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1.0 Introduction 

The Florida Department of Environmental Protection (FDEP) is currently developing a rule to 

establish numeric nutrient criteria for a number of water body types. The following summarizes 

FDEP view on the development of numeric nutrient criteria in Florida (FDEP website, 2011). 

The overarching FDEP goal is to “manage nutrients in surface water and groundwater at loadings or 

concentrations that result in protection and maintenance of healthy, well-balanced aquatic 

communities”. Absent site-specific analyses, water quality criteria should be based on a 

quantifiable linkage between anthropogenic nutrient enrichment and a biological response (such as 

seagrass growth) that can be used to numerically interpret the narrative nutrient criteria. There is 

value in knowing whether nutrient concentrations are potentially elevated to environmentally 

harmful levels, but conversely, it is equally important to identify adverse biological effects and 

determine if they are linked to nutrients before deciding that nutrient reductions should be pursued. 

The Department recognizes the role of site-specific factors that affect nutrient responses and 

proposes to base new standards on establishing a systematic numeric interpretation of the existing 

narrative criteria. This concept is intended to implement Rule 62-302.530 (47)(b), FAC which 

states, “in no case shall nutrient concentrations of a body of water be altered so as to cause an 

imbalance in natural populations of aquatic flora or fauna.” 

As envisioned by FDEP, the narrative nutrient criteria would continue to apply to all waterbodies, 

and numeric interpretations would be applied when adequate scientific information is available. 

The narrative would be implemented using a systematic structure that numerically interprets the 

narrative nutrient criteria for each waterbody in a hierarchical manner 

Numeric interpretations are most accurate when determined as a site-specific function. Therefore, 

nutrient Total Maximum Daily Loads (TMDLs), Site Specific Alternative Criteria (SSAC), and other 

site specific actions written to achieve the narrative nutrient criteria should be given preference 

over more broadly applicable interpretations. 

The first tier of the hierarchical approach entails an evaluation of previously established site-specific 

numeric interpretations of the narrative criteria (including TMDLs, SSACs, and other interpretations 

embodied in an official Department action. This would be the primary interpretation of the 

narrative nutrient criteria. Currently, the Sarasota Bay Estuary Program (SBEP) Policy Board has 

approved a series of segment-specific numeric nutrient criteria. FDEP is represented on the SBEP 

Policy Board, therefore, Sarasota Bay is presumably a candidate for inclusion in the first tier of the 

hierarchical approach. 

FDEP has also stated that if nutrient TMDLs are expressed as loads instead of concentrations, the 

loads do not have to be translated into concentrations to be deemed the numeric interpretation of 

the narrative nutrient criteria. This document presents concentration-based numeric nutrient 

criteria for the five bay segments of Sarasota Bay. 

Finally, FDEP recognizes that future TMDL rules may include a response target (chlorophyll a, for 

example) designed to implement the narrative nutrient criterion. Currently, the recommended 
2 

assessment of the proposed numeric nutrient criteria for Sarasota Bay is built of assessing the 

achievement of a series of segment-specific chlorophyll a targets. 

Over the past several years, the SBEP has conducted a series of tasks with the ultimate goal of 

establishing estuarine numeric nutrient criteria for Sarasota Bay. 

This first part of this document provides background information concerning the Sarasota Bay 

estuarine system, including a brief physical characterization of the system and a summary of 

previous work completed with respect to Sarasota Bay estuarine targets. The latter part of this 

document provides the data and methodology utilized for developing estuarine numeric nutrient 

criteria for Sarasota Bay, the targets resulting from application of the methodology, the proposed 

numeric nutrient criteria, and the proposed methodology for implementation and compliance of the 

Sarasota Bay estuarine numeric nutrient criteria. 

1.1 Sarasota Bay and Its Watershed 

Sarasota Bay is a fifty-three mile long coastal lagoon on the southwest coast of Florida (Figure 1-1). 

It is comprised of one large bay segment (Sarasota Bay proper) and several smaller segments 

ncluding Palma Sola Bay in the north and a series of three contiguous segments (Roberts Bay, Little 

Sarasota Bay, and Blackburn Bay) to the south. Sarasota Bay has four inlets or passes (Venice Inlet, 

Big Sarasota Pass, New Pass and Longboat Pass). The SBEP area is bounded to the north by Anna 

Maria Sound, which opens into Tampa Bay and to the south by Venice Inlet. There are numerous, 

small tidal creeks that enter the bay along the eastern shoreline, ranging in size from Phillippi Creek 

(drainage area of 36,417 acres) to Palma Sola Creek (drainage area of 900 acres). The watershed is 

highly developed and consists of agricultural, residential, commercial, and light industrial land 

uses. 

Circulation is primarily driven by tidal exchange with the Gulf of Mexico. Sarasota Bay circulation 

is forced by the tides at Anna Maria Sound, Longboat Pass, New Pass, and Big Pass. Tidal 

circulation in Little Sarasota Bay is forced by tides at Venice Inlet and the Intracoastal Waterway 

running through the middle of the bay. The closing of Midnight Pass in Little Sarasota Bay in 1983 

permanently altered the circulation in the three lower segments. 

 

Between 1950 and 1988, an estimated 18% of the seagrass acreage in Sarasota Bay was lost due to 

physical alterations (dredge and fill), and excess nitrogen loading and higher algae concentrations, 

which ultimately caused light limitation to the seagrasses. In 1990, all municipal wastewater plants 

were required to provide Advanced Wastewater Treatment for direct discharges to the bay and 

tributaries. 

In addition to the significant reductions in nitrogen loadings from municipal wastewater treatment 

plants, stormwater regulations enacted in the 1980s also resulted in reduced nitrogen loads to the 

bay. Phillippi Creek (38% of the watershed), Bowlees Creek (7%) and Catfish Creek (3%) have 

been retrofitted to remediate flooding and provide treatment. Nitrogen loading from Phillippi 

Creek has decreased 60% since 1988, while overall nitrogen loading to Sarasota Bay has been 

reduced by at least 46%. A fertilizer ordinance prohibiting application during the wet summer 

months was enacted within 75% of the watershed. 
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The SBEP, in cooperation with local scientists and the FDEP, has developed tabular listings of 

symptoms of nutrient enrichment in Sarasota Bay, along with potential explanations of these 

expressions, to aid in development of numeric nutrient criteria for the bay. These listing are 

provided in Tables 1-1 and 1-2 below. These tables provide a summary of potential responses to 

nutrient enrichment expressed in the bay, and notes whether these responses are currently or 

historically found in the bay. 
Table 1-1. Checklist of nutrient enrichment symptoms in Sarasota Bay. -= Empty cell/no data; N/A = Not availableResponse Variable Observed 

Historically or 

Currently? 

Explanation 

Low dissolved oxygen (DO) (hypoxia/anoxia)

Yes, limited in 

space and time 

During the period 1998-2008, there were no years in which the proportion of DO samples exceede4.0 mg/l criterion by 10% in any bay segment. 

Reduced clarity No. Water clarity improved by approximately 0.4m from 1987 to 2000. Recent trend analyses (1998-20

indicate statistically significant improvements in water clarity in Palma Sola Bay while no significant 

were shown in the other four bay segments. 

Increased chlorophyll aconcentrations 

No. During the period 1998-2008, there were statistically significant reductions in chlorophyll a in Palm

Bay, Sarasota Bay proper, and Blackburn Bay. No significant trends were detected in either Roberts Little Sarasota Bay. 

Phytoplankton blooms (nuisance or toxic) 

Yes, limited in 

space and time 

Red tide blooms originating in the Gulf of Mexico have occasionally entered the Bay. The most rec

tide event affecting Sarasota Bay was in 2005. 

Problematic epiphyte growth 

No Research showed that epiphytes reduce the light available to seagrasses by nearly 50% as a yearly a

No problems with excessive epiphytic growth have been documented. 

Problematic macroalgal growth 

No Nuisance macroalgal blooms have not occurred over the past two years (2009-10). Recent trends sh

low macroalgal biomass throughout the Bay. 

Submerged aquatic vegetation (SAV) community changes or loss 

Yes, historically. Current seagrass acreage in Sarasota Bay is 24% higher than 1950 acreage. Total seagrass acreage (2

has increased 46% since 1988. Seagrass beds designated as continuous (SWFWMD) have increased since 1988. 

Emergent or shoreline vegetation community changes or loss 

Yes, historically. Historical losses have occurred due to shoreline hardening and development. The SBEP recently up

its Habitat Restoration Plan to identify, prioritize and implement restoration projects to offset these 

historical wetland and shoreline vegetative losses. 

Coral/hardbottom community changes or loss 

Unknown No coral or natural hard bottom is present in Sarasota Bay. 

Impacts to benthic community 

No Benthic communities are not routinely monitored in Sarasota Bay. Abundant shellfish populations h

been reported and bay scallops have shown a return to the bay after years of absence. 

Fish kills Yes, limited in 

space and time 

Periodic fish kills have occurred from red tide blooms entering the bay; however, no fish kills have breported as a direct result of nutrient inputs into the estuary. Fisheries data show high abundances ojuvenile and adult fish within all bay segments. 
Table 1-2. Checklist of additional factors in Sarasota Bay .- = Empty cell/no dataNutrient Factors Observed? Explanation Increased nutrient loading or concentrations 

No Nitrogen loading to Sarasota Bay, using the EPA approved Watershed Management Model, has been 

reduced by 46% since 1988. Nitrogen loading from Phillippi Creek, which drains 38% of the watershed, has decreased 60% since 1988. 

Mitigating factors that could prevent nutrient expression 

Yes Bay hydrologic residence times and circulation; season of nutrient inputs; seasonally high water color. 

Other significant stressors to biological communities 

No 

Natural high-nutrient episodes (e.g., seasonal or event driven) 

Yes Elevated nutrient and/or chlorophyll a concentrations have been observed during periods of extremely 

high rainfall (e.g., the El Niño event in 1998), tropical storms, and/or domestic/industrial spills. 
7 

2.0 Objective 

The objective of this document is to propose estuarine numeric nutrient criteria specific to the five 

segments of Sarasota Bay: Palma Sola Bay, Sarasota Bay, Roberts Bay, Little Sarasota Bay, and 

Blackburn Bay. These criteria are expressed as in-bay TN concentrations. SBEP has also developed 

loading-based TN criteria and both concentration and loading-based TP criteria (Janicki 

Environmental, 2011) that are summarized in Appendix A. 

3.0 Development of Seagrass, Light Attenuation, and Chlorophyll 

a Targets 

This section provides detailed summary of work previously completed by the SBEP in the 

establishment of segment-specific seagrass targets and the associated water quality (light attenuation 

and chlorophyll) targets. 

3.1 Background and Rationale

As discussed above, between 1950 and 1988, approximately 18% of the seagrass acreage in 

Sarasota Bay was lost due to excess nitrogen loading. This excess nitrogen loading resulted in 

increased algae concentrations which caused light limitation detrimental to seagrass survival and 

growth. Additional seagrass loss was due to physical disturbances and shoreline modifications. 

Since 1980, all municipal wastewater treatment plants were required to provide Advanced 

Wastewater Treatment (AWT) for discharges directly to the Bay and its tributaries. In addition to 

the significant reductions in nitrogen loadings from municipal wastewater treatment plants, 

stormwater regulations enacted in the 1980s also resulted in reduced nitrogen loads to the Bay. 

Overall, nitrogen loading to Sarasota Bay has been reduced by at least 46% since 1988. 

Sarasota Bay was named an estuary of “national significance” in 1987 which led to its designation 

as a National Estuary Program by the EPA two years later. The Sarasota Bay Estuary Program is 

dedicated to improving and protecting the area’s greatest and most important natural asset - 

Sarasota Bay. The SBEP strives to improve water quality, increase habitat and enhance the natural 

resources of the area for use and enjoyment by the public. 

A Management Conference was formed comprising federal, state, regional and local officials who 

oversaw the development and implementation of a Comprehensive Conservation and Management 

Plan (CCMP) for Sarasota Bay. Several priority concerns were identified: 

 declines in water and sediment quality, 

 loss of wetlands and other coastal habitats, 

 loss of seagrasses, 

 declines in finfish and shellfish populations, and 

 overuse. 

The Management Conference also developed plans of action to address these concerns through 

technical studies and citizen action plans which resulted in the development of the CCMP in 1995. 

Progress in the implementation of the CCMP has been documented. A State of the Bay report 

(SBEP, 2010) has been recently completed. 
8 

While not explicitly stated, the SBEP CCMP recognized the linkages between nutrient enrichment, 

algal productivity, light attenuation, and seagrass growth and reproduction in a similar fashion to 

the Tampa Bay Estuary Program nutrient loading-chlorophyll-seagrass paradigm. 

3.2 Development of Seagrass Targets 

One of the primary SBEP goals is to maintain and/or restore seagrass coverage to its historic extent. 

The seagrass target project provided technically-defensible quantitative seagrass targets for the 

Sarasota Bay ecosystem. Establishment of seagrass targets provides a necessary basis for 

management decisions regarding water quality and other issues that can influence the distribution 

and persistence of this resource. Targets were defined through an analysis of historic and recent 

aerial surveys of the study area. 

The historic aerial photos used to establish the baseline extent of seagrass in the study area were 

dated circa 1950. Recent trends in and persistence of seagrass throughout the SBEP were 

determined through analysis of GIS shapefiles based on aerial surveys executed biannually by the 

Southwest Florida Water Management District since 1988. Due to anthropogenic modifications in 

the estuary such as shoreline build-out and the dredging of the Intracoastal Waterway (ICW), certain 

areas have been altered to the extent that they have no reasonable potential for restoration; these 

so-called non-restorable areas have been identified and removed from the analyses. 

The trend analyses show that Sarasota Bay proper is currently at its highest seagrass level since 

1950 and exceeds the baseline extent (see Appendix B). The seagrass coverage in Roberts Bay and 

Blackburn bays also increased since the baseline period. In Palma Sola Bay, the seagrass coverage 

has remained very similar over the entire period of record. In contrast, Little Sarasota Bay has 

shown a decline in seagrasses since 1950. 

The definition of the most appropriate seagrass targets was reached with input from the Technical 

Advisory Committee (TAC). The TAC recommended that the greater of either the historic or recent 

(2004-2006) seagrass coverages be established as the target in each segment. The sole exception to 

this rule was Little Sarasota Bay. Since 1984, the direct connection to the Gulf of Mexico (Midnight 

Pass) has been closed. This physical alteration may have contributed to the difference in seagrass 

coverage between the historic and current coverages. However, a recent FDEP decision precludes 

re-opening of this pass. Therefore, the recent coverage in Little Sarasota Bay has been established 

as the target. Table 3-1 presents the seagrass targets that were adopted by the SBEP Management 

and Policy boards. 

Table 3-1. SBEP seagrass coverage and targets. Unit of measure=acres. 

Bay Segment Historical 

(1950) 

Current 

2004-2006 

Average 

Seagrass 

Target 

Palma Sola 1,031 1,015 1,031 

Sarasota 7,269 7,041 7,269 

Roberts 283 348 348 

Little Sarasota 883 702 702 

Blackburn 273 447 447 

Total 9,739 9,552 9,997 
9 

3.3 Development of Chlorophyll a Targets 

In October 2009, the SBEP Policy and Management boards directed the TAC to develop numeric 

nutrient criteria for the estuarine waters of the area. A subcommittee of the TAC began the process 

by reviewing the existing seagrass and chlorophyll a data and proposing a set of chlorophyll a

targets to support the development of the numeric nutrient criteria (Janicki Environmental, 2010). 

In line with the goal of restoring and protecting seagrass populations, the SBEP had a goal of 

improving water clarity (e.g., by reducing algal abundance). Recent results from ambient water 

quality monitoring programs indicate that the chlorophyll a concentrations have declined in all 

segments for the period 1998 to 2009. Further analysis of the chlorophyll concentration data using 

non-parametric trend tests (Kendall-Tau) revealed significant decreasing trends in chlorophyll in all 

segments except Roberts Bay (Figure 2). This finding, in conjunction with the increased seagrass 

acreage, provide strong evidence that the management efforts of the SBEP are bearing fruit with 

improved water quality and increased seagrass abundance. 

Figure 2. Sarasota Bay monthly chlorophyll a concentrations. 
10 

Given that the recent extents of seagrass coverages are meeting the established targets, the 

subcommittee determined that the recent chlorophyll a concentrations and resultant water clarity 

are protective of the seagrasses in each of the SBEP segments. Upon review of the chlorophyll a

concentration data, it was deemed appropriate to include not only the data from the 2004-2005 

period but also from several antecedent years (2001-2003). The resultant mean chlorophyll a 

concentrations from this overall period (2001-2005) were established as the targets for each 

segment (Table III-2). The subcommittee further recognized that there may be years in which these 

targets may be exceeded without causing significant reductions in seagrass cover. This means that 

there is some allowable amount of variation that should not elicit a significant degradation in water 

quality and therefore seagrass coverage. The subcommittee defined this level of variation as the 

standard deviation around the mean annual chlorophyll a concentrations in each segment for the 

entire period of record. Therefore, a distinction is made between a target, i.e., a desired 

chlorophyll a concentration and a threshold, i.e., a chlorophyll a concentration above which 

undesirable chlorophyll a concentrations exist. The chlorophyll a threshold for each segment is the 

sum of the target and the standard deviation around the mean annual chlorophyll a concentrations 

in each segment. The thresholds shown in Table 3-2 are used in later sections of this report in the 

development of the numeric nutrient criteria in the SBEP estuarine waters. 

Table 3-2. SBEP recommended chlorophyll a targets and thresholds (μg/L). 

Bay Segment Target Chlorophyll a

(μg/L) 

Inter-annual Variability 

(1 SD of Annual Means)

Threshold Chlorophyll a

(μg/L) 

Palma Sola 8.5 3.3 11.8 

Sarasota 5.2 0.9 6.1 

Roberts 8.2 2.8 11.0 

Little Sarasota 8.2 2.2 10.4 

Blackburn 6.0 2.2 8.2 

4.0 Proposed Criteria 

The SBEP employed a stressor-response relationship in a similar manner to that proposed by Janicki 

Environmental (2010a) and EPA (2010). This approach involves the development of a quantitative 

relationship (i.e., model) between a chlorophyll a and some measure of nutrient condition. In this 

case, the independent variables used in the model-building process included loadings, 

concentrations, and estimates of residence time. The loadings data included monthly hydrologic, 

TN, and TP loads as well as cumulative total loads extending from two to six months (e.g., 2-month 

cumulative TN load = TN load current month + TN load one- month prior). The water quality 

constituents included TN and TP concentrations along with numerous other constituents. A 

complete presentation of the process followed to develop the proposed criteria for SBEP can be 

found in Janicki Environmental (2010b). The results of the analyses for each segment are as 

follows. 
11 

4.1 Roberts Bay 

TN concentration was identified as the variable that makes that greatest contribution to explaining 

the variability in chlorophyll a concentrations in Roberts Bay. As can be seen in Figure 4-1, there is 

a pattern of increasing chlorophyll a concentrations with increasing TN concentrations. 

Figure 4-1. Relationship between monthly average chlorophyll a and TN concentrations 

in Roberts Bay. 

A regression model between chlorophyll a and TN concentrations was developed and the residuals 

from this model were examined to identify any other explanatory variables that might contribute to 

the overall variance accounted for by the model. The residual analysis revealed a seasonal 

difference in residuals. Specifically, given the same TN concentrations, higher chlorophyll a 

concentrations can be expected during the wetter, warmer summer months (July-October) than 

during the remainder of the year. Therefore, a seasonal term was added to the regression equation. 

The season term is a dummy variable which equals one during July-October and zero other months 

of the year. The final regression equation is: 

[Chlorophyll a] = -5.73 + (27.07 * [TN]) + (3.41 * season) 

The model was fit with 133 observations and resulted in an R2 value of 0.62. The regression was 

highly significant with a probability of a greater |F| value of < 0.0001. The slope and parameter 

coefficients were also highly significant. A plot of predicted versus observed chlorophyll a

concentrations is presented in Figure 4-2. 
12 

Figure 4-2. Predicted versus observed chlorophyll a concentrations for Roberts Bay (R2

=0.62). 

4.2 Little Sarasota Bay 

TN concentration was identified as the variable that makes that greatest contribution to explaining 

the variability in chlorophyll a concentration. As can be seen in Figure 4-3 there is a pattern of 

increasing chlorophyll a concentrations with increasing TN concentrations. 

Figure 4-3. Relationship between monthly average chlorophyll a and TN concentrations 

in Little Sarasota Bay. 

A regression model between chlorophyll a and TN concentrations was developed and the residuals 

from this model were examined to identify any other explanatory variables that might contribute to 

the overall variance accounted for by the model. As was found in Roberts Bay, the residual 

analysis revealed a seasonal difference in residuals. Specifically, given the same TN 

concentrations, chlorophyll a concentrations can be expected to be higher in Little Sarasota Bay 
13 

during the wetter, warmer summer months (July-October) than during the remainder of the year. 

Therefore, a seasonal term was added to the regression equation. The season term is a dummy 

variable which equals one during July-October and zero other months of the year. The final 

regression equation is: 

[Chlorophyll a] = -4.48 + (21.59 * [TN]) + (2.97 * season) 

The model was fit with 133 observations and resulted in an R2

 value of 0.57. The regression was 

highly significant with a probability of a greater |F| value of < 0.0001. The slope and parameter 

coefficients were also highly significant. A plot of predicted versus observed chlorophyll a

concentrations is presented in Figure 4-4. 

Figure 4-4. Predicted versus observed chlorophyll a concentrations in Little Sarasota Bay 

(R2

=0.57). 

4.3 Blackburn Bay 

TN concentration was identified as the variable that makes that greatest contribution to explaining 

the variability in chlorophyll a concentration. As can be seen in Figure 4-5, there is a pattern of 

increasing chlorophyll a concentrations with increasing TN concentrations. 

A regression model between chlorophyll a and TN concentrations was developed and the residuals 

from this model were examined to identify any other explanatory variables that might contribute to 

the overall variance accounted for by the model. Similar to both Roberts Bay and Little Sarasota 

Bay, this analysis revealed a seasonal difference in residuals. Specifically, given the same TN 

concentrations, chlorophyll a concentrations can be expected to be higher in Blackburn Bay during 

the wetter, warmer summer months (July-October) than during the remainder of the year. 

Therefore, a seasonal term was added to the regression equation. The season term is a dummy 

variable which equals one during July-October and zero other months of the year. The final 

regression equation is: 

[Chlorophyll a] = -3.55 + (23.72 * [TN]) + (1.73 * season) 
14 

Figure 4-5. Relationship between monthly average chlorophyll a and TN concentrations 

in Blackburn Bay. 

The model was fit with 133 observations and resulted in an R2 value of 0.73. The regression was 

highly significant with a probability of a greater |F| value of < 0.0001. The slope and parameter 

coefficients were also highly significant. A plot of predicted versus observed chlorophyll a

concentrations is presented in Figure 4-6. 

Figure 4-6. Predicted versus observed chlorophyll a concentrations in Blackburn Bay (R2

=0.73).

4.4 Sarasota Bay 

TN concentration was identified as the variable that makes the greatest contribution to explaining 

the variability in chlorophyll a concentrations in Sarasota Bay. As expected, there is a pattern of 

increasing chlorophyll a concentrations with increasing TN concentrations (Figure 4-7). As in the 

regressions developed for Roberts Bay, Little Sarasota Bay, and Blackburn Bay, initial efforts 
15 

revealed a seasonal difference in residuals. This indicates that given the same TN concentration, 

higher chlorophyll a concentrations are expected during the summer months. Therefore, a 

seasonal term was added to the regression equation. The season term is a dummy variable which 

equals one during the wet season (June-October) and zero other months of the year. 

Unlike Roberts Bay, Little Sarasota Bay, and Blackburn Bay, Sarasota Bay is a substantially larger 

system with greater spatial variability in TN concentrations. Specifically, TN concentrations in the 

northern portion of the bay (Figure 4-8) are greater than those in the southern portion (Table 4-1). 

In contrast, there is less spatial variability in the chlorophyll a concentrations. As a result, given the 

same TN concentrations, higher chlorophyll a concentrations are found in the southern portion of 

the bay. Therefore, a region term was added to the regression equation to account for the spatial 

differences in TN and chlorophyll a concentrations in Sarasota Bay. 

Figure 4-8. Northern and southern portions of the Sarasota Bay segment. 

Table 4-1. Comparison of water quality within Northern and Southern Sarasota Bay. Values 

represent medians for the period 1998-2009. 

Variable Northern Sarasota Bay Southern Sarasota Bay 

Chlorophyll a (μg/l) 5.2 3.4 

TN (mg/l) 0.56 0.28 

Color (PtCo units) 20 10 

Northern

Region
16 

Further analysis of the residuals from the regression model revealed that color also contributed to explaining 

the variation in chlorophyll a and was added to the regression equation. The final regression equation 

obtained is: 

 [Chlorophyll a] = -1.06 + (3.58 * [TN]) + (0.32 * color) + (2.03 * season) – (4.84 * region)

Figure VI-7. Relationship between monthly average chlorophyll a and TN concentrations in 

Sarasota Bay. 

The model was fit with 156 observations and resulted in an R2

 value of 0.67. The regression was 

highly significant with a probability of a greater |F| value of < 0.0001. The slope and parameter 

coefficients were also significant. A plot of predicted versus observed chlorophyll a concentrations 

is presented in Figure 4-8. 

Figure 4-8. Predicted versus observed chlorophyll a concentrations in Sarasota Bay (R2

=0.67).
17 

4.5 Palma Sola Bay 

The relationship between chlorophyll a concentrations and both TN concentrations and loads were 

graphically examined. There is no apparent relationship between chlorophyll a concentrations and 

either TN concentrations or loads. A similar lack of relationships was found for TP concentrations 

and loads, as well as a series of cumulative loading. 

Several other analytical tools were applied to discern if a quantitative relationship between 

chlorophyll a concentrations and either TN concentrations or loads could be found. Specifically, 

various applications of logistic regression techniques, changepoint analyses, and a reference 

condition approach were investigated. 

Logistic regression was used to predict the probability of a chlorophyll a concentration greater than 

the threshold value of 11.8 μg/L for Palma Sola Bay as a function of TN concentration. Based on 

the logistic regression results, a TN concentration that is predicted to result in a chlorophyll a

concentration exceedance in the wet season is 0.57 mg/L and in the dry season 1.31 mg/L. Using 

these values and calculating a weighted mean TN concentration results in an annual average 

annual TN concentration of 1.06 mg/L. 

Changepoint analysis was performed to identify a potential threshold TN value that was associated 

with a non-linear increase in chlorophyll a concentrations. A statistically significant TN 

changepoint value of 0.76 mg/L was identified as the value that maximized the difference in the 

distribution of chlorophyll a concentrations between two groups. The average chlorophyll a

concentration was 7.69 μg/L for the high [TN] group and 11.6 μg/L for the low [TN] group. 

The reference condition approach, in this case a Reference Period of 2001-2005, identified a TN 

concentration threshold of 0.93 mg/L.

4.6 Proposed TN Criteria 

The SBEP water quality subcommittee of the TAC considered three potential candidate methods for 

estimating the TN criterion for Palma Sola Bay: The subcommittee recommended the third option – 

i.e., that based on the 2001-2005 ambient TN data. The full TAC concurred with the 

subcommittee’s recommendation. 

The SBEP Management and Policy committees approved the TAC recommendations for the TN 

concentration-based numeric criteria (Table 4-2). 

Table 4-2. SBEP recommended TN criteria. 

Bay Segment TN Criteria 

(mg/L) 

Palma Sola 0.93 

Sarasota Dependent upon observed color; for the period 1998-

2009 the criteria would vary between 0.28 - 1.34 mg/L 

Roberts 0.54 

Little Sarasota 0.60 

Blackburn 0.43 
18 

5.0 Implementation 

The proposed compliance assessment strategy involves two steps. The initial step is the 

comparison of the mean annual chlorophyll a concentrations in each bay segment to the 

established chlorophyll a thresholds. Compliance is achieved if the threshold is met in that year. If 

the chlorophyll a threshold is exceeded in more than two years during any five-year period, the 

second step would be an assessment of nitrogen concentrations during that period will be 

completed. The justification for this “2-in-5 year” compliance assessment has been developed 

(Janicki Environmental, 2010) and summarized in Appendix C. 

The recommendation for compliance assessment also hinges on the availability of the appropriate 

data for a defensible assessment. Thus, how the specific spatial and temporal averaging has been 

conducted in the development of the targets and thresholds as well as the compliance assessment is 

critical. The following discusses this aspect of the implementation of the proposed numeric 

nutrient criteria for Sarasota Bay. 

From the initial efforts to establish defensible water quality targets through the development of the 

RA, the primary data sources have been Sarasota and Manatee counties. The Sarasota County 

program is probabilistic, with five (5) monthly-specific initially randomized sampling sites chosen 

for each sub-segment within Sarasota Bay, Roberts Bay, Little Sarasota Bay, and Blackburn Bay. 

Sampling and analyses are completed under contract with the County by Mote Marine Laboratory. 

The Manatee County sampling and analyses are completed by County staff at a series of sampling 

sites that were randomly chosen in both Palma Sola Bay and the Sarasota Bay. The specific 

sampling sites are presented in Table 4-1. Maps showing the locations of these sites are presented 

in Appendix D. 

Defensible compliance assessment will depend upon continued monitoring at the sites described 

above to ensure that the annual assessment for attainment of the proposed chlorophyll a thresholds 

and TN criteria. Consideration must also be given to the temporal averaging. The mean annual 

chlorophyll a concentrations have been calculated by first calculating the segment-specific 

arithmetic monthly means and subsequently calculating an arithmetic annual mean. The 

compliance would be assessed by calculating the chlorophyll a threshold i.e., the sum of the 

arithmetic annual mean and the estimate of the interannual variability (see Table 3-2) The TN 

compliance would be based on a geometric annual mean for each bay segment. 

6.0 References 

Florida Department of Environmental Protection (FDEP) website. 2011. 

http://www.dep.state.fl.us/water/wqssp/nutrients/index.htm

Heil, C.H., M. Revilla, P.M. Gilbert and S. Murasko. 2007. Nutrient quality drives differential 

phytoplankton community composition on the southwest Florida shelf. Limnol. Oceanogr., 

52:1067–1078. 

Janicki Environmental, Inc. 2010a. Empirical Approaches to Establishing Numeric Nutrient Criteria 

for Southwest Florida Estuaries. Prepared for Tampa Bay Estuary Program, Sarasota Bay Estuary 

Program, and Charlotte Harbor National Estuary Program. 
19 

Janicki Environmental, Inc. 2010b. Numeric Nutrient Criteria for Sarasota Bay. Prepared for 

Sarasota Bay Estuary Program, Sarasota, FL. 

Janicki Environmental, Inc. 2011. Numeric Nutrient Criteria: Task 1 - TN and TP Concentration 

and Loading Based Criteria. Prepared for Sarasota Bay Estuary Program, Sarasota, FL. 

Lapointe, B. 2009. Sarasota Bay Macroalgae Study: Interim Report. 

MacDonald, T.C., E. Weather, P.W. Stevens and R.H. McMichael, Jr. 2010. Nekton of Sarasota Bay 

and a Comparison of Nekton Community Structure in Adjacent Southwest Florida estuaries. Annual 

Report to the Sarasota Bay Estuary Program. 199 p. 

Mote Marine Laboratory. 1993a. Water and Sediment Quality: Trends and Status for Sarasota Bay. 

Mote Marine Laboratory Technical Report No. 254. 179 pp. 

Mote Marine Laboratory. 1993b. Bay Bottom Habitat Assessment Final Report. Mote Marine 

Laboratory Technical Report No. 303. 

Mote Marine Laboratory. 1995. Light Attenuation with Respect to Seagrasses in Sarasota Bay, 

Florida. Mote Marine Laboratory Technical Report No. 407. 53 pp. 

PBS&J. 2009. Status and trends in pollutant loads and natural resource responses in Sarasota Bay. 

Final Report to the City of Sarasota. 15 pp. 

Sarasota Bay Estuary Program. 2010. State of the Bay 2010. Celebrating Paradise: Staying the 

Course. Sarasota Bay Estuary Program, Sarasota, FL. 

Scheda Ecological Assoc, Inc. 2010. Sarasota Bay Estuary Program Five Year Habitat Restoration 

Plan: FY 2010 – FY 2014. Final Report to the Sarasota Bay Estuary Program. 

Serviss, G.M. and S. Sauers. 2003. Sarasota Bay Juvenile Fisheries Habitat Assessment. Final Report 

to the Sarasota Bay National Estuary Program. 212 pp. 

Stephenson, S.P. and S.P. Geiger. 2010. Bay Scallop Project 2009 Annual Report. Annual Report 

of the Florida Fish and Wildlife Research Institute. 67 pp. 

Tomasko, D.A., C.A. Corbett, H.S. Greening and G.E. Raulerson. 2005. Spatial and temporal 

variation in seagrass coverage in Southwest Florida: assessing the relative effects of anthropogenic 

nutrient load reductions and rainfall in four contiguous estuaries. Mar. Poll. Bull. 50:797-805. 

U.S. Environmental Protection Agency (EPA). 2010. Methods and Approaches for Deriving 

Numeric Criteria for Nitrogen/Phosphorus Pollution in Florida’s Estuaries, Coastal Waters, and 

Southern Inland Flowing Waters. 
APPENDIX A. 

Criteria Expressed as TN and TP Concentrations, and as 

TN and TP Loads 

1.0 Introduction 

This appendix provides summaries of the derivation and application of the recommended numeric

nutrient criteria for the SBEP.  Segment‐specific stressor‐response relationships between chlorophyll a

and nitrogen concentrations were developed, and utilized to derive numeric nutrient criteria in terms of

TN concentration.    Additional analyses have been completed to provide numeric nutrient criteria in

terms of TP concentrations, and in terms of TN and TP loadings, should these be necessary.

2.0 Total Nitrogen Concentrations 

The SBEP has developed recommended numeric nutrient criteria for Sarasota Bay as segmentspecific mean annual total nitrogen concentrations (Janicki Environmental, 2010). The strategy for 

developing the numeric nutrient criteria is based on the chlorophyll a thresholds (Table 2-1) (Janicki 

Environmental, 2010) and segment-specific quantitative relationships between chlorophyll a and 

nutrients. The following describes the approach used. 

Table 2-1. Recommended chlorophyll a targets and thresholds (μg/L). 

Bay Segment Target Chlorophyll a

(μg/L) 

Inter-annual Variability 

(1 SD of Annual Means)

Threshold Chlorophyll a

(μg/L) 

Palma Sola 8.5 3.3 11.8 

Sarasota 5.2 0.9 6.1 

Roberts 8.2 2.8 11.0 

Little Sarasota 8.2 2.2 10.4 

Blackburn 6.0 2.2 8.2 

2.1 Roberts, Little Sarasota, and Blackburn Bays 

The stressor-response relationships for Roberts Bay, Little Sarasota Bay, and Blackburn Bay (Janicki 

Environmental, 2010) indicated very similar responses in chlorophyll a concentrations to changes 

in nutrients. Specifically, two terms, TN concentration and season, explained more than 60% of 

the variation in the chlorophyll a data. 

For each of these segments, the segment-specific regression was used to estimate the TN 

concentrations that correspond to the chlorophyll a thresholds. This resulted in an estimated TN 

concentration for each season. The annual mean of the seasonally-specific TN concentrations was 

calculated by weighting for the number of months in each season. This weighted annual mean TN 

concentration is that TN concentration that corresponds to the chlorophyll a threshold 

concentration, and therefore is the proposed numeric nutrient criterion for each segment. 
Figures 2-1 through 2-3 present comparisons of the proposed numeric criteria for Roberts Bay, Little 

Sarasota Bay, and Blackburn Bay, expressed as an annual geometric mean TN concentration, to the 

recent ambient geometric mean TN concentrations measured in each segment. The geometric 

means are used to achieve consistency with the approach used by EPA in the proposed freshwater 

numeric nutrient criteria. 

Figure 2-1. Comparison of the proposed TN criterion to observed TN concentrations 

(expressed as geometric means) in Roberts Bay. 

Figure 2-2. Comparison of the proposed TN criterion to observed TN concentrations 

(expressed as geometric means) in Little Sarasota Bay. 

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

[TN] (mg/l)

Ambient [TN] (mg/l) [TN] Criterion (mg/l)

ROBERTS BAY

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

[TN] (mg/l)

Ambient [TN] (mg/l) [TN] Criterion (mg/l)

LITTLE SARASOTA BAY
Figure 2-3. Comparison of the proposed TN criterion to observed TN concentrations 

(expressed as geometric means) in Blackburn Bay. 

2.2 Sarasota Bay 

The relationship between chlorophyll a concentrations and nutrients in Sarasota Bay were more 

complex than those observed in Roberts Bay, Little Sarasota Bay, and Blackburn Bay. This resulted 

from the spatial variability within Sarasota Bay and the influence of color on the relationship 

between chlorophyll a concentrations and TN concentrations in that segment. Therefore, 

application of the regression derived for Sarasota Bay to estimate the proposed numeric nutrient 

criterion is more complex. Since color influences the relationship between chlorophyll a 

concentrations and TN concentrations, the TN concentration that corresponds to the threshold 

chlorophyll a concentrations for Sarasota Bay will vary from year-to-year depending upon the 

ambient color observed in a year. 

To estimate the TN concentration that corresponds to the threshold chlorophyll a concentrations for 

Sarasota Bay, the mean color for each region and season was calculated for a given year. This 

mean color was used to calculate the TN concentration corresponding to the chlorophyll a

threshold for each region and season. The annual mean of these TN concentrations was calculated 

by weighting for the number of months in each season, as was done for Roberts Bay, Little Sarasota 

Bay, and Blackburn Bay. This weighted annual mean TN concentration is that TN concentration 

that corresponds to the chlorophyll a threshold concentration for a given year. These mean annual 

TN concentrations are the proposed numeric nutrient criterion for Sarasota Bay. 

Figures 2-4 presents a comparison of the proposed numeric criteria for Sarasota Bay expressed as an 

annual mean TN concentration, to the recent ambient geometric mean TN concentrations 

measured in Sarasota Bay. 

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

[TN] (mg/l)

Ambient [TN] (mg/l) [TN] Criterion (mg/l)

BLACKBURN BAY
Figure 2-4. Comparison of the proposed TN criterion to observed TN concentrations 

(expressed as geometric means) in Sarasota Bay.

2.3 Palma Sola Bay 

No significant quantitative relationship was found between chlorophyll a concentrations and either 

the TN or TP concentrations or loadings in Palma Sola Bay (Janicki Environmental, 2010). 

Therefore, the approach to derive a numeric nutrient criterion for Palma Sola Bay necessarily differs 

from that used for the other SBEP segments. 

The SBEP water quality subcommittee of the TAC considered three potential candidate methods for 

estimating the TN criterion for Palma Sola Bay: 

 The logistic regression results suggested wet and dry season TN concentrations of 0.57 mg/l 

and 1.31 mg/l, respectively. The annual mean, weighting for season, gives a result of 1.06 

mg/l as a candidate TN criterion. Note that the logistic model fit was weak – r2

=0.25. 

 The changepoint analysis identified a breakpoint in the TN concentrations of approximately 

0.76 mg/l. 

 Following the logic used by the subcommittee to establish chlorophyll a concentrations for 

the SBEP segments 

- the mean TN concentration for the 2001-2005 period was 0.74 mg/l 

- the standard deviation of the annual mean TN concentrations for the period of 

record was 0.19 mg/l 

- therefore, this method results in a candidate TN criterion of 0.93 mg/l. 

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

[TN] (mg/l)

Ambient [TN] (mg/l) [TN] Criterion (mg/l)

SARASOTA BAY
All three potential candidate methods give relatively similar results. 

The subcommittee recommended the third option – i.e., that based on the 2001-2005 ambient TN 

data. The full TAC concurred with the subcommittee’s recommendation on 23 July 2010. 

Figures 2-5 presents a comparison of the proposed numeric criteria for Palma Sola Bay expressed as 

an annual mean TN concentration, to the recent ambient geometric mean TN concentrations 

measured in Palma Sola Bay. 

Figure 2-5. Comparison of the proposed TN criterion to observed TN concentrations 

(expressed as geometric means) in Palma Sola Bay. 

3.0 Total Phosphorus Concentrations 

As described in Janicki Environmental (2011), multiple analyses were completed in the evaluation 

of potential TP criteria expressed as in-bay concentrations. The first set of analyses was performed 

to evaluate potential methods of deriving TP concentration criteria commensurate with the 

previously established TN concentration criteria and/or chlorophyll a thresholds. These included: 

 examination of the relationships between TN and TP concentrations within each segment, 

following the rationale that the TN concentration criteria had already been developed 

(Janicki Environmental, 2010) and relationships between TN and TP concentrations could 

provided TP concentration criteria; 

 examination of relationships between monthly TP concentrations with chlorophyll a

concentrations, with the potential to derive TP concentration criteria based on chlorophyll a

thresholds (Janicki Environmental, 2010); and 

 application of a reference period approach to establishing TP concentration criteria. 

0

0.2

0.4

0.6

0.8

1

1.2

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

[TN] (mg/l)

Ambient [TN] (mg/l) [TN] Criterion (mg/l)
The most appropriate method was determined to be the Reference Period approach. No 

relationships were found between TP and TN concentrations appropriate for developing TP 

concentration criteria as a function of the TN concentration criteria. Similarly, no relationships 

were found between TP concentrations and chlorophyll a concentrations appropriate for 

developing TP concentration criteria based on chlorophyll a thresholds. The Reference Period 

approach was utilized, with the period defined as the 2001-2005 period, as utilized for establishing 

the chlorophyll a thresholds. 

Following this approach, numeric nutrient criteria expressed as TP concentrations for the five bay 

segments were derived. Targets were based on 2001-2005 reference period data, and the standard 

deviations in each segment were based on the annual means. The TP concentration target, 

standard deviation, and threshold for each segment are provided in Table 3-1. 

Table 3-1. TP targets and thresholds based on the Reference Period approach. The reference 

period was 2001-2005.

Segment TP Target 

(mg/L) 

Standard Deviation of Long-term 

Annual TP Concentrations 

TP Threshold 

(mg/L) 

Palma Sola Bay 0.13 0.13 (1996-2008) 0.26 

Sarasota Bay 0.15 0.04 (1998-2008) 0.19 

Roberts Bay 0.19 0.04 (1998-2009) 0.23 

Little Sarasota Bay 0.18 0.03 (1998-2009) 0.21 

Blackburn Bay 0.17 0.04 (1998-2009) 0.21 

 

The proposed TP concentration criteria are compared to the observed geometric mean annual TP 

concentrations in Figures 2-1 through 2-5. The horizontal lines represent the proposed criteria. 

 

Figure 3-1. Comparison of proposed TP concentration criterion for Palma Sola Bay to the annual 

geometric mean TP concentrations from 1996 through 2008. 
Figure 3-2. Comparison of proposed TP concentration criterion for Sarasota Bay to the annual geometric 

mean TP concentrations from 1996 through 2008. 

Figure 3-3. Comparison of proposed TP concentration criterion for Roberts Bay to the annual geometric 

mean TP concentrations from 1998 through 2009. 
Figure 3-4. Comparison of proposed TP concentration criterion for Little Sarasota Bay to the annual 

geometric mean TP concentrations from 1998 through 2009. 

Figure 3-5. Comparison of proposed TP concentration criterion for Blackburn Bay to the annual geometric 

mean TP concentrations from 1998 through 2009. 
4.0 Total Nitrogen and Total Phosphorus Loadings 

As described in Janicki Environmental (2011), the simplest method to propose criteria expressed as 

loadings to bay segments is based on relationships between segment TN and TP concentrations and 

TN and TP loadings delivered to each segment. The current proposed TN concentration criteria 

and TP concentration criteria described above can be compared to TN and TP loadings to the 

segments. If significant relationships are found between the nutrient loads and their respective 

segment concentrations, then the proposed numeric nutrient criteria could be expressed as 

loadings. However, based on the limited relationships found between the nutrient concentrations 

and nutrient loads to those segments, the results of these analyses do not provide adequate 

evidence to support recommendations for TN and TP loading criteria. 

A second method evaluated to provide potential TN and TP criteria expressed as loadings to bay 

segments is based on relationships between segment chlorophyll a concentrations and TN and TP 

loads delivered to each segment. Chlorophyll a thresholds have been developed for the SBEP 

(Janicki Environmental, 2010), and may be used to derive loading criteria if appropriate 

relationships exist. The results of these analyses did not provide adequate evidence to support 

recommendations for TN and TP loading criteria based on the relationships between chlorophyll a

concentrations and TN and TP loadings in the bay segments. 

Establishment of loading-based nutrient criteria should be consistent with the chlorophyll a

threshold and concentration-based TN and TP criteria already proposed for Sarasota Bay. The third 

approach to developing loadings-based numeric nutrient criteria for both TN and TP is the 

reference period approach. Based on the methods used for development of the chlorophyll a

threshold and the proposed TP concentration criteria, loading targets and thresholds were 

developed. As with TP concentrations, the reference period was 2001-2005. Because loading data 

are available through 2008, the period used to calculate the standard deviation was 1998-2008. 

These loading criteria (thresholds) are considered to be commensurate with reference period TP 

concentrations proposed as criteria above, and with the reference period chlorophyll a thresholds 

developed previously (Janicki Environmental, 2010). The loading targets and standard deviations 

are presented in Table 4-1. By summing the target loads plus one standard deviation (Table 4-1), 

the loading criteria (thresholds) are obtained. The loading criteria for TN and TP are presented in 

Table 4-2 based on the 2001-2005 reference period. 

Table 4-1. Reference Period Loading-based TN and TP targets (2001-2005) and 

standard deviations (1998-2008). 

Segment 

TP Target 

(tons/yr) 

TP Standard 

Deviation 

(tons/yr) 

TN Target 

(tons/yr) 

TN Stadard 

Deviation 

(tons/yr) 

Palma Sola Bay 6.7 1.0 37.9 6.6 

Sarasota Bay 31.8 3.4 215.3 21.9 

Roberts Bay 42.4 6.4 213.3 37.5 

Little Sarasota Bay 7.3 1.6 40.3 9.2 

Blackburn Bay 9.3 2.3 55.4 15.6 
Table 4-2. Reference Period Loading-based TN and TP criteria.

Segment TP Load 

(tons/yr) 

TN Load 

(tons/yr) 

Palma Sola Bay 7.7 44.5 

Sarasota Bay 35.2 237.2 

Roberts Bay 48.8 250.8 

Little Sarasota Bay 8.9 49.5 

Blackburn Bay 11.6 71.0 

The proposed TN and TP loading criteria are compared to the observed annual TN and TP loadings 

in Figures 4-1 through 4-5. The horizontal lines represent the proposed criteria. 

Figure 4-1. Comparison of proposed TN and TP load criteria for Palma Sola Bay to annual loads.
Figure 4-2. Comparison of proposed TN and TP load criteria for Sarasota Bay to annual loads.
Figure 4-3. Comparison of proposed TN and TP load criteria for Roberts Bay to annual loads. 
Figure 4-4. Comparison of proposed TN and TP load criteria for Little Sarasota Bay to annual loads. 
Figure 4-5. Comparison of proposed TN and TP load criteria for Blackburn Bay to annual loads. 
5.0 References 

Janicki Environmental, Inc. 2010. Numeric Nutrient Criteria for Sarasota Bay. Prepared for 

Sarasota Bay Estuary Program, Sarasota, FL. 

Janicki Environmental, Inc. 2011. Sarasota Bay Numeric Nutrient Criteria: Task 1 – TN and TP 

Concentration and Loading Based Criteria. Prepared for the Sarasota Bay Estuary Program, 

Sarasota, FL. 
APPENDIX B. 

Data Description and 

Assessment of Seagrass, Water Quality, and Loadings 

1.0 Data Description 

This appendix provides identification and description of the seagrass, water quality, and loadings 

data utilized for establishing numeric nutrient criteria in the Sarasota Bay Estuary system. 

1.1 Seagrasses 

An estimate of seagrass extent is available for 1950, based on historic aerial photos. Recent trends 

in and persistence of seagrass throughout the SBEP were determined through analysis of GIS 

shapefiles based on aerial surveys executed biannually by the Southwest Florida Water 

Management District since 1988. Due to anthropogenic modifications in the estuary such as 

shoreline build-out and the dredging of the Intracoastal Waterway (ICW), certain areas have been 

altered to the extent that they have no reasonable potential for restoration; these so-called nonrestorable areas have been identified and removed from the analyses. 

The definition of the most appropriate seagrass targets was reached with input from the Technical 

Advisory Committee (TAC). The TAC recommended that the greater of either the historic or recent 

(2004-2006) seagrass coverages be established as the target in each segment. The sole exception to 

this rule was Little Sarasota Bay. Since 1984, the direct connection to the Gulf of Mexico (Midnight 

Pass) has been closed. This physical alteration may have contributed to the difference in seagrass 

coverage between the historic and current coverages. However, a recent FDEP decision precludes 

re-opening of this pass. Therefore, the recent coverage in Little Sarasota Bay has been established 

as the target. Table 1-1 presents the seagrass targets that were adopted by the SBEP Management 

and Policy boards. 

Table 1-1. SBEP seagrass coverage and targets. Unit of 

measure=acres. 

Bay Segment Historical 

(1950) 

Current 

2004-2006 

Average 

Seagrass 

Target 

Palma Sola 1,031 1,015 1,031 

Sarasota 7,269 7,041 7,269 

Roberts 283 348 348 

Little Sarasota 883 702 702 

Blackburn 273 447 447 

Total 9,739 9,552 9,997 

 
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Nutrient and hydrologic loads were estimated for the period 1988-2008 for the five bay segments 

within the greater Sarasota Bay watershed. Drainage basins for each bay segment were delineated 

based on drainage boundaries provided by Manatee and Sarasota counties. Nutrient loading 

estimates were derived for each of the 114 drainage basins using the Spatially Integrated Model for 

Pollutant Loading Estimates (SIMPLE) which was designed and calibrated by Jones Edmunds & 

Associates, Inc (JEA, 2009). 

The SIMPLE model consists of six modules that produce pollutant loading estimates for the primary 

point and non-point sources within a watershed: 1) Direct Runoff, 2) Baseflow, 3) Irrigation, 4) 

Point Source, 5) Septic Tanks, and 6) Atmospheric Deposition. We used the SIMPLE model to 

estimate nutrient loads for the first five sources, but calculated atmospheric deposition externally. 

Nutrient loads from the SIMPLE model were combined with loads from atmospheric deposition to 

estimate Total Nutrient Loads to each bay segment. 

Rainwater runoff and groundwater flow, both tightly coupled to precipitation, are the primary 

mechanisms by which nutrients are transported from the watershed to Sarasota Bay. In order to 

estimate nonpoint source nutrient loads related to these hydrologic processes, the Direct Runoff 

and Baseflow modules reference an externally generated table of monthly hydrologic values that 

estimate rainfall, runoff and baseflow for all combinations of land use and soil type in the Sarasota 

Bay watershed. 

2.0 Assessment of Conditions 

The following sections provide segment-specific comparisons of observed conditions to the 

seagrass targets, and summaries of TN, TP, and chlorophyll a concentrations and hydrologic, TN, 

and TP loadings for each SBEP segment. Times series of monthly mean values for each bay 

segment were produced to allow visual inspection of trends over time and to allow a comparison 

between bay segments. 

2.1 Seagrass 

The trend analyses show that in Palma Sola Bay, the seagrass coverage has remained very similar 

over the entire period of record (Figure 2-1). Sarasota Bay proper is currently at its highest seagrass 

level since 1950 and exceeds the baseline extent (Figure 2-2). The seagrass coverage in Roberts 

Bay (Figure 2-3) and Blackburn Bay (Figure 2-5) also increased since the baseline period. In 

contrast, Little Sarasota Bay (Figure 2-4) has shown a decline in seagrasses since 1950. 
Figure 2-1. Annual seagrass acreages in Palma Sola Bay. Horizontal line = seagrass target. 

Figure 2-2. Annual seagrass acreages in Sarasota Bay. Horizontal line = seagrass target.

0

200

400

600

800

1000

1200

1950 1988 1994 1999 2001 2004 2006

0

1000

2000

3000

4000

5000

6000

7000

8000

1950 1988 1994 1999 2001 2004 2006
Figure 2-3. Annual seagrass acreages in Roberts Bay. Horizontal line = seagrass target. 

Figure 2-4. Annual seagrass acreages in Little Sarasota Bay. Horizontal line = seagrass target. 

0

50

100

150

200

250

300

350

400

1950 1988 1994 1999 2001 2004 2006

0

100

200

300

400

500

600

700

800

900

1000

1950 1988 1994 1999 2001 2004 2006
Figure 2-5. Annual seagrass acreages in Blackburn Bay. Horizontal line = seagrass target. 

2.2 Total Nitrogen Concentrations 

Times series of monthly mean values for each bay segment were produced to allow visual 

inspection of trends over time and to allow a comparison between bay segments. Trends in TN 

concentrations were assessed using graphical plots and the seasonal Kendall Tau trend test (Hirsch 

et al., 1982; Hirsch and Slack, 1984). The seasonal Kendall Tau is a nonparametric test that 

estimates the median slope from all pair-wise comparisons in a timeseries of data. The statistical 

test accounts for seasonality and serial autocorrelation prior to evaluating the statistical significance 

of the trend in the time series. Therefore, the seasonal Kendall Tau is a sophisticated and robust 

method to evaluate trends in water quality data that often do not fit the assumptions necessary for 

the use of parametric statistics (e.g. linear regression). 

Time series plots of monthly TN concentrations are provided for each segment in Figures 2-6 

through 2-10. In Palma Sola Bay (Figure 2-6), the mean annual TN concentrations for the 1998-

2008 period averaged 0.77 mg/L. The lowest annual concentration (0.59 mg/L) occurred in 2004; 

the highest annual value of 1.09 mg/L occurred in the drought year of 2001. There was no 

significant trend in TN concentrations in Palma Sola Bay over this time period. 

The mean annual TN concentrations for the 1998 through 2009 period in Sarasota Bay averaged 

0.35 mg/L (Figure 2-7). The lowest annual value of 0.28 mg/L occurred in 2006, a moderately dry 

year. The highest mean annual concentration of 0.41 mg/L occurred in 2004, a somewhat wetter 

year. There was no statistically significant trend in TN concentrations in Sarasota Bay during this 

period. 

0

50

100

150

200

250

300

350

400

450

500

1950 1988 1994 1999 2001 2004 2006
The mean annual TN concentrations for the 1998 through 2009 period in Roberts Bay averaged 

0.43 mg/L (Figure 2-8). There was very little inter-annual variation in TN concentrations. The 

lowest annual value of 0.36 mg/L occurred in 2007 with the highest mean annual TN concentration 

of 0.48 mg/L observed in 2002. There was no statistically significant trend in TN concentrations in 

Roberts Bay during this period. 

The mean annual TN concentrations in Little Sarasota Bay for the 1998 through 2009 period 

averaged 0.49 mg/L (Figure 2-9). The lowest mean annual TN concentration of 0.43 mg/L was 

observed in 1998 while the highest mean annual TN concentration was 0.56 mg/L found in 2001. 

There was no statistically significant trend in Little Sarasota Bay TN concentrations during this 

period. 

The mean annual TN concentrations in Blackburn Bay during the 1998-2009 period in averaged 

0.34 mg/L (Figure 2-10). The lowest annual mean TN concentration of 0.26 mg/L occurred in 

1998. The highest annual mean concentration of 0.41 mg/L was observed in 2005. There was a 

statistically significant increasing trend in TN concentrations in Blackburn Bay during this period. 

Figure 2-6. Monthly TN concentrations (mg/L) in Palma Sola Bay. 
Figure 2-7. Mean monthly TN concentrations (mg/L) observed in Sarasota Bay. 

Figure 2-8. Mean monthly TN concentrations (mg/L) observed in Roberts Bay. 
Figure 2-9. Mean monthly TN concentrations (mg/L) observed in Little Sarasota Bay.

Figure 2-10. Mean monthly TN concentrations (mg/L) observed in Blackburn Bay.
2.3 Total Phosphorus Concentrations 

Times series of monthly mean TP values for each bay segment were produced to allow visual 

inspection of trends over time and to allow a comparison between bay segments. As for TN, trends 

in TP concentrations were assessed using graphical plots and the seasonal Kendall Tau trend test. 

Time series plots of monthly TP concentrations are provided for each segment in Figures 2-11 

through 2-15. 

Mean annual TP for the 1998-2008 period in Palma Sola Bay (Figure 2-11) averaged 0.16 mg/L. 

The lowest annual value (0.07 mg/L) occurred in 2004, a moderately wet year. The highest annual 

value (0.33 mg/L) occurred in 2008. A statistically significant, but slight increasing trend in TP 

concentrations was observed during the 1998-2008 period. 

Mean annual TP concentrations for the 1998-2009 period in Sarasota Bay averaged 0.13 mg/L 

(Figure 2-12). The lowest mean annual concentration of 0.06 mg/L occurred in 2009, while the 

highest annual value, 0.22 mg/L, occurred in 2002. There was a statistically significant but slight 

decreasing trend in Sarasota Bay TP concentrations during this period. 

Mean annual TP concentrations for the 1998 through 2009 period in Roberts Bay averaged 0.17 

mg/L (Figure 2-13). The lowest mean annual TP concentration (0.09 mg/L) occurred in 2009 and 

the highest annual mean annual (0.22 mg/L) was observed in 2001. There was a significant 

decreasing trend in Roberts Bay TP concentrations during this period. 

Mean annual TP concentrations in Little Sarasota Bay averaged 0.17 mg/L during the 1998-2009 

period (Figure 2-14). The lowest mean annual TP concentration was 0.09 mg/L in 2009; while the 

highest mean annual concentration was 0.22 mg/L in 1999. There was a statistically significant 

decreasing trend in Little Sarasota Bay TP concentrations during this period. 

The annual mean TP concentrations in Blackburn Bay averaged 0.15 mg/L during the 1998-2009 

period (Figure 2-15). The lowest annual mean of 0.06 mg/L occurred in 2009. The highest annual 

mean TP concentration was 0.21 mg/L and was observed in 2001. There was no statistically 

significant trend in Blackburn Bay TP concentrations during this period. 
Figure 2-11. Mean monthly TP concentrations (mg/L) observed in Palma Sola Bay. 

Figure 2-12. Mean monthly TP concentrations (mg/L) observed in Sarasota Bay. 

 
Figure 2-13. Mean monthly TP concentrations (mg/L) observed in Roberts Bay. 

Figure 2-14. Mean monthly TP concentrations (mg/L) observed in Little Sarasota Bay.
Figure 2-15. Mean monthly TP concentrations (mg/L) observed in Blackburn Bay.

2.4 Chlorophyll a

Times series of monthly mean chlorophyll a values for each bay segment were produced to allow 

visual inspection of trends over time and to allow a comparison between bay segments. As for TN 

and TP concentrations, trends in chlorophyll a concentrations were assessed using graphical plots 

and the seasonal Kendall Tau trend test. Time series plots of monthly chlorophyll a concentrations 

are provided for each segment in Figures 2-16 through 2-20. 

Mean annual chlorophyll a concentrations for the 1998-2008 period in Palma Sola Bay averaged 

8.25 μg/L (Figure 2-16). The lowest annual value of 4.89 μg/L occurred in 2005, a significantly wet 

year. Lower chlorophyll concentrations may be expected if higher volumes of freshwater are 

reducing residence time on an annual basis. The highest annual value, 11.3 μg/L, occurred in 

1998, also a wet year. A significant decreasing trend in chlorophyll a concentrations was observed 

during the 1998-2008 period. 

Mean annual chlorophyll a for the 1998 through 2009 period in Sarasota Bay averaged 5.0 μg/L 

(Figure 2-17). The lowest annual value of 3.3 μg/L occurred in 2006, a year of moderate rainfall. 

The highest annual value, 6.0 μg/L, occurred in 2009, a dry year. There was a statistically 

significant but slight decreasing trend in chlorophyll a concentrations in Sarasota Bay during this 

period. 

Mean annual chlorophyll a concentrations for the 1998-2009 period in Roberts Bay averaged 7.3 

μg/L (Figure 2-18). The lowest mean annual concentration of 3.6 μg/L occurred in 2007, a dry year. 

The highest mean annual concentration, 11.6 μg/L, occurred in the drought year of 2001. There 
was no statistically significant trend in chlorophyll a concentrations in Roberts Bay during this 

period. 

Mean annual chlorophyll a concentrations averaged 7.3 μg/L in Little Sarasota Bay during the 1998-

2009 period (Figure 2-19). The lowest mean annual chlorophyll a concentration of 4.9 μg/L 

occurred in 2007 and the highest mean annual chlorophyll a concentration, 11.2 μg/L, occurred in 

2001. There was a statistically significant but slight decreasing trend in chlorophyll a 

concentrations in Little Sarasota Bay during this period. 

Mean annual chlorophyll a concentrations for the 1998-2009 period in Blackburn Bay averaged 5.3 

μg/L (Figure 2-20). The lowest annual mean chlorophyll a concentration was 3.0 μg/L and occurred 

in 2007. The highest annual mean chlorophyll a concentration was 9.3 μg/L and was observed in 

2001. There was a significant decreasing trend in chlorophyll a concentrations in Blackburn Bay 

during this period. 

Figure 2-16. Mean monthly chlorophyll a concentrations (μg/L) observed in Palma Sola Bay. 
Figure 2-17. Mean monthly chlorophyll a concentrations (μg/L) observed in Sarasota Bay. 

Figure 2-18. Mean monthly chlorophyll a concentrations (μg/L) observed in Roberts Bay. 
Figure 2-19. Mean monthly chlorophyll a concentrations (μg/L) observed in Little Sarasota Bay. 

Figure 2-20. Mean monthly chlorophyll a concentrations (μg/L) observed in Blackburn Bay. 
2.5 Hydrologic, Total Nitrogen, and Total Phosphorus Loadings 

Hydrologic and nutrient loads were estimated for the period 1989-2008 for five bay segments 

within the SBEP area. The total annual hydrologic, TN, and TP loads to each bay segment are 

presented in Figures 2-21 through 2-23. 

The highest annual hydrologic loads to Palma Sola Bay were observed during wetter years 

(generally >55 inches) of 1992, 1995, and 2003 (Figure 2-21). Drier years, in terms of total rainfall 

(<40 inches), occurred in 1990, 1999, 2000, and 2007 and corresponded to the lowest observed 

hydrologic loads during those years. As expected, the highest annual nutrient loadings for TN and 

TP were observed during years of peak hydrologic loads in 1988, 1992, 1995, 2003, and 2005 

(Figures 2-22 and 2-23) 

As with Palma Sola Bay, higher-than-average annual hydrologic loads to Sarasota Bay were 

observed during wetter years of 1992, 1995, and 2003, as well as 2005 (Figure 2-21). Drier years 

occurred in 1990, 1999, 2000, and 2007 and corresponded to the lowest observed hydrologic 

loads during those years. The highest annual nutrient loadings for TN and TP were observed during 

years of peak hydrologic loads in 1992, 1995, 2003, and 2005 (Figures 2-22 and 2-23). Sarasota 

Bay also had noticeably higher than average TN loadings in 1989 despite an average hydrologic 

load that year. 

The highest annual hydrologic loads to Roberts Bay were observed during wetter years of 1992, 

1995, 2003, and 2005 (Figure 2-21). Drier years occurred in 1990, 1999, 2000, and 2007 and 

corresponded to the lowest observed hydrologic loads during those years. The highest annual 

nutrient loadings for TN and TP were observed in 1992, 1995, 2003, and 2005 during years of 

peak hydrologic loads (Figures 2-22 and 2-23). Higher than average annual nutrient loads were 

also observed during 1997 for Roberts Bay. 

Little Sarasota Bay received the highest annual hydrologic loads during 1992, 1995, 2003, and 

2005 (Figure 2-21). The highest TN and TP loads were observed during the same years (Figures 2-

22 and 2-23). Lowest hydrologic loads occurred in 1990, 1999, 2000, and 2007. 

Blackburn Bay received the highest annual hydrologic loads during 1992, 1995, 2003, and 2005 

(Figure 2-21). As was the case throughout the greater Sarasota Bay watershed, the lowest 

hydrologic loads to Blackburn Bay were observed in 1990, 1999, 2000, and 2007. The highest 

annual loadings for TN and TP were observed in 1992, 1995, 2003, and 2005 (Figures 2-22 and 2-

23). Higher than average annual nutrient loads were also observed during 1997 for Blackburn Bay. 

 
Figure 2-21. Annual hydrologic loads by bay segment. BB=Blackburn Bay, 

LS=Little Sarasota Bay, PS=Palma Sola Bay, RB=Roberts Bay, SB=Sarasota Bay. 

Figure 2-22. Annual TN loadings by bay segment. BB=Blackburn Bay, LS=Little Sarasota Bay, 

PS=Palma Sola Bay, RB=Roberts Bay, SB=Sarasota Bay. 
Figure 2-23. Annual TP loadings by bay segment. BB=Blackburn Bay, LS=Little Sarasota Bay, 

PS=Palma Sola Bay, RB=Roberts Bay, SB=Sarasota Bay. 

3.0 References 

Hirsch, R.M., J.R. Slack, and R.A. Smith. 1982. Techniques of trend analysis for onthly water 

quality data. Water Resources Research. 18:107-121. 

Hirsch, R.M. and J.R. Slack. 1984. A nonparametric trend test for seasonal data with serial 

dependence. Water Resources Research. 20:727-732. 

Jones Edmunds & Associates. 2009. Sarasota County Pollutant Loading Model Development 

(W552) SIMPLE-Monthly Design Report. Prepared for Sarasota County and Southwest Florida 

Water Management District. 49pp. 
APPENDIX C. 

Implementation Issues: 

Targets, Thresholds, Type I Error and 

Compliance Assessment for Numeric Nutrient Criteria 

Using the Reference Period Approach 

Background 

Site specific numeric nutrient criteria for individual estuarine water bodies in southwest Florida 

from Saint Joseph Sound in Clearwater, Florida through Estero Bay, Florida are being proposed as 

alternatives to the application of regional or state wide model based standards. These site specific 

criteria rely on the identification of a response endpoint and the endpoint defined for these 

estuaries has been defined as a threshold chlorophyll a concentration in all cases. The temporal 

scale has been defined as yearly; therefore, the assessment statistic is an annual average chlorophyll 

a concentration. Generally, the geometric annual average is used; however, in cases where the data 

are first averaged monthly, a simple arithmetic average is used. These threshold chlorophyll a

concentrations for all estuaries have been identified using a reference period approach. Subsequent 

numeric nutrient criteria have been developed either by applying a stressor response relationship 

between nutrients and chlorophyll a concentrations, or by simply calculating an average of the 

annual averages of the reference period. 

The reference period approach relies on the identification of a period in time when these estuarine 

water bodies were sufficient to support full aquatic life uses. The overarching logic is that, provided 

a reliable stressor response model cannot be developed to accurately predict that point at which a 

system would no longer meet its full aquatic life use, water quality conditions during of a period in 

time when that waterbody was meeting its designated use would be protective of full aquatic life 

uses. For example, the estuarine open water segment of Saint Joseph Sound has been meeting full 

aquatic life uses according to FDEP water quality standards and the Impaired Waters Rule since 

2003. This means that chlorophyll a concentrations (Chla) have been below an annual average of 

11 μg/L and dissolved oxygen concentrations (DO) have been above 4 mg/L in at least 90% of the 

samples. These “endpoints” (i.e., Chla and DO) are typical indicators used to assess the health of 

estuarine waters. The period of time between 2003 and 2009 was therefore chosen as the reference 

period for Saint Joseph Sound. 

To establish numeric nutrient criteria using the reference period approach, a period of time would 

be identified when the waterbody was meeting its designated use, parameters would be defined to 

characterize the population of water quality values for chlorophyll a, total nitrogen (TN) and total 

phosphorus (TP) during that time, and then threshold values would be defined to represent a 

deviation from the expected condition of the reference period. The following paragraphs provide 

an example of how targets, thresholds and the type I error, and compliance assessment procedures 

have been established using the reference period approach. 

Reference Period Example 

To begin this example, a hypothetical reference period distribution of chlorophyll a concentrations 

was generated. Chlorophyll a concentrations in estuaries typically exhibit “lognormal” distribution 
character

becomes

lognorma

and a sta

in Figure

correspon

Protectio

geometric

chloroph

hypothet

Given th

product o

from the

obtain th

selecting

close to t

know tha

annual av

of annua

expected

ristics. This 

normally d

al distributio

ndard deviat

e 1. Once t

nding to the

n (FDEP) an

c means as

yll a, we no

ical evaluatio

e theoretica

of a typical 

distribution

he geometric

12 samples

the overall a

at variability 

verages from

l averages is

. 

Fi

implies that 

distributed w

n of chlorop

tion of 4.49 

he data are

normal distr

nd the Enviro

 regulatory 

ow consider

on and back

l distribution

monitoring p

of log value

c mean. F

and calcula

average of th

will exist du

m the referenc

s centered o

igure 1. Simu

when a natu

which confor

phyll a conc

μg/L. This d

natural log

ribution (Figu

onmental Pr

statistics fo

the log tran

transform th

n of Figure 

program. Fo

es, and calc

urther, we c

ting the aver

e reference 

ue to samplin

ce period dis

n a value ve

ulated distribu

ural log trans

rms to most

centrations w

istribution co

g transformed

ure 2). Since

rotection Ag

or parameter

nsformed val

he averages to

2, we can g

or example, 

culate an ave

can repeat 

rage of the l

period since

ng. For exam

stribution. A

ery close to

ution of chloro

sformation is

t parametric

was simulate

omposed of

d, the distri

 the Florida 

gency (EPA) 

rs with logn

ues to repre

o obtain the

generate ann

we can rand

erage and ba

this experim

og values. W

e it is a rando

mple, in Figu

s can be see

the overall 

ophyll a conc

s applied to t

statistical te

d using a m

10000 obse

bution beco

Department

have propo

normal distr

esent the dat

geometric m

nual average

domly selec

ack transform

ment many 

We expect ea

om sub-sam

ure 3, we ha

en in Figure 3

average in F

centrations. 

the distributi

ests. Therefo

mean of 6.75

ervations is sh

omes bell sh

of Environm

sed using an

ributions suc

ta underlying

means. 

es to simulat

ct 12 observa

m that avera

times, each

ach average 

ple, howeve

ave generated

3, the distrib

Figure 2 wh

ion, it 

ore, a 

5 μg/L 

hown 

haped 

mental 

nnual 

ch as 

g this 

te the 

ations 

age to 

time 

to be 

er, we 

d 100 

bution 

ich is 
Figu

Figure 3.

re 2. Distribu

 Distribution

tion of the na

 of 100 annua

tural log tran

l averages of

sformed valu

f the log trans

per year. 

ues of the sim

sformed chlor

ulated distrib

ophyll values

ution above.

 using 12 samples 
To derive

3. This di

Targets a

Once the

targets an

 

The refer

geometric

to the re

However

populatio

can be c

averages

value to 

was from

Using the

standard 

deviation

distributio

exceed to

distributio

e the geomet

istribution is

Figure 4. Geo

and Threshol

e geometric m

nd threshold

rence period

c means. Tha

eference peri

r, it can be 

on ranges be

considered a

of the refere

represent an

m the same 

e z table of 

deviation of

n of the popu

on that defin

o reject the

on that thres

tric annual a

shown in Fig

ometric mean

ds 

means have 

ds for this the

d target for 

at is, 5.947 μ

iod conditio

seen from F

etween 3.9 μ

a population

ence period.

n annual ave

population a

standard sta

f the distribu

ulation of geo

nes with 95%

hypothesis 

shold value e

averages, we

gure 4. 

ns taken from 

been calcula

eoretical refe

this distribut

μg/L is our go

on we identi

Figure 4 that

μg/L and 8.3

n of values

 Based on n

erage above 

as the refere

atistical tests,

ution in Figu

ometric mea

% confidence

that it belo

equals 7.59 μ

e simply back

the simulated

ated we have

rence period

tion can be

oal for the w

fied as bein

t the distribu

μg/L. There

that represe

normal distri

which we w

ence period 

, only 5% o

ure 4 would

ns. Therefor

e what value

onged to the

μg/L. 

k transform t

d chlorophyll 

e all the info

d distribution

defined as t

water body to

ng indicative

ution of ann

efore, the dis

ent the exp

bution theor

would reject 

distribution

of a normal d

d lie above t

re, a thresho

e a given ge

e reference 

the annual a

concentration

ormation nec

n. 

the overall a

o ensure that

e of full aqu

ual geometr

stribution of

pected distrib

ry, we can a

the hypothe

of annual g

distribution 

the mean+1

old can be co

eometric mea

period distri

averages of F

ns above. 

cessary to dev

average of a

it remains si

uatic life sup

ric means fo

geometric m

bution of an

assign a thre

esis that the 

geometric m

with a mean

1.65*the stan

onstructed fo

an would ne

ibution. Fo

Figure 

velop 

all the 

imilar 

pport. 

or this 

means 

nnual 

eshold 

value 

means. 

n and 

ndard 

or this 

eed to 

r this 
The threshold value provides a level of certainty that a future single geometric mean value (i.e. a 

sample) is not declared to exceed the reference distribution simply due to sampling. As was 

demonstrated above, we know that some portion of the reference distribution values will be above 

the target value. In fact, nearly 50% of the annual geometric means will be higher than the target. 

However, only 5% of the values will be higher than the threshold value of 7.59 μg/L due to 

chance. This construct defines what is known as the Type I error rate or False Positive rate. That 

is, we are willing to accept that 1 in 20 times we may get a value that is higher than 7.59 μg/L that 

still belongs to the reference period distribution. As was seen in Figure 4, 5% of the values did 

exceed 7.59 μg/L even though we know the entire population of values. 

Therefore, the type I error rate is a value that is selected based on judgment and while 5% is 

typically used, there is no definitive rationale for 5% versus 1% or 10%. If we wish to be more 

conservative, we would select a lower type I error rate by choosing a larger value (e.g., 1.96) to 

multiple against the standard deviation to minimize the potential for falsely declaring that a value 

was different from the reference distribution. If we have reason to believe that the water body may 

not fully meet its designated use at values at the higher end of the reference distribution, one could 

select a higher type I error rate which in turn would equate to a smaller z score to multiply by the 

standard deviation (e.g., 1). For example, selecting 1 standard deviation equates to a type 1 error 

rate of 16%. However, the type 1 error rate does have implications on the compliance assessment. 

Compliance Assessment 

 

Now that the definition of targets, thresholds, and type 1 error has been identified, there is another 

consideration that must be taken into account when evaluating criteria exceedances. The 

exceedance frequency for an exceedance due to chance is defined by the type 1 error rate as 

described above. However, the exceedance frequency and duration component also must be 

established to allow for some anomalous condition unrelated to anthropogenic activity such as an 

El Niño, or La Niña cycles. There is substantial evidence that these meteorological anomalies can 

result in higher chlorophyll a concentrations (e.g., Morrison et al. 2006, Sherwood 2010). 

Therefore, this type of exceedance is different from the type I error described above. Since we have 

previously defined the type I error rate, we have already made the choice as to the false positive 

rate we are willing to accept. The implementation question is now posed to ask “what is the 

frequency of exceedances and assessment cycle that allows for occurrences unrelated to local 

anthropogenic activities but remains sensitive to capturing population deviations from the reference 

period due indicative of human adverse effects?” 

To address this question the Multivariate ENSO Index calculated by Klaus Wolter of the National 

Oceanic and Atmospheric Administration (see Wolter and Timlin 1993) was used as described in 

several implementation documents produced by Janicki Environmental regarding implementation 

of numeric nutrient criteria (Janicki Environmental, Inc. 2011a-c). It is easy to see in Figure 5 that 

when El Niño or La Niña events occur they tend to last more than a single year. In fact, it’s quite 

possible for many of the single events to cross a calendar year. Further information on the 

frequency and duration of ENSO events can be found at: http://www.esrl.noaa.gov/psd/enso/mei/
Figure

Based on

result in 

one year

allowanc

2 exceed

It is poss

such that

exceedan

one migh

to a natu

pursued 

threshold

criteria ar

of the 2 i

e 5. Classifica

n this analys

higher annu

r in a 5 yea

e as an exce

ances in a 5

ible that the

t both the pr

nce occurs d

ht calculate t

ural anomaly

as the impl

d values with

re inextricab

n 5 impleme

ation of El Niñ

is, it makes

al geometric

ar cycle as 

eedance freq

year assessm

type I error 

robability of 

ue to anoma

he union pro

y. This was 

ementation 

h known typ

bly linked and

entation rule

ño and La Niñ

sense to all

c average tha

is currently

uency in a fi

ment cycle. 

rate and the

f an exceeda

alous condit

obability of a

beyond the

process is r

pe 1 error ra

d should not

is provided 

ña events as de

low for the 

an the refere

y proposed b

ve year asse

e probability

ance occurrin

ions could b

an exceedan

scope of th

refined. Beca

ates, the crit

t be separate

in Janicki En

escribed in Ja

potential tha

ence period 

by FDEP.

essment cycle

of an anoma

ng by chanc

be integrated

ce due to ch

his memoran

ause the pro

eria and the

ed. Further in

nvironmental

anicki Environ

at an anoma

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Therefore th

e is to allow

alous event 

ce and the p

d. That is, ov

hance and an

ndum but o

oposed crite

e 2 in 5 yea

nformation s

 (2011). 

nmental 2011a

alous event c

alue in more

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for no more

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probability th

ver a 5 year

n exceedance

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upporting th

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cycle 

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he use 
References 

Janicki Environmental, Inc. 2011a. Sarasota Bay Numeric Nutrient Criteria: Task 4 - 

Implementation Issues. Letter Memorandum Prepared for Sarasota Bay Estuary Program. Sarasota, 

Florida 

Janicki Environmental, Inc. 2011b. Charlotte Harbor Numeric Nutrient Criteria: Implementation 

Issues. Letter Memorandum Prepared for Charlotte Harbor Estuary Program. Ft. Myers, Florida 

Janicki Environmental, Inc. 2011c. Tampa Bay Numeric Nutrient Criteria: Task 4 – 

Implementation Issues. Letter Memorandum. Prepared for: Tampa Bay Estuary Program. 

Morrison, G., E.T. Sherwood, R. Boler, and J. Barron. 2006. Variations in water clarity and 

chlorophyll a in Tampa Bay, Florida, in response to annual rainfall, 1985-2004. Estuaries and 

Coasts. 29:926-931. 

Sherwood, E.T. 2010. 2009 Tampa Bay Water Quality Assessment. 2010. Technical Report #02-10 

of the Tampa Bay Estuary Program. Prepared by the Tampa Bay Estuary Program. 

Wolter, K., and M.S. Timlin, 1993: Monitoring ENSO in COADS with a seasonally adjusted 

principal component index. Proc. of the 17th Climate Diagnostics Workshop, Norman, OK, 

NOAA/NMC/CAC, NSSL, Oklahoma Clim. Survey, CIMMS and the School of Meteor., Univ. 

of Oklahoma, 52-57. 

Download PDF.http://www.esrl.noaa.gov/psd/people/klaus.wolter/MEI/#ref_wt1
APPENDIX D. 

Tables and Maps of 

Manatee County and Sarasota County 

Monitoring Sites Utilized for 

Water Quality Assessment in 

Each Segment 

   
Palma Sola Bay – Manatee County Monitoring 

Station Location Year Month 

1 2 3 4 5 6 7 8 9 10 11 12 

458 27.49700, -82.65683 1995 X 

1996 X X X X 

1997 X X X 

1998 X X X X 

1999 X X X X X 

2000 X X X X 

2001 X X X 

2002 X X X X 

2003 X X X X 

2004 X X X 

2005 X X X X 

2006 X X X X 

2007 X X X X 

2008 X X X X 

587 27.47319, -82.64874 1996 X X X X X 

1997 X X X X 

1998 X X X 

1999 X X X X 

2000 X X X X 

2001 X X X X 

2002 X X X X X 

2003 X X X X 

2004 X X X X X 

2005 X X X X 

2006 X X X X 

2007 X X X X 

2008 X X X X 

589 27.48150, -82.68308 1995 X 

1996 X X X 

1997 X X X X 

1998 X X X 

1999 X X X X 

2000 X X X X 

2001 X X X 

2002 X X X X 

2003 X X X X 

2004 X X X 

2005 X X X X X 

2006 X X X X 

2007 X X X X 

2008 X X X X 

   
Palma Sola Bay – Manatee County Monitoring (continued) 

Station Location Year Month 

1 2 3 4 5 6 7 8 9 10 11 12 

590 27.46900, -82.66367 1995 X 

1996 X X X 

1997 X X X 

1998 X X X X 

1999 X X X X 

2000 X X X X 

2001 X X X X 

2002 X X X 

2003 X X X X 

2004 X X X X 

2005 X X X X 

2006 X X X X 

2007 X X X X 

2008 X X X X 

   
Sarasota Bay – Manatee County Monitoring 

Station Location Year Month 

1 2 3 4 5 6 7 8 9 10 11 12 

464 27.49604, -82.69544 1995 X 

1996 X X X 

1997 X X X X 

1998 X X X X 

1999 X X X X 

2000 X X X X 

2001 X X X X 

2002 X X X X 

2003 X X X X 

2004 X X X X 

2005 X X X X 

2006 X X X X 

2007 X X X X 

2008 X X X X 

597 27.41525, -82.59467 1996 X X X X X 

1997 X X X 

1998 X X X 

1999 X X X X 

2000 X X X X 

2001 X X X X 

2002 X X X 

2003 X X X X 

2004 X X X X 

2005 X X X X 

2006 X X X X 

2007 X X X X 

2008 X X X X 

598 27.43558, -82.63981 1995 X 

1996 X X X X 

1997 X X X X 

1998 X X X 

1999 X X X X 

2000 X X X X 

2001 X X X X 

2002 X X X X 

2003 X X X X 

2004 X X X X 

2005 X X X 

2006 X X X X 

2007 X X X X 

2008 X X X X 

   
Sarasota Bay – Manatee County Monitoring (continued) 

Station Location Year Month 

1 2 3 4 5 6 7 8 9 10 11 12 

600 27.41875, -82.60593 1995 X 

1996 X X X 

1997 X X X X 

1998 X X X 

1999 X X X X 

2000 X X X X 

2001 X X X X 

2002 X X X X X 

2003 X X X X 

2004 X X X 

2005 X X X X 

2006 X X X X 

2007 X X X X 

2008 X X X X 

604 27.40242, -82.58064 1996 X X X X 

1997 X X X X 

1998 X X X X 

1999 X X X X 

2000 X X X X 

2001 X X X X 

2002 X X X X 

2003 X X X X 

2004 X X X 

2005 X X X X 

2006 X X X X 

2007 X X X X 

2008 X X X X 

607 27.39904, -82.60052 1995 X 

1996 X X X 

1997 X X X X 

1998 X X X X 

1999 X X X X 

2000 X X X X 

2001 X X X X 

2002 X X X X 

2003 X X X X 

2004 X X X X X 

2005 X X X X 

2006 X X X X 

2007 X X X X 

2008 X X X X 

   
Sarasota Bay – Manatee County Monitoring (continued) 

Station Location Year Month 

1 2 3 4 5 6 7 8 9 10 11 12 

608 27.38020, -82.59224 1995 X X 

1996 X X X X 

1997 X X X X 

1998 X X X X 

1999 X X X X X 

2000 X X X X 

2001 X X X X 

2002 X X X X 

2003 X X X X 

2004 X X X 

2005 X X X X 

2006 X X X X 

2007 X X X X 

2008 X X X X 

658 27.48112, -82.69929 1996 X X X X X 

1997 X X X X 

1998 X X X 

1999 X X X X 

2000 X X X X 

2001 X X X 

2002 X X X X 

2003 X X X 

2004 X X X X X 

2005 X X X X 

2006 X X X X 

2007 X X X X 

2008 X X X X 

659 27.46650, -82.68750 1995 X 

1996 X X X X 

1997 X X X X 

1998 X X X X 

1999 X X X X X 

2000 X X X X 

2001 X X X X 

2002 X X X 

2003 X X X X 

2004 X X X X 

2005 X X X X 

2006 X X X X 

2007 X X X X 

2008 X X X X 

   
Sarasota Bay – Manatee County Monitoring (continued) 

Station Location Year Month 

1 2 3 4 5 6 7 8 9 10 11 12 

660 27.45332, -82.67522 1995 X 

1996 X X X X 

1997 X X X X 

1998 X X X 

1999 X X X X 

2000 X X X X 

2001 X X X 

2002 X X X X X 

2003 X X X X 

2004 X X X X X 

2005 X X X X 

2006 X X X X 

2007 X X X X 

2008 X X X X 

667 27.43714, -82.66078 1996 X X X X X 

1997 X X X 

1998 X X X X 

1999 X X X X X 

2000 X X X X 

2001 X X X X 

2002 X X X X 

2003 X X X X 

2004 X X X 

2005 X X X X 

2006 X X X X 

2007 X X X X 

2008 X X X X 

668 27.42152, -82.64686 1996 X X X 

1997 X X X X 

1998 X X X X 

1999 X X X X 

2000 X X X X 

2001 X X X X 

2002 X X X X 

2003 X X X X 

2004 X X X X X 

2005 X X X X 

2006 X X X X 

2007 X X X X 

2008 X X X 

   
Sarasota Bay – Manatee County Monitoring (continued) 

Station Location Year Month 

1 2 3 4 5 6 7 8 9 10 11 12 

669 27.41117, -82.64317 1995 X 

1996 X X X X 

1997 X X X 

1998 X X X X 

1999 X X X X X 

2000 X X X X 

2001 X X X X 

2002 X X X X 

2003 X X X 

2004 X X X X X 

2005 X X X X 

2006 X X X X 

2007 X X X X 

2008 X X X X 

676 27.39768, -82.62686 1996 X X X X X 

1997 X X X X 

1998 X X X X 

1999 X X X X X 

2000 X X X X 

2001 X X X X 

2002 X X X 

2003 X X X X 

2004 X X X X 

2005 X X X X 

2006 X X X X 

2007 X X X X 

2008 X X X X 

   
Sarasota Bay – Sarasota County Monitoring, January-June 

Station Location 

January February March April May June 

10-1 27.34662,

‐82.58386

27.35361,

‐82.57388

27.35334,

‐82.58079

27.34649,

‐82.58940

27.34539,

‐82.57901

27.35884,

‐82.57789

10-2 27.34507,

‐82.56928

27.34098,

‐82.56656

27.33487,

‐82.56876

27.33876,

‐82.57272

27.33905,

‐82.57277

27.33852,

‐82.56789

10-3 27.33112,

‐82.58462

27.33438,

‐82.57998

27.32844,

‐82.58688

27.33883,

‐82.58128

27.33421,

‐82.57938

27.3252,  

‐82.58018

10-4 27.31723,

‐82.56625

27.31019,

‐82.56429

27.32557,

‐82.56707

27.32571,

‐82.56717

27.32673,

‐82.56785

27.32441,

‐82.55596

10-5 27.31366,

‐82.55307

27.30761,

‐82.55623

27.30747,

‐82.54939

27.30447,

‐82.55538

27.31689,

‐82.55359

27.31206,

‐82.55169

11-1 27.35841,

‐82.56685

27.36783,

‐82.56561

27.36094,

‐82.57067

27.36327,

‐82.56689

27.36058,

‐82.57022

27.37032,

‐82.56841

11-2 27.35354,

‐82.55847

27.34727,

‐82.55640

27.34770,

‐82.56161

27.35432,

‐82.56184

27.34440,

‐82.5629

27.35302,

‐82.56599

11-3 27.34038,

‐82.55334

27.33591,

‐82.55658

27.33708,

‐82.56055

27.34309,

‐82.55347

27.34022,

‐82.55848

27.33358,

‐82.55878

11-4 27.32574,

‐82.55068

27.32305,

‐82.54990

27.32567,

‐82.54475

27.31827,

‐82.54685

27.32823,

‐82.54878

27.32388,

‐82.54816

11-5 27.30577,

‐82.54215

27.31270,

‐82.54251

27.31328,

‐82.54573

27.30974,

‐82.54561

27.30490,

‐82.54369

27.31187,

‐82.54505

7-1 27.37763, 

-82.60928 

27.38528,

‐82.61878

27.37768, 

-82.60438 

27.37572, 

-82.61023 

27.36905, 

-82.61430 

27.37482, 

-82.60818 

7-2 27.36627, 

-82.59251 

27.36948, 

-82.59851 

27.36055, 

-82.60065 

27.36163, 

-82.59953 

27.36777, 

-82.59883 

27.36767, 

-82.59352 

8-1 27.37630, 

-82.58350 

27.38169, 

-82.57971 

27.38850, 

-82.58593 

27.38045, 

-82.58578 

27.37688, 

-82.58288 

27.37815, 

-82.58418 

8-2 27.38346, 

-82.57163 

27.38079, 

-82.57216 

27.37888, 

-82.57587 

27.38017, 

-82.56623 

27.37287, 

-82.57583 

27.37682, 

-82.57575 

US-1 27.38590,

‐82.62170

27.36690,

‐82.61510

27.38850,

‐82.60500

27.37580,

‐82.61330

27.38790,

‐82.63550

27.38430,

‐82.60880

US-2 27.37240,

‐82.60940

27.37460,

‐82.59480

27.37970,

‐82.59840

27.37200,

‐82.58750

27.37000,

‐82.59940

27.37470,

‐82.60490

US-3 27.37630,

‐82.58350

27.38169,

‐82.57971

27.38850,

‐82.58593

27.38045,

‐82.58578

27.37688,

‐82.58288

27.37815,

‐82.58418

US-4 27.38346,

‐82.57163

27.38079,

‐82.57216

27.37888,

‐82.57587

27.38017,

‐82.56623

27.37287,

‐82.57583

27.37682,

‐82.57575

US-5 27.35110,

‐82.59440

27.36060,

‐82.58990

27.35590,

‐82.59880

27.35650,

‐82.60500

27.35830,

‐82.59430

27.36290,

‐82.59770

   
Sarasota Bay – Sarasota County Monitoring, July-December 

Station Location 

July August September October November December 

10-1 27.34424,

‐82.58265

27.35439,

‐82.58502

27.3455,

 ‐82.59462

27.35317,

‐82.58200

27.35917,

‐82.57619

27.34934,

‐82.58149

10-2 27.34924,

‐82.56986

27.33525,

‐82.56750

27.34412,

‐82.57124

27.33932,

‐82.56744

27.34747,

‐82.56917

27.34128,

‐82.56857

10-3 27.33400,

‐82.58137

27.33128,

‐82.58449

27.33926,

‐82.58047

27.33075,

‐82.58471

27.33983,

‐82.58141

27.33483,

‐82.57905

10-4 27.32052,

‐82.56628

27.32936,

‐82.56975

27.31507,

‐82.56589

27.31177,

‐82.56508

27.32254,

‐82.57461

27.32844,

‐82.56228

10-5 27.30575,

‐82.54863

27.31240,

‐82.55368

27.30965,

‐82.55321

27.31382,

‐82.55319

27.30675,

‐82.55676

27.30528,

‐82.54905

11-1 27.36572,

‐82.56273

27.36236,

‐82.56318

27.36698,

‐82.56980

27.36367,

‐82.56204

27.35999,

‐82.56758

27.36393,

‐82.56917

11-2 27.35322,

‐82.55562

27.35341,

‐82.56227

27.34891,

‐82.55895

27.35294,

‐82.56188

27.35127,

‐82.55658

27.34649,

‐82.56710

11-3 27.33725,

‐82.55643

27.33979,

‐82.55321

27.33112,

‐82.55516

27.33770,

‐82.55514

27.33695,

‐82.55966

27.34055,

‐82.55682

11-4 27.32226,

‐82.54559

27.31907,

‐82.54764

27.32487,

‐82.54659

27.32001,

‐82.54623

27.32545,

‐82.54976

27.32778,

‐82.54871

11-5 27.31022,

‐82.54121

27.30910,

‐82.54346

27.30436,

‐82.54324

27.31165,

‐82.54243

27.30748,

‐82.54224

27.31016,

‐82.54557

7-1 27.38025, 

-82.61425 

27.37452, 

-82.60813 

27.36491, 

-82.60823 

27.37973, 

-82.60183 

27.38077, 

-82.61188 

27.37025, 

-82.60916 

7-2 27.36670, 

-82.59143 

27.36647, 

-82.58840 

27.36065, 

-82.59453 

27.37328, 

-82.59063 

27.35581, 

-82.59526 

27.37553, 

-82.59221 

8-1 27.38777, 

-82.59458 

27.37904, 

-82.58343 

27.38414, 

-82.58860 

27.38478, 

-82.58350 

27.37421, 

-82.58307 

27.38191, 

-82.58427 

8-2 27.37907, 

-82.57290 

27.37951, 

-82.57035 

27.37632, 

-82.57216 

27.37123, 

-82.57739 

27.38449, 

-82.57244 

27.37703, 

-82.57264 

US-1 27.38920,

‐82.63400

27.38290,

‐82.61400

27.36900,

‐82.61360

27.38890,

‐82.61430

27.38710,

‐82.62520

27.38230,

‐82.60800

US-2 27.37240,

‐82.60210

27.36860,

‐82.60780

27.38780,

‐82.60130

27.37050,

‐82.5940

27.37140,

‐82.60100

27.37250,

‐82.60790

US-3 27.38777,

‐82.59458

27.37904,

‐82.58343

27.38414,

‐82.58860

27.38478,

‐82.58350

27.37421,

‐82.58307

27.38191,

‐82.58427

US-4 27.37907,

‐82.57290

27.37951,

‐82.57035

27.37632,

‐82.57216

27.37123,

‐82.57739

27.38449,

‐82.57244

27.37703,

‐82.57264

US-5 27.35440,

‐82.59760

27.36400,

‐82.60310

27.36340,

‐82.58760

27.36090,

‐82.59400

27.35440,

‐82.60680

27.36030,

‐82.60260

   
Little Sarasota Bay – Sarasota County Monitoring, January-June 

Station Location 

January February March April May June 

14-1 27.23947,

‐82.51646

27.23565,

‐82.51529

27.23802,

‐82.52170

27.23997,

‐82.51890

27.23664,

‐82.51948

27.23379,

‐82.51922

14-2 27.23144,

‐82.51299

27.22582,

‐82.51452

27.22078,

‐82.51332

27.22795,

‐82.51073

27.22378,

‐82.50552

27.23065,

‐82.51085

14-3 27.21773,

‐82.51221

27.21638,

‐82.50430

27.20581,

‐82.50502

27.21258,

‐82.50245

27.21720,

‐82.50704

27.21136,

‐82.50371

14-4 27.19807,

‐82.50269

27.19453,

‐82.50167

27.20371,

‐82.50126

27.20034,

‐82.50261

27.20444,

‐82.50305

27.19106,

‐82.49980

14-5 27.18361,

‐82.49477

27.18644,

‐82.49840

27.19021,

‐82.49503

27.18220,

‐82.49668

27.18782,

‐82.49620

27.18587,

‐82.49337

Little Sarasota Bay – Sarasota County Monitoring, July-December 

Station Location 

July August September October November December 

14-1 27.24116,

‐82.51845

27.24264,

‐82.52177

27.23837,

‐82.51715

27.23511,

‐82.52013

27.23964,

‐82.51495

27.23552,

‐82.52132

14-2 27.22550,

‐82.51247

27.23152,

‐82.50869

27.23177,

‐82.51597

27.22613,

‐82.51325

27.22335,

‐82.51206

27.23039,

‐82.50961

14-3 27.22112,

‐82.50562

27.20965,

‐82.50335

27.21801,

‐82.51122

27.21758,

‐82.50273

27.21974,

‐82.50496

27.20594,

‐82.50431

14-4 27.20046,

‐82.50259

27.19595,

‐82.49653

27.20052,

‐82.49762

27.19858,

‐82.50238

27.19530,

‐82.50244

27.19762,

‐82.49727

14-5 27.18120,

‐82.49282

27.19005,

‐82.49946

27.18391,

‐82.49674

27.18990,

‐82.49436

27.18770,

‐82.49842

27.18353,

‐82.49713

   
Roberts Bay – Sarasota County Monitoring, January-June 

Station Location 

January February March April May June 

13-1 27.28860,

‐82.55061

27.29469,

‐82.55020

27.29211,

‐82.54466

27.29969,

‐82.54459

27.29256,

‐82.54665

27.29720,

‐82.54781

13-2 27.28192,

‐82.54274

27.28420,

‐82.54711

27.28039,

‐82.54666

27.27881,

‐82.54358

27.28469,

‐82.54454

27.28119,

‐82.54489

13-3 27.27008,

‐82.54462

27.26242,

‐82.53693

27.26596,

‐82.53956

27.26316,

‐82.53887

27.26714,

‐82.54102

27.26400,

‐82.53956

13-4 27.25993,

‐82.53610

27.25521,

‐82.53337

27.25855,

‐82.53496

27.25842,

‐82.53482

27.25299,

‐82.53107

27.25810,

‐82.53460

13-5 27.24447,

‐82.52525

27.24812,

‐82.52477

27.24532,

‐82.52124

27.24532,

‐82.52646

27.24572,

‐82.52386

27.24374,

‐82.52199

Roberts Bay – Sarasota County Monitoring, July-December 

Station Location 

July August September October November December 

13-1 27.29164,

‐82.54427

27.29592,

‐82.54452

27.29030,

‐82.54766

27.29178,

‐82.55099

27.29051,

‐82.54812

27.29347,

‐82.54677

13-2 27.27946,

‐82.54573

27.28598,

‐82.55009

27.28120,

‐82.54242

27.28559,

‐82.54434

27.28305,

‐82.54844

27.28378,

‐82.54740

13-3 27.27038,

‐82.54272

27.27429,

‐82.54398

27.26706,

‐82.53928

27.26634,

‐82.54074

27.26439,

‐82.53892

27.27005,

‐82.54504

13-4 27.25470,

‐82.53197

27.25259,

‐82.52970

27.25750,

‐82.53300

27.25707,

‐82.53238

27.25946,

‐82.53508

27.25612,

‐82.53564

13-5 27.25261,

‐82.52955

27.24856,

‐82.52309

27.25082,

‐82.52574

27.24775,

‐82.52234

27.25003,

‐82.52496

27.25038,

‐82.52899

   
Blackburn Bay – Sarasota County Monitoring, January-June 

Station Location 

January February March April May June 

16-1 27.17680,

‐82.49412

27.17026,

‐82.49108

27.17215,

‐82.49066

27.17502,

‐82.49255

27.17147,

‐82.49221

27.16933,

‐82.48797

16-2 27.15984,

‐82.48401

27.16061,

‐82.48471

27.15797,

‐82.48304

27.16579,

‐82.48645

27.15784,

‐82.48231

27.15861,

‐82.48309

16-3 27.15160,

‐82.47709

27.15301,

‐82.48082

27.14596,

‐82.47679

27.15453,

‐82.48033

27.14884,

‐82.47570

27.15340,

‐82.48046

16-4 27.14028,

‐82.47166

27.14384,

‐82.47175

27.13647,

‐82.47014

27.14340,

‐82.47466

27.14072,

‐82.47088

27.13781,

‐82.47115

16-5 27.13132,

‐82.47028

27.13347,

‐82.46917

27.12844,

‐82.46978

27.12514,

‐82.46936

27.13212,

‐82.47122

27.13080,

‐82.46968

Blackburn Bay – Sarasota County Monitoring, July-December 

Station Location 

July August September October November December 

16-1 27.17459,

‐82.49122

27.17770,

‐82.49345

27.16960,

‐82.49064

27.17174,

‐82.49235

27.17467,

‐82.49089

27.16986,

‐82.48801

16-2 27.16012,

‐82.48224

27.16605,

‐82.48649

27.16197,

‐82.48452

27.16133,

‐82.48455

27.16057,

‐82.48311

27.16442,

‐82.48579

16-3 27.14879,

‐82.47383

27.15472,

‐82.47897

27.14932,

‐82.47496

27.15314,

‐82.48020

27.14761,

‐82.47785

27.15243,

‐82.47850

16-4 27.14008,

‐82.47017

27.14343,

‐82.47405

27.14075,

‐82.47156

27.14298,

‐82.47512

27.14051,

‐82.47043

27.14054,

‐82.47178

16-5 27.12788,

‐82.46935

27.13458,

‐82.46950

27.13033,

‐82.47017

27.13421,

‐82.47046

27.13017,

‐82.46992

27.13274,

‐82.46941

   
Figure 1. January monitoring sites used for assessment of water quality conditions. 
Figure 2. February monitoring sites used for assessment of water quality conditions. 
Figure 3. March monitoring sites used for assessment of water quality conditions.
Figure 4. April monitoring sites used for assessment of water quality conditions. 
Figure 5. May monitoring sites used for assessment of water quality conditions. 

   
Figure 6. June monitoring sites used for assessment of water quality conditions. 

 
Figure 7. July monitoring sites used for assessment of water quality conditions. 

 
Figure 8. August monitoring sites used for assessment of water quality conditions. 

   
Figure 9. September monitoring sites used for assessment of water quality conditions. 

   
Figure 10. October monitoring sites used for assessment of water quality conditions. 

 
Figure 11. November monitoring sites used for assessment of water quality conditions. 

 
Figure 12. December monitoring sites used for assessment of water quality conditions.