Assessment of fisheries habitat tasks 1, 2, 3, and 4 : final report for grant period 4/1/89 thru [sic] 12/31/89

[From the U.S. Government Printing Office, www.gpo.gov]

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ASSESSMENT OF FISHERIES HABITAT

FINAL REPORT
for

TASKS 1, 29 3, and 4

DECEMBER, 1989

Funds for this project were provided by the Department of
Environmental Regulation, Office of Coastal Management using
funds made available through the National oceanic and
Atmospheric Administration under the Coastal Zone Management
Act of 1972, as amended.

ASSESSMENT OF FISHERIES HABITAT
TASKS 1, 2, 3, and 4

FINAL REPORT

for

GRANT PERIOD 4/l/89 thru 12/30/89

Kenneth.D.@-Haddad, Gail A. McGarry:, Richard E.-,Matheson, Jr.,
Walter J. Conely, Paul Carlson, Michael Durako,
Jamie L. Serino, and Timothy MacDonald

December, 1989

Department ofNatural Resources
Q) Division of Marine Resources
Florida Marine Research Institute

Zlz

Funds for this project were provided by the Department of
Environmental Regulation, Office of Coastal Management using
funds made available through the National Oceanic and
Atmospheric Administration under the Coastal Zone Management
Act of 1972, as amended.

EXECUTIVE SUMMARY

This report contains Tasks I-IV of the Coastal Zone Management program
at the Florida Marine Research Institute. Task I work products are
centered around the development of the Marine Resource Geographic
Information Systems (MRGIS) and the dissemination of both digital and hard
copy data into the user community. A focus of this Task has been the
development of a detailed GIS database for the Little Manatee River
Watershed. Data layers are in various stages of completion and analyses
have been conducted. Task II work products are based on the goal to link
and quantify the relationship between fisheries species to estuarine
habitats. A major effort, linked to Task I, to study the distribution of
fishes in the Little Manatee River, relative to salinity, habitat and land-
use, has been continued in.this Task. Sampling has been on a two week
basis and preliminary analyses are providing information on the
distrib@tion of fish relative to salinity. Task III work products complete
a project relating potential environmental stresses (i.e., hypoxia, light)
to physiological correlates of Thalassia testudinum. A stress indicator
(ethanol) has been identified for hypoxia events and sulfide toxicity and
recovery have been observed. An assessment of carbon (food) uptake in
Thalassia has also been conducted, demonstrating that this plant can use
multiple carbon sources. This suggests that foodweb assessments will be
difficult when using carbon isotope signatures. This work complements
previous CZM work that identified environmental stress and los.s of seagrass
habitat as a major problem in long term resource management. These three
tasks now represent a major thrust of the Florida Marine Research Institute
to develop techniques and provide information to more effectively manage
our marine resources.

Since sound information on habitat quantity, location, and importance
to Florida's fisheries and non-game resources has never been addressed with
a methodical, holistic approach, this type of information has not been
available to the researcher or resource manager. Although much of what we
are doing will require long term database development, the preliminary
information has been and continues to be requested by agencies, planners,
and researchers. We expect this program to continue to grow and the
knowledge gained to be of critical importance'to the future of our coastal
natural resources.

Task IV is providing the vehicle to get our information and project
results to the general public. The Seagrass Task Force Report is in the
final editing stage and is being prepared for publication and will be an
important document for those concerned with management of this resource.
The most effective approach to resource management is by an informed public
guiding the governmental processes. By providing factual non-technical
information to the public, they can make better decisions when facing tough
issues regarding our marine environment. Through brochures, presentations
and other forms of media, we are accomplishing these goals and the results
can only be positive for Florida's future.

Task 1: MARINE RESOURCE GEOGRAPHIC INFORMATION SYSTEM (MRGIS)

The primary objectives of this task were to continue the development of the

Little Manatee River (LMR) watershed CIS data base, distribute MRGIS digital,

tabular and hardcopy habitat data, improve our capability for hardcopy map

production, expand MRGIS interfaces to tabul ar data, and field test the multi-

spectral video imaging system. Also, we added data layers on an estuarine basis

for Tampa Bay and Apalachicola Bay.

MRGIS Development for the Little Manatee River Watershed

The development of the LMR CIS database has progressed with major focus on

completion of data layers important to water quality analyses. These data will

be analyzed for correlations between.various landcover, land-use, and soil

components and various water quality and fisheries data currently being

collected.

CIS DATABASE DEVELOPMENT

The,development of a GIS database is complex, dynamic and requires data

acquisition from many sources. Since the future analyses to be conducted with

the CIS data layers will be quantitative, it is imperative that cartographic

integrity be maintained. This constraint has inhibited the data entry but the

results of maintaining this approach will have long-term benefits.

Figure 1 depicts some of the layers of data being implemented on the Marine

Resource Geographic Information System (MRGIS). These layers represent data we

have accessed, identified as available in map form, or can be generated

from aerial photography or satellite imagery-

the base map data layer to which all other layers are referenced) consists

of an April, 1988 SPOT satellite panchromatic image geo-referenced to 7.5 minute

U.S.G.S. quadrangles in a Universal Transverse Mercator (UTM) projection. The

MRGIS data layers are currently in raster format although we can accept vector

data or convert raster data to vector for various analyses or for data

distribution.

Data Layers

Numerous problems have been encountered generating appropriate overlays.

Some data sources, problems, and solutions are depicted in Table 1. It should

be understood that many of these databases were not created with GIS entry in

mind and do not have the cartographic integrity of a photogrammetrically

developed map. Problems have been compounded by the fact that the rectified

SPOT data were more spatially resolved that National Map Accuracy Standards for

1:24,000 maps, making geo-referencing difficult and creating overlay problems at

common borders (eg., shorelines defined by soils vs. land use vs. flood zones).

Furthermore, many data are in scales smaller than 1:24,000, compounding overlay

difficulties. This does not present a problem if the limitations of the

analyses are understood and not misused. For example, the future land-use data,

if originally developed by the county at 1:100,000 scale, cannot be applied to

individual zoning issues at a parcel level but can be used to project land-use

changes over larger portions of the watershed.

Complete watershed coverage has been built for flood z.ones, future land

use, and general land cover 1988. The estuarine portion of the watershed has.

land cover 1950 and land cover 1982 completed. The status and specific problems

with several remaining data layers are as follows:

1. Soil: Soil data have been recompiled, by the Soil Conservation

Service, and scan digitized for the LHR portion of Hillsborough County. Those

data are in the MRGIS and being corrected and quality checked. The data are

currently grouped by U.S.G.S. quad. Joining the quads (edge matching) to

provide a continuous watershed coverage has proven difficult due to the

complexity of soils polygons. Soil quads for the Manatee County portion of the

watershed have been received and joined to form a continuous coverage. Based on

preliminary observations, it appear's that'merging the soils data from Manatee

County with Hillsborough County will be challenging. Problems are occurring in

the edge matching process and disparate polygon labelling.

2. Elevation: The Southwest Florida Water Management District is

providing this particular data layer. The data have been generated and we are

currently developing the methods and formats for data transfer.

3. Drainage: This data layer is the most tedious effort for compilation.

NRAP photos (1:50,000 scale) have been enlarged to 1:24,000 scale and detailed

drainage line work is being interpreted. This type of interpretation has not

been done for many areas in the U.S., particularly at the resolution being

attempted for this program. For example, individual drainage ditches within

agricultural fields are being identified, along with their connectivity to the

tributaries of the watershed. This will allow better analysis of sources of

waterborne constituents and will allow network analyses.

4. Land cover/Land use: A land cover layer has been developed for the

entire watershed. Thi s was developed by the Florida Game and Freshwater Fish

Commission in cooperation with the FMRI. These data are for 1987 (from Landsat

Thematic Mapper) and provide a first look at land cover from a habitat and

runoff potential. A 1988 SPOT image is being used to complete adetailed land

use coverage. The land use data are- being compiledat a 0.1 hectare resolution.

5. Watershed and subbasins: This data layer has been digitized from maps

provided from SWFWMD (Figure 2). We,bave judged the boundaries to be

inaccurate in many areas because the basins were originally delineated in the

1970s. Substantial changes have occurred in the drainage characteristics of the

watershed which need to be readdressed by the U.S.G.S.

Tabular attribute data

Tabular data, such as soils definitions,.bald eagle nesting locations,

LMR station locations and all of the associated water quality or fish

distribution data, permitted effluent discharges, and other digital data that

represent a singular geographic location are also required for analyses. The

biggest problem in working with these data are positional accuracies and data

exchange formats.

Quality Control and Assessment

Data quality control and assessment are extremely important in the

generation of the GIS data layers and their tabular attributes. The two

components of concern are cartographic integrity and data accuracy (i.e., is it

where it should be and is it being called the right thing?). When accessing

data bases outside the control of FMRI, these issues are often difficult to

assess prior to data entry. Where we have control, such as in the soils

digitization, we have taken extreme measures to insure cartographic integrity

but we can only accept the Soil Conservation Service s ability to properly

identify soils. In most cases accuracy assessment of the information has not

been completed by the parent organization. For data being developed at FMRI,

such as land use, statistical analyses of classification errors are being

conducted.

Data analyses

Numerous test analyses have been conducted on portions of the watershed

with many of the data layers. Only the results of an analyses specific to water

quality data will be presented, The specific, analyses addressed the issue of

what land covers comprise the drainage area (subwatersheds) of each of seven

water quality stations. This type of information, in conjunction with other

data layer information, can be used to assess the contribution of runoff to

water quality findings.

Table 2 summarizes the general coverage, in hectares, for each of the 7

water quality stations depicted in Figure 2. It should be noted that

subwatersheds are defined by station locations while subbasins are defined by

U.S.G.S. criteria. These data do not reflect subbasin analyses.

The entire watershed comprises 57,364 hectares (573.64 sq. kilometers).

Upland plant communities comprise 13% of the watershed and consist of pinelands

to hardwood forests. Wetland plant communities constitute 9% of the watershed

ranging from saltmarsh to hardwood swamp. Water bodies comprise.3% of the

watershed, not including the river and its tributaries.

Agriculture/pasture/barren constitute 75% of the watershed. This category

is very general and includes urban areas. Urban areas represent a small portion

of this percentage and will be well defined in the detailed land use data layer.

In Table 2 this category is representative for the subwatetsheds except at ST7

which is the urbanized Sun City Center area.

Within each of the subwatersheds, the dominant land cover is

agriculture/pasture/barren with*a high of 90% at ST2 and a low of 63% at ST4.

Most of the areas.are in agriculture with a small percentage of pasture. At ST1

the coverage is dominated by pasture rather that agriculture and at ST7 the

coverage is dominated by barren (or urban in this case).

Although these data have significance in their current form, the full power

of the data will be realized as the investigators begin to associate their

finding with the information in each data layer or by association of multiple

data layers.

Many analyses which have been conducted with the various data layers have

not been presented in this final report due to the pictorial nature of the

results. Multiple layered analyses have been successfully tested and

preliminary results are being reviewed by local governmental planning agencies

through pictorial presentations of the data development process and analyses

results. A manuscript titled Basisn-Wide Management summarizes some of the

analysis results (Task 1, Attachment A). In addition, a manuscript is currently

in preparation which describes the difficulties and solutions for digitizing

soils data in a cartograghically accurate base and summarizes analyses using

soils data. The focus of the soils analyses are on results applicable to

enhancing watershed management.

Future Work

The development of the LMR MRGIS data base is on& of the most detailed and

extensive for any area in the U.S.. This is'necessary due to the resolution of

the water quality and biological data being collected for the watershed. This

also means that the data base development must be of high accuracy if the

process is to be quantifiable. The unification of all of the watershed data

will result in the ability to quantitatively analyze the relationship between

upland development, wetland functions, water quality, environment, and

ultimately the effects of changes of these parameters on the local fishery

production. This has never been accomplished at the resolution being applied in

this program. The future work includes the addition of data layers not yet

available at the needed resolution and replacement of data layers,which are

being used until better 'resolution data can be digitized. Substantial effort

must be placed on the integration and analyses of the disparate forms of data

for the watershed. In addition, the process and results need to be

systematically presented to state and local government in order to facilitate a

better understanding of the implications of their decisions on the LMR watershed.

This can only be accomplished by presentation of accurate and usable information.

The final accomplishment will be the transfer of the technology to management

agencies and implementation of applicable portions of the LMR GIS data

development and analyses approach to other regions of the State.

MRGIS Data Distribution

Numerous requests for data and data analyses continue as part of the CZM

MRGIS operations. Table 3 list some of the requesters for maps, data summaries,

and presentations between April and December 1990. It can take hours or weeks

to fulfill these requests depending on the area and types of data to be created

or extracted from the MRGIS. The requests can range, for example, from the

simple reproduction of an existing map of the Big Bend area to high level

mapping of the Lake Jackson Aquatic Preserve and the entire watershed. Table 3

does not reflect multiple requests from the same entity nor the many "over the

phone" requests which are completed with a few minutes of work.Collectively, the

data and other related requests consume a substantial portion of MRGIS

operations. We continue to believe that this effort contributes substantially

to improved natural resource decisions at federal, state, regional, and local

level s. To improve data distribution capabilities an 8 pen, 38 inch bed, Calcomp

plotter and a 300 dpi, color, wax-thermal printer have been added to the MRGIS.

The plotter allows vector data to be.,printed at large scale from ARC/INFO. The

wax-thermal printer allows color printing of the raster data at high resolution

and with greater clarity than the inkjet printer. The color prints in this

report are from this hardcopy device.

MRGIS APPLICATIONS

The techniques developed with the MRGIS for wetlan ds mapping and trend

analyses are currently under evaluation by the NOAA Coastwatch Program and the

federal multi-agency Habitat Loss and Modification Working Group for

implementation of a nation-wide coastal wetland monitoring effort and for

evaluation of the "no net loss" policies being planned by the various federal

agencies. The following section is a draft manuscript to be included in a USFWS

publication, which summarizes the techniques and concepts applied to the MRGIS

mapping and trend analysis efforts..

MARINE WETLAND MAPPING AND MONITORING IN FLORIDA

INTRODUCTION

The State of Florida has one of the most extensive coastlines in the United

States and climatically ranges from tropical and sub-tropical to temperate.

This has resulted in a very complex and diverse assemblage of species and

habitat which are often unique and fragile. Florida's population growth is one.

of the highest in the nation with over 80% of state inhabitants living within 16

km of the coastline. The resultant impacts on our marine and estuarine

resources, although at times obvious, have been poorly understood, rarely

quantified, and assumed to be far reaching.

ECOSYSTEM ANALYSES AND MANAGEMENT

With such a diverse richness of Florida's marine resources and a resultant

diverse group of users, management of the resources is not an easy task. This

is compounded by the rapid growth occurring in the State and its currently

unquant ifiable impact on our marine resources.

A primary goal of the Florida Department of Natural Reso urces, Marine

Research Institute is to conduct research and synthesize that research into

information which can be used to make sound resource management decisions. Most

mari ne resource management strategies and actions in Florida have been oriented

to single species. As technical data on the status and trends of our coastal

and marine resources have become available, it has become evident that this

targeted approach to management is inadequate over the long-term. Habitat has

been lost, species abundance has declined, polluted waters have reduced

shellfish harvest areas, and fisheries have been closed.

This realization has been stimulating the evolution of an ecosystem

approach to resource management. This approach is based on the fact that

without an understanding of species interactions, communities, community

interactions, and cumulative environmental impacts (natural and man-induced),

our management actions will often be reactive rather than preventive or

corrective.,

HABITAT MAPPING AND TREND ANALYSES

@A first step in building a digital ecosystem database is the determination

of the extent and location of critical habitat. In 1983 FMRI, through the NOAA

Office of Ocean and Coastal Resource Management and Department of Environmental

Regulation, initiated a program to map and monitor coastal wetlands and

submerged habitat including saltmarsh, mangroves, submerged aquatics, oyster

reefs, and unconsolidated bottom. With such an expansive coastline in Florida,

unconventional methods for the mapping effort were analyzed.

Initially, mapping techniques were evaluated to determine cost, accuracy,

and production time comparisons between digital image processing of Landsat

Thematic Mapper (TM) data and cartographic ae rial photography methods. A 69%

cost saving and 83% production time reduction was realized with TM data (Haddad

and Hoffman, 1985a)'. It was also determined that aerial photography was often

needed for photointerpretation and digitization into the resource map when

submerged habitats were being mapped (Haddad and Hoffman, 1985b). Accuracies of

classification for both aerial photographs and TM data were >90% for marine

wetlands. Based on these results FMRI began a systematic mapping of Florida's

estuarine and marine wetlands, excluding the Everglades National Park and

Biscayne Bay. That effort began in 1984 and was completed with updates in 1986

and required approximately 2 man.years of effort (1 man year = 2080 hrs).

TREND ANALYSES

Habitat trend analyses have also been completed for selected areas of the

State from the 1940's to the present. A major conclusion from the trend

analyses have been that submerged aquatics have often undergone the greatest

loss and this loss is no longer due to mechanicallimpacts but rather changes in

water quality. This is supported by the fact that losses often occur in deeper

waters within the estuaries, suggesting insufficient light penetration as a

causative factor. Loss of marsh and mangrove has substantially decreased in

Florida and where sufficient protective measures have been established,

increases in aerial extent have been observed.

MAPPING TECHNIQUES

A decision on a base map was required early in the program. The base map

is the digital map to which all data are referenced. As is common for many

areas, none were not available in digital form on a statewide basis and the cost

or digitization was prohibitive. It was determined that the only reasonable

approach was to make the TM data the base map and any additional map layers

(i.e., seagrass, oysters) would be digitally rectified to that base.

GEOGRAPHIC REFERENCING

TM data consist of I spectral layers of information for each 1/4 acre (30m

x 30m) on the ground, and a thermal band with 4 acre resolution. Each spectral

band is rectified to 7.5 minute USGS Quadrangles in a UTM projection using a

bilinear interpolation technique. Welch et al, 1985 have determined that this

type of process can achieve accuracy standards for 1:50,000 scale maps and

approach standards for 1:24,000 scale maps. Rectification of the individual

spectral bands, rather than the finished product, is standard because of our

need to continually return to the raw data for additional analyses.

IMAGE ANALYSES

We have not developed a rigid protocol for statistical analysis of the

satellite imagery data, but workable techniques have been standardized.

Numerous types,of statistics have been tested for their ability to classify

marine and estuarine wetlands and for computer processing times. Standard

classifiers such as the maximum likelihood, which can use either supervised or

unsupervised approaches to generate statistical clusters, have been found to be

processing intensive and cumbersome in a production operation. This observation

is based on our specific needs, relative to coastal wetlands, and does not

consider the use of this approach for general mapping needs. With this type of

algorithm, and most algorithms in use, the higher the spatial resolution the

more difficult it is to resolve confusion within and among classes. At some

point human intervention with a photointerpretive-like process is necessary.

our approach has been to use a very rapid parallel-piped type of classifier

to initially process the date into 256 classes. The classifier is run on the

green, red, and near-infrared, and the red, near-infrared, and mid-infrared TM

spectral bands, respectively, *to generate two statistical images. The first

image is pictorially similar to a color-infrared photograph and can be image

interpreted by identifying those clusters which represent the wetland categories

of interest. It is often advantageous to use the second image because of its

accentuation on the infrared bands. In particular, we have found that the mid-

infrared band enhances our ability to differentiate wetlands. In many cases, we

use both images to selectively differentiate categories of interest with the

results being a third image comprised of the best clusters from each image.

Although this approach is rapid and effective it still does not meet

accuracy standards expected for wetlands mapping when compared to interpretation

of photographs at similar spatial resolutions. The associative and subjective

analyses performed by a photointerpreter are not yet reproducible statistically.

On the other hand, use of the TM mid-in.frared band can have advantages in

certain analyses where identification of different-levels of moisture content

enhance the ability to differentiate wetland types beyond those observable in an

infrared photograph.

Once the images are clustered as best can be statistically accomplished,

NHAP aerial photographs, existing National Wetlands Inventory (NWI) maps, ground

truthing, and a myriad of other data sources are used to identify or confirm

clusters which are not pure to a given wetland type. For example, some of the

clusters representing mangroves may be confused with a wet orange grove or a

freshwater wetland resulting in a.70% identification accuracy. The remote

sensing literature has many examples of this type of confusion and reports the

statistical inaccuracies of this type of analysis. This reflects an academic

approach to image analyses and not a production approach. We routinely "fix"

the confused clusters by using simple digital manipulations based on the

interpreter's assessment of the data. Orange groves and freshwater wetlands are

reclassed into appropriate categories often increasing identification accuracies

for mangroves >95%.

This flexible and rapid approach to wetlands mapping results in a high

accuracy product but only for wetlands. We routinely produce a final map

product which merges the wetland types with the original color infrared-like

image. By providing this pictorial image for the background data, the user is

able to orient to the image and eliminate the need for a summary presentation of

the data not classified as wetlands.

SEAGRASSES

Seagrass mapping presents special problems for satellite image analyses.

Landsat only collects an image over a given area once every 16 days. This means

that conditions conducive to mapping must all coincide on that given day. If

the water is clear and clouds do not obscure the area, there is good potential

for using imagery for seagrass mapping. We have not found any statistical

analyses which ade quately define seagrasses, although we have had success in

limited cases. Variations in water clarity, water depth, and sediment type

preclude the use of standard spectral analyses. The image must be manually

"photointerpreted" in either the blue, green, or red spectral bands. Because of

these obstacles we commonly use aerial photography, either existing or

contractually flown, to map seagrasses. The photographs are photointerpreted,

rectified to the Landsat base map, and the seagrass coverage is conventionally

digitized as wetland types into the database.

HABITAT TREND ANALYSES TECHNIQUES

Trend analyses for coastal wetlands can be conducted with numerous

techniques. The creation of the data for actual analyses must be with caution

because, in most cases, it is difficult to separate errors in classification

from actual habitat changes. Trend analyses cannot be conducted on data that

use different classification systems that have not been normalized. In fact, it

is very difficult to compare data that have been interpreted by different

investigators using the same classification system if tedious interpretive

calibrations are not conducted. If done properly, habitat trend analyses can

provide valuable insights on impacts of habitat management regulations and

changes in resources which utilize those habitats.

HISTORICAL DATA

Historical analyses have been accomplished for a number of areas in Florida

by photointerpreting archived photographs from the 1930s to 1970s. We rectify

the interpreted data to the Landsat base map and table digitize them into a

separate data layer. When using aerial photography the interpretations often

must be transferred to a USGS quadrangle to geo-correct the data for spatial

inconsistencies prior to digitization. We can often bypass this step by using a

three point triangulation method when digitizing off the photographs. When

positional deviations are observed new points are picked and the digitization

process if continued. If the interpretation of the historical photographs is

compatible to the TM analyses then trend analyses can be conducted. We have not

attempted to compare historical Landsat MSS data to the recent TM data because

of the uncertainties introduced by spectral and spatial resolution differences.

CONTEMPORARY DATA

When building a database for trend analyses it is important to create an

accurate habitat data layer to which historical and future data will be compared.

it is our conclusion that contemporary data should be that layer. The

contemporary data can be ground truthed and corrected for errors in

classification which cannot be done for historical photographs. This also gives

the investigator a "feel" for the area and increases the potential for accurate

interpretation of the historical photos. By expending initial efforts in the

creation of the contemporary data, a considerable reduction in effort is

realized when developing the historical database and conducting future map

updates.

DATABASE UPDATES

One approach to updating the habitat database is to remap a given area for

comparison with the original maps. That process is time consuming. Since TM

data are digital we have developed a technique which takes advantage of that

attribute. When working with a focused database, such as coastal wetlands, we

process the new TM data into 256 classes as previously described. This produces

an image, rectified to the base map, which can be manipulated to update the

original map. The ori ginal data are used to mask a given habitat which is then

compared in a very rudimentary fashion to the new TM image. For example, when

updating mangroves, we would use the original coverage of mangroves to locate

those areas in the new TM image which should contain mangroves. Mangroves, in

the new image, can be expected to fall within a specific range of statistical

clusters and those clusters which fall outside that range are identi fied as

potential areas of change. These areas can then be visually assessed to the

changes. In theory, an inverse process can be used to identify areas of

mangrove growth but we have not tested this approach due to insignificant

amounts of growth in wetlands since our initial mapping effort utilizing TM

data.

PROBLEMS WITH DISPARATE DATA

Figures 3-5 depict the results of the updating process except that we have

used mangroves digitized from a 1982 NWI aerial photographic mapping effort as

the mask to a 1987 TM image in order to show both the process and, if using

disparate data sources, the problems. The observed areas of change represent

differences in final product resolution, habitat classifications, and real

changes in habitat. Figure 3 is a general map of a coastal area of Tampa Bay,

Florida.- The data have been consolidated to 3 classes and are a digital

representation of the 1982 NWI map. Figure 4 represents the statistically

clustered 1987 TM data for the area of mangroves delineated in the 1982 data.

Figure 5 shows those areas which were labelled as mangrove in 1982 but were not

classified as mangrove in 1987. Quantitatively the area was reduced from 2,952

ha of mangrove to 2,564 ha, a 13% loss. However, when investigating the changes

it becomes obvious that a large portion of that change is not real and

represents differences in interpretation techniques and classification systems.

Many of the smaller areas of change are actually uplands within the mangrove

complex. These types of features are averaged by th e photointerpreter to become

mangroves even though the photography was 1:24,000 scale. In the photointerpre-

tation and digitization process it becomes impractical and costly to try to

delineate these features at that scale. The photointerpreter makes a conscious

decision to delineate them or they are lumped into the mangrove classes; digital

processing automatically maintains their separation.

The utilization of classification systems also contributes to discrepancies

in data updating. The NWI maps are based on the Cowardin system while the State

of Florida uses a modified Anderson system tailored to state needs. In Figure

5, a 162 ha area defined by NWI as mangrove falls outside the spectral clusters

we consider mangrove. In fact, this is a salt flat which has 30% or less

mangrove and would never be classified as mangrove. To confuse the process

further, this same area was called the equivalent of a salt flat in the 1950 NWI

analyses and thus shows a misleading increase of 162 ha of mangroves within the

same classification system.

The point to be made is trend analyses must be conducted with caution and

with a full evaluation and understanding of the data being compared. In fact,

of the 388 ha change between 1982 and 1987 less than 17 ha are due to real

change (<I% change). If the original image used was TM rather than NWI then the

data updating would not have the problems that have been identified. This does

not indicate that one process is better than the other, just that they are

different.

CIASSIFICATION SYSTEMS

The importance of the classification system cannot be under estimated when

using satellite image processing for habitat delineation. This is something

which must be addressed in the initial stages of a mapping program. Since we

have been primarily mapping coastal wetlands we have chosen to tailor our

classification to Florida wetlands by name. Thus we name a saltmarsh complex a

saltmarsh and if we go to the next level of delineation we would name Juncus and

Spartina as components of that complex. Our classification, at that point,

could be cross referenced with either the NWI Cowardin system or the Anderson

system. Because we are working with raster data at 30m spatial resolution we

have categories that consist of marsh and water. These areas are often

presented as a marsh/water category which is not used in most classification

systems.

It has been our observation that the TM analyses can be better tuned to the

Anderson system and can have major discrepancies with the Cowardin system. It

is best to determine the limits of the classification systems relative to TM

processing and develop a hybrid system. If this is not done, much effort can be

spent attempting to force a classification of the data and reduce the ability to

efficiently conduct trend analyses.

CONCLUSIONS

The Florida Marine Research Institute has developed and implemented a

coastal mapping effort designed for efficient and cost effective mapping and

monitoring of Florida's geographically expansive coastal wetlands. A

combination of Landsat satellite imagery, aerial photography, ground truthing,

and ancillary map data are used to produce digital maps from a Landsat TM map

base. We have-described, in a very general presentation, the techniques and

concepts we employ in the map making and subsequent habitat trend analyses. The

success of this effort has be-en based on the flexibility built into the

standardization of the mapping process.

Many issues such as ground truthing and digital and hardcopy data

distribution have not been discussed. All require substantial planning and can

become major operational components of an effective program. We have also

evaluated SPOT satellite data for mapping efficiency and do use SPOT data when

higher resolution mapping is required., The spectral superiority (particularly

the mid-infrared bands) and the lower costs of Landsat TM data make its use more

advantageous for large geographic areas.

Although our habitat mapping effort is important, it has little long-term

meaning if the habitat is not considered as part of an ecosystem. The wetlands

are just one layer of information, out of many, that we are building in the

Marine Resource Geographic Information System. Linkage to dredge and fill

permits and other types of permits which allow us to reconstruct permitted

habitat losses which cannot be mapped is being investigated. Concurrent with

our mapping efforts we are conducting field research to quantitatively assess

species utilization and production within the different habitats * All of these

efforts will eventually provide the information necessary to implement an

ecosystem approach to coastal resource management.

REFERENCES

Haddad, K.D. and B.A. Harris. 1985a. Use of remote sensing to assess estuarine

habitats. Pp. 662-675 In O.T. Magoon, H. Converse, D. Minor, D. Clark, and L.T.

Tobin (eds.), Coastal Zone '85, Proceedings of the Fourth Symposium on Coastal

and.0cean Management, Vol. 1. New York. American Society of Civil Engineers.

1294 pp.

Haddad, K.D. and B.A. Harris. 1985b. Assessment and trends of Florida's marine

fisheries habitat: an integration of aerial photography and thematic mapper

imagery. Pp. 130-138 In S.K. Mengel and D.B. Morrison (eds.), Machine

Processing of Remotely Sensed Data. West Lafayette, In. Purdue University. 370

PP.

Welch, R. , T.R. Jordon, and M. Ehlers. 1985. Comparative evaluation of

geodetic accuracy and cartographic potential of Landsat-4 and Landsat-5 thematic

mapper image data. Photogram. Eng. and Remote Sensing 51(11):1799-1812.

Example of a MRGIS Application

Since inclusion of all the analyses conducted on the MRGIS is not feasible

in this final report an example has been selected to demonstrate a single

application. Theapplication used data being included in the MRGIS data base

for individual estuaries and was the result of afisheries application request

rather than the more common growth management application requests.

The Florida Marine Fisheries Commission is charged with developing rules

for the states fisheries management. One of the common problems in the

management and rul e making process is the lack of information. The MRGIS has

recently been presented to the Commission as a tool for providing information in

a format better suited for certain types of data. A first application of the

MRGIS in the fisheries management process is being focused on the evaluation of

current estuarine shrimping areas relative to natural resources, bathymetry,

nursery areas, and eventually to current rules and regulations.

Figure 6 depicts the MRGIS applications concept to the shrimping

information data base. A primary management question concerns the potential

impacts of shrimping on the natural resources, particularly seagrasses which

grow in the shallower portions of our estuaries. Figure 7 depicts and

summarizes the MRGIS analytical approach in determining shrimping areas that

impact seagrasses and the depth of the seagrasses that are impacted. The

results of this analysis provide the managers with pictorial and quantitative

assessments of existing management impacts and the results of potential

management decisions. Figures 8-12 depict data layers used in the analyses and

the results for Apalachicola Bay. The figu res are simplified and much reduced

in scale for presentation purposes. jigures 8-10 show the data layers used in

the analyses. Figure 11 presents the location of resources by depth which are

within shrimping areas. This particular analyses includes both seagrasses and

oyster reefs. Figure 12 depicts only seagrasses, within the shrimping areas,

which are impacted and demonstrates that for Apalachicola Bay potential impacts

are minimal.

Table 4 summarizes a similar analysis for Tampa Bay with quite different
results. Tampa Bay has both bait and food shrimping @nd the areas fished are

significantly different. Approximately 19,164 acres of bay bottom are bait

shrimping area. Forty four percent of that area is comprised of seagrass and

90% of the seagrass occurs in depths of <3 ft.. If the Commission were to

consider restricting shrimping to >3 ft. then 55% of the bait shrimping area

would be eliminated while 90% of the seagra@sses would be removed from the

potential impact of bait shrimping. On the other hand food shrimping would

still be allowed to occur over 98% of the exiting food shrimping areas.

These types of analyses have not previously been available in fisheries

management and the potential for improving the fisheries management and rule

making process is substantial.

Interface Tabular Data to the MRGIS

A full 'link to DBASIII+ has been accomplished. The DER STORET and permit

data bases were evaluated for linkage to the MRGIS. Although it appears to be

technically feasible an evaluation of the data itself has been advised prior to

exp.ending effort in data conversion. Positional accuracies and certain aspects"

of the quality of data need to be evaluated. A full link to the DNR/TJSFWS

manatee mortality data base has been completed. Approximately 66% of those data

had to be upgraded for positional accuracy

It appears that positional accuracy (3. e. location of the data point in UTM

or Lat/Lon) is a pervasive problem in tabular data. This may be due to lack of

quality control, technical difficulties in locating a ground point, data

originally not planned for link to a GIS, and many other reasons. In many cases

these limitations can be overcome by modifying the types of analyses conducted

with the data. But it becomes difficult to use the MRGIS to determine the

submerged bottom resources at the location of a manatee mortality in the Indian

River Lagoon when many of the points fall on land, Interstate 95, and in New

York.

Figure 13 depicts the Little Manatee River watershed and its tributaries

and was pr oduced digitally on the MRGIS. The boxes located in the watershed

represent well water pumping stations. These data were converted from the

SWFWMD mainframe data base and linked to the MRGIS though the DBAS interface.

Each data record contains information on a given.well (ie., pumping rat@es) and

the fields of information within a record can be sorted for presentation and

analyses relative to the map layers in the MRGIS. Numerous interactive analyses

can be conducted with these or any other data with positional locations

attached.

The DBAS interface continues to be upgraded with additional capabilities

and is proving to be one of the most important software advances on the MRGIS

and in raster data analyses.

Multi-s Pectral Video Imaging System

In this task we proposed to test the airborne imaging system for high

resolution data collection using a small aircraft. This was not accomplished

.I I

due to the priorities of the other portions of MRGIS operations. In particular,

it was believed that the data dissemination effort were priority and we were

backlogging requests which we considered important to fill. Test were conducted

to determine the functionality of the equipment and future testing is planned.

"MUM M

Data T-,,De Source Problems Solu@ions

Base Map SPOT Pancromatic Geo-referencing to Careful selection of control points
satellite data 1:24,000 USGS Quads. to reduce spatial errors found on
USCS quads

1950/1980 FDNR & USFWS aerial 30 meter data resampled to 10 meter data
Land cover photography

1988 Land cover SPOT Multi-spectral StaListicdl analyses Incorporate TM satellite data in
satellite imagery. difficult at 10 meter both the- statistical analyses phase
spatial resolution and interpretation phase. Use NILAP
color-IR aerial photography.

Soils Soil Conser-vation Ser- Soils delineated on photo- Soils scientist re-compile soils
vice & Manatee County, bas'ed separates are not carto- maps onto .1:24,000 USGS Quads. Scan
Fl. graphically accurate. digitize for digital access

Elevation USGS Quads and Southwest 5 ft. contours from USCS Quads Accept resolution of USCS data or
Fla. Water Managment Dis- are not adequate in a@low re- digitize SWMID maps
tri c t - (SWFWM.D) lief watershed. SWFWMD bas un-
digitized 1 & 2 ft. contours

Flood Maps Federal Emergency Manage- Cartographically inaccurate Use 3 point triangulation to
ment Agency and very general spatially digitize.

Future land- Hillsborough-and Manatee Cartographically inaccurate 'Use 3 point triangulation. Cross-
use plans Counties and different classification reference classi fication system
schemes

Drainave Aerial photography Time consuming interpretation None

Table Sources, problems, and solutions for some of the data
layers being entered on the MRGIS for the 111R.

Upland Wetland Agriculture
Plant Plant Pasture
Station Communities Communities Water Barren Total

ST1 624 718 208 6,577 8,127

ST2 151 61 1 1,848 2,061

ST3 4,281 1,527 226 17,169 23,203

ST4 2,531 1,060 47 6,249 9,887

ST5 77 79 26 862 1,044

ST6 6,515 3,115 1,684 27,989 39,303

ST7 127 341 42 1,636 2,146
(urban)

Total
Watershed 7,337 5,301 1,859 42,870 57,364

Table 2. Distribution, in hectares, of major land-cover types for the sub
watershed drainage areas defined by the location of water quality stations.
Note: ST7 is urban rather than Agriculture.

TABLE 3. List of MRGIS data requests and presentations (April 1989-Dec.
1989)

1. East Central Florida Regional Planning Council
2. Florida Department of Transportation
3. Department of Natural Resources - Terra Ceia Aquatic Preserve
4. Bionetics, Kennedy Space Center
5. Planning and Zoning Department, Volusia County
6. Environmental Management Dept., Pinellas County
7. West Side Fire Dept., Bradenton, FL
8. Tampa Bay Regional Planning Council
9. T.A. Herbert and Associates, Tallahassee, FL
10. Rookery Bay National Estuarine Research Reserve
11. American Friends Service Committee, Tampa Bay Area
12. Committee on Environmental Regulation, Tallahassee, FL
13. University of Florida, Zoology Dept.
14. Florida Oceanographic Society
15. Department of Natural Resources - Bureau of Aquatic Preserves
16. Wakulla County Planning Dept.
17. The Conservancy, Naples, FL
18. State of Florida - Office of the Governor
19. USDA Soil Conservation Service
20. Department of Natural Resources - Marathon Laboratory
21. NOAA/National Marine Fisheries Services
22. Bureau of Seafood Marketing
23. Earth Observation Satellite Company
24. SPOT Image Corporation
25. US EPA, Washington
26. Army Corp., Mobile District, Alabama
27. Duval Audubon Society
28. State of Florida Information Resource Commission
29. DNR Executive Office
30. City of Naples
31. Commission on the Future of Floridas Environment
32. State of Florida Auditor Generals Office
33. Federal/State Gulf of Mexico Program
34. Technical Resources Inc.
35. Office of the Governor/Office of Planning and Budget
36. Tampa College "River Quest." Presentation
37. Marine Mammal Commission presentation
38. Nichols State Univ. La presentation
39. Florida Council of Yacht Clubs -presentation
40. SPOT Conference Orlando 'presentation
41. Univ. of Fla.
42. Fla. Institute of Technology
43. South Florida Water Management District
44. South West Florida Water Management District
45. Eckerd College
46. Manatee County
47. Coastal Zone 89 presentation
48. Federal Interagency Habitat loss and modification working group
(including presentation)
49. Texas Dept. of Wildlife and Parks
50. NOAA/Strategic Assessment Branch
51. NOAA/National Oceanographic Data Center presentation

Table 3. Continued

52. NOAA/National Ocean Survey/Coastwatch
53. Chesapeake Bay Task Force presentation
54. FL. A&M University
55. Univ. S. Florida Regional GIS Workshop presentation
56. Division of Forestry presentation
57. GIS/LIS
58. Florida Marine Fisheries Commission
59. Maynard Hiss
60. University of Rhode Island
61. U.S. Fish and Wildlife Service, Atlanta
62. 'US EPA Atlanta
63. Dauphin Island Sea Lab, Alabama
64. Suwannee River Water Management District
65. N.W. Florida Water Management District
66. Tampa Tribune
67. St. Petersburg Times
68. Bradenton Herald
69. Miami Herald
70. New York Times
71. Time Magazine
72. Massachusetts Institute of Technology
73. USFWS National Wetlands Research Center
74. Dept. of Community Affairs
75. Senator James Kirkpatrick

TAMPA BAY

DEPTH OF SEAGRASSES WITHIN SHRIMP HARVEST AREAS

BAIT SHRIMPING

SEAGRASS ACRES NON-SEAGRASS ACRES TOTAL AREA
DEPTH SHRIMPED SHRIMPED SHRIMPED

< 3 Feet 7582 90% 2831 27% 10,413 54%

3 to 6 Feet 0347 04% 4556 42% 4,903 26%

> 6 Feet 0535 06% 3313 31% -3,848 20%

Total 8464 100% 10,700 100% 19,164 100%

IF BAIT IS REGULATED BY DEPTH

DEPTH SHRIMPING AREA REDUCED

< 3 Feet 54%

3 to 6 Feet 26%

> 6 Feet 20%

FOOD SHRIMPING

SEAGRASS ACRES NON-SEAGRASS ACRES
DEPTH SHRIMPED SHRIMPED

< 3 Feet 0 0040 0%

3 to 6 Feet 0 0575 2%

> 6 Feet 0 32@209 98%

Total 0 32,824 100%

Table 4. Summary of MRGIS analyses results to determine the amount and depth of
seagrass trawled during shrimping efforts in Tampa Bay.

Base Map REMOTE SENSING

SPOT
Panchromatic REMOTE SENSING
Image

Land Cover REMOTE' SENSING
10,50

Land Cover REMOTE SENSING
1982

Land Cove'r. REMOTE SENSING
1988

REMOTE SENSING

Elevation REMOTE SENSING

Flood Zones

Future Land RE140TE SENSING
Use

Drainage

Transportation

Public Lands

Jurisdictional
Tabular data Boundaries
Water quality parameters
Fisheries data Hydrology
Fla. Natural Areas Inventory
Permitted discharges
Hydrological parameters Etcetera
Soils attributes

Figure 1 Some of the data -layers being implemented on the I-IRCIS
for the I-MR watershed. Those layers dependent on remoce
sensing are no'ted. Tabular data to be linked to the data
layers are al so noted.

360000 370000 380000 390000

3 17 0 0 0 0 3070000

S
..-ST
STS

3060000- ..... ....... 3060000

30@0000 3050000

3600oo 370000 380000 390000

Figure 2 Water quality stations within the Little Manatee River
watershed. 'Dotted lines represent sub-basins.

own=

Figure 3 1982 WI classification of mangroves for a portion of
Tampa Bay.

& F

.... .......

N 1:

j. i ":i! :i li@

iij!;jj
:21

it
..........

........ . ....... ... ...
. .........

4 ;;j

i:::i: i!;; i:5- I
..............

'I
it

Figure 4 1987 Thematic Mapper data within the area designated as
mangroves in 1982. . Bright areas and linear features
such as roads represent discrepancies in interpretation
and classification of the data.

IN 11

FigUre 5 1987 Thematic Mapper data classified as mangroves in
1982, but not classified as mangrove in 1987.

GIS CONCEPT

Living Resources

Bottom Dept h

Shrimping Areas

Average Salinity'

Tabular Data
Jurisdiction

Marinas

Channel Location

Laws

Boat Ramps

MANAGEMENT

Figure 6 Conceptual application of GIS to shrimp manacgement.

MRGIS ANALYSIS

PROGRAM STATEMENTS

10 IF (CH4-17) 20, 50, 30
20 IF (CH4-15) 30, 50, 50
30 CHO=O
40 RETURN
50 IF (CH1-04) 60, 60, 60
60 CHO=CH2
70 RETURN
80 END

WHAT THE PROGRAM DOES

10 IF THE AREA IS A SHRIMPING AREA LOOK AT THE DEPTH; IF NOT, LEAVE AS IS.

20 IF DEPTH IS < 3 FEET TO > 6 FEET, LOOK AT THE BOTTOM RESOURCE.

30 IF THE BOTTOM RESOURCE IS SEAGRASS, THEN PRINT THE DEPTH OF THE SEAGPASS.

Figure 7. Query and summary of an analysis to determine depth of seagrasses
that are trawled for shrimp,

Ssr-T!@!.

APALkCHICOLA. BAY NATURAL RESOURCES

SEAGRASS
FRESH GRASS
OYSTERS
MARSH

Figure 8

....... ....

DEPTH CONTOURS

@lq _j
DEPTH < 3 FT 2j228 HA
DEPTH 3-6 FT 21248 HA
DEPTH > 6 FT 3140 6 HA
CHANNEL MARKERS/BRIDGES

Figure 9

s
7-4 ILA
- nr- I M P'l N G" 11 1 El 'A

SMALL WHITES & BROWNS 2,377 HA
WHITES & BROWNS 801-5-5 HA
LARGE WHITES & BROWNS 3,332 HA
MARSH NURSERY AREA
GRASS NURSERY AREA

Figure 10

DEPTH OF SUBMERGED RESOURCES
IN SHRIMPING AREAS

DEPTH < 3 FT 343 HA
DEPTH 3-6 FT 277 HA
DEPTH > 6 FT 123 HA
CHANNEL MARKERS/BRIDGES

Figure

.. ... . . . ......... ...... .
. . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . .
. . . . . .. . . . . . . . . .

t
. ........... .

. . . . . . . . . .
.............
40

]DEPTH OF S- EAGRA
WITHIN SHRIMPING AREAS
D
EPTH <' 3 FT 127 HA
DEPTH 3-6 FT 2 HA
DEPTH 6 FT 0 HA

Figure 12

0
PI
naXT 0
0 0 0
T R-110
0 0 0
0 D Q-J@
0 -)0 @3 0 D
dw @J@
D 0 0
0 0
0 0
00 D

D
0 T-
\a C)
D
0 0C C 7D
rr--

Figure 13: Locations of water wel:l. pumps in the Little Manatee
River watershed. These data were imported into the
MRGIS data base through the DBAS link.
Oj
r

Task II. Methodologies for measuring habitat carrying capacity

and fisheries utilization.

CARRYING CAPACITY

Gear Testing:

This activity continued in Cockroach Bay during 1989 with an

emphasis on quantitative methods,for sampling juvenile and small

adult fishes in seagrass beds as well as unvegetated shallow-

water habitats. As mentioned in the April 1989 Final Report, the

preferred type of sampling gear for seagrass beds (based on
previous testing) was a 1 m2 roving dropnet (RDN). This sampling,

gear is, howev er, highly selective for demersal and semi-demersal

species. Thus, in 1989 we began testing two types of sampling

gear designed to quantitatively collect pelagic species: a 120 m
pull-through seine (PTS) and a 1 m2 bow-mounted pushnet (BMPN).

The RDN and associated sampling methodology were described in

the 1986, 1967, and April 1989 Final Reports. RDN sampling was

conducted once or twice per month with five to twelve drops being

executed on each sampling date.

The PTS is similar to the long-haul seine described by

Kjelson and Johnson (1975). Our version,of this net is 122 m

long by 2.4 m deep with a 2.4 by 2.4 by 2.4 m bag at one end and

a seine pole attached to the bag end. The net is deployed in a

circular configuration by boat. when the circle is completed, a

seine pole is driven into the substrate beside the attached pole

but an the outside of the net. Thus, as the boat continues

closing the circle the net is forced between two seine poles.

This procedure reduces escapement by maintaining the net in an

upright position with weights on or near the substrate and floats

at the surface. The circle is closed until only the bag portion

of the net remains, and this portion is then gathered onto the

boat. Nineteen sets were conducted with this net during June,

August, and September 1989.

The BMPN is similar to that described by Kriete and Loesch

2
(1980). our net has an opening of 1 m , is 3 m long, and is

constructed of 3.2 mm mesh. It is attached to an aluminum frame

that is fitted to the bow of a 5 m outboard boat and is equipped

with a flow meter. Testing of this sampling gear was quite
preliminary ci-di@-ing the time period covered by this report. only

11 samples were collected in July and August, and details such as

tow duration, sampling depth, etc., are still being evaluated.

For this reason the only comparison'of this gear with the other

two will be in terms of species richness and relative abundance

of dominant species.

Species Richness and Abundance:

Although final identifications are not complete for all

samples collected during the report period, preliminary results

can be presented for our three types of sampling gear. Number of

species collected by each sampling gear were as follows: RDN, 35

species; PTS, 49 species; and BMPN, 16 species. The latter total

was undoubtedly affected by the paucity of samples. The RDN

total compared favorably with the 1 988 total of 38 species.

Rank abundance of species indicated relatively greater

abundance of pelagic species in PTS and BMPN samples and greater

abundance of demersal and semi-demersal species in DN samples

(Table 1). Abundant pelagic s peciets included Anchoa mitchilli,

Hg,@U@la laquana, and Opisthonema oglinum (see Appendix A for

common names of fish species). A. mitchili was obviously of

relatively greater importance in PTS and BMPN samples, only 1

specimen of H. laquana was collected by the RDN, and no specimens

of 0. oglinum were collected by the RDN. Chloroscombrus

chrysurus is a schooling species probably similar in habits and

habitat to the above-mentioned pelagic species and was only

important in BMPN samples. Demersal or semi-demersal species

(i.e., those go@iherally associated with the bottom or some other

substrate such as seagrass blades) included Bairdiella chrysoura,

Lagodo rhomboides, Eucinostomus spp., Lucania parva, Syngnathus

scovelli, and Gobiosoma spp. Four members of this group were the

top four species in abundance in RDN collections.

Density Comparisons:

Comparisons of densities for selected species in August 1989

RDN versus PTS samples again indicated the marked difference in

selectivity of these two types of sampling gear (Table 2).

Species that we have utilized in this comparison include most of

those listed amo ng the dominants in Table 1 plus the economically

valuable species Cynoscion nebulosus. Mean calculated densities

were 2.8 and 16 times greater,. respectively, in PTS samples for

the pelagic species A. mitchilli and H. laquana, while another

pelagic species, 0. oglinum, ranked among the top few species in

density in PTS samples but was absent from RDN samples. On the

other hand, densities for six demersal or semi-demersal species

ranged from 3.2 to more than 30 times greater in RDN than in PTS

samples.

In summary, our data indicate that accurate measurement of

habitat carrying capacity in areas such as Cockroach Bay would be

impossible with either the RDN or PTS alone, although a

combination of these two types of gear may yield reasonable

estimates fish populations densities in.such areas. The eventual

role of the BMPN in these studies is unclear at this time. Data

collected by the RDN to date may be used to make reasonable

predictions regarding densities of several demersal or semi-

demersal species to be expected per area of a Tampa Bay seagrass

bed.

HABITAT UTILIZATION

Methods:

The Little Manatee River was sampled approximately biweekly

from January through September 1989. Fishes were sampled.with a

22.7 m bag seine (15 sites per sampling date), a 9 m bag seine (2

sites), and a 6.1 m otter trawl (11 sites). In 1988 we used a

3.6 m otter trawl and did not use the smaller seine. Mesh size

in both seines and in the cod end liner of the trawl was 3.2 mm.

Station locations ranged from the mouth of the river (Station 1,

Fig. 1) upstream to nearly permanent freshwater (Station 6, Fig.

1). During the nine-month period covered by this report,

300,058 specimens (representing at least 87'species) were

collected, identified, and measured.

Seven physical/chemical parameters were measured at each of

the six sampling stations on each sampling data (see April 1989

Final Report). The discussion below will emphasize salinity,

water temperature, dissolved oxygen, and pH. Values for these
parameters over the first nine months of 1989 will be presented

and compared with the same period in 1988.

Fish community data will be presented below at two different

levels. First, we will present a brief comparison of the entire

community in 1988 versus 1989. Second, we will concentrate on 17

species,that-are either numerically dominant or of considerable

economic value. These species will be compared and contrasted in

terms of seasonal and spatial distribution and distribution in

relation to salinity. Wherever possible, data will be compared

between 1988 and 1989. This presentation is meant to illustrate

just some of the ecological data available in our data set.

Distribution of fishes in the Little Manatee River is obviously

not determined by a single factor such as salinity, and, upon

completion of the 1989 data set, we will begin multivariate

analyses in hopes of determining the relative importance of

various habitat variables in determining the distribution of key

species in this system.

We would like to mention at this point that our specimens

and data regarding exotic fishes of the genus Tilapia are

currently being examined by J. D. Williams and D. Jennings of the

U. S. Fish and Wildlife Service in Gainesville, Florida. Tilapia

spp. are well-established and oftenabundant in some Little

Manatee River collections, and we believe that they could have a

significant impact on fish community dynamics in this system.

Dr. Williams and Ms. Jennings are conducting a nationwide survey

of Tilapia populations and are among the few persons qualified to

identify the various species (especially as juveniles).

Station Descriptions:

All stations were at the same locations as presented in the

April 1989 Final Report with some minor variations in sampling

scheme and exact sample sites (Fig. 1).' The number of trawl tows

was decreased.-from three to two at Stations 1, 3, and 4 and from

three to one at Stations 5 and 6. At Station 3 the 22.7 m seine

was utilized at 2 sites on oppostie banks of the river (former

sites 3A and C),, while a third seine haul was conducted with the

9 m seine just inside the mouth of a small creek entering the

river at Sun City Heritage Park. At Station 4 an additional

seine haul was conducted with the 9 m seine in a small cove just

upstream of the Interstate 75 bridge. And, finally, the number

of seine hauls at Stations 5 and 6 was reduced from-three to two

(on opposite banks of the river). All of the deletions were made

in an effort to reduce time wasted in unproductive or redundant

sampling and seem to have had little effect on the overall scheme

of fish distribution represented in our data base. The two new

sites were added in an effort to include microhabitats not

sampled in the previous scheme.

Physical/Chemical Data:

Salinity values varied markedly over this period, and

seasonal patterns often differ ed from those exhibited in 1988.

At sites 1A and 1C there was less stratification between surface

and bottom salinities in 1989, and the decrease from high summer

values occurred in July instead of August (Figs. 2 and 3).

Overall, however, the salinity range was relatively restricted

and values were generally higher at these sites in 1989.

Although the data set is incomplete for 1989, patterns at sites

2A and 2B seemed similar between years with relatively low (but

fluctuating) values in winter and spring, high values in mid-
summer, and relatively low values in late-summer-ear.ly fall

(Figs. 4 and 5). Surface-bottom stratification was not

pronounced in either year, and salinity ranges were similar

although values never reached as low as 0 ppt in 1989. Site 2C

also exhibited similar patterns between years, but stratification

was much greater in 1988 (Fig. 6). Also, surface salinities

often ranged much lower in 1986, especially in spring and late

summe,r-early fall. Site 3B was not stratified in either year and

showed a late spring-summer increase in salinity in both years

(Fig. 7). Values did, however, fluctuate more widely between

sampling periods in 1989 and fewer zero or near zero values were

recorded. Site 4A was also poorly stratified with values peaking

in summer (Fig. 8). Again, however, fewer zero values were

recorded in the low salinity periods. At sites 5A and 6A

stratification and seasonal pattern were similar between years,

but the summer salinity peak was higher in 1989 (Figs. 9 and 10).

In fact, the May and June values for site 6A were the only non-

zero.salinity values that we have recorded at that site. In
summary, salinity patterns were somewhat.similar between 1988 and
1989, but values were often somewhat higher in the latter year,

especially at upstream stations.

As in 1988 dissolved oxygen values generally peaked in

winter-spring, decreased during summer, and often increased

somewhat during fall (Figs. 11-13). Stratification was greatest

at sites 2C and 4A, where bottom values were much lower than

surface values on several dates, and seasonal dissolved oxygen

depression was again greatest at sites 2C, 3B, and 4A.
Tempera@@:@_e patterns were nearly identical among stations

and were similar between years (Figs. 14-16). In both years

temperatures increased from January through May and remained at a
stable 25 to 300 C through September. The major difference

between years was in the minimum recorded temperatures: as low as
80 C in 1988 versus 160 C in 1989. Temperature stratification

was minimal.

Values for pH exhibited little vertical stratification but

varied markedly among seasons and stations as well as between

years (Figs. 17-19). At Stations 1 and 2 values fluctuated but

were notably lower from winter through mid-summer than in late

summer-early fall. this pattern was somewhat reversed in 1988

and fluctuations were much less marked. At Station 3 the above-

mentioned seasonal pattern was not evident, and fluctuations

were, again, greater than in 1988. At Station 4 pH decreased in

May and June, increased markedly in July, and decreased again in

late July through September. In 1988 values were relatively

stable over these months. At Stations 5 and 6 pH values

exhibited wide fluctuations wi th peaks in winter, spring, and

summer and generally low values in late summer-fall. The peak

values in 1989 (pH>S) were never reached during this same time

period in 1988 although similar values were recorded in October

through December,

Fish Community:

Despite the incomplete 1989 data set, the dominant species

in the Little Manatee River were similar in 1988 and 1989 at the

two most downstream stations but varied more upstream (Table 3).
At Station 1 the dominant five species were'exactly the same in

both years. Station 2 rankings were only changed by the reversal

of Eucinostomus spp. and Leiostomus xanthurus. At Station 3 two

Spec ies that were relatively more important further upstream in

1988, Gambusia affinis and Poecilia latipinna, entered the top

five in 1989 replacing Eucinostomus spp. and Brevoortia spp.

This trend was directly related to the addition of the new seine

site in the creek mouth at this station: most G. affinis and P.

latipinna were collected at this site. We must also mention,

however, that several large samples of both Eucinostomus spp. and

Brevoortia spp. were preserved in 1989 for verification of

identification and that addition of these samples to the data

base might affect the rankings of these two groups at several

stations. The top five species at Station 4 were nearly

identical (with some rearrangement) except for the fact that

Eucinostomus. spp. replaced Brevoortia spp. At Station 5 gobies

became more important in 1989 with Gobiosoma spp. and Microgobius

gulosus entering the top five list.- Finally, at Station 6 four

of the top five species are identical but M. gulosus replaced

Fundulus seminolis. In both years perhaps the most striking.

factor in these data was the overriding numerical importance of A.

nitchilli over the entire estuarine portion of this river.

Distribution of 17 selected fish species among 16 salinity

categories exhibited reasonably good consistency between years

(Table 4). Five species (Fundulus seminolis, Lucania goodei,

Garbusia affinis, Poecilia latipinna, and Trinectes maculatus)

exhibited a.strong preference for fresh or oligohaline waters

(categories 0 to ca. 3), while four.species (Fundulus similis,

Lagodon rhomboides, Bairdiella chrysoura, and Cynoscion

nebulosus) displayed a preference for mesohaline to polyhaline

waters (ca. category 4 and above). Of the remaining eight

species, Microgobius gulosus and Centropomus undecimalis were

most common in freshwater but ranged widely along the salinity

gradient; Menidia spp. and Leiostomus xanthurus were somewhat

more abundant in more saline waters but were also widely

distributed ; and Anchoa mitchilli, Cynoscion arenarius, Sciaenops

ocellatus, and Mugil cephalus were scattered throughout mostly

the freshwater to mesohaline portions of the spectrum. Most of

the differences in salinity distribution between years were

slight, and most were in the form of a slight shift towards

higher salinities in 1989. In some cases these differences might

reflect the slightly higher salinities throughout the study area

in 1989, but in four of the most obvious cases (i.e., A.

mitchilli, G. affinis, P. latipinna, and C. undecimalis) these

differences were directly related to the addition of the creek
site at Station 3 (all four species were collected in significant
numbers at this site). Furthermore, the data from this site may

be misleading since salinity was recorded outside of the mouth of

this creek, and the seine was pulled into the creek. Salinities

will be recorded well inside the creek in 1990.

Distribution of these same 17 species among our six sampling

stations was reasonably'consistent with the salinity data

presented above and compared favorably between years (Table 5).

The five low-salinity forms were obviously most abundant at

Stations 4 through 6. Pronounced differences between years wer e

noted in G. affinis and P. latipinna: in both species relative

numbers were much higher at Station 3 in 1989 than in 1988. This

trend was, again, directly related to the addition of the creek

site at Station 3. Among the four mesohaline to polyhaline

forms, more than 50% of the specimens were collected at Station 1

in both years. This association was most pronounced in L.

rhomboides, especially in 1989. None of these species

demonstrated-a pronounced expansion of range due to the slightly

higher overall salinities in 1989. of the remaining eight

species A. mitchilli was most common at Stations 3 and 4 but was

relatively' numerous in at least one of the years at each of

Stations 1 through 5, Menidia spp. were most common at Stations

1 and 2 but were also relatively numerous at Stations 3 and 4, C.

undecimalis was most numerous at Stations 3 and 4 with relative

numbers at Station 2 being greater in 1988 than in 1989, C.

arenarius was most common at Station 3 in both years with

significant numbers only at Stations 1 through 4, 1. xanthurus

was most numerous at Stations 2 and 3 in 1988 and Stations 1 and

3 in 1989 with significant numbers only at Stations 1 through 4,

S. ocellatus was concentrated at Stations 2 through 3 in both

years, M. cephalus was most numerous at Stations 2 and 3 in 1988

and at Stations 3 and 4 in 1989, and M. gulosus was most numerous

at Stations 4 and 5 in 1988 and at Stations 4 and 6 in 1989 with

significant numbers at Stations 2 through 6.. Again, none of.

these distributional patterns indicated a marked shift related to

the generally-higher salinities in 1989.

Numbers of specimens collected per month for some of these

same species demonstrated some pronounced seasonal trends in

abu ndance and generally agreed fairly well between years (Figs.

20-23). Periods of peak abundance usually represented peak

juvenile recruitment into the river. Among the species figured,

L. rhomboides, L. xanthurus, and M. cephalus reached peak

abundance in winter and spring; S. ocellatus peaked in fall and

early winter; and B. chrysoura, C. arenarius, C. nebulosus, and

M. gulosus peaked from late spring through early fall. B.

chrysoura seasonal numbers were distinctly bimodal with peaks in

May and August-September in both years. Finally, peak abundances

for several species (i.e., C. arenarius, C. nebulosus, L.

xanthurus, M. cephalus, and M. gulosus) ranged from one to two

months earlier in 1989 than in 1988.

Mean standard length of specimens captured at each station

exhibited moderate to pronounced patterns of differential'size

distribution in several species, and these patterns were generally

consistent between years (Fig. 24). Larger specimens of A.

mitchilli and F. similis were generally found at the river mouth.

Larger C. arenarius, on the other hand, exhibited a marked
tendency to occur further upstream, and this tendency remained

obvious in both years when the data were analyzed for indiviudal

months during peak recruitment (Fig. 25).

In conclusion, distributional patterns of fishes in the

Little Manatee River were fairly consistent between years despite

the incomplete status of the 1989 data set. The higher overall'
salinity value@--for 1989 were not reflected in any wholesale

changes in distribution among the species considered in detail

(although a close examination of the data for Station 6 did

indicate a reduction in numbers of so-me of the freshwater species

during the May and June period of high salinity). We would

predict, however, that such wholesale changes would occur with

more radical interannual differences in salinity patterns.

Finally, as we mentioned above, it was obvious that a variety of

factors controlled the distribution of fish species in this

riverine system and that multivariate analyses along with

integration of these data with MRGIS habitat information will be

necessary to obtain an understanding of observed patterns.

LITERATURE CITED

Kjelson, M. A., and G. N. Johnson. 1975. Description and

evaluation of a long-haul seine for sampling fish populations

in offshore estuarine habitats. Proc. 28th Ann. Conf.

Southea. Assoc. Game Fish Comm. 1974: 171-179.

Kriete, W. H., Jr., and J. G. Loesch. 1980. Design and relative

efficiency of a bow-mounted pushnet for sampling juvenile

pelagic fishes. Trans. Am. Fish. Soc. 109(6): 649-652.

Table 1: Numerically dominant species in collections made in
Cockroach Bay in 1989. Acronyms for different types of
sampling gear and complete species names defined in text.

BMPN RDN PTS

A. mitchilli 310 L. rhomboides 1145 A. mitchilli 64329

B. chrysoura 182 L. parva 407 'B. chrysoura 6363

C. chrysurus 35 S. scovelli 204 ;Ht- j 5176
jaquana

L. rhomboides 23 Gobiosoma spp. 166, Eucinostomus spp. 1487

Eucinostomus spp. 21 A. mitchilli 161 0. oalinu 1115

Table 2: Density calculations for selected species based on
August 1989 RDN and PTS samples (#/ m 2). Three sample dates/
gear. Full species names in text.

RDN PTS

Species Mean Range Mean Range

A. mitchilli 4.57 0.31-10.2 12.59 <0.01-35.78

H. laquana 0-03 0.00- 0.10 0.48 0.10- 1.24

0. oglinum 0.00 ---------- 0.18 0.00- 0.52

S. scovelli 0.22 0.06- 0.40 <0.01 ---------

B. chrysoura 0.64 0.50- 0.71 0.20 0.07- 0.38

C. nebulosus 0.07 0.00- 0.13 0.01 <0.01- 0.03

Eucinostomus 0.42 0.00- 0.81 0.04 <0.01- 0.10
SPP.

L. rhomboides 0.64 0.38- 0.80 0.05 0.02- 0.07

Gobiosoma spp. 0.30 0.00- 0.71 <0.01 ---------

Table 3: Most abundant fish species from six sampling
stations in the Little Manatee River; 1988 vs. 1969.

Total Total
1988 collected 1989 collected

STATION 1
Menidia spp. 14,141 Menid.-.,.a spp. 31,205
Anchoa mitchilli 11,479 Anchoa mitchilli 28,897
Lagodon rhomboides 7,662 Lagodon rhomboides 8,395
Eucinstomus spp. 3,356 Eucinostomus spp. 5,702
Leiostomus xanthurus 2,972 Leiostomus xanthurus 3,825

STATION 2
Anchoa mitchilli 36,342 Anchoa mitchilli 19,898
Menidia spp. 101798 Menidia spp. 15,291
Leiostomus xanthurus 5,061 Eucinostomus spp. 21668
Eucinostomus spp. 4,142 Leiostomus xanthurus 695
Fundulus similis 1,016 Fundulus similis 633

STATION 3
Anchoa mitchilli 48,034 Anchoa mitchilli 43,899
Menidia spp. 7,590 Menidia spp. 9,864
Leiostomus xanthurus 5,071 Gambusia affinis 6,068
Eucinostomus spp. 3,814 Poecilia latipinna 2,067
Brevoortia spp. 1,674 Leicstomus xanthurus 1,080

STATION 4
Anchoa mitchilli 64,731 Anchoa mitchilli 48,719
Gambusia affinis 11,042 Menidia spp. 61727
Brevoortia spp. 8,240 Gambusia affinis 3,278
Menidia spp. 6,472 Trinectes maculatus 2,250
Trinectes maculatus 3,011 Eucinostomus spp. 1,516

STATION 5
Gambusia affinis 21,162 Anchoa mitchilli 8,225
Anchoa mitchilli 18,510 Gambusia affinis 3,794
Trinectes maculatus 7,470 Trinectes maculatus 2,175
Brevoortia spp. 4,814 Gobiosoma spp. 1,687
Poecilia latipinna 4,569 Microgobius gulosus 474

STATION 6
Anchoa mitchilli 15,117 Anchoa mitchilli 6,846
Trinectes maculatus 9,055 Gambusia affinis 2,201
Gambusia affinis 9,046 Trinectes maculatus 2,135
Lucania goodei 2,252 Lucania Parva 725
Fundulus seminolis 2,081 Microgobius gulosus 693

TabLe 4. Distribution of seLected fish species in the LittLe Manatee River in reLation to surface saLinity catego-
ry, 1988 and 1989. Categories as foLlows: 0) 0.0-0.5 , 1) 0.6-2.0, 2) 2.1-4.0, 3) 4.1-6.0, 4) 6.1-8.0, 5) 8.1-
10.0, 6) 10.1-12.0, 7) 12.1-14.0, 8) 14.1-16.0, 9) 16.1-18.0, 10) 18.1-20.0, 11) 20.1-22.0, 12) 22.1-24.0, 13)
24.1-26.0, 14) 26.1-28.0, 15) 28.1-30.0. ALL numbers are percentages of the totat numbers of that species caught
in a given year.

SALINITY CATEGORY

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

A. mitchilli
1988 24 14 27 3 10 2 7 6 4 2
1989 8 6 7 21 8 1 21 9 20

F. simitis 1988 14 3 4 2 4 3 1 5 5 9 7 16 17 9
1989 3 2 6 4 1 1 1 5 17 3 16 29 5 7 1

F. seminotis
1988 85 3 8 1 2 1 1
1989 84 5 3 2 5 1

goodei
1988 99 ---- 1
1989 94 1 3 1 2

G. affinis

1988 94 2 2 1 1 1
1989 51 15 13 18 1 2 1

P. (atipinna
1988 89 2 6 2 1
1989 71 16 2 8 2

Menidia sop.
1988 9 8 5 4 9 4 10 1 8 9 2 7 7 6 10
1989 6 1 7 2 4 3 5 3 12 3 7 11 25 7 3

C. undecimaLis

1988 49 41 5 3 3
1989 33 10 14 1 30 3 3 6 1

L. rhomboides

1988 18 2 1 13 3 6 1 2 9 1 4 5 15 19
1989 2 1 7 18 6 34 20 9 2

B. chrysoura
1988 5 5 3 5 4 16 11 13 3 6 1 27 1
1989 2 7 1 2 30 4 33 1 20

C. arenarius

1988 29 11 9 16 2 2 23 2 4
1989 22 10 31 5 12 1 4 10 2 2

TabLe 4. Continued.

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

C. neboLosus
1988 5 4 1 1 6 14 15 11 18 8 5 3 9
1989 4 2 7 1 2 2 2 39 9 30 1

xanthurus
1988 11 19 1 6 11 17 7 5 3 3 11 1 2 2
1989 4 12 1 5 4 6 3 4 3 50 1 2 3

S. oceLLatus
1988 19 16 13 11 13 9 5 7 5 2
1989 24 30 2 20 4 5 13 1 1

M. cephatus
1988 10 21 2 2 3 12 8 19 9 4 3 2 3 2
1989 14 8 40 4 8 3 2 2 13 4 3

gulosus 1988 62 3 1 5 2 1 1 8 2 2 9 1
1989 63 3 12 3 4 3 2 2 3 2 2 1

T. maculatus

1988 93 2 1 1 1 1 1
1989 81 4 5 1 2 2 1 1 2

Table 5. Distribution of selected fish species anong six
sanpling stations in the Little Manatee River, 1988 and 1989.
Station locations described in text. Nuinbers are percentages of
the total nunber of that species caught in a given year.

STATION
1 2 3 4 5 6

A. mitchilli
1988 6 19 25 33 10 8
1989 18 13 28 31 5 4
F. similis 1988 51 24 22 3
1989 66 20 14

F. seminolis
1988 1 1 11 58 30
1989 1 34 28 38
L. goodei l9ig-- 1 22 77
1989 1 18 80

G. affinis
1988 27 51 22
1989 39 21 25 14

P. latipinna
1988 2 19 65 13
1989 4 56 30 6 4

Menidia spp.
1988 36 27 19 16 1
1989 49 24 15 11 1

C. undecimalis
1988 26 26 36 10 3
1989 1 3 64 31 1

L. rhomboides
1988 70 8 4 18 1
1989 90 6 2 2

B. chrysoura
1988 68 9 9 13 1
1989 69 21 7 3

C.' arenarius
1988 26 17 41 15
1989 3 14 50 33

Table 5. Continued.

STATION
2 3 4 5 6

C. nebulosus
1988 63 13 11 12 1
1989 53 28 15 2 1

L. xanthurus
1988 20 35 35 9 2
1989 58 11 16 14 1

S. ocellatus
1988 8 25 55 11 1
1989 2 18 47 30 3

M. cephalus
1988 14 33 50 3
1989 11 13 29 47

M. guloSus
1988 5 19 14 24 32 6
1989 3 10 10 40 15 22

T. maculatus
1988 1 5 15 36 44
1989 1 1 4 32 31 30

TAMPA BAY

LMR WATERSHED

FIGURE LITTLE MANATEE RIVER WATERSHED

FI GURE 2

.35- Sallnit Station IA LMR 1988
0-0 Surface
30-- L - L Bottom

25-
0-
0- A 0
9-
20--
/0\
C 15--
7
0
10-- 0 0
0

0-
i F M A M i i A s

35 Salinity Station IA LMR 1989
0-0 Surface
30-- L-L Bottom

CD-
20--

0
C 15--

V) 10--

5--

0-
i F M A M i i A S

Month

Fl GURE 3

35- Sall-n-it - Station 1 C LMR 1988
0-0 Surface
30-- L-A Bottom

25-- L.
CD- 4L X
20-- 0 0

15--
0
V) /0\
10--
0 0
5--

0
i F M A M i i A S

35 Sol-inity Station I C LMR 1989
0-0 Surface
30-- Z@-,L Bottom

25--
CP 6
20--,
0
15-- 0/
0
10--

5--

0- 1 F M A M i i A s

Month

FIGURE 4

35- Schnity - Stclion 2A LMR 1988
0-0 Surface
30-- L-L Bottom

25--

20--
A

10--

5 0 0
.0 0
i F l\A A M i i A s

,35- Sclinity Station 2A LMR 1989
0-0 Surface
30-- L-,L Bottom

25--

20-- '0
0
15--

0
10--

5--

0
i F M A M i i A s

Month

FI GURE 5

35 Sclinit Station 2B LMR 1988
0-0 Si-.@rface
30-- L-,Lls Bottom

25-- A-A
Q-
0- - Z@ /0 0
20

A
C 15-- 0

0
lO__
A

n-O
0-
i F M A M i i A s

35 Sol init Station 2B LMR 1989
0-0 Surface
30-- Bottom

25--

n
20--

C 15--

0
V) 10--

5--

0-
/(0

i F M A M i J A S

Month

FI GURE 6

Salinit Station 2C LMR 1988
35-
0-0 Surface
30-- L-,L Bottom

25-- Z@
Z@
20' Z@-L 0
A-
0 Z@
E 15- 0-010
0 'ns 0' 0
U) 10__ 0-0 A
0 G
5-- 0
0- 0 0-0-0
i F M A M i i A S

35-- salinity - Station 2C LMR 1989
0-0 Surface
30-- A - L Bottorn

25-- A
r) 0
20-- A - IL A-A. ILI
A
C: 15-- 0 0 0
>" 0'
10__ 0
A 0 0 0,6
5--
0
0 1 F M A M i i A s

Month

FIGURE 7

35- Salln-Ity Station 3B LMR 1988
0-0 Surface
30-- L-L Bottom

25--

Q-
20--
Ozz 0.3
C

0
C/) 10-- L
0
5--
0
0
J F m A M i i A s

Salinity - Station 3B LMR 1989
35
0-0 Suriace
t @
30 -L Bot m

25--
4-@

20--

>\
15--

C/@

5--
@O
0--
i F M A M i i A s

Month

FIGURE 8

35- Salinity Station 4A LMR 1988
0-0 Surface
30-- L-L Bottom

25--

20--

C 15--

C)
10-- Ao A
\0\
5-- 0

0- X-3 L-1
i F M A M i A s

35- Salini Station 4A LMR 1989
0-0 Surface
30-- L-L Bottom

25--

20--

0
10--

5--
A
O\
0-
i F M A M i i A S

Month

'FIGURE 9

35 Salinity - Station 5A LMR 1.988
0-0 Surface
30-- L-L Bottom

25--

20--

>1
:tf
C 15--

0
10-

5--

0-
X..l X-1
i F M A M i A s

35- Sol-inity Station 5A LMR 1989
0-0 Surface
30-- 'A -L Bottom

25--

20--

15--

0
V) lO__

5--

0
i F M' A m i i A s

Month

FIGURE 10

Salinity 'Stotion 6A LMR 1988
35-
30-- 0-0 SLirface
L-L Bottom

25 --

20--

C 15--

10-

5--

0-
X-1
F M A M A S

35- Solinity Station 6A LMR 1989
30-- Surface
25-- z@,-A Bottom
0-
20--

15--

0
10--

0--0
o- SS8 nG 8 E) 8
\-@F M A M i i A s

Month

FIGURE 11

10- DO Station 1 A - LMR 1989
0-0 Surface
6-6 Bottom
E

x 6--
'Al 0
a)
>
0 4- 0 0
Ln
.V)

2-
i F M A M i i A s

10-- DO -Stat;on 1 C - LMR 1989
0-0 Surface
6-Z@ Bottom

0.
8--

C;n
X 0 2,;
0
0

2
0
U) 4--
U)

2-
i F M A M i i A s

DO S-to-tion 2A LMR 1989

0-0 Surface
Bottom
E

Ol
>@ 6
x 6--
0 N
-a @2-0
(U
-> 2 0
0 4--

2- -1 F M A M i i A

Month

FI GURE 12

10 DO - Station 2B - LMR 1989
0-.0 Surface
n,-n Bottom
E
a
Cl 8--

cn
x 6--
0

2
0 \0
V) 4--
V)

2-
F M A M i i A S

D() Stci('on 2C LMR '1989
10 -
0-0 SLII-fOCe
L-n Bottom
E
0 0

0, 0
0
6-- C)
0-0 0
d)

Z,
4--
C)
C)

2 A
i F M A M i i A S

10- DO `@tntion 3B - LMR 1989
0-0 Surface
L-Z@ Bottom
E
Cl

0
C
Q) C
x 6-- L5 Zs\
0

0 4-- 0-
0 --
Ln 0

2- 0
i F M A M i i A

FIGURE 13

10- DO Station 4A - LMR 1989
0-0 Surface
z@-Z@ Bottom
E
CL
0, 0
0 /0
C
Q) n - @\ 0-0
CD
>1
x 6--
0 0 0
_0
a) \0
2
0 4--
V)
U)
r)

2-
i F M A M A S

Station 5A - LMR 1989
DO

0-0 Surface
0 6,-7--,n4 Bottom
E
0- L
Q,

X 6-- 0-0
0

0-0

4--
(A

7-
i F M A M i i A S

DO Station 6A - LMR 1989
10-
0-0 Surface
Z@ Bottom
0
CL
Cl

0) 0
>1
x 6-- 0
0 0
_0
(1)
OV,4.-
Ul)

i s

Month

FI GURE 14

35 Temperature - Station 1 A LMR 1989
0-0 Surface
30-- L-n Bottom

25--
ILI
Q) 6, /
20-- 6

Cn
1O__

0
F M A M i i A s

35 Teniperature - Station 1 C LMR 1989
0-0 Sul-face
30 Bottom 0el @,a

25--

20--
C)

15-.

1O__

5--

0
J F M A M i i A

TenilDerature Station 2A LMR 1989
35-

30-- Z@--@@% Botlorn

25--

20--

10--

5--
01-
i F M A M i i A s

Month

FIGURE .15

35 Temperature - Station2B LMR 1989
0-0 Surfoce
30-- L-6 Bottom

V) 25--

(U
U 20--

15--

5--

0 1
i F M A M i i A s

35- TernpercitLil-e Station 2C LMR 1989
0-0 Surface
30-- Bottom

0 ":)Zcn
.2 25--

4) 20--

15--

10--

5 -

0-
i F M A M i i A s

35- Tel-1-1percitUl-e Station 3B LMR 1989
0-0 curfoce
30-- 4@--Z@ Bottom

25--
ILI)
20--

15--

0)
10.-

5--

0
i F M A M i i A s

Month

Fl GURE 16

35 Temperature - Station 4A - LMR 1989
0-0 Surface
30-. Bottorn 2

25--

n
(0 20- x
V)
Q)
15--

CD
lo--
51
0
i F m A m i i A S

Ternj.-.-erak.ire Station _5A LMR 1989
35
--- 0-0 Surlac,--
30-- ------ (D

25--

Q)
U 20-- 0

0)
10--

5
oi-
i F m A m i i A s

t @--:tcjtlon 6A LMH 1989
35
Surfnre
V) 30-- !@-Z-\ Elcitlom 0-0 0 0
25--

(U
20--

V) 0
Q)
Q) 15--
L-
C)n
10..

5
ol
11 F m A m i i A S

Month

Fl GURE 20

N umber/ Month LMR
50--
45 Lagodon rhomboides D-El 1988
40-- 0-0 1989

35--

30--

25--
20-- O'El-
15--
10-- 0
zo
El
0 El

J F M A M J J A S 0 N D

50-- Number/ Month LMR
Bairdiella gh ysourg -[1 1988
45 El
40-- 0-0 1989

35--
30-- 0
a)
25--
0 0 El
20--
15-- 0
10- / 0
5--.
0- 9 9 0 0 Fl-B--E
/E

i F M A M J i A S 0 N D

Month

FI GURE 17

10 pH Station 1A LMR 1989
0-0 Surface
Bottom

0
'o-", /0/
0,-
6
i F M A M i i A s

pH Stollon 1C - LMR 1989
10-
(-)---0 Surface
n-n Bottom

0-2

0 -0

6-
i F M A M i i A s

10- PH Station 2A LMR 1989
0-0 Surface
Bottom

C6_0@@ la
0
0

A\6

6-
i F M A M i i A s

Month

FIGURE 18

10 pH Station-2B @LMR 1989
0-0 Surface
Bottom

6
i F M A fli i i A s

10- pH Stotion 2C LMR 1989
0-0 Surface
Bottom

8--

CIO - a Z:z 0;@

0
6- 6
i F M A M i i A S

10- pH Station 38 LMR 1989
0-0 Surface
n-"l Bottom

0 0-00
C?

i F M A M i A s

Month

FIGURE 19

10 p 1-1 -Stotion 4A --LMR 1989
0-0 Surfoce
L-L Bottom

M 8-- 0
CL 0
Z-\ lk
\0/ 0

i F M A M i i A s

10-- pH StaLion 5A LMR 1989
(D -0 SLirfCJCe
Botton)

0 0

i F M A M i i A s

10- PH Station 6A LMR 1989
(D-0 SUrface
Bottom

0
`@,\ - 0
0,
8-- 0-0

0-4)

i F M A M i A s

Month

FIGURE 21

Number/ Month LMR
50--
45-- Cynoscion arencrius 1988
40- 0-0 1989

35--

30--
c: El
Q) 0
lu 25--
Q) El
0- 20--

15-

5--

0-
E3 B
J F M A M J J A S 0 N D

50- Number/ Month LM R
cy nebulosus
.45-- .@i,2n 0-0 1988
40-- 0-0 1989
35-- 0
30-- 0
Q)
P 25--

A 20--

15-

lO__ 0

5--
0- 0
J F M A M J J A S 0 N D

FIGURE 22

80-- Number/ Month LMR
70-- 0 D-0 1988
0-0 1989
60-- Leiostomus xanthurus
4-@ 50--

U 40--
L-
Q)
30-- F-1

20--

lo-- El 0----
0-0-, D
0- 5-10@0 El E3 z
J F M A M J J A S 0 N D

80-- Number/ Month LM R
70-- 0 El-El 1988
60-- 0-0 1989
Sciaeng-p-@j ocellatus_
50--

Q)
40--
Q) El
30--

20-- El
0
10--
El.-El,
0--
L= L-A D 8
J F M A M j J A S 0 N D

Month

FI GURE 2.3

Number/ Month LMR
50-
45-- M-9@1 -9-t2hgll u s EI-El 1988
40-- 0-0 1989
35-- 0

30--
0
25--

20-- E]
15- 0
10-- 0 f7
5-- El,, 0
0 0 n P:@ - F@
k-,/ " El
J F M A M J J A S 0 N D

50-- Number/ Month (%) - LM R
0
45-- Microdobius [email protected]@s, us 1988
40-- M 0-0 1989

35--

30--
Q)
U 25--
Q) 0
a- 20--

15--

10--
El
0

5-- 0 -0
n o
0 1 F M A M j J A S 0 N D

Month

FI GURE 24

55-- Annual Mean Standard Length - LIVIR
50-- Anchoo mitchilli 0-0 1988
E 0-0 1989
E 45--

40 --

c
35.- 0

30--
0
_0
c 25--
0

20--

15-
1 2 3 4 5 6

55- Annual Mean Standard Length - LMR
Fundulus similis 0-0 1988
50 0-0 1989
E
45-- 0

40--
CP
35--
0
30--
C)
25--
V) 20--

15
2 3 4 5

55-- Annual Mean Standard Length - LMR
0-0 1988
50-- -CY-00aci norLu
Lio n gije _a. 0-0 1989

E 45--
-C 40-- 0
On
0
35-- 0

30--

_0
c 25-- 0
0

20--

S
Station

FI GURE 25

55-- Monthly Mean Stcndard Length LMR
50-- Cynoscion orencrius 0----0 EI-D July 1988
0-0 July 1989
E 45--
Z@-,!ni August 1988
40-- 0-0 August 1989
c 0
Q)
0 Z@
30-- 0
CD 2
_0
c: 25--
0
C/) 20--
15 Z@
1 2 4 5 6

Station

APPENDIX A

Common names of selected fishes from the Little Manatee River and

Cockroach Bay. All names base d on Robins et al. (1980)a.

Anchoa mitchilli bay anchovy
Brevoortia spp.b menhaden

Harengula jaguana scaled sardine

Opisthonema oglinum Atlantic thread herring

Fundulus seminolis Seminole killifish

Fundulus similis longnose killifish

Lucania goodei bluefin killifish

Lucania parv rainwater killifish

Gambusia affinis mosquitofish

Poecilia latipinna sailfin molly
Menidia spp.c silversides

Syngnathus scovelli gulf pipefish

CentroDomus undecimalis snook

Chloroscombrus chrysurus Atlantic bumper
Eucinostomus spp.d mojarras

Lagodon rhomboides pinfish

Bairdiella chrysoura silver perch

Cynoscion arenarius sand seatrout
Cynoscion nebulosus spotted' seatrout

Leiostomus xanthurus spot

Sciaenops ocellatus red drum

Mugil cephalus striped mullet
Gobiosoma spp.e gobies

APPENDIX A (cont.)

Microgobius gulosus clown.goby

Trinectes maculatus hogchoker

aRobins, C. R., R. M. Bailey, C. E. Bond, J. R. Brooker,, E. A.

Lachner, R. N. Lea, and W. B. Scott. 1980. A list of common and

scientific names of fishes from the United States and Canada

(fourth edition). Amer. Fish. Soc., Spec. Publ. 12, 174 p.
bIncluding B. patronus and B. smithi.
cIncluding M. peninsulae and M. beryllina.
dIncluding E. harengulus and E. gula.
eIncluding G. bosci and G. robustum.

TASK III: PHYSIOLOGICAL RESPONSES OF THE
SEAGRASS, Thalassia testudinum, -TO HYPOXIC STRESS AND LIGHT
REDUCTION.

INTRODUCTION

The critical habitat value of seagrass meadows has been
demonstrated f or hundreds of f ish and invertebrate species,
prompting concern over worldwide declines in seagrass bed area
wherever coastal areas and estuaries are exposed to human
development. Dramatic losses of seagrasses have occurred in West
Australia, the Caribbean, Europe, and the continental United
States. Within the United States, extensive declines of
seagrass beds have been documented in the Northeast United
States, Chesapeake Bay, and Florida.

The decline of seagrasses in Florida has occurred at an alarming
rate. Previous research by DNR personnel, funded by the CZM
program, has'-documented seagrass losses in Tampa Bay, Charlotte
Harbor, and the Indian River. Areal declines in seagrass beds
have been estimated at one third for Charlotte Harbor and one
half for Tampa Bay for the 40 years prior to 1982. Seagrass
losses have also occurred in the Indian River lagoon.

While some Florida seagrass beds have been lost directly to
dredge and f ill, much of the loss has been due to gradual "die-
back" of seagrass beds in response to poorly-understood stresses.
We use the term "die-back" to describe the gradual decrease in
size, density, and productivity of seagrass beds. For reasons
which are not clear, turtle grass, Thalassia testudinum, appears
to be more susceptible to die-back than the other two seagrass
species (Halodule wrightii and Syringodium f ilif orme) . The
mechanism most frequently suggested as the cause of seagrass die-
back is decreased productivity due to shading. Shading, in turn,
may result from sediment resuspension, phytoplankton blooms, or
epiphyte growth. All of these processes, in turn, may be
accelerated or exacerbated by human activity, perhaps explaining
the anthropogenic contribution to seagrass dieback.

Our research has studied the etiology of seagrass die-back
processes, based on the underlying hypothesis that natural and
anthropogenic stressors, such as shading, cause seagrass die-back
by induction of hypoxia (ie. suffocation) or sulfide toxicity in
roots or rhizomes. Significant results of CZM-funded research to
date in our lab include: 1. Demonstration of sulfide uptake and
detoxification by seagrasses using stable sulfur isotope ratios
of plant tissue; 2. Thalassia tolerates sediment sulfide
concentrations as high as 3 millimoles per liter, considerably
more than typically occurs in sediments of Tampa Bay, Charlotte
Harbor, or Indian River. 3. Thalassia rhizomes in Tampa Bay,
Charlotte Harbor, and Indian River have high levels of ethanol

and an enzyme which catalyzes ethanol production (alcohol
dehydrogenase, ADH) , suggesting that, hypoxic stress occurs
frequently. We conclude that, while- Thalassia is able to
detoxify sulfide and survive h@poxic stress under normal
conditions, chronic stress, natural or anthropogenic, may cause
die-back.

OBJECTIVES

To better understand the adaptation and capacity of Thalassia
testudinum and other seagrass species to hypoxia and synergistic,
chronic stresses, we outlined three sub-tasks for research this
fiscal year.

1. Development and refinement of physiological analysis
techniques.

Total free amino acid (TFAA)- concentrations in rhizome tissue
are of great interest because 1. free amino acids may be involved
in hypoxic stress responses and 2. qualitative amino acid
analyses are-.--tedious and expensive. No published technique has
proven satisfactory for the simultaneous analysis of primary and
secondary amino acids in the same sample, so we modified two
existing techniques to make a single procedure which gives
reliable estimates of both primary and secondary amino acids on
the same sample.

A number of different solvents and treatments have been described
in the scientific literature for extraction of amino acids and
other proximate constituents from plant and animal tissue. There
seem to be important quantitative and qualitative differences
among procedures, so we also tested the efficiency of several
extraction solvents and treatments in extracting amino acids from
freeze-dried Thalassia rhizome tissue.

2. Field experiments to test the synergistic effects of shading
on rhizome hypoxia.

Two field experiments were conducted during this fiscal year. In
July 1989, we performed a short-term experiment, using a
complete, randomized-block design to test the effects of rhizome
severance, water column anoxia, and shading on Thalassia.

We also performed ethanol and ADH analyses on a long-term
Thalassia shading study performed by other FMRI researchers.
The study began in March 1989 and was sampled for several
growth-related parameters. We sampled hypoxic metabolites on 7
September 1989 to take advantage of shortening daylengths and
warm water temperatures which enhance hypoxic stress.

3. Laboratory experiments were also carried out to examine the
hypoxic stress responses of the three seagrass species Thalassia
testudinum, Halodule wrightii'J. and Syringodium filiforme, under
controlled conditions.

The results of three such experiments are reported below. The
first experiment tested differences in aerobic respiration rates
and hypoxic responses of Thalassia rhizome apices and mature
segments. The second experiment focused on the anaerobic ethanol
production rates of Thalassia, while the third measured aerobic
respiration rates and anaerobic ethanol production rates of all
three seagrass species.

METHODS

1. Physiological Analysis Techniques

Total Free Amino Acid Concentrations (TFAA)- Our technique uses
o-phthaldialdehyde (OPA) to create a product with amino acids
which can be detected by fluorescence with an excitation
wavelength of 405 nm and an emission wavelength of 450 nm.
Because OPA reacts only with primary amino acids, we use sodium
hypochlorite (NaOCl) to oxidize secondary amino acids, such as
proline and hydroxyproline, to primary amino acids.

Freeze-dried Thalassia rhizome tissue was extracted with four
solutions: 70% ethanol, 3.75% sulfosalicylic acid, 0.1 N sulfuric
acid, and 1.0 N sulfuric acid. Each of these extractions was
performed under five treatment conditions: room temperature for
one hour, room temperature for four hours, overnight at 40 C,
sonication for two minutes followed by one hour at room
temperature, and microwaving followed by one hour at room
temperature. Extraction of 5-10 mg of tissue with 1.0 ml solvent
was performed in 1.8 ml polypropylene micro-centrifuge tubes.

After extraction, tubes were centrifuged, and supernatant (50 ul)
from each microcentrifuge tube was transferred to each of two
fluorometers cuvettes containing 2.5 ml distilled water. OPA
reagent (2.5 ml) was added immediately to one cuvette of each
pair for the analysis of primary amino acids. secondary amino
acids (proline and hydroxyproline) were measured in the other
cuvette by adding sodium hypochlorite buffer (100 ul) and
microwaving for 20 seconds before addition of OPA reagent. The
fluorescence of the OPA/amino acid complex was measured using a
Turner Model 111 fluorometer with F4T5B lamp, 7-60 primary
.filter, and paired 5-60 and 3 secondary filters.

2. Field Experiments

The short-term experiment used a complete, randomized-block,
experimental design to test the 6f f ects of three variables on
rhizome gas concentrations and hypoxic stress. The variables
tested were 1. presence or absence of light, 2. water column
oxygen status, and 3. rhizome integrity. Light was excluded from
dark treatments by inverting an opaque 5-gallon bucket over a
circular patch (30 cm diameter) of seagrass bed; light treatments
had no bucket over them. Water column oxygen concentrations were
manipulated by covering patches of seagrass with clear plastic
sleeves: we anticipated that oxygen dissolved in water within the
sleeves would be rapidly depleted at night. Dark/Aerobic
treatments were covered by inverted, opaque buckets through which
ambient water was circulated by small, submersible bilge pumps.
Rhizome integrity was disrupted by enclosing plots with buckets
and cutting rhizomes around the exterior perimeter of buckets.
Two replicate 5-gallon buckets were used for each treatment.
Buckets were placed over seagrass plots at 1300-1500 h one day,
and samples were harvested from each bucket the following
afternoon.

We also sampled ADH and ethanol concentrations in Thalassia
rhizome tissue from a long-term shading study. Six replicate
plots of Thalassia, 3 in approximately 1.0 m deep water and 3 in
approximately 1.8 m deep water, were shaded with neutral density
screen. Shade treatments began March 1989, and we sampled
rhizome tissue in September 1989.

3. Laboratory Experiments

Methods for all seven lab experiments were similar. Rhizomes with
an intact apex and at least two photosynthetic short shoots were
collected from Tampa Bay or Florida Bay seagrass beds. Rhizome
segments were surface-sterilized by immersion in 10%
Chlorox/seawater and antibiotics (polymixin/nitrofurantion, 250
mg of each per liter ASW).

Tissues were incubated in 10 glass, closed, 20-ml syringes with
air headspaces for 24 hours before being flooded with a helium
headspace to induce hypoxic stress. syringes were incubated in
the dark, immersed in seawater to maintain temperature stability
and reduce diffusive fluxes between the syringe headspace and the
atmosphere.

Headspace gas concentrations were monitored periodically by gas
chromatography. In early experiments, ethanol production was
measured in the headspace of the syringe, as well. Howeverf
tissue was harvested for ethanol in later incubations.

4. Statistical Analyses- for all experiments were performed using
one- and two-way analyses of variance and Duncan's multiple range
tests (SAS Institute, 1987).

RESULTS AND DISCUSSION

1. Physiological Analysis Technicrues (TFAA)-

OPA (o-pthalaldialdehyde) is typically used f or pre- or post-
column derivatization of amino acids for HPLC. However, our
adaptation of the reagent to a manual technique produced
reproducible, linear, standard curves for all primary amino acids
tested in the concentration range from 0.5 to 40 umoles/liter
(Figure 1.1). Slopes of standard curves for glutamine, glutamic
acid, arginine, glycine, and alanine were not signficantly
different, especially when the OPA reagent was made freshly each
morning. The F4T5 lamp, used with the 7-60 primary filter, gave a
higher blank value than the F4T4 lamp. The F4T5 lamp was chosen
for the analysis because it caused less rapid degradation of the
fluorescent OPA-amino acid product. Minimum b@lank values were
obtained using freshly-made OPA reagent and double-distilled
water for dilution of samples.

Standard curves -for proline determined by hypochlorite oxidation
before reaction with OPA had slopes approximately 1/3 those of
primary amino acids. Yield was not significantly altered by
changing the strength or volume of oxidizing buffer or by
increasing the microwave exposure time. The consistency of the
@slopes for the proline standard curve, however, suggested that 1.
oxidation of proline by hypochlorite was quantitative, but 2. the
proline-OPA product may have had less intense fluorescence.
Approximately 7% of the primary amino acid remained after
oxidation, making it necessary to correct calculated
concentrations of secondary amino acids for residual primary
amino acids.

Results of the extraction experiment (Table 1.1) showed that no
single combination of solvent and treatment yielded the highest
recovery of both primary and secondary amino acids from Thalassia
rhizomes. Greatest recoveries of primary and secondary amino
acids from Thalassia rhizome tissue were obtained by sonication
with sulfosalicylic acid (3.75% aq@ and extraction with sulfuric
acid (1.0 N) for 24 hours at 4, C, respectively. The latter
treatment, however, was unsuitable because it significantly
decreased recoveries of primary.amino acids.

The two techniques yielding the best overall extraction
efficiencies for both primary and secondary amino acids were 1)
sonication with 3.75% sulfosalicylic acid and 2) sulfuric acid
(1.0 N) extraction at room temperature for 1 hour. The
sulfosalicylic acid technique recovered 100% and 87.4% of
primary and secondary amino acids, respectively. Sulfuric acid
(1N) held at room temperature for 1 hour extracted 88.1% of the
primary amino acids and 97.9% of the secondary amino acids. The
overall extraction efficiencies of the two techniques were 94.9%
for 1 N sulfuric acid and 91.2% for sulfosalicylic acid.

R
U'- E D
E.

4- 1

C:1

4,
I.J

i rT
Lj 4-

FIGURE 1.1: STA NDARD DURVES FOR AMINO ACIDS MEASURED WITH OPA. Upper curve F4T5 lamp with
7-60 primary filter. Lower curve - F4T4 lamp with 7-60 and 1% neutral density
filters.

TABLE 1. 1: EFFECT OF EXTRACTION SOLVENT AND TREATMENT ON AMINO ACID RECOVERY FROM THALASSIA RHIZOMES
Data are means of three replicate samples expressed as micromoles amino acid per gram dry weight rhizome
Within each group of amino acids, numbers with the same postscript are not significantly different.

TREATMENT

Room Temperature 24 Hours
Solvent 1 Hour 4 Hours sonicate microwave at 40C

A. Primary Amino Acids

Ethanol (70%) 104.9 f 122.3 de 122.6 de 80.5 g 116.7 ef

H2SO4 (0.1 N) 146.3 ab 144.2 abc 147.2 ab 141.4 abc 134.6 bcd

H2SO4 (1.0 N) 136.4 bcd 140.5 abc 134.7 bcd 140.6 abc 134.4 bcd

Sulfosalicylic 144.4 abc 148.3 ab 154.9 a 128.3 cde 138i9 abcd
Acid (3.75%)

B. Secondary Amino Acids

Ethanol (70%) 182.0 ef 113.1 hi 145.5 fgh 90.1 i 172.8 ef

H2SO4 (0.1 N) 203.9 e 112.6 hi 184.6 ef 124.5 ghi 172.7 ef

H2SO4 (1.0 N) 351.8 ab 199.7 e 321.8 bc 201.4 e 359.5 a

Sulfosalicylic 286.4 cd 166.4 ef 314.1 c 158.8 fg 270.9 d
Acid (3.75%)

2. Field Experiments-

The short-term experiments performed at Fort Desoto, July 19,
1989 demonstrated the physiological integration of Thalassia
short shoots (Table 1-2). Light/dark treatments had only
marginally significant effects on rhizome oxygen concentrations
and no effects on rhizome carbon dioxide and methane. Restricted
circulation in the water above the experimental plots
(open/closed treatments) had virtually no effect on rhizome carbon
dioxide and oxygen and a very small effect on rhizome methane.
cutting rhizome connections around the perimeter of each bucket,
however caused dramatic effects on all three gases within
Thalassia rhizomes. These data indicate a high degree of
physiological integration among short shoots along a given
rhizome, allowing photosynthetically-active short-shoots to
support the oxygen needs of rhizome apices growing at depth in
the sediments.

Responses of Thalassia to the field shading treatments were mixed
(Table 1.3). Although Hall (et al.) found statistically
significant differences in turnover time of above-ground biomass
between their deep shade treatment and all other treatments,
there were no significant differences in rhizome ADH activity
among the treatments. Ethanol was undetectable in all but three
samples from the 'entire experiment and showed no significant
day/night or treatment-related differences.

Lack of hypoxic stress responses in the shading experiment may be
due to the high wave energy, coarse-grained sediments, and low
turbidity at this site. Even Thalassia in the deep shade
treatment at this site may receive sufficient light to meet the
respiratory needs of its belowground tissue, especially if the
chemical and biological oxygen demand of the sediments is low.

Turnover times of above-ground biomass from this site and a
turbid, low-energy site sampled by Carlson and Acker (1985)
support this hypothesis. Turnover times measure the time
required for the plant to replace its total inventory of leaf and
shoot material; healthy, fast-growing plants generally have low
turnover times. When plants are stressed, turnover times
increase as the res ult of slower growth rates and longer
retention times for leaves. At the low-energy site, significant
growth reduction occurred within 3 weeks after shade treatments
,began. At the present site, 6 months elapsed before significant
changes in turnover time developed. Furthermore, the turnover
times for unshaded, control treatments at the low-energy site
were comparable to the deep shade treatment at the high-energy
site. Turnover time of shaded Thalassia at the low-energy site
was double that of the deep shade treatment and five times
greater than the shallow shade treatment.

TABLE 1. 2: ANALYSIS OF VARIANCE FOR SHORT-TERM HYPOXIA FIELD
EXPERIMENTS. Fort DeSoto, July 19, 1989. A. Analyses of variance-
Data are F-Ratios and p-values; Values of p < 0.05 denote significant
effects of independent variable (treatment) on dependent variables (gas
concentrations). B. Multiple Range Tests- Data are gas concentrations;
values within each horizontal line which have the same letter subscript
are not significantly different.

A. Analysis of variance

Rhizome Gas Concentration

Treatment carbon Dioxide Oxygen Methane

F-Ratio P F-Ratio P F-Ratio P

Light/Dar.k.-,. 0.03 0.86 21.84 0.11 1.25 0.28

Aerobic/Anoxic 0.00 0.99 0.00 0.96 1.17 0.29

Rhizome cut 5.58 0.03* 7.56 0.01* 19.7 0.0003*

B. Multiple Range Tests

Treatment

Parameter DCC DCU DOC DOU LCC LCU LOC LOU

Methane 6.5 3.2 5.6 2.4 nd 2.3 4.4 1.9
a abc ab bc bc abc C

Oxygen 13.4 13.5 6.2 20.6 nd 22.1 15.2 23.1
ab ab b a a ab a

Carbon 6.6 7.3 11.5 2.9 nd 5.4 8.5 4.6
Dioxide ab ab a b ab ab ab

TABLE 1.3: GROWTH AND PHYSIOLOGICAL CHARACTERISTICS OF SHADED Thalassia
testudinum. Tampa Bay shading study sampled September 5-9, 1989.
Numbers within each column which have the same letter postscript are not
significantly different.

Parameter
ADH Activity Ethanol Turnoverl Turnover2
Site Treatment (umol/gFW min) (umol/gFW) (days) (days)

Shallow Control 4.17 a ud 30.2 a 118 a

Shade 4.27 a ud 49.9 a 227 b

Deep Control 4.61 a ud 44.7 a --

Shade 4.18 a ud 112.4 b

2 Hall, Tomasko, and Courtney (in preparation)
Carlson and Acker (nearby site, 1985)

3. Laboratory H Doxia Experiments-

In initial laboratory experiments (Table 1.4), rhizome alcohol
dehydrogenase (ADH) activity was Significantly higher in mature
rhizome segments exposed to anaerobic conditions for 96 hours
than initial samples or rhizome tissue incubated in air for a
comparable period. Over 96 hours, however, apical ADH activity
declined significantly from initial values. ADH activity of
mature and apical tissue incubated in air for 96 hours were not
signficantly different from initial values. This experiment
demonstrated 1) that ethanol production is the primary adaptive
strategy of Thalassia for tolerating rhizome hypoxia, but 2) the
capacity of rhizome apices to sustain prolonged periods of stress
is less than that of mature rhizome segments.
Estimation of rhizome ethanol concentrations from the
concentrations in syringe headspace proved unreliable because of
the high solubility of ethanol in water. If any water was
present in a syringe, the water rapidly scavenged ethanol from
the headspace. Subsequent experiments relied on destructive
sampling of the rhizome tissue at the end of each incubation
and/or sequential harvest of tissue during the incubation.

Experiments using sequential harvest of rhizome tissue were very
successful. The first experiment used only apical tissue from
Thalassia rhizomes (Figure 1.2), and segments were harvested at
varying intervals from 1 to 48 hours. Mean ethanol production
rate for the experiment was 1.1 umoles per gram fresh weight
rhizome per hour. Anaerobic carbon dioxide production rates were
0.87 umoles/ gram/ hour, suggesting slight losses of C02 to
dissolution in the water present.

Preliminary experiments comparing mature rhizome segments of
Halodule, Syringodium, and Thalassia demonstrated signficant
rates of ethanol production under anaerobic conditions for all
three species (Figure 1.3). Halodule rhizome segments had he
highest ethanol production rates (1.73 umoles gFW 1 hour_@),
Syringodium was intermediate with 0.85 umoles gFW-1 hour-1 . and
Thalassia had the lowest rates (0.61 gFW_1 hour-1). Lower rates
for Thalassia in this experiment than the previous experiment
probably resulted from lower incubation temperatures (250C vs
300C).

CONCLUSIONS

Ethanol production (fermentation) is an extremely primitive and
costly strategy for tolerance of anoxia, yet it is consistent
with the taxonomic ranking of Thalassia in the botanical family
Hydrocharitaceae. This family includes many seagrasses and
aquatic macrophytes. Its costliness arises from the fact that
each mole of glucose which is oxidized anaerobically will produce
only 2 moles of ATP for cellular metabolism rather than 38 moles
of ATP produced by aerobic respiration. At the same time,
ethanol is auto-toxic to plant tissue, so many ethanol-producing

TABLE 1. 4 ETHANOL AND ALCOHOL DEHYDROGENASE PRODUCTION IN RHIZOMES OF
Thalassia testudinum. Rhizome Hypoxia Experiment 2. Aerobic and
anaerobic incubations were. held for 96 hours in glass syringes filled
with air and helium, respectively.' ADH activity is expressed as umoles
ethanol per gram fresh weight rhizome tis.sue per minute; ethanol
concentration as umoles per gram fresh weight rhizome tissue.

Treatment

Parameter/ Tissue Initial Aerobic Anaerobic

Alcohol Dehydrogenase Activity

Rhizome Apex 4.89 bc 4.44 b 2.34 c

Mature Rhizome 3.68 bc 3.06 bc 8.16 a

Headspace Ethanol

Rhizome Apex nd 0.01 0.51

Mature Rhizome nd 0.07 0.83

...... ....... . ...... ..... ........... ... ... . . ... . ..

..... ...... ... . .... .
.... ..... ..... ... - - .... . .... ..

Figure 1.2: TIME COURSE PRODUCTION OF ETHANOL BY THALASSIA RHIZOMES IN HELIUM ATMOSPHERE.

Li I
-.1 f 11 -- @ f 11
A
E-jlH,-L'-J%1@'L PR Dl U

Halodule

Syringodium

Thalassia

FIGURE 1.15: PRODUCTION OF ETHANOL BY SEAGRASS RHIZOMES IN HELIUM ATMOSPHERE.

species have adapted to allow ethanol to diffuse rapidly from
their roots into the surrounding sediments or water. Ethanol
diffusing into seagrass sediments may also exacerbate sulfide
stress by stimulating anerobic sulfate-reducing bacteria.

organisms in fluctuating environments typically possess both
avoidance and adaptive responses to stressors. For example,
mobile organisms exposed to hypoxic water may first avoid stress
by leaving the area. However, if an extensive area is affected,
these same organisms may become quiescent and lower their
respiratory rates in response to lowered oxygen concentrations in
the water. Not all,organisms have evenly balanced avoidance and
adaptive strategies for stressors; frequently one strategy,
either avoidance or adaptive, dominates within an organism.

The reliance of Thalassia on fermentation as a adaptive response
to anoxia may result from its well-developed adaptations for
avoiding anoxia. Thalassia possesses a well-developed system of
air spaces (lacunae or aerenchyma) which provide a continuous
path for photosynthetically-produced oxygen to diffuse to
belowground tissue. Under all but the most extreme conditions,
this mechanism protects belowgroung tissues from hypo .xic
conditions in surrounding sediments. However, when respiratory
rates are high and oxygen production is minimal (e.g., late
summer nights) , fermentation provides a short-term adaptive
response and maintains tissue viability.

We must also consider the possibility of endosymbiotic micro-
organisms in seagrass roots and rhizomes which oxidize ethanol
and prevent autotoxicity within the plant. Ethanol-oxidizing
symbionts would explain discrepancies between potential ADH
activities measured in rhizome tissue and rates of ethanol
production in laboratory incubations of root and rhizome tissue.

A. E'f feet of carbon source on Thalassia growth and carbon
isotopic composition.

A general assumption in past studies using stable isotope

compositions of organic matter to trace carbon f low in ecosystems is

that the isotopic compositions of organic matter sources are

distinctive and relatively invariate (Benner et al., 1987). However,

seagrass carbon isotopic composition is subject to variation at

several levels and these variations may lead to ambiguities in

assessing their trophic importance (Fry et al., 1987). Both

laboratory and field studies suggest that this variation may be due to

isotopic changes in dissolved inorganic carbon (McMillan and Smith,

1982; Zieman et al., 1965). The goal of this research task is to

elucidate, in a more definitive manner, the magnitude (and possibly

the mechanism) of these effects. Two approaches have been employed.

The first approach has been to culture Thalassia seedlings in natural

sediments and ashed sediments ammended with heavy end member (dried
Thalassia leaves, del 13C=-6 to -12 ppt) and light end member (dried
Aviccenia, del 13C= -25 to -30 ppt) organic matter. Other treatments

include no amendment (control), a standard growth media (Ji ffy-7 peat
pellets, del 13C= -27.ppt), and ashed sediments bubbled with C02 gas,
which is isotopically very light (del 13C=-40 to-60 ppt). This last

treatment was used to induce a maximum potential shift effect.

Because of the presence of microorganisms in the above system,

observed patterns may be affected by the extent of carbon cycling and

the relative contributions of DIC versus DOC. Therefore a second

experimental system was employed which used a similar experimental

design as above, except with sterile media and axenic seedlings. The

results from this series should allow for the determination of source

(DIC vs DOC) versus process (i.e. remineralization) effects.

Growth, as determined from green leaf area measurements (Durako

and Moffler, 1981), was monitored monthly. After threel six, and

nine months in culture, four seedlings from each treatment were

harvested for biomass determinations. overlying water and new leaf
material was. also sampled and the del 13C values of DIC and organic

matter was determined using standard methods.

RESULTS

Biomass data f rom aquarium cultures indicate a high degree of

variability in biomass accumulation and resource allocation patterns

(Table 1). The decrease in biomass between 3 and 6 months in culture

was the result of a breakdown of the temperature control equipment in

the culture room. This resulted in extreme temperature fluctuations

for a several'da y period and the seedlings were visibly stressed. The

continued decline in biomass from 6 to 9 months indicates that the

seedlings never fully recovered from the earlier stress event. Growth

(as biomass accumulation) was highest in the natural sediment

treatment at 6 months, however, by 9 months biomass was comparatively

greater in both amended-sediment treatments and in the ashed

sediments. The relativley high root:shoot (R:S) ratios inthe ashed

sediment and natural sediment treatments indicate that these seedlings

may be experiencing some type of nutrient limitation. Relatively good

growth was also evident in the Avicennia-ammended sediment treatment

and these seedlings had low R:S ratios indicating nutrient

sufficiency.

Stable carbon isotope data from the aquarium treatments reveals

the influence of carbon source and concentration on seedling isotope

13
signatures (Table 2). Del C values for the peat pellets and the

Avicennia leaves are about -26 ppt, compared to the value for the

Thalassia leaves of about -10 ppt. The leaves of the seedlings were

1.5-2.0 ppt lighter in the former treatments compared to the latter

(mean= -13.1 and -13.5 compared to -11.54), after 6 months in culture.

However, after 9 months seedlings in the Tha lass ia-amended sediment

treatment were lighter (mean=-22.2 compared to -18.3 and -21.0).

The importance of dissolved inorganic concentration (DIC)'is most
clearly seen in the C02 bubbled and control treatments. The dell3c
value for the C02 gas used for the first three months was -11.3 ppt
(surprisingly heavy and due to the synthetic s ource of the gas,' a

problem which was corrected at month 3 with gas from another
supplier). This del13C value is almost the same as the normal value
for Thalassia. However, the dell3C values for the seedlings in this

treatment were very light (mean= -24.67). The bubbling resulted in 4-

fold increase in DIC, and the much lighter carbon isotope values of

the seedlings reflect greater isotopic descrimination at the enzyme

level. In contrast, DIC concentrations were lowest in the control

treatment and the seedlings in this treatment had relatively heavy

carbon isotope signatures. In fact, the trend in isotopic
discrimination (del del13C the difference between the DIC and the
plant dell3C values) in all treatments corresponded closely with the

differences in DIC concentrations (increasing as [DIC] increased),

suggesting differing degrees of carbon limitation. The increase in

discrimination may also reflect a decreasing carbon contribution from
stored seed reserves (del 13 C of seed approximate'ly -7 ppt).

Biomass data from axenic tube cultures indicate that no root

production in media with org anic'carbon additions (Table 3). There

was also little biomass difference between the light and dark

treatments suggesting the seedlings were using stored seed reserves

for most of their growth. Seedlings in sucrose-amended Von Stosch media

accumulated more biomass after 3 months in culture, but. after 6

months they had less biomass, especially in the shoot fraction, than

seedlings in unamended VS media.
Del 13C data from the axenic seedlings reveals definite

assimilation of sucrose (Table 4). Seedlings in both the 1 and 3%
enriched media -had del13C values that were significantly more negative

than the other treatments. There also seems to be additional isotopic

discrimination in the light versus dark-cultured seedlings. Because

of the low number of surviving axenic seedlings in the Thalassia and

Avicennia enriched media it's impossible to state if there was an
effect in the del 13C signature.

These results, while preliminary, do show the high degree of

variability which may occur in stable carbon isotope composition of

Thalassia (range observed in this work: -4.5 to -57.1 ppt PDB). The

interaction between organic-carbon sources and DIC concentration on

this species' stable carbon isotope signatures may help in

understanding its physiological characteristics and needs to be

understood before this technique can really be used to trace organic

carbon through food webs.

Table 1. Biomass (mg) and resource allocation patterns in
Thalassia aquarium seedling cultu res [means S.D.), n=4].

Treatment Age Root Shoot Seed Total Seedling Root
(months) (root+shoot) Shoot

Natural 3 83.1 69.8 156.1 309.0 152.9 1.19
sediments (26.7) (10.5) (62.2)
6 60.4 58.3 99.3 218.0 118.7 1.04
(14.8) (22.9) (42.5)
9 39.4 44.8 42.4 126.6 84.2 0.87
(19.6) (10.9) (8.3)

Peat pellets 3 46.9 45.9 74.3 167.1 92.8 1.02
(18.0) (5.8) (15.7)
6 27.2 44.2 49.8 121.2 71.4 0.64
(7.7) (8.9) (17.4)
9 31.1 51.4 36.7 119.2 82.5 0.64
(9.2) (23.4) (7.3)

Ashed 3 31.8 61.7 86.4 179.9 93.5 0.51
sediments (24.0) (6.6) (6.0)
+ C02 6 31.6 46.0 65.8 143.4 77.6 0.69
(7.8) (8.3) (17.9)
9 31.1 24.6 42.4 98.1 55.7 1.26

Ashed 3 28.8 70.5 169.9 269.2 99.3 0.41
sediments (12.4) (41.1) (202.4)
+ Avicennia 6 46.6 77.8 55.2 179.6 124.4 0.60
(17.0) (21.1) (4.9)
9 35.2 69.9 49.8 154.9 105.1 0.50
(17.5) (17.2) (5.4)

Ashed 3 19.5 48.0 45.6 113.1 67.5 0.41
sediments (14.2) (19.1) (15.2)
+ Thalassia 6 35.3 66.4 64.8 166.5 101.7 0.53
(16.2) (18.1) (26.3)
9 47.7 64.5 43.0 155.2 112.2 0.74
(23.9),, (8.6) (12.4)

Ashed 3 57.6 42.6 65.0 165.2 100.2 1.35
sediments (20.3) (14.2) (21.3)
6 50.1 50.4 58.3 158.8 100.5 0.99
(6.7) (10.0) (17.8)
9 50.4 50.8 45.1 146.3 101.2 0.99
(10.7) (14.6) (6.3)

Table 2. Dell3C values (ppt of aquarium treatment water dissolved
(DIC), PD
inorganic carbon ang Thalassia seedling leaf tissue, and
relative isotopic discrimination.

Treatment Date pH (C02] dell3c dell3c Del-del
(mM) carbonate leaf

Natural 8/16/88 7.53 2.25 -10.1 - 9.1 1.0
sediments 11/22/88 8.31 1.71 -11.5 -13.3 (1.0) - 1.8
2/23/89 8.31 1.65 -10.6 -16.7 (1.6) - 6.1
5/09/89 8.03 2.23 -12.5 -20.1 (1.8) - 7.6

Peat 8/16/88 8.18 2.18 - 7.0 - 9.1 - 2.1
pellets 11/22/88 8.33 2.00 - 9.8 -13.1 (1.5) - 3.3
2/23/89 8.28 2.04 - 9.7 -17.8 (3.2) - 8.1
5/09/89 8.09 3.35 6.0 -18.3 (1.8) -12.1

Ashed __8/16/88 7.64 2.21 8.2 9.1 - 0.9
sediments 11/22/88 7.00 11.11 -11.3 -24.7 (1-2) -13.4
+ C02 2/23/89 7.10 16.32 -39.9 -50.8 (9.0) -10.9
5/09/89 7.97 13.39 -52.8 -57.1 - 4.3

Ashed 8/16/88 8.00 1.99 - 8.8 - 9.1 - 0.3
sediments '11/22/88 8.47 2.94 - 9.2 -13.5 (1.2) - 4.3
Avicennia 2/23/89 8.28 1.51 -13.0 -18.8 (2.4) - 5.8
5/09/89 8.37 1.78 -15.4 -21.0 (1.3) - 5.6

Ashed 8/16/88 8.13 2.02 - 9.4 - 9.1 0.3
sediments 11/22/88 8.40 2.11 - 8.4 -11.5 (1.1) - 3.1
+ Thalassia 2/23/89 8.39 2.05 -11.6 -16.6 (3.7) - 5.0
5/09/89 8.12 2.68 -13.2 -22.2 - 9.0

Ashed 8/16/88 8.21 1.89 - 9.1 - 9.1 0.0
sediments 11/22/88 8.64 1.65 -11.8 -11.9 (1.4) - 0.1
2/23/89 8.24 1.23 - 9.0 -17.2 (1.4) - 8.2
5/09/89 8.00 3.12 -11.2 -19.2 (1-7) - 8.0

mean S.D.)
Value estimated 'assuming equilibrium with C02 gas (dell3c= -
11.3 ppt) used for bubbling.

Table 3. Biomass (mg dwt) and resource allocation patterns in axen
Thalassia seedling cultures [mean S.D.)].

Treatment Age Root Shoot Seed Total
Von Stosch (months)
light 3 1.5 16.0 69.9 87.4
(3.0) (13.3) (40.0)
6 5.8 46.1 54.3 106.2
(7.5) (12.1) (20.7)

dark 3 - 19.8 54.9 74.7
(9.0) (17.6)
6 0.8 51.2 60.9 113.2
(1.5) (16.2) (22.7)
VS + 1% sucrose
light 3 - 13.0 129.9 142.9
(7.5) (85.3)
6 - 16.3 59.1 75.4
(5.7) (22.6)

dark 3 - 13.0 71.9 84.9
(2.7) (33.1)
6 - 14.5 48.5 63.0
VS + 3% sucrose (7.0) (6.2)
light 3 - 10.7 113.6 124.3
(4.1) (37.5)
6 - 14.9 54.7 69.6

dark 3 - 14*9 93*5 108*4
(5.6) (13.3)
6 - 17.2 87.8 105.0
(1.4) (34.9)
VS + 1% Thalassia leaves
light 3 - 31.0 77.4 108.4
(18.3) (31.2)
6 - 40.8 56.5 97.3
(25.0) (30.5)
dark 3 - 5.0 43.0 48.0
(3.3) (20.3)
6

Table 4. mean leaf del13C values S.D.) for axenic Thalassia
seedlings after 3 and 6 months in various culture media.

Treatment dell3C (Ppt PDB)
3 months 6 months
Von Stosch light - 7.2 (0.8) - 5.4 (1.2)
dark* - 5.2 (1.2) - 4.5 (1.7)
V9 + 1% Sucrose
light -17.3 (2.8) -18.0 (1.4)
dark -15.2 (1.2) -19.2
VS + 3% Sucrose
light -19.7 (1.4) -21.6
dark -14.8 (2.5) -12.5
VS + 1% Thalassia
light - 8.0 -
dark - 6.7 (0.8) -
VS + 1% Avicennia
i i ght- - 9.4 -
dark - 6.9 -

dell3C = -24.1
dell3c = -10.0
del13C = -26.6

References

BENNER, R., FOGE M-
,it-, . SPRAGUE E.K., HODSON, R.E. (1987).
Depletion of 'C in lignin and its imp1ications for stable
carbon isotope studies. Nature 329:708-710.

BITTAKER, HI.F., IVERSON, R.L. (1976). Thalassia testudinum
productivity: A field comparison of measurement methods.
Mar. Biol. 37:39-46.

DURAKO, M.J., MOFFLER, M.D. (1981). Variation in Thalassia
testudinum. seedling growth related to geographic origin.
pp. 100-117. In: STOVAL, R.H. (ed.): Proc. Eighth Annual
Conference ' on Wetlands Restoration and Creation.
Hillsborough Comm. College, Tampa, Florida.

DURAKO, M.J., MOFFLER, M.D. (1987). Nutritional studies of the
submerged marine angiosperm Thalassia testudinum. I. Growth
responses,of axenic seedlings to nitrogen enrichment. Amer.
J.Bot. 74:234-240.

FRY, B., MACKO, S.A., ZIEMAN, J.C. (1987). Review of stable
isotopic investigations of food webs in seagrass meadows.
Pp. 189- 209 In: DURAKO, M.J., PHILLIPS, R.C., LEWIS,
R.R. (eds.) : Subtropical-Tropical Seagrasses of the
Southeastern United States. Fl. Mar. Res. Publ. No. 42.
Fla. Dept. Nat. Resour. Bur Mar. Res. St. Petersburg,
Florida. 209 pp.

IVERSON, R.L., BITTAKER, H.F. (1986). Seagrass distribution and
abundance in eastern Gulf of Mexico coastal waters. Est.
Coastal Shelf Sci. 22:577-602.
MCMILLAN, C., SMITH, B.N. (1982). Comparison of del 13C values
for seagrasses in experimental cultures and in natural
habitats. Aquat. Bot. 14:381-387.

THAYER, G.U., USTACH, J.F. (1981). Gulf of Mexico wetlands:
value, state of knowledge, and research needs. Pp. 1-30.
In: Proc. Symp. Environ. Res. Needs in the Gulf of Mexico
(GOMEX). U.S. Dept. Commerce, Vol. II B.

ZIEMAN, J.C. (1982). The ecology of the seagrasses of south
Florida: A community profile. U.S. Fish and Wildlife
Service, Office of Biological Services, Washington, D.C.
FWS/OBS-82/85. 123 pp.

ZIEMAN, J.C., MACKO, S.A., MILLS, A.L. (1985). Role of seagrasses
and mangroves in estuarine food webs: Temporal and spatial
changes in stable isotope composition and amino acid content
during decomposition. Bull. Mar. Sci. 35:380-392.

TASK IV: PUB LIC INFORMATION ON COASTAL WETLANDS AND CORAL REEFS

Subtask A: Distribution of Estuarine and Coral Reef Brochures

Efforts on Task IV, Subtask A, focused on continuing distribution
of the educational brochures on marine habitats. During the
period from January 1989 through September 1989, 63,156 brochures
were distributed. The totals listed below do not include
brochures distributed by laboratory personnel or those taken from
our reception area.

Cor,-@l Reefs 12,709

Estuaries 13,186

Seagrasses 12,170

Mangroves 13,134

Salt Marsh 11,957

63,156

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639 Ocean Avenue, Unit 108 305/289-1212 305/653-1200
Boynton Beach 33435 Florida Upper Keys C of C Opa-locka C of C
305/732-9501 P.O. Box 274-C P.O. Box 1014
Clewiston C of C Key Largo 33037 305/451-1414 Opa-locka 33054 305/681-7011
P.O. Box 275 Greater Key West C of C Pahokee C of C
Clewiston 33440 813/983-7979 402 Wall Street 115 East Main Street
Coconut Grove 33133 Key West 33040 305/294-2587 Pahokee 33476 305/924-5579
305/444-7270 Greater Lake Worth C of C Palm Beach C of C
Coral Gables C of C 1702 Lake Worth Road 45 Coconut Row
50 Aragon Avenue Lake Worth 33460 305/582-4401 Palm Beach 33480 305/655-3282
Coral Gables 33134 305/46-1657 Greater Lantana C of C Greater Plantation C of C
Coral Springs C of C 212 Iris Street 7401 Northwest Fourth Street
9767 West Sample Road Lantana 33462 305/743-8664 Plantation 33317 305/587-1410
Coral Springs 33065 305/752-4242 Greater Marathon C of C
Dania C of C 3300 Overseas Highway
P.O. Box 838 Marathon 33050 305/743-5471
Dania 33004 305/927-3377 Tri-City C of C
Davie/Cooper City C of C 6130 West Atlantic Boulevard
4185 Southwest 64th Avenue Margate 33063 305/972-0818
Davie 33314 305/581-07890
Deerfield Beach C of C
1601 East Hillsboro Boulevard
Deerfield Beach 33441
305/427-1050

'Chamber of Commerce 118

WHO TO CONTACT

Tourist Development Council
Manatee County
P.O. Box 321
Bradenton 33506 813/722-3900
Tourist Development Council
Charlotte County
P.O. Box 1398
Englewood 33533 813/474-7713
Tourist Development Council
Lee County
P.O. Box 2445
Fort Myers 33902-9990
813/335-2631
DeSoto County C of C'
P.O. Box 149
Arcadia 33821 813/494-4033
Bonita Springs Area C of C
P.O. Box 104
Bonita Springs 33923
813/992-2943
Cape Coral C of C
2051 Cape Coral Parkway
Cape Coral 33904 305/542-3721
Greater Pine Island C of C
P.O. Box 525
Matlacha 33909 813/283-0888
Englewood Area C of C
601 South Indiana Avenue
Englewood 33533 813/474-5511
Everglades Area C of C
P.O. Box E
Everglades City 33929
813/695-3941
Metropolitan Fort Myers C of C
P.O. Box CC
Fort Myers 33902 813/334-1133
Fort Myers Beach C of C
P.O. Box 6109
Fort Myers Beach 33931
813/463-6451
Immokalee C of C
P.O. Drawer C
Immokalee 33934 813/657-3237
Lehigh Acres C of C
P.O. Box 757
Lehigh Acres 33936 813/369-3322
Marco Island C of C
P.O. Box 913
Marco Island 33937 813/394-7549
Naples Area C of C
1700 North Tamiami Trail
Naples 33940 813/262-6141
Charlotte County C of C
P.O. 2702 Tamiami Trail
Port Charlotte 33952 813/627-2222
Sanibel-Captiva Islands C of C
Causeway Road
Sanibel Island 33957 813/472-1080

*Chamber of Commerce 92

WHO TO CONTACT
Citrus County Commission and Land o' Lakes C of C Greater Seminole Area C of C
Tourlst Development Council P.O. box 98 P.O. Box 3337
110 North Apopka street Land O'Lakes 33593 813/996-6470 Seminole 33542 813/392-3245
Inverness 32650 904/720-8500 Greater Largo C of C Sun City Center C of C
Tourlst Development Council P.O. box 326 P.O. Box 5,10,3
Pinellas County Largo 33540 813/584-2321 Sun City Comer 13571 8131634-5111
Newport Square #109A Longboat Key C of C Greater Tarpon C of C
2333 East Bay Drive 510 Bay Isles Road 11.0. box 420
Clearwater 33540 813/530-6452 Longboat Key 33548 Tampa 33601 8131228-7777
Greater Sarasota Tourism 813/383-1212 North Tampa C of C
Assoclatlon Madeira Beach C of C 11.0. box 8247
655 North larnlami 501 150th Avenue Tampa 13674 813/935-7200
33577 811/957-1877 Madeira Beach 33708 West Tampa C of C
Tampa/Hillsborough County 813/391-7373 105 West Columbus Drive
Convention & Visitors Bureau West Pasco C of C Tampa 33607
100 South Ashley Drive. 40 West Main Street Ybor City 1513 Eighth Avenue
Suite 850 New Port Richey *33552 Tampa '33605 81312,18-3712
Tampa 33601 813/223-1111 8 111842 -7651 Greater Tarpon Springs C of C
Manatee C of C Oldsmar C of C 528 Last Tafpon Avenue
P.O. Box 321 P.O. Box 521 Tarpon Spfings Avenue
Bradenton 33506 813/748-3411 Oldsmai 33557 813/536-5988 Tarpon Springs '335589 813 937-6109
Anna Marla Island C of C Greater Palm Harbor Area C of C Thonotosassa C of C
P.O. Box 336 1000 North U.S. 19 300 105 Main S11 eel
Bradenton Beach 33510 Palm State Bank Building Thonotosassa '33592 8131986-4241
8131778-1003 Palm Harbor 33563 8131784-4287 Treasure Island C of C
Greater Brandon C of C Pinellas Park C. of C. P.0. box 9284
408 West Brandon boulevard 5851 Park Boulevard Treasure Island 33706 813/360-1741
Brandon 33511 8131689-1221 Pinellas Park 33565 813/544-4777 Women's C of C of the Greater
Hernando County C. of C Gulf Beaches
101 East Fort Dade Avenue Greater Plant City C of C
11.0. Di awer CC P.O. Box 9206
Brooksville 33 5 12 9041796-2420 Plant, City 33566 813/754-3707 Treasure Island 33706
Greater Clearwater C of C South I'llilsborough, County C of C 813/392-4968
13.0. Box 457 3 15 U.S. Highway 4 1, South Venice Area C of C
Clearwater 33517 8131461 -0011 Ruskin '1357Q 813/645-3808 257 North TamlainiTrall
Pinellas Suncoast C of C Sa f ety Harbor C of C Venice 33595 813/488-2236
St. Petersburg/Clearwater Airport. 210 Main Street
Zephridlis C of C
Suite 239 Salety I larbor 33572 8131726-2890 691 Fifth Avenue
Clearwater 33520 813/53 1-4657 St. Petersburg Area C of C Zephyrhills 33599 813/782-1913
P.0. Box 1371
Citrus County Suncoast C of C
St. Petersburg 3 3 7 3 1
City/COUNTY Building
Crystal River 32629 904/795-3 149 913/82 1-4069
Greater Dade City C of C St. Petersburg Beach Area Cof C
Meridian bt Seventh Street P.O. Box 66375
Oode City 33 525 904/567-3769 St. Petersburg Beach 33736

Greater Dunedin C of C
434 Main Sueet Sarasota County C of C
Dumedin 33528 913/736-5006 P.O. Box 308
Homosassa Springs Area C of C Sarasota 33578 813/955-8187
P.O. 11ox 1098 Siesta Key C of C
Homosassa Springs 32047 P.O. Box 5 ( 8 8
904/628-2666 Sarasota 33579 8131924-9696
Greater Hudson Area C of C
710 Old Dixie Highway
Hudson 33507 813/868-9395
Holliday Isles C of C
P.O. Box 273
Indiain Rocks beach 33535
813/595-4575

WHO TO CONTACT

Tourist Development Council Groveland/Mascotte C of C Tavares C of C
Orange County P.O. Box 115 P.O. Box 697
7680 Republic Drive, Suite 200 Groveland 32736 904/429-3678 Tavares 32778 904/343-2531
Orlando 32819 305/345-8882 Greater Haines City C of C Umatilla C of C
Kissimmee/St. Cloud convention P.O. Box 986 P.O. Box 300
& Visitors Bureau Haines city 33844 813/422-3751 Umatilla 32784 904/669-3511
P.O. Box 2007 Kissimmee 32741 305/847-3174 Union Park 32817 305/277-5951
Kissimmee 32742 305/847-5000 P.O. Box 1982 P.O. Box 9080
Greater Seminole County C of C Kissimmee 32741 305/847-3174 Union Park 2817 305/277-5951
P.O. Box 784 Lake Alfred C of C Wauchula/Hardee County C of C
Altmonte Springs 32701 P.O. Box 956 P.O. Box 683
305/834-4404 Lake Alfred 33850813/956-1334 Wauchula 33873 813/773-6967
Apopka Area C of C Greater Lake Placid C of C Wildwood Area C of C
180 East Main Street P.O. Box 187 P.O. Box 1179
Apopka 32703 305/886-1441 Lake Placid 33852 813/465-4331 Wildwood 32785 904/748-2221
Auburndale C of C Greater Lake Wales C of C West Orange C of C
111 East Park Street P.O. Box 191 P.O. Box 522
Auburndale 33873 813/967-3400 Lake Wales 33853 813/676-3445 Winter Garden 32787 305/656-1304
Avon Park C of C Lakeland Area C of C Winter Haven Ara C of C
P.O. box 1330 P.O. Box 3538 P.O. Box 1420
Avon Park 33825 813/453-3350 Lakeland 33802 813/688-8551 Winter Haven 33880 813/293-2138
Greater Bartow C of C Leesburg Area C of C Winter Park C of C
P.O. Box 956 P.O. Box 269 P.O. Box 280
Bartow 33830 813/453-3350 Leesburg 32748 904/787-2131 Winter Park 32790 305/644-8281
Belleview/South Marion C of C Longwood/Winter Springs C of C
P.O. Box 602 P.O. Box 963
Belleview 32620 904/245-2178 Longwood 32750 305/831-9991
Sumter County C of C Maltland/South Seminole C of C
P.O. Box 158 110 North Maltland Avenue
Bushnell 33513 904/793-3099 Maltland 32751 305/644-0741
Clermont C of C Mount Dora C of C
P.O. Box 417 P.O. Box 196
Clermont 32711 904/394-4191 Mount Dora 32757 904/383-2165
Dunnellon Area C of c Greater Mulberry C of C
P.O. box 868 P.O. Box 254
Dunnellon 32630 904/489-2320 Mulberry 33860 813/425-1125
Eagle Lake C of C Ocala/Marion county C of C
P.O. Box 884 P.O. Box 254
Eagle Lake 33839 Ocala 32678 904/629-8051
Eustis C of C Orlando Area C of C
P.O. Box 1210 P.O. Box 1234
Eustis 32726 904/357-3434 Orlando 37802 305/425-1234
Lake County C of C St. Cloud 32769 305/892-3671
P.O. Drawer AZ P.O. Box 5
Eustis 32726 904/728-4955 St Cloud 32769 305/892-3671
Fort Meade C of C Greater Sanford C of C
P.O. box 91 P.O. Drawer CC
Fort Meade 33841 813/285-8253 Sanford 32771 305/322-2212
Frostproof C of C Greater Sebring C of C
P.O. Box 968 309 South circle
Frostproof 33843 813/635-4066 Sebring 33870 813/385-8448

Chamber of Commerce 64

Page No. 1
04/07/88
List for E & I letters

Name Title Organization Address City
Mrs. Donna Strickland Supervisor of Dept. Education, 620.E. University Gainesville
Science Environmental Ave.
Education
Mrs Burney Winkler Dir.of Curriculum FL Dept. Education, 582 North Temple Ave Starke
K-12 Environmental
Education
Mr. Jerry Edgar Director,Vocational FL Dept. Education, 425 E. Central Ave. Blountstown
Education Environmental 6-20
Education
Dr. Richard Crump Supervisor, FL Dept of 900 Walnut Street Green Cove
Secondary Education, Spring
Environmental
Education
Dr. James Yopp Director of FL. Dept. Education, Rt #7, Box 541 Lake City
Elementary Education Environmental
Education
Dr. Ronnie D. Kirkland Director of FL Dept Education, 392 South Blvd. East Macclenny
secondary Education Environmental
Education
Mr.Dave Howell Science Resource FL Dept, Education, 1274 south Florida Rockledge
Teacher Environmental Alit.
education
Alton Cheatham FL Dept Education, Peace River Charlotte
Environmental Elementary School Harbor
Education
Mrs Nancy Leaderer Supervisor, FL.Dept. Education, 1532 Kingsley Ave., Orange Park
Elementary Environmental Suite 110
Curriculum Education
Dr. Mildred Berry Supervisor,Science Fl. Dept. Education, 1450 N.E. 2nd Ave. Miami
Environmental Room 918
Education
Mr, Curtis Scott Program Specialist FL P.O. Drawer 820 Panama City
Dept. Education,Envir
onmental Education
Mrs. Angie Matamoros Curriculum Cluster FL Dept, Education, 6650 Griffin Road Ft.Lauderdale
Supervsr. Sci/Hlt Environmental
Education
Mrs. Roberta Dilocker Coordinator,Math & FL Dept. Education, 1007 West Main St. Inverness
Science Environmental
Education
Dr. Haydee Navarro Director of FL Dept. Education, 3710 Estey Ave Naples
Instruction Environmental
Education
Mr. William Stanko Head Fl. Dept Education 530 La Solona Arcadia
Teacher,Environmenta Environmenal
I Lab Education
Mrs. Paula Whiltier Deputy Supt. for FL Dept. Education, P.O. Box 3-E Cross City

Dr. Richard Conkling Coordinator for FL Dept. Education, P.O. Box 755 Bunnell
Curriculum Environmental
Education

04/071BB
List for E I letters

Nafll@ Title Organizat.ion Address rity

Mr. Harrison Schofield Director of Pr ojects FL Dept. Education, P.O. Box 67 Trenton
Environmental
Education
fis.Lillian Sasnett Director o f FL Dept, Education, P.O. Box 1(159 Jasper
I n s t r u c t i ona I En v i r onment a I
Services Education
Mr. Martin Yungman District Director of FL 919 U.S. 41 North Broolsvillk
Curriculum Dept.Education,Envir
onmEntal Education
Or, Jed Klein Director Instruction FL Dept Education, 1701 Prud@ntial Jacksonvill
Environmental Drive e
Education
hr. C.T. Ponder Secondary FL Dept. Education, 155 Ave E Apalachicol
Administration Environmental a
Education
Mr. Gmirge Steele Director of FL Dept.Education, P.O. Box 453 Moore Haven
Administrative Environmental
Services Education
tV John Masterson DiT@@ctor of FL Dept. Education, P.O. Dravff JG79 Wauchula
Curriculum 6-12 Environmental
Education
l1r. Dewayne Lemler Coordinator, FL Dept Education, 426 School StrEet Sebring
Secondary Education Environmental
Education
l1r.Roy Hyatt Di r . /Envi ronmental FL Dept P.O. Box 6216 Gonzalez
Sensitivity Proj Education,Environmen
tal Education
Mrs. Mary Bal:er Chapter 1, Program FL Dept. Education, P.O. Box 918 Quincy
Supervisor Environmental
Education
Mrs. Barhara Director of FL Dept Education, Gulf Couoty Poyt St.
Shirley-Scott Instructional Environmental Courthouse jo@
Servi ce Education
Mr. Kenneth Dooley Asst.Supervi5or for FL Dept P.O. Box 1380 Labplle
Instruction Education,Environmen
tal Education
Mr. Michael Mullins Coord.of Ft. Dept Education, P.O. Box 3408 Tampa
EnvironmentalEd. Environmental
Education

Mrs. Jean West Special Programs FL Dept Education, 211 W. Iowa Ave Bon i (a i
Administrator
Environmental
Education
Mrs. Dorothy Bishop Dir.Instructional Fl Dept.Education, 1490 W.Warhington
Seryices.&Staff Environmental Street
Education
Mr.P. William Hammond Dir. Environmental Nature Center, Ortiz Ft. 11yer
Ed.,Instr,SPTV, Ave
Mrs. Shirley Bateman Dir. of Instruction FL Dept Education, P.O. Box 429 -Br i fol
Environmental
Educat ion

04/07/00
List for E & I letter,@

flame Title Organizatitin Address

Mr. Wiley C. Kerlin Dir. Secondary FL Dept. E ducation, P.O. Box 170 N a] i
Education Envi ronmental
Education
Or, A.Ronald Hudson Asst Super, FL Dept. Education, 1990 25th Str@et Vero Beach
Instruction Environmental
Education
Mrs. Dolores H. Ceraso Administrative As5t. Fl. Dept Education, P. 0. Box 58 Mayo
for Programs Environmental
Education
Mrs.Mildred Hall Secondary Science FL Dept. Education, 2757 West Nnqacola Tallahas5ee
Curr.Team Environmental Street
'Education
Mr. James Ray Dir of Personnel and FL Dept Education, P.O. Box 449 Madison
Sec,Educ. Environmental
Education
1,, Ba,I,ra Anderson lir, Ile, Idu,alion 11 Dept. Education,- 500 East Ocean Blvd. StU31-t
Environmental
Education
jir. Thomas L. Melvin Di-r-,-Vocational rL Dept Education, P.O. Brix J959 Mar i anna
Education Environmental
Education
Mrs.Beverly Haskims Super. Secondary rL Dept Education, 201 Burleigh nlvd Taw@s
Education Envi r onmental
Education
Mr. Paul D, Johnson Asst. Supt. Instruc. Fl Dept Education, P.O. Draver 1*29
Services Environmental
Education
Mr. Robert Kitzmiller Supervisor of Fl Dept Education, P.O. Boy '1061 Br 4411ton
Science Environmental
Education
Mrs. Betty Cox Director of Fl Dept Education, 560 East Ocean blvd. Stuart
Secondary Education Environmental
Education
Mrs, Betty Cox Specialist Fl Dept. Education, 242 White St. P.O. box 1788 Key Yest
Environmental
Education
Iiis5 Sharon Suits Science Education FL Dept. Education, 100 S.11. Fifth AYE. Okeechobee
Contact Environmental
Education
Dr. R. Camille Dorman Asst. Super. Fl Dept. Education, P.O. box 24630 W@st ralm
Instruction Environmental
Education
Mr. Dick Mullenax Science Supervisor Fl. Dept Education, P.O. box 391 P.Artou
Environmental
Education
Mr. Jack Roberts Super.,Media,Career, Fl Dept Education, 310 Preston rt.-oirt Ft. Pi*erce
Consumer Ed. Environmental
Education
Mrs. Leona Davis Dir. Secondary Fl Dept Education, 1201 Atlantic Ave Feri)Andin@
Education Dept. Environmental
Education

rage- No. .1
04/07/8B
List forE&I letters

T i t I Oyqanization Address City

Ms. Arlene Bridges Program Consultant, F1 rlppt Education, P.O. Box 271 Orlandf,
Ele. Science Envi ronment a I
Education
Mr. Steven Pinck Supervisor Science Fl Dept Education, 7227 U.S. Highway 41 Lind
Enviy onmental O'Lal..
Education
Mrs. Meredith M.DarkeT Dir. Middle school rl Dept. Education, 200 S. 7th St!i-A
Ed.Services Environmental
Education
Mr. Micky Walker Coord. Math and F1 Dept Education, 603 Canal Str@et
Science Environmental
Education
Mr. Joe W. Stantrin Science Sup@r, Fl Dept Education, 120 Lovery Pl;c@ 11A I (-ol;
Secondary Accredit. Environmental
Education
Mr. Blaine Muse Dir.Middle School FlDqt. P.O. Box 11,18
and Sec. Ed Education,Environmen
tal Education
Mr. Thomas ti. Baird Dir.,-K-1.2.-Science Fl Dept Education, 205 4th St. S.W. Largc-
Environmental
Education
Dr. Sandra McDonald Dir. Curric. and FI Dept Education, 40 Orange Strr-et
Instruction Environmental Augustine
Education
Mr. Richard Codispoti Super, Science F1 Dept Education, 2418 Hatton Street Sarasota
Education Environmental
Education
Mrs. Bettie Palmer Consultant/Coor of Fl Dept Education, 1211 Helloriville, V-@ S-411 for d
Sc i enc e Environmental
Education
fir. Lawrence Hughes, Jr Instructional Coord. rl Dept Education, 502 North C(-rl@cr Nrry
Enyironmental Street
Education
Ms. sue reel Coord. Special Fl Dept P.O. Box 100 v a y fr d v f I
Programs Education,Environmen le
tal Education
Mr. Larry D. Ross Instructional Fl Dept Education, 202 N FloritIF Street Buchr)El!
Supervisor Environmental
Education
Mr. Howard McNeill Asst. Super. for FI Dept Education, 55 S.W. 6th Street Lal:e Butler
Instruction Environmental
Education
Director of
Mr. James King Fl Dept Education, Park Ave Defuniak
Instruction Environmental. Springs
Education
Mr. Marvin Johns Director of F1 Dept Education, 224 West Parshley Live Oak
Instruction Environmental Street
Education
Ms. Billie Wisniewski Science Supervisor Fl Dept Education, P.O. Box 1910 Daytona
Envi ronment al Beach
Education

List for E & I letters

T i t I i Orgarization "dress Ci tNY

Pat Williams Director of Fl Dept Education, 206 North Third Chipl ey
111struction EjivironfAental Street
Education
ay Crituity Public Library Fl or i da State 25 West Government Panama City
Library Depositories Street
Vista Campus Library F I or i d aState Documents Department Florida North Ili afqi
Libr OT Y Depositories 1) t T 111 t i oil I I
i
ward roinity Div. of F) or i da S t a t e 100 South Andrews For t
r ar i P@ Library Depositories Ave. Lauder din! e
Cocoa Public Library Florida StAte 430 Delatinoy Ave coc,)a
Library Depositories
rida Atlantic Florida State P.O. Box 3092 Boca Raton
fiversity Library Library Depositories
norida International Florida State Documents Section Tamkifii 17-4mpus Ili anli
iv, Library Depositories
1 1, ( ai I
Fl or i irl,4 Stat @ Uili V@f si ty Florida State DOCURVItS -Nfli Ta! I lhas5e@
br.:!ry Depositories Division
c Florida State 1212 North Ocean jactsnil 1i I I
.k-sorivi I I e Publ i c
lbrary Library Depositories Street
iami Beach Public F1 or i da State 2100 Collins Ay(.. Miami !34-0)
ibrary library Depositories
liami Bade Public Florida State lot West Flagler Niaof
Library Library Depositories
cala Public Library Florida State 15 Southeast Os-ola Ocala
I Library Depositories Ave.
Orange Courity Library Florida State lot East Central Orland.)
istrict Library Depositories '
t. Petersburg Public Florida State 3745 Ninth Ave Narfli St.
fibrary Library Depositories Petersburg
State Library of Florida Florida State Document Section R.A. Gray Building Tallahassee
Library Depositories
Istetson University Florida State Dupont-Ball Library Deland
Library Depositories
Jacksonyille University Florida State Carl S. Swisher University Blvd. Jacksonvill
Library Depositories Library Horth e
Tampa-Hillsborough County Florida State . @900 North Ashley Taikpa
Lib, Sys. Library Depositories .
University of Central Florida State P.O. Box 25000 Orlando
Florida Libry Library Depositories
Univ@rsity of Florida Florida State I Documents Department Gainesville
Library Library Depositories
University of Miami Florida State Gov't Publication: P.O. 249214 Cora)
Library Library Depositories Gables
University North Florida Florida State Documents DiyiBion P.O. B,)x 17605 Jacksonvill
Library Library Depositories e
University of South Florida State Library-Special 4204 Fowler Ave Tampa
11o, i la Depositories Collections
06yersity West Florida Florida Stake Documents-Jolvi 03ce Pensacola
Library Depositories Library

List for E & I letters

TitlE Organization Address City

Vist Pali., r@'ia(ll Public Florida State 100 Clematis West Palm
I Beach
Library Depositories
Aitastasia State P.Ec. Area Fl. DHR Div Rec t@ 5 Anastasia Park St.
Parts, Part Service Drive Augustine
'.iialachicola Rivir & Bay FDNR Div Rec L 261 Seventh Street Apalachicol
Parks, Fl Parl: a
Service
llifiia H,-)nda cwtiti P6c. FOR Div Rec & Parks Rt. I Box 782 Big Pine
@.rea Par I., Service Key
Pio State FDNR Div Rec and 12301 Gulf Beach Pensacola
;;.ifreition ArEa Parts Park Service Highway
Pill 9t@-'q)a- Cap Fl. Stite FDHR Div. Parks and 1200 S. Crandon Blvd Key
Rec, Park service Biscayne
Suiow Plantation Ruitis Ulqir FDIIR Div. Parks and P.O. Box 655 Bunliel I
Uate Hist. Rec. Park Service
Ounedi ii
i1al ad,@si Island State FOUR Div Parks and No I Causevay Blvd
F, af k Ric Park Service
Cape St. Giorge State Ratipl. FDIIR Div Parks and 261 Seventh Street Apalachicol
P. E @e r v e Pec, ParL Service a
Pedar Vey State Museum
FDIIR Div Rec.and P.O. Box 538 Cedar Key
Parks/Park Service
Cayo C-)it]l State Part FDlIR Div of Rac and P.O. Box 1150 Boca Grande
Parks/Park Service
I'h3rlott@ Harbor State FDI-IR Div Rec and P.O. 591 Bokeelia
Risel-le Parks/Park Service
Cheki @a Stato Recreation FDHR Div Rec and P.O. Box 1313 Horiestead
Aria
A Parks/ Park Service
Col I i er Seminole State FOUR Div Rec and Marco
Parle Parks/Park Service
Coll;titution Convention Ranger FDNR Div Rec and 200 Allen Memorial Port St.
StateMuseum Parks/Park Service Way Joe
Crystal River State Arch. FDHR Div Rec and 3400 N. Museum Ft. Crystal
Siti Parks/Park Service River
D@Illoi- wiggilli Pass State 11100 Gulf Shore Dr. Hapl es
(cc, Area N
of . jal i -all Bruc e"St . P.O. Box 62 Eastpoint
rit-of j, I @ I ;lid
[mlen 'Aat,- 1"';rdEns P.O. box 26 Point
l1ashington
S' P.O. Box 548 Copel and
F.
F @ v 1) 1: V. cc CII a t i p a r I... Rt.4 box 213-J-1 St.
Augustine
Flaglir Bea--h State Pc': 3100 SGuth AIA Hagler
A
Or en Beach
F') r clil-1-1i qlat@ P31-1. 2601 Atlantic Ave Fernandini
Peach

Ft. l0at Stat@
200 Atlantic Beach Ft. Pierce
F" i Ar i. a Blvd
Ft. 13-ihiry Tayor State P.O. Box 289 YeY West

No. 7
04/0710P
List for E & I letters

Name 'Title Organization Address City

Fred Gannon Rocky Bayou Rt. I box 597 Hiceville
P@c. Area..
Grayton Beach State Rec P.D. Box 1061, Santa Rosa
Area' Beach
Hillsborough River State 15402 U.S. '0101 HoTth Thonoto5ass
Park a
Honeymoon Island State No I Causeqay Blvd Dune(li (I
Pec Area
Hugh Taylor Birch State 3109 Eask Sunrise Ft
Pec Area Blyd Laude-(dale
John D. McArthur Beach 10900 S.P. 70'31 North Palm
State Park Beach
John P@Ilnecamp Coral Reef P.O. pq.,@ 497 rey Largo
state PrV
John Lloyd Beach State Mr. 6503 North Ole;,n Dr Dania
Pec Area
Gamble Plantation Hist 3708 Patten Ave Ellenton
Site
Kingsley Plantation Hist P.O. Bo@ 321 Fort George
Site
Key Largo Coral Reef P.D. Cox 01147 Key Largo
Nat'l Swtuar
Voreshan State Historic P.O. Box 7 E5twj
Site
Lignumvitae Key State P.D. Box 1052
Botanical Ste
Little T31bot Island 12157 llectsrher Fort George
State P0 Drive
Looe Yey State Rec Area Route I Po@ 792 Big Pine
Yey
H3113tee Springs State Pt.2 Fiy '017 rhieflalld
Park
HyaH,a River State Park 13207 S.R. 72 Sarasota
Ney Smyrna Sugar Mills Ranger r.o. Box 86t New SM, ,trn@
Hist. SitE Rtarh
Orlilocknee Piver State P.O. Pox 5
Park
fflet,; River State Rec P.O. Pox V01,15 Uorth Kiawi
Area
Oscar Scherer State Rec P.C. Rriy, ^J3R osprey
Area
Pahokee State Rec Area P.D, Dfe!@TT 7V',
St. Andrews State Rec 4415 Thomas Drive P3 I) aPa Ci t 7
Area
San Marcos de Apalache P.C. Box 27 St.' Marl's
State Site
Sebastian Inlet State 9700 South Alt. 110t)Mfl@
Pec. Area ?@ach
St. Joseph Peninsula St 2.r Route 1, Box -Port St.
State Park 2011 Joe
Tomol-.a State Parl, 209'9 North De3ch f4 Annd
Street Beach

Page No. 8
04/07/88
List for E & I letters

Name Title Organization Address City

Bay State P.O. Box 187 Cedar Key
Preserve
Washington Oaks State Rte 1, Box 128-A St.
Gardens Augustine
Weedon Island State 1500 Weedon Island St.
Preserve Drive Petersburg
Glavis Jr. District Manager 4415 Thomas Drive Panama City
Johnny Johnston District Manager 3540 Thomasville Tallahassee
Road
William Perry District Manager 4801 S.E. 17th Gainesville
Street
Gilbert Becker District Manager 2099 North Beach Ormond
Street Beach
Johnson District Manager Rt. 1 Box 107-AA Clermont
John District Manager P.O. Box 398 Osprey
Richard' Doaroski District Manager P.O. Box 8 Hobe Sound

Michael Hurphy District Manager P.O. box 2660 Key Largo
Arnold Kuenzler District Manager 1800 Wekiwa Circle Apopka
Russell Denser Historic & 3900 Commonwealth Tallahassee
Environmental Land, Blvd
Management
Long Key State Rec Area P.O. Box 776 Long Key
Jamie L. Information Bureau of marine 100 Second Ave South St.
Specialist III Research Petersburg,
Director of Tourism Escambia County 1401 E Gregory St Pensacola
Bay City Tourist, P.O. Box 9416 Panama City
Development Council
Emerald Coast P.O. Box 4204 Fort Walton
Tourist Development Beach
Council
Apalachicola Day 45 Market Street Apalachicol
Chamber' of Commerce a
Levy County Chamber P.O. Box 118 Cedar Key
of Commerce
Liberty County P.O. 526 Bristol
Chamber of Commerce
Washington County P.O. Box 457 Chipley
Chamber of Commerce
Wakulla County P.O. Box 598 Cravfordvil
Chamber of Commerce le
Dixie County Chamber P.O. Box 547 Cross City
of Commerce
Walton County P.O. Box 29 DeFuniak
Chamber of Commerce Springs
Destin Chamber of P.O. Box 8 Destin
Commerce
Greater Fort Walton P.O. Box 640 Fort Walton
Beach Chamber of Beach
Commerce
Greater Gulf Breeze P.O. Box 337 Gulf Breeze
Chamber of Commerce

List for r 7@ 1 letfEi

a rile t I e I q all i z at i4l Add,-

Santa Rosa Chamber 501 I'A@; t SfrE@f Mi
of Colhlwce S11
flonticello-Jefferson 420 Vesf llp@jjj,wl,
IL I :-
C of C St
Bay County Chamber P.D. B.), turY,
of Commerce
Pensacola Area P. 0. b o Y. 5 50 P E 11 r a,a
Chamber of Commerce
Pprry-Taylor County P.D. Boy 55 11 P r %,
Chamber ofCommerce
Port St. Joe @ Gulf P.O. pnX F92 poyt St.
C of C Jo@
Tallahassee Chamber P.O. Box i 0@'4 T @. I I nT !I%
of Commerce
Niceville-ValpaTaiSO 179 John S i r) s valpal-liso
C of r parkjay
jacYsonville. 103 Horl @
collyelltion & Suite 2`!"1 e,
Visitor's Bureau
We5t Nat;9,11.1 County C P.O. B04 "ID Ca I I ah@n
of r
Amelia 151and P.D. Bo:, 172 Ferr"tilitia
rernandina B@3ch C Nach
of C
r1agler County C of P.O. 69.9
r
6ainesville Area C P.D. N- , I Ir
,)f C
Jacksonville Area P.O. Flo- 3e`q
Chamber of Commerce
Jacksonville Beaches P.O. Pox 5 (1 .12 7 J a C 1: :,!1 v i I
Area C of C
I-Ake City/Col!jmbia P.D. P-- 5 a 1, eC y
r.oullty C of C
Clay Count), Chamber P.D. D o v 11,14 1 Or3?ij P.G r
of Commerce
Putnam County P.D. Bc
Chamber of Commerce
St. Augustine @ St. P.D. @c. t ,
John's County C of C
Tourist DeYE-10pMent 201 SE Fi glltj@ AVC
Council d a
Tourist Devel opment Boy. Kpy 1je5t
Council
Tourist Development 555 17 L I 'S t.t
Council
Tour i st Development 1555 N 1
Council Lakes Hve@
204
Belle Glade Chamber 540 5c,011
of Commerce Str ek@t

04107M
List for E & I'letters-

Name Title Organization Address City

Lower Keys Chamber P.O. bo x 511 r g P i
of Commerce I'E,Y
Greater Boca Paton P.O. Do, 1@'Wj Pr-ca Paton
Chamber of Commerce
Greater Boynton 6319 OceAv 11vi Uni I; on
Beach C of C 108 Beach
Coconut Grove 34371 Maii) Highway coconlit
Chamber of Commerre (3f -)%e@ I
Coral Gables Chamber 50 Arawli, foa C o I --.I
of Commerce Sab I e
Coral Springs 9767 West Sai.-ifile F@'r At
Chamber of Commerce road Springs
Dania Chamber of P.O. 130% V'c 'I i a
Commerce
Davie Cooper City 4185 9 64th @Ye D-1via
Chamber of Commerce
Peer f i el d Beac 11 1601 ['20 Ili I lstrmr, er t i e I (I
Chamber of Commerce Blvd, P e a@ h
Greater Delray Beach 64 @outhz-asl Fifth Vel r:.-.
Chamber of Commerce Av@ BL%ach
Ft. P.O. Bo-! 1-151F. Ft,
Lauderdale/Broward C Lauderdale
of C
Hallandale Chamber P.O. box 249 1 R@idfl e
of Commerce
Ili al eali/Miami 59 I-lest 'Ith S!
Springs Chamber of
Commerce
Greater Hollywood C P.O. Box 23145 Hollywood
of C
Greater 650 U.S. lfighuaj- I Howtest6ad
Homestead/Florida
City C of C
Islamorada Chamber P.O. Box 915 Islamorada
of Commerce
Jupiter/Tequesta P.0.1 ho-, 917 Jupiter
Chamber of Commerce
Key Biscayne Chamber 95 Hest McIntyre Yey
of Commerce Street Biscayne
Key Colony Beach P.O. Box 89 1'ey Colony
Chamber of Commerce Beach
Florida Upper Keys P.O., Box 274C Key Largo
Chamber of Commerce
Greater Ifey West 402 Wall St Key flest
Chamber of Commerce
Greater Lake Worth 1702 Lifl:A. Porth Pd Lake Worth
Chamber of Commerce
6reat.er Lantana 212 Iris Street Lantana
Chamber of Commerce
Greater Marathon 3330 Overseas rli r a t h on
Chamber of Commerce Highway

04/07/88
List for E & letters
Name Title Orgallizatiol; Address City

Tri City Chamber OV 6130 West Atlantic Margat@
Commerce Blvd,
Greater Miami 1601 Bisciyne Fl-,!d Oiini (-omp]E@, 7th f1i Frili
Chamber of Commerce F1 )or
North Dade C of C P.D. Box CK"W Mi =-I-1i
South Dade Chamb@r 900 Perrine- A-ve Mi ailli
of Commerce
Latin Chamber of P.O. Box 7@0821 Mi ami
commerce
Mj ami Beach Chamber 1920 Meridian Avi. I'Urli @@A-Jl
of Commerce
Miami Shores Chamber 9523 Hov@ht:,0- Miami
of Commerce Second Ave Sh,lr a :
Northwest Dade 45 Curtir's Pai i.w8y hi a if, i
Chamber of Commerce spriliqi.,
North Miami Chamber 1300 kFt Di,I-ie North Nplfli
of Commerce Hi ghway
North Miami Beach 39 HorthEpst IF34 North Miami
Phamber of Commerce St Beadl
Palm Beach Chamber 45 Coconol, Palm B@ach
of Commerce
Greater Pompano 2200 East Atlailtic F, f-.. if, p -@ 11 o
Chamber of Commerce Blvd P a a - It
Northern Palm Beach '0601 Bt k1a (I v 1 i P i V i e
County C of C B e -I - It
Southern P. 0. B o ".. 131 0 5 8 J, @Cklth Miami
Iiiami/Kendall Area C
of C
Sunrise Chamber of 3122 North rin@ Still Y i P
Commerce Island
Florida Gold Coast P.O. Bo,@ E-572) r1o r f =- i d c-
Chamber of Commerce
Greater West Palm P. a. B 0 "4 2, r. I flest
Beach Chamber of piach
Commerce
Tourist Development P.D. Box 3121
Coullc i I
Tour i st Development P.O. Bc@., I @ng I e,4r)rjd
@,)Ullc i I
Tour i st, Developmet it P. fl. F, t1yers
Council
Cape Coral Chamber '105 1 Capp Cor2l f@app floral
of Commerce Partway
Greater Pine Island P.D. BoN @'5 11,t) @-- Ila
C of C
Englewood Area 601 SOLIU! Indi-ana Lv-11 ct@---,od
Chamber of Commerce ave
Everglades Area P,O, Box E
Chamber of Commerce Ci ty
Metropolitan rt. P.D. Box CC Fort M.):ers
Myers C of C

T i t I i i on AddT eSS City

I ars P@ach P. 0. Box C109 Fort Myers
bt@,- of Commer,ce Beach
]a-laoid Chawber P. 0. 913 Marco
Iii i r C e I s I a II d
W.pl Ar&a Chamber 1700 North Tahiiatai Naples
T Trail
Chai !o(ti County P. 0. 2702 Tawi ami Port
G, 50- 1-- f u (Commerce Trai I Charl otte
Canibel-Captiva Causeway Road Sanibel
1311 1 C113hiber Of I sl and

Tc,ui i st Development Newport Square 4109A 231.3 East Bay Drive Clearwater
i t
@,i @-t r Sarasot 655 Noyth Tawtiuii Sarasota
T@,ur i sw Assoc i at i on
,Lli,o Hillsborutigh 10 South Ashley Suite 850 T amp a
iou,J Y C-311vent i -311 Drive
Purtau
hartatie ChawtbeT of P.O. box 321 Bradenton

e r c e
Anitd Na6a Island P.O. Box 3136 Bradenton
I`h@,hher of Commerce Beach
fii -Jtr Clearwater P.O. Box 2457 Clearwater
i'A1114ber of Commerce
1)iii@:llas Suncoast St . Suite 239 6learvater
Chatiber of Commerce Petersburg,Clearwate
r Airport
1`1 t;us County City County Bldg Crystal
!'Xw- oatJ Vhaidber of River

f,4iater Dunedin 434 Main Street Du n e d i n
-,iItber of Commerce
Springs P.O, Box 1098 Homosassa
Ai ia Chamber of Springs

1:;@atEr Hudson Area 13740 Old DiKie j
Hudson
I'11awher of Coomerce Highway
Longboat Key Chamber 510 Bay Isles Rd Longboat
-)f Cowulerce Key
llu-diira Beach 501 150th Ave Madeira
Chamber of Commerce Beach
Wkst Pasco Chawber 407 Main St New Port
of Commerce Richey
Cireater Palm Harbor 1000 North U.S, 19 Palm State Bank Pal I,
Area Chamber of 1300 Bldg. Harbor'

Fic@uth Hillsborough 315 U.S. Highway 41 Ruskin
r1tinty Chamber of South

I'afEty Harbor 200 Main Street Safety
1'haNbir of Commerce Harbor

P?p 11-3. 13
04/07/88
List for E & I.Ietters

Nalle Title Organizatfoll 'Addres=1 City

St, Petersburg P.D. Bo@ 1371 St.
Chamber of Commerce Petersburg
St, PPterShLirg Beach P.O. U1.75
Chamber of Commerce Petersburg
Beach
Sarasota Coutity P.O. Box 3100
Chamber of Commerce
Siesta Key Chamber P.D. Do.@ 5109 Sarasota
of CorfimercE
Sun City Center P.O. pok 5203 Sul) rity
Chamber of r'ommeyre Cent er
Greater Tampa P.O. 14 o -i 12 (1 Tampa
Chamber of Commerce
North Tampa Chamber P.O. Box 02447 Tampa
of Commerce
West Tar.,,pp Chamber 306 Pt-c:): folmOw-,
of Commerce Driv@
Ybor City 1513
Greater Tarpon 28 E,@J Tarpon
Springs Chamber of Spring;
Commerce
Treasure Island P.C. fv;) ?@pklj
Chamber of Commerce
Venice Area Chamber 257 North Tatiiauii
of Commerce Trail
Brevard County 2235 'fourtilsy
Tourist Development Parkvay tslatid
Council
Tourist DeVelOpWitnt P.O. Box 2775 'n o 1; 1
Council B ;- a C 11
Cocoa Beach Area 4')1 Nwredge 131kd r:ncoa
Chamber of Commerce
Daytona Beach Area P.O. E'.ox 21775 o 1) a
Chamb er of Commerce
Daytona Beach Shores 3616 South Atlantic Da'j- t fill a
Chamber of Commerce Ave Suite A
Shores
St. Lucie County 2200 klirgini3. tv;@ Fwt Pier-
Chamber of Commerce
Hobe Sound Chamber P.O. V.,(.1 Sc"Jill
of Commerce I
South Brevard Cj@@ 0: !@Mvf !ii
Chamber of Commerce StTavbl idge A-;@
New SmyrnalEdgewater P.O. Box 12@ Smy(na
Chamber of Commerce
Orwind llta@h Chamber P.B. Pij, 074 fly nond
of Commerce R4,01
Ormond by the Sea P.O, '1r,(
Chamber of Commerce
Palm Bay Area Chamb(- P.11. Pfi@
of Commerce

0411117168
List for E & I lettirs-

amE T i t I Orplization Addr@sn @-ity

Titu5villp tre.:k 201"') @j!
Chimber of Commerre 144;hiwi@--w
VETO Biach ch:.mher PA 1 .101
') f c) m wl,-! ( , C.-
Jensen Reach Chat-ber 1@(11) !(:., Ki:
of Portmerre Commercial 9t i

PAGE
.10/08/87 FLOR IDA DEPARTMENT OF EDUCATION
FILE 60.663 CONTACT PERSON SYSTEM
DISTRICTS WITHIN CONTACT AREA
CONTACT AREA: It ENVIRONMENTAL EDUCATION

02 BAKER ()3 SAY
01 ALACHUA MR. CURTIS SCOTT
MRS. DONNA STRICKLAND DR. RONNIE 0. KIRKLAND
SUPERVISOR OF SCIENCE DIRECTOR OF SECONDARY PROGRAM SPECIALIST
EDUCATION P:.Q. DRAWER 620
620 E. UNIVERSITY AVE. 392 SOUTH BLVD. EAST
GAINESVILLE FL 32601-5498 MACCLENNY FL 32063-2717 PANAMA CITY EL 32402-0820
904/259-6251 EXT ItO 904/672-4100 EXT 436
904/395-0586 EXT 586 82 1 -5354 777-4364
651-1586 06 BROWARD
05 BREVARD MRS. ANGIE MATAMOROS
04 BRADFORD MR . DAVE HOWELL
MRS. BURNEY WINKLER CURRICULUM CLUSTER SUPERVIS13R
OIR. OF CURRICULUM K-12 SCIENCE RESOURCE TEACHER SCIENCE/HEALTH
582 NORTH TEMPLE AVENUE 1274 SOUTH FLORIDA AVENUE 6650 GRIFFIN ROAD
-2698 ROCKLEDGE FL 32955-2497 Fr. LAUDERDALE FL 33314-0000
STARKE FL 32091 305/631-1911 EXT 510 305/765-604G
964/964-6800
620-5229 08 CHARLOTTE 09 CITRUS
07 CALHOUN MR. ALTON L. CHEATHAM MRS. ROBERTA,DILOCKER
MR. JERRY EDGAR PEACE RIVER ELEMENTARY SCHOOL COORD. OF MATH AND SCIENCE
DIRECTOR. VOCATIONAL EDUCATION HANCOCK AVENUE 1007 WEST MAIN STREET -4698
425 E. CENTRAL AVE.. G-20 22400 INVERNESS FL 32650
BLOUNTSTOWN FL 32424-0000 CHARLOTTE HARBOR FL 33950-0000 904/72G-1931 EXT 260
904/674-8144 813/625-4773 647-1011

COLLIER
10 CLAY DR. HAYDEE NAVARRO
to CLAY MRS. NANCY LEADERER
OR. RICHARD CRUMP SUPERVISOR. ELEMENTARY DIRECTOR OOF INSTRUCTION
.SUPERVISOR, SECONDARY CURRICULUM
CURRICULUM 1532 KINGSLEY AVE/SUITE ilo 3710 ESfEY AVENUE
SOO WALNUT STREET FL 33942-4499
GREEN COVE SPRINGFL 32043-3199 ORANGE PARK FL 32073-0000 NAPLES
904/284-6500 EXT 461 904/269-8130 8 13/643 -2700 EXT G21
835-1508 752-1011

12 COLUMBIA 13 DADE 14 DESOTO
DR. JAMES YOPP DR. MILDRED BERRY MR. WILLIAM STANKO
DIRECTOR OF ELEMENTARY ED. SUPERVISOR. SCIENCE HEAD TEACHER. ENVIRONMENTAL
LEARNING LABORATORY
RT, 7, BOX 541 450 N.E. 2ND AVE. ROOM 918 530 LA SOLONA AVENUE -4911
LAKE CITY FL 32055-0000 MIAMI FL 33132-1397 ARCADIA FL 33821
904/752-7812 305/37G-1989 813/494-6611
432-tSB9

10/08/87 PAGE 2
FILE &a.663 FLORIDA DEPARTMENT OF EDUCATION
CONTACT PERSON SYSTEM
DISTRICTS WITHIN CONTACT AREA
CONTACT AREA: ii ENVIRONMENTAL EDUCATION

15 DIXIE 16 DUVAL 17 ESCAMBIA
MRS. PAULA M. WHITTIER DR. JED KLEIN MR. ROY L. HYATT
DEPUTY SUPT. FOR INSTRUCTIONAL DIRECTOR. INSTRUCTION DIR.JENVIRONMENTAL SENSITIVITY
SERVICES PROJECT
P.O. BOX J-E 1701 PRUDENTIAL DRIVE P.O, BOX 636
CROSS CITY FL 32628-0860 JACKSONVILLE FL 32207-8154 GONZALEZ FL 32560-0636
904/498-508G 904/390- 2 129 904/9Ga-0135
825-2129

18 FLAGLER 19 FRANKLIN 20 GADSDEN
DR. RICHARD 0. CONKLING MR. C. T. PONDER MRS. MARY BAKER
COORDINATOR Of CURRICULUM SECONDARY ADMIN. CHAPTER 1. PROGRAM SUPERVISOR

P.O. BOX 755 155 AVENUE E P.O. BOX Big
BUNNELL FL 32010-0755 APALACHICOLA FL 32320-2099 QUINCY FL 32351-0818
904/437-3351 EXT 25 904/653-8835 .904/627-9651 EXT 250
352-7100 771-4770 791-050

21 GILC@IRIST 22 GLADES 23 GULF
MR. HARRISON SCIiOFIELD MR. GEORGE STEELE -MRS. BARBARA SHIRLEY-SCOTT
DIRECTOR OF PROJECTS DIRECTOR OF ADMINISTRATIVE DIRECTOR Of INSTRUCTIONAL SERV
SERVICES
P.O. BOX 67 P.O. BOX 459 GULF COUNTY COURTHOUSE
TRENTON FL 32693-OOG7 MOORE HAVEN FL 3347-t-0459 PORT ST. JOE FL 3245G-i698
904/463-2331 EXT 20 813/946-0811 904/229-8256
231-4906

24 HAMILTON 25 HARDEE 26 HENDRY
)AS. LILLIAN SASNETT MR. JOHN MASTERSON MR. KENNETH DOOLEY
DIRECTOR Of INSTRUCTIONAL DIRECTOR OF CURRICULUM 6-12 ASST. SUPT. FOR INSTRUCTION
SERVICES
P.O. BOX 1059 P.O. DRAWER 1678 P.O. BOX 1980
JASPER FL 32052-1059 WAUCHULA FL 33873-1678 LABELLE FL 33935-1980
904/792-1211 813/773-9058 813/675-5266 EXT 302
735-4266

'27 HERNANDO 28 HIGHLANDS 29 HILLSBOROUG"
MR. MARTIN A. YUNGMAN MR. DEWAYNE LEMLER MR. MICHAEL MULLINS
DISTRICT DIRECTOR OF COORDINATOR. SECONDARY COORD. Of ENVIRONMENTAL ED.
CURRICULUM EDUCATION
919 U.S. 41 NORTH 426 SCHOOL STREET P. 0. BOX 3408
BROOKSVILLE FL 34601-0000 SEBRING FL 33870-6099 TAMPA FL 33601-3408
904/796-6761 EXT 413 813/382-1121 EXT 208 B13/272-4B21
630-5011 742-1208 547-482 1

PAGE 3
10/08/87 FLORIDA DEPARTMENT OF EDUCATION
FILE 60-663 CONTACT PERSON SYSTEM
,DISTRICTS WITHIN CONTACT AREA
.... CONTACT AREA: il ENVIRONMENTAL EDUCATION

31 INDIAN RIVER 32 JACKSON ELVIN
30 HOLMES DR. A. RONALD HUDSON MR. THOMAS L. M
DIRECTOR. VOCATIONAL EDUCATION
MRS. JEAN WEST INSTRUCTION
SPECIAL PROGRAMS ADMINISTRATOR ASST. SUPT. FOR

P.O. BOX 5958
211 W. IOWA AVENUE 1990 25TH ST. FL 32960-3395 MARIANNA FL 32446-59513
FL 32425-2103 VERO BEACH 904/526-4510 EXT 215
BONIFAY 305/567-7165 EXT 203 774-1011
904/547-9341 465-1203
23t-4054 35 LAKE
34 LAFAYETTE MRS. BEVERLY HASKINS
33 JEFFERSON MRS. DOLORES H. CEPASO
MRS. DOROTHY BISHOP SUPERVISOR SECONDARY
DIR.. INSTRUCTIONAL SERVICES ADMINISTRATIVE ASSISTANT FOR
PROGRAMS & PERSONNEL EDUCATION
STAFF DEVELOPMENT 201 W. 13URLEIGH 13OULEVARD
WASHINGTON STREET P.O. BOX 58 TAVARES FL 32778-249.6
1490 W. MAYO FL 32066-0`058
MONTICELLO FL 32344-1132 904/294-1351 EXT 6 904/343-3531 EXT 252
904/997-3562 660-1252
282-4012 37 LEON 38 LEVY NSON
36 'LEE MR. PAUL D. JOH
Mr. William Hammond MRS. MILDRED HALL ASSISTANT SUPT. FOR
Environmental Educ. SECONDARY SCIENCE CURR. INSTRUCTIONAL SERV-
Dir.. ImpOVEMENT TEAM
Instruc. Dev- Serv. 2757 WEST PENSACOLA STREET P.O. DRAWER 129
Nature Center. Ortiz Avenue TALLAHASSEE FL 32304-2998 BRONSON FL 32621-0129
Ft. Myers FL 33901-0000 904/4B7-7188 - 904/486-2151
813/275-3033 620-5201

41 MANATEE
40 MADISON ROBERT B_ KIT2MILLER
39 LIBERTY MR. JAMES RAY MR.
MRS. SHIRLEY BATEMAN DIR. of PERSONNEL AND SUPERVISOR OF SCIENCE
-DIRECTOR Of INSTRUCTION SECONDARY EDUCATION P.O. BOX 9069
P.O. BOX 429 p. 0. BOX 449 FL 32340-D449 BRADENTON FL 33506-9069
BRISTOL FL 32321-0429 MADISON Bi3/7,16-5171 EXT 289
904/643-2249 904/973-408t 536-1289

43 MARTIN
42 MARION 43 MARTIN MRS. BETTY COXE
MR. WILEY C. KERLIN DR. BARBARA ANDERSON DIRECTOR OF SECONDARY
DIRECTOR. SECONDARY EDUCATION A)IRECTOR OF ELEMENTARY EDUCATION
EDUCATION 500 EAST OCEAN BOULEVARD
500 EAST OCEAN BOULEVARD
P.O. BOX 670 FL 34994-0000 STUART FL 34994-0000
OCALA FL 32678-0670 STUART 305/287-6400 EXT 253
904/732-804t EXT 224 305/287-64oo EXT 224 24t-i253
656-1320 241-1224

PAGE 4
10/08/87 FLORIDA DEPARTMENT OF EDUCATION
FILE 60.663 CONTACT PERSON SYSTEM
DISTRICTS WITHIN CONTACT AREA
CONTACT AREA: il ENVIRONMENTAL EDUCATION

44 MONROE 45 NASSAU 4G 6KALOOSA
MRS. BETTY COX MRS. LEONA DAVIS MR. JOE W. STANTON
SPECIALIST DIRECTOR OF SECONDARY SCIENCE SUPERVISOR/SECONDARY
EDUCATION ACCREDITATION
242 WHITE ST.-P.O. BOX 1788 1201 ATLANTIC AVENUE 120 LOWERY PLACE
FORT WALTON BEACHFL 32548-5595
KEY WEST FL 33040-1788 FERNANDINA BEACH FL 32034-3499
305/296-G523 EXT 239 904/261-7628 904/244-2161
420-1239
47 OKEECHOBEE 48 ORANGE 49 OSCEOLA
MISS SHARON SUITS MS. ARLENE BRIDGES MR. BLAINE MUSE
SCIENCE EDUCATION CONTACT PROGRAM CONSULTANT. ELEMENTARY DIRECTOR OF MIDDLE SCHOOL &
INSTRUCTIONAL SERV. SCIENCE SECONDARY EDUCATION
iOQ S.W. FIFTH AVENUE P. 0. BOX 271 P.O. BOX 1948
OKEECHOBEE FL 34974-0000 ORLANDO FL 32802-0271 K I SS I MMEE FL 32742-1948
813/763-3157 EXT 28 305/422-3200 EXT 374 305/a47-3929 EXT 231
329-1374 .352-7440
50 PALM BEACH 51 PASCO 52 PINELLAS
DR. R_ CAMILLE DORMAN MR. STEVEN RINCK MR. THOMAS M. BAIRD
ASSISTANT SUPERINTENDENT/ SUPERVISOR OF SCIENCE DIRECTOR. K-i2 SCIENCE
INSTRUCTION
P.O. BOX 24690 7227 U.S. HIGHWAY 41 205 4TH STREET. S.W.
WEST PALM BEACH FL 33416-4G90 LAND O'LAKES FL 34639-0000 LARGO FL 34640-0000
305/684-5115 813/996-3600 EXT 243 B13/585-9951 EXT 215
222-51iS 597-1243
53 POLK 54 PUTNAM 55 ST JOHNS
MR. DICK MULLENAX MRS. MEREDITH M. BARKER DR. SANDRA MCDONALD
-SCIENCE SUPERVISOR DIRECTOR OF MIDDLE SCHOOL DIRECTOR, CURRICULUM AND
EDUCATION SERVICES INSTRUCTION
P'O. BOX 391 200 S. 7TH SIREET 40 ORANGE STREET
BARTOW FL 33830-0391 PALATKA FL 32077-4612 ST. AUGUSTINE FL 32084-0000
813/534-2274 904/329-0532 904/824-7201 EXT 73
541-2274 632-0532
56 ST LUCIE 57 SANTA ROSA 58 SARASOTA
l4r. Jack Roberts MR'' NICKY WALKER MS. RICHARD CODISPOTT
Supervisor/Media. Career 6 COORDINATOR/MATH & SCIENCE SUPERVISOR OF SCIENCE
Consumer Eaucation EDUCATION
310, Preston Court 603 CANAL STREET 2418 HATTON STREET
Ft. Pierce FL 33450-0000 MILTON FL 32570-6706 SARASOTA FL 34237-0000
305/464-3051 904/623-3663 EXT 220 a 13/953 - 5000 EXT 320
691-1220 529-1320

PAGE 5
10/08/87 FLORIDA DEPARTMENT OF EDUCATION
FILE 60.663 CONTACT PERSON SYSTEM
DISTRICTS WITHIN CONTACT AREA
.... CONTACT AREA: li ENVIRONMENTAL EDUCATION

60 SUMTER 61 SUWANNEE
59 SEMINOLE MR. MARVIN JOHNS
MRS. BETTIE PALMER MR. LARRY D. ROSS
CONSULTANT/COORDINATOR OF INSTRUCTIONAL SUPERVISOR DIRECTOR OF INSTRUCTION
SCIENCE 224 WEST PARSHLEY STREET
12il mELLONVILLE AVENUE 202 N. FLORIDA STREET LIVIE.OAK FL 32060-2396
SANFORD FL 32771-2296 BUSHNELL FL 33513-9401
305/322-1252 904/793-5588 EXT 50 904/362-2252 EXT 276
621-7032

.63 UNION 64 VOLUSIA
62 TAYLOR MS. BILLIE WISNIEWSKI
MR. LAWRENCE HUGHES. JR. MR. HOWARD G. MCNEILL SCIENCE SUPERVISOR
INSTRUCTIONAL COORDINATOR ASST. SUPERINTENDENT FOR
INSTRUCTION
502 NORTH CENTER STREET 55 S. W. GTH STREET P.O. BOX 1910
LAKE BUTLER FL 32054-2599 DAYTONA BEACH FL 32015-1910
PERRY FL 32347-2757 904/496-2045 EXT 23 904/255-6475
904/584-4964 821-5383

66 WALTON 67 WAS14INGTON
65 WAKULLA Mr. James King MR. PAT WILLIAMS
MS. SUE KEEL DIRECTOR OF INSTRUCTION
COORDINATOR SPECIAL PROGRAMS Director of Instruction
Park Avenue 206 NORTH THIRD STREET
P.O. BOX 100 FL 32428-1265
CRAWFORDVILLE FL 32327-0100 DeFunlak Springs FL 32433-0000 CHIPLEY
904/892-2228 904/638-7222
904/926-7131 EXT 33 771-4060
277-3143

-q

RECEIVED
Florida Department of uatural Resources FEB 4 1986 REV. 01/23/86
Division of Recreation and Parks
BUF.=AU C--F
Florida Park Service
C7

Park Address Location Phone No. Park Manager County org. Code.
Alfred B. Maclay State Gardens 3540 Thomasville Road 5. 5 nii . 11. on 904/b93-4455 Charles 11. Smith Leon 7450 9020 002
Tallahassee, FL 32308 U.S. 319 14i 111 am J. Kelle -rman

St. johns 745o 9040 003
ook
-@q3 -.@,@San ra
n@ ,30
'D r i A I A a t S R .
`@iia s a Par 04 4 7 134,1,
Anastastii"St7afid' Ve"MrMtTOW@,
iL
6'n'e!':t--FLX32b85 oseph
rv . TZP
-1@@WoodaH ;V;': Mi 1 ey -111 n' t 7450 5030 143
*9
"S see"address 04/653@
-.1Apa*1ach1cbla--!R1vd-r 26 j "8 06 3-...@.,
@[email protected] treet SC-ij-- 3134057`@@
"iApala@h ola, FL 32320
pta .11 fc
o@ @turai ne _r .
y.
5-qW-?,XT0
`2353 @':Rc
ki@@
'7 'Wj A.6 Mh Tx@ 7450 9080 005
Box' 2 Of
-;`,Ba ia llonda'N-Stite.,Rec@eatloh I 12;da'. @w
i g'Pi rfe'Ke@- FL-@@33043 1@Marathonla@E@
V.X 'r- W
k@l 1. -.", , -E
9 04 4 9 2-15 9 5 J 6 s"Al. Cra ne ki@ @,jil. sc
ig Lagoon ;Stai te@,.@FRe@ccrQ@a@t@@In f
. . . . . . . 7450 9010 128
LJ% A @e i Pensacola, FL 32507
Ur -Y 7*, U -;
!BaggsZ@ap(FJ Ida s, '12 0 b 'S
Off '.U :S, 'fl )sbutter-4;,
Dade'."( 7450 9030 011
N@l '04", "OP-4--
tionWea. "-Ke*@ Biscayne, FL 33149 irkaj
11 M11- M'TreWaffie' R6 @=@3 a-m!4@e4s1'X::,taN,i Ite!
Blackwater Piver State Par@k Vt. 1, Box 57-C Off U, :AO, 15 mi. 9GI/623-2363 Robert 0. Perry Santa Rosa 7450 9010 008
11olt, FL
II.E. of Milton
Blue Spring State Park Star Route@3 2.5 mil. W. of 904/775-36G3 Daniel E. Paul Volusla 7450 9090 101
Orange City, FL 32763 Orange City Nicholas D. Robins
-,,,WPw,CrAk-@State. Park see Tomoka Ormond Beach, FL Volusia 7450 9040 139

Bul ovi P I a n ta ti o n Ru A r.S
7450 9040 009
.0. Box 655 4'3 D 0
9041 9 2219..,:Range.rRo)ert. I.Qud tz-.@j,
n S
,@2@tateAli storl 6unn S.E.

Caladcsi -.Island --State.
@ @,rk,,' @: "? ilq-:@ , Of 14 te" -@N@,Pi npllas`@@,,-
tay Blvd.@
a.@s j-6131443-5903 4:William Cutts- "
4.7450 905uOJO
'@o h'a-l d A .-';Wei
............. bunedl@-, FL 33.528.--@'
Dunedi n.
TN
Cape st:@Georqe State'Reser @261 Seve
a
-t7-- - Ld@e Ej.@@Lt---9 rav s 29
nth Street dd 0 -8063 anger`@Stephen L. T
Apalachicola, FL 7450 5020 1
.41653 i - t
-32320
Cedar- Ye'y'-,St'a'te tWscum P.6-. Box 538 'S R U@2 "'t.
:::U. 4 @:4?@ Q4 I @@Lev 7450 9030 012
C

Florida State Parks

Park Address Location Phone ?to. Park Xanager County Org. Code

00
'Imp ga.
.0.-' Box 11 Ki@8137 Jod' Cr k 7450 9060 127
tP 4e@4;iand)-' --283'-2929
B oc-a@ G ri 6-6 de"
k P ;.GispaFrilla:@@lWd
@.Z.z IA4 4@L FC14-33921 i
g-1fa",FTg- te Ila rb t 242-!4-1W! 111 am L 4.5he f t0 I ;-Qr. 'M
W @' 9 @;ef_'813/283:: harlotte' - 7450 5020 133
WNW,
-591
ese@ C Bokeel i i'XFL:
- - _ _,* F L1_ 3 19 1 @1- 0 5 9 1
W
te 'Recreation '11'v Ta 7450 9080 090
-P- -.69X A.@,,V;Q,-,3O5jL53-:-O9 9 Ge6"rge L ',@J ", -,@NrrAjj@' @.e
ppe V
@0 IPP
Area oTnestea "-FL 3303@@'4

C
'-.FL"-33937 nT.S_n41,"' LAI%; 13/394-rj@W I v - 6 111 r 7450 9060 013
006am
I.no -Sta te Pa r-k .0 -1 - _' '
Robe t
S. of flaples r
'qj
i,co- R-C @enl:W, T G61 f 7450 9010 014
Y@,@.Rahqe'r.@ ut etj.
nstitutio 200 'M fe'@ '7).On'u. S_*@' 98. 9 04 72 2 9,-Ri J
L'6-s ta-te-t-10" se um Port St. Joe, FL 32456

_@J el oc k
@Muse66 P t., ls@t'W
gica
745'0 9050 017
@Crystdl'RiVer"'@tafe;. --:@:-:34 'A' *0* V"@c9 04 7 9_@ -@-8 1 7'@ a@ me _s
R ver, F
i@6h'ai@761 6: 1 -S1 te s,@t@ryshial' i

Off S.R. 476, 11 904/793-4781 Lewis Vt. Edwards Sumter 7450 9050 018
Dade Battlefield State 0 .1* A
Hi storic Site B'YN@'@l I z1FC 3513

Dead Lakes State Recreation P.O. Box 939 1 mi . 11 of Wevia. 904/639-2702 Ranger Lathy Greene Gul f 7450 9010 110
Area Wawahi tchka, FL 32465 E. of S.R. 70, .5 mi.

De Leon Springs State P.O. Box 1338 Corner Ponce De Leon 9G4/985-4212 Roy C. Ogles Yolusia 7450 9090 145
Recreation Area De Leon Springs, FL 32028 Burt Parks Road Robert I!amser
qT-
@'@196
Dalno5-4'i 'q'g'j 'n's' Pass 5-ta'te'
Shore-Dr: LI .%1dvii n Ili 991 ns' 7450 9060 091
on A
,LRec rea ti rea-- Nap e _,__FL-33S63-

Devil's Mlillhopp,_r State 4732 II.W. 53rd Avenue see address 904/377-5935 Randall Brown Alachua 7450 9030 109
Geological Site Gainesville, FL 32601

ola'as
in 7450 9020 068
4/670-2111 Zjh
rge'zlsland
St
Dr. Julian G-.,- Bruce 0.": Box 62 14- 'P, FrYhkl,
Z@='fslaind Sta'te'!!Park -s tpo' i n' t FL 32328
T.
treeter Y7
.,,,Eden State Garde*n-s-r- P.O. B6x'26 Off U.S.1@@@904 231-421@@'Dav'Y@ Z450 9010 020
--Po I nt Vas i gton-,-FL-32454 **-S.R
hin .`395

RECEIVED
FEB 4 1986
BUREAU OF MARINE RESEARCH

Florida State Parks
Page 3

Park Address Location Phone No. Park Manager County Org. Code
Fakahatchee Strand State P.O. Box 548 On S.R. 29, 6 mi. N. 813/695-4593 Collier 7450 9060 114
Preserve Copeland, FL 33926 of Everglades City

Falling Waters State Rt. 5,Box 660 On S.R. 77A, 3 mi. 904/638-4030 William T. Maphis, Sr. Washington 7450 9010 021
Recreation Area Chipley, FL 32428 S.

Faver-Dykes State Park Rt. 4, Box 213-J-1 Off U.S. 1, 15 mi. 904/794-0997 Theodore W. Kersey St. Johns 7450 9040 022
St. Augustine, FL 32036 S.

Flagler Beach State 3100 South AlA see address 904/439-2474 Douglas R. Carter Flagler 7450 9040 024
Recreation Area Flagler Beach, FL 32036 S. Thomas N. Futch

Florida Caverns State Park 2701 Caverns Road On S.R. 167, 3 mi. 904/482-3632 Albert W. Smith, Jr. Jackson 7450 9020 025
Marianna, FL 32446 N. James H. Lien

Forest Capital State Museum 204 Forest Park Drive On U.S. 19-98, 904/584-3227 Ranger James W. Griest Taylor 7450 9020 026
Perry, FL 32347 1 mi. S.

Fort Clinch State Park 2601 Atlantic Avenue On U.S. AlA, 3 mi. 904/261-4212 Roy G. Kemp Nassau 7450 9040 027
Fernandina Beach, FL 32034 E.

Fort Cooper State Park 3100 S. Old Floral City Rd. 2 mi. S.E. on 904/726-0315 Alton C. Morrell Citrus 7450 9050 096
Inverness, FL 32650 S.R. 39

Fort Gadsden State Historic P.O. Box 157 On S.R. 65, 6 mi. 904/670-8988 See St. George Island Franklin 7450 9020 028
Site Sumatra, FL 32335 S.W.

Fort Pierce Inlet State 200 Atlantic Beach Blvd. North Beach 305/461-1570 William F. Benson St. Lucie 7450 9070 106
Recreation Area Fort Pierce, FL 33449 Daniel I. Griffin

Fort Zachary Taylor State P.O. Box 289 Southard St. on 305/294-2354 Jeffrey A. DiMaggio Monroe 7450 9080 125
Historic Site Key West, FL 33041 Truman Annex

Fred Gannon Rocky Bayou Rt. 1, Box 597 On S.R. 20, 5 mi. 904/897-3222 Malcolm B. McHenry Okaloosa 7450 9010 055
State Recreation Area Niceville, FL 32578 E.

Grayton Beach State P.O. Box 1062 On S.R. 30A, S. of 904/231-4210 James A. Murrian Walton 7450 9010 033
Recreation Area Santa Rosa Beach, FL 32459 U.S. 98

Florida State Parks
Page 4

Park Address Location Phone llo. Park 1-11anager County Org. Code

Highlands Hammock State Park Rt. 1, Box 310 On S.R. 634, 6 mi. 813/385-0011- Peter A. Anderson Highlands 7450 9090 036
Sebring, FL 33870 V1. Valinda A. 111chols

.11111sborough River State; Park-!7@35402 U.S.,-.301
-11 llsbonug
qaAark W.'G iss6H 9050 037
2
_51honotosassa 5524824 Stepheri..A-

X 4 Z55 --Ja'd R. :Chaffber at n i ne as 20
llone@mo'o_n Is-land"S6't6 `,'Vo I Causeway 01 of 8 13 7 3 4. ...... .. k 7450 9050 1
@.-Izecreatlon Area
Dunedin'@Fl_ .33523..' 5-11"L586"N Rob er t -

see a re ss 105/564-4521 Br An L.':.Polk rowar
Ilugh. Taylor Birch State -,:3109 East Sunrise Blvd.-- dl d Y 7450 9070 039
Rec@reation ARea o r
Ft. Lauderdale.-FL '33304 0

Ichetucknee Spr-ings State Rt. 2, Box 109 On S.R. 47, 4 mi . 904 /497 -2 511 Randall E. )tester Columbia 7450 9030 036
Park Fort White, FL 32038 11.14. Thomas Ledbetter
John _]O@oq S.R -703 Si nge fl i6 09 7 :-`j oh n 11. Fj 11 ya w G`Beach
It e @: 51621'-
NO m FL'
'Park it)'.Pal ' B
eac 7450 9070 140
or h

John Gorrie State 1.1-iscun Aplachicola, FL 32320 On 6 ti Street 904/653-9347 see St. George.1sland Franklin 7450 9020 0412

C-'- 1 R,
'jehn Peninek de"Of U.S--.-@305/451_-4-20_2" *'-,,,Ca"rl 11.1lielsen' -7450 9030 o15
amp ora ee ox onroe
zGeorge L. on-is
State'Park A
Key!Largo 3303L,
1@.' 2_!q I @55324
5

'--Broward 7450 9070 107
@,.,@,'..!'305/923-2@833@--,,Si@dney,'J Leve
John U. Beach 'State 6503 Ilort Ocean Drii
. @_ldyd @* - - _- __ -@-?@,7I7,7.
Rec rea tl on-'A D
'330(A
-ea ant a ;4L -

A. Scott
__,-Jonathan Dickinson State Park 'i@'16450 S.E. Fe@er-al-k,@y'.:-"@@'l":"@'@6e"'addr.e.'-s.-s'@;'.' 05/546-2771 D o n a V@" 14arti n 7450 9070 043
r
-Hoba -Sound,- FL ----z-Greft. 'T6ppi n

8131722-'1017 Pau w or
0 8 a en :,.On*U.S.*
Judah P. Benjamin:'C 'n@eae,@'a "@'VO P' tt 'A:ve-nu'e` 3 01- -6a-f' 7450 9060 031
a'
Ver.ori
Plahtation StatL
Historic Site

ion tate P.O. Box 321 'Off S. 904/251* 3122 see Little TalDot Is and--- Duval
ri ngsley Plantat S AIA,' 7450 9040 C44
Gcor 3 mi 1I.E.--of Jak.
Ili storic.,51 te go,-FL

RECEIVED
FEB 4 1980

Florida State Par@s @'T RCH
Page 5

Park Address Location Phone No. Park 1.1,anaqer County Org. Code

Key Largo Coral Reef P.O. Box 1083 74 50 5030 141
30S/451-1644 see Looe Key Monroe
......... . ... . ...... ...... .
National Marine-Sanctuary Key Largo, FL 33037

74 50 906 0 0-15
Koreshan State.-III storic SI te" P.O. Pox 7 -- - U.S. 41 A Eite ro--81-31992-031 i Ste_v@ 'A. Ba nt6n Lee
Estero. FL 33928 :Daniel C. Martin

Lake Gri ffin State 103 Ilighway 441127 see address 90-1/787-7402 Keith 1. Westlake La@e 74 50 9050 04 6
Recreation Area Fruitland Park, FL 32731

Lake Jackson hounds State 1313 Crovider Road Off U.S. 27 11. 9C4/562-0042 Ranger Robert Morley Leon 7450 9020 0,17
Archaeological Site Tallahassee, FL 32308

Lake Kisshnince State Park 14248 Camp l4ack Road Off S.R. 60, 15 mi 813116 96 -1112 David C. Randall Polk 7450 9090 037
Lake Uales, FL 33853 E. Barry A. Burch
Lake Louisa State Park Rt. 1, flo,,t 107-AA 3 mi . o 1 f S. R. 561 9011/394-2280 John F. Lynch Lake 7450 9050 108
Clermont, FL 3271.1 on Lake Nellie Rd.

Lake Manatee State 20007 S.R. 64 s 11' K. Wood
ee a ress, 813/746-80,12 Wi iam I'lanatee 7450 9060 088
Recreation Area Bradenton, FL 33508

Lake Talquin State Star Route 1, Box 2222 On S.R. 20, 20 mi. 9a;/576-8233 Hubert C. Gri f fi n Leon 7450 9020 093
Recreation Area Tallahassee, FL 32304 W. @3
Lignunivitae Key State P.O. Box 1052 Off Coast--Long Ke"y'.- Patrick V. Vells Monroe .)7450 90BO 097
Botanial Site Islamorada, FL 33036 SRA, U.S. I at Layton

Little Talbot Island State 12157 Ifeckscher Drive see address 904/251-3231 Azell flail Duval 7450 9040 049
Park Fort George-. FL 32226 Maxwell R. Forehand

Long Key State R@:Creation P.O. Box 776 0 U.S. 1 at Layton 305/664-A.815 John J. Roche Monroe 7450 9090 050
-Area Long Key,'FL 33001 Vickie L. Hess

Looe Key National Miarine Route I , Box 782 SOS/872-4039 Billy D. Causey Monroe 74 50 503 0 1,14
Sanctuary
B' 9 P' ne YCY3 FL 33043

Lower W-ekiva River Route 1, Box 189 3 05/322 -7 587 Ranger David T.- Vai I Se mi nol e 7450 15020 124
State Reserve Sanford, FL 32771

Florida State Parks
Page 6

Park Address Location Phone flo. Park f.lanager County Org. Code

IlYd@t6e`5prings State Park k 745D 9030 053
,Rt.----2-8ox-6l7 14 --@:'904/493-4288 :Char a evy
thfiifi .1 5L [email protected]
e and) -J 0 s c ph'@'E Smyth'-"".
Marjorie Kinnan Rawlings Rt. 3, Box 92 On S.R. 325 at 9W/466-3672 Ranger Sally Morrison Alachua 7450 9030 039
State Historic Site Hawthorne, FL 32640 Cross Creek

Mike Rcess Gold Mad Branch Rt. 1, Box 545 On S.R_ 21, 6 W E. 904/473-4701 Paul Vlorthington Clay 7450 9030 03Z
State Park Keystone Heights, FL 32656 Pamela flurfey

er-State Park- -72 d B I
akk
a Riv- 02 .!Robert L-.-'Dy6' I I aras ta @,,-7450 qD60 ms
y S. d s
-:_see a re s
Y4
araso -9542 -Leroy-B;'@Wi
S -SC -SS2@4095

Ilew, Siayrna Sugar Mi I I Ruins it
',@@P-O.*Box 861 on S. h Volusi
04 /428 -@,Z 126 Ranger'. ara @orris a 7450 9040 058
-@State'lflstbric ite it s . - - I I
.ew myrna"Beac ,.F
-River' Stafe'.r0a-jV.-.@
konee r P 0 a ox
U.S.::@319 mi .
/962-2771 '-@.:Clyde i c h o i
4
:@SopcfioOpy 'i@-FL@-32i5 7450 9020 0sq
6 Wakulla

O'Leno State Park Rt. 2, Box 307 On U.S. 441, 6 mi- 9@"/454-1853
High Springs, FL 32643 Alachua 7450 9030 050
Ben 0. @Iatson

a e
Oleta River St t
ox 601 0 .... .. .
MA o __F- ,
5
Recreation -Ar@i @-':305/94 7-6357 Paul J "Ri (Iqs Dad 7450 9030 138
mi FL @'33160 e
:.on -A51
11. E.
Olustce Battlefield State P.O. Box 2 On U.S. 90, 2 mi. E. 904/752-3866 Ranger Francis J. Loughran Baker V, 7450 90,10 061
Ilistoric Site OlustLe, FL 32072
_Y
Oscar,.SCherer State ... .. ..
:P.O. Box 398 6 -3154"',Darrell
nU.S. @,:. t -I : -_ . - ..1.. 17.1 .@
L. Re@reitlon Area - , @,z - R.'Kriusi -- -
I '. 1, @
-Osprey FL 3r'9---' S
3 SO 9060 052
W.@ Evans

Pahokee State Recrea..
r -rjr@awer .719 .4 I'At @'@:s3051924-7832 m
0 on
W6' S' 4 h6
.Area
-FL'- 33476- .6a t as-`k-@`P.@i@_@ -;":, P a I MBeach* 74SO 9070 053
7-':@- @'Pallokee' ke e
lio
P

Payncs Creek State itistoric P.O. Box 547 .5 mi .E. on 8131375-4717 Robert L. Henry Ha rdee 7450 9090 110
Site Boviling Green, FL 33B34 S.R. 664-A

Paynes Prairie Statz! Rt. 2, Box 41 On U.S. 441 S. of
Preserve Micanopy, FL 32667 Gainesville 9W/466-3397 Jack 14. Giilen Alachua 7450 9030 092
Tully.D. Yendrick

RECF-IVEO
FEB 4 1986

Florida State Parks
Page 7

Park Address Loca ti on Phone No. Park Manager County Org. Code

Ponce De Leon Springs State P.O. Box 126 On S.R. 181-A, 904 /836-4 281 Odell L. Mize Hol me s 7450 9010 094
Recreation Area Porice de Leon, FL 3.) 4 5 5 1 mi. S.

PrAirie-Lakes State Preserve P.O. Box 220 On S.R. 523, 8 mi. 305/436-1626 see Lake Kissimme Osceola 7450 9090 116
Kenansville, FL 32739 W.
RaVine State Gar@2ns P.O. Box 1096 On Twigg Street* 904 /328-4 366 Frank J. Alogna Putnain 7450 9040 085
Palatka, FL 32077 Cha rl e s R. Dickerman

Rock Springs Run State Route 1, Box 189 904 /383-3 311 Walter 14. Thomson Orange 7450 5020 150
Reserve Sanford, FL 32771

San Felasco Hammock State
Preserve see Devil's Mi 1 ]hopper Gainesville, FL Alachua 7450 9030 119
St. Andrews State 4415 Thomas Drive S.'on S.R. -392 off s-'.904/234-2522 Cecil Dykes 7450 9010 0,G7
Bay
'FL '32407 904 /234 -3 570 een
'Recreation Ar6a@@ @--m--`----Panama City, Carl 0. 11
qO4 @92 5-6 16 See Ochl oc konee Ri ver Wa kul 1 7450 9020 071
ta te P.O. Box 27 4-.
San Marcos de: ApaldC e Turn righ a end 2
Historic Si te St.- I-11arks, FL 32355 of S.'R.'@,363

Sebastian Inlet State 9700 South AIA see address 305/727-1752 Perry J. Smith Brevard 7450 9070 072
Recreation Area Melbourne Beach, FL 32951 David Jovers

Stephen Foster State Folk P.O. Drawer G On U.S. 41 11. 904 /397 -2 733 Richard W. Miller Hami I ton 7450 9030 132
Culture Center Mi i te Springs , FL 32096 Jimmy R. Richards
Suwannee River State Park Rt. 8, Box 297 On U.S. 9 0, 13 mi 9(A/362-2746 Terry L. Pitts Suwa nnee 7450 9030 073
Live Oak. FL 32060 W.

@O f
n S.R. o 90-1/227 -1327 James C. Mock
T. H. Stone t-12inorial Star Route 1, Box 200 dul f 7450 9010 W9
:St. Joseph Penin la Port St. Joe, FL 3245G S..98 Johnny M ze
su
tate Park
..S

Tenoro-- State Reserve 3329 Tenoroc Mine Road Bli/665-5270 Peter D. 1-loodward Polk 74SO 5020 148-
Lakeland, FL 33805

M OEM M M M M M M M@M M

Florida State Parks
Page a

Park Ad dress Location Phone 110. Park Hanaqer County org. Code

_g,
FS
_:E a
The Barnacle State Ili storic 1 6 1 11 44;1
-.,,-A-seL--:Bi 11 i da' 485-1-WO "P- D a d 7450 9080 105
I ksaggs@_, ape- or -1. 1L
Coconut Grove-*C
F

Three Ri vers State Rt, 1, Box 15-A On S.R. 271, 2 mi. 904 j 593-6 56 5 Russell A. Williams Jackson 7450 9020 075
Recreation Area Sneads, FL 32460 H.

wG it
-_.--@,..!@Yolusia 7450 9040 076
Toanka -State Park No r th 6e"a'ch 'ftree t see' dd '9GIJ@77:739 1,,,,
r eqrge
1 er :@S@
"a@4H i c h a 6 1

Torreya State Park Rt. 2. Box 70 On S.R. 12, 13 mi . 904/643-2674 141 llie F. Williams Liberty 7450 9020 077
Bristol, FL 32321 H.E.
Box-187 62@@@56 jjn@al 11 L 410 9030 100
-%@Waccasassa".'Bay Sts e 7 -
-tedar@@ Ke'Y'. Fl_-@"32625

-l'!" 74
Yo_tjhq-@ 1 7450 9040 079
f Walter W.'@@.
ashington Oaks @State'-Gardd_ j28-A
,pa
2M.On' AIA:rr. ag er:,-@@
Sf, ugusti @'e","tL5t2d86' ifaft Nei n, a 6@ Ga [email protected]

t,:- ,.111Q
wY r
; 75 TY -
I b7n, P i n e 1 a s
I s I a- T. erXe on" s and Drjve'@@[ =-,
jktedon n S r R
QM K@e 7450 9050 111

Wekiwa Springs State Park 1800 Wekiwa Circle Off S.R. 436, 31 mi. 305/839-3140 Paul E. Perras Orange 7450 9090 03- 0
Apopka, FL 32703 N. E. Thomas C. Linley

William fleardall Tosohatchee 3365 Taylor Creek Road 305/568-5893 Charles C. Motthews Orange 7450 5020 132
State Reserve

YDor City State Museum see Weedon Island 1818 9th Ave., Tampa Ilillsborough 7450 9050 123
,ftulee Sugar Mill Ruins".5tate-z-,111
'.S;- @I 9 A llo;@osa s sa
@@@rjc Zi te, see Crysta _Rive:r`,@2" @'-"M Ci t@U'@ 74 50 9050 032

8L)APAL' 40
C T

Florida State Parks
Page 9

Park Address Location Phone No. District Mananer County Org. Code

District I Office 4415 Thomas Drive St. Andrews State 904/234-3751 Glavis C. Tiller, Jr. Bay 7450 9010 991
Panama City, FL 32407 Recreation Area SC 221-3420

Pistrict II Office 3540 Thornasville Road Alfred B. Maclay 904/488-3648 Johnny Johnston Leon 7450 9020 992
Tallahassee, FL 32308 State Gardens SC 278-3648

District III Office 4801 S.E. 17th Street 901/1373-3665 William L. Perry Alachua 7450 9030 993
Gainesville, FL 32601 SC 620 5158

District IV Office 2099 North Beach Street Tomoka State Park 904/677-1122 Gilbert N. Becker Volusia 7450 9040 994
Ormond Beach, FL 32074 SC 352-7614

District V Office Rt. 1, Box 107-AA Lake Louisa 901/394-2280 Torrey Johnson Lake 7450 9050 995
Clermont, FL 32711 State Park SC 352-7110

District VI.Office P.O. Box 398 Oscar Scherer State 813/966-3594 John A. Baust Sarasota 7450 9050 996
Osprey, FL 33559 Recreation Area SC 552-7740

District VII Office P.O. Box 8 North Beach Road. 305/744-7603 Richard A. Domroski Martin 7450 9070 997
Hobe Sound, FL 33455 Jupiter Island SC 451-5321

District VIII Office P.O. Box 2660 John Pennekamp Coral 305/451-3005 Michael K. Murphy Monroe 7450 9080 998
Key Largo, FL 33037 Reef State Park 305/451-3027
SC 451-5325

District IX 0ffice 1800 Wekiwa Circle Wekiwa Springs 305/889-82466 Arnold P. Kuenzler Orange 7450 9090 999
Apopka, FL 32712 State Park SC 352-7065

Ili storic and Evironmental 3900 Commonwealth Blvd. 904 /488-6242 Russell K. Danser Leon 7450 5020 951
Land Management Tallahassee, FL 32303 SC 278-5242

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