External Peer Review of EPA’s

“Proposed Methods and Approaches for Developing 

Numeric Nutrient Criteria for Florida’s Inland Waters”

Peer Review Comments

Draft Final

EPA Contract No. EP-C-07-059

Work Assignment No. 1-16

Submitted to:

Jacques Oliver

Health and Ecological Criteria Division (4304T)

Office of Science and Technology

U.S. Environmental Protection Agency

1200 Pennsylvania Avenue, NW

Washington, DC 20460

Submitted by:

Eastern Research Group, Inc.

110 Hartwell Avenue

Lexington, MA 02421-3136

August 11, 2009

Printed on Recycled Paper
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conducted the review according to a charge prepared by EPA and instructions prepared by ERG. ERG 

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i

Table of Contents

Peer Reviewer Comments

1. Please comment on the use of the approaches and methodologies presented in the technical 

document, “Proposed Methods and Approaches for Developing Numeric Nutrient Criteria for 

Florida’s Inland Waters,” for deriving numeric nutrient criteria, given the available data, protective 

of the Florida’s designated uses of Florida’s class III waters (i.e., “Recreation, Propagation and 

Maintenance of a Healthy, Well-Balanced Population of Fish and Wildlife”)...................................3

2. Chapter 3. Please comment on the use of the SCI, LVI, and SDI as reliable indicators of the aquatic 

life designated use attainment and whether these metrics appear to be sensitive indicators to nutrient 

enrichment?.......................................................................................................................................11

3. Chapter 4. Please comment on the approach used, given the available data, to derive the proposed 

nitrate-nitrite criteria for Florida’s streams (< 40 pcu)......................................................................15

4. Chapter 5. Please comment on the regionalization of Florida’s streams in support of the nutrient 

benchmark approach. ........................................................................................................................18

5. Chapter 6. Please evaluate the stressor-response approaches for numeric nutrient criteria 

development. .....................................................................................................................................20

6. Chapter 7. Please evaluate the Nutrient Benchmark Distributional Approach. ................................24

7. Chapter 8. Please evaluate the reliability of the Nutrient Longitudinal Study to protect the aquatic 

life use downstream and whether this approach can be applied to other estuaries or lakes in Florida?

...........................................................................................................................................................27

8. Chapter 9. Please evaluate the methods for developing chlorophyll a numeric nutrient criteria for 

lakes. .................................................................................................................................................30

9. Chapter 10. Please evaluate the methods for developing chlorophyll a numeric nutrient criteria for 

lakes based on stressor-response analyses. .......................................................................................34

10. Chapter 11. Please comment on the “all streams” statistical distribution approach for deriving 

numeric nutrient criteria....................................................................................................................40

11. Chapter 12. Please comment on extrapolating background nutrient concentrations as an approach to 

deriving numeric nutrient criteria......................................................................................................41

12. Chapter 13. Please comment on the use of multiple regression and statistical distribution 

approaches to deriving numeric nutrient criteria...............................................................................43

13. Chapter 14. Please comment on the downstream protection approaches..........................................45

Additional Comments/References..............................................................................................................51

1

PEER REVIEWER COMMENTS

3

Specific Questions

1. Please comment on the use of the approaches and methodologies presented in the technical 

document, “Proposed Methods and Approaches for Developing Numeric Nutrient Criteria 

for Florida’s Inland Waters,” for deriving numeric nutrient criteria, given the available 

data, protective of the Florida’s designated uses of Florida’s class III waters (i.e., 

“Recreation, Propagation and Maintenance of a Healthy, Well-Balanced Population of Fish 

and Wildlife”).

a. What are the strengths and weaknesses of approaches and methods employed given 

the available data? 

b. To what extent can each line of evidence be used independently to support the 

derivation of numeric nutrient criteria for each of the parameters EPA has 

recommended?

c. Given the data available, what additional technical considerations can you 

recommend in the derivation of numeric nutrient criterion for each parameter?

Reviewer 1 The driving force for creation of the document I am currently reviewing comes from the 

Clean Water Act. The Clean Water Act (CWA) establishes the basic structure for 

regulating discharges of pollutants into the waters of the United States and regulating 

quality standards for surface waters. The basis of the CWA was enacted in 1948 and 

was called the Federal Water Pollution Control Act, but the Act was significantly 

reorganized and expanded in 1972. "Clean Water Act" became the Act's common name 

with amendments in 1977. Reading this whole act quickly shows that the term fish is 

used approximately 68 time and recreation approximately 72 times, leading to the 

general goal of protecting waters so they are “Swimmable” and “Fishable” on into the 

future.

This goal leads to an impossible management situation that the best swimming lakes are 

generally clear unproductive lakes (oligotrophic) and the best fishing lakes are 

generally green productive lakes (eutrophic). A strength of the document is that it 

attempts at all costs to set nutrient standards that are low, which would favor a 

swimming condition. However, a great weakness of the document is that fish are not 

considered in the document and if they were considered a low nutrient standard would 

not favor “Fishable.” Additionally, the Florida Fish and Wildlife Conservation 

Commission had no part in the creation of this document, which I think is a great 

mistake and another weakness of the document. Their insights as to how nutrients relate 

to fish and wildlife should be part of this document. As the document and standards are 

set up now, most of the excellent fishing and wildlife observing lakes in Florida would 

be classified as impaired.

The strengths in the document entitled “, “Proposed Methods and Approaches for 

Developing Numeric Nutrient Criteria for Florida’s Inland Waters,” revolve around the 

general understanding that geology and the Ecoregion concept is the master variable 

determining water chemistry of aquatic systems. From my experience working on 

Florida aquatic systems, the factor accounting for the largest amount of variance in 

nutrient concentrations of rivers, lakes and estuaries is the geology in which the system 

lies. This agrees with the basic Ecoregion concept that the USEPA already uses. This is 

a great strength of this document in Section 5 for streams and Section 14 for Estuaries 

because both Sections show the importance of geology and/or Ecoregion. 
Unfortunately, this same concept is not used for Florida lake nutrient standards 

discussed in this document, another weakness.

Within an individual Ecoregion the next factors accounting for variance in nutrient 

concentrations are all related to lake morphology and hydrology. These factors can 

account for significant variance in nutrient concentrations within an individual 

Ecoregion and for the most part, these factors are ignored in the current document 

adding another weakness. However, expanding the use of the Vollenwider Model 

concept described in Section 14.2.1 could greatly strengthen the scientific grounds for 

nutrient standards set in the document. This approach has been extremely successful in 

lakes (Bachmann and Canfield 1981) and shows great promise in Estuaries (Meeuwig et 

al. 1998; Meeuwig 1999; Meeuwig et al. 2000).

Driving lake morphology and hydrology impacts on nutrient concentrations and lake 

trophic state is the year-to-year variation in water inputs from rainfall. I have tried to 

model impacts of rainfall to nutrient concentrations in lakes with little success (Hoyer et 

al 2005). The reason is that changes in lake water level can cause trophic state 

parameters to increase (25% of the time), decrease (~25% of the time) or have no 

impact (~50% of the time) depending on the dominant mechanisms working within 

individual lakes. The importance of this concept for the current document is that many 

lakes have tremendous year-to-year variability and many of the approaches used in this 

document to define nutrient standards do not have enough long-term data to define what 

true background variance is. Thus, setting standards on a lake after a 100-year flood or 

draught could make it impossible for the lake to ever reach the standard again. Some 

form of long-term variability needs to be part of any nutrient standard.

The long-term variability of lake water chemistry add difficulty to the strength of the 

document, which is understanding the important role that color has on aquatic systems 

in Florida. However, lakes in Florida are extremely dynamic and can go from a color of 

20 PCU to 150 PCU after one rain storm and maintain color over 40 PCC for months if 

not a year before they clear up. Thus, using a fixed 40 PTU as a cut of for clear and 

colored systems may not be the best approach for setting nutrient standards. One month 

a lake many meet a standard and the next be in violation.

The approaches to setting standards in this document should not be independent of each 

other because all ecological processes are connected. Unfortunately, the report entitled 

“Proposed Methods and Approaches for Developing Numeric Nutrient Criteria for 

Florida’s Inland Waters” shows that different groups were working independently of 

each other and not communicating. For example, the rivers and estuary groups followed 

an Ecoregion and water shed type approach and the lake groups did not. All of the 

different Sections should follow the same general game plan.

My recommendation for developing a nutrient standard for Florida is to first use all 

available data and develop the most comprehensive Ecoregions possible, following the 

lead of Griffith et al. 1997. The upper 25% of the distribution of nutrient concentrations 

in lakes within an Ecoregion should be examined to see if they meet use and those that 

do not should be examined for restoration activities. Those that do should be monitored 

to make sure they are not changing. To make this determination, all long-term water 

chemistry data available should be used to define normal background variance for 

nutrient concentrations in lakes that could then be used as a standard classifying any 

lake exceeding the defined normal background variance as impaired or not meeting use. 
5

Once the remaining lakes have be classified as meets use, monitoring lakes to see if 

they fall within normal back ground variance would work to maintain lakes in a 

swimmable and fishable condition. Finally, I would consult with the Florida Fish and 

Wildlife Conservation Commission to define how nutrients impact the fish and wildlife 

populations using aquatic systems and have them help define when nutrients in a 

system cause harm to the fishable waters.

Canfield, Jr., D. E. and Bachmann, R.W. 1981. Prediction of total phosphorus 

concentrations, chlorophyll a, and Secchi depths in natural and artificial lakes. Can. J. 

Fish. Aquat. Sci. 38:414-423.

Griffith, G. E., D. E. Canfield, Jr., C. A. Horsburgh, and J. M. Omernick. 1997. Lake 

regions of Florida. Report to the Florida Department of Environmental Protection. U. S. 

Environmental Protection Agency, Corvallis OR.

Hoyer, M. V., C. A. Horsburgh, D. E. Canfield, Jr., and R. W. Bachmann. 2005. Lake 

level and trophic state variables among a population of shallow Florida lakes and within 

individual lakes. Canadian Journal of Fisheries and Aquatic Sciences. 62: 1-10.

Meeuwig, J. J., J. B. Rasmussen, and R. H. Peters. 1998. Turbid waters and clarifying 

mussels: their moderation of empirical chl:nutrient relations in estuaries in Prince 

Edward Island, Canada. Mar. Ecol. Prog. Ser. 171: 139-150.

Meeuwig, J. J. 1999. Predicting coastal eutrophication from land-use: an empirical 

approach to small non-stratified estuaries. Mar. Ecol. Prog. Ser. 176: 231-241.

Meeuwig, J. J., P. Kauppila, and H. Pitkanen. 2000. Predicting coastal eutrophication in 

the Baltic: a limnological approach. Can. J. Fish. Aquat. Sci. 57: 844-855.

Reviewer 2 In my document Question 1 is a "General Charge Question" with three general 

considerations (i.e. strengths and weaknesses, validity of lines of evidence, 

additional technical considerations for deriving criteria) that I took into 

consideration throughout the document in reviewing the individual chapters. So, 

the general charges are addressed throughout the review, of course depending 

upon the contents of the individual chapters.

Reviewer 3 The State of Florida has developed multiple lines of evidence in support of numeric 

nutrient criteria for inland waters. Those lines include effects-based relationships 

between biological communities and nutrients, stressor-response relationships between 

nutrients and periphyton indicators for streams and chlorophyll a for lakes and 

estuaries, descriptive statistics, models linking downstream condition to upstream 

nutrient loads, and heuristic arguments based on historical comparisons, 

paleolimnology, and review of extant literature. Collectively, these lines of evidence 

are defensible and support numeric criteria. For some of the analyses, a few minor 

refinements are suggested to help make the results less ambiguous, and in some cases, 

more applicable. 
The biological indices, especially the Stream Condition Index (SCI) based on 

macroinvertebrate community composition and structure, and the Lake Vegetation 

Index (LVI), were convincingly demonstrated to be robust measures of resource 

condition relative to a gradient of anthropogenic disturbance. The Stream Diatom 

Index was strongly influenced by regional geology (however, component metrics were, 

apparently, sensitive to a nutrient gradient). Significant, though necessarily fractional, 

amounts of variation in SCI and LVI scores were explained by a nutrient gradient, 

particularly nitrogen. Unfortunately, the small sample size (N~75) used in the 

statistical analyses for both stream invertebrates and, to a lesser extent, lake vegetation, 

appeared to limit the ability to “read” the nutrient signal through the noise of 

confounding and collinear variables. The report was vague with respect to which SCI 

data were used in the analyses. For example, no mention is given as to whether the data 

were culled to remove sites influenced by spurious factors (e.g., sites known to be 

affected by toxic levels of pollution, highly degraded physical habitat, desiccation, 

combined sewer overflows, etc.) prior to analyses. If this was not done, it is highly 

recommended. 

The derivation of nitrate-nitrite criteria for clear, spring streams employed historic 

comparisons, stratification by water color, laboratory dose-response experiments, 

analysis of hydrologic and demographic data, and change point analysis based on data 

collected over a nutrient gradient. As such, the methodology is particularly robust, and 

the criteria defensible, especially in terms of recreational and aesthetic uses.

The regionalization with respect to nutrients was straightforward, methodologically 

sound, and in keeping with the results of others (i.e., collapsing multiple ecoregions into 

several nutrient regions - sensu Robertson et al. 20061). 

The stressor-response analyses presented in Chapter 6 were conducted on data 

retrospectively, but managed to avoid the tinge of data dredging by acknowledging 

collinearity among stressor variables, and by noting that a measured stressor variable 

can serve as a proxy for unmeasured variables. The analyses showed statistically 

significant relationships between nutrients and biological metrics based on either 

macroinvertebrates or diatoms, but given the aforementioned caveats, were not 

considered sufficiently strong for derivation of criteria. Although the relationships were 

weak, and may not, in isolation, serve as a basis for criteria, change points in the 

biological metrics in relation to either TP or TN (or DIN, NOx, etc.) would serve as an 

additional line of evidence for criteria. The results from the rapid periphyton 

assessment, however, appeared to provide the least ambiguous results, yet were used 

only to support the general theme that nutrient enrichment produces observable effects. 

Again, change point analysis on these data would augment the overall effort. 

The methods used to identify least-impacted benchmark sites in Chapter 7 were 

rigorous and resulted in a population of sites that yielded a reference range for nutrient 

concentrations in the various nutrient regions. The report correctly cited an important 

caveat for using a percentile approach, namely, that the approach fails to identify a 

threshold concentration over which biological impairment is increasingly likely. The 

strength of the percentile approach hinges on the supposition of the absence of evidence 

 

1 Environmental Management (2006) 37:209-229
7

is evidence of absence (i.e., no biological impairment observed at a few sites with high 

nutrient concentrations, ergo, the criteria should be protective). However, before this 

can be concluded, mitigating factors, specifically those that allow for good biological 

condition to be maintained in the presence of known or suspected stressors, must first 

be ruled out, or at least understood with an eye toward implementation. The reference 

range approach should be supplemented with an “all” sites approach (as in Chapter 11), 

wherein distributions of nutrient concentrations are examined by categorical level of 

SCI scores (e.g., poor, fair, good, excellent ranges) for all sites within a region (or 

regions) where biological data exist. This would provide a contrast between degraded 

sites, sites meeting expectations, and benchmark sites that may help inferentially show 

the nutrient concentrations over which degradation is likely. 

The longitudinal study of the Steinhatchee and Waccasassa basins and estuaries loosely 

demonstrated that nutrient concentrations found in minimally disturbed watersheds are 

not associated with detrimental effects, particularly loss of seagrass beds. This study 

would have been much more compelling if an enriched system, especially one enriched 

with nitrogen, had been offered for comparison.

Chapter 9 details a basis for chlorophyll a thresholds for Florida lakes based on 

empirical relationships between TP, TN and chlorophyll a (i.e., Trophic State Index), 

and augments that with several other lines of evidence, specifically, paleolimnology, 

BPJ, literature review, user perception, existing condition, and reference distribution. 

The report and appendices were vague with respect to which data were used (a subset of 

those referred to in Chapter 10?) and the strength and form (i.e., linear vs. non-linear) of 

the relationships forming the TSI; however, having a direct, and empirically derived, 

stressor-response model on which to base criteria is clearly a strength. The additional 

lines of evidence roughly converge on the proposed threshold of 20 ug/l chlorophyll a

(i.e., meso-eutrophic boundary) for colored lakes, and the lower threshold of 9 ug/l 

(oligo-mesotrophic boundary) for clear lakes in the panhandle region. The exercise in 

investigating the relationship between cyanobacteria and chlorophyll a was offered as 

evidence that the proposed chlorophyll threshold will protect beneficial uses; however, 

the exercise was equivocal. The real question is whether increasing nutrient 

concentrations over time alter the composition of the algae community in a given 

waterbody, thereby increasing the probability of a harmful bloom.

The stressor-response analyses for lakes provided in Chapter 10 presented two lines of 

effects-based evidence, one based on an aquatic vegetation index (LVI), the other on 

chlorophyll a. The LVI was statistically associated with mean nutrient concentrations 

averaged over the preceding year, thus demonstrating a stressor-response relationship. 

The strength of association (for both lake types), as the report acknowledges, was what 

one might have expected given that multiple factors influence lake vegetation, but was 

deemed insufficiently robust for derivation of nutrient criteria, except for TP in clear 

lakes. These data, however, should be used in change point analysis as an additional 

line of evidence supporting numeric criteria. Correcting for the extraneous 

environmental variables by using the residuals from a regression of the LVI on the 

ancillary variables in change point analysis might help. The statistical associations 

between chlorophyll a and nutrients were much stronger, based on a large data set, and 

in keeping with numerous published results. These relationships were used to derive 

criteria. 
Compiling descriptive statistics on ambient water chemistry, as in Chapter 11, is a 

necessary step toward gaining a broad understanding of the system at a population 

level. However, the reference approach, in the absence of biological data, provides the 

weakest line of evidence for criteria development. The all sites chemistry data should 

be, as previously mentioned, paired with biological data (i.e., the SCI, SDI, or a 

sensitive component metric) and reexamined within ranges of the biological data. 

The effort toward extrapolating background nutrient concentrations (Chapter 12) was 

equivocal, perhaps because the work was done ad hoc with available data. Sorrano et 

al. (2008) demonstrated the application for lakes, but the applicability for streams is 

questionable, given that streams are open systems and inherently more variable than 

lakes. Furthermore, the approach, with respect to streams, would seem to offer little 

additional resolution beyond that given by the exhaustive benchmark approach (Chapter 

7).

The multiple regression models provided in Chapter 13 offer a more refined way to 

derive criteria than the conventional linear models appearing in Chapters 9 and 10, 

though the results from all three chapters generally comport each other, adding strength 

to the overall effort of defining criteria. 

The meat of Chapter 14 is section 14.1.14. The description of model development 

preceding it is highly ancillary for the exercise of deriving nutrient criteria. A very 

general and emphatically brief summary of the TMDLs would suffice as a precursor, 

with details of the models appearing as appendices. To wit, simply stating and 

referencing that approved TMDLs have been developed for the respective estuaries 

identifying the target loads listed in Table 10 would suffice. Given that water quality 

models are abstractions, and have a good deal of inherent uncertainty, the derived 

stream reach concentrations suggested as criteria in Table 10 should be compared to 

reference ranges (i.e., which percentile for both the benchmark sites and the all sites do 

they match). Also, some expression of uncertainty around the estimates should be 

provided. That said, linking protection of downstream uses with upstream 

concentrations is an important component of the criteria derivation process, and the 

results presented in Table 10 appear to generally comport with the other finding listed 

throughout the report, thereby adding strength to the overall effort.

Reviewer 4 The document has remarkable breadth of coverage made possible in part because 

Florida made the investment in building a massive data record. Considerable technical 

effort has been devoted to exploration of different approaches for development of 

numeric nutrient criteria. Not all approaches will be found to have equal merit for 

developing nutrient criteria in Florida, but the opportunity to compare and contrast 

those approaches is invaluable. After consideration of relative merits, EPA and Florida 

should be well-positioned to move forward with criteria development.

It was disappointing, although understandable, that there was no synthesis component 

that might consider how the various approaches fit together. It does not seem likely that 

all approaches will have equal merit in this case. Will one approach play a primary role 

and others be used as confirmation? At some point, it will be necessary to reconcile 

differences among the numbers produced by each method. This step may require 
9

additional work on some methods; the level of effort, especially with regard to 

application of statistical tools was not uniform across the approaches. For example, 

more might be done to extract thresholds from the “wedge-shaped” response 

relationships.

I would like to see more discussion about the interface between science and policy. 

Biological condition, for example, can be characterized largely by technical 

evaluations, but the threshold consistent with use attainment is mainly a policy decision. 

That distinction is sometimes obscured behind discussions about the precision of 

possible thresholds.

Reviewer 5 The document reviewed represents a compilation of methods and approaches from 

several sources, namely Florida’s Department of Environmental Protection (DEP), 

USEPA and their contractors, by which EPA proposes to assist the State of Florida in 

determining nutrient criteria for the protection of designated uses of inland waters as 

mandated by the Clean Water Act. The effort presented here represents a wide-ranging 

assessment of techniques, from a number of perspectives, to determine comprehensive 

nutrient criteria for both N and P for inland waters. A series of relatively thorough, 

though often high-level, considerations of standard techniques is presented for 

establishing numerical water quality criteria for lakes, streams, rivers, springs and 

downstream waters. 

The approaches cover a range of biological response variables including invertebrates, 

periphyton, algae, Submersed Aquatic Vegetation (SAV), chlorophyll a. The 

controllable stressor variables of direct concern are nitrogen and phosphorus, although 

mention is made of the importance of other stressor variables, such as DO and color. 

EPA recognizes that a single nutrient criterion for all waters is unrealistic and will result 

in inadequate protection of inland waters. Therefore, EPA recommends the states adopt 

criteria for two stressor parameters, in this case TN and TP, and two response variables, 

for example chlorophyll a and water clarity. 

The proposal does not explicitly include a second response parameter for consideration 

and focuses on chlorophyll a as a response parameter but does not treat water clarity at 

all. Though many secondary response variables are analyzed: invertebrates, lake 

vegetation, seagrass, fishery, lake trophic state, only chlorophyll a is proposed as a 

response parameter. Nor does the document consider stressor parameters other than TN 

and TP. Other candidates, such as low DO, organic matter load or sediment load, may 

be as or more appropriate stressors for some waters, however are not formally 

incorporated into recommendations. This is likely a function of the lack of availability 

of data and a desire to address (at least initially) the most common response parameters 

being used throughout the country.

DEP and EPA clearly recognize the complex nature of the task at hand: proposed 

criteria must have a high probability of being effective and of eliciting the predicted 

results or the program will be undermined. Therefore, it is recommended that several 

elements be included in the proposed approaches, to wit:

 The approaches must be geographically based and be applicable statewide

 There must be provision for differential application of criteria, depending on 

conditions and geography
 Downstream effects must be evaluated

 The approaches should be ecosystem-oriented

 They should target specific response variables

 Approaches must be standardized and transportable

 The strategy must incorporate research and monitoring

 Temporal variability should be taken into consideration

 Sampling protocol and schedules must be matched to the timescales of relevant 

processes

Of necessity, many simplifying assumptions are made in the various analyses and 

recommendations throughout the document, some of which are innocuous and others 

should be further evaluated. Evaluations of these assumptions are elucidated in the 

individual chapter assessments. Some approaches presented are likely not to be 

effective for all waters in Florida and some approaches are not sufficiently developed or 

expounded here to make a thorough consideration of them. Although the approaches 

should be geographically comprehensive, south Florida estuaries are noticeably absent 

from the discussion and analyses. The proposed models for downstream loading 

calculations are insufficient to assess whether criteria are protective in areas where 

downstream waters do not receive a coherent mass flow, such as in Florida Bay.

Biological response is related to a number of variables that obscure the dose-response 

relationships. A better understanding of the underlying interactions and processes will 

allow a refinement of the basic relationship. Understanding of the physics of the 

system is essential to understanding nutrient processing: depth, bathymetry, residence 

time, tidal prism are important factors determinant of rates and interactions. Also 

lacking is a clear recommendation for a gap analysis of information required be 

obtained for improvements in the establishment of criteria. The document lacks an 

outline of the kinds of data required to implement a comprehensive nutrient strategy. 

Such a plan would be effective if components include: a research and monitoring plan, 

or a reference to one, and an adaptive strategy for reviewing the effectiveness of the 

criteria, on a schedule, and revising the criteria as necessary.

A general caveat about the hysteresis effect is also worthwhile at this point. While the 

aim is to maintain nutrient concentrations below a threshold in waters that are not 

impaired, for waters that are impaired, rolling back concentrations to the threshold 

concentration may not necessarily be restorative of impaired waters to a non-impaired 

condition. Every increment above an empirically derived threshold produces an 

ecosystem that is in further imbalance, with biogeochemical alterations whose effects 

are not easy to detect, account or predict. Applying reference conditions or even doseresponse experiments does not account for changes leading to these hysteresis effects. 

The trajectory of the ecosystem backwards along a nutrient gradient is unlikely to be 

linear or to be the exact reverse of the trajectory forward along that gradient. Often, the 

dose-response relationship is far different, and less favorable in the reverse direction. 

This fact, in context of the results of the statistical analyses, experiments and field 

observations included in this document argue for a protective threshold somewhat more 

conservative than the bare minimum required for prevention of a step increase in a 

relatively pristine system.

In summary, there is a good foundation for establishing nutrient criteria presented here. 

Mass balance models and simple process-oriented accounting for nutrient 
11

transformations and flows would go a distance in supporting the nutrient dose-response 

relationships and frequency distribution benchmarks. The proposal should succeed 

with incorporation of a plan for continued research and monitoring that will provide the 

information necessary to supply these models. 

2. Chapter 3. Please comment on the use of the SCI, LVI, and SDI as reliable indicators of the 

aquatic life designated use attainment and whether these metrics appear to be sensitive 

indicators to nutrient enrichment?

Reviewer 1 I understand the desire to tag a nutrient standard to some form of biological measure 

because the Florida Statue F.A.C. 62-302.400 defines a designated use for its water of 

“Recreation, propagation and maintenance of a healthy, well balanced population of 

fish and wildlife.” With this in mind, I examined and tested the ability of an Index of 

Biological Integrity (IBI), using fish data, to account for variability in anthropogenic 

impacts (Schultz et al. 1999; Schultz et al. 2000). I found that the IBI could not account 

for the variability in anthropogenic impacts. The problem was that there are naturally 

occurring gradients in Florida that are related to individual metrics used to calculate an 

IBI that overshadow anthropogenic impacts (trophic state, pH, lake surface area and 

others). Developing models relating metrics to these naturally occurring gradients then 

examining residuals and anthropogenic measures may be a good way of fine tuning 

IBIs but I have not yet attempted that analysis.

For this vary reason I believe that the SCI, LVI and SDI are the wrong approach for 

setting nutrient standards for the State of Florida. My strength is not with invertebrates 

but I know individual species of aquatic plants and diatoms are found in lakes with 

different water chemistry along gradients of pH, alkalinity and nutrient concentrations 

(Hoyer et al 2004; Beal 1977). As mentioned in my general comments these water 

chemistry parameters correspond to different geological factors across Florida. Thus 

any biological index that has metrics that vary with a naturally occurring gradient will 

be of little use in determining the extent of anthropogenic impacts. This seems to be 

pointed out with the SDI in the report showing the relation between pH and SDI in 

Section 3.7. As I mention, there may be a way to model the relations between SCI, LVI, 

SDI and naturally occurring gradients related to geology and then examine the relations 

between the residuals and anthropogenic measures.

Another large shortcoming of the LVI is that there is no metric in it accounting for the 

total abundance of aquatic plants in a lake system. The presence or absence of 

individual plant species and/or plant community types have little impact on whole lake 

species composition of other fauna. However, the lake’s total percent area covered 

(PAC) with aquatic vegetation and/or percent volume infested (PVI) with aquatic plants 

are directly related to the species composition of other fauna in lake systems. For 

example, both fish and aquatic bird communities have individual species that increase 

as a percentage of the whole community when PAC and PVI increase and individual 

species that decrease when PAC and PVI decrease. Additionally, fish and bird 

communities have opportunistic species that maintain a constant percent of the 

community as aquatic plant abundance changes.
Beal, E. O. 1977. A manual of marsh and aquatic plants of North Carolina with habitat 

data. Tech. Bul. No. 247. The North Carolina Agricultural Experiment Station.

Hoyer, M. V., D. E. Canfield Jr., C. A. Horsburgh, and K. Brown. 1996. Florida 

freshwater plants a handbook of common aquatic plants in Florida lakes. SP 189. 

University of Florida/Institute of Food and Agricultural Sciences. Gainesville, Florida.

Schulz, E. J., M. V. Hoyer and D. E. Canfield. 1999. An Index of biotic integrity: a test 

using limnological and fish data from 60 Florida lakes. Transactions of the American 

Fisheries Society 128: 564-577.

Schultz E. J., M. V. Hoyer, and D. E. Canfield Jr. 2001. Reply to comment: An index of 

Biotic Integrity: A test with limnological and fish data from sixty Florida lakes. 

Transactions of the American Fisheries Society 130:172-173.

Reviewer 2 Chapter 3.

I commend South Carolina DEP on the development of the SCI. Clearly they spent a 

lot of time and effort to produce a solid, scientifically defensible product. It is an 

excellent tool for assessing benthic health for general pollution impacts (organic, 

chemical stresses, and sedimentation problems). However, its use to detect nutrient 

pollution is likely to be only partially successful. It would work where a stream was 

chronically polluted by nutrients (downstream of a point source with no nutrient limits, 

a stream polluted by septic system leachate, a high-fertilizer agricultural field perhaps); 

these situations would produce chronic algal blooms and consequent semi-continuous 

issues with bottom hypoxia or food chain disruptions from excessive Cyanobacteria. 

However, in a situation where nutrient loading is acute (i.e. rain event driven) like in a 

suburb for instance, blooms may be short lived. Benthic invertebrates are known 

(especially in the South) to colonize rapidly and be multivoltine, thus by sampling 

benthos rarely (such as every couple of years, or even twice a year) acute impacts will 

be missed and the SCI will be misleading in these circumstances.

As to the LVI, invasive aquatic macrophytes will colonize and overgrow even pristine 

waters. While elevated nutrients will certainly exacerbate such a situation, invasive 

nuisance species often do not require excessive nutrients to proliferate and the index 

will not reflect nutrient loading.

Regarding the SDI, as noted in the material this diatom index has issues especially with 

the naturally-acidic pH values present in Florida (and other Southern) waters. Benthic 

diatom indices were developed by Ruth Patrick and others working in northern streams 

in Pennsylvania and such areas, where acid streams were un-natural (caused by acid 

mine drainage, for instance) and devastating to many species that were not evolved 

under such conditions. Thus, the SDI at present remains more of a goal than a product 

useful for nutrient loading assessment in Florida waters.

Reviewer 3 Biological indices have been widely and successfully employed. The SCI and the LVI 

for Florida were clearly developed using well-established and sound methodologies, 
13

were convincingly demonstrated to be sensitive to environmental gradients and 

anthropogenic disturbance, and are therefore good indicators of aquatic life use 

attainment. The periphyton based SDI was apparently still in a developmental stage for 

Florida waters, though the SDI has been demonstrated in other regions to be particularly 

sensitive to pollution gradients. Chapter 3 does not explicitly address whether or not 

the indices are sensitive to nutrient gradients; chapter 6 does.

Reviewer 4 The SCI and the LVI appear to be sensitive to human disturbance making them useful 

reaching conclusions about use impairment. Reliability was tested by having experts 

evaluate biological condition without foreknowledge of the SCI or LVI scores. There 

was very good correspondence between the expert assessments and the actual index 

scores. Each index (SCI and LVI) was developed to be responsive to human 

disturbance as defined by a human disturbance gradient (HDG). The HDG for the SCI 

included a water quality index that incorporated several water quality measurements, 

while the HDG for the LVI included ammonia concentration.

Both indices – SCI and LVI – respond to changes in nutrients, but they also respond to 

other facets of human disturbance. [Chapter 7 presents a more compelling 

demonstration of the relationship between disturbance and nutrients.] The “wedgeshaped” relationships that appear throughout the document are expected because of the 

multiple pathways by which human disturbance can affect biological communities. 

Wedge-shaped relationships present a challenge in terms of defining thresholds for 

nutrient effects, but the challenge is worth confronting because the effect is real and 

important.

The distinction between reference and “impaired” sites is not so clear that everyone will 

be convinced, the elegant statistical analyses notwithstanding. The underlying premise 

is that stressors produce a gradient of biological response (Biological Condition 

Gradient). When experts evaluated sites for biological condition (and without 

foreknowledge of SCI or LVI scores), they could agree about the qualitative evaluation 

of sites at the ends of the spectrum (reference vs. impaired), but did not agree about 

those in the middle of the spectrum.

The results of the expert panel show clearly that reasonable people may disagree about 

the biological condition of sites in the middle of the stressor gradient. Nevertheless, the 

analysis is used to support the position that “not reference” equals impaired. This 

position seems to prejudge a policy decision regarding attainment, which is not 

necessarily synonymous with reference.

Selecting the 2.5th percentile as the threshold for impairment would seem to be the 

quantification of a policy decision regarding use attainment. Yet, it suggests that 2.5% 

of all reference sites would be considered impaired. Give the very rigorous screening 

procedures used to select the benchmark nutrient reference sites, the threshold for use 

attainment is set quite high. A passage from the text (page 21) suggests that the 

willingness to tolerate misclassification of impacted sites may have been less than that 

for reference sites.

Therefore, the risk is low (virtually non-existent for the SCI) in applying the biological 

assessment tool and falsely identifying impacted sites as attaining an aquatic life use.
In contrast to the optimism I feel about use of the SCI and LVI, there seems to be less to 

recommend the SDI (described as still under development in other parts of the report). 

The report concludes that it is “an unreliable tool for assessing adverse human effects 

on stream systems,” and I would not disagree. The sensitivity of diatom assemblages to 

pH is a strong confounding factor, but no one should be surprised that diatoms are 

sensitive indicators of pH. The extensive literature on acidification is replete with 

examples. Perhaps the broader question concerns the merits of including the entire 

algal community rather than restricting analysis to diatoms.

Reviewer 5 This chapter describes two existing index approaches currently in use by DEP for 

assessing condition of streams and lakes: the Stream Condition Index (SCI), and the 

Lake Vegetation Index (LVI). There is also a short discussion of the Stream Diatom 

Index (SDI) which is currently under development by DEP. It is not clear how the SDI 

would be used in relation to the SCI. All three techniques are tied into the EPA’s 

Biological Condition Gradient (BCG) approach of rating systems on a six-tier scale of 

habitat degradation, a standard assessment methodology widely applied and validated 

throughout the country. The SCI was linked to the BCG via a calibration exercise and 

the two systems cross-walked with a high degree of fidelity.

The SCI is based on macroinvertebrates and generally applied by comparison to 

reference sites, since the pristine condition of most sites sampled has long-since been 

altered by human impact. Through multiple lines of evidence, fundamental ecological 

concepts, expert opinion, reference conditions, SCI ratings were established which 

indicated impairment. The technique must account for, and remove, effects of natural 

variation and stress on community response variables. The methodology for 

establishing the rating scale and determining the threshold for impairment appeared 

sound and well-founded.

Similar to the SCI, the Lake Vegetation Index incorporates four metrics that together 

give an indication of the health of the water body compared to a reference scale. A 

calibration of the LVI to BCG similar to that done with the SCI was performed with 

equally encouraging results. The LVI examines aquatic plant complexes as a measure 

of the health status of the lake ecosystem. The index is an integrative approach that 

yields overall score of condition based on multiple factors. The application of the 

reference site approach is well-justified and appears be based on a methodology that 

yields statistically valid results. The general interpretation of the highly variable results 

in the low range of the Human Disturbance Gradient (HDG) is reasonable. Sampling 

guidance in order to reduce Type 1 errors (false positives) is well constrained and 

reasonable. Analysis of variability at a site over time reflects the inherent temporal 

variability that may be expected in the natural world when applying this index.

Both the SCI and LVI approaches deliver a robust, standard way of identifying 

impaired waters for which nutrient criteria should be targeted and that are linked to the 

BCG used by EPA throughout the country. The utility of the SDI, based on diatom 

community structure, is less clear at this point. While the technique has been used in 

Scandinavia (Soininen and Kononen, 2004) and Western Europe (Prygiel, 1994) for 

many years, the application to Florida waters is as yet untested and will require further 

development. If improvements are made to the diatom index, it could provide a needed 

complement to the information provided by the SCI for streams. 
15

3. Chapter 4. Please comment on the approach used, given the available data, to derive the 

proposed nitrate-nitrite criteria for Florida’s streams (< 40 pcu).

Reviewer 1 My major concern about the approach used to set nitrate-nitrite standards for clear 

(<40 PCU) is that only concentration is used and the total load of nitrogen is not 

accounted for in different systems. This is important to me because I examined 

impacts of nutrients to the growth of aquatic plants and periphyton in 17 central 

Florida streams (Canfield and Hoyer 1988) and five coastal streams (Hoyer et al. 

2004) and in each case concentration was not related to total biomass of aquatic 

plants and/or periphyton. Both studies showed that physical factors (canopy cover, 

water clarity, mean depth, stream velocity, substrate type, and/or salinity) were more 

important to the growth of plants and/or periphyton in the rivers than nutrient 

concentrations. Additionally, each study showed that the percentage of nutrient 

incorporated in the total biomass of aquatic plants and/or periphyton was extremely 

small compared to the annual load suggesting that regardless of concentration plenty 

of nutrients are available throughout the year to support the growth of aquatic plants.

Canfield, D. E., Jr., and M. V. Hoyer. 1988. Influence of nutrient enrichment and 

light availability on the abundance of aquatic macrophytes in Florida streams. 

Canadian Journal of Fisheries and Aquatic Sciences 45: 1467-1472.

Hoyer, M. V., T. K. Frazer, S. K. Notestein and D. E. Canfield, Jr. 2004. Vegetative 

characteristics of three low-lying Florida coastal rivers in relation to flow, light, 

salinity and nutrients. Hydrobiologia 528:31-43.

Reviewer 2 Chapter 4.

I really liked the approach used in the derivation of a nitrate benchmark for clearwater spring-sourced systems in Florida. It was based on multiple lines of evidence. 

There were two types of bioassays performed, and since I have utilized and published 

results of bioassays on a number of occasions I was pleased by this. I also liked the 

fact that field data were included utilizing periphyton coverage and nutrient data, with 

regressions performed. In fact, strong statistical analysis was a hallmark in this 

criterion derivation.

A couple of comments to improve the scientific validly of the approach follow. I 

noted that the great majority of the literature cited within this chapter consisted of 

Florida DEP reports and other reports (USGS) – which are “grey literature”, and not 

peer-reviewed by the academic scientific community. That weakens the arguments a 

bit (although I agree that the proposed standard appears reasonable). The authors 

should get deeper into the peer-reviewed literature on this (if there is literature 

available on the subject). The second issue is that of ammonium. This is a form of 

inorganic nitrogen that is readily utilized by algae, yet no data are provided on its 

prevalence in the spring sites. In North Carolina the inorganic N in groundwater can 

be dominated either by nitrate or ammonium, depending upon sources (i.e. nitrate 

often dominates downflow from golf courses, but ammonia dominates where septic 

system leachate is a factor). To strengthen their arguments the authors need to 

provide data on ammonium in the springs – if it is low then the proposed standard is 

valid, but if it is high adjustments may need to be made. In fact, ammonium is used 
in Chapter 6 (see Fig. 6.1) so it should be taken into account here as well.

Reviewer 3 Chapter 4 clearly articulates the beneficial uses of Florida’s clear, spring fed streams 

by providing the historic narrative and photographic comparisons. This approach is 

particularly apt for the issue of nutrient enrichment, where concentrations tend to rise 

slowly over time, attendant effects are subtle, and the changing condition becomes 

culturally normative (at least until conditions become egregious). The empirical 

evidence presented in Figure 4-4 corroborated the anecdotal historic accounts, and set 

the stage for the experimental work. The concentrations found to saturate algal 

growth in the laboratory experiments dovetailed nicely with the change point 

thresholds identified in the field surveys. The TMDLs described in section 4.7 pulled 

together multiple lines of evidence: comparison of existing condition (i.e., nitrogen 

concentrations) with reference condition, longitudinal field surveys, and change point 

analysis to identify target concentrations. Again, the thresholds found in the TMDL 

work converged with the field surveys and laboratory studies. In total, Chapter 4 

presents a highly defensible basis for nitrogen criteria applicable to clear streams.

Reviewer 4 The proliferation of nuisance algae in Florida’s spring ecosystems over the last 50 

years is disturbing (and the photographic documentation in the report is dramatic). 

The attendant ecological changes are significant, as are the concerns about 

impairment of recreational use. The scale of disturbance is astonishing, and there is 

little doubt that it is of anthropogenic origin. The application of herbicides – intended 

to suppress non-native vegetation – apparently created a disturbance that may have 

facilitated algal dominance. It is not clear how the disturbance may have complicate 

efforts to develop nutrient thresholds.

The documentation of increasing nitrogen concentrations seems thorough. The 

connection to human population growth is logical, although the basis for the proposed 

lag time should be strengthened. It is asserted, but not documented, that “nitratenitrite has been linked to many of the observed detrimental impacts in spring 

systems.” Nevertheless, I would agree that lower nitrate concentrations are be 

desirable.

An issue not discussed is the appropriateness of deriving criteria based on studies of a 

nuisance species (Lyngbya) in a disturbed ecosystem. The laboratory studies identify 

nitrate concentrations below which Lyngbya biomass and growth rates are low. I 

searched in vain for an explanation of how this information would lead to conclusions 

about the nitrate concentrations supportive of a healthy native plant community in the 

spring ecosystems. Even the field surveys contain no information about nitrate 

concentrations in springs that still have healthy native plant communities.

The rest of the chapter makes good use of field data to identify thresholds based on 

periphyton abundance. The case for the proposed threshold of 0.35 mg/L needs to be 

stronger; visual inspection of the figures might lead readers to conclude that a lower 

number would be more representative.

Reviewer 5 This chapter described the derivation of criteria for TN and TP for springs and clear 

streams in Florida. The DEP recognizes the unique importance of the clear stream 
17

class of Florida aquatic ecosystems. Pollution of groundwater and the reduction of 

groundwater supply through consumptive use have increasingly become threats to 

spring ecosystems, leading to replacement of native SAV by exotic species, algal 

overgrowth and the development of thick benthic algal mats. Secondary problems 

include organic matter accumulation, hypoxia, loss of water transparency and 

deleterious shifts in faunal composition, including to toxic species.

It is proposed that the spring analysis and protocol for criteria development be 

expanding to all clear stream systems. This broadening of target systems may be 

applicable but there are differences between stream and a spring ecological systems 

which may present difficulty with transportability. These inequalities include 

differential source waters, biogeochemistry and ionic composition and higher 

temperatures that may affect biota differentially and promote uncertainty in 

predictions deriving from nutrient enrichment. Moreover, given the nature of sources 

and nutrient inputs in the two types of flowing waters, N inputs to stream sources may 

be more directly detectable and effectively controllable than those to springs drawing 

from subsurface inputs, arguing for a different set of analytical tools at least (and 

possibly nutrient criteria) for the two types of systems.

By one criterion, namely the presence of nuisance macroalgae, a nutrient criterion of 

xx is suggested. By a second criterion, “excessive” algal growth, another is suggested. 

On both lines of evidence, a TN criterion of 0.35 mg/L is proposed to represent a 

threshold with a significant margin of safety. Based on the data presented though, 

both criteria seem to suggest a threshold closer to 0.23 would more effectively 

provide that margin.

Notes

p. 49: wouldn’t the conservative target concentration be 401 instead of 420 μgN/L?

The inconsistent use of units (μg and mg) is distracting. Concentrations should all be 

expressed in one unit, preferably μg.

p. 51: why 0.23 is unnecessarily protective is not made clear- what is the support for 

this statement? The authors make a point to state that the microcentrifuge experiment 

that produced the 0.23 result is likely the more accurate of the two experiments- why 

disavow that statement now? Further if the range between 0.23 and 0.44 mg/L 

“clearly demonstrate” an imbalance of aquatic flora, why is 0.23 “unnecessarily 

protective?” 

Figure 4-12: While there is clearly a step around 0.44 (consisting of only two points), 

there is equally clearly an increase beyond about 0.24 mg/L. Why disregard that? It 

appears that the lower threshold is being set at too high a concentration. There is a 

school of thought that the first evidence of alteration of the ecosystem in response to a 

stressor such as nutrients is already beyond the important threshold- that the historic 

buffering and homeostatic properties of the system have been exceeded and the 

system is in motion, possibly toward a change in state. At the least, autocatalytic 

properties may begin to create feedbacks that amplify the negative effects of stressors 

(Odum, 2007). 
4. Chapter 5. Please comment on the regionalization of Florida’s streams in support of the 

nutrient benchmark approach.

Reviewer 1 This could be the strongest section of the document and I wish the approach was 

broadened to each section. I cannot overemphasize the importance of the variable 

geology in Florida and its strong impact on the water chemistry of aquatic systems. 

Griffith et al (1997) defined 47 Lake Regions in Florida based on water chemistry, 

hydrology and physiography of over 1,000 Florida lakes. This may be a lot of regions 

and some of them may be able to be combined but collapsing them to only five nutrient 

regions dilutes some of the complicated geology present in Florida. I think combining 

all available data in Florida and refining Griffith et al. (1997) regions would be the best 

approach for setting nutrient regions for the state of Florida.

Griffith, G. E., D. E. Canfield Jr., C. A. Horsburgh, and J. M. Omernick. 1997. Lake 

regions of Florida. EPA/R-97/127 U.S. Environmental Protection Agency, Corvalis, 

OR.

Reviewer 2 Chapter 5

Clearly there is strong regionalization in terms of TP for Florida’s streams; it is well 

known that phosphate mining is a major industry and that P releases from the Gulf 

Coast rivers impact algae blooms in western Florida Bay. The authors did a logical job 

of working through several techniques to obtain their final product. Kriging is well 

known as a grouping technique of choice in these situations. I have a few comments for 

consideration:

1. Much is made of the “nutrient reference streams/sites” but these are not really 

explained until later in the report (Chapter 7). At least some information on their 

criteria as presumably unimpacted systems should be up front in Chapter 5.

2. It is not explained why the Everglades region is not addressed in this chapter.

3. The TN stream nutrient regions deserve their own map, like the one for TP on 

Figure 5-7.

Reviewer 3 Robertson et al. (2006) demonstrated that collapsing ecoregions (and drawing ad hoc 

boundaries) into aggregated nutrient regions was an effective way of setting regional 

expectations for ambient nutrient concentrations. The methods presented in Chapter 5 

appear rigorous, and accomplished the objective of stratifying meaningful population 

units.

Reviewer 4 Establishing a spatial framework is an important practical component of criteria 

development. EPA provided a good starting point with the elaboration of the ecoregion 

approach. States are well served by the initial framework, but can use local knowledge 

to improve the scheme. Florida has taken a logical approach by adapting the ecoregion 
19

boundaries to accommodate those geological considerations that affect phosphorus 

concentrations in surface waters.

The number of regions seems manageable from a regulatory perspective and, although 

the scheme was developed to recognize geologic factors controlling phosphorus 

concentrations, it does not seem to be in conflict with nitrogen distributions. The result 

seems to be a suitable companion to the nutrient benchmark approach.

Reviewer 5 Chapter 5 discusses a scheme for the regionalization of the state in order to develop a 

spatial framework for better understanding of nutrient effects on inland waters and in 

recognition that differences in landscape or seascape settings can have an overarching 

effect on nutrient dose-response relationships in the environment. The narrative 

describes the procedure undertaken for determining, verifying, refining and classifying 

regions for determination of stream nutrient criteria for P and N. Regionalizations were 

established based first on the EPA ecoregions, then refined based on taxonomy of 

biological distributions, then finally by nutrient levels. It is not clearly explained how 

the ecoregion approach and the biological taxonomy approach were used in support of 

the nutrient approach, if at all. Biology may not reflect underlying nutrient regime or 

biogeochemistry.

There is much description, a disproportionate amount of space in fact, of the means by 

which a part of the western peninsula is split two subregions: Peace River and Bone 

Valley, based on TP concentration. The discussion of regionalization based on TN is 

barely mentioned, although TN is more heterogeneous and therefore more difficult to 

classify. Further, there is no discussion how the southern portion of Florida would be 

subdivided into, perhaps, Everglades, rocky glades, marl prairie, coastal plain and 

riverine environments, creating equally heterogeneous landscapes. As demonstrated in 

the application of nutrient regionalization in later chapters, the step is a productive one 

and does assist in the evaluation and quantification of effects of nutrients on biological 

responses; further detail on state-wide regionalization is required.

Notes

P 61: The statement that bioregions were not sufficiently homogeneous with regard to 

nutrient concentration has no backup. What were the criteria for homogeneity and why? 

The alternatives based on a slew of variables are not defined well nor is a justification 

provided for their use.

How will the disparate regionalizations between N and P driven be reconciled to each 

other and to the biogeography? Or will they? Does the biology reflect the nutrient 

regionalization(s)? TN or TP or whatever is limiting? This would have been an 

interesting analysis- there is more to regionalization than classifying based on nutrient 

levels as surely the authors understand. 

How will the regionalization be connected to the criteria formation? This is not 

described in this section although it may be referenced in other parts of the document. 

It would be useful to understand how the regionalization will be incorporated into the 

overall process of criteria development here as part of the chapter describing the 

classification framework itself.
5. Chapter 6. Please evaluate the stressor-response approaches for numeric nutrient criteria 

development.

a. Please provide any additional approaches or methods that could use the available 

data to derive numeric nutrient criteria.

b. Can the stressor-response approach, as described, dependably correlate in-stream 

nutrient concentration with measurement of biological condition at the same place 

and time? What else may need to be considered?

c. What issues need to be considered when stressor-response based criteria are applied 

across the regionalization scheme presented in Chapter 5 (or other an alternative 

scheme)? 

Reviewer 1 As mentioned above, and the conclusions of Section 6, other factors (pH, color, canopy 

cover, stream velocity, water color and aquatic plant abundance) appear to be driving 

the biological responses of rivers more than nutrient concentrations. However, fish and 

aquatic bird’s abundances in a wide range of rivers are directly related to nutrient 

concentrations, so the basic productivity of rivers is still functioning similar to lakes. 

Therefore, I feel the best approach to evaluate biological stressor-response is to make 

sure to separate streams into ecoregions based on geology, hydrology and physiography 

then develop the best models relating biological measures to physical factors of the 

stream and compare the residuals of these models to nutrient concentrations within 

ecoregions.

Hoyer, M. V., and D. E. Canfield Jr. 1991. A phosphorus-fish standing crop 

relationship for streams. Lake and Reservoir Management 7: 25-32.

Hoyer, M. V., S. K. Notestein, T. K. Frazer, and D. E. Canfield, Jr. 2006. Bird density, 

biomass, and species richness on five Florida coastal rivers, with comparisons to 

Florida lakes. Hydrobiologia. 567: 5-18.

Reviewer 2 Chapter 6

As I indicated earlier, using benthic taxa to assess nutrient impacts can at best provide 

partial guidance. However, I agree that there is a general trend of negative responses to 

increasing TN and ammonium. To strengthen this point the authors need to add to 

Figure 6-1 the r2and p values, so the reader can see the individual statistics associated 

with the relationships (and see if they are indeed statistically significant). 

I also have a question regarding the first paragraph on page 73 – why would % very 

tolerant taxa show an adverse response to increasing N?

To the point of alternative techniques, there are a couple of approaches that I have 

found useful. In addition to searching for nutrient criteria, it is useful to determine 

nuisance levels of periphyton biomass that can afflict streams. Dodds et al. (1998) 

analyzed data sets from several hundred streams for nutrients, benthic chlorophyll and 

planktonic chlorophyll using a frequency distribution approach and dividing the sets 

into lower, middle and upper thirds, with the dividing line of the lower two thirds the 

border between oligotrophic and eutrophic streams, and the middle-upper dividing line 

being the border between mesotrophic and eutrophic streams. Table 1 of that paper 
21

provides the suggested boundaries for those parameters. A follow-up paper (Dodds et 

al. 2002) utilized worldwide data sets and both parametric and non-parametric statistics 

to analyze stream data and found significant relationships between N and P and mean 

and maximum chlorophyll a (benthic). They also provided breakpoints (Table 6 of that 

paper). While these papers utilized data from northern streams in and outside the US, 

Florida appears to have a significantly large data set to utilize these techniques (both as 

a whole and by individual ecoregion) as a complement to the already-utilized 

approaches they have taken. By the way, those authors (as well as others such as 

Eugene Welch) consider benthic chlorophyll a concentrations of 100-150 mg/m

2

to be 

nuisance levels of benthic algal biomass.

Dodds, W.K., J.R. Jones and E.B. Welch. 1998. Suggested classification of stream 

trophic state: distributions of temperate stream types by chlorophyll, total nitrogen, 

and phosphorus. Water Research 32:1455-1462.

Dodds, W.K., V.H. Smith and K. Lohman. 2002. Nitrogen and phosphorus relationships 

to benthic algal biomass in temperate streams. Canadian Journal of Fisheries and 

Aquatic Sciences 59:865-874.

Another approach that would certainly provide an additional basis for determining 

stream nutrient criteria would be nutrient addition bioassays conducted on stream water 

for various ecoregions. We have done so in North Carolina Coastal Plain streams that 

are heavily colored, and have utilized both pristine and impacted systems (Mallin et al. 

2001; 2004). We utilized response variables including chlorophyll a (planktonic), 

bacteria counts, ATP, and biochemical oxygen demand (BOD5 and BOD20). Our 

results found breakpoints for nitrogen (either nitrate, ammonium, or urea) between 200 

and 500 ppb, above which there was significant phytoplankton growth and consequent 

significant BOD increases. We also found no significant algal response to phosphorus 

inputs, but significant bacteria and ATP responses to P loading above 500 ppb (and 

significant BOD responses) – see Mallin et al. (2001; 2002 and 2004).

Thus, the response to N by phytoplankton chlorophyll a seen by the Florida DEP 

statistical analysis in the more colored streams is not all surprising to me. It is 

important to note that phytoplankton can utilize organic N as well as inorganic N; 

organic N (such as urea) is characteristic of waste from cattle feedlots and grazing 

areas, which are abundant in Florida.

An additional point is that there are heterotrophic responses to nutrient loading that are 

not usually measured or even considered. Our streamwater bioassays found significant 

stimulation of BOD via the indirect route of N stimulation of algal loom formation and 

subsequent decay, as the Florida DEP also notes as a problem in this document. 

However, the direct impact of nutrients (especially phosphorus) on bacterial growth and 

BOD increases needs consideration as well, as seen in the publications listed below.

Mallin, M.A., L.B. Cahoon, D.C. Parsons and S.H. Ensign. 2001. Effect of nitrogen and 

phosphorus loading on plankton in Coastal Plain blackwater streams. Journal of 

Freshwater Ecology 16:455-466.

Mallin, M.A., L.B. Cahoon, M.R. McIver and S.H. Ensign. 2002. Seeking sciencebased nutrient standards for coastal blackwater stream systems. Report No. 341. 

Water Resources Research Institute of the University of North Carolina, Raleigh, 
N.C.

Mallin, M.A., M.R. McIver, S.H. Ensign and L.B. Cahoon. 2004. Photosynthetic and 

heterotrophic impacts of nutrient loading to blackwater streams. Ecological 

Applications 14:823-838.

An additional paper that delves more into the heterotrophy aspect of eutrophication is 

below:

Dodds, W.K. 2006. Eutrophication and trophic state in rivers and streams. Limnology 

and Oceanography 51:671-680.

There was a question as to whether time and place issues essentially throw a wrench in 

the nutrient loading and biological response paradigm. One must remember that 

streams are not totally “canopied” unless they are in parks and reserves. In reality 

streams wend their way through forests (canopied), then open farm fields (full sunlight), 

and road crossings (full sunlight). Thus in a nutrient-impacted stream there will be 

opportunities to form algal blooms even if much of it is in a forest. As to stream 

discharge, while elevated streamflow will certainly suppress bloom formation, in 

Florida the slope of the land is extremely gentle in most areas, and elevated flows will 

be seen only after rain events. Thus, there should be plenty of opportunities for algal 

blooms to form in nutrient-enriched streams. In North Carolina we have documented 

very dense algal blooms in blackwater streams downstream from nutrient sources, 

including streams that spend time in forested areas (Mallin et al. 2004).

Reviewer 3 a) Please provide any additional approaches or methods that could use the 

available data to derive numeric nutrient criteria.

The regressions involving the SCI and SDI (and/or their component metrics) appear 

confounded by multicollinearity. For the purposes of examining effects-based 

relationships, NOx and ammonia nitrogen should not be combined into a single 

variable, as the two are measuring different aspects of the pollution gradient. Ammonia 

nitrogen is a marker for organic enrichment and toxicity, whereas nitrate-nitrite nitrogen 

is a good indicator of nutrient enrichment from properly treated municipal effluent and 

agricultural pollution. NOx should be included in the regressions in lieu of other 

expressions of cross-correlated nitrogen given the work presented in Chapter 4. Change 

point analysis along a NOx gradient should be done using the residual variation in 

biological metrics following regression on conductivity, color and ammonia nitrogen. 

The wide confidence intervals resulting 

from bootstrapping during change point 

analysis should not be construed as a 

limitation. Rather, the median change 

points found for each metric should be 

considered in aggregate – do they 

generally fall within the same ballpark? If 

so, that shows a strong signal that can be 

used as a line of evidence supporting 

criteria. 

Gradient A

Condition

Gradient B, C, etc.
23

Quantile regression applied to wedge-shaped data sets should be used to identify a 

subset of data that is responding to a gradient of interest. The two data sets can then be 

compared to help understand the secondary gradients, and to perform direct gradient 

analysis on the data that are relatively less influenced by the secondary gradient(s).

b) Can the stressor-response approach, as described, dependably correlate instream nutrient concentration with measurement of biological condition at the same 

place and time? What else may need to be considered?

The report is vague with respect to which data are used for the SCI regressions. The 

sample size of ~ 75 appears rather small. Were these data collected prospectively along 

a nutrient gradient, randomly selected, or the result of a data cull to remove spurious 

sites from existing data? As described, the results add another line of evidence to the 

whole body of work. 

c) What issues need to be considered when stressor-response based criteria are 

applied across the regionalization scheme presented in Chapter 5 (or other an alternative 

scheme)? 

The two issues are sample size within strata, and collecting data along a defined 

gradient within strata to properly derive criteria specific to a region. Clearly, nitrogen 

criteria derived for a nitrogen limited region cannot be applied to a region primarily 

phosphorus limited as the criteria would be over-protective. However, across regions, 

states, and in disparate parts of the country, identified nutrient thresholds generally fall 

in the same ballpark (~ 0.02-0.07 mg/l TP, and ~ 0.5-1.0 mg/l N), such that criteria 

derived for one region can be reasonably applied to another if the two are relatively 

homogeneous with respect to parent geology. 

Reviewer 4 There is a refreshingly candid recognition that conditions in natural streams make it 

difficult to elucidate dose-response relationships in as clean a manner as would be 

possible in laboratory situations. Under controlled conditions, the relationships 

between nutrient concentrations and biological responses have been studied 

exhaustively and can be defined quantitatively. Certainly, the same processes are in 

play in the natural environment, but the responses to stressors are likely to be more 

variable because other factors are not controlled. The increased variability does not 

mean that the fundamental relationships between nutrients and biological responses are 

no longer operative, however.

Nutrient supplies set an upper bound on algal growth, for example, but the observed 

amount of chlorophyll often will not reach the potential defined by the nutrient supply. 

Nutrients control growth, but not loss factors (e.g., grazing or scouring). In addition, 

growth may be suppressed by toxics, like heavy metals. This scenario, in which 

nutrients set only the potential for growth, is fully consistent with the wedge-shaped 

relationships that appear so often in the report. At high nutrient concentrations, algal 

response may be high or low depending on the role that other factors, such as flow, may 

play in regulating algal biomass. Similarly, the SCI may be high or low at low nutrient 

concentrations because biological condition can be suppressed by other factors. At the 
same time, however, when nutrients are high, the SCI is unlikely to be high.

Deriving dose-response relationships from field data is a worthy goal, despite the 

difficulties, because they would facilitate identification of thresholds for nutrient 

impairment. Do suitable applications exist for dealing with the wedge-shaped 

relationships? It would be disappointing if none exists, although it would not preclude 

drawing on these data for confirmation of thresholds derived by other methods.

Reviewer 5 Relationships between nutrient concentrations and various biotic parameters in the 

ecosystem were developed in order to assess if quantifiable dose-response algorithms 

could be used in establishing nutrient criteria. The analysis of dose-response 

characteristics of nutrient enrichment on macroinvertebrates, periphyton abundance and 

chlorophyll a concentrations yielded ambiguous results. While all analyses showed the 

adverse impact of nutrients on ecosystem components, the high degree of variability in 

the relationships rendered the establishment of well-constrained quantitative 

relationships untenable.

It is likely that the utility of applying analysis of macro-invertebrates in relation to 

nutrients to determine dose-response curves that can be used to establish quantitative 

criteria is of dubious value. While impairment of a stream will undoubtedly redound 

through the trophic chain, looking at higher trophic levels as a first cut and as a means 

to determine nutrient criteria is not likely to be effective beyond its utility as a screening 

tool. The instantaneous effect of nutrient enrichment is felt in the microbial and 

plankton communities, whose impairment then links to other ecosystem components 

such as invertebrates. THAT component will suffer directly through a potentially long 

trophic chain that sometimes must pass through the detrital stage, or via negative 

impacts on environmental conditions such as reduced DO and changes in transparency 

and prey composition. 

6. Chapter 7. Please evaluate the Nutrient Benchmark Distributional Approach.

a. What, if any, additional measures should be considered in the selection of 

benchmark sites to ensure the selection of minimally disturbed sites?

b. Is there anything that can address or reduce the natural variability in the 

benchmark distribution to enhance its representativeness for each Florida 

Bioregion?

c. In Florida many surface waters have naturally low dissolved oxygen levels. Are 

there any issues to consider when including waters that experience naturally low 

levels of DO as reference streams for nutrients?

d. What issues should be considered if the distribution of a reference condition 

parameter (e.g., total N) substantially overlaps with the distribution of that 

parameter in all waters of a bioregion? 

Reviewer 1 Again, I like the idea of separating the rivers into groups using an Ecoregion concept. 

However, I have always had a problem with setting up reference benchmarks within 

regions due to the large amount of within and among variance associated with any 

biological and/or water chemistry measurements. As pointed out above, much of this 
25

variance is due to physical factors (color, canopy cover, stream velocity, slope, mean 

depth etc..) that have nothing to do with anthropogenic impacts. The selection process 

Listed in Chapter 7 could cause the elimination of lakes from the data base that are truly 

not impacted and it could also cause the selection of rivers that are unique and not really 

representative of the individual Ecoregion.

For this section, I would recommend an approach of modeling what factors account for 

the most variance in biological measures and nutrients concentrations within individual 

Ecoregions and the plot the residual against measurements of potential of anthropogenic 

impacts (LDI). Any relations or break points between the residuals and measures of 

potential anthropogenic impacts may help point to a nutrient standard.

Reviewer 2 Chapter 7

Please define WBID up front in this chapter

I am extremely impressed by the way DEP has gone about choosing reference sites for 

nutrient criteria. It was a multifaceted approach utilizing LDI, 303(d) list, the proposed 

N criteria, aerial photos, site visits, statistical analysis, and expert opinion. I can think 

of nothing that would improve upon their selection process.

As to natural variability in a benchmark stream, one aspect that may not have been 

considered is tidal action in freshwater streams. In the Coastal Plain, streams even 20 

miles inland can move with the tides, so sampling at a given tidal stage (say mid-tide 

outgoing) can reduce any variability from that source.

The question about naturally low DO values is interesting. The Coastal Plain in NC, 

SC and GA has numerous blackwater streams that have naturally low pH and low DO. 

This is due to their draining extensive swampy areas where the water is in contact with 

organic sediments and bacterial action, which draws down the DO; thus the water 

entering such streams already has low DO. Additionally, these streams receive copious 

inputs of DOM from the watershed, which is essentially food for bacteria, which then 

impart a BOD on the water. In unimpacted waters there are healthy animal 

communities that are adapted/evolved to situations of pH of 3-4, and DO of 4.0 (LMB 

fishing can be quite good!). Thus, these streams should not be excluded from use as 

benchmarks; in fact, their inorganic nutrient levels are usually quite low (the majority of 

their nutrient load is in the refractory organic form).

Reviewer 3 a) What, if any, additional measures should be considered in the selection of 

benchmark sites to ensure the selection of minimally disturbed sites?

The methods used to identify, screen, cull and eventually select benchmark sites were 

rigorous and sound.

b) Is there anything that can address or reduce the natural variability in the 

benchmark distribution to enhance its representativeness for each Florida Bioregion?

The real question is what steps can be taken to understand the variability inherent in 

natural systems. With respect to nutrients, some of the benchmark sites have relatively 
high nutrient concentrations co-occurring with good biological condition. Yes, that is 

in keeping with physically intact systems having a higher assimilative capacity than 

degraded systems, or systems overly taxed. A careful examination of the sites where 

good biology and high nutrient levels intersect should be done with an eye toward 

identifying mitigating factors like canopy cover, local stream gradient (i.e., slope), 

substrate composition, the form of nutrient resulting in the high concentration (e.g., 

wetland-derived nitrogen vs. nitrate from groundwater), etc. That information would 

then aid in interpreting data from all sites.

c) In Florida many surface waters have naturally low dissolved oxygen levels. 

Are there any issues to consider when including waters that experience naturally low 

levels of DO as reference streams for nutrients?

The daily range of DO is the key to understanding nutrient enrichment. For streams 

with naturally low DO (blackwater streams), the DO per se does not define the 

reference condition. In those cases, high DO concentrations during the day may signal 

enrichment. 

d) What issues should be considered if the distribution of a reference condition 

parameter (e.g., total N) substantially overlaps with the distribution of that parameter in 

all waters of a bioregion? 

I simply cannot emphasize strongly enough the need to examine the distributions of 

nutrient concentrations within categorical ranges of the SCI (or some other biological 

measure/metric) for benchmark sites and for all sites by region.

Reviewer 4 Considerable effort has been applied to the task of screening benchmark sites. The 

steps seem reasonable in general. Exclusion of sites on the basis of a nitrate threshold 

seems like a clever basis for identifying far-field effects transmitted via groundwater, 

although setting the threshold at 0.35 mg/L presumes adoption of the proposed 

criterion. The exclusion of sites with SCI <40 reflects the assumption, already 

mentioned above, that impaired equals “not reference.” Perhaps this is a trivial matter 

with regard to the number of sites excluded.

I have reservations about equating “representativeness” with a minimization of 

variability in the benchmark set. It seems to suggest that an “ideal” number exists for 

reference, rather than a range. Very strict criteria have been used to select those sites 

that are minimally disturbed. In addition, sites were excluded when nutrient 

concentrations were “outliers.” While it is true that these procedures reduce variability, 

it is not a foregone conclusion that they improve the representativeness of the remaining 

sites.

Exclusion of nutrient outliers is troubling because it seems contrary to the following 

statement on page 85:

One disadvantage of using the benchmark approach is that it does not identify the 

specific nutrient levels at which biological impairment occurs. For this reason, it 

cannot be concluded a priori that adverse effects on aquatic life actually occur at 

concentrations above these values.

The rigorousness of the benchmark screening process leads me to believe that all 
27

nutrient concentrations observed at the benchmark are fully protective of the use. 

Consequently, it causes me to wonder why the impairment should not be set to the 

concentration that represents an outlier with respect to the benchmark distribution.

The final question on the Technical Charge is not a topic addressed explicitly in the 

chapter, but it is an interesting issue (if I understand it correctly). When there is 

substantial overlap between distributions of TN (for example) at reference sites and at 

all sites in the bioregion, there are two obvious interpretations – most sites are close to 

reference conditions, or undisturbed has given way largely to minimally disturbed. In 

either case, it undermines the statistical distribution approach to characterization of 

reference conditions based on a percentile of all sites. In the present situation, given the 

rigorousness of the process to select nutrient benchmark sites, it would be logical to 

conclude that most sites in the region were in attainment.

Reviewer 5 The crux of the document for establishment of nutrient criteria is embedded in this 

chapter, where DEP advocates an explicit recommendation to utilize the benchmark 

approach in lieu of the dose-response approach in the establishment of specific nutrient 

criteria for Florida’s inland waters. The dose-response analysis, described in Chapter 6, 

was insufficiently robust to develop a quantitative nutrient criterion for either N or P. 

Consequently, an analysis of the site distributional approach was undertaken. An 

elaborate screening protocol is described for winnowing available sites to benchmark 

pool. Though some assumptions can be questioned, the overall impression is of a 

conservative approach, ensuring a valid list of candidate datasets with which to 

establish minimally impacted benchmark sites. 

The lowest SCI scores for the benchmark sites with respect to N and P concentrations 

show no dose-response relationship between nutrients and SCI. Florida DEP 

considered using 75, 90, 95 and 99 percentiles of benchmarks, with adjustment for 

nutrient region, for use in setting numeric nutrient criteria for TN and TP, settling on 

the 90th percentile. The strengths of this recommendation include: General 

applicability, standardization, speed. Weaknesses include: Lack of mechanistic 

understanding of processes underlying the patterns, Lack of predictability, lack of 

inclusion of far field effects downstream as (described in analysis of Chapter 8). The 

proposed N and P criteria selected are supported by a significant amount of underlying 

analysis and are credible options as a first-cut. Continued assessment of the 

effectiveness of these criteria through a variety of standardized performance measures is 

critical in determining their validity. These performance measures are not considered in 

this document and it is a recommendation that a rigorous protocol of evaluation be 

implemented.

7. Chapter 8. Please evaluate the reliability of the Nutrient Longitudinal Study to protect the 

aquatic life use downstream and whether this approach can be applied to other estuaries or 

lakes in Florida? 

Reviewer 1 This nutrient longitudinal study focuses on only nutrient concentrations and not nutrient 

loads. Upstream concentrations have little to due with the whole load to Deadman Bay 

or Waccassassa Bay, which could potentially change chlorophyll and thus water clarity 
in the Bays potentially impacting the important grasses. Adding the data that has 

already been collected to discharge values and using the Vollenweider approach 

described in Section 14 would allow the prediction of the change in the nutrient 

concentration of the river needed to a significant change in the bays. As mentioned 

above, this approach has been extremely successful in lakes (Bachmann and Canfield 

1981) and shows great promise in Estuaries (Meeuwig et al. 1998; Meeuwig 1999; 

Meeuwig et al. 2000).

Canfield, Jr., D. E. and Bachmann, R.W. 1981. Prediction of total phosphorus 

concentrations, chlorophyll a , and Secchi depths in natural and artificial lakes. Can. J. 

Fish. Aquat. Sci. 38:414-423.

Meeuwig, J. J., J. B. Rasmussen, and R. H. Peters. 1998. Turbid waters and clarifying 

mussels: their moderation of empirical chl:nutrient relations in estuaries in Prince 

Edward Island, Canada. Mar. Ecol. Prog. Ser. 171: 139-150.

Meeuwig, J. J. 1999. Predicting coastal eutrophication from land-use: an empirical 

approach to small non-stratified estuaries. Mar. Ecol. Prog. Ser. 176: 231-241.

Meeuwig, J. J., P. Kauppila, and H. Pitkanen. 2000. Predicting coastal eutrophication in 

the Baltic: a limnological approach. Can. J. Fish. Aquat. Sci. 57: 844-855.

Reviewer 2 Chapter 8

Florida DEP conducted the longitudinal study in naturally phosphate-rich river basins to 

assess whether nutrient concentrations representative of the upper portion of the 

benchmark site distribution were protective of the designated uses of the downstream 

(estuarine) waters. Samplings were performed for a variety of standard physical, 

chemical, and biological parameters, and they were performed at the sites during the 

same day, which is an appropriate approach to reduce intraday variability. Whether it 

was winter or summer, the results showed no algal blooms, low to moderate nitrate 

concentrations, low TSS, low turbidity, normal Secchi depths, and with a couple of 

exceptions, generally good dissolved oxygen levels. As noted the benthic communities 

were in good shape, and periphyton coverage was no problem. TN was either lower 

than or average compared with moderate sized rivers elsewhere. Historical trend lines 

did not appear to show any concerns, except for an apparent increase in TN in the 

Waccasassa River over time – which did not translate into increased chlorophyll a. The 

estuarine chlorophyll a concentrations were not at levels that would be a problem to 

estuaries in general, and the seagrass beds, while the seagrass coverage appeared to be 

robust. I would concur with the conclusion that the estuaries are not being adversely 

affected by the (generally) naturally high TP concentrations in the headwaters. This 

should be an appropriate tool to help assess baseline concentrations and affects in other 

estuaries and lakes in Florida.

Reviewer 3 It is important to describe relatively intact systems as basis for comparison with those 

more disturbed, and from that standpoint, this chapter has value. As a standalone, 

however, this chapter offers little insight. It would be really helpful to meld the results 

of Chapter 8 with those of Chapter 14, including doing a model of nitrogen loading for 

the Waccasassa and Steinhatchee estuaries for comparison (and validation) to the others 
29

presented in Chapter 14. Similarly, a description of the condition of seagrass beds in 

the estuaries listed in Table 10 in Chapter 14 should be compared to those for the 

Waccasassa and Steinhatchee for context.

Reviewer 4 The longitudinal study seeks to demonstrate “proof of concept” by showing no adverse

effects in the estuary when tributary streams meet benchmark nutrient conditions. 

Although the longitudinal studies showed that the two rivers and two receiving estuaries 

are minimally disturbed, I would hesitate to conclude that they constitute proof of

concept. Criteria for each water-body type would likely be based on concentration 

thresholds, but the concentration in the stream alone does not translate directly into the 

concentration expected in the estuary (or lake). Mass transport and the hydraulic 

properties of the estuary (or lake) also would be needed to make such a prediction.

It does not seem practical on a statewide basis to derive stream criteria that are 

uniformly protective of uses in every estuary. Large differences among estuaries in 

hydraulic properties, for example, would preclude simple application of the same 

stream criteria everywhere (least common denominator?). Conversely, there is no 

reason to assume that all streams are in attainment just because they terminate in an 

estuary that is in attainment.

Criteria should be set separately for streams and estuaries (or lakes) to be protective of 

uses in each system. The TMDL process is well-suited to the task of reconciling 

situations where the stream is in attainment, but the estuary downstream is not. There is 

no reason to try to preempt that process.

Reviewer 5 Downstream reaches (streams and estuaries) are the ultimate recipients of watershed 

nutrient inputs and are usually the most susceptible waterbodies to loadings, despite the 

often attenuated nature of the upstream loads of constituents. They are also most 

complicated due to geochemical interactions, the heterogeneous nature of physical 

forcings, differences in water residence times, nutrient turnover, nutrient mass balance 

characteristics, differences in biota and biological processing. This chapter describes 

what purports to be a pilot study of the nature of upstream nutrient effects on 

downstream estuaries. The window on the subject is somewhat limited here as the two 

estuaries selected are in the same geographic area, the same bioregion, the same 

nutrient region, subjected to similar loadings, low levels of nutrient impact (meaning 

little elucidation of nutrient processing), generally similar processes and biology, and a 

limited timeframe of analysis (two samplings in 2008 and 2009). In fact, the study is 

attempting to show that the presence of unspecified seagrass and existence of an 

unspecified fishery of indeterminate province proves that the upstream benchmarks are 

protective of downstream waters. 

The analysis is minimal in the extreme. The supporting evidence of an unimpacted 

fishery, its description or its history is non-existent. There is no exposition of the type 

of seagrass in the downstream receiving waters, the SAV density, condition, its 

antecedent history, or documentation of any change over time. A fruitful dataset to 

mine for additional analysis along these lines would be that of the Tampa Bay seagrass 

restoration program (e.g. Greening and Janicki, 2006). 

Still, there is the fact that SAV found downstream of a benchmark concentration is 
encouraging. Such assessments might be considered more a screening tool- if there is 

impairment in the downstream estuary, upstream protective action must be taken; if 

there is no apparent impairment, further assessment may still be required to truly 

comprehend the effect of upstream impacts on downstream communities and 

ecosystems.

The conclusion that the benchmark is protective appears accurate as far as it goes, but 

there are many factors, assumptions and questions that remain untested by this pilot 

study. The fact the chlorophyll a increased at every station in the downstream direction 

is noteworthy. The high concentrations of organic compounds observed and 

hypothesized as being derived from exports from surrounding marshes gives a sign that 

nutrient transformations in the watershed are a potential source and nutrient spiraling 

may generate unanticipated loads of transformed species (organic N such as humics, 

urea, ammonium) with varying bioavailability that can and will cascade through the 

ecosystem in unpredictable ways. 

Marine end member nutrient subsidies provide additional inputs to estuaries that also 

must be accounted when determining whether impairment downstream might result 

from inputs upstream. A nutrient that may be limiting in a freshwater spring may not 

be in the downstream receiving water body. General understanding of estuarine 

circulation and coastal water mass transport, if not outright circulation modeling, will 

be required in many cases for true assessment of nutrient fate and transport and 

downstream effects. Furthermore, as with interpretation of any of these studies, the 

non-linear response of downstream systems to upstream inputs may result in rapid 

crossing of thresholds or tipping points earlier in the nutrient loading trajectory than 

expected. 

Caution must be applied in interpreting the results of such underspecified analyses in 

two of the most unimpacted streams in the state. Application of this analysis to lakes 

bears the same caveats. Each distinctive water body (stream, lake, estuary, spring, 

river) should be assessed in its own context for response to nutrient criteria.

8. Chapter 9. Please evaluate the methods for developing chlorophyll a numeric nutrient 

criteria for lakes.

a. Please provide any additional considerations which might provide support for 

numeric nutrient criteria development.

Reviewer 1 The trophic state scale as originally defined is a gradient without a real break point so I 

have always had difficulty with one individual chlorophyll number as a standard. The 

standards that are being proposed are reasonable and I appreciate the groupings by color 

and specific conductance. As mentioned above, color can become a problem with this 

proposed chlorophyll standards because with one rainfall color can change from low to 

high with one rainfall shifting the chlorophyll standard from 10 to 20 μg/l which is a 

huge difference. Using specific conductance to get at differences based on geology is 

conceptually a good idea but there are many lakes in Florida near the coast that have 

high specific conductance because of saltwater interferences (e.g., Walton County Dune 

Lakes).
31

The proposed chlorophyll standards also do not take into account the abundance of 

aquatic plants within individual lakes. Lake with abundant aquatic macrophytes will 

maintain low chlorophyll levels. However, if the macrophytes are controlled or die 

naturally that same lake will have much higher chlorophyll levels. This needs to be 

accounted for in any type of chlorophyll standard.

Getting back to the original purpose of setting standards, keeping waters fishable and 

swimmable for the future, almost all of Florida’s exceptional fishing lakes would have 

chlorophyll concentrations exceeding 20μg/L making them impaired on paper. This is 

one reason why I mentioned in my general comments that Florida Fish and Wildlife 

Conservation Commission needs to be involved with setting nutrient standards.

The approach I like the most that was reviewed in the document is the one taken by 

Alabama of maintaining the existing condition. Several studies (Knowlton et al 1984; 

Terrell et al. 2000) have calculated normal background variance of chlorophyll in lakes 

and they are all quite similar. Taking the abundant long-term data that is now available 

and defining normal background variance would be a good way to setting a chlorophyll 

standard. This would require constant monitoring of lakes but any lake that has an 

annual mean exceeding the normal background variance could be defined as not 

meeting use. The monitoring would be expensive with state biologists but volunteers in 

Florida LAKEWATCH have cost effectively been measuring chlorophylls for over 20 

years so it could be accomplished on a large scale.

Knowlton, M. F., M. V. Hoyer, and J. R. Jones. 1984. Sources of variability in 

phosphorus and chlorophyll and their effects on use of lake survey data. Water 

Resources Bulletin 20: 397-407.

Terrell, J. B., D. L. Watson, M. V. Hoyer, M. S. Allen, and D. E. Canfield Jr. 2000. 

Temporal water chemistry trends (1967-1997) for a population of Florida waterbodies. 

Lake and Reservoir Management 16: 177-194.

Reviewer 2 Chapter 9

I appreciate the use of the variety of approaches DEP has taken in devising the 

proposed lake chlorophyll a thresholds. They have adapted the TSI to Florida’s rather 

unique situation of lakes to properly account for colored waters interference with Secchi 

depth measurements, and incorporated rather conservative N/P ratios to devise their 

TSIs. As to the use of paleolimnological studies – I am not a fan of their use to set 

numeric criteria. While they can provide some excellent information on past histories 

of large systems such as Chesapeake Bay, and provide strong evidence for pollution 

episodes (metals in cores) and species changes, I do not feel their level of historic 

specificity is clear enough for setting these criteria. I do feel that expert opinion 

supports the 20 μg/L criterion, though.

As to biological responses, there is something that DEP should consider both as a 

potential reason for chlorophyll a use as a response variable, and impacts of increasing 

chlorophyll a concentrations. This would be the impact of chlorophyll a on 

biochemical oxygen demand (BOD5 and longer-term, perhaps BOD20). In a selection 

of Coastal Plain waters (urban lakes, urban streams, estuarine tidal creeks, and a large 
river) Mallin et al. (2006) found strong correlations between chlorophyll a

concentrations and BOD levels. I assume that Florida DEP has a rather robust BOD 

data set and perhaps they could produce regression equations for BOD as a response 

variable to chlorophyll a (or, for that matter, examine the use of BOD as a response 

variable to N and P concentrations). BOD is more closely linked to hypoxia than is 

chlorophyll.

Mallin, M.A., V.L. Johnson, S.H. Ensign and T.A. MacPherson. 2006. Factors 

contributing to hypoxia in rivers, lakes and streams. Limnology and Oceanography

51:690-701.

Reviewer 3 Chapter 9 is essentially a heuristic exercise, but a presentation of how the equations 

listed on page 126 were derived (scatter plots, statistical output, etc.) would have been 

helpful. Presumably these are based on regressions using data from the 313 lakes 

referred to on the same page. Otherwise, the information present has value in that it 

shows convergence across regions and studies, thereby strengthening the target criterion 

of 20 ug/l chlorophyll a.

The section relating cyanobacteria abundance to chlorophyll a levels offered little 

towards understanding effects of nutrient enrichment. It simply argues that maintaining 

existing conditions, will, in general, prevent HABs. A better approach would be, where 

data are available, to look at trends in cyanobacteria abundance over time for selected 

lakes where nutrient concentrations have increased. 

a) Please provide any additional considerations which might provide support for 

numeric nutrient criteria development.

The results from Chapter 9 should be melded with those from Chapter 10. Specifically, 

for lakes where the LVI was scored, the TSI should be calculated, and the scores 

regressed against each other. That might show a significant change point in the LVI in 

relation to the TSI, thus bolstering both indices as effects-based outcomes.

Reviewer 4 Florida has already developed a proposal for chlorophyll criteria in lakes, and the 

chapter summarizes multiple lines of evidence in support of those criteria. The 

development of lake criteria benefits from long experience is assessing lake water 

quality. Past assessments have focused largely on trophic state using a Trophic State 

Index (TSI). Carlson’s original concept for a TSI was modified by substituting nitrogen 

for Secchi depth and by averaging the three component indices. Although Carlson did 

not recommend averaging component indices, it is not without precedent. The use of a 

TSI for criteria development is practical, especially when there is a strong interest in 

supporting fishery yield (to the extent that fishery productivity is related to trophic 

state).

Six lines of evidence were examined in the chapter. The conclusion is drawn that they 

“converge to support the Florida IWR TAC’s original recommendation that 20 μg/L of 

chlorophyll a in colored lakes is protective of designated uses.” All approaches are not 

necessarily mutually compatible, however.

a.) Florida is fortunate in dealing principally with natural lakes because 

paleolimnological studies can be used to good advantage. These studies suggest that at 
33

least some Florida lakes have always been relatively productive. If some lakes were 

productive prior to human disturbance, it argues for caution in the application of a 

reference distribution approach, wherein low productivity is presumed to reflect 

minimally disturbed conditions.

b.) It is not clear what role expert opinion (i.e., what other states have done) 

should play in view of the other options available, unless it is a matter of seeking 

reassurance in similar conclusions.

c.) Biological response is clearly a desirable approach, and several states have 

presented ideas. Minnesota has probably done the most in this regard. [Note that, the 

information attributed to Colorado is mistaken because no proposals have been made 

yet for nutrient criteria.] Criteria developed for fishery support may not be uniformly 

compatible with all uses in other states.

d.) User perceptions would seem to be a good basis for defining thresholds for 

aesthetics in particular, but work in Texas suggests that “acclimation” of the observer 

may affect perceptions.2 One of the difficulties in considering criteria simultaneously 

for fishery support (likely to be on the high side of chlorophyll) and user perception 

(likely to want clearer water) is the potential for objectives to be in conflict. What 

approach would Florida take to balance fishery and aesthetic considerations if these 

were found to be in conflict?

e.) Maintenance of existing conditions can be a strong approach for setting 

thresholds in situations where there has been a relatively long history of data collection 

and conditions have remained relatively stable. Generally, this would be more 

applicable to site-specific criteria development for a single lake where it might be 

practical to assume that uses are being met currently. It is difficult to see how it would 

address use protection on the statewide level.

f.) The reference approach is mentioned only briefly in the chapter. Supporting 

materials show that much effort was invested in this approach, which also produced 

recommendations for nutrients and transparency. However, as mentioned above, 

development of criteria with this approach would have to be reconciled with the 

paleolimnological information.

The connection between chlorophyll and toxins produced by cyanobacteria is examined 

in some detail because of the proposed magnitude of the chlorophyll criterion. An 

annual average chlorophyll concentration of 20 ug/L creates a measurable risk that one 

or more instantaneous values might exceed the World Health Organization’s moderate 

risk threshold of 50 ug/L. Previous studies have shown a tendency for cyanobacteria to 

become the dominant phytoplankton at higher chlorophyll levels. Under the 

circumstances, it was prudent to address the issue in the criteria development process. 

Evaluation of data from a large set of lakes dispelled this concern.

Reviewer 5 This chapter discusses the history and background of the derivation of trophic state 

indices for lakes that have been used in Florida and several lines of evidence for the 

established chlorophyll a standard for lakes. Paleolimnological studies indicate that 

some lakes in Florida have had naturally high chlorophyll a levels even prior to human 

habitation, around the currently established standard threshold of 20 μg/L. This is 

consistent with paleologic evidence from the region arguing for establishment of a 

chlorophyll a threshold around that range. Certain colored lakes had even much greater 

concentrations several times higher which supports the application of site specific 

 

2

http://www.twca.org/downloads/report/report_no_appendix.pdf; see Conclusions.
alternative criteria (SSAC) for lakes that warrant a deviation from a lower criterion. 

Biological responses of macroinvertebrates and fisheries have been investigated but so 

far have not proved useful as ecological attributes for specifying nutrient criteria.

Based on these and several additional lines of evidence including user perceptions and 

threshold for maintaining existing conditions, DEP has settled on a chlorophyll a 

threshold of 9 μg/L for clear lakes and 20 μg/L for high conductivity lakes. These are 

reasonable thresholds given the lines of evidence presented. In the absence of sufficient 

data, DEP has proposed to use the 90th percentile of reference conditions for nutrient 

criteria. This is also a reasonable alternative but the evidence for its use is not 

presented in this chapter.

Notes

p. 124: Note misleading sentence structure: Florida lakes do not have cool-water 

fisheries (true) but do have oxygenated hypolimnia (contrary to the implication). 

9. Chapter 10. Please evaluate the methods for developing chlorophyll a numeric nutrient 

criteria for lakes based on stressor-response analyses.

a. Please provide any additional considerations which might provide support for 

numeric nutrient criteria development.

b. Please evaluate the proposed classification and sub-classification approach for lakes.

Reviewer 1 I mentioned above problems with the LVI and that naturally occurring gradient like pH 

and nutrient concentrations that are impacted by geology are related to the LVI. 

Therefore, I am glad to see the Section 10 suggests that nutrient relations with LVI are 

not robust enough to be used here to determine nutrient standards.

If chlorophyll standards are set at 9 μg/L for clear waters and 20 μg/L for colored and 

highly conductivity clear lakes them the modeling conducted in Section 10 is done well 

and correctly. The corresponding nutrient standards would reflect the set chlorophyll 

standards.

I am concerned and not sure we have the ability to easily classify lakes into the color 

and/or conductivity groups that are being recommended. For sure, using color data Lake 

Okeechobee as any kind of a model for other lakes in the state is not appropriate 

because there are no other lakes in the state like Okeechobee. Using 40 PCU as the cut 

off for colored and clear lakes can be a difficult boundary to really define. For example, 

Grasshopper Lake in Lake County Florida would be classified as colored for 4 years 

and clear for 4 years between 2000 and 2008 (Figure 1). Florida LAKEWATCH has 

color data on multiple lakes that show the same kind of difficulty. Additionally, 18 

coastal dune lakes in Walton County Florida (Hoyer and Canfield 2008) show data 

where the lakes would be classified as low conductivity and/or high conductivity 

depending on the year data are collected (Figure 2). I feel much more work needs to be 

done with long-term data to better define the lake groups based on color and 

conductivity.
35

Figure 1. Relationship between color and date in Grasshopper Lake, Lake County 

Florida between 2000 and 2008 (Florida LAKEWATCH, unpublished data).
Figure 2. Relationship between salinity and date in Alligator Lake, Walton County 

Florida between 2003 and 2008 (Florida LAKEWATCH, unpublished data).

Hoyer M. V. and D. E. Canfield, Jr. 2008. Findings from workshops on citizen’s 

concerns regarding the future management of Walton County Coastal Dune lakes. 

Report to Chactawhatchee Basin Alliance and Coastal Dune lakes Advisory Board. 

Florida LAKEWATCH, Department of Fisheries and Aquatic Sciences, University of 

Florida/Institute of Food and Agricultural Sciences. Gainesville, FL.

Reviewer 2 Chapter 10

Macrophyte analysis – the lack of a strong correlation between nutrients and 

macrophyte coverage is not at all surprising to me. Even at log scale there is a 

remarkable amount of scatter in the plots. As alluded to earlier in this review (Chapter 

3) invasive macrophyte species do not need high nutrients to overtake a water body; just 

a lack of natural grazers and competitors. Additionally, as pointed out in this chapter, 

emergent or otherwise rooted macrophytes draw mainly upon soil nutrients to sustain 

the, which would not be reflected in the water column nutrient concentrations. One 

further note on this: on page 135, line 5; it states that lake vegetation exhibited a 

significant adverse response to nutrients. Actually it was a positive response (though 

weak).

Chlorophyll a analysis – The DEP has analyzed a robust data set to draw its 

chlorophyll-nutrient responses, and I agree that yearly averages are appropriate. Unlike 
37

in northern states, blooms can occur is spring and fall in Florida lakes (they can do so as 

well even in the Carolinas). The response relationships are strong and little scatter is 

present on the regression graphs. I am also pleased with the way DEP has broken out 

the colored lakes by degree of color. It is evident that in highly colored systems there 

will be a dilution of the regression strength with less available light. That having been 

said, highly colored lakes can and do support algal blooms, especially the shallow lakes 

that characterize much of Florida. While applying the criteria for the moderatelycolored lakes to the highly colored lakes may be considered by some a bit 

overprotective, I support this approach, having seen dense blooms in colored lakes in 

the Carolinas.

I am pleased with the use of 20 ug/L of chlorophyll a for colored lakes and for the clear 

but high conductivity lakes. However, I feel that the 9 μg/L response criterion for the 

clear, low conductivity lakes is too high. These systems are really gems that need 

stricter protections. I have been in them and, while their biotic purposes may be 

protected by 9 μg/L, their aesthetic ones may not be. For a large-scale example of what 

I am getting at we can look to Lake Tahoe, once one of the clearest lakes in the world 

but now inexorably becoming more eutrophic due to land development along the shoes 

and airborne N. I also wish to note that, on a worldwide scale, Wetzel (2001) Table 13-

18, uses a mean of 1.7 μg/L with a range up to 4.5 μg/L for his definition of 

oligotrophic lakes. So I would favor a chlorophyll a response criteria of 5 μg/L for 

clear, low conductivity Florida lakes.

Wetzel, R.G. 2001. Limnology: Lake and River Ecosystems, 3rd Ed. San Diego, 

Academic Press, 1006 p.

The attempt to determine a relationship between chlorophyll a and the percent of 

cyanobacteria dominance is interesting. I surmise that it was not particularly successful 

in that cyanobacteria respond strongly to physical factors as well as nutrients – by that I 

mean that cyanobacteria are adapted to the warm waters and high sunlight that 

characterizes so many Florida lakes. I would like to recommend DEP have a look at 

some work out of JoAnn Burkholder’s group at North Carolina State University, in 

which they found that TP and chlorophyll a were both significant predictors of total

cyanobacterial abundance (see Touchette et al. 2007). They also found the presence of 

cyanotoxins in drinking water reservoirs, and I wonder if DEP has a program to do so, 

and what nutrient factors these toxins may be related to.

Touchette, B.W., J.M. Burkholder, E.H. Hannon, J.L. Alexander, C.A. Kinder, C. 

Brownie, J. James and C.H. Britton. 2007. Eutrophication and cyanobacterial 

blooms in run-of-river impoundments in North Carolina, USA. Lake and Reservoir 

Management 23:179-192.

Reviewer 3 a) Please provide any additional considerations which might provide support for 

numeric nutrient criteria development.

As noted for the SCI and streams, the stressor-response relationship between the LVI 

and nutrients appears to offer an additional line of evidence for identifying thresholds 

for setting criteria. Again, using the residuals of the LVI following regression on color 

and conductivity in change point analysis over a gradient of TN or TP should be tried. 
b) Please evaluate the proposed classification and sub-classification approach for 

lakes.

A separate slopes regression model would help here. Coding the three 

color/conductivity strata –1, 0, and 1, would allow one to directly compare differences 

between the strata in unit response of chlorophyll to nutrients, and help to evaluate the 

appropriateness of the chlorophyll a targets.

Reviewer 4 The derivation of criteria by this stressor-response analysis appears to aim at a tiered 

approach for nutrients. If a lake is “biologically healthy” and chlorophyll does not 

exceed the appropriate threshold, some latitude is granted for phosphorus and nitrogen 

concentrations. This is a very practical way of acknowledging uncertainty in the doseresponse relationship. In the present case, however, it is not clear what action would be 

taken if chlorophyll is within bounds, but one or both nutrients exceed the upper 

threshold (lower prediction interval).

There seems to be a strong rationale in the report and in supporting documents for 

partitioning lakes into clear and colored categories. It is not apparent if all lakes can 

easily be segregated into those two groups, or if there is an unbroken continuum of 

lakes. It may be an important practical matter if two similar lakes having 39 and 41 pcu 

respectively might be assigned standards that differ by a factor of two.

Less information is presented regarding the merits of conductance as an additional 

classification variable, although there is little doubt that higher nutrient concentrations 

in general would be associated with increasing solute concentrations. It might be 

interesting to learn more about the TAC’s reasoning regarding the 100 umho/cm 

dividing line, but I don’t have any particular reservations about accepting their 

conclusion. Using a rolling average for color seems like a very sound, if somewhat data 

intensive, approach.

Florida presently has independent approaches for development of criteria based on 

chlorophyll or lake vegetation. Are the two approaches drawing on the same set of 

lakes? Lakes in my area (and I believe it is true elsewhere) that have an abundance of 

macrophytes typically have very sparse phytoplankton populations even when nutrient 

concentrations in the water column would normally support more phytoplankton. 

Conversely, lakes with moderate to high levels of suspended algae rarely develop any 

substantial growth of macrophytes. If this observation applies to Florida lakes, it might 

have implications for the criteria development strategy. A plot of chlorophyll vs. LVI 

might be helpful.

Reviewer 5 The preferred means of determining a nutrient criterion for inland waterbodies is use of 

a stressor-response relationship. Florida DEP addressed the determination of nutrient 

criteria for lakes based on two response variables: lake vegetation and chlorophyll a. 

Both groups of primary producers are expected to respond to nutrient enrichment, but in 

different ways: macrophyte vegetation, generally benthic vegetation would largely be 

expected to decrease in response to enrichment, as a function of reduced light in the 

water column. This light attenuation is attributed to the increase in phytoplankton 

chlorophyll a that occurs with increased nutrient availability. As such, the macrophyte 

response is indirect- nutrients are not affecting the plants themselves, in fact would tend 
39

to promote increases in macrophyte growth, all else being equal. But given that most 

macrophyte species are generally unable to grow to the lake surface, they will be 

primarily impacted by the more direct response of phytoplankton growth to nutrient 

enrichment. As such, because it is at least the second link in this chain, any relation 

between nutrients and macrophytes would be expected to be looser, with the degree of 

“play” dependent on many other factors. 

In fact, DEP investigated the relationship between macrophytes and nutrients and found 

exactly that to be the case- using the lake vegetation index (LVI) a weak, though 

significant correlation with nutrient concentration was found. An adverse (i.e. inverse) 

response of vegetation to nutrients was apparent but insufficiently robust to be 

applicable as a basis for establishing nutrient criteria. A more effective relationship 

between nutrients and phytoplankton chlorophyll a was found, and produced a useful 

basis for establishing nutrient criteria as discussed in the previous chapter (Chapter 9). 

Authors recommend that the criteria be performance-based. This is a reasonable and 

acceptable way to proceed- provided that it works both ways. The recommendation of 

the chapter’s authors is that if nutrient criteria are exceeded but there is no exceedance 

in the designated response variable (chlorophyll a), then no nutrient reductions are 

needed. This makes sense ecologically and from a management point of view. 

However and conversely, when data show that nutrients are within in compliance of 

established criteria, yet chlorophyll a criteria are exceeded, then one would expect that 

nutrient reductions would have to be undertaken. This reflects on a much larger issue 

that permeates this document: every one of the analyses and criteria presented are 

statistically-based, usually based on a lot of long-term monitoring data and a very few 

variables. This results in the emergence of general patterns that are accompanied by 

high variability. Fifty-to-sixty percent of explained variance is considered exceptional. 

The performance-based approach proposed by DEP for lake chlorophyll a begs the 

question of what is responsible for the large variability associated with all nutrientbased dose-response relationships. The variability is a function of lake and stream 

physical and biological processing of nutrient inputs. The large variability of 

bathymetry, hydrology, physico-chemistry, flushing, tidal signal, and biology makes 

one marvel that nutrient-chlorophyll relationships are as robust as they are. Yet the 

refinement and true understanding of those relationships will only be achieved by an 

understanding of the processes operating within the ecosystem, their rates and the 

timescales of these processes with respect to the nutrient supply. This so-called 

impedance matching (Ulanowicz and Hannon, 1987) is an ecosystem principle that 

reflects how well-tuned a system is to its cross-boundary flows, and that determines, in 

time and space, its ability to process these flows, both as inputs and export. The 

remainder of this sum is left within the system for a time as a stock or pool with which 

the system can push off in a variety of trajectories, depending again on internal 

processing. 

Therefore, while accepting and endorsing DEP’s call for performance-based approach 

to establishment of criteria, this is a recommendation for investment in additional 

research into ecological relationships and evaluation of systems or classes of systems 

and their driving processes. Within a modicum of understanding of these mechanisms, 

managers will be able to make informed decisions about whether and how to shape the 

Site Specific alternatives for managing nutrients, beyond what the useful and necessary 

screening of blind statistical approaches provides.
10. Chapter 11. Please comment on the “all streams” statistical distribution approach for 

deriving numeric nutrient criteria

Reviewer 1 Again using the Ecoregion concept to form the base for analyses is a good start that

needs to be used throughout the document. The second paragraph in Section 11 points 

out that “Multiple factors can strongly influence the expression of biological responses 

to nutrient across water bodies, such as water velocity, residence time, availability of 

other nutrients, presence of grazers, availability of light (due to tree canopy cover 

and/or water transparency) and availability of suitable habitat. I have mentioned above, 

that in my experience physical factors dominate most aspects of stream biology and 

overshadow impacts of nutrients. For this reason I have a hard time with this approach 

to setting standards. No matter what percentage of the data distribution you use for a 

standard, some streams that are meeting use and functioning fine will be considered 

impaired.

Reviewer 2 Chapter 11

Florida DEP certainly has a robust “All Streams” data set with which to work. The 

outlier removal process could use a bit of tweaking, in my opinion. I liked that they did 

not use the removal of the upper adjacent value – that seems rather confusing to me. 

What does concern me is using TN of 100 mg/L and TP of 15 mg/L as screening 

thresholds. Levels of nutrients found in raw human sewage include TN of 35 mg/L, 

ammonium of 15 mg/L and TP of 10 mg/L (Clark et al. 1977). Therefore, unless DEP 

is sampling raw sewage ditches it would be reasonable to remove outliers more in line 

with these concentrations that the ones DEP utilized!

Clark, J.W., W. Viessman, Jr., and M.J. Hammer. 1977. Water Supply and Pollution 

Control, 3rd edition. IEP-A Dun-Donnelly Publisher.

I do have another issue with the statistical approach. DEP kicked out data when there 

were 4 or less observations within a year. Ho9wever, a lot of variability can occur with 

only 5 or 6 samples as well, both seasonal and event-driven. I suggest drawing the line 

at 8 observations or less as year as a cutoff point for data sets. Natural log 

transformation is proper for nutrients and chlorophyll – my own laboratory regularly 

does this for our publications. Finally, the comparisons between the empirical and 

theoretical 25th percentiles produced tight agreement in general. Thus, with the 

exception of the upper outliers and number of observations I am in support of this 

approach.

Reviewer 3 To reiterate what I noted in the general comments, descriptive statistics are necessary 

for a broad understanding of systems at the population level. However, the reference 

approach, in the absence of biological data, provides the weakest line of evidence for 

criteria development. The all sites chemistry data should, emphatically, be paired with 

biological data (i.e., the SCI, SDI, or a sensitive component metric) and reexamined 

within ranges of the biological data.

Reviewer 4 The “all streams” approach has been touted by EPA ostensibly because it can be applied 
41

to situations where dose-response relationships are not available and reference 

conditions do not exist or are very scarce. However, because reference (or minimally 

disturbed) sites seem readily available in Florida, there is little motivation to use the all 

streams approach. It is not reassuring to know that “the 25th percentile from the All 

Streams data was less than the 75th percentile ... from the Benchmark data set.” Some 

reference sites still will be classified as impaired.

Reviewer 5 The All Streams approach to developing water quality criteria is an alternative 

suggested by EPA for areas where data insufficiency precludes the development of 

specific numerical nutrient criteria for a region. For the Florida nutrient database, this 

is an interesting data exercise that presents an alternative benchmark for a nutrient 

region. The lower 25 percentile nutrient benchmarks for all streams, the TN and TP 

criteria proposed by EPA as the upper nutrient threshold for this analysis, represents a 

much lower concentration for both nutrients than the 90th percentile reference 

benchmark as calculated in Chapter 7.

This is a spare chapter that presents data without significant analysis. The information 

presented here is lacking recommendation or interpretation. It would have been an 

improvement to present actual shapes of nutrient concentration frequency distributions 

graphically, and specifically with the two alternative approaches overlain for each 

nutrient for each nutrient region.

The All Streams approach is presented as a fail-safe option to criteria determination 

and, in the absence of more sophisticated analyses or data sufficiency; it presents a 

reasonable, quite conservative stop-gap provision. The next step that would have been 

anticipated was not taken here- that is relating the nutrient thresholds as calculated 

using All Streams to various estimates of stream condition as was done for the other 

alternatives, dose-response and nutrient benchmark distributional approach. It was not 

explained why that was not undertaken, but obviously the All Streams statistical 

distribution approach is not being considered as an option for establishing numerical 

nutrient criteria for Florida (nor can its worthiness as an option be thoroughly assessed 

given the minimal analysis presented).

11. Chapter 12. Please comment on extrapolating background nutrient concentrations as an 

approach to deriving numeric nutrient criteria.

Reviewer 1 As the conclusion of Section 12 states, the data used in this section are too cloudy to be 

of any significant use in determining nutrient standards.

Reviewer 2 Chapter 12

I agree that candidate nutrient criteria cannot be reliably derived using the Dodds and 

Oakes (2004) method. A few comments on Chapter 12:

1) My Chapter 12 citations of tables and figures did not match the ones supplied. I 

assume Table 1 is actually Table 12-5, Figure 1 is Figure 12-3, Figure 2 is 12-2, and 
Figure 4 is 12-4.

2) Regarding the 9% increase between 1995 to 2004, I think we can safely assume it is 

due to increased landscape development (been to Gainesville lately? I couldn’t 

recognize the place when I drove through last winter....).

3) The directions of the correlations certainly are similar to what we see in the Coastal 

Plain of the Carolinas. TN and TP are negatively correlated with forest, TIN positively 

correlated with urban land and negative with wetlands, and so on. We also find fecal 

coliforms and TSS negatively correlated with wetlands, by the way.

Reviewer 3 It is a moot point. Having rigorously identified benchmark sites that are good 

representations of regional background conditions obviates the need for extrapolating 

historic background conditions.

Reviewer 4 It seems unfair to say that the Dodds and Oakes method didn’t work (“candidate 

nutrient criteria could not be reliably derived using the Dodds and Oakes (2004) 

methods as applied here with the available data”); it was not given an adequate test 

because, as stated in the report, the required data were not available. Instead, LDI 

scores were used in a simple regression model, from which only weak patterns were 

evident.

The effort to derive background conditions based on the LDI relationship seemed 

perfunctory in view of the very promising results presented previously in the report. In 

Chapter 7 (Figure 7-2), nutrient export (kg/ha/y) was strongly related to LDI for the St 

Mark’s watershed, and background yields could have been estimated. Perhaps the 

results for one watershed are not replicated elsewhere, but at least the effort should have 

been made to explore the possibility. 

Reviewer 5 This chapter presents an interesting concept that describes modeling that enables the 

back-calculation of natural nutrient levels in unimpacted hydroscapes by extrapolating 

the relationship between some index of land use and water-borne nutrient levels to the 

y-intercept where anthropogenic land use purportedly equaled zero. The authors chose 

the LDI (Landscape Development Intensity) index of human disturbance calculated 

from the area-weighted value of land use type, because it is a standard calculation of 

DEP and exists for many sites in Florida. The results are predictably scattered- there is 

no evidence of a clean relationship with low variance with such an exercise using an 

integrative parameter such as the LDI index. Nonetheless the results are intriguing and 

not altogether worthless.

The study design basically assumes that inorganic N and TP are tracers for human 

activity, on the assumption that these constituents, particularly nitrate, nitrite and 

ammonium would become more part of the landscape with increasing human activity. 

Because organic N is produced and released in great quantities by natural forested lands 

and wetland communities, it is predicted to be poorly correlated with LDI. The results 

do show significant relationships between nutrients and LDI, and no significance 

between organic N and LDI. 
43

The non-linearity of N vs. LDI is to be expected and renders the hoped-for linear 

trajectory to an intercept on the nutrient axis an unattainable goal. Nutrient releases and 

transformation in the landscape resulting from human impact are fraught with 

variability, thresholds, breakpoints, non-linearities such that a simple linear backprojection is not realistic. The simple fact that human impact alters the system’s 

hydrology in unpredictable ways will create a non-linear nutrient response. Ultimately 

though there are more effective ways of deriving benchmarks for nutrients in 

unimpacted waters that are presented in Chapters 6 and 7.

12. Chapter 13. Please comment on the use of multiple regression and statistical distribution 

approaches to deriving numeric nutrient criteria.

Reviewer 1 For reasons mentioned above, I am not comfortable with setting standards based on a 

percentage of a distribution of data. There are too many lakes that are functioning well 

and meeting uses that will be considered impaired. Similarly, without more work on 

long-term color data in lakes, I am uncomfortable with the separation of lakes into 

colored and clear lakes based on a measured color of 40 PCU.

Reviewer 2 Chapter 13

I am in agreement that large variability in chlorophyll a and nutrient concentrations 

renders a linear regression inefficient for this task, and that the non-parametric model is 

likely to yield more relevant results.

Editing remark – page 175, middle, Figure 2 should read Figure 13-3 I believe.

Page 182 – there are some issues with the Outliers and Invalid Data. Nitrate is kicked 

out if it is above 75 mg/L, yet TN is kicked out if it is above 20 mg/L – a disconnect 

here. The highest nitrate I have seen in a stream is 25 mg/L (below a failing wastewater 

treatment plant) thus DEP needs to bring this expulsion criterion down to 20 or 25 

mg/L. As to chlorophyll a, the highest level I have seen in a bloom is 400 μg/L, while 

DEP is using 1,000 μg/L as a criterion. I suggest cutting that way down to at least < 400 

μg/L. As to Secchi depth, I am not aware of Florida lakes that are 50 m deep, so why 

use a Secchi of 50 m to kick out an outlier? How about 10 m?

Another concern I have is determining annual averages using all available data for a 

given station in a year. What if it is only 3 data points? Many programs are skewed 

toward “growing season” sampling (admittedly Florida has a long growing season) but 

this would tend to skew the data for some lakes toward elevated chlorophyll in the 

means. I suggest using a lower limit of 8 samples in a year to create a mean, with 

samples taken seasonally to collect lower-impact periods as well.

Reviewer 3 The multiple regression models provided in Chapter 13 offer a more refined way to 

derive criteria than the conventional linear models appearing in Chapters 9 and 10, 

though the results from all three chapters generally comport each other. More 
importantly, however, the results suggest that once static numeric criteria are derived 

for either nitrogen or phosphorus, those criteria should be interpreted as having 

uncertainty when applied to a specific waterbody, and therefore not applied with the 

traditional independent application reserved for toxicants. Figures 13-5 and 13-7 

clearly show the range of potential criteria derived from a population of lakes. 

As with Chapter 11, the distributional analyses of data are important for understanding 

the system at a population level, but are not particularly helpful for deriving criteria. 

Again, melding in the LVI and examining the chemistry data within categorical levels 

of the LVI would help to lend context to the percentile ranges.

Reviewer 4 I am not familiar with multiple logistic regression, but it seems like an innovative 

analytical approach, and the graphs are informative. Placement of the diagonal line 

(now set to the “average ratio between ln (TN) and ln(TP)”) deserves more attention 

because it makes an important statement about the nutrient regime. The ratio used in 

the graph (0.588/0.013 = 45:1) is very high and indicative of a phosphorus-limited 

situation. Placement of the diagonal line might be adjusted according to expectations 

for a particular region. For example, in supporting references for Chapter 9, an N:P 

ratio of 16:1 was assumed to have relevance for distinguishing between limitation by N 

or P.

The output of the within-lake model (Figure 13-2) shows the risk inherent in basing 

assessments solely on nutrient concentrations. Basing decisions on nitrogen and 

phosphorus relationships from the entire data set would place criteria well below 

anything observed in the lake, even though most chlorophyll measurements in the lake 

are in attainment of the 5 ug/L threshold. The analysis seems to add weight to the 

notion that a tiered approach would be useful.

Why are the distributional statistics for lakes determined on a statewide basis when 

there are identifiable geographic patterns for phosphorus and nitrogen in streams?

Reviewer 5 Chapter 13 provides an intriguing analysis of the use of non-parametric statistics and 

Bayesian modeling techniques in establishing nutrient criteria for lakes. The analysis 

presents a proof-of-concept exercise that demonstrates how a set of TN and TP criteria 

might be developed using multiple regression models. The results of the analysis 

supports an earlier recommendation in this review that within-lake models of TN-TP 

and chlorophyll a will yield the most robust results and the most likely statistical 

approximation of a mechanistically based cause and effect relationship. 

Various aspects of the balance between site specificity, model robustness and the need 

for a large enough sample size to support three degrees of freedom leads to the 

expansion of the sample size across similarly classed lakes such that a large pool of 

lakes (93) can be fit to the model. It is curious that the entire pooled dataset in figure 

13-4 shows individual lakes within the pool seem to trend to a lower slope than the 

slope of all pooled observations. This is not discussed in the text. Overall, the 

nonparametric multiple regression approach to setting nutrient criteria protective of a 

specific chlorophyll threshold for lakes seems to hold promise and should be further 

explored.
45

It is of passing note that here as in other chapters, the distinctiveness of colored lakes is 

brought up and significant attention is devoted to incorporating terms in the model that 

will account for color. There are a number of colored lakes that show a negative 

relationship between color and chlorophyll a. While this most obviously may be related 

to light attenuation, there are other possibilities. Often the constituents of colored 

dissolved organic matter may be inhibitory to phytoplankton growth, and they may 

often act as binding or chelating agents for nutrients, reducing bioavailability. 

Therefore, the complication of dose-response mechanisms introduced by colored waters 

continues to plague efforts to quantify relationships with simple models.

13. Chapter 14. Please comment on the downstream protection approaches.

a. Does the modeling approach provide a sound, scientific basis for determining 

numeric nutrient loadings from upstream waters to estuaries?

b. Could these approaches be used to determine nutrient loadings for other waterbody 

types (i.e., lakes)?

c. Given the available information, do these approaches account for spatial variability, 

distance from downstream water, and estimated assimilation?

d. Do you know of any alternative approaches to capturing the relationship between 

upstream and downstream water quality in a WQS.

Reviewer 1 The downstream protection approaches described in Section 14 are sound and 

consistent with the conventional approach used for decades to manage eutrophication in 

lakes (Bachmann and Canfield 1981). While it has not been used extensively, 

Vollenwider type models have successfully estimated actual total phosphorus 

concentrations in estuaries and have tied nutrient concentrations to different land uses 

(Meewig et al 1998; Meewig 1999). Breaking the estuaries into watershed and 

measuring the actual loads from different sources is the only way to really manage 

aquatic systems. Using some form of Vollenwider loading model will allow managers 

to pinpoint significant loads that may be causing unwanted eutrophication.

One significant problem I have with Section 14 is that there is an assumption that 

nitrogen is the only important nutrient controlling trophic state in estuaries. In 2000 I 

sampled near shore coastal waters from three stations off of every Florida County that 

touched the ocean. These data showed that total phosphorus accounted for significantly 

more variance in measured chlorophyll than total nitrogen, strongly suggesting that 

phosphorus in the primary limiting nutrient in near shore coastal waters of Florida 

(Hoyer et al. 2002). Tampa Bay is an exception to this and nitrogen is more important 

there, but that is because Tampa Bay receives water from phosphorus rich soils. 

Therefore, the modeling efforts accomplished in Section 14 should be done using 

phosphorus instead of nitrogen.

Canfield, Jr., D. E. and Bachmann, R.W. 1981. Prediction of total phosphorus 

concentrations, chlorophyll a , and Secchi depths in natural and artificial lakes. Can. J. 

Fish. Aquat. Sci. 38:414-423.

Hoyer, M. V., T. K. Frazer, S. K. Notestein and D. E. Canfield, Jr. 2002. Nutrient, 
chlorophyll, and water clarity relationships in Florida’s nearshore coastal waters with 

comparisons to freshwater lakes. Canadian Journal of Fisheries and Aquatic Sciences 

59: 1-8.

Meeuwig, J. J., J. B. Rasmussen, and R. H. Peters. 1998. Turbid waters and clarifying 

mussels: their moderation of empirical chl:nutrient relations in estuaries in Prince 

Edward Island, Canada. Mar. Ecol. Prog. Ser. 171: 139-150.

Meeuwig, J. J. 1999. Predicting coastal eutrophication from land-use: an empirical 

approach to small non-stratified estuaries. Mar. Ecol. Prog. Ser. 176: 231-241.

Meeuwig, J. J., P. Kauppila, and H. Pitkanen. 2000. Predicting coastal eutrophication in 

the Baltic: a limnological approach. Can. J. Fish. Aquat. Sci. 57: 844-855.

Reviewer 2 Chapter 14

14.1.5 – I am concerned about one of the statements on page 188. It states “in the 

absence of more specific information it may be appropriate to reduce the anthropogenic 

contribution of the TN load to estuaries by a constant fraction.” This is not appropriate. 

As is pointed out within this very chapter, Florida estuaries vary widely in their 

watershed/water ratios, their percent loading by individual sources, their total loads, 

their size, depth, flushing, and certainly their response variables such as seagrass 

coverage and fisheries. So, the answer here is that if necessary specific information is 

not available – DEP needs to get the funding to obtain that information. There is no 

“one size fits all” solution for ecological problems such as this.

14.1.18 - Another concern I have is that of the contribution of septic systems to the 

nutrient load in estuarine waters. While DEP certainly accounts for direct point source 

contributions of nutrients to estuaries in their models, it is known from research in the 

Carolinas that nutrients from septic systems directly enter estuarine waters as well 

(Cahoon et al. 2006). Especially on the west coast of Florida there are many septic 

systems with direct or near-direct access to estuaries. In studies in Sarasota Bay and 

Charlotte Harbor it has been found that fecal microbes from septic systems enter the 

surface waters on the outgoing tide (Lipp et al. 1999; 2001); thus, presumably 

ammonium and TP will as well. This should be factored in for estuaries where septic 

system use is prevalent.

Cahoon, L.B., J.C. Hales, E.S. Carey, S. Loucaides, K.R. Rowland and J.E. Nearhoof. 

(2006). Shellfish closures in southwest Brunswick County, North Carolina: Septic 

tanks vs. storm-water runoff as fecal coliform sources. Journal of Coastal Research

22:319-327. 

Lipp, E.K., S.A. Farrah and J.B. Rose. (2001). Assessment and impact of fecal pollution 

and human enteric pathogens in a coastal community. Marine Pollution Bulletin

42:286-293. 

Lipp, E.K., J.B. Rose, R. Vincent, R.C. Kurz and C. Rodriquez-Palacios. (1999). Diel 

variability of microbial indicators of fecal pollution in a tidally influenced canal: 

Charlotte Harbor, Florida. Southwest Florida Water Management District, Technical 

Report.
47

The tide is an important consideration in obtaining accurate measures of nutrient 

loading to downstream waters. The most accurate way of accomplishing this is by use 

of boat mounted acoustic Doppler current profiling (Reed et al. 2004). This process has 

been utilized to obtain the most comprehensive modeling of nutrient loading, trends 

over time and patterns in the Neuse River Estuary to date (Burkholder et al. 2006). 

Additionally, in terms of spatial variability, the sampling scheme supporting that effort 

was able to conclusively show that collecting data only mid-stream leads to incorrect 

loading and impact estimates. By that I mean that near-shore sampling should be 

accomplished as well as mid-stream, because due to wind, current and tidal patters 

some of the largest algal blooms are found in shallower areas near-shore.

Reed, R.E., H.B. Glasgow, J.M. Burkholder and C. Brownie. 2004. Seasonal physicalchemical structure and acoustic Doppler current profiler flow patterns over multiple 

years in a shallow, stratified estuary, with implications for lateral variability. 

Estuarine, Coastal and Shelf Science 60:549-566.

Burkholder, J.M., D.A. Dickey, C. Kinder, R.E. Reed, M.A. Mallin, G. Melia, M.R. 

McIver, L.B. Cahoon, C. Brownie, N. Deamer, J. Springer, H.B. Glasgow, D. Toms 

and J. Smith. 2006. Comprehensive trend analysis of nutrients and related variables 

in a large eutrophic estuary: A decadal study of anthropogenic and climatic 

influences. Limnology and Oceanography 51:463-487.

Finally, I recommend that the modelers also have a look at the following paper:

Ensign, S.H., J.N. Halls and M.A. Mallin. 2004. Application of digital bathymetry data 

in an analysis of flushing times of two North Carolina estuaries. Computers and 

Geosciences 30:501-511.

This paper provides an approach that determines both flushing time of the estuary and 

assimilation of N within that estuary, and consequent export to sea.

Reviewer 3 a) Does the modeling approach provide a sound, scientific basis for determining 

numeric nutrient loadings from upstream waters to estuaries?

The concentrations identified in Table 10 of Chapter 14 are simply an additional line of 

evidence that support identification of criteria. Models are abstractions and depend on 

the quality of inputs. The TMDLs presented appear to have been developed by 

adhering to good methods, and were well-calibrated using empirical data. The 

approach would be more compelling if the examples for intact systems (as previously 

noted) were included for comparisons. 

b) Could these approaches be used to determine nutrient loadings for other 

waterbody types (i.e., lakes)?

Yes, it would have been nice to see the Vollenweider example worked out for a few 

lakes.

c) Given the available information, do these approaches account for spatial 
variability, distance from downstream water, and estimated assimilation?

I am not sufficiently familiar with the vagaries of the SPARROW model to comment on 

this point.

d) Do you know of any alternative approaches to capturing the relationship 

between upstream and downstream water quality in a WQS.

Short answer, no. The load-based targets for a receiving body are the most 

straightforward, and defensible on an ad hoc basis. In other words, criteria derived to 

protect the use of a given class of waterbodies should stand unless superseded by 

another need.

Reviewer 4 The SPARROW model was designed for estimating nutrient loads, and it has typically 

been applied to large regions (e.g., multi-state). While there is no conceptual reason 

why the model could not be applied to lakes as well as estuaries, there may be a 

practical limitation to the lower bound on geographic scale. As stated in a recent USGS 

fact sheet3:

In general, SPARROW models illustrate the broad spatial patterns of water quality 

well, but may be less accurate for a single stream because of limitations in the 

underlying data sets.

I am not sufficiently familiar with SPARROW to know if it incorporates process (e.g., 

denitrification) that would be relevant to assimilative capacity.

I think the larger issue concerns the extent to which this approach provides information 

useful to the development of nutrient criteria for streams. Some of the concerns are the 

same as those I cited for the Nutrient Longitudinal Study (Chapter 8). There is a 

fundamental question about linking attainment in estuaries with attainment in tributary 

streams.

SPARROW provides nitrogen load estimates that are used to drive models (not 

presented) that predict concentrations in each estuary. It is not clear if the linkage 

includes contributions of nitrogen generated by the marsh grasses within the estuary. 

Based on existing thresholds, conclusions are reached about total loads (and thus a 

flow-weighted concentration) consistent with attainment in estuaries. In the context of 

the TMDL process, it looks like a reasonable approach.

It remains a mystery how this information relates to the criteria that are appropriate for 

attainment in streams. Given the differences among estuaries in hydraulic conditions, 

for example, it is hard to imagine how generalizations can be made about the allowable 

load, much less the appropriate concentrations in tributary streams. Perhaps that was 

the motivation for the comment on page 211:

It is important to note that values derived from this approach are not applicable to 

protection of instream conditions or use attainment.

The section on lake modeling is so brief that it is hard to evaluate. Just like estuaries, 

 

3

SPARROW fact sheet – http://pubs.usgs.gov/fs/2009/3019/
49

there is a fundamental issue about the linkage between concentration-based standards in 

lakes and in the tributary streams. Criteria are defined to protect uses in lakes; if they 

aren’t being met, a TMDL should be developed.

Reviewer 5 Two potential methods are presented for assessing the “protectiveness” of watershed 

nutrient criteria to downstream waters- estuaries and lakes respectively. The bulk of the 

chapter deals with a description of application of the Spatially Referenced Regression 

on Watershed Attributes (SPARROW) model, developed by USGS. This model is used 

to estimate TN loading from the watershed to the receiving estuary for 13 estuaries in 

the state. While the model shows promise as a tool for estimating N loads to many 

Florida estuaries, it is important to note that several Florida estuaries would be 

inappropriate as targets for SPARROW modeling. Specifically, several estuaries of the 

southern peninsula, such as Florida Bay, Whitewater Bay and Rookery Bay, are not 

amenable to analysis by the SPARROW watershed model. Large interaction of surface 

flows with groundwater flows, the lack of mass flow or well-constrained point-source 

input, and multiple ungauged inputs would render such modeling ineffective.

There is a need also to evaluate the spatial heterogeneity of receiving waters, 

particularly in estuaries. The gradients that characterize estuarine systems demand that 

spatial analysis be performed, or at least considered, at the sub-basin or sub-estuary 

scale (Madden et al. 2008). Direct loadings from point sources in the upper estuaries 

render those areas different in the extreme from the lower estuary, or even mid-estuary. 

Spatially complex receiving waters create complex hydrodynamic circulations, nutrient 

regimes and biological responses. Nutrient spiraling, airshed loading and other 

uncertainties will combine create complex dose-response relationships. Adaptation of 

SPARROW analysis to the sub-estuary scale is warranted. Temporal scales are also 

exceedingly important to estuarine processing of nutrients- the timestep of the sampling 

protocol and of the analysis is critical and these need to be evaluated in the 

establishment of criteria. Seasonality, pulses, and low frequency oscillations, such as 

ENSO, will impart variability in physical and biological processing of nutrient inputs. 

The section describing application of the Vollenweider model to downstream lakes 

represents a start to the issue of protectiveness of upstream criteria inland receiving 

waters. There is minimal discussion of implementation presented. The model is valid 

for the application described- calculation of P loading and concentration in lakes as 

functions of discharge, residence time, lake volume and flow-weighted nutrient 

concentration. Yet some aspects of watershed management are not adequately 

addressed. The total loading rate can be calculated, but the lake would be receiving 

loading from multiple sources, both point and non-point. Any action taken would be 

dependent on the source(s) of the nutrient and a balancing of the source reductions 

necessary to achieve compliance. How that would be apportioned or even determined 

among the sources is left for later exposition. 

The widening of the application from single lakes to regions of lake should be 

undertaken with caution. The uncertainties of the model when applied to a single lake 

will be amplified exponentially if broadened to groups of lakes, with the attendant 

issues of assigning and apportioning reduction becoming even more intractable. The 

protectiveness of the upstream nutrient criteria should be approached with more rigor 

with respect to lakes, with individual modeling efforts per lake and strict determination 

of the terms in the model, including sources, atmospheric deposition and processing.
Furthermore, it is probable that the suggestion to address lake regions by averaging of 

terms across groups of lakes would generate additional uncertainty to the point where 

models would break down. An understanding of lake mean depth and morphoedaphic 

factors is necessary to completely assess the fate of P entering a lacustrine system. 

Biogeochemical fate and transformation of nutrients, in this case P, will be dependent 

on the nature of the soils and sediments, presence of groundwater seeps and nutrient 

inputs, presence of phosphatic rock, fluctuations in lake depth, and biological variables 

such as whether or not benthic vegetation is present, the presence and types of 

phytoplankton communities, predation and trophic interactions within the system, types 

of fauna present. 

P dynamics will also be dependent on status of other nutrients - N dynamics and 

cycling, N limitation of primary production, nitrification- denitrification coupling 

(Jenkins and Kemp 1994), and C limitation of primary production. In short, simple 

models will work well as a primary screening tool as applied to individual lakes with 

well-constrained datasets and boundary conditions but there is a large uncertainty 

associated with demanding too much predictive capability from them, especially when 

used to “batch process” the information for groups of lakes. 
51

Additional Comments/References

Reviewer 1 Preface

It is obvious that individual scientists have spent several years creating this document. 

This is truly a large, technical and complicated document, especially with all of the 

appendices, to review in a short two-week time. I could spend several months following 

lines of analyses and testing them with data I have available or finding other available 

data to test them. With that said, I will give my best general and specific comments on 

this document with the caveat that I could do a much better job with much more time. 

Additionally, in the future of such endeavors, giving reviewers much more time and 

even chances to question the original authors would lead to a much stronger final 

document.

Reviewer 2 My Peer Review Charge has no "Specific Question 1". "Specific Charge Questions" 

begin with 2. (Chapter 3). 

In my document Question 1 is a "General Charge Question" with three general 

considerations (i.e. strengths and weaknesses, validity of lines of evidence, additional 

technical considerations for deriving criteria) that I took into consideration throughout 

the document in reviewing the individual chapters. So, the general charges are 

addressed throughout the review, of course depending upon the contents of the 

individual chapters.

Overall, I am pleased that Florida DEP has spent a lot of time and resources attempting 

to obtain nutrient criteria. I am supportive of the majority of the techniques utilized 

within the document. There are a few approaches I took issue with as noted within. I 

have also supplied some alternatives (some which can be used in parallel) that DEP 

may wish to try (I have supplied references) to provide greater scientific validity to their 

efforts in this very important process.

Reviewer 3

Reviewer 4

Reviewer 5 Conclusions and overall recommendations

This effort represents a good foundation for the development of nutrient criteria for 

inland waters in the State of Florida. However, overall, the document is a mixed result 

due to several methodologies in the process of being developed; lack of statewide 

applicability and the most effective current methodology for streams the SCI as a good 

functional baseline from which to start. The Dose-Response analyses proved 

unsatisfactory yet should, with additional research and information development, hold 

promise. Methods to determine whether the upstream criteria are protective of 

downstream waters are insufficiently evaluated in this document. The SPARROW 
52

model should be applied cautiously and only to appropriate systems in assessing 

downstream effects, namely those with well-defined channel flows, and well- especially 

to receiving reaches and coastal waters. The Nutrient Distributional Approach 

represents a good backstop where data are insufficient to develop specific numeric 

criteria. 

What the document mostly lacks is an overall orientation and strategy, a set of clear 

recommendations, and an implementation plan for bringing these various approaches to 

bear. A determination of the boundaries of analysis, of what protocol takes precedence, 

when each would be applied, where each is applicable, how data and results are to be 

synthesized to arrive at criteria is wanting. Recognizing that this is a work in progress, 

there is the expectation that a coherent strategy for combining the information in these 

individual chapters will be developed. It is expected that with additional input and 

review, and development of the document and well-rounded approach, such a strategy 

for implementation will be forthcoming.

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