Tampa Bay Estuary Program 

Model Evaluation and Update: 

Chlorophyll a – Light Attenuation 

Relationship

Prepared for: 

Tampa Bay Estuary Program 

Mail Station I-1/NEP 

100 8th Avenue SE 

St. Petersburg, FL 33701 

Prepared by: 

1155 Eden Isle Drive NE 

St. Petersburg, FL 33704 

March 2001
FOREWORD 

This report was prepared by Janicki Environmental, Inc. under Contract No. T-98-06 for the 

Tampa Bay Estuary Program. 

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ACKNOWLEDGMENTS

This project was conducted under the guidance of the TBEP and the Modeling 

Subcommittee of the TBEP TAC. Review and suggestions for the project were provided by 

the TBEP staff and members of the TAC Modeling Subcommittee. In particular, thanks are 

extended to Dick Eckenrod, Holly Greening, and the Modeling Subcommittee. 

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TABLE OF CONTENTS 

FOREWORD ........................................................................................................... i 

ACKNOWLEDGMENTS .............................................................................................ii 

1 INTRODUCTION ....................................................................................................1-1

2 METHODS...............................................................................................................2-1

3 RESULTS ..................................................................................................................3-1

4 DISCUSSIONS AND CONCLUSIONS .....................................................................4-1

5 REFERENCES............................................................................................................5-1 

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1 INTRODUCTION 

The Tampa Bay National Estuary Program (TBNEP) developed a Comprehensive 

Conservation & Management Plan (CCMP), entitled Charting the Course, which was 

the culmination of five years of effort aimed at bringing together the participants of 

the TBNEP to address the key environmental issues affecting Tampa Bay. The 

CCMP specifically addressed several major issues, including water quality and 

habitat loss. The loss of seagrasses in Tampa Bay drew particular interest, given 

their important role in the ecological functioning of the bay. 

Seagrasses provide critical habitat for recreationally and commercially important fish 

and invertebrate species. Seagrasses in Florida provide juvenile nursery and adult 

feeding areas for red drum, spotted seatrout, spot, silver perch, sheepshead, snook, 

shrimp, and the bay scallop (Zieman and Zieman, 1989). Seagrass meadows are 

also important feeding areas for the Florida manatee. Seagrasses serve to improve 

water quality by reducing nutrients in the water column and are an important 

component of the energy and nutrient cycles in coastal environments. 

Seagrass extent and condition can be impacted by many factors, including water 

quality, physical factors such as prop scarring and currents, seagrass disease, and 

location of seagrass beds in relation to offshore transverse sandbars. The TBNEP 

Technical Advisory Committee (TAC) recognizes that these and other factors may 

affect progress towards reaching adopted seagrass restoration goals, and is currently 

initiating actions which will assist with addressing factors in addition to water clarity 

and quality (including the initiation of measuring the depth of water at various 

seagrass beds around the bay, and the monitoring of potential seagrass disease). 

Actions needed to address additional factors, such as the bay-wide effects of prop 

scarring or the location of various seagrass beds, will be included in discussions of 

future monitoring needs.

In Tampa Bay, seagrasses typically grow at depths no deeper than six to eight feet. 

Light is one of the limiting factors on the depth at which seagrasses can be found. 

Light requirements for growth vary by seagrass species. Turtle grass, the most 

common seagrass species in Tampa Bay, has an estimated light requirement of 

20.5% of the incident subsurface light (Dixon and Leverone, 1995). For the 

purposes of seagrass restoration target setting, this was assumed to be the minimum 

light requirement for seagrasses in Tampa Bay (Janicki and Wade, 1996). 

To address the issue of seagrass habitat loss, recommended seagrass protection and 

restoration targets were developed (Janicki et al., 1995). Seagrass restoration targets 

were determined by comparing 1990 seagrass extent to that observed in 1950. 

Seagrass targets were defined as those portions of Tampa Bay that had seagrasses in 

1950, did not have seagrasses in 1990, and had not been permanently altered to 

preclude restoration of seagrasses. 

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To strive toward the seagrass restoration goal, the TBNEP developed the Nitrogen 

Management Strategy. The Strategy seeks to prevent future impacts due to excessive 

nitrogen loadings to Tampa Bay. To address these concerns, a paradigm that relates 

nitrogen loading to chlorophyll and seagrass was utilized, as shown in Figure 1-1. 

Figure 1-1. The TBNEP Nitrogen Management Strategy Paradigm. 

An empirical modeling approach was taken to define the relationships between TN 

loads and chlorophyll a concentrations and between chlorophyll a concentrations 

and light attenuation (Janicki and Wade, 1996). 

The objective of this report is to re-evaluate the empirical relationship between 

chlorophyll a concentrations and light attenuation using the water quality data 

collected since 1994 by the Environmental Protection Commission of Hillsborough 

County (EPCHC). 

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2 METHODS 

A principal working hypothesis was earlier developed that observed light 

attenuation is directly related to chlorophyll a concentrations, turbidity, and color 

(Janicki and Wade, 1996). Regression results suggest that the variation in 

chlorophyll a concentrations could explain the majority of the variation in light 

attenuation as measured by the diffuse light attenuation coefficient, Kd. Beer’s Law 

allows approximation of Kd as follows: 

K z d I e ( )

0

− Iz = ×

where: Iz = the incident light at depth z,

 I0 = the incident light just below the surface, and 

 Kd = the diffuse light attenuation coefficient (1/meters). 

Giesen et al. (1990) reported that the diffuse attenuation coefficient Kd can be 

approximated by a factor (that typically ranges between 1.5 and 1.8) divided by the 

Secchi disc depth (expressed in meters). Concurrently measured Kd and Secchi disc 

depths reported by the City of Tampa Bay Study Group (Johansson, pers. comm.) 

were used to verify this relationship for Tampa Bay and to refine bay segmentspecific factors. 

The depth to which a particular amount of light penetrates, expressed as the 

percentage of incident irradiance, can be estimated using the following 

rearrangement of Beer’s Law: 

K factor Light = − × × d ) ) 100

% Z ( 1 ln (

where: Z =the depth to which the defined % light penetrates 

% Light =the desired % light (defined as 20.5% for this study) 

 

Kd factor =the bay segment-specific factor that relates Kd and 

 Secchi disc depth 

 

The relationship between chlorophyll a concentrations and light attenuation, 

expressed as the depth to which 20.5% of the surface irradiance penetrates, was 

expressed by the following equation: 

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ln (C ) â ln (Z ) t,s = α t,s + t,s × t,s

where: Zt,s = the depth to which 20.5% of surface irradiance 

 penetrates in month t and bay segment s

 Ct,s = average chlorophyll a concentration in month t 

 and bay segment s 

 αt,s and βs = regression parameters. 

Least squares regression methods were used to estimate the regression parameters 

(Janicki and Wade, 1996). The results of the regressions indicated that the variation 

in the observed depths to which 20.5% of surface irradiance penetrates could be 

explained by the variation in observed chlorophyll a concentrations. Monthly 

specific regression intercept terms were used to avoid any potentially confounding 

effects of seasonality in the independent and dependent variables. Turbidity data 

were also investigated as a possible explanation for a portion of the remaining 

unexplained variation in the light penetration data. No improvement in the model 

fit was found. 

Water quality data collected by the EPCHC for the period 1995 through 1998 were 

obtained and incorporated into the TBEP water quality database (Janicki 

Environmental, 2000). These data were used to evaluate the chlorophyll a – light 

attenuation model developed previously using data from the period 1986 through 

1994. 

Initially, visual inspection of the relationship between chlorophyll a concentrations 

and Z20.5% was completed by plotting these data and identifying the period from 

which the data were obtained. Secondly, the chlorophyll a – Z regression was used 

to estimate Z given the observed chlorophyll a concentrations during 1995 through 

1998. Comparisons of the predicted and observed Z values, for both monthly and 

annual mean conditions, were also made. Thirdly, the residuals (i.e., the difference 

of the observed and predicted Z values) were related to observed turbidity and color 

values to assess whether differences in turbidity or color could account for the 

unexplained variation in the Z values. 

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3 RESULTS 

The results of the three methods used to evaluate the chlorophyll a – Z regression 

for Tampa Bay are presented below. 

Visual Comparison of the Chlorophyll a – Light Attenuation Relationship 

The following figures present the chlorophyll a – light attenuation relationship for 

all bay segments and for each of the bay segments: 

• Figure 3-1 - All bay segments 

• Figure 3-2 - Old Tampa Bay 

• Figure 3-3 - Hillsborough Bay 

• Figure 3-4 - Middle Tampa Bay - 31 

• Figure 3-5 - Middle Tampa Bay - 32 

• Figure 3-6 - Middle Tampa Bay - 33. 

Specifically, the depth to which 20.5% of incident radiation penetrates (Z) is plotted 

as a function of chlorophyll a concentration. In each plot, the 1995-1998 data are 

presented as triangles while the 1986-1994 data are presented as circles. 

Clearly, there is considerable similarity in the chlorophyll a – Z relationships from 

the 1986-1994 and 1995-1998 periods. Close scrutiny of the data does suggest, 

however, that the 1995-1998 data tend toward shallower Z values for the same 

chlorophyll a concentrations. This seems to be particularly true when chlorophyll a 

concentrations are less than 10 μg/L. Therefore, there is some evidence that at 

lower chlorophyll a levels incident light penetrated to somewhat shallower depths 

in the 1995-1998 period as compared to the 1986-1994 period. 

Comparison of Predicted and Observed Z Values Using the 1986-1994 

Chlorophyll a – Light Attenuation Regressions 

The following figures present a comparison of the observed mean monthly Z values 

for the 1995-1998 period to the Z values predicted by the ambient mean monthly 

chlorophyll a concentrations and the chlorophyll a – Z regressions developed from 

the 1986-1994 data (Janicki and Wade, 1996): 

• Figure 3-7 – Old Tampa Bay 

• Figure 3-8 – Hillsborough Bay 

• Figure 3-9 – Middle Tampa Bay – 31 

• Figure 3-10 – Middle Tampa Bay – 32 

• Figure 3-11 – Middle Tampa Bay – 33. 

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These plots include a line that represents a 1:1 relationship between predicted and 

observed values. Data points above the line represent months when the predicted Z 

value was greater than that which was observed. Data points below the line 

represent months when the predicted Z value was less than that which was 

observed. Close agreement in the predicted and observed Z values would result in 

a plot where the points were in close proximity to the line. If any bias in the 

predicted Z values exists then a disproportionate number of points would be found 

either above (observed > predicted) or below (observed < predicted) the line. 

These comparisons of mean monthly predicted and observed Z values also indicate 

that there is a small but consistent bias in the observed Z values. In all bay 

segments, the observed Z values were generally less than those predicted by the 

regressions. This suggests that for the same chlorophyll a concentration the mean 

monthly Z values observed during the 1995-1998 period was generally less than 

that observed during the 1986-1994 period. 

Table 3-1 presents a comparison of the mean annual predicted and observed Z 

values by bay segment. The differences in the observed and predicted Z values 

were typically greatest in 1996 and 1997 in all bay segments. In both years, the 

predicted mean annual Z exceeded the observed mean annual Z. In 1995 there 

was relatively good agreement between the predicted and observed mean annual Z 

values. In 1998, the observed mean annual Z exceeded the predicted value. 

Overall, the difference in Z values was approximately 0.3 meters in Old Tampa Bay 

and Middle Tampa Bay segments 32 and 33 and between 0.1 and 0.2 meters in 

Hillsborough Bay and Middle Tampa Bay segment 31. 

Table 3-1. Mean annual predicted and observed Z values. 

Bay 1995 1996 1997 1998

Segment Observed Predicted Observed Predicted Observed Predicted Observed Predicted

OTB 1.69 1.86 1.73 2.52 1.88 2.45 1.50 1.36

HB 1.11 1.12 1.26 1.58 1.16 1.40 0.99 0.95

MTB-1 1.24 1.24 1.35 1.93 1.07 1.31 0.98 0.87

MTB-2 1.79 1.95 1.88 2.48 1.84 2.52 1.42 1.26

MTB-3 1.81 2.05 2.3 3.32 1.91 2.25 1.47 1.38

Relationship Between Residuals from the Chlorophyll a – Light Attenuation 

Regressions and Other Variables 

To examine the potential influence of other variables that can affect light 

attenuation, the residuals from the chlorophyll a – light attenuation model estimated 

for the 1995-1998 period were plotted as a function of these variables. Specifically, 

turbidity and color can affect light attenuation. 

3-2
Residual Z values are plotted as a function of turbidity by bay segment in the 

following figures: 

• Figure 3-12 – Old Tampa Bay 

• Figure 3-13 – Hillsborough Bay 

• Figure 3-14 – Middle Tampa Bay – 31 

• Figure 3-15 – Middle Tampa Bay – 32 

• Figure 3-16 – Middle Tampa Bay – 33. 

Residual Z values are also plotted as a function of color by bay segment in the 

following figures: 

• Figure 3-17 – Old Tampa Bay 

• Figure 3-18 – Hillsborough Bay 

• Figure 3-19 – Middle Tampa Bay – 31 

• Figure 3-20 – Middle Tampa Bay – 32 

• Figure 3-21 – Middle Tampa Bay – 33. 

If either turbidity or color significantly influenced the chlorophyll a - light 

attenuation relationship, then a discernable pattern in the residuals would be 

expected. Thus, the residual Z values would be greater at higher values of either 

turbidity or color. Inspection of the residual plots suggests that neither turbidity nor 

color is significantly related to the residual Z value. 

3-3
Figure 3-1. Relationship between chlorophyll a and depth of 20.5% light attenuation, all bay segments. 
Figure 3-2. Relationship between chlorophyll a and depth of 20.5% light attenuation, Old Tampa Bay. 
Figure 3-3. Relationship between chlorophyll a and depth of 20.5% light attenuation, Hillsborough Bay
Figure 3-4. Relationship between chlorophyll a and depth of 20.5% light attenuation, Middle Tampa Ba
Figure 3-5. Relationship between chlorophyll a and depth of 20.5% light attenuation, Middle Tampa Ba
Figure 3-6. Relationship between chlorophyll a and depth of 20.5% light attenuation, Middle Tampa Ba
Figure 3-7. Relationship between observed and predicted depth of 20.5% light attenuation, Old Tampa 
Figure 3-8. Relationship between observed and predicted depth of 20.5% light attenuation, Hillsboroug
Figure 3-9. Relationship between observed and predicted depth of 20.5% light attenuation, Middle Tam
Figure 3-10. Relationship between observed and predicted depth of 20.5% light attenuation, Middle Tam
Figure 3-11. Relationship between observed and predicted depth of 20.5% light attenuation, Middle Tam
Figure 3-12. Relationship between turbidity and residuals of the depth of 20.5% light attenuation, Old T
Figure 3-13. Relationship between turbidity and residuals of the depth of 20.5% light attenuation, Hillsb
Figure 3-14. Relationship between turbidity and residuals of the depth of 20.5% light attenuation, Midd
Figure 3-15. Relationship between turbidity and residuals of the depth of 20.5% light attenuation, Midd
Figure 3-16. Relationship between turbidity and residuals of the depth of 20.5% light attenuation, Midd
Figure 3-17. Relationship between color and residuals of the depth of 20.5% light attenuation, Old Tam
Figure 3-18. Relationship between color and residuals of the depth of 20.5% light attenuation, Hillsboro
Figure 3-19. Relationship between color and residuals of the depth of 20.5% light attenuation, Middle T
Figure 3-20. Relationship between color and residuals of the depth of 20.5% light attenuation, Middle T
Figure 3-21. Relationship between color and residuals of the depth of 20.5% light attenuation, Middle T
4 DISCUSSION AND CONCLUSIONS 

The re-evaluation of the chlorophyll a – light attenuation model is one component 

of the overall examination of the nitrogen management strategy adopted by the 

Tampa Bay Estuary Program. The objective of this report is to re-evaluate the 

empirical relationship between chlorophyll a concentrations and light attenuation 

using the water quality data collected since 1994 by the Environmental Protection 

Commission of Hillsborough County (EPCHC). 

In general, the chlorophyll a – light model explains the observed variation in light 

attenuation as a function of chlorophyll a concentrations. However, there appears 

to be some bias in the predicted Z values at low chlorophyll a concentrations. 

Specifically, the depth to which 20.5% of the incident light penetrates was 

somewhat shallower during the 1995-1998 period than had been predicted by the 

model based on the 1986-1994 data. The bias is expressed at both monthly and 

annual time scales. 

To put the observed bias in the Z values in perspective, the differences in the mean 

annual Z values were converted to units of Secchi disc depth. Secchi disc depth is 

the specific indicator employed by the current monitoring program to evaluate 

spatial and temporal trends in light attenuation. The EPCHC measures Secchi disc 

depth at 0.5 foot intervals. The mean differences by bay segment in the mean 

annual Z values for the 1995-1998 period were: 

• Old Tampa Bay – 13 inches 

• Hillsborough Bay – 5 inches 

• Middle Tampa Bay 31 – 8 inches 

• Middle Tampa Bay 32 – 15 inches 

• Middle Tampa Bay 33 – 17 inches. 

Clearly, the difference in predicted and observed mean annual Secchi disc depths 

consistent with the Z values would be measurable given the existing monitoring 

program. Analysis of the Secchi disc depths observed in each bay segment show 

that the mean annual Secchi disc depths have decreased during the 1995-1998 

period compared to those of the 1986-1994 period. This decrease is on the same 

order as those listed above. 

Additional analyses were performed to evaluate possible reasons for the observed 

differences in the relationship between the 1986-1994 period and the 1995-1998 

period. A regression model based on data from the extended time period of 1986 

through 1998 was examined and the regression coefficients from this model were 

compared to those from the original model based on 1986-1994 data. Neither the 

monthly-specific intercept estimates nor the slope estimates from these two models 

were significantly different. 

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Another evaluation examined changes in the methods employed to collect and/or 

analyze the chlorophyll samples between the two periods. Mr. Tom Cardinale, 

EPCHC, provided information relating to any changes in equipment and methods 

employed during the sampling record. No relevant differences in either field or 

laboratory methods were reported. 

A hypothesis that might explain the observed bias is a change in phytoplankton 

community structure that could result in changes in light attenuation per unit of 

algal biomass. Phytoplankton community composition data have been collected by 

the City of Tampa Bay Study Group since 1978, and can be used to test this 

hypothesis. Preliminary indications point toward a shift in community dominance 

in Hillsborough Bay from blue-green algae prior to 1995 to diatoms in the 

succeeding period. 

Based on the outcome of these analyses, no readily apparent cause for the small 

bias in the chlorophyll a – light attenuation relationship could be found, but it may 

be that changes in phytoplankton community composition have contributed to this 

bias. It is recommended that the empirical relationships between chlorophyll a 

concentrations and light attenuation developed from the 1986-1994 water quality 

data continue to be employed as part of the model suite relating external nitrogen 

loads to light attenuation. Continued monitoring and analysis of the ambient 

chlorophyll a concentrations and water clarity is needed to ensure factors other than 

algal biomass are not contributing significantly to water clarity in the bay. 

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5 REFERENCES 

Dixon, L.K. and J.R. Leverone. 1995. Light requirements of Thalassia testudinum in 

Tampa Bay, Florida. Submitted to: Surface Water Improvement and Management 

Program, Southwest Florida Water Management District. Submitted by: Mote 

Marine Laboratory, Sarasota, Florida. Mote Marine Laboratory Technical Report 

Number 425. 

Giesen, W.B.J.T, M.M. van Katijk, and C. den Hartog. 1990. Eelgrass condition 

and turbidity in the Dutch Wadden Sea. Aquatic Botany. Vol 37. pp.71-85. 

Janicki, A. and D. Wade. 1996. Estimating critical external nitrogen loads for the 

Tampa Bay Estuary: An empirically based approach to setting management targets. 

Prepared for: Tampa Bay National Estuary Program. Technical Publication #06-96. 

Janicki et al., 1995. Habitat protection and restoration targets for Tampa Bay. 

Prepared for: Tampa Bay National Estuary Program. Technical Publication #07-93. 

Janicki Environmental, Inc. 2000. Tampa Bay Estuary Program Water Quality 

Monitoring Program Database. Prepared for: Tampa Bay Estuary Program. 

Johansson, R. 2001. Personal communication from Roger Johansson, February 

2001. 

Zieman, R.C., R.T. Zieman. 1989. The Ecology of the seagrass meadows of the 

west coast of Florida: A community profile. U.S. Fish and Wildlife Service. Biol. 

Rep. 85(7.25). 

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