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 Title Page
 Introduction and Methods and...
 Results
 Discussion
 Conclusion
 Literature cited






Group Title: Technical paper -- Florida Sea Grant College Program ; no. 34
Title: Biological survey and analysis of Florida's artificial reefs
CITATION PAGE IMAGE ZOOMABLE
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Permanent Link: http://ufdc.ufl.edu/UF00076014/00001
 Material Information
Title: Biological survey and analysis of Florida's artificial reefs
Series Title: Report number Florida Sea Grant College
Physical Description: ii, 11 p. : ; 28 cm.
Language: English
Creator: Bortone, Stephen A
Van Orman, Doyal
Florida Sea Grant College
Publisher: Florida Sea Grant College
Reproduced by National Technical Information Service
Place of Publication: Gainesville Fla
Springfield Ill
Publication Date: 1985
 Subjects
Subject: Artificial reefs -- Bibliography -- Florida   ( lcsh )
Artificial reefs -- Analysis -- Florida   ( lcsh )
Artificial reefs -- Surveys -- Florida   ( lcsh )
Genre: bibliography   ( marcgt )
non-fiction   ( marcgt )
 Notes
Statement of Responsibility: Stephen A. Bortone, Doyal Van Orman.
General Note: "July 1985."
Funding: This collection includes items related to Florida’s environments, ecosystems, and species. It includes the subcollections of Florida Cooperative Fish and Wildlife Research Unit project documents, the Florida Sea Grant technical series, the Florida Geological Survey series, the Howard T. Odum Center for Wetland technical reports, and other entities devoted to the study and preservation of Florida's natural resources.
 Record Information
Bibliographic ID: UF00076014
Volume ID: VID00001
Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved, Board of Trustees of the University of Florida
Resource Identifier: oclc - 29660536

Table of Contents
    Title Page
        Title Page
    Introduction and Methods and Materials
        Page 1
        Page 2
        Page 3
        Page 4
        Page 5
    Results
        Page 6
        Page 7
        Page 5
    Discussion
        Page 8
        Page 9
    Conclusion
        Page 9
    Literature cited
        Page 10
        Page 11
Full Text









BIOLOGICAL SURVEY AND ANALYSIS


OF FLORIDA'S ARTIFICIAL REEFS



By


Stephen A. Bortone
and
Doyal Van Orman






Project No. IR-83-12



Bi ol ogy Department
University of West Florida
Pensacola, Florida 32514



Technical Papers are duplicated in limited quantities for specialized audi-
ences requiring rapid access to information and may receive only limited edit-
ing. The text of this paper is retyped exactly from copy provided by the
senior author. This paper is provided by the Florida Sea Grant College with
support from NOAA Office of Sea Grant, U.S. Department of Commerce, grant num-
ber NA80AA-D-00038. It was published by the Sea Grant Extension Program which
functions as a component of the Florida Cooperative Extension Service, John T.
Woeste, Dean, in conducting Cooperative Extension work in Agriculture, Home
Economics, and Marine Sciences, State of Florida, U.S. Department of Agricul-
ture U.S. Department of Commerce, and Boards of County Commissioners, cooper-
ating. Printed and distributed in furtherance of the Acts of Congress of May
8 and June 14, 1914. The Florida Sea Grant College is an Equal Employment
Opportunity-Affirmative Action employer authorized to provide research, educa-
tional information and other services only to individuals and institutions
that function without regard to race, color, sex, or national origin.



TECHNICAL PAPER NO. 34
July 1985











INTRODUCTION

In recent years throughout the United States there has been active inter-
est in artificial reefs as a means of expanding the recreational and commer-
cial fisheries for midwater and bottom fishes. Numerous studies have been
conducted as a result of this growing interest by State and Federal agencies,
universities, and the private sector. Ample information is available concern-
ing different materials and how to construct artificial reef structures (Buck-
ley, 1982; Hilbertz, 1981; Kilma and Wickham, 1969; Parker et al., 1974; Shee-
hey, 1981; Stone, 1975; Stone et al., 1974; Turner et al., 1969; Woodhead et
al., 1982). Several excellent studies have addressed reef colonization,
standing crop, and other aspects of artificial reef development (Fast, 1974;
Hastings, 1979; Hastings et al., 1976; Lukens, 1981; Randall, 1963; Stone et
al., 1979; Turner et al., 1969), but sufficient evidence is lacking which
would serve as a guideline to increase or enhance the productivity features of
an artificial reef.

Recent efforts were made to determine which physical variables influenced
colonization of artificial reefs by assessing the available published and
unpublished literature, and constructing a data matrix of physical and biolo-
gical parameters. These data could have provided a basis for a statistical
prediction of the standing crop of fishes under certain environmental condi-
tions. Of the many studies available only 17 directly addressed the relation-
ship between the physical features of a reef and the fish production (Bortone,
1976; Crozier et al., 1977; Fast, 1974; Hastings, 1979; Hastings et al., 1976;
Hueckel and Stayton, 1982; Kilma and Wickham, 1969; Lukens, 1981; Parker et
al., 1979; Randall, 1963; Smith et al., 1979; Sonnier et al., 1976; Steimle
and Ogren, 1982; Stone et al., 1979; Turner et al., 1969; Walton, 1982; Wick-
ham et al., 1973). In addition to the unequal methods, recording procedures
and quantity of data presented made it impossible to accurately predict which
physical parameters are related to population density or diversity.

The overall objective of our investigation was to conduct visual assess-
ments of fish populations on a series of artificial reefs constructed of dif-
ferent types of materials existing under varied environmental conditions. Once
obtained the information would be analyzed and the results used to establish a
data base of physical and biological parameters which influence fish producti-
vity and production. These data could then serve as basic guidelines to per-
mit identification of factors which would require further investigation, and
to construct testable hypothesis regarding future artificial reef research.

METHODS AND MATERIALS

During October and November of 1983 we made a series of SCUBA dives on 30
artificial reefs representing ten primary areas along Florida's coastline.
The areas of investigation were selected based on zoogeographic zones, proxi-
mity to passes, protected harborages, and high recreational activities. At
each major area specific reefs were selected to encompass the different types
of materials used in artificial reef construction, reef profiles (high and
low), depths at which reefs are placed, the distances from inshore and off-
shore topographical influences, and substrates upon which the reefs are
placed.


4 .








The types of reef materials examined included ship hulls, barges, plat-
forms, concrete rubble and culvert, rubber tires, steel rubble and culverts,
and appliances. The type of material used in the construction of each reef
was recorded *as a percentage value. In instances where the composition was
mixed an estimate of the percent of each material was used. Depths of the
structures ranged from 3 meters to 29 meters, and distances from shore includ-
ed sites as far as 20 nautical miles seaward.

The intent of the investigation was to gather as many physical variables
as possible as well as to visually assess the fish population diversity and
density. Two divers conducted 25 minute dives on each chosen structure. Four
stations were selected on each reef, and one diver recorded the species and
numbers of fish observed at each station during a five minute interval. The
other diver collected water samples, temperature, core samples of the sub-
strate, and made physical measurements of the size and height of the structure
while making a visual assessment of the fish population.

Selected sites were photographed with a super 8 movie camera using photo-
flood and high speed Ektachrome film (ASA 160), with the focal distance set at
2 meters. Still photographs (35 mm) were also taken with a Nikonos IV using a
Mark 150 strobe and Ektachrome file (ASA 64). These records were used later
to verify the species and numbers documented by the divers.

The temperatures and salinities were recorded for the surface and the
bottom, and core samples were obtained using a polyvinyl chloride (PVC) pipe
20 cm long and 4 cm I.D. as a coring tool. In each case the sample was taken
approximately 4 meters outside the perimeter of the reef. The substrate was
later washed in fresh water, dried at 60 degrees C, then separated using a
series of serves (no's 10, 20, 40, 60, 80, and 120). Once separated each por-
tion was weighed and the percentage calculated. In addition the percentage of
shell hash was calculated for each size, and the total percentage recorded as
one of the physical variables. In three instances the entire substrate was
live coral and/or rock, and these values were also recorded as physical data.
Where only a portion of the substrate was solid, a subjective estimate of the
percentage was recorded.

We felt that two of the most significant physical factors to consider
were the size of a reef and it's cryptic nature. The area of each artificial
reef was determined by measuring the structure at the points of greatest di-
mension and recording the square meters of bottom area. The average height of
the material was then used to calculate the volume of the structure, and the
maximum height was recorded for profile analysis.

The cryptic nature of a structure was one of the most difficult to record
because it required converting a qualitative evaluation into a numeric value.
In doing this we carefully considered each type of structure, then assigned a
range of numeric values between one and ten. The range of values enabled us
to compare and evaluate similar and different structures individually and
collectively. For example barges were assigned a numeric range of three,
four, and five. If the barge being investigated was essentially intact, with
few hiding places, it was rated a three. If there were numerous holes and
debris, and many hiding places it was assigned a value of five. This method
was applied to concrete, ships, tires, and other structures as well. The









Japanese artificial reef was rated highest at ten, and block-like solid struc-
tures were rated the lowest with a one.

Visibility was determined with a 20 an Sechi disc by measuring horizon-
tally from the disc to the point at which the shape of the disc was no longer
clearly discernible. When visibility was less than'two meters the dive was
aborted.

Species lists and numbers of fishes recorded by divers were compared for
completeness and accuracy. The species were arranged taxonomically according
to Robins et al. (1980). Each family was listed chronologically from 1 to
193, and the species within each family were entered sequentially beginning
with one through the last species. The total number of each species was re-
corded by reef which enabled us to compare families, selected portions of the
reef community, of the total population with the recorded physical variables.
For initial analysis the biological data were reduced to six families which
represented the primary reef groups sought by recreational fishermen. They
are described by the following codes:

109 = Serranidae 120 = Carangidae

124 = Lutjanidae 127 = Haemulidae

129 = Sparidae 142 = Labrida

A data matrix was constructed listing reefs on the vertical axis and the
physical and biological variables on the horizontal axis. Reef identification
numbers consist of a three digit code which follows the identification process
in the Atlas of Artificial Reefs (Aska and Pybas, 1983). The following are
the numbers and descriptions which can be used to identify non-permitted
sites.

Reef Description

349 Reef F, 4.4 nautical miles west of Caxambas Pass,
Marco Island, Florida.

350 Reef E, 4.4 nautical miles west of Caxambus Pass,
Marco Island, Florida.

351 Shrimp boat, approximately 6 nautical miles north of
Key West, Florida.

352 Steel vessel, approximately 10.3 nautical miles north-
west of Key West, Florida.

353 Steel vessel, approximately 10.4 nautical miles north-
west of Key West, Florida.

354 Rock jetties, approximately 6 nautical miles north of
Key West, Florida.

433 Japanese artificial reef, 10 nautical miles west, of
Clearwater Pass, Clearwater, Florida.










434 Cement culverts, 10 nautical miles west of Clearwater
Pass, Clearwater, Florida.

600 Stage II platform, 2.2 nautical miles southwest of St.
Andrews Pass, Panama City, Florida.

650 Eight washing machines, 4.5 nautical miles southeast
of Pensacola Pass, Pensacola, Florida.

Physical variables recorded and used in the computer analysis are listed
below.


REEF:
YR BLT:
MAT S:
MAT C:
MATR:
MAT W:
COMP 1:
COMP 2:
COMP 3:
COMP 4:
COMP 5:
COMP 6:
COMP 7:
COMP 8:
LATITUDE:
Cryptic:
AREA M2:
AREA M3:
MAX HGHT:
DEPTH:
DST SHRE:
DST 10OF:
DST PASS:

VOL SHD:
WIND DIR:

WIND VEL:
CURR DIR:

CURRVEL:

VISIBILITY:
LONGITUDE:
TIDE TYPE:

W STMP L:
W STMP H:
W STMP A:
S STMP L:
S STMP H:


Reef identification number.
Year reef placed on site.


Percent
Pe recent"
Percent
Percent
Percent
Percent
Percent
Percent
Percent
Percent
Percent
Percent


steel in the composition.
cement.
rubber.
wood.
solid substrate.
substrate larger than 2.0 mm.
.850 2.0 mm.
.425 .850 mm.
.250 .425 mm.
.180 .250 mm.
.125 .180 mm.
less than .125 mm.


Latitude of the site.
Potential hiding places provided by the structure.
Bottom area in space meters.
Estimate of the volume of material in cubic meters.
Highest point of the structure. Recorded in meters.
Recorded in meters.
Distance from shore in nautical miles.
Distance from 100 fathom in nautical miles.
Distance to pass or entrance of the closest drainage.
Recorded in nautical miles.
Mean volume of discharge of the nearest drainage.
Predominant direction in degrees from which the wind
blows.
Mean wind velocity recorded in nautical miles per hour.
Resultant water current entered in degrees. Recorded
as the direction the current sets.
Mean current velocity recorded in nautical miles per
hour.
Visibility recorded in meters.
Longitude of the site.
S = semidiurnal; D = diurnal; M = mixed (Fernald,
1981).
Lowest winter surface temperature in Farenheit.
Highest winter surface temperature.
Average winter surface temperature.
Lowest summer surface temperature.
Highest summer surface temperature.









S STMP A:
W BTMPL:
W BTMP H:
W BTMP A:
S BTMP L:
S BTMP H:
S BTMP A
F STMP:
F BTMP:
WSSAL L:
W SSAL H:
W SSAL A:
S SSAL L:
S SSAL H:
S SSAL A:
W BSAL L:
W BSAL H:
W BSAL A:
FS SSAL:
F BASL:
SHELL:
FAMILY:
FALL:


Average summer surface temperature.
Lowest winter bottom temperature.
Highest winter bottom temperature.
Average winter bottom temperature.
Lowest summer bottom temperature.
Highest summer bottom temperature.
Average summer bottom temperature.
Fall surface temperature.
Fall bottom temperature.
Lowest winter surface salinity.
Highest winter surface salinity.
Average winter surface salinity.
Lowest summer surface salinity.
Highest summer surface salinity.
Average summer surface salinity.
Lowest winter bottom salinity.
Highest winter bottom salinity.
Average winter bottom salinity.
Fall surface salinity.
Fall bottom salinity.
Percent shell hash in substrate.
Family identification number.
The abundance of observed species.


The biological data were reduced to the sum of those species observed in
each of the six selected families and merged with the physical variables (Ap-
pendix 2). Basic descriptive and correlation coefficient analysis were per-
formed for all physical variables for each family (Appendix 3).

Stepwise regression analysis is limited to using approximately 20 inde-
pendent variables. The factors which we removed from the set of physical data
were variables such as temperatures, salinities, tidal variations, current and
wind directions and velocities, and volume of water sheds. It was felt that
these conditions could not be directly influenced by persons involved in im-
proving or constructing artificial reefs, and were therefore the best choices
for elimination. This succeeded in reducing the number of physical variables
in the set to 21. Missing information for reef 354 made it necessary to re-
move it from the data set which reduced the number of observations containing
adequate information to 27 reefs. The reduced physical data containing 21
variables for each observation were than merged with the reduced biological
data (Appendix 4).


Stepwise regression was conducted on the merged data
(.15 level) independent variables identified (Appendix 5).
then used in the multiple linear regression analysis for
the prediction mathematical models (Appendix 6).


and the significant
These results were
the construction of


RESULTS


Physical and biological data were recorded for 28 of the proposed sites.
The remainder were not surveyed due to rough water, reduced visibility, or the
inability to locate the site by using loran. These provided 28 observations
for physical variables and 494 observations for biological data (Appendix 1).









Greatest family diversity (15) occurred on site 629. This is an intact
steel barge located 4.6 nautical miles southwest of Destin Pass in 21.6 meters
of water on a predominately sand bottom containing 18% shell hash. It encom-
passes 1300 square meters of bottom area and its maximum height is 3 meters.
The highest species diversity (29) was sound on site 353, a non-permitted site
in Florida Bay. This is a sunken steel ship which broke in half after running
aground approximately 10.3 nautical miles northwest of Key West in 9.4 meters
of water. It rests on a hard coral and rock bottom, and covers 708 square
meters of bottom area with a maximum height of 5.9 meters.

Lowest diversity (7 species in 4 families) was recorded for site 432.
This reef consisted of concrete culverts and rubble located 2.9 nautical miles
west of Bradenton, Florida. It is situated 10.4 meters deep on a sandy bottom
containing 9% shell hash, and covers 1200 square meters of area with a maximum
relief of 1.2 meters.

The largest standing crop of fishes was recorded at site 600, which is
also a non-permitted reef. This platform structure is constructed similar to
an oil platform. It stands in 18.4 meters of water 2.6 nautical miles south-
east of St. Andrews Pass in Panama City. The structure extends above the
surface and covers 324 square meters of sand bottom containing 12% shell hash.

The results of the correlation analysis are condensed and presented here
for the parameters found significant (.05 level) during the calculations.

Serranids

Abundance was positively correlated to the distance from shore and the
distance from the pass. Negative correlations include fall and winter
surface temperatures, summer surface and bottom salinities, winter bottom.
salinity, and reef area in cubic meters.

Carangids

Abundance was positively correlated to visibility and medium grained
(.250 to .425 mm) sandy substrate.

Lutjanids

Abundance was positively correlated to rubber tires, fine grained (.125
to .250 mm) sandy substrate, area in square meters, depth, low summer
bottom temperature, average summer bottom salinity, and low surface sali-
nity.

Haemulids

Abundance for the family was positively correlated to 14 factors, and
there were no negative correlations. These variables include: medium
grained sandy substrate; maximum height of the reef; volume of the water
shed; low winter bottom temperature; all summer bottom temperatures; high
and low winter surface and bottom salinities; low summer surface salini-
ty; and average and high summer bottom salinity.









Sparids


Positive correlations were noted for coarse (larger than 2 mm) substrate
and the reef area in square meters. Abundance was negatively correlated
to the average summer bottom salinity.

Labrids

Family abundance was positively related to solid substrate, depth, cur-
rent velocity, and visibility.

Regression analysis produced mathematical models for all six families in
the reduced biological set. Variables which were identified as being signifi-
cant (.15 level) in the models indicated both positive and negative influen-
ces. An overview of these variables is presented for each family along with
comments concerning other factors in the models.

Serranids

Parameters determined significant in the model indicate positive correla-
tions to the size of a reef in square meters of bottom area, and the
distance from shore. Negative relationships were noted for steel and
rubber construction materials, the cryptic nature of the reef, the volume
of materials in cubic meters, and fall surface temperature.

Carangids

Models parameters for this family included only four variables. Positive
correlations for maximum height and visibility, and negative affiliation
with depth and fall bottom salinity.

Lutjanids

The variables in this model which reflect positive relationships are
rubber tires, bottom area in square meters, maximum height, fall surface
and bottom temperatures, average summer surface salinity, and fall bottom
salinity. Negative influences were noted for the area in cubic meters
and fall surface salinity.

Haemulids

Only 3 of the 21 independent variables were identified as significant in
the model Maximum height and distance to the pass were both positively
correlated to fall abundance, while the distance to shore has a negative
relationship.

Reasonable to excellent R-square values were obtained for all families
which strongly suggests that the models are well constructed, and that the
parameters have a high probability of significance. Mean square error values
were moderate to excessive which tend to weaken the models. Wide latitude in
the confidence levels existed for most of the models, and variations between
predicted abundance and observed values were generally wide ranged except for
Serranids. Overall consideration indicates that the models are of minimal
value as they presently exist.









S STMP A:
W BTMPL:
W BTMP H:
W BTMP A:
S BTMP L:
S BTMP H:
S BTMP A
F STMP:
F BTMP:
WSSAL L:
W SSAL H:
W SSAL A:
S SSAL L:
S SSAL H:
S SSAL A:
W BSAL L:
W BSAL H:
W BSAL A:
FS SSAL:
F BASL:
SHELL:
FAMILY:
FALL:


Average summer surface temperature.
Lowest winter bottom temperature.
Highest winter bottom temperature.
Average winter bottom temperature.
Lowest summer bottom temperature.
Highest summer bottom temperature.
Average summer bottom temperature.
Fall surface temperature.
Fall bottom temperature.
Lowest winter surface salinity.
Highest winter surface salinity.
Average winter surface salinity.
Lowest summer surface salinity.
Highest summer surface salinity.
Average summer surface salinity.
Lowest winter bottom salinity.
Highest winter bottom salinity.
Average winter bottom salinity.
Fall surface salinity.
Fall bottom salinity.
Percent shell hash in substrate.
Family identification number.
The abundance of observed species.


The biological data were reduced to the sum of those species observed in
each of the six selected families and merged with the physical variables (Ap-
pendix 2). Basic descriptive and correlation coefficient analysis were per-
formed for all physical variables for each family (Appendix 3).

Stepwise regression analysis is limited to using approximately 20 inde-
pendent variables. The factors which we removed from the set of physical data
were variables such as temperatures, salinities, tidal variations, current and
wind directions and velocities, and volume of water sheds. It was felt that
these conditions could not be directly influenced by persons involved in im-
proving or constructing artificial reefs, and were therefore the best choices
for elimination. This succeeded in reducing the number of physical variables
in the set to 21. Missing information for reef 354 made it necessary to re-
move it from the data set which reduced the number of observations containing
adequate information to 27 reefs. The reduced physical data containing 21
variables for each observation were than merged with the reduced biological
data (Appendix 4).


Stepwise regression was conducted on the merged data
(.15 level) independent variables identified (Appendix 5).
then used in the multiple linear regression analysis for
the prediction mathematical models (Appendix 6).


and the significant
These results were
the construction of


RESULTS


Physical and biological data were recorded for 28 of the proposed sites.
The remainder were not surveyed due to rough water, reduced visibility, or the
inability to locate the site by using loran. These provided 28 observations
for physical variables and 494 observations for biological data (Appendix 1).









DISCUSSION


The preliminary results of stepwise and linear regression analysis re-
flect high R-square values which leave little doubt that the models are of
value. The other less positive aspects of the analysis requires further ex-
planation.

Successful construction of a mathematical model for predicting fish popu-
lations on a given reef requires several things: 1) an adequate volume of the
data must be gathered; 2) the samples must be representative of the entire
population; 3) the data must be properly manipulated and analyzed to account
for variations in the samples. Each of these conditions was examined and the
following comments are extended.

We feel that the number of investigations was smaller than required for
the task. High R-square values can be obtained with limited assessments, but
a low mean square error (reported high in our models) is needed, and is ad-
versely influenced by a small number of observations.

In addressing the representative sampling factor and how it effects out
results several points are important. Our investigations were conducted at a
time when seasonal faunal changes normally occur. Some members may have al-
ready migrated to deeper, more stable water. Samples were taken shortly after
the end of the heaviest seasonal fishing period. It's possible that signifi-
cant numbers of key families were harvested during that time. On three of the
sites we assessed spearfishermen were actively engaged in taking fish from the
reef. On another site divers were harvesting stone crab claws, and concurrent
fishing occurred on one other structure. These activities may have caused key
species to move out of the area thereby altering the results of the sample. A
red tide bloom occurred two weeks before we assessed the area between Tarpon
Springs and Sarasota. Local biologists reported dead grouper and snapper as
well as small reef fish. All of these conditions can cause variations in the
abundance of fish recorded for the different sites. If there were significant
variations in the observed values they would have an adverse effect on the
model, and especially on the predicted values and confidence levels obtained
for each observation.

Two things which minimize these effects and strengthen the models are to
obtain more information through additional observations, and to manipulate the
raw data. The effects of wide variations in data can be reduced by transform-
ing the values to a logarithm scale. This wasn't done initially because good
results obtained with raw data are more powerful statistically than those ob-
tained from transformed data. Other actions such as transforming percentage
values recorded in raw terms (90%, 45%, etc.) to values such as .90 and .45 or
to a logarithm scale would reduce excessive variations and enhance the process
of analysis.

Grouping entire families into one abundance value may cause undesirable
results in analysis. In this instance we are trying to construct a predictive
model for catchable fish, but we are including the population of their non-
catchable relatives in analysis. Selection of specific members of key fami-
lies would reduce the adverse effect and align the models to our specific
needs.









The important point is that although the models are, at present, loosely
constructed they appear reliable enough to warrant transforming the data, and
if significant improvements are noted efforts should be made to field test the
results.


CONCLUSION

Additional analysis is needed on the existing data to eliminate some of
the excessive latitude noted in the models. To do this several steps should
be taken.

1) A recently modified program which enables us to include abundance data
of selected families as part of the set of independent variables should
be used in the analysis.

2) Recorded percent values, raw abundance data, and other factors should
be transformed in some manner to minimize excessive variance.

3) The biological data set should be reduced to specific groups within
each key family.

The existing data are inadequate and suspected of being non-representa-
tive of the annual population. Therefore this type of study should be repeat-
ed to:

1) Provide more data through increased observations.

2) Expand the results to include all seasons.

3) Account for variations due to seasonal changes and other influencing
factors.

4) Field test the improved models.


LIST OF APPENDICES

1. Raw physical and biological data (14 pages)

2. Merged physical and reduced biological data \0( ~ -s)

3. Descriptive statistics and correlation coefficient analysis p. .

4. Merged reduced physical and reduced biological data (T>- P .a)

5. Stepwise regression (RP i..s)

6. General linear model \ pocQ6 <


Editorial Note: Due to the number of pages and format of the computer print
out, the appendices are not reproduced in this report. Interested read-
ers may request this highly technical information from the senior author
at the address noted on the title page.
-%-' V\U









The important point is that although the models are, at present, loosely
constructed they appear reliable enough to warrant transforming the data, and
if significant improvements are noted efforts should be made to field test the
results.


CONCLUSION

Additional analysis is needed on the existing data to eliminate some of
the excessive latitude noted in the models. To do this several steps should
be taken.

1) A recently modified program which enables us to include abundance data
of selected families as part of the set of independent variables should
be used in the analysis.

2) Recorded percent values, raw abundance data, and other factors should
be transformed in some manner to minimize excessive variance.

3) The biological data set should be reduced to specific groups within
each key family.

The existing data are inadequate and suspected of being non-representa-
tive of the annual population. Therefore this type of study should be repeat-
ed to:

1) Provide more data through increased observations.

2) Expand the results to include all seasons.

3) Account for variations due to seasonal changes and other influencing
factors.

4) Field test the improved models.


LIST OF APPENDICES

1. Raw physical and biological data (14 pages)

2. Merged physical and reduced biological data \0( ~ -s)

3. Descriptive statistics and correlation coefficient analysis p. .

4. Merged reduced physical and reduced biological data (T>- P .a)

5. Stepwise regression (RP i..s)

6. General linear model \ pocQ6 <


Editorial Note: Due to the number of pages and format of the computer print
out, the appendices are not reproduced in this report. Interested read-
ers may request this highly technical information from the senior author
at the address noted on the title page.
-%-' V\U










LITERATURE CITED


Aska, D.Y., and D.W. Pybas. 1983. Atlas of artificial reefs in Florida.
Florida Sea Grant College. 15 p.

Bortone, S.A. 1976. Effects of a hurricane on the fish fauna at Destine,
Florida. Florida Sci. 39(4):245-248.

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