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.

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
back-projection 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.

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.

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.

Chapter 14. Please comment on the downstream protection approaches.

Does the modeling approach provide a sound, scientific basis for
determining numeric nutrient loadings from upstream waters to estuaries?

Could these approaches be used to determine nutrient loadings for other
waterbody types (i.e., lakes)?

Given the available information, do these approaches account for spatial
variability, distance from downstream water, and estimated assimilation?

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.

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
physical-chemical 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
sheet:

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, 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.

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 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.

Literature Cited

Greening, H. and A. Janicki. 2006.  Toward reversal of eutrophic
conditions in a subtropical estuary: water quality and seagrass response
to nitrogen loading reduction in Tampa Bay, FL USA.  Environ. Management
38:163-178.

Madden, C. J., R. Smith, E. Dettmann, N. Detenbeck, J. Kurtz, J.
Latimer, J. Lehrter, W. Nelson, S. Bricker.  2008.  A typology of
estuaries supporting the development of a national nutrient criteria
framework for estuarine systems.  USEPA report of the National Nutrient
Criteria Development Workgroup.  In EPA review.

Odum, H. T. 2007. Environment, Power and Society for the 21st Century:
The hierarchy of energy. 2nd Edition. Columbia University Press. 426 pp.

Prygiel, J. 1994. Comparaison de six indices diatomiques et et deux
indices invertebres pour l’estimation de la qualite de l’eau de la
riviere Senese (France). Ecologia Mediterranea, 20(1/2):121-133.

Soininen, J. and K. Kononen. 2004. Comparative Study of monitoring
South-Finnish rivers and streams using macroinvertebrates and benthic
diatom community structure.  Aquatic Ecology. 38:63-75.

Ulanowicz, R. and B. Hannon. 1987. Life and the production of Entropy.
Proc. Royal Soc. London. 232:181-192.

 Environmental Management (2006) 37:209-229

   HYPERLINK
"http://www.twca.org/downloads/report/report_no_appendix.pdf"
http://www.twca.org/downloads/report/report_no_appendix.pdf ; see
Conclusions.

 SPARROW fact sheet –   HYPERLINK "http://pubs.usgs.gov/fs/2009/3019/"
\t "_blank"  http://pubs.usgs.gov/fs/2009/3019/

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[Federal Register Volume 85, Number 110 (Monday, June 8, 2020)]
[Notices]
[Pages 34791-34793]
[FR Doc No: 2020-12273]

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SECURITIES AND EXCHANGE COMMISSION

[Release No. 34-88989; File No. SR-OCC-2020-004]

Self-Regulatory Organizations; The Options Clearing Corporation;
Order Approving Proposed Rule Change To Modify the Sequence for
Processing Options Transactions

June 2, 2020.

I. Introduction

    On April 6, 2020, the Options Clearing Corporation (``OCC'') filed
with the Securities and Exchange Commission (``Commission'') the
proposed rule change SR-OCC-2020-004 (``Proposed Rule Change'')
pursuant to Section 19(b) of the Securities Exchange Act of 1934
(``Exchange Act'') \1\ and Rule 19b-4 \2\ thereunder to describe a
change to the sequence in which options transactions are processed.\3\
The Proposed Rule Change was published for public comment in the
Federal Register on April 21, 2020.\4\ The Commission has received no
comments regarding the Proposed Rule Change. This order approves the
Proposed Rule Change.
---------------------------------------------------------------------------

    \1\ 15 U.S.C. 78s(b)(1).
    \2\ 17 CFR 240.19b-4.
    \3\ See Notice of Filing infra note 4, 85 FR at 22197.
    \4\ Securities Exchange Act Release No. 88654 (Apr. 15, 2020),
85 FR 22197 (Apr. 21, 2020) (File No. SR-OCC-2020-004) (``Notice of
Filing'').
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II. Background

    Currently, OCC processes all securities and commodity futures
options transactions in the following sequence: \5\ (1) Opening Buys;
(2) Opening Sells; (3) Closing Buys; (4) Exercises; (5) Closing Sells;
and (6) Assignments. As discussed below, OCC's Clearing Members
indicated that the current processing sequence could raise issues
related to compliance with exchange rules requiring that firms exercise
only ``outstanding'' net long positions.\6\ OCC proposes to change the
order in which it processes such transactions by moving ``Closing
Sells'' ahead of ``Exercises,'' which would result in the following
sequence: (1) Opening Buys; (2) Opening Sells; (3) Closing Buys; (4)
Closing Sells; (5) Exercises; and (6) Assignments. The current
processing sequence was designed to protect Clearing Members against
certain errors; however, OCC believes that operational changes as well
as increased Clearing Member proficiency in trade processing warrants a
change to the processing sequence to reflect the tools OCC offers its
Clearing Members as well as increased Clearing Member proficiency.\7\
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    \5\ A ``commodity future'' is defined in Article I(c)(24) of By-
Laws as ``a futures contract within the exclusive jurisdiction of
the Commodity Futures Trading Commission that is traded on, through
the facilities of, or subject to the rules of a futures market.''
Options on securities futures currently do not exist. See https://www.theocc.com/components/docs/legal/rules_and_bylaws/occ_bylaws.pdf.
    \6\ See Notice of Filing, 85 FR at 22198.
    \7\ See id.
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Current Processing Sequence

    The current processing sequence was designed to protect against the
risk that an erroneously coded transaction could prevent a Clearing
Member from appropriately exercising a long position. The vast majority
of customer securities options positions are maintained on a gross
basis at OCC. A miscoded sell transaction of one customer could close
out a long position in the same series of another customer, which would
prevent the latter from exercising the long position. Processing
closing sell transactions after exercises avoids the prevention of
exercises by erroneously coded sell transactions.
    Market-Maker and Other Net Accounts: The current processing
sequence applies to firm, customer, and Market-Maker accounts. The
processing sequence for Market-Maker accounts, however, includes one
additional step because Market-Maker accounts are held on a net
basis.\8\ At the end of each trading day, OCC nets offsetting positions
in the same options series in each Market-Maker account. OCC nets
offsetting positions before processing the exercise of long
positions.\9\ From a systems perspective, this means that the current
processing sequence for Market-Maker accounts is as follows: (1)
Opening Buys; (2) Opening Sells; (3) Closing Buys; (4) Position
Netting; (5)

Exercises; (6) Closing Sells; and (7) Assignments.
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    \8\ As noted above, the vast majority of customer accounts are
maintained on a gross basis. A few Clearing Members have established
the functionality to designate sub-accounts within their omnibus
customer and firm accounts held at OCC. These sub-accounts are
established for a specific customer or joint back office account and
the account holders can elect to hold these accounts on a net basis
to assist with the position reconciliation process. When the account
holders elect to hold the accounts in this manner, they are subject
to the same netting process to which Market-Maker accounts are
subject. See Interpretation and Policy .04 to Article VI, Section 3
of OCC's By-Laws available at https://www.theocc.com/components/docs/legal/rules_and_bylaws/occ_bylaws.pdf.
    \9\ OCC represented that netting before exercise is designed to
address operational risk concerns related to the processing of
dividend play transactions by Market-Makers. See Notice of Filing,
85 FR at 22198. A dividend play is a trading strategy that
historically was primarily engaged in by Market-Makers and involved
buying and selling an equal number of call options right before a
dividend date on the underlying equity and exercising the long call
options with the goal of capturing the dividend on the underlying
equity.
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    Clearing Members have visibility into the trade information that
OCC receives, which is now available in near real-time.\10\ OCC
provides for visibility through a screen in ENCORE and an On Demand
Position file provided to Clearing Members, both of which allow
Clearing Members to evaluate the availability of long positions to
cover exercises notices. OCC also permits Clearing Members to adjust
positions for the purpose of correcting the miscoding errors as
described above. Specifically, Clearing Members may correct such errors
by entering a position adjustment in ENCORE prior to exercises being
processed.\11\
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    \10\ When the current processing sequence was adopted, OCC
received trades in a batch file from each exchange at the end of the
trading day. OCC would then process trades on a batch basis prior to
the opening of trading the following business day. In contrast, OCC
now receives trade information on a near real-time basis. The
functionality to receive trades on a near real-time basis has been
available through OCC's ENCORE clearing system since 2002. See id.
    \11\ OCC allows Clearing Members to make such position
adjustment only for non-critical aspects of a trade. For example, a
Clearing Member would not be permitted to change the price or symbol
of a trade.
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    Additionally, OCC's Clearing Members have indicated that the
current processing sequence could raise issues related to compliance
with exchange rules requiring that firms exercise only ``outstanding''
net long positions.\12\ Clearing Members have indicated that a customer
position could be subject to conflicting closing sale and exercise
instructions. Under OCC's current processing sequence, such
instructions could lead to a position that was intended to be closed
out being exercised instead.
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    \12\ See Notice of Filing, 85 FR at 22198. The rules of one
exchange provide that, ``an outstanding options contract may be
exercised during the time period specified in the Rules of [OCC] by
the tender to [OCC] of an exercise notice in accordance with the
Rules of [OCC].'' NYSE Arca Rule 6.24-O(a). See also FINRA Rule 2360
(b)(23) and NYSE American Options Rule 980(a). An ``outstanding''
contract is ``an options contract which has been issued by [OCC] and
has neither been the subject of a closing writing transaction nor
has reached its expiration date.'' NYSE Arca Rule 6.1-O(b)(26). See
also FINRA Rule 2360 (a)(26).
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Proposed Processing Sequence

    OCC proposes to modify the processing sequence for all securities
and futures options transactions for all account types to process all
closing sell transactions prior to all exercise transactions.\13\ OCC
proposes to change the order in which it processes such transactions by
moving ``Closing Sells'' ahead of ``Exercises,'' which would result in
the following sequence: (1) Opening Buys; (2) Opening Sells; (3)
Closing Buys; (4) Closing Sells; (5) Exercises; and (6) Assignments.
For Market-Maker and other accounts held on a net basis, OCC proposes
to net offsetting positions after closing sells but before exercises.
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    \13\ OCC currently uses the same processing sequence for options
on commodity futures; however, OCC understands that futures
customers and Clearing Members are indifferent to the processing
sequence for futures transactions. See Notice of Filing, 85 FR at
22199. Futures firms submit very few trades marked as closing
transactions, and as a result, submit nightly adjustments to correct
their open interest, which, in turn reduces the potential of an
exercise error since the firms verify their long positions on a
daily basis. Id.
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    OCC discussed the current processing sequence and the Proposed Rule
Change with its Clearing Members at the OCC Roundtable, an OCC-
sponsored advisory group comprised of representatives from OCC's
participant.\14\ Based upon those discussions, OCC believes that its
current processing sequence for options transactions no longer needs to
be designed to protect Clearing Members from errors in customers'
accounts that would result in closing out a position that was intended
to be exercised.\15\ Further, OCC represented that Clearing Members
believe the Proposed Rule Change would help them comply with certain
Exchange rules that require customers to exercise only ``outstanding''
net long positions.\16\ As noted, Clearing Members now have visibility
into near real-time trade data and the ability to adjust positions
prior to exercise to correct errors in the coding of non-critical
aspects of a trade, which was not available when the current processing
sequence was established.
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    \14\ The OCC Roundtable is made up of Exchanges, a cross-section
of OCC Clearing Members, and OCC staff who hold regular monthly
operations update calls.
    \15\ See Notice of Filing, 85 FR at 22199.
    \16\ See Notice of Filing, 85 FR at 22199. By processing all
buys and sells prior to exercises, Clearing Members believe that the
proposed processing sequence would help address situations in which
a customer position is subject to conflicting closing sale and
exercise instructions, which could lead to a position being
exercised that was intended to be closed out under the current
processing sequence. Id.
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III. Discussion and Commission Findings

    Section 19(b)(2)(C) of the Exchange Act directs the Commission to
approve a proposed rule change of a self-regulatory organization if it
finds that such proposed rule change is consistent with the
requirements of the Exchange Act and the rules and regulations
thereunder applicable to such organization.\17\ After carefully
considering the Proposed Rule Change, the Commission finds that the
proposal is consistent with the requirements of the Exchange Act and
the rules and regulations thereunder applicable to OCC. More
specifically, the Commission finds that the proposal is consistent with
Section 17A(b)(3)(F) of the Exchange Act.\18\
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    \17\ 15 U.S.C. 78s(b)(2)(C).
    \18\ 15 U.S.C. 78q-1(b)(3)(F).
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A. Consistency With Section 17A(b)(3)(F) of the Exchange Act

    Section 17A(b)(3)(F) of the Exchange Act requires, among other
things, that the rules of a clearing agency be designed to promote the
prompt and accurate clearance and settlement of securities
transactions.\19\ Based on its review of the record, the Commission
believes that modifying OCC's processing sequence for all securities
and futures options transactions as described above is consistent with
the promotion of prompt and accurate clearance and settlement of
securities transactions for the reasons described below.
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    \19\ 15 U.S.C. 78q-1(b)(3)(F).
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    Clearing Members have raised concerns regarding their ability to
comply with exchange rules given OCC's current processing sequence.
Specifically, exchanges require market participants to exercise only
outstanding net long positions. Processing exercises after buys and
sells could address situations in which a customer position is subject
to conflicting closing sale and exercise instructions, which could lead
to a position being exercised that was intended to be closed out.
    The current processing sequence was designed to ensure that a
market participant would be able to exercise its long positions even if
a trade has been miscoded. The need for such protections, however,
arose at a time when trades were received and processed in a batch at
the end of the day. Visibility into the near real-time trade
information provided to OCC allows Clearing Members to better
understand the long positions available for exercise and to correct
coding errors through position adjustments.
    Further, as noted above, OCC's determination to propose a change to
its current processing sequence was supported by discussions with
Clearing Members at the OCC Roundtable and during regular monthly
operations update calls with Clearing Members and exchanges. Given the
position adjustment tools available to Clearing Members to address
miscoded transactions, the Commission believes

that revising OCC's processing sequence to facilitate compliance with
exchange rules would promote the prompt and accurate clearance and
settlement of securities transactions. The Commission believes,
therefore, that the proposed processing sequence is consistent with the
requirements of Section 17A(b)(3)(F) of the Exchange Act.\20\
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    \20\ 15 U.S.C. 78q-1(b)(3)(D).
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IV. Conclusion

    On the basis of the foregoing, the Commission finds that the
Proposed Rule Change is consistent with the requirements of the
Exchange Act, and in particular, the requirements of Section 17A of the
Exchange Act \21\ and the rules and regulations thereunder.
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    \21\ In approving this Proposed Rule Change, the Commission has
considered the proposed rules' impact on efficiency, competition,
and capital formation. See 15 U.S.C. 78c(f).
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    It is therefore ordered, pursuant to Section 19(b)(2) of the
Exchange Act,\22\ that the Proposed Rule Change (SR-OCC-2020-004) be,
and hereby is, approved.
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    \22\ 15 U.S.C. 78s(b)(2).
    \23\ 17 CFR 200.30-3(a)(12).

    For the Commission, by the Division of Trading and Markets,
pursuant to delegated authority.\23\
J. Matthew DeLesDernier,
Assistant Secretary.
[FR Doc. 2020-12273 Filed 6-5-20; 8:45 am]
 BILLING CODE 8011-01-P