EPA 600R-08/004

An Approach for Developing 

Numeric Nutrient Criteria for a 

Gulf Coast Estuary 

U.S. Environmental Protection Agency 

Office of Research and Development 

National Health and Environmental Effects Research Laboratory 

Gulf Ecology Division 

1 Sabine Island Drive, Gulf Breeze, FL 32561 

January 2008 
Disclaimer 

This report provides information to States, Indian tribes (hereafter tribes), and other authorized 

jurisdictions for the purpose of assisting development of numeric nutrient criteria for adoption into 

water quality standards under the Clean Water Act (CWA). Under the CWA, States and tribes are to 

establish water quality criteria to protect designated uses. State and tribal decisionmakers retain the 

discretion to adopt approaches on a case-by-case basis that differ from the approaches used in this 

report when appropriate and scientifically defensible. Although this report provides hypothetical 

numeric nutrient criteria that would serve to protect resource quality and aquatic life, it does not 

substitute for the CWA or U.S. Environmental Protection Agency’s (EPA’s) regulations nor is it a 

regulation itself. Thus, it cannot impose legally binding requirements on EPA, States, tribes, or the 

regulated community and may not apply to a particular situation or circumstance. 

Cover photo by James Hagy. 
iii

Contributing Authors 

James D. Hagy III, Ph.D. 

Research Ecologist 

U.S. Environmental Protection Agency 

Office of Research and Development 

National Health and Environmental Effects Research Laboratory 

Gulf Ecology Division 

Gulf Breeze, FL 

(850)934-2455, hagy.jim@epa.gov 

Janis C. Kurtz, Ph.D. 

Research Ecologist 

U.S. Environmental Protection Agency 

Office of Research and Development 

National Health and Environmental Effects Research Laboratory 

Gulf Ecology Division 

Gulf Breeze, FL 

Richard M. Greene, Ph.D. 

Branch Chief, Ecological Dynamics and Effects Branch 

U.S. Environmental Protection Agency 

Office of Research and Development 

National Health and Environmental Effects Research Laboratory 

Gulf Ecology Division 

Gulf Breeze, FL 

Citation 

Hagy, J. D., J. C. Kurtz, and R. M. Greene. 2008. An approach for developing numeric nutrient criteria 

for a Gulf coast estuary. U.S. Environmental Protection Agency, Office of Research and Development, 

National Health and Environmental Effects Research Laboratory, Research Triangle Park, NC. EPA 

600R-08/004. 44 pp.
iv

Acknowledgments 

This manuscript would not have been possible without the vision and sustained efforts of a 

large number of people at the Gulf Ecology Division, whose work over more than a decade provided 

much of the data available to characterize water quality and ecological processes in Pensacola Bay. 

Much of this work has been published separately and cited herein. We thank Mike Lewis and Richard 

Devereux for sharing unpublished data and Linda Harwell for assistance in obtaining data from the 

National Coastal Assessment and Florida's Inshore Monitoring and Assessment Program. Ed Decker 

helped us better understand how regulatory mechanisms function under the Clean Water Act. Ed 

Dettman, Walt Nelson, and Cheryl Brown provided helpful comments at several stages of manuscript 

preparation. We appreciate the significant contributions of several individuals who edited the 

document and developed its final layout. These include John Barton and Keith Tarpley of NHEERL's 

National Information Management and Site Support Staff and Barbra Schwartz and others at the 

National Center for Environmental Assessment. 

This is contribution no.1322 of the Gulf Ecology Division of the U.S. Environmental Protection 

Agency’s National Health and Environmental Effects Research Laboratory. 
v 

Table of Contents 

List of Tables ...........................................................................................................................................vi 

List of Figures..........................................................................................................................................vi 

Executive Summary..............................................................................................................................vii 

1. Introduction ........................................................................................................................................1 

1.1 Background .....................................................................................................................................1 

1.2 Study Site ........................................................................................................................................3 

2. Methods ...............................................................................................................................................7 

2.1 Water Quality Data for Pensacola Bay ...........................................................................................7 

2.2 Ecoregional Water Quality Characterization ..................................................................................7 

2.3 Aerial Submerged Aquatic Vegetation Surveys .............................................................................8 

2.4 Watershed Characteristics and Land Use........................................................................................9 

3. Results and Discussion .....................................................................................................................11 

3.1 Ecoregional Comparisons and thePercentile Approach................................................................11 

3.2 Algal Biomass, Productivity, and Community Composition........................................................14 

3.3 Preventing Hypoxia.......................................................................................................................16 

3.4 Protecting Seagrass Habitats.........................................................................................................18 

3.5 A Watershed Perspective ..............................................................................................................20 

3.6 Nutrient Criteria ............................................................................................................................22 

4. Summary and Conclusions..............................................................................................................27 

5. References..........................................................................................................................................29 

Appendix A: Observations in EPA’s Level III Ecoregion 75 ................................................................33 

Appendix B: Observations in Florida’s Level IV Ecoregion 75a...........................................................34 

Appendix C: List of Acronyms and Abbreviations ................................................................................35 
vi

List of Tables 

Table 1. Sources of water quality data used in this study.........................................................................7 

Table 2. Ecoregional water quality conditions computed for U.S. Environmental Protection 

Agency’s Level III ecoregion 75 and Florida’s Level IV ecoregion 75a...............................................14 

Table 3. Seasonal median chlorophyll-a in Pensacola Bay surface waters and its 

interquartile range...................................................................................................................................15 

Table 4. Plankton community respiration rate and sediment oxygen demand in the Pensacola Bay 

system .....................................................................................................................................................17 

Table 5. Area of submerged aquatic vegetation beds in the Pensacola Bay system circa 

1950 and in 1960, 1980, 1992, and 2003................................................................................................19 

Table 6. Suggested nutrient and nutrient-related water quality criteria for Pensacola Bay 

resulting from the weight-of-evidence approach described herein.........................................................25 

List of Figures

Figure 1. Locations of stations sampled during two major studies of water quality conditions 

in the Pensacola Bay system and a 2003-to-2004 study of benthic and planktonic metabolism .............3 

Figure 2. A conceptual model illustrating historical, ecologic, and socioeconomic factors of 

potential importance for developing and evaluating water quality management options for 

Pensacola Bay...........................................................................................................................................4 

Figure 3. The locations of water quality monitoring stations visited under the Environmental 

Monitoring and Assessment Program during 2001 and 2002 and the Florida Inshore Monitoring 

and Assessment Program during 2000 through 2004...............................................................................8 

Figure 4. Procedure for computing statistical comparison values for estuaries .......................................8 

Figure 5. Distribution of summer estuary median surface water quality values by salinity zones 

for estuaries in Level III ecoregion 75 and Level IV ecoregion 75a......................................................13 

Figure 6. Frequency histogram of surface chlorophyll-a concentrations in mesohaline waters 

of the Pensacola Bay system from 1996 to 2001....................................................................................15 

Figure 7. Observations of bottom dissolved oxygen in the Pensacola Bay system during the 

summers of 1996 through 1999 indicating the locations and frequency of observations less than 

2.0 mg L-1 ...............................................................................................................................................16 

Figure 8. Coverage of submersed aquatic vegetation in Pensacola Bay circa 1950 and in 1992...........18 

Figure 9. Land cover in the Pensacola Bay watershed circa 2001 .............................................................. 21 

Figure 10. Flow diagram illustrating logical path followed to determine appropriate        

approach for determining nutrient criteria for Pensacola Bay .................................................................... 23 
vii 

Executive Summary 

Nutrient enrichment is currently a major 

cause of impaired water quality and degraded 

ecosystem health in coastal marine ecosystems 

such as estuaries. The Clean Water Act (CWA) 

legislation provides much of the legal framework 

for water quality management. Effective 

management of nutrient enrichment in estuaries 

under the CWA presently is inhibited by the lack 

of numeric criteria for nutrients and nutrientrelated water quality indicators. We describe and 

demonstrate a manageable, science-based 

approach for developing water quality criteria for 

nutrients (nitrogen and phosphorus), chlorophylla, dissolved oxygen (DO), and water clarity for a 

single estuary, Pensacola Bay, FL, with which we 

were very familiar. As a component of the 

approach, we modified the U.S. Environmental 

Protection Agency’s (EPA’s) percentile approach 

to compare water quality indicators in three 

salinity zones of Pensacola Bay with comparable 

values from other estuaries. We also conducted a 

broad-based quantitative assessment of both 

nutrient-related conditions and processes in the 

bay and nutrient inputs to the bay, which 

contribute to a logical process leading to 

determination of nutrient criteria. 

To apply the percentile approach, it is 

necessary to identify a class of water bodies, 

estuaries in this case, that can be compared 

reasonably. We defined a class of estuaries on the 

basis of EPA’s Level III ecoregions and Florida’s 

Level IV ecoregions. Within these schemes, 

Pensacola Bay is located within ecoregion 75 and 

ecoregion 75a, respectively. Estuaries were 

defined according to the National Oceanic and 

Atmospheric Administration’s coastal assessment 

framework, which identifies estuarine drainage 

areas. We assembled median summer surface 

water quality data for 28 estuaries in Level III 

ecoregion 75 and 7 estuaries in Level IV 

ecoregion 75a. Three salinity zones (<5, 5 to 18, 

and >18) also were defined so that water quality 

in each salinity zone of Pensacola Bay could be 

compared with water quality within 

corresponding salinity zones in other estuaries. 

Chlorophyll-a in Pensacola Bay was comparable 

with the median for ecoregion 75 and was 

somewhat higher than other systems in ecoregion 

75a. Nutrients and water clarity in oligohaline 

water were also similar to the median. In 

contrast, water clarity and nutrient concentrations 

in mesohaline and higher salinity waters were in 

the best 25% of estuaries (>75th percentile for 

water clarity and <25th percentile for nutrients). 

Our analysis of major nutrient-related 

water quality concerns in Pensacola Bay found 

that seasonal hypoxia and seagrass loss were the 

major issues. Seasonal hypoxia affected an 

average of 25% of the bottom area in recent 

studies. Seagrass loss is extensive in the system. 

About 95% of seagrass habitat was lost between 

1950 and 1980. Almost no recovery was 

observed in surveys in 1992 and 2003. Yet, other 

indicators of ecosystem function point to lower 

nutrient-related impacts. Nitrogen and 

phosphorus loading rates to the system are 

moderate. Phytoplankton productivity was 

moderate (320 g carbon m-2

 year

-1) as was 

plankton and benthic metabolism. Nutrient 

concentrations were generally low, and 

phytoplankton were nutrient limited. Studies 

indicate that hypoxia may result significantly 

from a natural propensity toward oxygen 

depletion, whereas the extent of seagrass loss 

may be a legacy of formerly more degraded 

water quality conditions. 

Nutrient yields from Pensacola Bay’s 

largely forested watershed are low (262 kg 

nitrogen km-2 year-1 and 21.8 kg phosphorus km-2

year

-1). Concentrations of nitrogen in rainfall are 

also relatively low (14 μM). However, rapid 

population growth in the coastal counties of the 

watershed may cause increased nutrient loading 

in the future. We conclude that water quality 

criteria for nutrients and nutrient-related water 

quality measures could be based reasonably on 
viii 

currently observed conditions because evidence 

that more stringent criteria are scientifically 

defensible, necessary, or even achievable, is 

lacking. Hypothetical criteria resulting from 

application of this approach are presented. 

The approach to criteria development that 

we describe could provide a broad template for 

analyses in other systems. It would be most 

useful for systems that, like Pensacola Bay, do 

not have clear evidence of water quality or water 

quality-related ecological impacts resulting from 

anthropogenic nutrient enrichment. Conversely, 

systems with very high nutrient inputs resulting 

from point sources, landscape changes, or other 

anthropogenic causes may require substantial 

nutrient reductions. Although elements of our 

analytical approach may be useful as part of an 

approach for determining criteria for these 

systems, additional elements will be needed to 

determine reduced levels for nutrient 

concentrations and nutrient-related water quality 

measures that are appropriate to the system and 

protective of designated uses. 
1 

1. Introduction 

1.1 Background 

The U.S. Congress responded to the 

desire of the American people to aggressively 

protect U.S. waterways from pollution with 

passage of the 1972 Federal Water Pollution 

Control Act and subsequent amendments, which, 

since the 1977 amendments, have been known 

collectively as the Clean Water Act (CWA; U.S. 

House of Representatives 2000). The CWA put 

into place a water quality standards process, 

within which ambient water quality criteria are 

centrally featured. Ambient water quality criteria 

are concentration limits determined such that the 

legally identified or “designated” human and 

aquatic life uses of a water body are not impaired 

by the target pollutant. Since passage of the 

CWA, standard approaches have been developed 

for establishing aquatic life criteria for toxic 

chemicals, generally utilizing experimentally 

determined acute and chronic laboratory toxicity 

data for multiple species (Stephan et al. 1985). 

Management actions enabled by the CWA have 

successfully eliminated the most egregious toxic 

impairments. 

Nitrogen and phosphorus are major plant 

nutrients that occur naturally in varying amounts 

and are necessary for normal ecological function 

of aquatic ecosystems. Nutrients become 

pollutants, however, when concentrations or 

loadings are increased excessively. 

Anthropogenic nutrient enrichment often causes 

eutrophication (Nixon 1995) and a related 

spectrum of usually adverse environmental 

impacts. Coastal nutrient enrichment has 

increased during the past half century and has not 

been curtailed effectively by water quality 

management under the CWA (NRC 2000). In the 

United States, water quality impairment is 

tracked by the U.S. Environmental Protection 

Agency (EPA) via a list of impaired waterways 

known as the Section 303(d) list, referring to the 

relevant section of CWA legislation. Nutrient 

enrichment or nutrient-related effects (e.g., 

oxygen depletion, algal growth, harmful algal 

blooms) combine as the leading cause for 

inclusion on the Section 303(d) list (U.S. 

EPA/OWOW, public communication). Global 

trends in coastal nutrient enrichment are similar 

in many regards to those in the United States 

(GESAMP 2001). 

In 1998, EPA expressed its view (U.S. 

EPA 1998) that establishing numeric criteria for 

nutrients and related water quality indicators 

(e.g., chlorophyll-a) was an important step 

toward reducing nutrient impacts. Others have 

expressed a similar perspective. A survey of 

water quality managers for 18 U.S. estuaries 

found that one of the major impediments to 

effective management of eutrophication was a 

lack of regulatory authority to require nutrient 

reductions, including a lack of numeric nutrient 

criteria (NRC 2000). In the absence of numeric 

criteria, determination of water quality 

impairment generally is based on narrative water 

quality criteria. Commonly referred to as “freefroms,” narrative criteria describe in qualitative 

terms what undesirable environmental conditions 

are proscribed (e.g., water should be free from 

excessive algal blooms caused by nutrient 

enrichment). A problem with narrative standards 

is that a procedure for interpreting the standard to 

determine numeric targets must be developed 

before regulatory actions can be imposed (U.S. 

EPA 1999a). With the possibility of regulatory 

action undermined by poorly defined standards, 

many efforts to manage eutrophication rely 

primarily on nonregulatory (i.e., voluntary, 

educational) approaches (NRC 2000). For 

example, the more than 20-year, high-profile 

effort to restore the Chesapeake Bay has 

emphasized voluntary rather than regulatory 

approaches, with numeric criteria being proposed 

only recently (U.S. EPA 2003). Adoption of 

numeric standards for nutrients and nutrientrelated water quality indicators could simplify 

both determination of nutrient-related water 
2 

quality impairments and implementation of 

regulatory actions to improve water quality. 

Regulatory approaches ultimately may be needed 

to reverse current trends. 

There are several reasons why most water 

bodies are presently protected under narrative 

rather than numeric nutrient criteria: 

• natural nutrient concentrations vary widely 

among aquatic ecosystems, requiring that 

numeric criteria be derived on a regional or 

even site-specific basis; 

• nutrient enrichment effects usually are 

expressed in relatively complex ways that 

preclude the use of experimental assays, 

similar to toxicity tests, to derive nutrient 

criteria; 

• sensitivity to nutrient enrichment is expected to 

vary significantly among systems; and 

• ambient nutrient concentrations are usually not 

as useful as indicators of biological effects as 

are ambient concentrations of toxic chemicals 

(e.g., high nutrient concentrations may reflect a 

lack of nutrient limitation, whereas low 

nutrient concentrations may have been caused 

by an active phytoplankton bloom). 

Despite the challenges of deriving 

ambient water quality criteria for nutrients, EPA 

adopted a national strategy to develop nutrient 

criteria in 1998 (U.S. EPA 1998) and has since 

published technical guidance and recommended 

nutrient criteria for most U.S. rivers, streams, 

lakes, and reservoirs (e.g., U.S. EPA 

2000a,b,c,d). EPA published technical guidance 

for establishing nutrient criteria for estuaries and 

coastal marine waters (U.S. EPA 2001) but 

stopped short of recommending specific 

approaches. Determining nutrient criteria for 

estuaries may be more complicated than for 

many freshwater systems because of a number of 

factors that include those below. 

• Estuaries are influenced to varying degrees by 

exchanges of matter and energy (e.g., resulting 

from tides) at their seaward margins. 

• Widely varying physical and chemical 

conditions strongly influence biotic 

communities in estuaries (Kennish 1986). 

Feedback effects contribute to significant water 

quality differences among systems. 

• Estuaries often are subject to multiple stressors 

influencing nutrient-related water quality. 

Examples include fishing, dredging, and exotic 

species invasions. 

• Strong gradients in water quality are often 

present within estuaries, complicating 

specification and implementation of numeric 

criteria. 

In view of these observations, developing 

a scientific basis for nutrient criteria could 

require an understanding of nutrient inputs, 

transport, fate, and the important biological 

response mechanisms of the resident biotic 

communities in each system (NRC 2000). The 

failure in most cases of simple nutrient doseecological response models has been noted as a 

reason that complex simulation models may be 

needed to directly model complex ecological 

behavior related to nutrients in coastal waters 

(Fitzpatrick and Meyers 2000, but see Boynton 

and Kemp 2007 for examples of simple models 

that illustrate predictable ecological responses). 

Cloern (2001) outlined how the field of coastal 

eutrophication research has progressed largely 

from limnological concepts to the point where it 

is grappling increasingly with the additional 

complexity of coastal marine systems. 

Recognizing the importance of 

developing numeric nutrient criteria and also the 

difficulty of doing so, this study was undertaken 

to demonstrate an approach that could be used to 

determine numeric nutrient criteria (and criteria 

for nutrient-related response indicators) for a 

single coastal system (Pensacola Bay, FL) with 

which we were very familiar. Like many 

estuaries, Pensacola Bay has not received intense 

research and management focus. Thus, this study 

demonstrates that conclusions can be reached 

regarding criteria with reasonable but still 

incomplete scientific information. To address our 

objectives, we undertook the following: 

• examined the data available to characterize 

current and past water quality conditions in the 

Bay, 

• reviewed the scientific knowledge regarding 

the environmental conditions and processes 

influencing water quality in the bay that could 

inform nutrient criteria setting, 
3 

• compared water quality conditions in 

Pensacola Bay with a group or class of 

estuaries that we expected to share similar 

ecological attributes, and 

• synthesized the assembled information using a 

“weight-of-evidence” approach to suggest 

scientifically justifiable water quality criteria 

for nutrient and nutrient-related water quality 

indicators. 

To place our demonstration in a larger 

context, we discuss the potential for applying the 

demonstrated procedure to other estuaries. 

1.2 Study Site 

The Pensacola Bay system is a complex 

of estuarine bays arranged in two major arms that 

combine to form Pensacola Bay proper. The 

component bays include Escambia Bay, 

Blackwater Bay, East Bay, and Pensacola Bay 

(Figure 1). Santa Rosa Sound is excluded from 

this analysis even 

though it adjoins the 

bay, because in terms of 

important ecological 

processes, it is 

relatively distinct. The 

combined Pensacola 

Bay system is mediumsized (370 km2

) and 

shallow (mean depth = 

3 m) and has been 

characterized as a 

partially stratified, 

drowned river valley 

estuary (Schroeder and 

Wiseman 1999). Tides 

are diurnal and have a 

low amplitude, ranging 

from 15 to 65 cm. The 

basin includes three 

major watersheds that 

drain via the Escambia, 

Blackwater, and Yellow 

rivers. The Escambia 

River discharges into 

Escambia Bay, whereas 

the Blackwater and 

Yellow rivers discharge 

into Blackwater Bay 

and East Bay, the 

eastern branch of the system. Both branches join 

Pensacola Bay, which connects to the Gulf of 

Mexico through the narrow (800-m-wide) 

Pensacola Pass (Figure 1). 

The condition of the Pensacola Bay 

system, particularly that of Escambia Bay, 

became a matter of public concern as early as the 

late 1960s (Olinger et al. 1975), earlier than in 

many estuaries. Initial evidence for a pristine 

condition was based on biological surveys of 

stream fauna (Academy of Natural Sciences of 

Philadelphia 1953). By the early 1960s, after the 

establishment of significant industrial pointsource discharges (especially ammonium [NH4

+

] 

and organic matter), similar biological surveys 

indicated declining health in the river. Reports of 

fish kills and declining fisheries outputs 

ultimately led to actions that, by the mid 1970s, 

greatly reduced the point sources and, in some 
4 

cases, eliminated them completely. Olinger et al. 

(1975) provides a remarkable early compilation 

of ecological conditions in the bay, intended 

principally to document the recovery of the 

system following reductions in industrial waste 

loads. No comparable data were collected after 

1975 until bay-wide water quality surveys were 

begun by EPA beginning in 1996 (U.S. EPA 

2005). Whereas differences in survey 

methodology and 

data reporting 

mostly preclude 

quantitative analysis 

of ecological 

changes, comparing 

early data and the 

conclusions of the 

early investigators 

with more recent 

studies suggests that 

neither the 

ecological 

conditions nor the 

nature of the major 

ecological concerns 

have changed 

dramatically in the 

past 30 years. The 

major ecological 

concerns in 1975 

were bottom water 

hypoxia; loss of 

seagrass habitats; 

toxic contamination; 

and degradation of 

biotic communities, 

including fisheries. 

Bottom water 

hypoxia and loss of 

seagrass habitats, 

both of which are 

likely to be related 

to nutrient 

enrichment, 

continue to be 

concerns for 

Pensacola Bay (U.S. 

EPA 2005). U.S. 

EPA (1999b) 

reported that sediment toxicity in the Pensacola 

Bay system is confined mainly to the three urban 

bayous (Bayou Grande, Bayou Chico, and Bayou 

Texar; Figure 1). However, toxic contamination 

of seafood, especially by mercury, remains a 

regional issue in the Gulf of Mexico. Blue crab 

(Callinectes sapidus) in Pensacola Bay have been 

shown to be contaminated with polychlorinated 

biphenyls, likely acquired by bioaccumulation 
5 

from residual contamination of sediments 

(Karouna-Renier et al. 2007). 

Many of the important ecological 

processes and environmental concerns, including 

the human and aquatic life uses of the bay and 

the major stressors of the ecosystem can be 

summarized effectively and communicated in a 

conceptual model (Figure 2). Developing such a 

model, or at least acquiring the information 

necessary to do so, is probably an important step 

toward determining a scientifically sound 

procedure for deriving nutrient criteria. By 

comparing and contrasting conceptual models for 

different systems, one can gain a greater 

understanding of the similarities and differences 

among those systems and how those differences 

may impact criteria development. We include our 

conceptual model without extensive discussion 

here because many aspects of the model are 

addressed in subsequent sections.
6 
7 

2. Methods 

This study is based on “found” data from 

several types of sources, including national 

databases, water quality surveys, and aerial 

remote sensing. The following describes the data 

collected and either the methods or appropriate 

references describing the methods. 

2.1 Water Quality Data for 

Pensacola Bay 

Two major studies provided the majority 

of the water quality data for Pensacola Bay used 

in this study (Table 1). In the first study 

(hereafter “quarterly survey”), 38 sites selected 

using a probabilistic survey design (Summers 

et al. 1995, U.S. EPA 2005) were sampled 

quarterly (spring, summer, fall, and winter) 

during surveys beginning in May 1996 and 

concluding in February 2001. In the second study 

(hereafter “monthly survey”), 29 water quality 

surveys were conducted approximately monthly 

from April 2002 through December 2003 and 

from May 2004 through November 2004 (e.g., 

Hagy and Murrell 2007). Monthly surveys 

included 15 sites oriented along two axial 

transects of Pensacola Bay (Figure 1). Additional 

water quality data were obtained from Florida’s 

Inshore Marine Monitoring and Assessment 

Program (IMAP; McRae et al. 2004), which 

collected a total of 64 observations on multiple 

water quality variables in the Pensacola Bay 

system between 2000 and 2004. Most 

observations (53 of 64) were made during an 

intensive survey in 2003. 

2.2 Ecoregional Water Quality 

Characterization 

To compare water quality in Pensacola 

Bay with other estuaries in the region, water 

quality statistics were summarized for estuaries 

in EPA’s Level III ecoregion 75 (Omernik 1995), 

encompassing the southeast coastal plain and 

Florida’s Level IV ecoregion 75a (Griffith et al.

1994), encompassing the west Florida panhandle 

region eastward to the Big Bend region of Florida 

(Figure 3). Because these ecoregions are defined 

to encompass regions of land, not water, estuaries 

were associated with an ecoregion when the land 

surrounding the estuary was substantially within 

ecoregion boundaries. Thus, Florida’s ecoregion 

75a includes all inshore marine waters from 

Perdido Bay eastward to the Suwannee River 

(Figure 3). Water quality data for the ecoregional 

characterization were obtained from IMAP 

(McRae et al. 2004) and EPA’s National Coastal 

Assessment (NCA; U.S. EPA 2004). Both 

assessment studies utilized a probabilistic survey 
8 

Figure 3. The locations of water quality monitoring 

stations visited under EMAP during 2001 and 2002 and 

IMAP during 2000 to 2004. The distribution of sampling 

stations within the southern coastal plain ecoregion 

(region 75 of EPA Level III ecoregions) (upper panel) and 

within the Gulf Coastal Flatwoods region (Florida’s Level 

IV ecoregion 75a) (lower panel). NCA stations were 

omitted from the ecoregion 75a analysis. Estuarine 

drainage areas in ecoregion 75a, as defined under 

NOAA’s coastal assessment framework, are identified as 

follows: A = Perdido Bay, B = Pensacola Bay, 

C = Choctawhatchee Bay, D = St. Andrew Bay, E = 

Apalachicola Bay, F = Apalachee Bay, and G = 

Suwannee River.

Figure 4. Procedure for computing statistical comparison 

values for estuaries. The 25th percentile of estuary 

medians was used for comparison values for water quality 

indicators where lower values are better (e.g., nutrients, 

chlorophyll-a). The 75th percentile was used for secchi 

depth, where higher values indicate higher water clarity.

design with sampling conducted only during a 

late summer index period (Table 1, Figure 3). 

The procedure for water quality 

characterization (Figure 4) involved computing, 

for each variable of interest, the median of all 

water quality observations in each of three 

salinity zones in each estuary. We defined three 

salinity zones based on surface salinity values: 

(1) oligohaline (salinity < 5), (2) mesohaline 

(salinity 5 to 18), and (3) polyhaline (salinity > 

18). We defined each estuary according to the 

boundaries of estuarine drainage areas (EDAs) 

defined by the National Ocean and Atmospheric 

Administration's Coastal Assessment Framework 

(NOAA 1999a). Data from IMAP and NCA were 

referenced to EDAs within the coastal assessment 

framework using a geographic information 

system (ArcGIS 9.2, ESRI, Inc.). Data not falling 

within EDAs, such as those falling within 

“coastal drainage areas,” were excluded from the 

analysis. 

2.3 Aerial Submerged Aquatic 

Vegetation Surveys 

Data describing the extent of submerged 

aquatic vegetation (SAV) in Pensacola Bay were 

obtained from investigations that employed 

interpretation of aerial photographs taken as early 

as 1949 and as recently as 2003. Maps of SAV 

coverage for circa 1950 were obtained from 

Olinger et al. (1975), who interpreted 

photographs obtained for highway construction. 

For this study, maps from Olinger et al. (1975) 

were scanned to TIFF files, geo-referenced 

against corresponding modern shorelines, and 

then manually digitized to a vector coverage at 

the same resolution as the original map (modern 

shoreline extracted from 1:100,000 scale digital 

line graphs by the U.S. Geological Survey 

(USGS) National Wetlands Research Center, 

Gulf Breeze, FL, Project Office). Tabulated SAV 

coverages for 1960, 1980, and 1992, were 

obtained from Schwenning et al. (2007), which 

also describes the photo-interpretation and 

digitization protocols (also see Lores et al. 2000). 

SAV coverage data for 1992 and tabulated SAV 
9 

coverage data for 2003 were obtained from the 

USGS National Wetlands Research Center, 

Lafayette, LA. 

2.4 Watershed Characteristics and 

Land Use 

Data describing land use in the Pensacola 

Bay watershed were obtained from the 2001 

National Land Cover Database using the MultiResolution Land Cover Consortium Viewer 

(Homer et al. 2004; http://www.mrlc.gov/). The 

database provides land use and land cover 

classifications at 30-m resolution. Classifications 

are derived from Landsat-7 Enhanced Thematic 

Mapper imagery and additional supporting data. 

Land cover data for the Pensacola Bay watershed 

were extracted from the larger data set and 

tabulated by classification using the ArcGIS 9.2 

geographic information system indicated above. 
10
11

3. Results and Discussion 

3.1 Ecoregional Comparisons and the 

Percentile Approach 

Identifying appropriate benchmarks or 

“reference conditions” against which to compare 

water quality conditions is a key feature of EPA’s 

recommended approaches for developing nutrient 

criteria (U.S. EPA 2000a,b). We modified EPA’s 

percentile approach for freshwaters to define 

benchmark water quality values that have 

potential applicability to Pensacola Bay. 

A central feature of the approach, which we 

applied here, is identification of a suitable class 

of similar estuaries from which a reference 

condition can be determined. In the context of 

nutrients, similarity refers to a similarity in 

ecological attributes that influence the response 

of a system to nutrient inputs. 

There are many classification schemes for 

coastal systems, each serving different objectives 

and emphasizing different ecological attributes 

(Kurtz et al. 2006). Unfortunately, there is little 

consensus regarding which classification 

schemes would be most appropriate in terms of 

predicting response to nutrient inputs. None have 

been demonstrated to be useful for that purpose. 

One concern is that, even though many important 

attributes of estuaries have been considered (e.g., 

residence time, mean depth, ratio of watershed 

area to estuary area; Kurtz et al. 2006), a much 

broader set of factors (e.g., climate, geology, 

character of offshore water quality) likely 

contributes to the ecological character of 

ecosystems. 

As an alternative to the available 

estuarine classifications, we utilized EPA’s Level 

III ecoregions and, simultaneously, the more 

finely resolved Level IV ecoregions for Florida 

to define a class of estuaries for Pensacola Bay. 

Pensacola Bay lies within the “southern coastal 

plain” ecoregion 75 in the Level III scheme 

(Figure 3). The shores of Pensacola Bay include 

several of Florida’s Level IV ecoregions, but the 

“Gulf coastal flatwoods region” (ecoregion 75a) 

encompasses much of the coast surrounding 

Pensacola Bay and a significant span of coastline 

mostly to the east of the bay (Figure 3). Although 

the definition of these ecoregions is based on 

climatological, geological, and biological 

attributes (Omernik 1987) and pertains to the 

watersheds of estuaries rather than to the 

estuaries themselves, we expect that the 

ecological character of inshore coastal waters 

must reflect to some degree the ecological 

attributes of the surrounding land. Moreover, 

because the ecoregions define geographically 

contiguous regions of the coast, we expect 

similarity in many attributes to arise simply from 

proximity. Important differences can occur, 

however, particularly when the ecoregion spans 

oceanographically distinct regions. For example, 

tides vary dramatically within ecoregion 75; 

minimal diurnal tides occur on the northern Gulf 

coast, whereas large semidiurnal tides occur 

along the Atlantic coast of Georgia and South 

Carolina. These differences alone contribute to 

other large ecological differences, such as the 

presence of extensive intertidal salt marshes in 

Georgia (Dame et al. 2000), which practically 

define the Georgia coast, versus the more limited 

extent of salt marshes in west Florida. The 

smaller spatial extent of Florida’s Level IV 

ecoregions eliminates the most glaring withinclass differences, but at the cost of a class that 

includes fewer systems. Even though it is likely 

that important differences remain within even 

these smaller classes, further division leads 

toward the perspective that every estuary is 

completely unique, precluding any role for 

comparative ecological analysis in development 

of nutrient criteria. 

U.S. EPA (2000a,b) define a variety of 

options for determining reference conditions for 

classes of freshwater systems. The preferred 

approach is to derive water quality criteria on the 

basis of conditions in relatively pristine water 

bodies. When a set of sufficiently pristine water 
12

bodies can be identified, criteria have been based 

on the 75th percentile of water body median 

values for such pristine sites (U.S. EPA 2000a,b). 

Given the pervasive human presence in many 

coastal marine areas, we assumed that few, if 

any, estuaries were sufficiently pristine to adapt 

this approach for estuaries. Another approach is a 

historical reference condition in which water 

quality conditions observed prior to significant 

anthropogenic impacts provide a basis for 

comparison. For most estuaries, limited 

availability of historical data precludes this 

approach. The record of historical water quality 

data for Pensacola Bay is unusually extensive, 

but, as is common, early monitoring was 

undertaken in response to obvious pollution 

impacts (Olinger et al. 1975) and does not 

quantify the unimpaired or pristine condition. 

Thus, historical data cannot be used to 

characterize pristine water quality conditions in 

Pensacola Bay. Lacking either pristine sites or 

adequate historical data, we derived levels we 

call “comparison values” from the statistical 

distribution of water quality conditions in all the 

estuaries in the class (Figure 4), adapting the 

percentile approach of U.S. EPA (2000a,b). 

Because the class includes sites subject to a range 

of nutrient enrichment, we utilized the 25th 

percentile of estuary median water quality values 

to derive comparison values. EPA (2000a,b) cite 

empirical evidence from lakes to support this 

choice when reference quality sites are not 

available. We did not assume that there is any 

relationship between the 25th percentile of 

estuary median water quality and water quality in 

a hypothetical set of pristine estuaries. We simply 

chose to examine the 25th percentile as a 

potentially useful reference point in the 

distribution of estuary medians. For water clarity, 

the same ideas apply, but higher values indicate 

“better” water quality. Therefore, we used the 

75th percentile as a comparison value. We 

contrasted values based on two classes: (1) all 

estuaries in ecoregion 75 (Appendix A) and 

(2) the subset of those estuaries within ecoregion 

75a (Appendix B). 

Our application of the percentile approach 

differs from that of U.S. EPA (2000a,b) in 

several important ways. First, because the 

available regional-scale data sets from NCA and 

IMAP include only late summer data (Table 1), 

our analysis is limited to summer (June through 

September). We do not see this as a major 

limitation because most water quality problems 

related to nutrient enrichment, especially 

hypoxia, are expressed primarily during summer. 

Thus, we assumed that, if water quality supports 

the designated uses during summer, uses outside 

of summer are also likely to be met. The second 

difference is that we divided observations into 

salinity zones, based on the principle that water 

quality parameters in estuaries commonly vary 

along the salinity gradient. We selected three 

zones (salinity < 5, 5-18, and > 18) with the 

objective of resolving differences associated with 

the salinity gradient, while ensuring that a 

sufficient quantity of data was available in each 

zone in most estuaries. Our objectives in defining 

the zones likely could have been met with 

different definitions (i.e., breakpoints); however, 

an attempt to define values for a greater number 

of salinity zones likely would have resulted in 

excessive parsing of the available data. Finally, 

we consider the values obtained via this approach 

to be guidelines or comparison values, not values 

that can be adopted defensibly as criteria without 

further scientific support. 

The computed median values show that 

summer water quality in a significant portion of 

estuaries in ecoregions 75 and 75a was 

characterized by low nutrient and moderate 

chlorophyll-a concentrations, with concentrations 

generally lower in ecoregion 75a than in 

ecoregion 75 as a whole (Figure 5, Table 2). 

Concentrations of chlorophyll-a, nitrogen, and 

phosphorus are commonly higher in Mid-Atlantic 

estuaries (NOAA 1997). Nutrient concentrations 

are commonly higher in Pacific coast estuaries 

influenced by coastal upwelling (NOAA 1998). 

Summer median nutrient concentrations and 

water clarity in Pensacola Bay were comparable 

to or lower than the 25th percentile (higher than 

the 75th percentile for water clarity) for the 

ecoregion, with a few exceptions. 
13

Figure 5. Distribution of summer estuary median surface water quality values by 

salinity zones for estuaries in Level III ecoregion 75 (left three plots) and Level IV 

ecoregion 75a (right three plots). Salinity zones are oligohaline (O; salinity < 5),

mesohaline (M; salinity 5-18)], polyhaline (P; salinity > 18). Red lines indicate summer 

medians by salinity zone for Pensacola Bay. Identical values are shown in both the left 

and right halves of each plot. DIN = NO2

-

+ NO3

-

+ NH4

+

; TN = total nitrogen, TP = total 

phosphorus.

Inorganic nitrogen and phosphorus 

concentrations in oligohaline waters were higher 

than the 25th percentile, but concentrations in 

higher salinity water were comparable or lower 

than the corresponding 25th percentile in those 

salinity zones. Total phosphorus (TP) 

concentrations were comparable to the 25th 

percentile values across the salinity zones, 

whereas total nitrogen (TN) concentrations were 

comparatively lower in oligohaline waters and 

higher in polyhaline waters (Figure 5, Table 2). 

Median chlorophyll-a was higher in Pensacola 

Bay than the 25th 

percentile values in all 

salinity zones for both 

ecoregion 75 and 

ecoregion 75a (Table 2). 

Instead, median 

chlorophyll-a in 

Pensacola Bay was 

similar to the median for 

ecoregion 75 and closer 

to the upper quartile for 

ecoregion 75a (Figure 5). 

The statistical 

approach described here 

is a repeatable, 

quantitative scheme for 

computing water quality 

measures that can serve 

as comparison values for 

both causal variables 

(e.g., nutrients) and 

nutrient-related response 

variables such as water 

clarity (secchi depth) and 

chlorophyll-a. In the 

absence of water quality 

thresholds clearly tied to 

loss of ecological 

integrity, these 

comparison values are 

useful for placing values 

for any one estuary in 

perspective. There are 

several factors that limit 

the range of 

interpretations for these 

comparison values. One 

question is whether the 25th percentile (or 75th 

percentile for water clarity) of estuary medians is 

an appropriate comparison value, and whether it 

approximates a minimum condition protective of 

designated uses as suggested by EPA (2000a,b). 

A broader comparison with the distribution of 

values in the ecoregion (i.e., Figure 5) gives a 

more complete comparative perspective but still 

leaves open the question of whether a particular 

water quality value supports use attainment. 

Water quality values at the 25th percentile of the 

ecoregional distribution could be either 
14

nd = No data 

nonprotective of uses or excessively restrictive 

for a particular estuary. A second concern is the 

assumption that the estuaries in either ecoregion 

75 or ecoregion 75a are an appropriate “class,” 

and that Pensacola Bay is a member of that class. 

We suggest that the percentile approach is likely 

to produce values in a reasonable range for 

estuaries, but that, because the approach is 

inherently independent from effects-based 

considerations and is not certain to generate 

appropriate values, the values should be 

evaluated in the context of other information 

available about the estuary in question before 

they could be used to determine criteria. In the 

following sections, we discuss ecological 

conditions and processes in the Pensacola Bay 

system to provide a thorough evaluation of the 

science that may be pertinent to selection of 

numeric nutrient criteria. 

3.2 Algal Biomass, Productivity, and 

Community Composition

Chlorophyll-a is an easily monitored and 

conceptually appealing indicator of trophic status 

and eutrophication in aquatic systems, obvious 

reasons why it already is used widely in water 

quality management related to nutrients. Other 

simple descriptors of the phytoplankton 

community, such as productivity; community 

composition, including presence of harmful 

algae; and growth dynamics, also can provide 

useful insights. We assembled basic information 

about the phytoplankton community in Pensacola 

Bay to explore its implications, if any, for 

managing nutrients in the bay. 

Seasonal and salinity zone chlorophyll-a 

medians varied between 1.6 and 7.4 μg L-1, with 

the highest values during summer (5.6 to 

7.3 μg L-1; Table 3). Both summer and nonsummer values were “low” to “medium” 

according to standard ranges described by NOAA 

(1997). “High” concentrations (>20 μg L-1) 

occurred very infrequently (Table 3, Figure 6). 

Of 1,390 chlorophyll-a measurements in the 

Pensacola Bay system between 1996 and 2004, 

only 36 (2.5%) were greater than 20 μg L-1. 

Murrell et al. (2007) measured phytoplankton 

production rates in Escambia Bay using carbon 

Table 2. Ecoregional water quality conditions for chlorophyll-a (Chl-a), secchi depth, dissolved inorganic 

nitrogen (DIN = NO2

-

 + NO3

-

 + NH4

+

), phosphate (PO4

3-

), total nitrogen (TN), and total phosphorus (TP) computed 

for EPA’s Level III ecoregion 75 and Florida’s Level IV ecoregion 75a. Values are the 25th percentile of summer 

estuary medians, except for secchi depth, where the value is the 75th percentile of estuary medians. Summer 

medians for Pensacola Bay are shown for comparison. Data are for surface water. Values in parentheses for 

ecoregion 75 and 75a are the number of estuaries included for each variable. Values in parentheses for 

Pensacola Bay are the number of observations included. TN and TP values were not computed for ecoregion 75 

because data were only available for a portion of the ecoregion. Pensacola Bay medians were computed from a 

combined data set that includes EPA’s EMAP quarterly surveys (1996 to 2001, EPA’s monthly surveys (2002 to 

2004), and Florida’s IMAP surveys. IMAP sampled Pensacola Bay intensively in 2003 and also visited two

stations in 2004.

Group

Chl-a

(μg l-1)

Secchi Depth

(m)

DIN

(μM)

PO4

3-

(μM)

TN

(μM)

TP

(μM)

Oligohaline (Salinity < 5)

Ecoregion 75 3.8 (16) 0.93 (12) 2.9 (15) 0.11 (15) nd nd

Ecoregion 75a 2.1 (6) 1.6 (4) 2.6 (6) 0.023 (6) 23.4 (6) 0.67 (6)

Pensacola Bay 5.6 (103) 0.9 (93) 8.7 (102) 0.18 (86) 29.2 (49) 0.88 (32)

Mesohaline (Salinity 5-18)

Ecoregion 75 5.1 (21) 1.0 (21) 1.3 (20) 0.13 (21) nd nd

Ecoregion 75a 4.1 (7) 1.0 (7) 0.81 (7) 0.065 (7) 26.5 (7) 0.56 (7)

Pensacola Bay 7.3 (233) 1.2 (198) 0.97 (210) 0.11 (122) 31.7 (59) 0.55 (47)

Polyhaline (Salinity > 18)

Ecoregion 75 4.3 (28) 1.3 (28) 0.59 (27) 0.11 (28) nd nd

Ecoregion 75a 3.5 (6) 1.4 (5) 0.47 (6) 0.052 (6) 20.5 (6) 0.73 (6)

Pensacola Bay 5.8 (107) 2.0 (100) 0.44 (102) 0.048 (82) 32.7 (57) 0.43 (56)
15

Figure 6. Frequency histogram of surface chlorophyll-a 

concentrations in mesohaline (surface salinity = 5-18) waters of 

the Pensacola Bay system from 1996 to 2001. “Low,” “Medium,” 

and “High” designations refer to descriptors used by NOAA 

(1997). Dotted lines indicate the median concentration. Data are 

from the EPA/ORD quarterly surveys of Pensacola Bay.

Table 3. Seasonal median chlorophyll-a in Pensacola 

Bay surface waters and its interquartile range (25th

to 75th percentile). Salinity zones were determined 

from surface water salinity.

Median 

Chlorophyll-a

(μg L-1)

Interquartile 

Range

(μg L-1)

Oligohaline (Salinity < 5)

Winter 2.2 (1.2 - 3.7)

Spring 4.0 (2.6 - 5.4)

Summer 5.6 (3.8 - 8.7)

Fall 1.6 (1.2 - 3.7)

Mesohaline (Salinity 5-18)

Winter 3.5 (2.6 - 5.2)

Spring 5.8 (3.7 - 8.4)

Summer 7.3 (5.1 - 10.7)

Fall 5.0 (3.1 - 7.2)

Polyhaline (Salinity > 18)

Winter 3.4 (2.6 - 4.7)

Spring 3.8 (2.1 - 4.8)

Summer 5.8 (3.8 - 8.1)

Fall 3.4 (2.5 - 6.0)

14 uptake methods and estimated that annual 

phytoplankton productivity was 320 g carbon m-2

year

-1 (0.88 g carbon m-2 day-1). Among estuaries, 

where annual production commonly varies 

between 100 and 500 g carbon m-2 year

-1

(Boynton et al. 1982, Boynton and Kemp 2007), 

the annual production rate for Pensacola Bay is 

“mesotrophic” or moderate. The summer 

phytoplankton assemblage is dominated by 

cyanobacteria (Murrell and Lores 2004, 

Murrell and Caffrey 2005), whose low 

chlorophyll-a content relative to carbon 

(phycoerythrin is the dominant light-gathering 

pigment in most cyanobacteria; MacIntyre 

et al. 2002) undoubtedly contributes to the 

high ratio of annual productivity to 

chlorophyll-a. The phytoplankton community 

in Pensacola Bay is usually nutrient limited 

and can be limited by either phosphorus or 

nitrogen (Murrell et al. 2002, Juhl and Murrell 

2005). Relief of nutrient limitation associated 

with periods of increased freshwater and 

nutrient inputs manifests as increased 

chlorophyll-a concentration, increased 

phytoplankton production (Murrell et al. 

2007), and a greater relative abundance of 

eukaryotic phytoplankton (Juhl and Murrell 

2005) in Pensacola Bay. 

The available information points to 

several key conclusions regarding the 

phytoplankton community in Pensacola Bay. 

First, there is no clear evidence that the 

phytoplankton community is stimulated strongly 

by excess nutrients, or that it is unbalanced or 

otherwise causing adverse ecological effects. If 

chlorophyll-a concentrations were frequently in 

NOAA’s (1997) high (20 to 60 μg L-1) or 

“hypereutrophic” (>60 μg L-1) range, or, if 

annual phytoplankton productivity was among 

the highest found in estuaries, one might have 

a priori cause for concern regarding excess 

phytoplankton. Median summer chlorophyll-a 

concentrations were generally higher than the 

25th percentile of systems within the ecoregion, 

especially for ecoregion 75a (Table 2). However, 

the small differences are probably not 

ecologically significant. We do not know of any 

study directly implicating chlorophyll-a 

concentrations in the low range observed in 

Pensacola Bay with failure to support any human 

or aquatic life uses. Experimental evidence 

(Murrell et al. 2002, Juhl and Murrell 2005) 

shows that phytoplankton biomass and 

production in Pensacola Bay are limited by 

nutrients. This provides a mechanistic 

expectation that increased nutrient inputs will 
16

Figure 7. Observations of bottom dissolved oxygen in the 

Pensacola Bay system during the summers of 1996 through 

1999 indicating the locations and frequency of observations 

less than 2.0 mg L-1, a level commonly used as an 

operational definition of hypoxia. Data are from EPA/ORD 

quarterly surveys (upper panels). The computed extent of 

hypoxia in Pensacola Bay by month from 2002 to 2004, 

based on EPA/ORD monthly transect surveys (lower panel).

increase phytoplankton production and possibly 

phytoplankton biomass. Unfortunately, simple 

linear dose-response relationships fail to capture 

the relationship between nutrient loads or 

concentrations and chlorophyll-a in Pensacola 

Bay (Murrell et al. 2007). Relationships that we 

expect to observe on the basis of known causal 

mechanisms often are hidden by the natural 

complexity that characterizes estuarine 

ecosystems (e.g., flushing, food web interactions) 

and, therefore, are not easily seen in field 

observations (Cloern 2001). Some empirical 

relationships between nutrients and chlorophyll-a 

have been found among systems and, through 

time, within systems (Boynton et al. 1982); 

however, such relationships usually are only 

adequate to provide broad direction for 

management (i.e., increased nutrients are 

associated with higher chlorophyll-a). 

Nonetheless, it is important and useful to 

recognize that, on the basis of experimental 

evidence documenting nutrient limitation of 

phytoplankton, we expect that increased nutrient 

inputs would increase phytoplankton production 

and biomass in Pensacola Bay. 

3.3 Preventing Hypoxia 

Hypoxia, which we define here as 

DO < 2 mg L-1, is a common phenomenon in 

bottom waters of Pensacola Bay (Hagy and 

Murrell 2007). Where it occurs, hypoxia should 

be a concern because of its direct impact on 

marine life (Diaz and Rosenberg 1995). Globally, 

hypoxia has increased in coastal waters in some 

relation to nutrient overenrichment, commonly 

causing negative effects on the health and 

productivity of biological communities (Diaz 

2001). Thus, hypoxia is a significant threat to 

both human (e.g., fisheries) and aquatic life use 

attainment in coastal systems. 

Observations of hypoxia in the Pensacola 

Bay system date back to Hopkins (1969), who 

found oxygen concentrations as low as 

0.48 mg L-1 in bottom waters of Escambia Bay 

during a late-summer study. Olinger et al. (1975) 

reported bottom water oxygen less than 1 mg L-1

in Escambia Bay but concluded that conditions 

had improved since 1969. The recent monthly 

survey data (Table 1) show that hypoxic bottom 

waters occurred between April and November, 

with the maximum extent in late summer 

(Figure 7). Hypoxia currently affects an average 

of 25% of the bay bottom during summer and 

can, at times, affect a much larger fraction 

(Figure 7). 

Olinger et al. (1975) recognized long ago 

that the bay often was strongly stratified, and that 

weak circulation probably contributed to the risk 

of hypoxia. Hagy and Murrell (2007) quantified 

the stratification and circulation to better 

characterize conditions that create a high 

susceptibility to hypoxia. They found that 

hypoxia developed in Pensacola Bay despite 

moderate oxygen consumption rates in the lower 

water column and sediments. Total (i.e., 

combined) oxygen consumption for the lower 

water column and sediments was estimated to be 

0 to 1.5 g oxygen m-2 day-1 using a box model 

(Hagy and Murrell 2007). The model estimates 

were in reasonable agreement with average 

integrated oxygen consumption rates (0.94 g 

oxygen m-2 day-1) measured during summer at 
17

several stations throughout the Pensacola Bay 

system (Table 4). Oxygen consumption in 

Pensacola Bay is low compared with other 

estuarine and coastal marine systems (e.g., 

Hopkinson 1985, Cowan et al. 1996) and is much 

lower than rates from a very eutrophic system 

such as the Chesapeake Bay, where integrated 

metabolism below the pycnocline can exceed 

10 g oxygen m-2 day-1 (Kemp et al. 1997). 

Table 4. Plankton community respiration rate (Rp) 

integrated from the pycnocline to sediments (i.e., 

lower water column) and sediment oxygen demand 

(SOD) at stations in the Pensacola Bay system 

(Figure 1) with varying levels of bottom water (BW) 

oxygen (mg L-1). SOD was measured using 5-hour 

incubations of diver-collected cores. Plankton 

respiration rates were measured in 24-hour 

incubations in BOD bottles. All rates have units of g 

oxygen m-2 day-1. Unpublished data provided by M. 

Murrell.

Station

BW

O2 SOD Rp Total

PCOLA28 5.2 0.32 0.34 0.66

PCOLA20 2.5 0.27 0.07 0.34

PCOLA29 0.7 0.04 0.25 0.29

BP04 4.2 0.37 0.86 1.23

PCOLA26 1.1 0.12 0.88 1.00

BP03 5.0 0.38 1.48 1.86

P05C

 (6/28/04) 1.6 0.48 0.58 1.06

P05C

 (7/27/04) 1.4 0.50 0.59 1.09

Average  0.31 0.63 0.94

Coastal systems can be naturally 

susceptible to hypoxia. A well-known example 

on the Gulf coast is the occurrence of “jubilee” 

events, in which marine animals (especially 

crabs) climb onto the beach to avoid low-oxygen 

waters. Jubilees have occurred in Mobile Bay, 

AL, for more than a century (May 1973, 

Schroeder and Wiseman 1988). There is 

presently no evidence that hypoxia did not occur 

in Pensacola Bay prior to significant human 

influence, nor are there adequate data to 

document any trend in dissolved oxygen (DO) 

during the past several decades. Nevertheless, 

because relatively extensive hypoxia occurs 

presently in Pensacola Bay, hypoxia should be a 

focus for water quality management. We can 

infer that hypoxia presently limits human and 

aquatic life uses of Pensacola Bay because the 

direct effects of hypoxia on many species of 

marine life are known (Diaz and Rosenburg 

1995, Campbell and Goodman 2004). Although 

current science for Pensacola Bay cannot predict 

the magnitude of increase in extent or severity of 

hypoxia expected from a particular increase in 

nutrient inputs or the extent to which the severity 

of hypoxia might increase, both conceptual and 

quantitative models indicate that increased 

nutrients most likely would increase the extent 

and severity of hypoxia, resulting in loss of 

existing aquatic life uses. 

Defining a broadly applicable approach 

for determining DO criteria in estuaries where 

hypoxia may occur naturally is a difficult 

proposition. The ecoregional approach that we 

applied for nutrients and chlorophyll-a may not 

be adequate for DO because EPA’s Level III 

ecoregions do not reflect the physical 

oceanographic characteristics of estuaries that 

influence the development of hypoxia. In fact, 

none of the classification schemes that have been 

devised for estuaries have been shown to be 

effective for grouping systems according to their 

intrinsic vulnerability to hypoxia. Moreover, the 

data sets and statistical indicators (i.e., medians) 

that we used are not suitable to characterize the 

extent of hypoxia in most instances; the estuary 

median generally provides little information 

about the extent of bottom DO. For Pensacola 

Bay, where an average of 25% of the bottom is 

hypoxic during summer, the median 

concentration is, by definition, higher than our 

defined threshold (i.e., >2.0 mg L-1). Relatively 

elaborate DO criteria have been developed for 

Chesapeake Bay based on a tiered aquatic life use 

approach and the oxygen levels known to be 

minimally supportive of those uses (U.S. EPA 

2003). The complex approach utilized for 

Chesapeake Bay, however, may not be feasible 

for many of the nation’s estuaries because the 

information required to delineate tiered-use areas 

is not available. For Pensacola Bay, it may be 

reasonable to define only two areas: (1) the area 

that is susceptible to hypoxia, which would have 

a criteria defined in terms of areal extent; and (2) 

an area that is much less susceptible to hypoxia 

(e.g., surface waters), for which criteria could be 

defined in terms of the requirements of resident 
18

Figure 8. Coverage of submersed aquatic vegetation in 

Pensacola Bay circa 1950 and in 1992. Data for circa

1950 were digitized from coverage maps reported by 

Olinger et al. (1975). Areas for which no coverage data 

was available are indicated by “nd.” SAV coverage for 

1992 is from the USGS National Wetlands Research 

Center, Lafayette, LA.

biota. Current areal extent of bottom water 

hypoxia is well defined and could provide the 

basis for a criterion defined as a multiyear 

average extent (e.g., 3 years). A reasonable 

implementation strategy must include an 

averaging period of several years because the 

extent of hypoxia varies strongly on an 

interannual basis (Figure 7). Freshwater inflow 

level, which varies from year to year, is an 

important driver of such changes (Hagy and 

Murrell 2007). For above-pycnocline waters and 

nonstratified waters, DO concentrations should 

be greater than 4.0 mg L-1

, a level sufficient to 

prevent most impacts on marine life in Pensacola 

Bay (assuming summer temperature ≈30 °C) and 

that is also consistent with current Florida criteria 

for Class III marine waters (FAC 2005). In the 

monthly survey data, DO concentrations in the 

bay exceeded this value almost all the time. The 

Florida statute also requires a minimum of 

5.0 mg L-1 as a 24-hour average. This is most 

likely met much of the time as well, but, because 

most of the available data in the estuary are 

daytime point observations, good estimates of the 

24-hour average are not available. 

Design of compliance monitoring is an 

important consideration for DO because 

sampling must adequately quantify spatial extent 

for hypoxia in bottom waters and minimum 

concentration for other waters. The data sets for 

Pensacola Bay illustrate the potential for 

problems. Florida’s IMAP measured bottom 

water oxygen at 29 stations in Pensacola Bay 

during an intensive probabilistic survey in 2003, 

observing oxygen < 2 mg L-1 at 6 stations (21%), 

which can be interpreted to mean that 21% of the 

bottom was hypoxic. The transect-based surveys 

obtained similar results. In 2004, however, IMAP 

visited just two sites and observed no hypoxia, 

even though hypoxia was much more extensive 

in Pensacola Bay in 2004 than in 2003 (Figure 7). 

Neither the transect surveys nor the probabilistic 

IMAP surveys sampled at night, when minimum 

concentrations may have occurred. 

3.4 Protecting Seagrass Habitats 

One of the most widespread and wellrecognized consequences of nutrient enrichment 

in coastal systems is the loss of submerged rooted 

vascular plants (commonly referred to as 

submerged aquatic vegetation [SAV]), which are 

well adapted to low-nutrient, high-light 

environments (Short and Wyllie-Echevarria 

1996). Excess nutrients have been cited 

specifically as a major cause of SAV loss in the 

northern Gulf of Mexico, including every major 

estuary in northwest Florida (USGS 2004). Other 

causes of SAV loss, such as prop scarring, 

disease, and even food web shifts also have been 

identified (Dawes et al. 2004). 

Historically, the SAV bed extended along 

a large fraction of the shoreline of Pensacola Bay 

(Figure 8). Olinger et al. (1975) delineated the 

extent of SAV beds from aerial photographs 

taken as early as 1949. Aerial photography was 

conducted for the purpose of highway 

construction and was repeated at sporadic 

intervals, according to highway construction 
19

needs. The result is an irregular series of SAV 

coverage maps (Olinger et al. 1975, also 

reproduced by Lores et al. 2000). Although 

several areas of the estuary never were surveyed 

during this time period, SAV beds delineated 

within the available imagery covered 17.7 km2

from 1949 to 1951 (Table 5). By overlaying the 

circa 1950 SAV coverage map on the bathymetry 

of the bay (based on 1993 surveys [Divins and 

Metzger, public communication]), one can 

estimate that SAV attained a maximum 

colonization depth of as much as 6 m in 

Pensacola Bay, 2 to 3 m in East Bay, and 1 to 2 

m in the presently more turbid areas of northern 

Escambia Bay. Based on average light 

requirements for seagrasses (Duarte 1991), 

average secchi depth may have been nearly 5 m 

in portions of Pensacola Bay. Water clarity is 

currently much less than this (Figure 5), although 

several observations approaching this value were 

made during the monthly surveys. 

nd = No data 

 SAV surveys in Escambia Bay show that 

significant SAV loss occurred within a few years 

of the earliest surveys (Olinger et al. 1975), and 

that SAV virtually was eliminated in much of the 

Pensacola Bay system by 1980 (Schwenning 

et al. 2007). Particularly rapid and complete SAV 

loss occurred in the Floridatown area of northeast 

Escambia Bay (Figure 8) following initiation of 

industrial point source discharges in the area. 

Approximately 50% of SAV was lost bay-wide 

by 1960, and all but a few percent by 1980 

(Table 5). SAV coverage in nearby Santa Rosa 

Sound also declined about 50% between 1960 

and 1980 and remained relatively constant 

thereafter (Table 5). The freshwater SAV species 

Vallisneria americana accounted for >80% of the 

1992 coverage in Escambia Bay, mostly in the 

Escambia River delta, with limited beds of 

Ruppia maritima also present (Lores et al. 2000). 

These beds suffered massive mortality because of 

high salinity in 2000 (Lores and Sprecht 2001) 

and recovered only partially by 2003. Most of the 

SAV habitats remaining in the Pensacola Bay 

system are in Santa Rosa Sound. These beds are 

dominated by Thalassia testudinum, with 

Halodule wrightii also present. Although still 

significant in coverage, we have observed that 

the vegetation appears stunted and sparse 

compared to apparently healthier beds in 

northwest Florida (e.g., St. Joseph’s Bay). 

 The decline in SAV coverage between 

1950 and 1980 has been attributed to poor water 

quality resulting from industrial pollution and, to 

a very limited extent, to dredging for harbor 

construction (Olinger et al. 1975). The causal 

relationships between 

current water quality 

and the present 

distribution of SAV are 

not clear. The 

underwater light 

environment has been 

cited as the most 

important predictor of 

SAV survival. 

Thalassia requires 20% 

to 25% of surface 

irradiance at its 

maximum colonization 

depth (Duarte 1991, Dawes et al. 2004). 

Assuming a conservative 25%, the light field in 

Pensacola Bay is currently adequate to support 

Thalassia to a depth of approximately 2 m in the 

polyhaline reaches (where salinity is appropriate 

for Thalassia), consistent with its present 

maximum colonization depth. 

SAV is absent from many places in 

Pensacola Bay where light appears to be 

adequate, an observation for which there are 

many possible explanations (Koch 2001). 

Metabolic stress associated with high sulfide in 

sediment pore waters has been implicated as a 

possible stressor in Pensacola Bay, where sulfide 

Table 5. Area (km2) of submerged aquatic vegetation (SAV) beds in the Pensacola 

Bay system. Data for 1949 through 1951 were computed from maps reported by 

Olinger et al. (1975). The computed area is a lower limit because some areas were 

not covered by the aerial photography, which was conducted for the purpose of 

highway construction. Omitted areas include Blackwater Bay, the western shore of 

East Bay, western Pensacola Bay, and Santa Rosa Sound. Data for 1960, 1980, 1992,

and 2003 are from the USGS National Wetlands Research Center, Lafayette, LA.

Basin 1949-1951 1960 1980 1992 2003

Escambia Bay 4.82 1.05 0.24 1.78 0.45

East Bay 8.21 4.76 0.20 0.69 0.11

Pensacola Bay 4.70 3.71 0.55 1.14 1.51

TOTAL 17.73 9.52 1.00 3.62 2.07

Santa Rosa Sound nd 25.00 14.47 11.17 12.27
20

concentrations as high as 5 mM have been 

measured (Devereux, unpublished data). Sulfide 

is especially harmful to plants when water 

temperature and salinity are high (Koch and 

Erskine 2001), as is common during summer in 

Gulf coast estuaries. Absence of Thalassia also 

may result from poor propagation. Flowering and 

seed production by Thalassia is reduced or 

absent in northwest Florida, which is at the 

northern limit of the more tropical range for that 

species (Dawes et al. 2004). In the absence of 

seed production, revegetation occurs slowly by 

rhizome extension, which has been observed in 

Pensacola Bay (Lores et al. 2000). H. wrightii

appears to be within both temperature and 

salinity tolerances; the reasons for its absence are 

not clear. 

Based on the global and regional trends 

relating nutrient enrichment and SAV loss (Short 

and Wyllie-Echevarria 1996), one may infer that 

SAV loss in Pensacola Bay is also a consequence 

of nutrient enrichment. Because SAV beds create 

important habitat for a variety of estuarine biota 

(Dawes et al. 2004), their protection and eventual 

restoration is critical to supporting aquatic life 

uses of Pensacola Bay. Thus, the water quality 

requirements for SAV growth and survival 

should be a significant consideration for 

determining nutrient criteria for Pensacola Bay. 

Although much is known about seagrass ecology, 

effective decision-support tools based on that 

knowledge are not readily available for many 

applications, including Pensacola Bay. SAV 

growth models (e.g., Eldridge et al. 2004) have 

the ability to integrate the effects of many factors 

to predict SAV growth. Such models have been 

implemented for many SAV species and have 

been integrated in some cases with fully coupled 

hydrodynamic and water quality models (Cerco 

and Moore 2001). Although promising, the 

results of these models cannot be transferred 

across systems without adaptation to local 

conditions, calibration, and validation. EPA is 

presently adapting a SAV model developed for 

Thalassia in Laguna Madre, TX (Eldridge et al. 

2004), to growth conditions in Pensacola Bay, a 

promising first step. However, approaches to 

extrapolating from local SAV growth conditions 

to appropriate water column nutrient 

concentrations for the bay have not been 

developed, and quantitative relationships 

between nutrients and SAV are unclear. 

As in the case of hypoxia, some policy 

alternatives can be evaluated on the basis of our 

knowledge of SAV ecology in Pensacola Bay. 

First, consistent with Gulf-wide trends, SAV 

habitats in Pensacola Bay are degraded presently 

relative to their past condition. Second, the best 

available science links losses of SAV to nutrient 

enrichment both globally and in the Gulf of 

Mexico region. In the case of Pensacola Bay, it 

remains unclear to what extent, if any, current 

nutrient concentrations or water clarity are an 

impediment to SAV growth, coverage, or 

restoration success. The weight of evidence 

suggests that an increase in nutrients likely would 

pose a risk of further degradation of these 

important habitats and should be prevented 

through appropriate numeric criteria. Meanwhile, 

continued monitoring of SAV habitats should be 

pursued at a regular interval, along with 

advancements in predictive models relating water 

quality conditions to growth and survival of SAV 

species. An important need is relating SAV 

requirements in the littoral habitats where they 

occur to nutrient conditions at the larger scale to 

which nutrient criteria likely would apply (e.g., 

Cerco and Moore 2001). 

3.5 A Watershed Perspective 

An increase in nitrogen and phosphorus 

export from watersheds accompanies conversion 

of primarily forested lands to cropland and 

developed land uses (Reckhow et al. 1980, 

Jordan et al. 1997). Therefore, information on the 

impacts of human activity in a watershed 

provides important insight into the extent to 

which nutrient inputs to coastal waters may have 

increased and the potential for management 

actions to reduce nutrient enrichment and its 

adverse impacts. 

As of 2001, the Pensacola Bay watershed 

included approximately 7% developed land and 

6% cropland. The remaining land was forest 

(including silviculture), shrub land, or pasture 

and grassland (Figure 9). Nearly all of the 

developed land is in the immediate vicinity of 

Pensacola Bay, whereas the cropland is 

concentrated in the lower Escambia River 
21

Figure 9. Land cover in the Pensacola Bay watershed (data from the 2001 

National Land Cover Database).

watershed (Figure 9). The relatively small extent 

of development in the fluvial watershed 

corresponds to the low human population 

density, which has remained nearly constant at 

about 10 km-2 from 1970 through 2000 (NOAA, 

public communication). Population for the 

watershed as a whole was 29 km-2 in 2000 

(NOAA, public communication), very similar to 

the 2000 median for Gulf of Mexico estuaries 

(31 km-2), which, overall, are populated much 

less densely than those in the Mid-Atlantic region 

(182 km-2). As in many coastal areas, the 

population in the Pensacola Bay watershed is 

growing rapidly; population in the watershed 

increased 42% between 1970 and 2000 (NOAA, 

public communication). Developed land in Santa 

Rosa County, FL, one of two coastal counties in 

the watershed is projected to increase 350% by 

2060 (Zwick and Carr, 2006). 

Nutrient loading from the watershed 

remains relatively low, most likely because only 

a small fraction of the watershed has been 

developed or put into row-crop production. 

Cherry and Hagy (2006) estimated the input from 

rivers of dissolved inorganic nitrogen (DIN) and 

phosphate (PO4

3-) into Pensacola Bay. Based on 

the ratio of average TN to average DIN for fresh 

water (TN/DIN = 2), the estimated average input 

of TN was 1.2 × 104

 kg nitrogen day-1. When 

scaled by the fluvial watershed area (17,069 

km2

), the average TN yield delivered from the 

watershed to the bay was 262 kg nitrogen km-2

year-1. Using the same approach for TP, the 

estimated average TP load and average watershed 

TP yield was 1.0 × 103

 kg 

phosphorus day-1 and 21.8 kg 

phosphorus km-2 year

-1, 

respectively. Both nitrogen and 

phosphorus yields are consistent 

with reported values for entirely 

forested watersheds (Reckhow 

et al. 1980), indicating that 

current nutrient loadings from 

upland areas of the Pensacola 

Bay watershed are low. The 

SPARROW model (Smith et al. 

1997), which predicts nutrient 

yields of watersheds at the 

national scale, provides a point 

of comparison for our estimates, 

with a few caveats. The 

SPARROW model estimate of 

average nitrogen and 

phosphorus yield for the 

hydrologic units comprising the 

Pensacola Bay watershed are 

548 kg nitrogen km-2

 year

-1 and 

53 kg phosphorus km-2 year-1. 

Relative to the overall range of 

values from SPARROW for the 

conterminous United States, 

these values are very similar to 

our estimates for Pensacola Bay, 

even though they are 

approximately twofold higher 

for both nitrogen and 
22

phosphorus. As the developers of the SPARROW 

model note, the estimates are most reliable for 

comparing regional attributes of watersheds but 

are less reliable at smaller scales (Smith et al. 

1997). 

When nutrient export from the Pensacola 

Bay watershed is expressed per unit of estuary 

area, rather than per watershed area, the loadings 

appear somewhat higher. Scaled in this way, the 

TN and TP loading rates from the watershed to 

Pensacola Bay are 12 g nitrogen m-2

 year

-1 and 

1 g phosphorus m-2

 year

-1, respectively, well 

within a moderate range of nutrient loading rates 

for estuaries (Boynton et al. 1995). The contrast 

between the relatively low yield rates and the 

moderate loadings per unit of estuarine area 

reflects the fact that the Pensacola Bay watershed 

is nearly 50 times the size of the estuary, 

approximately 2 times the median ratio for 

estuaries (NOAA 1999b). 

Atmospheric nitrogen deposition is a 

possible source of anthropogenic nitrogen 

enrichment that could impact Pensacola Bay 

independent of land use change. Using local 

measurements, Cherry and Hagy (2006) 

estimated that wet nitrogen deposition in the 

vicinity of the bay was 0.3 g nitrogen m-2

 year

-1. 

The 1999 to 2004 average for the watershed, 

computed from national maps (NADP 2005; data 

obtained electronically from source identified 

therein), was comparable at 0.36 g nitrogen m-2

year

-1. Assuming that dry nitrogen deposition is 

55% of wet deposition (ratio based on local data; 

Hagy and Cherry 2006), atmospheric nitrogen 

deposition is approximately 0.5 g nitrogen m-2

year

-1 (= 500 kg nitrogen km-2

 year

-1). As a direct 

input to the bay, this amounts to a small (4%) 

fraction of TN inputs. In contrast, it is a 

significant input to the watershed, about twofold 

greater than nitrogen export via rivers. Assuming 

that nitrogen exports via stream flow are 20% to 

40% of the total of all nitrogen inputs to the 

landscape (Boyer et al. 2002), atmospheric 

deposition may account for two-thirds of that 

input. Given its likely quantitative significance, it 

would be helpful to know if atmospheric nitrogen 

deposition in the Pensacola Bay watershed has 

increased substantially over time. Several facts 

suggest that any increase was probably fairly 

small. First, nitrogen concentrations in rainfall 

remain among the lowest for U.S. coastal 

watersheds (14 μM; NADP 2005). Only U.S. 

Pacific coast estuaries have significantly lower 

nitrogen concentrations in rainfall (NADP 2005). 

Because U.S. nitrogen oxide emissions in 1990 

were 2.3-fold higher than in 1900 (U.S. EPA 

1995), and the largest increases probably 

occurred where deposition presently is elevated, 

the proportional increase in the Pensacola Bay 

watershed was likely less. 

The above observations regarding the 

Pensacola Bay watershed suggest that significant 

reductions in nutrient loading from the fluvial 

portion of the watershed may not be possible, 

even if slight improvements could be achieved by 

implementing best management practices on 

existing agricultural land, managed forests, 

developed land, and point sources. Because the 

landscape in the immediate vicinity of the bay is 

much more intensely developed and populated, 

loadings from that segment of the watershed may 

be higher and, therefore, potentially could be 

reduced through improved nutrient management. 

For the largest portion of the watershed, 

however, the risk of a significant increase in 

nutrient loading because of conversion of forest 

to urban and suburban development (Wickham 

et al. 2002) is much greater than is the potential 

for nutrient reductions. 

3.6 Nutrient Criteria 

 Below we examine the information that 

we used and the logic that we followed to define 

an approach for deriving nutrient criteria for 

Pensacola Bay. We then apply the approach to 

derive hypothetical criteria. We also examine 

how the scientific information about the bay 

influenced the approach that was followed. 

In our evaluation of Pensacola Bay water 

quality, we examined the environmental history 

of the bay, current attributes of the phytoplankton 

community, the prevalence of low DO (i.e., 

hypoxia), the status of seagrass (SAV) habitats, 

and the status of land use and nutrient exports 

from the watershed. We related these elements 

via a conceptual model of key ecosystem 

processes related to nutrients (Figure 2). We also 

evaluated water quality in Pensacola Bay in a 

comparative context by applying a modified 
23

Figure 10. Flow diagram illustrating the logical path followed to determine an 

appropriate approach for determining nutrient criteria for Pensacola Bay (boxes A

through E) and a subset of possible alternative paths (boxes F through J) that may 

have been followed had the scientific findings been different.

percentile approach in an ecoregional analysis of 

water quality (Figure 5, Table 2). 

We evaluated these data by posing a 

series of questions for which the answers, as well 

as the uncertainty associated with them, 

influenced the logical progression. It can be 

informative to consider the questions (below) 

separately, but they also may be considered part 

of a logic path (Figure 10). 

• Has water quality declined relative to a 

documented historical condition? 

• Is the estuary degraded in comparison to 

similar estuaries (i.e., estuaries in the same 

class?) 

• Are there environmental measures or indicators 

of conditions widely associated with nutrient 

overenrichment? 

• Are nutrient loads significantly enriched 

because of anthropogenic causes? 

At the end of the process, we determined 

that a nutrient criteria for Pensacola Bay 

reasonably could be defined by the current water 

quality conditions (Figure 10). Below, we explain 

the process, as outlined in Figure 10, in greater 

detail. 

Our analysis began with the historical 

data. We concluded that there were no data to 

indicate clearly that water quality in Pensacola 

Bay had declined because of nutrients (box A in 

Figure 10). This effectively eliminated the 

possibility of deriving criteria based, in large 

part, on a historical reference condition approach 

(box F). Had the available historical data shown a 

substantial decline in water quality, we may have 

considered a greater role for historical data in 

deriving nutrient criteria (box F). Even if this had 

been the case, additional supporting information 

still would be useful to further evaluate and 

support the values. 

Comparison of water quality in Pensacola 

Bay with other estuaries (box B in Figure 10) in 

its ecoregion-based class (Table 2, Figure 5) 

showed that water quality was often among the 

best in the class, and that it was not degraded 

relative to the class. Because current values for 

many water quality indicators were better than 

the comparison values obtained from the 

percentile approach, it did not seem reasonable to 

use these values as criteria. If, on the other hand, 

the comparison values determined via the 

percentile approach were 

better than current values, 

one might reasonably begin 

with the comparison values 

as criteria, then provide 

additional supporting 

evidence as possible 

(box G). 

Despite finding 

comparatively good water 

quality in terms of nutrient 

concentrations, water clarity, 

and chlorophyll-a, Pensacola 

Bay has both significant 

bottom water hypoxia and 

extensive loss of seagrass 

habitat, conditions widely 

associated with nutrient 

enrichment in estuaries (box 

C in Figure 10). Because 

hypoxia and seagrass loss 

have well-known negative 

impacts on estuarine 

systems, we expect that 
24

human and aquatic life uses are limited by these 

conditions. Moreover, seagrass loss and hypoxia 

often increase with anthropogenic nutrient inputs. 

The juxtaposition of seagrass loss and hypoxia 

with otherwise good water quality presents a 

relatively complex picture for nutrient criteria in 

Pensacola Bay. It appears that much of the loss 

occurred during the 1950s and 1960s in 

association with industrial nutrient and organic 

inputs that were eliminated by the early 1970s. 

Thus, these causes are not present today. The 

factors that impede recovery, as well as the 

prospects and best approach for successful 

restoration could be understood better through 

additional research. The significant extent of 

hypoxia in the bay appears to reflect a natural 

susceptibility of the bay to hypoxia. It is not clear 

that realistic reductions in nutrients could 

eliminate hypoxia. Scientific uncertainty 

surrounding this conclusion also could be 

reduced through additional research, particularly 

improved modeling of the coupled physicalchemical dynamics of the ecosystem. Both SAV 

loss and hypoxia commonly are associated in 

estuarine and coastal waters with significant 

phytoplankton blooms, sometimes including 

harmful algal species. However, phytoplankton 

production and biomass in Pensacola Bay are 

relatively modest compared to other systems. 

High-biomass phytoplankton blooms occur 

infrequently; harmful algal blooms are not known 

to develop in Pensacola Bay but, on occasion, 

have been transported into the bay from the Gulf 

of Mexico (Tester and Steidinger, 1997). It 

appears that Pensacola Bay is prone to adverse 

impacts resulting from nutrient enrichment and 

already has been impacted in the past by 

nutrients, but it may not be demonstrating clear 

symptoms of nutrient enrichment at present. 

To better evaluate this hypothesis, we 

examined nutrient inputs to the bay (box D in 

Figure 10). EPA did not include evaluating 

nutrient sources as part of a recommended 

criteria development process for freshwater 

systems (U.S. EPA 2000a,b). Rather, this step 

usually is undertaken as part of the total daily 

maximum load process. However, this analysis 

was a useful diagnostic step for Pensacola Bay 

and could prove to be important for criteria 

development for other estuaries. Although there 

were no historical baseline data with which 

current loading data could be compared, our 

analysis of current nutrient inputs from rivers, 

land use in the watershed, and atmospheric 

nitrogen deposition suggested that it was unlikely 

that nutrient inputs have increased dramatically. 

Evaluating water quality in the major rivers 

entering the bay showed that nutrient export from 

the watershed was similar to pristine or nearly 

pristine watersheds. This observation was 

supported by the absence in the watershed of 

major causes of increased nutrient export (e.g., 

low population, minimal row-crop agriculture, 

low atmospheric nitrogen deposition). One could 

conclude that reasonable management actions 

probably could not effect significant reductions 

in nutrient inputs to the bay via the major 

tributary rivers. Further research could reduce the 

scientific uncertainty regarding nutrient loads 

from the more developed portions of the 

watershed immediately surrounding the bay, 

which remain poorly quantified. 

Ultimately, our approach to developing criteria 

(box E in Figure 10) was the same as if no 

impaired conditions were identified (box I). In 

each situation, we suggest that it is scientifically 

justified to define water quality criteria as the 

current water quality conditions because there is 

little justification for alternative, more stringent 

criteria. Table 6 outlines hypothetical criteria that 

are based on summer medians, by salinity zone, 

for the 1996 to 2004 timeframe. We computed 

criteria for chlorophyll-a, secchi depth, DIN, 

PO4

3-, TN, TP, and DO. For concentration-based 

water quality indicators (e.g., chlorophyll-a), the 

criteria include a 10% buffer and a suitable 

averaging period (e.g., 3 years), such that small 

climate-driven variations surrounding current 

water quality would not trigger a determination 

of impairment. Because we concluded that a 

portion of the bay may be subject to hypoxia 

even in the absence of anthropogenic nutrient 

enrichment, DO criteria for bottom water must 

accommodate this feature of the ecosystem in 

some way. Our evaluation of oxygen dynamics in 

the bay indicates that a sensible approach would 

define hypoxia and limit the acceptable extent in 
25

near-bottom waters (e.g., 0.5 m above the 

bottom). An approach that defines either a 

DIN = NO2

-

 + NO3

-

 + NH4

+ concentration minimum for 

all bottom waters of the bay or even a lower limit 

for the median concentration in the bay provides 

less precise regulation of the extent of hypoxia. 

Scientifically defensible definitions of hypoxia 

for Pensacola Bay could arguably vary from 2 to 

as high as 4 mg L-1, provided the limits of extent 

are defined accordingly. In our example, we 

defined hypoxia as <2.0 mg L-1, the level at 

which relatively hypoxia-tolerant species begin 

to exhibit significant mortality (Diaz and 

Rosenberg 1995). The corresponding limit for 

average extent of hypoxia (over several years) is 

approximately 25% of the surface area of the 

bay, or 90 km2 (Table 6). Concerns related to 

natural extent of hypoxia do not apply for surface 

waters, where Florida’s existing statute is both 

consistent with existing water quality conditions 

and with expectations of aquatic life uses 

(Table 6).

Given the complex ecology and 

ecological historical of Pensacola Bay, it would 

not be surprising if other estuaries were similarly 

complex. However, we expect that criteria 

development for many estuaries could follow a 

more typical model. For example, one might find 

that water quality in an estuary is degraded 

relative to some limited 

historical data, that values 

also are degraded relative 

to ecoregional reference 

sites, that commonly 

observed nutrient-related 

problems are present, and 

that nutrient inputs are 

elevated because of 

obvious anthropogenic 

causes. Here, a coherent 

picture emerges and 

would be supported by 

several lines of evidence, 

each of which would 

provide support and 

insight and final criteria 

determination. In an 

estuary where reasonable 

criteria would stipulate 

reduced nutrients and improved water quality, 

some additional elements may be helpful or even 

necessary (box H). For example, models 

describing relationships among water quality 

variables may be helpful to ensure that criteria 

for causal variables (i.e., nutrients) are 

reasonably consistent with expected values for 

response variables (DO and chlorophyll-a). 

Criteria other than those proposed here, including 

biocriteria, could be useful where the indicators 

that we used fail to capture the ecological 

impacts resulting from nutrient overenrichment. 

For example, a harmful proliferation of 

macroalgae occurs in some estuaries subject to 

nutrient enrichment and is an important measure 

of the overall response to nutrients. Development 

of additional case studies would be a useful way 

to demonstrate approaches for deriving criteria in 

situations that were not encountered in the case 

of Pensacola Bay. Such case studies, like this 

one, could provide a template that could be 

adapted as desired as States develop criteria for 

their estuaries. 

Table 6. Suggested nutrient and nutrient-related water quality criteria for 

Pensacola Bay resulting from the weigh-of-evidence approach described herein. 

All values are 3-year moving averages of summer medians. The quantities are 

based on observed values (Table 2) that have been adjusted to provide 10% 

allowance (i.e., 10% higher for concentrations, 10% lower for secchi depth).

Parameter Criteria Recommendation

Chlorophyll-a Summer median concentration <8 μg L-1 (all salinity zones)

Secchi Depth Summer median >0.8 m (salinity 0-5), >1.1 m (salinity 5-18), 

>1.8 m (salinity >18)

DO Bottom waters below a pycnocline must have oxygen >2.0 mg L-1

except for in an area that may average up to 25% of the mean 

low water surface area of the bay.

Surface waters or unstratified waters: oxygen >4.0 mg L-1 at all 

times. 24-hour average oxygen >5.0 mg L-1

DIN Summer median <10 μM (salinity <5), <1.0 μM (salinity 5-18), 

<0.5 μM (salinity >18)

PO4

3- Summer median <0.2 μM (salinity <5), <0.12 μM (salinity 5-18), 

<0.05 μM (salinity >18)

TN Summer median <35 μM (all salinity zones)

TP Summer median <1 μM (salinity 0-5), <0.6 μM (salinity 5-18), 

<0.5 μM (salinity >18)
26
27

4. Summary and Conclusions 

We developed and applied an approach 

for developing numerical water quality criteria 

for nutrients and nutrient-related water quality 

indicators in an estuary. The approach is best 

defined as a weight-of-evidence approach whose 

important elements include those below. 

• Developing a conceptual model to organize 

and present the important ecological science 

and other information related to nutrients in the 

system. 

• Comparing water quality and other ecosystem 

attributes in the system with values from other 

estuarine ecosystems in a reasonable 

comparison group. 

• Evaluating the incidence of actual or potential 

nutrient-related water quality impacts in the 

ecosystem. The most common examples 

include hypoxia, SAV loss, and high-biomass 

or harmful phytoplankton or macroalgal 

blooms. 

• Evaluating the extent to which impacts have 

been caused by anthropogenic nutrient 

enrichment using historical observations, 

analysis of ecosystem processes, ecological 

models, or other approaches. 

• Evaluating the extent to which nutrient inputs 

to the system are likely to have been increased 

by human activities. 

An additional desirable element of an 

analysis supporting criteria development is an 

assessment of the risks for future environmental 

changes, including the principal drivers of such 

changes. Such an assessment would help inform 

future programmatic reassessments of water 

quality criteria. Our analysis of the Pensacola 

Bay ecosystem indicates that increased human 

development associated with current population 

trends poses a significant risk for increased 

nutrient inputs. The most sensitive and easily 

monitored indicators of enrichment are likely to 

be nutrient inputs themselves (especially in 

freshwaters), phytoplankton biomass, and extent 

of hypoxia. SAV extent is presently too 

degraded; is too sensitive to other impacts, 

particularly salinity; and appears too slow to 

respond to improved conditions to serve as a 

reliable indicator of enrichment for most of 

Pensacola Bay. 

We believe that the weight-of-evidence 

approach we outlined here and applied to 

Pensacola Bay would be applicable for many 

estuarine systems. The approach is most 

applicable where enrichment impacts are 

relatively modest and where a suitable 

comparison group provides an adequate context 

that might be used to justify criteria requiring 

some reduction in nutrients. The approach may 

be a useful point of departure for systems that 

have been impacted seriously by nutrients. 

However, in these cases, additional tools likely 

will be needed to support criteria development. 

Better methods would be needed to determine 

what level of aquatic life uses are achievable 

(including what uses were supported historically) 

and to identify the water quality requirements for 

those uses and, particularly, the relationships 

among different water quality indicators (e.g., 

nutrients, chlorophyll-a, hypoxia). 
28
29

5. References

Academy of Natural Sciences of Philadelphia. 1953. 

Escambia River, Florida, vicinity of the Chemstrand 

Corporation Plant, Fall 1952 - Spring 1953. Stream 

survey report for the E. I. du Pont de Nemours and 

Company. Department of Limnology, Academy of 

Natural Sciences of Philadelphia, Philadelphia, PA. 

December 1953. 165 pp. 

Boyer, E. W., C. L. Goodale, N. A. Jaworski, and R. W. 

Howarth. 2002. Anthropogenic nitrogen sources and 

relationships to riverine export in the northeastern 

U.S.A. Biogeochemistry 57/58:137-169.

Boynton, W. R. and W. M. Kemp. 2007. Estuaries. In

Capone, D. G., D. A. Bronk, M. R. Mulholland, and 

E. J. Carpenter (eds.). Nitrogen in the Marine 

Environment. Second Edition. Academic Press, New 

York. In press. 

Boynton, W. R., W. M. Kemp, and C. W. Keefe. 1982. 

A comparative analysis of nutrients and other factors 

influencing estuarine phytoplankton production. 

pp. 69-90. In V. S. Kennedy, editor. Estuarine 

Comparisons. Academic Press, New York. 

Boynton, W. R., J. H. Garber, R. Summers, and W. M. 

Kemp. 1995. Inputs, transformations, and transport of 

nitrogen and phosphorus in Chesapeake Bay and 

selected tributaries. Estuaries 18(1B):285-314.

Campbell, J. G. and L. R. Goodman. 2004. Acute 

sensitivity of juvenile shortnose sturgeon to low 

dissolved oxygen concentrations. Transactions of the 

American Fisheries Society 133:772-776.

Cerco, C. F. and K. Moore. 2001. System-wide submerged 

aquatic vegetation model for Chesapeake Bay. 

Estuaries 24(4):522-534. 

Cherry, J. S. II and J. D. Hagy III. 2006. Pensacola Bay, 

Florida USA. Land-Ocean Interactions in the Coastal 

Zone (LOICZ) Biogeochemical Budgets. 

Electronically published by the Land-Ocean 

Interactions in the Coastal Zone (LOICZ) programme. 

(http://www.loicz.org). 

Cloern, J. E. 2001. Our evolving conceptual model of the 

coastal eutrophication problem. Marine Ecology 

Progress Series 210:223-253.

Cowan, J. L., J. R. Pennock, and W. R. Boynton. 1996. 

Seasonal interannual patterns of sediment-water 

nutrient and oxygen fluxes in Mobile Bay, Alabama 

(USA): regulating factors and ecological significant. 

Marine Ecology Progress Series 141:229-245.

Dame, R., M. Alber, D. Allen, M. Mallin, C. Montague, 

A. Lewitus, A. Chalmers, R. Gardner, C. Gilman, 

B. Kjerfve, J. Pinckney, and N. Smith. 2000. Estuaries 

of the south Atlantic coast of North America: Their 

geographical signatures. Estuaries 23(6):793-819.

Dawes, C. J., R. C. Phillips, and G. Morrison. 2004. 

Seagrass Communities of the Gulf Coast of Florida: 

Status and Ecology. Florida Fish and Wildlife 

Conservation Commission, Fish and Wildlife Research 

Institute and the Tampa Bay Estuary Program. 

St. Petersburg, FL. 74 pp. 

Devereax, R., personal communication. U.S. 

Environmental Protection Agency, National Health 

and Environmental Effects Research Laboratory, Gulf 

Breeze, FL. December 2006. 

Diaz, R. J. 2001. Overview of hypoxia around the world. 

Journal of Environmental Quality 30(2):275-281.

Diaz, R. J. and R. Rosenberg. 1995. Marine benthic 

hypoxia: A review of its ecological effects and the 

behavioral responses of benthic macrofauna. 

Oceanography and Marine Biology Annual Review

33:245-303.

Divins, D. L. and D. Metzger, public communication. 

NGDC Coastal Relief Model. National Geophysical 

Data Center, National Oceanic and Atmospheric 

Administration, Boulder, CO. Accessed November 

2006 

(http://www.ngdc.noaa.gov/mgg/coastal/coastal.html). 

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

40:363-377.

Eldridge, P. M., J. E. Kaldy, and A. B. Burd. 2004. Stress 

response model for the tropical seagrass Thalassia 

testudinum: The interactions of light, temperature, 

sedimentation and geochemistry. Estuaries 27(6):923-

937.

FAC 2005. Section 62-302.530(31), Florida Administrative 

Code. Table: Criteria for Surface Water Quality 

Classifications. Effective July 27, 2005. Accessed at 

U.S. EPA Internet site 

(www.epa.gov/waterscience/standards/wqslibrary). 

Fitzpatrick, J. J. and M. B. Meyers. 2000. A critical look at 

criteria. A review of methodologies that determine 

nutrient criteria for coastal and estuarine systems. 

Water Environment and Technology 12(2):34-39.
30

GESAMP (IMO/FAO/UNESCOIOC/WMO/WHO/IAEA/UN/UNEP Joint Group of 

Experts on the Scientific Aspects of Marine 

Environmental Protection) and Advisory Committee 

on Protection of the Sea. 2001. Protecting the oceans 

from land-based activities - Land-based sources and 

activities affecting the quality and uses of the marine, 

coastal and associated freshwater environment. 

GESAMP Reports and Studies Number 71. 162 pp. 

Griffith, G. E., J. M. Omernik, C. W. Rohm, and S.M. 

Pierson. 1994. Florida regionalization project. U.S. 

Environmental Protection Agency, National Health 

and Environmental Effects Research Laboratory, 

Western Ecology Division, Corvallis, OR. 

EPA/600/Q-95/002. 83 pp. 

Hagy, J. D., III and M. C. Murrell. 2007. Susceptibility of a 

northern Gulf of Mexico estuary to hypoxia: an 

analysis using box models. Estuarine, Coastal and 

Shelf Science 74:239-253.

Homer, C., C. Huang, L. Yang, B. Wylie, and M. Coan. 

2004. Development of a 2001 national land cover 

database for the United States. Photogrammetric 

Engineering and Remote Sensing 70(7):829-840.

Hopkins, T. S. 1969. The Escambia River and Escambia 

Bay during summer 1969. University of West Florida, 

Pensacola, FL (unpublished manuscript). 54 pp. 

Hopkinson, C. S., Jr. 1985. Shallow-water benthic and 

pelagic metabolism: evidence of heterotrophy in the 

nearshore Georgia Bight. Marine Biology 87:19-32.

Jordan, T. E., D. L. Correll, and D. E. Weller. 1997. 

Relating nutrient discharges from watersheds to land 

use and streamflow variability. Water Resources 

Research 33(11):2579-2590.

Juhl, A. R. and M. C. Murrell. 2005. Interactions between 

nutrients, phytoplankton growth, and 

microzooplankton grazing in a Gulf of Mexico estuary. 

Aquatic Microbial Ecology 38:147-156

Karouna-Renier, N. K., R. A. Snyder, J. G. Allison, M. G. 

Wagner, and K. R. Rao. 2007. Accumulation of 

organic and inorganic contaminants in shellfish 

collected in estuarine waters near Pensacola, Florida: 

Contamination profiles and risks to human consumers. 

Environmental Pollution 145:474-488.

Kemp, W. M., E. M. Smith, M. Marvin-DiPasquale, and 

W.R. Boynton. 1997. Organic carbon balance and net 

ecosystem metabolism in Chesapeake Bay. Marine 

Ecology Progress Series 150:229-248.

Kennish, M. J. 1986. Ecology of Estuaries, Vol. I: Physical 

and Chemical Aspects. CRC Press, Boca Raton, FL. 

254 pp. 

Koch, E. W. 2001. Beyond light: physical, geological, and 

geochemical parameters as possible submersed aquatic 

vegetation habitat requirements. Estuaries 24(1):1-17.

Koch, M. S and J. M. Erskine. 2001. Sulfide as a 

phytotoxin to the tropical seagrass Thalassia 

testudinum: interactions with light, salinity and 

temperature. Journal of Experimental Marine Biology 

and Ecology 266:81-95.

Kurtz, J. C., N. D. Detenbeck, V. D. Engle, K. Ho, L. M. 

Smith, S. J. Jordan, and D. Campbell. 2006. 

Classifying coastal waters: Current necessity and 

historical perspective. Estuaries and Coasts 29(1):107-

123.

Lores, E. M. and D. T. Sprecht. 2001. Drought-induced 

decline of submerged aquatic vegetation in Escambia 

Bay, Florida. Gulf of Mexico Science 19(2):161-164.

Lores, E. M., E. Pasko, J. Patrick, R. L. Quarles, 

J. Campbell, and J. Macauley. 2000. Mapping and 

monitoring of submerged aquatic vegetation in 

Escambia - Pensacola Bay System, Florida. Gulf of 

Mexico Science 18:1-14.

MacIntyre, H. L., T. M. Kana, T. Anning, and R. J. Geider. 

2002. Photoacclimation of photosynthesis irradiance 

response curves and photosynthetic pigments in 

microalgae and cyanobacteria. Journal of Phycology

38:17-38.

May, E. B. 1973. Extensive oxygen depletion in Mobile 

Bay, Alabama. Limnology and Oceanography

18(3):353-366.

McRae, G., M. Julian, and H. Brown. 2004. Florida's 

Inshore Marine Monitoring and Assessment Program 

(IMAP). Annual Report, Year Five. Florida Fish and 

Wildlife Conservation Commission, Fish and Wildlife 

Research Institute, St. Petersburg, FL. 97 pp. 

Murrell, M., personal communication. U.S. Environmental 

Protection Agency, NHEERL/Gulf Ecology Division. 

1 Sabine Island Drive, Gulf Breeze, FL 32563 (data 

provided November 2006). 

Murrell, M. C. and J. M. Caffrey. 2005. High 

cyanobacterial abundance in three northeastern Gulf of 

Mexico estuaries. Gulf and Caribbean Research

17:95-106.

Murrell, M.C. and E. M. Lores. 2004. Phytoplankton and 

zooplankton seasonal dynamics in a subtropical 

estuary: importance of cyanobacteria. Journal of 

Plankton Research 26(3):371-382.

Murrell, M. C., R. S. Stanley, E. M. Lores, G. T. DiDonato, 

L. M. Smith, and D. A. Flemer. 2002. Evidence that 

phosphorus limits phytoplankton growth in a Gulf of 

Mexico estuary: Pensacola Bay, Florida, USA. Bulletin 

of Marine Science 70(1):155-167.

Murrell, M. C., E. M. Lores, J. D. Hagy III, R. M. Greene. 

2007. Phytoplankton production in relation to nutrient 

distributions in a sub-tropical estuary: importance of 

freshwater flow. Estuaries and Coasts 30(3):390-402.
31

NADP. 2005. National Atmospheric Deposition Program. 

2004. Annual Summary. NADP Data Report, 2005-01. 

Illinois State Water Survey, Champaign, IL. 16 pp. 

Nixon, S. W. 1995. Coastal marine eutrophication: 

A definition, social causes, and future concerns. 

Ophelia 41:199-219.

NOAA. 1997. NOAA’s Estuarine Eutrophication Survey, 

Volume 4: Gulf of Mexico Region. National Oceanic 

and Atmospheric Administration, Office of Ocean 

Resources Conservation and Assessment, Silver 

Spring, MD. 77 pp. 

NOAA. 1998. NOAA’s Estuarine Eutrophication Survey, 

Volume 5: Pacific Coast Region. National Oceanic and 

Atmospheric Administration, Office of Ocean 

Resources Conservation and Assessment, Silver 

Spring, MD. 75 pp. 

NOAA 1999a. Coastal Assessment Framework. Special 

Projects Office, National Ocean Service, National 

Oceanic and Atmospheric Administration, Silver 

Spring, MD. 

NOAA 1999b. Physical and Hydrologic Characteristics of 

Coastal Watersheds. Coastal Assessment and Data 

Synthesis System, 1999. National Coastal Assessments 

Branch, Special Projects Office, National Ocean 

Service, National Oceanic and Atmospheric 

Administration, Silver Spring, MD. 6 pp. 

NOAA, public communication. Spatial Trends in Coastal 

Socioeconomics, Coastal Ocean and Resource 

Economics Program, National Ocean Service, National 

Oceanic and Atmospheric Administration, Silver 

Spring, MD. Accessed February 2007. 

NRC. 2000. Clean Coastal Waters: Understanding and 

Reducing the Effects of Nutrient Pollution. Ocean 

Studies Board and Water Science and Technology 

Board, Commission on Geosciences, Environment, 

and Resources, National Research Council, 

Washington, DC. 

Olinger, L. W., R. G. Rogers, P. L. Fore, R. L. Todd, B. L. 

Mullins, F. T. Bisterfield, and L. A. Wise. 1975. 

Environmental and recovery studies of Escambia Bay 

and the Pensacola Bay system, Florida. U.S. 

Environmental Protection Agency, Atlanta, GA. 

904/9-76-016. 468 pp. 

Omernik, J. M. 1987. Ecoregions of the conterminous 

United States. Map (scale 1:7,500,000). Annals of the 

Association of American Geographers 77(1):118-125.

Omernik, J. M. 1995. Ecoregions: A spatial framework for 

environmental management. pp. 49-62. In Davis, W. S. 

and T. P. Simon (eds.). Biological Assessment and 

Criteria: Tools for Water Resource Planning and 

Decision Making. Lewis Publishers, Boca Raton, FL. 

Reckhow, K. H., M. N. Beaulac, and J. T. Simpson. 1980. 

Modeling phosphorus loading and lake response under 

uncertainty: a manual and compilation of export 

coefficients. U.S. Environmental Protection Agency, 

Washington, DC. EPA/440/5-80/011. 

Schroeder, W. W. and W. J. Wiseman, Jr. 1988. The 

Mobile Bay estuary: Stratification, oxygen depletion 

and jubilees. In Kjerfve, B. (ed.) Hydrodynamics of 

Estuaries, Volume II, Estuarine Case Studies. CRC 

Press, Boca Raton, FL. pp. 41-529.

Schroeder, W.W. and W. J. Wiseman, Jr. 1999. Geology 

and hydrodynamics of Gulf of Mexico estuaries. pp. 3-

28 In Bianchi, T. S., J. R. Pennock,, and R. R. Twilley 

(eds.) Biogeochemistry of Gulf of Mexico Estuaries. 

John Wiley and Sons, Inc., New York. 

Schwenning, L., T. Bruce, and L. W. Handley. 2007. 

Pensacola Bay. pp. 129-142 in Handley, L., D. 

Altsman, and R. DeMay (eds.). Seagrass Status and 

Trends in the Northern Gulf of Mexico: 1940-2002. 

U.S. Geological Survey Scientific Investigations 

Report 2006-5287 and U.S. Environmental Protection 

Agency. 855-R-04-003. 267 pp. 

Short, F. T. and S. Wyllie-Echevarria. 1996. Natural and 

human-induced disturbance of seagrasses. 

Environmental Conservation 23(1):17-27.

Smith, R. A., G. E. Schwarz, and R. B. Alexander. 1997. 

Regional interpretation of water-quality monitoring 

data. Water Resources Research 33(12):2781-2798.

Stephan, C. E., D. I. Mount, D. J. Hansen, J. H. Gentile, 

G. A. Chapman, and W. A. Brungs. 1985. Guidelines 

for deriving numerical national water quality criteria 

for the protection of aquatic organisms and their uses. 

National Technical Information Service, Springfield, 

VA. PB85-227049.

Summers, J. K., J. F. Paul, and A. Robertson. 1995. 

Monitoring the ecological condition of estuaries of the 

United States. Toxicological and Environmental 

Chemistry 49:93-108.

Tester, P. A. and K. A. Steidinger. 1997. Gymnodinium 

breve red tide blooms: initiation, transport, and 

consequences of surface circulation. Limnology and 

Oceanography 42(5):1039-1051.

U.S. EPA. 1995. National air pollutant emission trends, 

1900-1994. U.S. Environmental Protection Agency, 

Washington, DC. EPA-454/R-95-011. 219 pp. 

U.S. EPA. 1998. National strategy for the development of 

regional nutrient criteria. U.S. Environmental 

Protection Agency, Washington, DC. EPA 922-R-98-

002. 47 pp. 
32

U.S. EPA. 1999a. Protocol for developing nutrient 

TMDLs. First Edition. Office of Water (4503F), 

United States Environmental Protection Agency, 

Washington, DC. EPA 841-B-99-007. 135 pp. 

U.S. EPA. 1999b. Ecological Condition of Estuaries in the 

Gulf of Mexico. U.S. Environmental Protection 

Agency, Office of Research and Development, 

National Health and Environmental Effects Research 

Laboratory, Gulf Ecology Division, Gulf Breeze, FL. 

EPA 620-R-98-004.

U.S. EPA. 2000a. Nutrient criteria technical guidance 

manual: Lakes and reservoirs. U.S. Environmental 

Protection Agency, Washington, DC. EPA-822-B00-

001. 232 pp. 

U.S. EPA. 2000b. Nutrient criteria technical guidance 

manual: River and Streams. U.S. Environmental 

Protection Agency, Washington, DC. EPA-822-B00-

002. 254 pp. 

U.S. EPA. 2000c. Ambient water quality criteria 

recommendations. Information supporting the 

development of state and tribal nutrient criteria. Lakes 

and reserviors in nutrient ecoregion XII. U.S. 

Environmental Protection Agency, Washington, DC. 

EPA 822-B-00-013. 77 pp. 

U.S. EPA. 2000d. Ambient water quality criteria 

recommendations. Information supporting the 

development of state and tribal nutrient criteria. Rivers 

and streams in nutrient ecoregion XII. U.S. 

Environmental Protection Agency, Washington, DC. 

EPA 822-B-00-021. 80 pp. 

U.S. EPA. 2001. Nutrient Criteria Technical Guidance 

Manual. Estuarine and Coastal Marine Waters. U.S. 

Environmental Protection Agency, Washington, DC. 

EPA-822-B-01-003.

U.S. EPA. 2003. Ambient Water Quality Criteria for 

Dissolved Oxygen, Water Clarity, and Chlorophyll a 

for Chesapeake Bay and its Tidal Tributaries. U.S. 

Environmental Protection Agency, Region III 

Chesapeake Bay Program Office, Office of Water, 

Washington, DC. EPA 903-R-03-002.

U.S. EPA. 2004. National Coastal Condition Report II. 

U.S. Environmental Protection Agency, Office of 

Research and Development, Office of Water, 

Washington, DC. EPA-620/R-03/002. 

U.S. EPA. 2005. The Ecological Condition of the 

Pensacola Bay System, Northwest Florida (1994-

2001). U.S. Environmental Protection Agency, Office 

of Research and Development, National Health and 

Environmental Effects Research Laboratory, Gulf 

Ecology Division, Gulf Breeze, FL. EPA/620/R05/002. 

U.S. EPA/OWOW, public communication. U.S. 

Environmental Protection Agency, Office of Wetlands, 

Oceans, and Watersheds, Total Maximum Daily Load 

Program Web site. Accessed December 2006 

(http://www.epa.gov/owow/tmdl). 

USGS. 2004. Seagrass habitat in the northern Gulf of 

Mexico: Degradation, conservation and restoration of a 

valuable resource. United States Geological Survey, 

Gulf of Mexico Program Office, Stennis Space Center, 

MS. 855-R-04-001. 26 pp. 

U.S. House of Representatives. 2000. United States Code. 

2000 Edition. Office of the Law Revision Counsel of 

the United States House of Representatives, U.S. 

Government Printing Office, Washington, DC. Title 

33, beginning with section 1251 accessed at 

http://www.gpoaccess.gov/uscode. 

Wickham, J. D., R. B. O’Neill, K. H.Ritters, E. R. Smith, 

T. G. Wade, and K. B. Jones. 2002. Geographic 

targeting of increases in nutrient export due to future 

urbanization. Ecological Applications 12(1):93-106.

Zwick, P. D. and M. H. Carr. 2006. Florida 2060, A 

population distribution scenario for the State of 

Florida. Geoplan Center, University of Florida, 

Gainesville, FL. 29 pp. 
33

Appendix A 

Observations in EPA’s Level III Ecoregion 75 

Estuaries included in EPA’s Level III ecoregion 75, defined as the “Southeast Coastal Plain,” 

and the number of surface water quality observations used to compute median water quality values for 

surface water. The estuaries are located between West Mississippi Sound, MS, and Winyah Bay, SC. 

Estuarine Drainage Area

Number of 

Observations

Altamaha River, GA 8

Apalachee Bay, FL 19

Apalachicola Bay, FL 58

Breton/Chandeleur Sound, MS 4

Broad River, SC 27

Charleston Harbor, SC 14

Charlotte Harbor, FL 48

Choctawhatchee Bay, FL 37

East Mississippi Sound, MS/AL 32

Indian River, FL 139

Mobile Bay, AL 52

North/South Santee rivers, SC 3

Ossabaw Sound, GA 13

Pensacola Bay, FL 70

Perdido Bay, FL 18

Sarasota Bay, FL 58

Savannah River, SC 14

St. Andrew Bay, FL 62

St. Andrew/St. Simons sounds, GA 21

St. Catherines/Sapelo sounds, GA 25

St. Helena Sound, SC 28

St. Johns River, FL 65

St. Marys River/Cumberland Sound, FL/GA 16

Stono/North Edisto rivers, SC 13

Suwannee River, FL 57

Tampa Bay, FL 74

West Mississippi Sound, MS 61

Winyah Bay, SC 7

TOTAL 1,043
34

Appendix B 

Observations in Florida’s Level IV Ecoregion 75a

Estuaries included in Florida’s Level IV ecoregion 75a, defined as the “Gulf Coast Flatwoods 

Region,” and the number of surface water quality observations used to compute median water quality 

values for surface water. The estuaries are located in the northern Florida Panhandle between Perdido 

Bay, FL, and Suwannee River, FL. The data are from Florida’s Inshore Marine Monitoring and 

Assessment Program. 

Estuarine Drainage Area

Number of 

Observations

Apalachee Bay, FL 18

Apalachicola Bay, FL 55

Choctawhatchee Bay, FL 36

Pensacola Bay, FL 67

Perdido Bay, FL 7

St. Andrew Bay, FL 60

Suwannee River, FL 56

TOTAL 299
35

Appendix C 

List of Acronyms and Abbreviations 

BOD biochemical oxygen demand 

BW bottom water 

C carbon 

Chl-a chlorophyll-a 

CWA Clean Water Act 

DIN dissolved inorganic nitrogen 

DO dissolved oxygen 

EDA estuarine drainage area 

EMAP Environmental Monitoring and Assessment Program 

EPA U.S. Environmental Protection Agency 

IMAP Florida Inshore Monitoring and Assessment Program 

μM micromolar 

mM millimolar 

N nitrogen 

N2 molecular nitrogen 

NCA National Coastal Assessment 

NH4

+ ammonium 

NO2

- nitrogen dioxide 

NO3

- nitrate 

NOX nitrogen oxide 

NOAA National Oceanic and Atmospheric Administration 

O2 molecular oxygen 

ORD Office of Research and Development 

P phosphorus 

PO4

3- phosphate 

Rp plankton community respiration rate 

SAV submerged aquatic vegetation 

SOD sediment oxygen demand 

TN total nitrogen 

TP total phosphorus 

USGS U.S. Geological Survey
36