status of phytoplankton in 

five Gulf coast rivers and their 

associated estuaries. Final Report. Southwest 

Florida Water Management District (SWFWMD 

Contract No. 00CON000038). 

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M.O. Hall. 2004. Changes in the distribution of 

seagrass species along Florida’s central Gulf 

coast: Iverson and Bittaker revisited. Estuaries 

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Seagrass status and trends in the northern Gulf of 

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267 pp. 

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and D.E. Canfield, Jr. 2002. Nutrient, 

chlorophyll, and water clarity 

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coastal waters with comparisons to 

freshwater lakes. Canadian Journal of Fisheries 

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and D.C. Behringer, Jr. 2008. Water quality 

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and Aripeka spring complexes, Citrus and 

Hernando Counties, Florida: origin of increasing 

nitrate concentrations. Technical Report prepared 

by the Ambient Ground-Water Quality Monitoring 

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District. 

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Petersburg, Florida. 

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L. Ahijevych. 2007. Florida Big Bend. 

pp. 171–188. In Handley, L., D. Altsman and 

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Water Quality Characteristics of the Nearshore Gulf Coast Waters Adjacent to Citrus, Hernando and Levy Counties

16 

Appendix 1 – Sampling coordinates 

System Station Latitude (N) Longitude (W) 

decimal minutes decimal minutes 

Withlacoochee 1 29°02.500 82°47.500 

 2 29°01.500 82°43.300 

 3 29°01.500 82°40.500 

 4 29°00.500 82°49.500 

 5 29°00.500 82°47.500 

 6 29°00.500 82°45.500 

 7 28°58.500 82°49.500 

 8 28°58.500 82°47.500 

 9 28°58.500 82°45.500 

 10 28°56.500 82°47.500 

Crystal River 1 28°55.500 82°44.500 

 2 28°55.500 82°42.500 

 3 28°55.500 82°40.500 

 4 28°54.300 82°37.100 

 5 28°53.500 82°44.500 

 6 28°53.500 82°42.500 

 7 28°53.500 82°40.500 

 8 28°51.500 82°44.500 

 9 28°51.500 82°42.500 

 10 28°50.500 82°39.500 

Homosassa 1 28°49.500 82°44.500 

 2 28°47.500 82°44.500 

 3 28°47.500 82°42.500 

 4 28°47.700 82°39.500 

 5 28°47.300 82°37.100 

 6 28°45.500 82°44.500 

 7 28°45.500 82°42.500 

 8 28°45.500 82°40.500 

 9 28°43.500 82°42.500 

 10 28°43.500 82°40.500 

Chassahowitzka 1 28°42.960 82°34.660 

 2 28°42.880 82°36.480 

 3 28°42.310 82°37.210 

 4 28°41.500 82°38.500 

 5 28°40.500 82°39.500 

 6 28°41.150 82°39.900 

 7 28°41.500 82°40.500 

 8 28°39.800 82°40.400 

 9 28°40.500 82°41.500 

 10 28°42.500 82°41.500 

Weeki Wachee 1 28°31.087 82°34.416 

 2 28°31.886 82°37.316 

 3 28°32.069 82°38.246 

 4 28°32.500 82°39.500 

 5 28°34.500 82°39.500 

 6 28°33.500 82°40.500 

 7 28°31.500 82°40.500 

 8 28°30.530 82°41.500 

 9 28°32.500 82°41.500 

 10 28°34.500 82°41.500