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Low-Level Monitoring of Bottlenose Dolphins,
Tursiops truncatus, in Charlotte Harbor, Florida
1990-1994

By

R. S. Wells, M. K. Bassos, K. W. Urian,
W. J. Carr, and M. D. Scott

U.S. Department of Commerce
National Oceanographic and Atmospheric Administration
National Marine Fisheries Service
Southeast Fisheries Science Center
75 Virginia Beach Drive
Miami, FL 33149

June 1996

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NOAA TECHNICAL MEMORANDUM
NMEFS-SEFSC-384

Low-Level Monitoring of Bottlenose Dolphins,
Tursiops truncatus, in Charlotte Harbor, Florida
1990-1994 =

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Institution

By

R. S. Wells, M. K. Bassos, K. W. Urian,
W. J. Carr, and M. D. Scott

U.S. DEPARTMENT OF COMMERCE
Mickey Cantor, Secretary

NATIONAL OCEANIC AND ATMOSPHERIC ADMINISTRATION
D. James Baker, Administrator

NATIONAL MARINE FISHERIES SERVICE
Rolland A. Schmitten, Assistant Administrator for Fisheries

June 1996

This Technical Memorandum series is used for documentation and timely communication of preliminary
results, interim reports, or similar special-purpose information. Although the memoranda are not subject
to complete formal review, editorial control, or detailed editing, they are expected to reflect sound
professional work.

NOTICE

The National Marine Fisheries Service (NMFS) does not approve, recommend, or endorse any
proprietary product or material mentioned in this publication. No reference shall be made to
NMFS, or to this publication furnished by NMFS, in any advertising or sales promotion which
would indicate or imply that NMFS approves, recommends, or endorses any proprietary product
or proprietary material mentioned herein, or which has as its purpose or intent to cause directly
or indirectly the advertised product to be used or purchased because of NMFS publication.

This report should be cited as follows: Wells, R. S.,M.K. Bassos, K. W. Urian, W. J. Carr, and M.
D. Scott. 1996. Low-level monitoring of bottlenose dolphins, Tursiops truncatus, in Charlotte Harbor,
Florida, 1990-1994. NOAA Tech. Mem. NMFS-SEFSC-384, 36 pp. + 8 Tables, 10 Figures, and 5
Appendices.

Authors’ affiliations: (RSW, MKB, KWU, WJC) Chicago Zoological Society/Dolphin Biology Research
Institute, c/o Mote Marine Laboratory, 1600 Thompson Parkway, Sarasota, FL 34236: (MJS)
InterAmerican Tropical Tuna Commission, c/o Scripps Inst. of Oceanography, La Jolla, CA
92037.

Copies may be obtained by writing the Southeast Fisheries Science Center, the primary author,
or:

National Technical Information Service
5258 Port Royal Road

Springfield, VA 22161

Telephone: (703) 487-4650

FAX: (703) 321-8547

Rush Orders: (800) 336-4300

This ts Southeast Fisheries Science Center Contribution MIA-95/96-39.

Table of Contents

Executive Summary
Introduction
Methods

Study Area
Survey Schedule
Field Techniques and Logistics
Photo-Identification Catalog
Analysis of Photographs
Data Processing
Estimation Procedures
Abundance
Interannual Trends and Power Analyses
Natality
Mortality
Immigration, Emigration, Residency, Transience

Results

Survey Effort

Photo-ID Catalog Development

Abundance Estimates and Trends

Power Analysis

Natality

Mortality

Immigration, Emigration, Residency, and Transience

Discussion

Photo-Identification Catalog

Abundance Estimates and Trends

Natality

Mortality

Immigration, Emigration, Residency, Transience
Summary of Population Parameters
Comparison of Abundance Estimation Methods
Power Analyses

Survey Design

Recommendations

on nf fF NY

Acknowledgments
Literature Cited
List of Tables
List of Figures
List of Appendices
ill

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iv

Low-Level Monitoring of Bottlenose Dolphins, Tursiops truncatus, in Charlotte
Harbor, Florida, 1990-1994
Final Report, NMFS Contract 50-WCNF-0-06023

Randall S. Wells, M. Kim Bassos, Kim W. Urian, William J. Carr, Michael D. Scott
Chicago Zoological Society, Sarasota Dolphin Research Program
c/o Mote Marine Lab, 1600 Thompson Parkway, Sarasota, Florida 34236

Executive Summary

The National Marine Fisheries Service (NMFS) has recognized a need for
low-level monitoring of bottlenose dolphin stocks in southeastern U.S. waters,
designed to detect catastrophic changes in the stocks. The main goals of the
monitoring are detection of large-scale changes in dolphin abundance and
establishment of archival databases for long-term trend detection. Low-level
monitoring can provide a short-term means of detecting large-scale changes in
population abundance and give decision makers the information necessary to
determine if modification of management plans is necessary. To these ends, the
NMEFS has funded several local research efforts in the southeastern U.S., including
the photographic identification effort in Charlotte Harbor, Florida, reported here.
Charlotte Harbor was of interest to management agencies at least in part because of
the use of this region from the 1960's through the 1980's for commercial dolphin
collection. More recently, Charlotte Harbor has been designated as a National
Estuary under the Clean Water Act.

Our Charlotte Harbor study area included the inshore waters from Lemon
Bay southward to northern Pine Island Sound on. the central west coast of Florida.
Photographic identification surveys were conducted through the study area on an
average of 24 boat-days in August of each year from 1990 through 1994. Mark-
resighting analyses modeled after a comparable study in Tampa Bay during 1988-
1993 allowed estimation of abundance and natality, analysis of inter-year trends, and
evaluation of seasonal residency. Our Charlotte Harbor photo-ID catalog for 1990-
1994 included 411 different dolphins.

During August of each year from 1990 through 1994, an average of about 308
dolphins used the Charlotte Harbor study area. The abundance apparently
increased from 198 - 369 (95% CLs) in 1990 - 1992 to 315 - 463 in 1993 - 1994. Part of
this increase appeared to be due to an increase in reproduction. The average natality
across the study years was 0.034, but a peak of 0.050 was reached in 1993. The
increase in the proportion of calves from 0.120 in 1990 to 0.210 in 1993 and 1994
suggests the successful recruitment of many of the young-of-the year. It was not
possible to calculate rates of immigration or emigration. Evidence from the high
proportion of animals present in multiple years and the absence of documentation
of unidirectional movements between Charlotte Harbor and other adjacent and
distant contiguous study areas along the central west coast of Florida indicate that
permanent immigration and emigration appear to be rare events. About 9% of the

V

dolphins appeared to be transients. Immigration, emigration, and transience are not
major influences on the number of arumals present at any given time, but they may
be important ecologically by providing a means of genetic exchange between
populations, as demonstrated for the Sarasota dolphin community and for Tampa
Bay. It was not possible to calculate a meaningful mortality rate, but stranding data
mirrored patterns of mortality reported from other parts of the central west coast of

Florida during the same period.

We attempted to summarize the components of the interannual differences
in abundance estimates. It appears that the increase in abundance from 1992 and
1993 may be attributed to a return to presumably normal mortality after high
mortality the previous year, a higher-than-normal number of young-of-the-year
recorded, a higher-than-normal number of calves recorded after a relatively low
number recorded the previous year, and a higher-than-normal number of residents
recorded in the area (due to increased movement into the area or more effective
photographic effort). These data suggest that conditions in the area improved in
1993, particularly in comparison to 1992, with relatively high recruitment and
possibly site fidelity, and improved survivorship.

A number of recommendations were made as a result of the findings of this
project. We recommend that monitoring be continued at least annually to track and
evaluate the apparent trend. More-intensive surveys would permit more-refined
determinations of natality, immigration, emigration, transience, and mortality.
Although two or three annual surveys can detect large trends in abundance, this
study illustrates the difficulty of interpreting the causes for the abundance changes
without more detailed or longer-term information. Photo-ID work should be
expanded to other seasons to examine previous reports of seasonal fluctuations in
abundance. Empirical studies designed to identify the appropriate level of effort for
mark-recapture surveys should be conducted. Photo-ID efforts should be expanded
to greater distances offshore and along the coast to examine immigration,
emigration, and transience in greater detail. Patterns of habitat use in Charlotte
Harbor should be examined through integration of GIS habitat data with our
sighting data. Efforts should be made to integrate ecological studies of the dolphins
of Charlotte Harbor with other research efforts under the National Estuary Program.
Dolphin community structure needs to be examined in more detail to define
biologically meaningful management units. Existing information on residency,
ranging and social patterns, and genetics should be integrated to arrive at population
designations. Analysis of community structure is necessary to interpret
immigration, emigration, and transience relative to population size. Sample sizes
for examination of mt-DNA haplotype distributions in Charlotte Harbor should be
augmented through biopsy darting or capture-release efforts. The genetics data
should be supplemented with telemetry data on movements and additional photo-
ID efforts. A correlation between increases in the number of dolphin strandings and
the occurrence of red tide blooms suggests that further investigation into the role of
red tide in dolphin mortality may be warranted.

Vi

Introduction

The National Marine Fisheries Service (NMFS) is responsible for establishing
quotas for take of bottlenose dolphins (Tursiops truncatus) and for monitoring the
populations of dolphins in the southeastern United States waters. Quotas have
been based on a rule-of-thumb developed by the Marine Mammal Commission in
which the annual quota has been set at 2% of the estimated dolphin abundance for a
geographical location. Most of the live-capture fishery for bottlenose dolphins has
occurred in the coastal Gulf of Mexico and the Florida east-coast waters. In recent
years, large scale mortalities of bottlenose dolphins have occurred in several
locations in southeastern U.S. waters. The NMFS completed sampling surveys in
these areas for abundance estimation, and recognized a need for low-level
monitoring of bottlenose dolphin stocks in southeastern U.S. waters, designed to
detect catastrophic changes in the stocks. The main goals of the monitoring were
detection of large-scale changes in dolphin abundance and establishment of archival
databases for long-term trend detection. Low-level monitoring could provide a
short-term means of detecting large-scale changes in population abundance and give
decision makers the information necessary to determine if modification of
management plans is necessary. To these ends, in 1987 the NMFS began funding
several local research efforts in the southeastern U.S. with the following stated
objectives:

1) Detection of large-scale (halving or doubling) interannual changes in relative
abundance and/or production of the bottlenose dolphin stocks in the southeast
U.S. The population rate parameters of relevance include: a reliable index or
estimate of local relative abundance, natality, mortality, emigration, and
immigration.

2) Establishment of archival databases for long-term trend detection in localized
geographical regions around the southeast US.

One of the regions selected by the NMFS for low-level monitoring was
Charlotte Harbor, along the southwestern coast of Florida. Charlotte Harbor was of
interest to management agencies at least in part because of the use of this region for
commercial dolphin collection. In addition to those removed by several active
collectors prior to regulation under the Marine Mammal Protection Act of 1972 (R.
Wells, pers. obs.), 43 dolphins were collected from these waters during 1973-1988
(Scott 1990). More recently, Charlotte Harbor has been designated as a National
Estuary under the Clean Water Act.

Aerial surveys to estimate bottlenose dolphin abundance in Charlotte Harbor
have been conducted on four occasions since 1975: by Odell and Reynolds (1980)
during 1975-76, and by the National Marine Fisheries Service during 1980-81, 1983-
1986, and 1994 (Thompson 1981; Scott et al. 1989; Blaylock et al. 1995). The aerial
survey study area included Charlotte Harbor proper, as well as Pine Island Sound to

7}

the south, and Gasparilla Sound to the north. The results of these surveys are
summarized in Table 1.

The approach selected for the low-level monitoring of Charlotte Harbor
olphins was photographic identification (photo-ID) surveys from small boats (see
reviews by Scott et al. 1990a; Wursig and Jefferson 1990). This technique has proven
effective in long-term studies of population-rate parameters in contiguous waters of

Sarasota Bay, immediately to the north (Wells and Scott 1990), and Tampa Bay
(Wells et al. 1995), the next bay system to the north of Sarasota. The residency
suggested by tagging studies in 1970-1971 (Irvine and Wells 1972) and 1984, and long-
term resightings of distinctive dolphins photographed by Wells (1986) during
surveys initiated -2 1982, indicated that Charlotte Harbor would be appropriate for
photo-ID surveys.

Photo-ID offers several advantages over aerial surveys for measuring certain
population rate parameters. The greatest advantage of using photo-ID methods is
the accumulation of information on the occurrence, distribution, and ranging
patterns of specific individuals. The ability to recognize individuals over time
provides opportunities to estimate abundance using mark-resight methods, to
evaluate possible cases of immigration, emigration, or transience, to monitor
individual female reproductive case histories, to determine the origins of carcasses
for mortality estimates, and to examine community structure (Wells 1986).

This report summarizes the results of five years of NMFS-sponsored
bottlenose dolphin research in Charlotte Harbor, conducted by the Chicago
Zoological Society (CZS). Annual photo-ID surveys were conducted during August
of each vear from 1990 through 1994. The study area included more than half of the
region of the aerial surveys, but did not include all of Pine Island Sound, due to
logistical and budgetary constraints. Photographs and sighting data were collected to
examine trends in abundance, natality, mortality, immigration, and emigration.

Methods

A

The Charlotte Harbor study area includes the enclosed bay waters eastward of
the chain of barrier islands from the north end of Lemon Bay southward to Captiva
Pass, as well as the shallow Gulf coastal waters and passes immediately surrounding
the barrier islands (Figure 1). The southern boundary of the study area extends from
Captiva Pass, through northern Pine Island Sound to Matlacha Bridge, east of Pine
Island. To the northeast, the study area extended to the Rt. 41 bridge over the Peace
River in Punta Gorda, and the El Jobean bridge over the Myakka River. The region
is composed of a variety of habitats and conditions, including highly productive
Seagrass meadows and mangrove shorelines, deep passes between barrier islands,
shallow, sandy Gulf waters, dredged channels, river mouths, and open bays.

This study area was selected in part because of its proximity to the long-term
Sarasota study site (Scott et al. 1990b; Wells 1991). Preliminary studies indicated that
a number of distinctively marked dolphins inhabited the region, and at least some
were present over a number of years (Irvine and Wells 1972; Wells 1986). The
photo-ID research being conducted in the Sarasota (ongoing) and Tampa Bay
(through 1993) waters to the north facilitated examination of immigration and
emigration. Inclusion of the Charlotte Harbor study area completed a nearly 200 km
long section of contiguous coastline for which movement patterns of bottlenose
dolphins could be determined.

The Charlotte Harbor study area provided a unique opportunity for
comparison with population rate parameter data collected from the Sarasota study
area. Strong similarities among the areas allowed some measure of control for the
effects of habitat on population parameters. The Charlotte Harbor study area is a
mirror image of the Sarasota study area, in terms of geography. Physiographically,
the areas are nearly identical, with bays of shallow seagrass meadows separated from
the Gulf of Mexico by long, narrow barrier islands. The bays communicate with the
Gulf through narrow passes. Each study area opens at one end into a large deep-
water, estuarine embayment, and each is restricted at the opposite end to a narrow,
artificially-maintained waterway. Both areas are of similar size. The Charlotte
Harbor area is much more nearly pristine than the Sarasota area, however.

We have divided the 701-km2 study area into five regions for assessment of
survey effort (Figure 1). Regions were identified by physiographic and effort criteria.
Because of the distances of some parts of the study area from our field stations, it
was not possible to survey all of Charlotte Harbor with uniform effort. The
segmentation was done in order to be able to quantify effort in different parts of the
study area in an attempt to make the within-region effort comparable across years.

The northernmost section, Region 1, includes Lemon Bay, a shallow bay with
a narrow dredged Intracoastal Waterway (ICW) channel and Stump Pass, a variably
navigable inlet from the Gulf of Mexico. Water depths range from less than 1 m
nearshore to 6 m in the Pass, but generally waters were 2 m or less. Coastal
development, primarily residential, was greater in this region than in all others.
Region 2 included Gasparilla Sound, Placida Harbor, Gasparilla Pass, and Bull and
Turtle Bays. Waters were generally less than 2 m deep, except for the dredged ICW
channel and a basin in Gasparilla Sound, where depths ranged up to 3 m, and
Gasparilla Pass, where depths reached 7 m. Bull and Turtle Bays are very shallow,
undeveloped, mangrove-fringed bays with extensive coverage by seagrass meadows.
Between these bays and Charlotte Harbor to the south is a wide band of shallow
waters, less than 2 m deep. Coastal development in this region in general is
intermediate between Region 1 and the remaining regions. The next section to the
south, Region 3, includes a large inlet, Boca Grande Pass, and the open waters of
Charlotte Harbor proper, along with the shallow southeastern coastal waters. Boca
Grande Pass is the primary connection between Charlotte Harbor and the Gulf of
Mexico, with depths of up to 24 m. Charlotte Harbor is about 3 m to 7 m deep

through its east-west axis, with fringing shallows of less than 2 m. Region 4 is the
continuation of Charlotte Harbor to the north and east, to the mouths of the Peace
and Myakka Rivers. The open waters of the north-south axis of Charlotte Harbor
are generally 3 m to 7 m deep, with fringing shallows of less than 2 m depth.
Freshwater inflow from the rivers varies seasonally, but continues year-round.
Little development is evident except at the mouths of the rivers, especially the town
of Punta Gorda on the Peace River. Region 5 includes the shallow waters to the
south between Charlotte Harbor and Pine Island Sound. This region includes
numerous sandy shoals and small mangrove islands, with channels through some
of the shoals and seagrass meadows. Depths average less than 2 m in most areas,
ranging up to 3 m to 4 min the channels. Low levels of residential development
occur on some of the islands.

Surv hedul

A two- to three-week window during August was selected to provide ample
opportunity to tully survey each region of the study area at least three to five times.
This timing was selected for several reasons. Late summer historically brought a
period of calm weather, providing a window of favorable survey conditions before
the cold fronts begin to penetrate southward into central Florida. The timing was
also considered to be advantageous for natality estimates. In adjacent waters to the
north, most of the year's calves were born by late summer (Wells et al. 1987; Urian
et al. in press). Based on an assumption of similar patterns of reproductive
seasonality, it seemed that a late summer survey would provide the best estimate of
numbers of calves born during that year (young-of-the-year).

Additional information on the occurrence of identifiable dolphins in
Charlotte Harbor was provided by occasional surveys during other times of the year.
Data from outside of the NMFS survey period each year were not included in
quantitative analyses for this report, but provided perspective.

Field fT

Surveys were conducted from 6-7-m outboard-powered boats. Two or, during
later years, three boats were used during each survey. Each boat was equipped with a
VHF radio, depth sounder, compass, thermometer, and eventually a hand-held
LORAN. Survey crews ranged in size from two to six people per boat. Survey
routes were selected each day based on predicted weather conditions and the status
of survey coverage. While searching for dolphin schools, the boats were operated at
the slowest possible speed that would still allow the vessel to plane, typically 33 to 46
km/hr, depending on the vessel. Once schools were encountered, the boats were
slowed to match the speed of the dolphins and moved parallel to the schools to
obtain photographs.

Every dolphin school encountered along a survey route was approached for
photographs. We remained with each dolphin school until we were satisfied that
we had photographed the dorsal fin of each member of the school, or until
conditions precluded complete coverage of the group. A suite of data including

a”

date, time, location, activities, headings, and environmental conditions were
recorded for each sighting. Numbers of dolphins were recorded in real time as
minimum, maximum, and best point estimates of numbers of total dolphins, calves
(dolphins < about 80-85% adult size, typically swimming alongside an adult), and
young-of-the-year (as a subset of the number of calves). A young-of-the-year is
defined as a calf in the first calendar year of life and is recognized by one or more of
the following features: (1) small size; 50%-75% of the presumed mother's length, (2)
darker coloration than the presumed mother, (3) non-rigid dorsal fin, (4)
characteristic head-out surfacing pattern, (5) presence of neonatal vertical stripes, (6)
consistently surfacing in “calf position" alongside the dorsal fin of the mother. The
specific parameters recorded are defined, and a sample data sheet is presented, in the
Appendices 1 and 2.

We used Nikon camera systems (FE, F3, 2020, 8008) with zoom-telephoto
lenses, motor drives, and data backs to photograph each school. Over the course of
the project, longer lenses (up to 300 mm) and auto-focus cameras and lenses were
incorporated, resulting in improved photo quality, and decreasing the time required
to obtain satisfactory photographic coverage of each group. Kodachrome 64 color
slide film was used throughout the surveys. The fine grain of this film provided
excellent clarity for resolution of fin features. Color film allowed evaluation of the
age of some wounds and fin features.

The survey team was based on Don Pedro Island, at the southern end of
Lemon Bay, near the southern extent of Region 1. This field station was 42 km from
the farthest edge of the study area in Region 4, 32 km from the most distant point in
Region 5, and 23 km from the most distant point in Region 6. The long distance and
the large areas of exposed waters in Charlotte Harbor meant that the boats often
faced abrupt changes in weather conditions and sea states during any given day, at
times preventing us from reaching or adequately covering some regions. To
facilitate access to the more distant regions, we began using a third boat in 1993 to
reduce the time required to cover these areas.

Photo-Identification Catalog

The patterns of nicks, notches, and scars on the dorsal fin and visible body
scars have been used successfully in numerous studies of bottlenose dolphins to
identify individuals over time (Scott et al. 1990a; Wursig and Jefferson 1990). Our
photographic catalog is based on exclusive categories that classify individuals with
similar features together. Each of the 12 categories of the catalog is based on: (1) the
division of the trailing edge of the dorsal fin into thirds and distinctive features
located in each third; (2) distinctive features on the leading edge of the fin; (3)
distinctive features on the anterior portion of the peduncle and (4) evidence of
permanent scarring or pigmentation patterns on the fin or body.

The primary photo-ID catalog is composed of the most diagnostic and best
quality original slides of each animal, filed alphabetically by each individual
dolphin's unique four-character code. Prints are made from the original slides and

filed in a working catalog used for initial searching for matches. A duplicate catalog
made from color photocopies of the color prints is maintained off-site as a backup
copy. We maintain three photo-ID catalogs that represent our different study areas:
the Sarasota Bay region, Charlotte Harbor, and Tampa Bay and the inshore waters of
the Gulf of Mexico. The catalog used for these analyses is a subset of a larger catalog
incorporating dolphins sighted outside of the limited Charlotte Harbor region
considered for this report. All catalogs are ultimately searched before an addition is

made to the appropriate catalog.

The photo-ID catalog for the 1990 - 1994 surveys included 16 dolphins first
identified from the Charlotte Harbor study area during 1982 through 1989. We
collaborated with Dr. Susan Shane in examination of 272 identification photographs
taken by her in Pine Island Sound during her behavioral studies (Shane 1987,
1990a,b). Examination of these photographs resulted in 24 matches with animals in
our identification catalogs for all areas, including 12 matches with our Charlotte
Harbor catalog. As of September 1995, there were 2,247 dolphins (1,870 distinctive
non-calves) in the DBRI photo-ID catalogs for all study areas, including Charlotte
Harbor.

Analysis of

Photographic slides are labeled with information from the corresponding
sighting: date, film roll number, sighting number, and location code. Labeled slides
are filed chronologically in archival-quality storage pages in binders. Comments
from sighting data sheets are read for clues and additional information to assist in
identification of animals (for example, distinctive features noted in the field, or
features distinguishing between two similar animals). Each slide is examined using
a 15-power lupe eyepiece to find all distinctive dolphins. Slides are sorted by each
identifiable individual within a sighting and the best-quality slides of each animal
showing the distinctive features of the fin are selected to compare with the photo-ID
catalog.

The most prominent feature of the fin is identified and the category that best
describes that feature is searched for a potential match. Matches are often made by
comparing the slide directly to the print in the catalog. However, with a close match
or to distinguish between fins with similar features, the original slide is used for
comparison. To verify a match between similar fins, both fins are projected using a
slide projector with a zoom lens and traced to line up distinguishing features. To
confirm long-term, long-distance, or difficult matches, three experienced photo-ID
researchers examine the potential matches and must vote unanimously on the final
match. When a match is made with a fin in our catalog, all slides are labeled with
the dolphin's unique 4-character code and its name, and the dolphin is scored as a
positive identification.

When a match is not found in the first category searched, all other possible
categories are searched to account for dolphins that have multiple identifying
characteristics. The entire catalog is searched before a new animal is added to the

catalog. If we are confident the fin is reliably recognizable, the dolphin is given a
name that describes the most obvious feature of the fin and a unique 4-character
code that abbreviates the name is selected. To be considered a catalog-quality image,
a new entry into the catalog must meet the following criteria: the entire fin, from
the anterior insertion to the posterior insertion of the dorsal fin and the trailing
edge of the fin must be visible, the image must be in focus and perpendicular to the
photographer, and, when available, both right and left side images of the fin are
selected for the catalog. The best-quality slide is labeled with the name, code, and
catalog category that describes the most prominent feature of the fin. A print is
made and added to the print catalog and the original slide is filed alphabetically in
the slide catalog.

An animal was occasionally “visually confirmed" in the field when it was
recognized because it was familiar to an observer and it was counted as a positive
identification for photo-analysis even though it may not have been documented
photographically.

For photo-analysis, a calf or young-of-the-year is considered positively
identifiable only if it can be recognized because of distinctive features that make it
identifiable independent of its mother. A small animal that appears in all slides
next to a larger animal in the "calf position,” (i.e., alongside and slightly behind the
presumed mother), is assumed to be a calf. If the calf is with an identifiable mother,
but the calf is not distinctive, it is not scored as a positive identification.

In some cases it is possible to identify animals in a sighting that are not
sufficiently distinctive to make long-term matches, or appear distinctive but are
unidentifiable because the entire fin is not visible, photo coverage is incomplete, or
photo quality is substandard. Each of these dolphins is classified as an "other..."
with some reference to the most distinguishing feature. Although it is not
considered a positive identification, an "other..." dolphin is counted toward
revision of the group-size estimates.

Fins that lack distinctive markings are considered "clean" but may also be
used in calculating or adjusting group size estimates. In some cases, "clean" fins
may be distinguished from one another within a sighting based on differences in fin
shape. This minimum count of "clean" fins is added to the positive identifications
and "other" fins to calculate the minimum, maximum, and best group size
estimates. Thus, the minimum estimate is a minimum count of distinguishable
fins within a sighting.

A grading system that integrates recognizability, photographic quality, and
coverage is used to identify the quality of a given sighting:

Grade-1 - All dolphins in the group were photographed or otherwise positively
identified. All the animals in the best field estimate are accounted for as a)
confirmed positive identifications; or b) as individuals that can be

distinguished within a sighting from a high quality photograph but do not
warrant status as a ‘marked’ dolphin in the catalog.

Grade-2 - There are photographs of some doiphins with distinctive fins that may be
in the catalog, but because of the quality of photographs it is not possible to
make appropriate comparisons with the catalog and make a match or assign an
identification.

Grade-3 - Photographic coverage is known to be incomplete, because all dolphins
were not approached for photographs, no photos were taken, film did not turn
out, sighting conditions were poor, etc.

Data P

Sighting data and results from photo-analysis are entered into the Dolphin
Biology Research Institute (DBRI) database. As of September 1995, the database
includes 10,307 sighting records of dolphin groups from Sarasota Bay, Tampa Bay,
Charlotte Harbor and the inshore Gulf waters from 1975 through 1994. We use the
FoxBase+/Mac Version 1.1 relational database management system containing
dBase programming language that permits us to write specific programs to
manipulate the database. A Macintosh IIsi computer is used for data entry and a
Macintosh Centris 650 computer is used primarily for data manipulations.

We defined our dataset based on temporal and geographic criteria. We
included sightings collected during the August surveys of 1990, 1991, 1992, 1993, and
1994 within the designated boundaries considered to comprise Charlotte Harbor
(Figure 1).

Group size estimates were derived from adjustments of field estimates based
on photo-analysis (see Appendix 2). Minimum, maximum, and best field estimates
were increased if the sum of the number of positively identified individuals plus
the number of “other...” dolphins, plus the number of "clean" dolphins exceeded
the original field estimates. The resulting revised minimum, revised maximum,
and final best estimates were used in all calculations involving group size.

Several of the abundance and trend estimates and the power analyses were
conducted at the Inter-American Tropical Tuna Commission with a VAX 3100/80
micro-computer and a 486 IBM-compatible personal computer. Linear regressions
were performed using a SAS procedure (SAS 1989). A FORTRAN program designed
for use on IBM-compatible personal computers (TRENDS2; Gerrodette 1993) allowed
us to conduct a power analysis to detect trends in abundance (Gerrodette 1987).

Esti :

The basic questions considered by this project were: "How many dolphins use
the Charlotte Harbor study area during the August survey period, and how does this
number vary from year to year?". A closed population was assumed because of the
brief period during which the surveys took place each year. There are a variety of
ways to calculate indices of abundance of bottlenose dolphins inhabiting Charlotte

Harbor. We followed the analytical procedures of Wells et al. (1995) as applied to
bottlenose dolphins in Tampa Bay during a simular study.

Method 1 (catalog-size method) simply involves tallying the number of
positively identified ("marked") individuals (M) sighted within the study area
during the survey period. We derived our overall catalog of marked animals for
each survey year by considering all sightings during the survey period regardless of
the photo grade. The inclusion of a fin in the catalog was dependent on the
recognizability of a dolphin, not the overall quality of coverage of a sighting. The
catalog-size method does not account for dolphins that are not distinctively marked.
The size of the annual Charlotte Harbor catalog (M) is an integral part of each of the
following three abundance estimation procedures.

Assuming comparable levels of sighting effort from year to year, the catalog-
size approach may provide a reasonable index for detection of trends of abundance.
To conduct a power analysis, however, a coefficient of variation (CV = var!/2 / N)
could only be calculated by considering each year (1990-1994) as a replicate sample. A
regression analysis of the five annual estimates was conducted to remove the effects
of a potential trend; a CV was then calculated from the residuals.

Method 2 (mark-proportion method) calculated the proportion of positively
identified dolphins (m) relative to the total group size (n) in each sighting of
"Grade-1" quality. The accuracy of the population-size estimates depends on the
confidence in identifications. Therefore, only Grade-1 sightings were used to derive
the proportion of marked animals. There was no relationship between group size
and the proportion of dolphins identified (r2 = 0.002).

The proportions of marked dolphins to group size (m/n) for each sighting
were averaged for each year. The total number of marked dolphins in the catalog
for a given year (M) was divided by the average proportion of marked dolphins to
yield an annual population estimate (N). A similar method was used by Shane
(1987) to estimate abundance in Pine Island Sound. A 2000-replicate non-parametric
bootstrap resampled the m/n proportions from observed groups to produce
variance estimates and percentile confidence limits.

Method 3 (mark-resight method) uses the Bailey modification of the Petersen
method to estimate abundance (Bailey 1951; Seber 1982; Hammond 1986). The
Bailey modification incorporates resampling with replacement in the model.
Because both marked and unmarked dolphins may be resighted multiple times, this
modification was deemed appropriate. The equation used was:

N = M (n2 +1) / (m2 + 1)

with a binomial variance of

v = M2 (n2 + 1) (n2- m2) / (m2 + 1)2 (m2 + 2)

where N is the population size, M is the total number of different marked dolphins
sighted during the year, n2 is the total number of dolphins sighted during all
complete surveys of the area, and m2 is the total number of marked dolphins
sighted during the same surveys. A complete survey consisted of a combination of
daily surveys that covered all of the regions (Figure 1) once during good or excellent
sighting conditions. These combinations were developed a posteriori for the
purpose of testing this estimation technique. Each ‘complete survey” required
three to six boat days over periods of three to fifteen days for completion due to the
large area to cover and the incidences of poor weather conditions. Only "Grade-1"
sightings were used to ensure that all marked dolphins present during these
sightings were identified and the group size was accurately counted. Because of the
difficulties of covering such a large area, only 2-3 complete surveys were conducted
each year. CVs were calculated from binomial variance estimates.

Method 4 (resighting-rate method) attempts to first estimate the number of
unmarked dolphins (u) in the area and then add them to the number of marked
dolphins in the catalog sighted that year (M) to estimate N. By assuming that
unmarked dolphins are resighted at the same rate as marked dolphins, the
following equation would estimate the number of unmarked dolphins:

u = (M/m2?2) (n2 - m2)

where M is the number of different marked dolphins sighted during the annual
survey period, n2 is the total number of dolphins counted from "Grade-1" sightings
during the annual survey period, m2 is the total number of marked dolphins
counted from "Grade-1" sightings during these same sightings, n2-m2 is the number
of unmarked dolphins counted from these sightings, and M/mz? 1s the proportion of
the number of marked individuals to the number of sightings of these marked
individuals. The population size is then estimated by

N=M+tu

and a CV was estimated by the regression analysis described in Method 1.

Estimati rannual Tr P lysi

Linear regression analyses were conducted to determine whether a trend was
present in the indices or estimates of abundance (i.e., the slope of the regression line
of abundance vs. year was significantly different from zero).

We used a power analysis to calculate the number of surveys or the CVs of
the estimates required to detect a trend (Gerrodette 1987). The power analysis relates
five parameters: alpha (the probability of making a Type-l error, i.e. concluding that

11

a trend exists when in fact it does not), the power, or 1 - beta (beta is the probability of
making a Type-2 error, i.e. concluding that a trend does not exist when in fact it
does), n (the number of surveys), r (the rate of change in population size), and the
CV of the abundance estimate. Additionally, one must choose whether a t- or z-
distribution and a one- or two-tailed test is appropriate, and whether r changes
exponentially or linearly. It is also necessary to determine whether the CV is
constant with abundance, the square root of abundance, or to the inverse of the
square root of abundance. Notice that the actual estimate is not used, only the
coefficient of variation of the estimate. This estimate can be the actual abundance
(population size as determined from mark-resight methods or censuses) or indices
of abundance (such as total number of marked animals in the photo-ID catalog for a
particular year, or total number of dolphins sighted per survey or time period).

One of the objectives of this research was to determine whether the photo-ID
method could detect a doubling or halving of population size with 80% certainty.
Thus, alpha = 0.05, beta = 0.20, power = 0.80, r = 1.00 or -0.50, n = 2 annual surveys,
and it is only necessary to calculate the CV required to detect a trend and compare it
with the CV of the abundance estimate calculated from the data. Alternatively, one
can use the CV of the estimate to solve for n, the number of surveys necessary to
detect the trend. In general, the lower the CV, the fewer the number of surveys
required to detect a trend (Gerrodette 1987). For mark-resight estimates, the CV
decreases as the proportion of marked animals in the population increases (Wells
and Scott 1990).

Traditionally in research, one is concerned mainly with alpha and Type-1
errors. This is conservative when considering whether to accept an alternate
hypothesis as truth or not, but may not be conservative from a management point
of view. Such a case might occur when the null hypothesis that a population is
stable is accepted when, in fact, it is declining (Type-2 error). Gerrodette (1987)
applied power analysis to linear regressions of abundance. Because the question
posed is whether a large change can be detected from one year to the next, and
because we used an annual survey period as the sampling unit, the sample size (n),
equals two. A linear regression is not feasible with only two data points, so it is
necessary to compare two distributions presumed to have known variances rather
than use a linear regression (TRENDS2 does this automatically).

Given the initial parameters specified by the NMFS (alpha = 0.05, power =
0.80, r = 1.00 or -0.50, and n = 2), one can calculate the CV necessary to detect trends
in abundance. We used a 1-tailed t-distribution for the TRENDS2 program, and
specified that rates of increase or decrease be exponential. We made this choice
because an exponential function is more typical of biological processes and because
detecting a 50% linear decline is a moot exercise given that the population would be
reduced to zero at the end of the second year. TRENDS2 also requires that the
model of the relationship between CV and abundance be specified. As suggested by
Gerrodette (1987) and a graph of our data, the "CV proportional to the square root of
abundance" option was selected. Given these parameters, a maximum CV of 0.05 is

required to detect an increasing trend and a CV of 0.07 is required for a decreasing
trend.

Assuming that the calculated estimates and variances are the true population
parameters, then a less conservative z-distribution can be used and the maximum
CVs would be 0.16 (increasing trend) and 0.23 (decreasing trend). Conversely, if a
more-conservative 2-tailed test were used, the maximum CVs would be 0.02
(increasing trend) and 0.03 (decreasing trend). We chose the 1-tailed t-distribution
option because it better fits the situation of considering a change in only one
direction at a time and because it could be argued that calculated variances may not
truly represent those of the population.

Natality was calculated as the proportion of dolphins in each sighting
considered to have been born within the calendar year. Though the total number of
calves was recorded for each group sighted, only the subset of calves considered to be
young-of-the-year was considered to be relevant to the measurement of natality
(Wells and Scott 1990). The average proportion of young-of-the-year was calculated
for each year.

Estimation pr :_Mortali

We obtained stranding records from the Southeast U.S. Marine Mammal
Stranding Network (D. Odell, pers. comm.) for bottlenose dolphins recovered from
southern Sarasota, Charlotte, and Lee counties from 1979 through 1994 to estimate a
minimum mortality rate for the Charlotte Harbor area. We examined photographs
of dorsal fins of carcasses provided by Bob Wasno of the Lee County Department of
Community Services, Tom Pitchford of the Florida Department of Environmental
Protection, and Mote Marine Laboratory's Marine Mammal Stranding Program.
We used photographs of animals that died during the period 1990 through 1995 and
were recovered within the counties encompassing the Charlotte Harbor study area.
Stranding records from outside our specified study area may be included because the
exact locations of strandings within Lee County were not available and Lee County
waters extend beyond our Charlotte Harbor study area. Photographs of the stranded
animals were examined to determine if the markings occurred post-mortem or if
decomposition obscured recognition.

We were unable to calculate rates of immigration and emigration for the
dolphins in Charlotte Harbor, because the criteria we have used in other areas (eg.,
Tampa Bay, Wells et al. 1995) were too restrictive for use in this project. To calculate
a rate of immigration, we needed to identify "permanent" movement into or out of
the study area during our survey period. "Permanent" is defined as being present or
absent for a period of at least two consecutive years (Wells and Scott 1990). For an
immigrant, we would have to document that the animal was not present for at least
two years prior to its first appearance in the catalog, and that it was seen in the study
area during each subsequent survey session (for at least two years). Thus, by

definition an immigrant would have to be absent during 1990-1991 (to clearly
establish its prior absence), first identified in 1992 (its year of immigration), and
present during 1993-1994. Similarly, an emigrant would have to demonstrate its
presence by being seen since the beginning of the study and for at least two
consecutive years before disappearing, and remaining absent for at least two years.
Given these restrictions, the only year for which such analyses would be possible
was 1992. This is the year for which we have the least data available, due to
Hurricane Andrew bringing our field season to a premature close. In the absence of
meaningful quantitative measures of immigration and emigration, we provide
qualitative descriptions of residency and movements between study areas, and we
present quantitative estimates of transience.

Marked dolphins were considered to be "residents" during the survey season
if they were identified in at least four of the five survey years. It must be recognized
that this definition of residency is limited; the repeated occurrence of these animals
during our surveys does not necessarily indicate a year-round presence.

The incidence of transience was estimated by identifying individuals that
were sighted in only one year of the five-year survey period and had no other
sighting records in the DBRI database. The incidence of transience was calculated as
the proportion of individuals that met the criteria above relative to the total catalog
size for each survey year. This rate is probably an overestimate because it may
include dolphins that in fact are not transients, but were missed during other
surveys, died, or their fins changed without being detected.

Results

Survey Effort

Surveys were conducted during windows of 10-18 days each year (Table 2).
The size of the window each year depended on weather and the number of boats
available. Weather, including Hurricane Andrew in 1992, adversely affected survey
schedules. During the first years of the project, only two boats were used, but in 1993
and 1994 three boats were used. Survey effort was measured in two ways. One
measure was a count of the number of boat-days. A boat-day was scored when a boat
left the dock to search for dolphins. On average, 24 boat-days were spent in the study
area each year (range = 16-28 days, Table 2). A more refined measure of survey effort
is the number of linear kilometers covered by our survey boats searching for
dolphins within the study area. The total number of kilometers surveyed while
"on-effort", (under excellent, good, or fair survey conditions, see appendix) are
summarized in Table 2, and are presented by region to allow a comparison of
within-region effort across years. Differences across years reflect the effects of
weather, and the use of variable numbers of boats.

Dolphins were seen throughout the study area, but they were not uniformly
distributed. Larger groups tended to be found in the more open and deeper waters

(Figures 2a-e). The total number of sightings and dolphins seen each year closely
track the level of survey effort (Figure 3). On average, six or seven photographs per
dolphin were taken each year. These results compare favorably with those of the

Tampa Bay survey project (Wells, et al, 1995).

Photo-

The level of survey effort was considered sufficient to warrant generation of
abundance estimates based on mark-resighting analyses. This conclusion was
supported by the high proportion of identifiable dolphins in the population (58% to
80%, Table 3), and the frequency distribution of resightings of identifiable dolphins
within survey years (Figures 4a-e). About one quarter of the dolphins were sighted
at least twice during a given survey year, up to a maximum of 8 times each.

Our Charlotte Harbor catalog for 1990-1994 included 411 different dolphins.
The catalog size provides a minimum population estimate for the Charlotte Harbor
study area ranging from 165 identifications in 1992 to 243 in 1994. On average, 55%
of the dolphins in an annual catalog were also seen in either the previous or
subsequent year, 51% were seen two years earlier or later, 51% were seen three years
earlier or later, 50% were seen four years earlier or later (Table 4).

Photographs taken during the 1990-1994 NMFS surveys built upon an existing
Charlotte Harbor catalog initiated in 1982 (Figure 5; Wells 1986). Of the animals
identified prior to the initiation of the surveys, 16 individuals were sighted
subsequently during the surveys in 1990-1994. As expected, during the initial years
of the surveys many identified dolphins were added to the catalog. New fins were
added to the catalog at a slower rate during subsequent years (Figure 5). The
proportion of first-time identifications comprising the annual catalog each year
declined from 99% in 1990 to 14% in 1994. These results are comparable to those
from the Sarasota community (Wells and Scott 1990) and Tampa Bay (Wells et al.
1995), suggesting a relatively closed population for the Charlotte Harbor study area.
Identifications added to the catalog over the years may represent changes to the fins
of known animals, non-distinctive calves acquiring new markings (only a small
number of calves are in our catalog), or animals that may have been missed in
previous years. We found that overall there were few changes to fin markings
throughout the surveys, and minor changes could be detected by a skilled observer
familiar with the catalog. However, dramatic changes to fin markings could easily
be undetected and could result in a previously identified animal being entered twice
in the catalog.

The stability of fin markings over time enhances the probability of resighting
individuals. The high frequency of resighting individuals and the long-term
sighting histories suggeste 1 high degree of residency for some animals in the
Charlotte Harbor study area during the survey period (Figure 6). The consistency of
the catalog and stability of fin markings over time contribute to our confidence in

meeting the assumptions associated with generating abundance estimates from
mark-resighting analyses.

Abundance Estimates and Trends

The catalog-size index (Method 1) resulted in minimum population estimates
of 165 to 243 dolphins over the five years of the study, with an average of 203 (Table
3). The Method-1 estimates are known to be underestimates because they do not
take into account the unmarked dolphins. Methods 2, 3, and 4 attempted to correct
for this underestimation.

Method 2 (mark-proportion method) calculated population-size estimates
from proportions of marked animals relative to revised minimum, revised
maximum, and final best group size estimates. The differences between minimum
and maximum population-size estimates were so small that we present only the
estimates based on the final best group size. The number of dolphins estimated by
Method 2 ranged from 226 to 422, with an average of 302 (Table 3).

Method 3 (mark-resight method) provided annual point estimates from the
combined sightings made during two or three "complete surveys’. The estimates
ranged from 238 to 385 across all years, with an average of 313 (Table 3).

Method 4 (resighting-rate method) provided annual point estimates ranging
from 194 to 385 dolphins, with an average of 267 (Table 3).

The abundance estimates were examined for trends across the five years of
the surveys. Population-size estimates varied from one year to the next (Figure 7).
The trends in abundance roughly followed variation in field effort, but the
relationship did not appear to be strong. Comparison of 95% CL for Methods 2 and 3
(Figure 8) indicate a significant difference in the abundance estimates from the first
three years compared to the last two years of the survey.

Power Analysis

The catalog-size index (Method 1) used a regression analysis of the five
annual estimates to remove the effect of a potential trend and calculated a CV of 0.15
from the residuals (although no trend was apparent, a test with only five data points
would be sensitive to outliers and would have low power). Given that alpha = 0.05,
power = 0.80, r = 1.00 or -0.50, and CV = 0.15, we can then calculate the minimum
number of surveys necessary to detect a trend. Three survey sessions would be
required to detect a decreasing trend and four for an increasing trend.

A bootstrap variance procedure applied to Method 2 (mark-proportion
method) yielded CVs ranging from 0.04 to 0.06, with an average CV of 0.05. This
would allow an increasing or a decreasing trend to be detected in two surveys.

The CVs for the estimates for the mark-resight method (Method 3) ranged
from 0.06 to 0.10, with an average CV of 0.08 for 1990-1994. This would allow an
increasing or a decreasing trend to be detected in three surveys.

Method 4 (resighting-rate method) used the regression analysis described in
Method 1 to yield a CV of 0.23. Three survey sessions would be required to detect a
decreasing trend and four for an increasing trend.

Natality
The natality rate, the proportion of dolphins considered young-of-the-year,

varied during the course of the surveys, ranging from 0.020 to 0.050 (Table 5). If
these rates are applied to the population size estimates derived by Method 2 (mark-
proportion method), then annual estimates of 7 to 17 young-of-the-year are derived
for the Charlotte Harbor study area. The mark-proportion estimates are used here
because the variances were low, and the estimates for population size and natality
were calculated in a similar manner, i.e. on a proportion-of-school basis.

Mortality
There were 116 records of stranded animals from South Sarasota, Charlotte,

and Lee counties from 1979-1994; 70 of these records were from 1990 to 1994 (Table 6,
Figure 9). We were unable to calculate a mortality rate due to the bias associated
with an increase in stranding response effort since the mid-1980s. Coastal
development and boating activity on Charlotte Harbor waters have also increased
dramatically, possibly contributing to the discovery of carcasses in previously
isolated areas. However, there are still many remote and inaccessible areas within
Charlotte Harbor where carcasses are unlikely to be found. All these factors
confound determination of the actual number of strandings and make it impractical
to calculate a mortality rate based on stranding records alone.

In an attempt to distinguish between mortalities and other kinds of losses
from the population, photographs of stranded dolphins were examined. A total of
30 photographs were available to compare with the photo-ID catalog. Dorsal fins in
photographs of 7 animals were deemed non-distinctive, i.e., they belonged to
neonates, calves or otherwise had no diagnostic markings. Twenty-three animals
were considered distinctive and were used to compare with the photo-ID catalog
(Table 6). We identified 2 of the stranded animals: One animal was sighted in the
first four years of the Charlotte Harbor surveys and stranded in March of 1994. The
other was first identified in 1990 and died in November of 1991.

Of the 411 dolphins in the 1990-1994 Charlotte Harbor catalog, 165 were not
seen during the last year of the study. Two of these (0.012) were confirmed as
mortalities based on fin identifications.

Immi
We were unable to develop a reasonable quantitative estimate of rates of
immigration or emigration for Charlotte Harbor due to the brevity of the study

period, as discussed under "Methods". All available data indicate that permanent
immigration and emigration were rare occurrences. None of the more than 900
dolphins identified from Sarasota Bay (1975-1994) and Tampa Bay (1975-1993), the
adjacent waters to the north, nor the 272 dolphins in photographs provided by
Shane from her Pine Island Sound study area immediately to the south, were
identified as immigrants to the Charlotte Harbor area during our study. Conversely,
none of the 411 dolphins identified from Charlotte Harbor waters during 1990-1994
were observed to take up residence in Sarasota Bay or Tampa Bay.

Residency to portions of the Charlotte Harbor study area was suggested by
repeated sightings of some individuals in the same waters over multiple years.
Sixteen of the 411 dolphins in the catalog (3.8%) were also seen in the area prior to
the initiation of the surveys in 1990. Twelve of these were first identified during
1982 - 1984. Twenty-seven dolphins (6.6%) were identified from the Charlotte
Harbor study area during all five of the survey years; 97 (23.6%) were seen during at
least four of the five survey years.

We did not find animals with regular movements through the entire study
area when we examined those seen in multiple years, and those with the requisite
15 or more sightings needed for description of a home range (Wells 1978). Instead,
we found clusters of sightings within localized areas, as has been described
elsewhere along the central west coast of Florida (Wells 1986; Wells et al. 1995). For
example, "CURL" was seen frequently in Lemon Bay during 1990 - 1994 (Figure 10 a).
Sightings of dolphins such as "THUV" (1982 - 1991, Figure 10 b), "HISC" (1990 - 1994,
Figure 10 c), and "TSMD" (1990 - 1994, Figure 10 d) were concentrated in Gasparilla
Sound. Long-term sightings of dolphin "RPPR" (1982 - 1994, Figure 10 e) were
spread through both Lemon Bay and Gasparilla Sound. Sightings of dolphin
"LGSL" (1982 - 1994, Figure 10 f) were concentrated in and near the deep waters of
Boca Grande Pass. "TFLN" (1982 - 1993, Figure 10 g) was seen repeatedly in the
shallows in northern Pine Island Sound. Dolphins "CLTO" (1982 - 1992, Figure 10 h)
and "ZIGY" (1990 - 1994, Figure 10 i) were seen primarily in the open, deeper waters
of southern and western Charlotte Harbor proper. Dolphin "POTP" (1990 - 1994,
Figure 10 j) was seen primarily in the shallow waters of eastern Charlotte Harbor.
Little can be said about the year-round residency of these animals, except that all of
the catalog members identified prior to the surveys were seen in months other than
August. While these examples provide documentation of the tentative existence of
long-term home ranges in the Charlotte Harbor area, they should not be interpreted
as indicating that all of the dolphins in the area fall into these patterns. Additional
sightings during different seasons would be required to accurately assign home
ranges or other movement patterns to the dolphins in Charlotte Harbor.

Movements back and forth between Charlotte Harbor and waters to the north
were recorded for ten (2.4%) dolphins of the 411 in the Charlotte Harbor catalog. A
few individuals, such as "DIPT" (Figures 10 k,!) appear to spend equivalent amounts
of time in southern Sarasota, Lemon Bay, and Gasparilla Sound, suggesting the
existence of a home range connecting these two regions. Others, such as"RY34"

(Figures 10 m,n) and "BSLC" (Figures 10 o,p), emphasize one region, Sarasota or
Charlotte Harbor, over the other, but on occasion move between regions. The most
extreme movements were made by "SLIT" (Figures 10 q,r). This dolphin was
observed in eastern Charlotte Harbor in August 1990, and in southern Tampa Bay in
July 1991, a minimum swimming distance of about 125 km. It was not possible to
describe a pattern for this animal based on only two sightings.

The longer-distance movements were similar to those demonstrated by
Sarasota males making occasional excursions into Tampa Bay (Wells 1993; Wells et
al. 1995). The gender is known for only three of the ten dolphins moving between
regions. Two of the dolphins traveling the longest distance between regions are
known males ("BSLC" and "RY34"), whereas one of the dolphins for which
sightings are more evenly spread across a more limited extent of border waters is a
female ("BRDO"). None of the other seven dolphins have been seen with a calf of
their own, suggesting, but not conclusively demonstrating, that they may be males.

Limited movements between our Charlotte Harbor study area and waters to
the south were indicated by matches with 12 of 272 photographs provided by Shane
from her study area including southern Pine Island Sound and associated waters.
These findings also supported the concept of local residency for dolphins in this
region, since none of the dolphins matched between our Charlotte Harbor catalog
and Shane's photographs were seen north of regions three and four of our study
area. In addition, while another 12 Shane dolphins were identified in our records
from nearby waters outside of our Charlotte Harbor study area, none of Shane's 272
dolphins were known from our Sarasota or Tampa Bay identification catalogs.
Shane (1987) reported that several of her dolphins apparently inhabited home
ranges in Pine Island Sound. Thus, at least some of the Charlotte Harbor and Pine
Island Sound dolphins appear to follow the home range mosaic pattern seen
elsewhere along the central west coast of Florida, in Sarasota and Tampa Bay (Wells
1986; Wells et al. 1995.).

Dolphins identified during only one year of the surveys were defined as
transients. There were a minimum of six and a maximum of 34 dolphins per year
that met our criteria for transience (Table 4) representing 4% to 14% of the annual
catalog size. This should be considered a maximum estimate, since it may also
include animals present during multiple years but not identified because of
undetected changes to the dorsal fin, or because they were not photographed. None
of the "transient" animals was seen in the Charlotte Harbor study area outside of the
survey season, nor were they seen in adjacent study areas, so their origins and
destinations remain undetermined.

Discussion

Photo-I iff

The ability to identify individuals over time using natural markings has
proved to be a valuable and benign research tool and a standard in population
studies of marine mammals. Maintaining a photographic database of individual
dolphins enables researchers to monitor not only population parameters but habitat
use, social association and distribution patterns.

The high proportion of marked dolphins and the high frequency of
resightings underscores the importance of including only excellent quality images of
distinctively marked individuals in the photo-ID catalog. This minimizes
subjectivity in the matching process and reduces the chance of making incorrect
identifications or missing them altogether.

The development and use of our photo-identification catalog has been tested
in three study areas, including Charlotte Harbor, and has proven effective in each
case. However, as the catalogs grow and we expand into different study areas, we
recognize the utility of developing computer-assisted matching and archiving
abilities.

A nce E

Comparison of the point abundance estimates from Methods 2, 3, and 4
indicates reasonable consistency across methods, and an indication of change from
the first three years to the last two years of the study (Figure 7). In all cases the lower
95% CLs were greater than or equal to the minimum count provided by the catalog-
size method. Thus, if we consider the most extreme 95% CL values to be the limits
to our estimates, the number of dolphins using the Charlotte Harbor study area
during the surveys was between 198 and 369 during 1990 - 1992, and between 315 and
463 during 1993 - 1994.

We attempted to identify the reasons for the apparent increase in abundance
of dolphins in Charlotte Harbor during the later years of the survey. Contra-
indicative results for Methods 2 and 3 in 1990 confound evaluation of the
significance of differences between 1990 and later years (Figure 8). An apparent
increase from 1992 to 1993 and 1994 was also evident, but field effort limitations
brought about by Hurricane Andrew complicate interpretation of this year's
estimate. Consistent patterns were obtained for both Methods 2 and 3 for
comparisons between 1991, and 1993 and 1994, however. Based on Method 2, the
abundance estimate from 1991 increased 31% and 61% in 1993 and 1994, respectively.
For Method 3, the comparable increases were 40% and 45%. For perspective, this
increase, within the summer season across years, is much smaller than the summer
to winter increases of 176% and 223% reported by Thompson (1981) and Scott et al.
(1989) for Charlotte Harbor and Pine Island Sound.

Though the increase does not represent an interannual doubling of the
population, the change was significant, based on comparisons of 95% confidence
limits (Figure 8). The increase was evident through all four abundance estimation
methods, and it ran counter to the patterns of consistency across years demonstrated
for Tampa Bay and Sarasota (Wells et al. 1995; Wells and Scott 1990). Our
evaluation approach was to first examine corroborative indicators of the change,
and then to test hypotheses about the possible biological or methodological source(s)
of the increase.

The apparent increase in numbers of dolphins during 1993-1994 was
corroborated by changes in the number of dolphins sighted per unit of sighting
effort. For this analysis, we divided the sum of the final best point estimates of
numbers of dolphins for each sighting for each year by the number of kilometers of
survey transects for that year. This density indicator should be less prone to
potential biases that might have resulted from violations of mark-recapture
assumptions. The number of dolphins per km increased by 14% from 1991 through
1993 and 1994 (Table 7). This measure provided additional supportive evidence of
an increase in the numbers of dolphins in Charlotte Harbor. We hypothesized three
potential biological sources of dolphins to account for the increase: (1) through
recruitment of young, (2) through an influx of new dolphins, and/or (3) from the
return of previously identified individuals.

If the increase was due to recruitment of young, then several expectations
follow. If we assume that Charlotte Harbor is a relatively closed population unit,
and the entire increase resulted from reproduction, then the number of young-of-
the-year during a given year should be greater than or equal to the change in
abundance from the previous year. As can be seen from Table 5, production of
young was nearly 2.5 times greater in 1993 than in 1990. At no time, however, does
reproduction during one year entirely account for abundance increases in the next
year.

If recruitment of young accounted for some, but not necessarily all, of the
apparent abundance increase, then the proportion of marked animals (m/n for
Method 2, Table 3) should decline over the years, since identifying marks tend to be
acquired with age, and calves tend to be less marked than older animals. The
accumulation of young-of-the-year from several years of increased reproductive
output should be reflected in increased numbers of unmarked calves and juveniles
in later years. The proportion m/n did in fact decline, from 0.80 in 1990, to 0.58 in
1994, suggesting a dilution of the pool of marked animals by young, as-yet
unmarked individuals.

Any increase indicated from mark-recapture analyses that is due to
recruitment of young, should be expected to be reflected by other indicators that are
not based on marked animals. Increases in numbers of young-of-the-year should
result in subsequent increases in calves. The number of young-of-the-year per
kilometer of survey transect tripled from 1990 through 1991, 1992, and 1993 (Table 7).

21

The number of calves of all ages observed per kilometer of survey transect increased
from 1990 values by 20% in 1991 and 1992, 40% in 1993, and 30% in 1994 (Table 7).
Thus, it seems reasonable to conclude that at least a portion of the apparent increase
in abundance of dolphins in Charlotte Harbor is the result of increases in
reproduction during the course of our project.

If reproduction accounts for only a portion of the increase in abundance, then
the balance must come from an influx of non-calves, either new to the area, or
residents that had not been identified in the middle years of the study. As described
above, non-calves would be expected to have acquired markings over time. Thus,
an influx of new animals should be reflected in an increase in the annual catalog
size in later years. Such an increase was apparent, but not dramatic (Figure 5). The
number of new animals added to the catalog each year declined from 1990 - 1991
through 1993 - 1994, however, indicating that many, but not all, of the non-calves
identified in later years were re-identifications of animals originally added to the
catalog in earlier years. In addition, the average proportion of dolphins in the
catalog in a given year that were identified in previous or subsequent years
increased in 1993 - 1994 (Table 4).

This increase may be explained partially by fluctuations in the timing of
seasonal increases in abundance. Aerial surveys by Thompson (1981) and Scott et al.
(1989) have shown summer-to-winter increases of 176-223% in Charlotte Harbor and
Pine Island Sound. If the main reason for the increased abundance was an influx of
non-calves, then we would expect the proportion m/n to remain relatively constant
over the five years. The fact that the proportion declined over the years suggests
that more of the increase is due to reproduction than to an influx of older, better-
marked animals (Table 3). The source of additional non-calves in Charlotte Harbor
was not the contiguous coastal waters to the north, based on the results of censuses
in Sarasota and Tampa Bays. It seems likely that any additional dolphins would
have originated in the Gulf of Mexico or Pine Island Sound.

Thus we are left with a series of potential explanations for the apparent
increase, none of which alone seems sufficient to explain the entire increase. In
terms of relative contributions to the increase, it seems that recruitment of young
had a greater potential effect than did reidentifications of earlier catalog members,
and each of these accounted for more of the increase than did an influx of new non-
calves.

We examined the possibility that the increase was at least in part a result of
methodological complications, perhaps exaggerating a smaller real increase in
numbers of dolphins. The low CVs, only slightly larger than those obtained by
Wells et al. (1995) for our first application of these estimation techniques, during the
Tampa Bay surveys, argued against methodological problems. We explored them,
however, because of several differences in methods between the two studies.

The primary methodological differences involved level of effort. We had
fewer boat-days each year for the Charlotte Harbor surveys than for the Tampa Bay
surveys due to budgetary limitations. Though the Charlotte Harbor study area was
82% as large as the Tampa Bay study area, we had only 56% as many within-study-
area boat-days each year compared to Tampa Bay. Fewer boat-days translated into
fewer kilometers of survey transects, which meant less intensive photographic
coverage of dolphins in the study area than was accomplished in Tampa Bay. This
in turn might have affected the development of the identification catalog, resulting
in an artificially low M in some cases. Differences in weather conditions from year
to year resulted in varying geographical coverage within the study area, which may
also have affected the size of M, and may have influenced m/n as well. Each of
these factors is critical to the calculation of abundance estimates.

Each of the abundance estimation procedures assumed that M accurately
represented the pool of marked dolphins in the study area during the survey period,
and was independent of level of effort. The high proportion of marked dolphins
(m/n), the relatively consistent values for M from year to year, and the numbers of
resightings of marked individuals over the course of each survey suggested that we
had obtained reasonable coverage and established a representative identification
catalog in Tampa Bay (Wells et al. 1995). In Charlotte Harbor, however, m/n
declined over time, the numbers of resightings per individual were smaller than
Tampa Bay (Figure 6), and M fluctuated across years.

One way in which effort might influence M would be through uneven
geographical distribution of surveys resulting in differential exposure to marked
individuals. Given the existence of individual ranging patterns as proposed earlier
in this report, decreased survey coverage of portions of the study area might mean
fewer opportunities to photograph residents of those regions, resulting in a smaller
and inaccurate M. Effort was not uniform across regions from year to year (Table 2).
Adverse weather conditions made it difficult to reach the more distant regions,
including Region 4 (Charlotte Harbor North) and Region 5 (northern Pine Island
Sound, Figure 1), during some years. Our survey coverage of these two regions in
1994 was approximately double the coverage during the early years, and M was
greater than in any previous year.

Region 5 was a potential source of complications regarding M both because
coverage was variable from year to year, and also because it opened into greater Pine
Island Sound to the south, a potential source of new dolphins or destination for
previously identified dolphins, outside of our study area. We attempted to control
for these complications by recalculating abundance estimates without including
Region 5 sightings, or the marked dolphins sighted only in Region 5. This analysis
showed that Region 5 had little effect on M or on the abundance trend.

We considered the possibility that uneven geographical coverage could result
in a biased m/n. If this ratio varies from region to region, then differential coverage
could result in a biased overall ratio, as applied in Method 2. We found that the

ratio m/n was smaller in Regions 4 and 5 than in the other regions, and these
regions were over-represented in the survey efforts of later years as compared to the
other regions. This provided one potential explanation for the decline in the
overall m/n in later years, and may have contributed to the apparent increase in
abundance as evident from the results of Method 2. The "complete survey days" of
Method 3 control for survey effort, however, and the general level of agreement
between the results of Methods 2 and 3 suggest that a potentially biased m/n was not
a major contributor to the increase in abundance.

The level of effort in Tampa Bay was greater and more consistent from year to
year than in Charlotte Harbor. For example, due to Hurricane Andrew coverage of
all regions in 1992 decreased to 51% - 65% of the kilometers surveyed in other years,
with a concomitant decline in M to 68% to 93% of the levels from the other years.
We examined the data for a direct relationship between survey effort and catalog
size, by regressing M against number of boat-days and numbers of kilometers
surveyed. No strong linear relationships were found, but M vs. boat-days
approached statistical significance (r2 = 0.74, p = 0.06), hinting at the role of effort in
the development of an adequate catalog. Our findings suggest that an optimal level
of effort exists between that expended in Tampa Bay and that in Charlotte Harbor.
Empirical studies designed to identify the appropriate level of effort for mark-
recapture surveys would be helpful.

Thus, methodological problems did not appear to be the primary factor in the
increase in the abundance of dolphins in Charlotte Harbor. Though the reasons for
the increase can not be fully explained with the information available, the increase
appears to be real, and appeared to be contributed to by several factors. The low CVs
associated with the abundance estimates provide additional confidence in the trends
that are evident. It is recommended that future surveys attempt to eliminate some
of the variables considered in the discussion above by striving for more intensive,
uniform effort throughout the study area.

It is difficult to interpret comparisons of our abundance estimates to those
reported from aerial surveys of Charlotte Harbor, because of methodological
differences, and because of differences in the areas surveyed. The aerial surveys
typically reported abundance estimates from Charlotte Harbor and Pine Island
Sound combined, whereas our vessel surveys only included the northernmost
portion of Pine Island Sound, due to logistical constraints. Our average abundance
estimate from Method 2 (mark-proportion) for our limited survey area was
comparable to the upper 95% CLs reported from the same season by Thompson
(1981) and Scott et al. (1989) for their larger study area. As has been noted in other
comparisons of vessel vs. aerial surveys (Scott et al. 1989; Wells et al. 1995), the aerial
surveys appeared to have underestimated the numbers of dolphins in Charlotte
Harbor.

The estimates we have derived reflect the numbers of dolphins found in the
Charlotte Harbor study area at least once during a two- to three--week period in

August of each year. The estimates are based on a catalog that includes all of those
dolphins for which satisfactory identification photographs were obtained during the
survey period, without distinguishing between differences in the degree of use of
the study area waters by different dolphins.

The catalog makes no distinction between those dolphins using the waters of
the study area on a regular basis vs. those photographed during an infrequent
passage through the study area. A number of overlapping home ranges occur along
the central west coast of Florida, including Tampa Bay, Sarasota Bay, and Charlotte
Harbor (Wells 1986), and home ranges apparently exist in Pine Island Sound (Shane
1987). The degree of overlap in home ranges in the Charlotte Harbor study area
appears to vary. The probability of finding a given dolphin occupying a partially
overlapping home range would be a function of the degree of overlap. The limits of
our study area were not biologically based. They did not necessarily coincide with
home range boundaries, for example, and therefore do not address the relative
importance of waters and habitat features in the study area. Evaluation of the
biological basis of population units has important management implications, but
this requires more-detailed analysis of the community structure of dolphins in the
Charlotte Harbor area.

Natality
Natality is likely underestimated because, if a diffuse calving season is

assumed, then it is likely that some young calves were lost prior to each annual
survey, and some may have been born after the survey. A spring through early fall
peak in calving with occasional births occurring at anytime during the year has been
reported for Sarasota Bay (Wells et al. 1987) and for the west coast of Florida in
general (Urian et al.. in press). Thus, the actual crude birth rate may have been
higher than the 0.020 to 0.050 reported from the 1990-1994 surveys.

The average Charlotte Harbor natality estimate of 0.034 for the period 1990-
1994 is comparable to that reported for Tampa Bay for 1988-1993 (0.033 + 0.0909,
Wells et al. 1995), and slightly lower than that reported for Sarasota Bay (0.055 +
0.0089 for Sarasota dolphins was calculated for the period 1980-1987 (Wells and Scott
1990). Observational effort in Sarasota has been ongoing, providing opportunities to
observe a higher proportion of births. The narrow window for the Charlotte Harbor
survey means that some calves are more likely to be missed. Thus, the Charlotte
Harbor natality measure should be compared to a Sarasota measure between the
crude birth rate and the recruitment rate (the proportion of calves surviving to age
1). For Sarasota Bay, the mean recruitment rate for 1980-1987 was 0.048 + 0.0085
(Wells and Scott 1990). Therefore, a comparable measure of Sarasota natality might
be between 0.048 and 0.055.

The variation in the natality rate over the five-year survey period also
supports the conclusions drawn from the abundance estimates regarding the
increase in population size.

ty
‘n

Mortality

Measurements of dolphin mortality rates for Charlotte Harbor proved to be
difficult to obtain during our survey period. In most cases we were unable to
distinguish between mortalities, emigrations, undetected fin changes, and animals
missed during the Charlotte Harbor surveys. In Sarasota, it has been possible to
evaluate losses from the population from two directions, through the collection and
examination of carcasses of identifiable individuals, and through records of
disappearances of known individuals (Wells and Scott 1990). Mortality estimates
are facilitated in Sarasota as compared to the Charlotte Harbor project because
Sarasota involves a smaller number of dolphins with a higher proportion of them
being identifiable, a smaller study area, a more-intensive, year-round monitoring
effort, and more-complete and consistent stranding response effort.

The number of strandings reported during the Charlotte Harbor survey may,
however, provide a relative index for comparison of mortality patterns. Dolphin
strandings in Sarasota Bay, Tampa Bay and more generally along the central west
coast of Florida followed the Charlotte Harbor pattern of dramatic increase from
1990 to 1991-1992, with a decline in 1993 (Wells et al. 1995). In Sarasota, strandings
reached levels two to three times normal from late 1991 through 1992 resulting in a
10% decrease in the size of the Sarasota population (unpublished data). No such
decline was observed in Charlotte Harbor, however. Severe red tides from blooms
of the dinoflagellate Gymnodinium breve occurred along the central west coast of
Florida during 1991, 1992, and 1994, the years of greatest numbers of strandings.
Though no direct cause-effect relationships between red tide outbreaks and dolphin
mortalities have yet been identified conclusively, the correlation noted here and
elsewhere (Geraci 1989) suggests that further investigation may be warranted.

Uneven stranding response effort in Charlotte Harbor over the five years of
the survey precluded quantitative trend analyses over the entire period of the
project. The situation in Charlotte Harbor could improve in time. Stranding
response teams are becoming more active in Charlotte Harbor, and communication
between teams is improving. We know that good photographs of fresh carcasses can
provide the basis for identifications (Urian and Wells 1993). These identifications
are important not only for monitoring the population, but also because knowing the
origin of a carcass can provide information that may aid in understanding cause of
death or interpreting levels of environmental contaminants in tissues. Long-term
and more frequent photographic monitoring of ine dolphins in Charlotte Harbor
would improve the basis for identifying and evaluating disappearances of catalog
members.

Immigration/Emigration/Residency /Transienc

Both immigration and emigration rates are difficult to interpret because of a
number of potentially confounding factors. The survey effort was limited to a two-
to three-week period, thereby minimizing the opportunity to identify dolphins in
other times of the year and other areas. Changes to the fins may hinder our ability
to identify individuals, resulting in the scoring of the changed fin as a new

identification and the original identification as a loss. Unidentified or missed
mortalities obscure actual emigration rates by counting them as losses instead of as
known mortalities. It is also possible animals were in the study area but not sighted,
or were photographed but not identified because of inadequate photographic quality
or coverage (Slooten et al. 1992).

Overall, about 9% of the Charlotte Harbor population was estimated to be
transient, whereas an average of 53% of the identifiable dolphins was known from
multiple years. The low incidence of immigration, emigration and transience
found for the dolphins in the Charlotte Harbor study area in the five-year period
suggest a relatively closed population, at least during the August survey period.
Resident dolphins have a greater chance of being resighted than do animals that are
known to have extended home ranges. Several individuals have been resighted in
the study area opportunistically during different seasons.

The apparent increase in abundance over the five years, and the dramatic
seasonal increase reported from the aerial surveys suggested that Charlotte Harbor
may not be as closed a unit as Sarasota or Tampa Bays. Seasonal increases from
summer to winter of 176% and 223% reported by Thompson (1981) and for Charlotte
Harbor and Pine Island Sound are much greater than the 25% seasonal increase
reported for Tampa Bay (summer to autumn, Scott et al. 1989). Shane (1987)
reported seasonal changes in patterns of occurrence in Pine Island Sound, but did
not present estimates of change in abundance. No significant seasonal changes in
abundance have been noted for Sarasota Bay, although seasonal changes in habitat
use were evident (Wells 1993). Assuming that the seasonal variations in Charlotte
Harbor reported from the aerial surveys reflect a true increase in abundance, then
photographic identification surveys during the season of greatest abundance may
shed light on the potential source of some of the increase in abundance reported
from our August surveys.

Summary of Population Parameters for Charlotte Harbor

During August of each year from 1990 through 1994, an average of about 308
dolphins used the Charlotte Harbor study area (average of Methods 2 and 3). The
abundance apparently increased from 198 - 369 (95% CLs, Methods 2 and 3) in 1990 -
1992 to 315 - 463 in 1993 - 1994. Part of this increase appeared to be due to an increase
in reproduction. The average natality across the study years was 0.034, but a peak of
0.05 was reached in 1993. The increase in the proportion of calves from 0.12 in 1990
to 0.21 in 1993 and 1994 suggests the successful recruitment of many of the young-of-
the year. It was not possible to calculate rates of immigration or emigration.
Evidence from the high proportion of animals present in multiple years and the
absence of documentation of unidirectional movements between Charlotte Harbor
and other adjacent and distant contiguous study areas along the central west coast of
Florida indicate that permanent immigration and emigration appear to be rare
events. About 9% of the dolphins appeared to be transients. Immigration,
emigration, and transience are not major influences on the number of animals
present at any given time, but they may be important ecologically by providing a

means of genetic exchange between populations, as demonstrated for the Sarasota
dolphin community and for Tampa Bay (Duffield and Wells 1991, Wells and Scott
1990, Wells et al. 1995). It was not possible to calculate a meaningful mortality rate,
but even though there was no indication from stranding data of catastrophic losses
from the population during the survey period, the data mirrored patterns of
mortality reported from other parts of the central west coast of Florida during the
same period.

We attempted to summarize the components of the interannual differences
in abundance estimates in Table 8. It appears that the increase in abundance from
1992 and 1993 may be attributed to a return to presumably normal mortality after
high mortality the previous year, a higher-than-normal number of young-of-the-
year recorded, a higher-than-normal number of calves recorded after a relatively
low number recorded the previous year, and a higher-than-normal number of
residents recorded in the area (due to increased movement into the area or more
effective photographic effort). These data suggest that conditions in the area
improved in 1993, particularly in comparison to 1992, with relatively high
recruitment and possibly site fidelity, and improved survivorship.

Comparison of Abundance Estimation Meth

Methods 2, 3, and 4 produced similar estimates of population size (Table 3)
even though the sampling units and calculations differed. All three of these
methods have similar assumptions: a closed population, an equal probability of
sighting all animals, random samples of dolphins resighted, and permanent and
reliable marks on the dolphins.

To detect a trend in abundance, the method with the lowest bias, greatest
precision, and easiest implementation in the field would be preferred. The accuracy
of the estimates depends greatly on the adherence to the assumptions above. The
problem of heterogeneity of sighting probabilities can cause a negative bias in the
estimate of N (e.g., Hammond 1986), and has been shown to occur in mark-resight
studies on bottlenose dolphins in Sarasota Bay (Wells and Scott 1990). To examine
the effects of heterogeneity on the different methods, a greater understanding of the
community structure of the area is necessary. Method 3, the mark-resight method,
attempted to reduce the potential effect of heterogeneity by balancing the coverage of
the regions within the study area, under the assumption that multiple communities
of dolphins having restricted home ranges could be over- or under-sampled if
coverage is not equal for all regions. Piecing together segments surveyed over a
period of several weeks, however, could lead to biases if the assumption of
population closure was violated. This assumption, based on the dolphin
communities of Sarasota Bay, could be tested when the movements and ranges of
Charlotte Harbor dolphins are better known.

The precision of the estimates is largely a result of the size and number of the
samples and the proportion of marked dolphins in the population (M/N). Three of
the above methods illustrate a range of compromises that can be made between the

first two factors. The mark-proportion method (Method 2) sampled individual
dolphin schools as units; this led to a large number of replicates, for which a
bootstrap resampling method for estimating variance works well. Alternatively, the
resighting-rate method (Method 4) used the entire survey season as a sampling unit,
yielding large sample sizes per season (139-381 dolphins), but at the expense of
replicate sampling. The mark-resight method (Method 3) used two or three
"complete surveys" of the area as a sampling unit, and about 43-170 dolphins per
field season, with sample sizes of about 2-88 dolphins per survey. The CVs
calculated from Methods 2 and 3 were both acceptably low, although they cannot be
compared directly because of the difference in variance-calculation methods
(Method 2 = non-parametric bootstrap; Method 3 = binomial).

All of these methods may be prone to a negative bias due to heterogeneity of
sighting probabilities, but this would be particularly true for Methods 2 and 4 if care
was not taken to survey all areas at least some time during the field season.
Estimates from Methods 2 and 4 averaged 4.9% and 20.1% lower than those of
Method 3.

Power Analyses

The power analysis has proved to be a useful tool for survey design and
management decisions. One can make a prior! management decisions about the
duration, sampling intensity, and statistical certainty of survey programs if one can
estimate the CV of the methods being contemplated. Given the objectives to detect
a halving or doubling in the population from one year to the next, it appears that
Method 2 (mark-proportion method) can accomplish this goal for Charlotte Harbor
dolphins with annual surveys. Method 3 (mark-resight method) would require up
to three annual surveys, although it detected a significant increase of 56% between
1992 and 1993. The other methods require additional assumptions about the 1990-
1994 abundance stability and are thus less useful. CVs can be obtained or improved,
however, by sampling more often than the annual surveys chosen for this study,
although care must be taken that additional variation due to seasonal differences in
dolphin abundance, movements, and behavior is taken into account.

Survey Design

Selection of a survey technique for detecting trends in dolphin population-
rate parameters should take into account the relative accuracy, precision,
repeatability, and efficiency of the available methodology. Our findings from
Charlotte Harbor and Tampa Bay indicate that coastal aerial surveys, while more
efficient than photo-ID surveys at covering large areas, provide estimates that are
less accurate and less precise.

The main reason for the close agreement among the estimates calculated
from the different methods and the precision of the CVs was the high percentage of
marked dolphins identified each year (58% to 80%). A large amount of survey effort
is required to maintain such a high percentage. Ideally, the surveys should have
two components: an intensive effort to photograph and identify dolphins (at the

29

potential expense of not following a rigorous survey route or sampling design), and
an effort to cover the whole area in a short period of time with repeatable survey
routes. The first component allows the development of the photo-ID catalog so that
sufficient numbers of marked dolphins are identified to estimate abundance
precisely, while the second component would provide a standardized effort each
year so that annual comparisons can be made.

Method 3 (mark-resight method) would provide satisfactory estimates from
the second component of such a survey because the statistical properties of the
more-traditional mark-recapture methods are well-known and the sampling units
provided adequate sample sizes of marked animals. In Charlotte Harbor, as in
Tampa Bay, however, it proved difficult to conduct "complete surveys” within the
available survey window. Instead, we could only survey regions repeatedly while
conditions were favorable when other regions were unworkable, and then shift our
efforts opportunistically. If “complete surveys" can not be conducted, then Method
2 (mark-proportion) provides an acceptable alternative as long as the numbers of
sightings and proportion of marked dolphins are high, and the effort among
different regions is not greatly biased. This method is particularly useful because it
can be more-readily calculated from the first component of the survey design during
which the largest numbers of groups would be sighted. Methods 1 (catalog-size
method) and 4 (resighting-rate method) may provide double-checks on the trends
and estimates of the other two methods.

Recommendations

¢ Monitoring should be continued at least annually to track and evaluate the
apparent trend. The more frequent the surveys, the better the chance of detecting
a trend towards a catastrophic decline. More-intensive surveys would permit
more-refined determinations of natality, immigration, emigration, transience,
and mortality. Although two or three annual surveys can detect large trends in
abundance, this study illustrates the difficulty of interpreting the causes for the
abundance changes without more detailed or longer-term information.

¢ Photo-ID work should be expanded to other seasons to examine previous reports
of seasonal fluctuations in abundance.

¢ Empirical studies designed to identify the appropriate level of effort for mark-
recapture surveys should be conducted.

¢ Photo-ID efforts should be expanded to greater distances offshore and along the
coast to examine immigration, emigration, and transience in greater detail.

¢ Patterns of habitat use in Charlotte Harbor should be examined through
integration of GIS habitat data with our sighting data. Efforts should be made to
integrate ecological studies of the dolphins of Charlotte Harbor with other
research efforts under the National Estuary Program.

¢ Community structure needs to be examined in more detail to define biologically
meaningful management units. Existing information on residency, ranging and
social patterns, and genetics should be integrated to arrive at population

30

designations. Analysis of community structure is necessary to interpret
immigration, emigration, and transience relative to population size. Sample
sizes for examination of mt-DNA haplotype distributions in Charlotte Harbor
should be augmented through biopsy darting or capture-release efforts. The
genetics data should be supplemented with telemetry data on movements and
additional photo-ID efforts.

° The accessibility of stranding data was highly variable from one responding
group to the next in Charlotte Harbor. Improved coordination of efforts and
availability of information would be helpful. Mote Marine Laboratory, Tom
Pitchford, and Bob Wasno provided excellent examples of cooperation and
assistance.

e The correlation between increases in the number of dolphin strandings and the
occurrence of red tide blooms suggests that further investigation into the role of
red tide in dolphin mortality is warranted.

Acknowledgments

The National Marine Fisheries Service supported all five years of this survey
project. We would like to thank Dr. Bernd Wursig and Texas A&M University for
their roles in obtaining and administering this contract. Earthwatch and many
EarthCorps volunteers participated in and supported the project during its first four
years. The Chicago Zoological Society provided RSW and KWU with funding and
logistical support. Additional assistance was provided by the Dolphin Biology
Research Institute, Mote Marine Laboratory, and the Inter-American Tropical Tuna
Commission. Dr. Dan Odell, scientific coordinator of the SEUS Stranding Network,
provided stranding data summaries, and photographs of stranded dolphins were
provided by Jay Gorzelany of Mote Marine Laboratory, Bob Wasno of the Lee County
Department of Community Services, Division of Marine Sciences, and Tom
Pitchford of the Florida Department of Environmental Protection. Dr. Susan
Shane shared dolphin identification photographs from her study area in Pine Island
Sound. We would like to thank Cannon's Marina, Mako Marine, Mariner
Outboards, Yamaha Outboards, West Marine Products, Captain Bill Joy at Palm
Island Resort, Mr. George Blechta, "Poppy" Donoghue, Casey Silvey, and Jack and
Fran Wells for their crucial assistance with the logistics of the field work. Blair
Irvine and Paul Harrison were responsible for developing our Foxbase database
system and associated programming -- without their tireless efforts we would not
have been able to effectively process the large quantities of data collected. Erika
Beyer and Shawn Irvine helped in the production of our computerized mapping
capabilities. We very much appreciate the field and lab contributions of Yvonne
Boudreau, Kristi Brockway, Forbes Darby, Travis Davis, Yves Delpech, Elisha
Freifeld, Sue Hofmann, Tristen Moors, James Thorson, and Michelle Wells. Tim
Gerrodette provided excellent advice on the power analyses. Special thanks go to
our NMFS COTR, Larry Hansen, for his support and patience. This project was
conducted under Scientific Research Permits Nos. 638 and 805 issued by the
National Marine Fisheries Service.

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Leatherwood and R.R. Reeves, eds.). Academic Press, San Diego, 653 pp.

Scott, M.D., R.S. Wells, and A. B. Irvine. 1990b. A long-term study of bottlenose
dolphins on the west coast of Florida. Pp. 235-244, In : The Bottlenose
Dolphin (S. Leatherwood and R.R. Reeves, eds.). Academic Press, San Diego,
653 pp.

Seber, G.A.F. 1982. The estimation of animal abundance. MacMillan Publ. Co.,
New York. 654 pp.

Shane, S.H. 1987. The behavioral ecology of the bottlenose dolphin. Ph. D.
dissertation. University of California, Santa Cruz. 147 pp.

Shane, S.H. 1990a. Behavior and ecology of the bottlenose dolphin at Sanibel
Island, Florida. Pp. 245-265, In: The Bottlenose Dolphin (S. Leatherwood and
R.R. Reeves, eds.). Academic Press, San Diego, 653 pp.

Shane, S.H. 1990b. Comparison of bottlenose dolphin behavior in Texas and
Florida, with a critique of methods for studying dolphin behavior. Pp. 541-
558, In: The Bottlenose Dolphin (S. Leatherwood and R.R. Reeves, eds.).
Academic Press, San Diego, 653 pp.

Slooten, E., S. M. Dawson, and F. Lad. 1992. Survival rates of photographically
identified Hector's dolphins from 1984 to 1988. Mar. Mamm. Sci. 8:327-343.

Thompson, N.B. 1981. Estimates of abundance of Tursiops truncatus in Charlotte
Harbor, Florida. NOAA/NMFS/SEFC/ Miami Laboratory, Fishery Data
Analysis Technical Report.

Urian, K.W. and R.S. Wells. 1993. Identification of stranded bottlenose dolphins
from the central west coast of Florida: 1991-1992. Contract No. 40-GENF-2-
00613. 3 pp.

Urian, K. W., D. A. Duffield, A. J. Read, R. S. Wells, and E. D. Shell. (in press)
Seasonality of reproduction in bottlenose dolphins, Turstops truncatus. J.
Mamm.

Wells, R.S. 1978. Home range characteristics and group composition of Atlantic
bottlenose dolphins, Tursiops truncatus, on the west coast of Florida. M.S.
thesis, University of Florida. 91 pp.

Wells, R.S. 1986. Population structure of bottlenose dolphins: behavioral studies
along the central west coast of Florida. Contract Rept. to National Marine

3)3

Fisheries Service, Southeast Fisheries Center. Contract No.45-WCNE-5-00366.
58 pp.

Wells, R.S. 1991. The role of long-term study in understanding the social structure
of a bottlenose dolphin community. Pp. 199-225, In: Dolphin Societies:
Discoveries and Puzzles (K. Pryor and K. S. Norris, eds.). University of
California Press, Berkeley. 397 pp.

Wells, R.S. 1993. The marine mammals of Sarasota Bay. Chapter 9, pp. 9.1 - 9.23 In:
Sarasota Bay: 1992 Framework for Action, published by the Sarasota Bay
National Estuary Program, 1550 Ken Thompson Parkway, Sarasota, FL 34236.

Wells, R. S., M. D. Scott and A. B. Irvine. 1987. The social structure of free-ranging
bottlenose dolphins. Pp. 247-305, In: Current Mammalogy (H. Genoways, ed.).
Plenum Press, New York, 519 pp.

Wells, R.S. and M.D. Scott. 1990. Estimating bottlenose dolphin population
parameters from individual identification and capture-release techniques.
Rep. int. Whal. Commn (Spec. Issue) 12:407-415.

Wells, R.S., K.W. Urian, A.J. Read, M.K. Bassos, W.J. Carr, and M.D. Scott. 1995.
Low-level monitoring of bottlenose dolphins, Tursiops truncatus, in Tampa
Bay, Florida: 1988-1993. Final contract report to the National Marine Fisheries
Service, Southeast Fisheries Center, Miami, FL. Contract Nos. 50-WCNF-7-
06083 and 50-WCNF-3-06098. 110 pp.

Wursig, B. and T. A. Jefferson. 1990. Methods of photo-identification for small
cetaceans. Rep. Int. Whal. Commn (Spec. Issue) 12: 43-52.

Table 1.

Table 2.

Table 3.

Table 4.

Table 5.

Table 6.

Table 7.

Table 8.

34

List of Tables

Summary of dolphin abundance estimates from aerial survey data,
1975-1994.

Summary of survey effort, 1990-1994.
Annual Charlotte Harbor dolphin population size estimates.

Matrix of number of dolphins identified in one year that were seen in
previous or subsequent years, and incidence of transience. See text for
explanation of rate derivations.

Young-of-the-year and calf proportions of the mark-proportion annual
population estimates.

Summary of known mortalities based on records of stranded dolphins in
the counties encompassing the Charlotte Harbor study area.

Proportion of dolphins sighted per kilometer surveyed.

Components of the inter-annual differences in abundance estimates. Nj is
the Method-3 abundance estimate for Year 1 (Table 3). Mortality is
estimated conservatively by the sum of the stranded dolphins reported
between surveys (September - August) in S. Sarasota and Charlotte
Counties. Reproduction includes two components. The first is the
number of YOYs added to the population in Year 2. The second is the
number of older calves, which can serve as an index of calf survivorship
and/or attractiveness of the area for raising calves. The change in the
number of calves is calculated by subtracting the number of calves in Year
1 and the number of YOYs in Year 1 (who would be calves in Year 2 if all
survived) from the number of calves in Year 2 (Table 5). (This
approximation also assumes that the number of calves that become
independent of their mothers each year remains constant.) Transients
present in Year 1 but not in Year 2 are subtracted; those present in Year 2
are added (Table 4). Fluctuations in the number of residents due to
movements into or out of the area or due to inability to photograph these
dolphins even when present can be estimated by first calculating the
difference between Year 1 and Year 2 in the number of marked residents in
the catalog (R = M - No. of Transients) and then adding the estimated
number of unmarked residents (R * (1 - m/n), Tables 3,4). The Sum of all
of these columns can then be compared with N2, the Method-3 abundance
estimate calculated for Year 2 (Table 3). The unaccounted-for difference
between the Sum and Nz is likely due to imprecision and bias of the
abundance estimates or the components listed in the table.

Figure 1.

Figure 2a.
Figure 2b.
Figure 2c.
Figure 2d.
Figure 2e.

Figure 3.

Figure 4a.
Figure 4b.
Figure 4c.
Figure 4d.
Figure 4e.

Figure 5.
Figure 6.
Figure 7.

Figure 8.

Figure: 9.

Figure 10a.
Figure 10b.
Figure 10c.
Figure 10d.
Figure 10e.
Figure 10f.
Figure 10g.
Figure 10h.
Figure 101.
Figure 10).
Figure 10k.
Figure 101.
Figure 10m.
Figure 10n.

List of Figures
Charlotte Harbor study area.

Locations of sightings during 1990-1994:
Locations of sightings during 1990-1994:
Locations of sightings during 1990-1994:
Locations of sightings during 1990-1994:
Locations of sightings during 1990-1994:

Groups of 1-5 dolphins.
Groups of 6-10 dolphins.
Groups of 11-15 dolphins.
Groups of 16-20 dolphins.
Groups of > 20 dolphins.

Survey effort and sighting results.

1990:
1991.
1992.
1995.
1994.

Frequency distribution of resightings:
Frequency distribution of resightings:
Frequency distribution of resightings:
Frequency distribution of resightings:
Frequency distribution of resightings:

Annual catalog size and numbers of additions to the catalog.
Sighting frequencies for identifiable dolphins, 1990-1994.
Population size estimates relative to survey effort.

Comparison of Method 2 (mark-proportion) and Method 3 (mark-
resight) abundance estimates, with 95% CLs. The CLs are not directly
comparable because Method 2 used a non-parametric bootstrap
variance estimate and Method 3 used a binomial variance estimate.

Number of reported strandings, by county.

Sightings of 'CURL': 1990 - 1994.
Sightings of 'THUV': 1982 - 1991.
Sightings of 'HISC': 1990 - 1994.
Sightings of "TSMD': 1990 - 1994.
Sightings of 'RPPR': 1982 - 1994.
Sightings of 'LGSL': 1982 - 1994.
Sightings of 'TFLN': 1982 - 1993.
Sightings of 'CLTO': 1982-1992.
Sightings of 'ZIGY': 1990 - 1994.
Sightings of 'POTP’: 1990 - 1994.
Sightings of 'DIPT': 1983 - 1994.
Sarasota sightings of 'DIPT': 1983 - 1994.
Sightings of 'RY34': 1984 - 1994.
Sarasota sightings of 'RY34': 1984 - 1994.

Figure 10o.
Figure 10p.
Figure 10q.
Figure 10r.

Appendix 1.
Appendix 2.
Appendix 3.
Appendix 4.
Appendix 5.

Sightings of 'BSLC’: 1982 - 1994.

Sarasota sightings of 'BSLC’: 1982 - 1994.
Sighting of 'SLIT': 16 August 1990.

Tampa Bay sighting of ‘SLIT’: 19 July 1991.

Appendices

Sample data form and environmental condition codes.
Definitions of relevant parameters from the sighting data forms.
List of sightings, by year, 1990-1994.

List of identified dolphins in each sighting, by year, 1990-1994.
Animal frequency by year, 1990-1994.

Table 1.

1983-86

1994

Summary of bottlenose dolphin abundance estimates from aerial
surveys of Charlotte Harbor and Pine Island Sound: 1975-1994.

All

Summer
Autumn
Winter
Spring
Summer
Autumn

Winter

Autumn

Abundance

Season Estimate_

64

10

L

118

375
611
709
331

277
157
912

Low Up Source

Odell and Reynolds (1980)

Thompson (1981)

Scott et al. (1989)

Blaylock et al. (1995)

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Table 4. | Number (%) of dolphins in the catalog of a given year (bold) that were identified
in previous or subsequent years. Dolphins identified in only a single survey
year were considered “transients”.

YEAR 1990 1991 1992 1993 1994
1990 209 106 (51%) 94 (45%) 108 (52%) 112 (54%)
1991 106 (60%) 178 82 (46%) 94. (53%) —- 105 (59%)
1992 94 (57%) 82 (50%) 165 102 (62%) 106 (64%)
1993 108 (50%) 94 (43%) 102 (47%) 218 148 (68%)
1994 112 (46%) 105 (43%) 106 (44%) 148 (61%) 243

Average: 53% 47% 46% 57% 61%

"Transients" 25 (12%) 18 (10%) 6 (4%) 15 (7%) 34 (14%)

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Table 7. Proportion of dolphins sighted per kilometer surveyed.

YEAR Dolphins /km Calves/km Young-of-the-year/km
1990 0:53 0.10 0.01
1991 0.51 0.12 0.03
1992 0.60 0.12 0.03
1993 0.58 0.14 0.03

1994 0.58 0.13 0.02

Table 8.

Yr 1- Yr2
1990-1991
1991-1992
1992-1993

1993-1994

Components of the inter-annual differences in abundance estimates. N1 is the
Method-3 abundance estimate for Year 1 (Table 3). Mortality is estimated
conservatively by the sum of the stranded dolphins reported between surveys
(September - August) in S. Sarasota and Charlotte Counties. Reproduction
includes two components. The first is the number of YOYs added to the
population in Year 2. The second is the number of older calves, which can serve
as an index of calf survivorship and/or attractiveness of the area for raising
calves. The change in the number of calves is calculated by subtracting the
number of calves in Year 1 and the number of YOYs in Year 1 (who would be
calves in Year 2 if all survived) from the number of calves in Year 2 (Table 5).
(This approximation also assumes that the number of calves that become
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Year 1 but not in Year 2 are subtracted; those present in Year 2 are added (Table 4).
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number of marked residents in the catalog (R = M - No. of Transients) and then
adding the e<timated number of unmarked residents (R * (1 - m/n), Tables 3,4).
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abundance estimate calculated for Year 2 (Table 3). The unaccounted-for
difference between the Sum and N? is likely due to imprecision and bias of the
abundance estimates or the components listed in the table.

Mortality Reproduction Transients
Ny (Year 2) YOYs Calves Yr1 Yr2 Residents Sum N?2
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Figure 2b. Locations of sightings during 1990-1994: Groups of 6-10 dolphins.

Figure 2c. Locations of sightings during 1990-1994: Groups of 11-15 dolphins.

Figure 2d. Locations of sightings during 1990-1994: Groups of 16-20 dolphins.

Figure 2e. Locations of sightings during 1990-1994: Groups of >20 dolphins.

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Figure 10(a). Sightings of ‘CURL’: 1990-1994

Figurel0(b). Sightings of THUV': 1982-1991

Figurel0(c). Sightings of 'HISC’: 1990-1994

Figurel0(d). Sightings of 'TSMD': 1990-1994

Figurel0(f). Sightings of 'LGSL': 1982-1994

Figurel0(g). Sightings of TFLN': 1982-1993

Figurel0(h). Sightings of 'CLTO': 1982-1992

Figurel0(i). Sightings of 'ZIGY': 1990-1994

1990-1994

Figure10(j). Sightings of ‘POTP'

Figurel0(k). Sightings of 'DIPT': 1983-1994

Figure 10(1). Sarasota sightings of 'DIPT’: 1983-1994

1984-1994

.

Figurel0(m). Sightings of 'RY34'

Figure 10(n). Sarasota sightings of 'RY34': 1984-1994.

Figurel0(o). Sightings of 'BSLC': 1982-1994

Figure 10(p). Sarasota sightings of 'BSLC': 1982-1994.

Figurel0(q). Sighting of ‘SLIT’: 16 August 1990

Figure 10(r). Tampa Bay sighting of ‘SLIT’:
19 July 1991

Dolphin Biology Research Institute

Sighting Sheets
Field Hours pate

cron EE a Sighting No: eee
Observers yh Re a eR el PT 9 es EGS: (aes) to ee
Location LOC ee

ae

besiege Aa ese. onavrucs “un al (eee Powe
Conditions ee

Depth eral. Water Temp: ea F Tide: nae Heading: , a es
Initia enera

Activity: mill Feed prob. Feed Travel Play Rest Leap Tallslap Chuff Social w/Boat Otner
ier {2 ae 4 5 = oo ae 8 9 ) ae

PHOTO ANALYSIS

Pos Min Max Revised Revised Final
not !Ded not iDed MIN MAX

FIELD ESTIMATES

TOTAL DOLPHINS == Ese] ES)
TOTAL CALVES Ee] ES] eS)
ae Fo Pe

YOUNG OF YEAR

Comments:

Associated Organisms:

Dolphins Sighted: ID confirmation: P= photograph V= visual O = other (explain)
Name Name Code Conf. Name Code Conf

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Photos: (roll: frame->frame)
Tape: (tape: counter)

Appendix |. Environmental condition codes.

CONDITION CODES:

SEA STATE

SIGHTABILITY =

Wave Height 0-0.2m (8 in) “TO Clear or few clouds Excellent i 0
Wave Height 0.2-0.4m (8-16 in) 1 [Partly cloudy ; non-interfering Good, unlikely to miss dolphins | 1
Wave Height 0.4-0.6m (16-24 in) 2 Some, could interfere Fair, may miss some dolphins {2
Wave Height 0.6-0.8m (24-32 in) | 3 , Interfering Poor, probably missing dolphins 3
Wave Height 0.8-1.0m (32-40 in) | 4 Not on effort 4
Wave Height > 1.0 m (>40 in) iS x

INITIAL OR GENERAL HEADING:
Use degrees in most cases, "360"=North
Milling="000"

In passes, rivers, use "IN" or "OUT" if degrees are less appropriate

Appendix 2
Definitions of Relevant Parameters from the Sighting Data Forms

Field Hours: The time the boat left the dock and time it returned. Time "off effort"
is recorded when no systematic effort is being made to search for dolphins.

Date: The date is entered as DAY/MONTH/ YEAR

Sighting No.: This is entered serially for each day.

Photographic Coverage: The box to the right of "Platform" is for an indication of the
quality of the photographic coverage of the group and is filled in during photo
analysis. 1 = Excellent: all dolphins in the group were photographed or
otherwise positively identified; 2 = Good: there are photographs of dolphins
with distinctive fins that might be in the catalog, but because of the photo quality
it is not possible to make appropriate comparisons with the catalog (e.g., it is
possible the out-of-focus fins may already be in the catalog, but can't be certain); 3
= Poor: photo coverage is known to be incomplete, because not all dolphins were
approached for photographs, no photos were taken, film did not turn out, etc.

Time: Time the dolphins were first sighted and the time they were left or last seen.

Location: A description of the location of the initial sighting.

LOC: A 3-letter code based on physiographical features.

Latitude and Longitude: These coordinates are calculated from a chart or from a
LORAN and entered as degrees, minutes, and 1/100ths of a minute.

Conditions and COND: This refers to meteorological and sea state conditions. They
are described briefly, and entered as a code in the box. The condition codes are
given on the attached page. A running log of environmental conditions relative
to survey effort (noted at each major change in conditions or significant location)
are kept in a separate logbook.

Field Estimates: These nine values are entered in real time in the field. The
number of TOTAL DOLPHINS includes all age classes in the sighting. The
MINimum estimated number present, the MAXimum estimated number
present, and the BESTestimate (between min and max) are entered. The BEST
estimate is a point estimate, count, or midpoint of a range of estimates. The
number of TOTAL CALVES includes all calves in the sighting, including young-
of-the-year. The number of YOUNG OF YEAR are all of the calves born within
the year. Typically, these are recognizable as newborns during the first six
months of life.

Photo Analysis: These values are entered after completion of photographic
analyses, and the Dolphins Sighted section at the bottom of the page. Pos IDs is
the number of animals positively identified from photographs or in real time.
Min not [Ded is the MIN minus Pos IDs, or the minimum number of dolphins
that were not identified. Max not IDed is the MAX minus the Pos IDs, or the
maximum number of dolphins not identified. Revised MIN is the sum of the
number of Pos IDs plus the Min not I[Ded. In most cases it will be the same as the
MIN, except when the number of Pos IDs exceeds the MIN. Similarly, the
Revised MAX will be the sum of the Pos IDs plus the Max not IDed. It will equal
the MAX except in those cases where the Pos IDs exceed the MAX. The Final
BEST estimate is the best point estimate, literal count, or midpoint of the

Revised MIN and Revised MAX estimates. It will be about the same as the BEST
field estimate except in those cases where Pos IDs exceed MIN, MAX, or BEST.
Dolphins Sighted: Dolphins positively identified in real time in the field are listed

by their Name and a "V" is entered under Conf. as a visual confirmation. Most

identifications are made in the lab, when the name and four place identification

Code are entered for each dolphin along with the Photographic Confirmations.
Photos: The photographer, roll and frame numbers.

| age

a

Ce a =) a Es ONG | Sete a err) ge 9TR00661
oe eS 81 8 ct x — C 9TRO0661
Oh 0-5 | C1 8 FC cae Bx C 91800661
eee See | Ps) pena c oT ROGET |
0. a0. | Pact Oey (ee ier ieee a c | 91800661 |
fee 2 eee et | wea fs A aes oes is ae wi [9T 800667 |
Ee0s tr 0M ea cst et [aoc | eal bor fs ors Rates| TsT800667 |
ce a [seU_ | eee Oe | ws oe PstR00667 |
a a Fa [on | eae are aise eee i 5780066!
0 h OS |= te A 20 S Peete ape CE Boe aoe c ST 800661
th soe ese BOs eo) ae ease (ee ea a er | oe S| oes | STRO06OT
0h eS eee Wal eo. ot ser | eee ot | Os Per Al toe z Pst 800661 |
a oer eS Ca ea oe eae erat | rear | i Pris0066r |
iO St BOD |e 0 Ce ee a a rr 97 SH COLT Z cS [ FI800661 |
ne ae 0 ap se 6591 | cot —— 1S | FIR00661
me rs ao ee Sa a A a Ts BS FIRO0661
0 see aS BOTT, I oR kG a SS

ta) 208 5-3 0 Z 0 Oc Cer lece | ws i Bees) sie 1 FIS00661
| 50 hee 16 0 t t Or | 61 C8= 1204 re ee FISO066T
S00 (OST TENG () [ | RE 4 78 81 oS oe 6781 l FIXV0661
O° T/SS08 ie 0 0 t C I 07 78 2 Eee Ei ea ee ee
GP 5 ee ke ES ee ee
BO ES Se ee ee a Ee
OS] Roe | 9 OP 2 26 1 eS) 0d SL 8h Oe S| Ooi Oniis|. J sees =| erponeed |
oe OR 0 o | 91 [cs [re | ov | 9¢ [aror | acor | 1 | 7s [eisoossr,
a ae Cae ne i
[Ol Senos Ox apse | ee5 Sor | ws | oe ier | ort |. a |. 6 _[e1so0esT |
ae ea Oia) ste | Zee jess s) e0 Wve ser wer |S oe Sle s00ser |
RR 0) FA a Oe
0 S20. ees RO ee sets ee eicot | os cy | ee | oe eer] Sette |, = levis s| crs0unal |
Ori 20 ate 0 Be te eee @ Sle) eee lect] Oe fe Or el wOEK | sez] FS [eT #00661
POs) 0, aoe a0 |S noe eee] oor | ee [on wma RL Tae ead eed ES [z1300661
oan PR “OSs hy See we se. i) ex sos | watt oe | BObie) peOIs|= a == cs cP ersounel |
0 2 el RECA a ae ee ie es ee es aIStic| TT Sle Rs el Cis006eT
a0 Si Os ON) OS |S ef ae eer eee food 3 9S fs Gee] DELIZ| ULI] 12 [= eo | Oi goneer |
LSad |dISOd | LSad |dISOd! Lsa@ |dIsod| das Dad | oasS | NIW | Dad | GNA | NIDad [aAaVAD

AOA | AOA | ATWO | ATWO [LOL | LOL |DNO1 ONOT] LWT | LWT | IVT | AWE | AINE [OLOHd KLADIS

O661 BIR sunysis

1990

Sighting Data

EE Fe

—_
Cc

0

>)

0)

POSID| BEST

ST

0)
Q

ons

(oa)

3
es es Ses eee
ais See Se Se eae

CALF
0)

POSID| BEST | POSID! B

0

)
0
0

0
0)
es ees Ea

vi es Se Se Ete as

(

CALF

foe)

TOT

10
0
OT dh eae Siat|nea OP abe Oa DR ORS |

asus
10
is Bees Ses es es Seas

i Tee | SiO
ieee ea ae oe eee

5

AS Re SEs Eee ee SS PES
EU 2 Soe ee a es ee ee ee ea

6
9

2

3
54
ra)

1

ees

.
a

eae

~_
7 Ls —_|O foal as] T (oa)
re) Ne a a SN I ONY les =
=
Z. orl Kes) fo] A} apaltea Al atata fon)
(a5) 00] 30 oc 20] oc | oc} 00 20] 20] 20] 00 io)
=

48
12

(eens Ea Wee eae ree

Ra
is a6

eos tone

ioe PS as

[eZee
Don Rats ems

44

aes

(Oiiae eases
ae

eis EE ae Bs
peoisita | roa ay

Giles ests
Si36i|294 OF |e? ote | ei [eed S|

26
26

2

(ee Es as eee

fa eas
ie Sa Sos

2
1324

Ail

(ales ira es
(iBvEoe Re eee

05s
lapel ers 2ie|

LBS 7
21s

9 A ECS Sa a
Ste Sieh Re ee ees

it [12007

| 1540 | 1553 [| 26 |
| 1408 | 1435 [ 26 |
| 1614 | 1620 |

ule al ae EUS
1 1150

+
4

RAD

l
2
a

,
Z

ean
ees 4268 Pass
et ee elealan

(

54

ta rie ol mera
(parses aleaeadlbee.
Ge Lee al lea
(oe Use ol ee eae
eres

7

19900816
19900816[ 60 |
19900818
19900818

19900818
19900818

19900816

FSU Te ye Mira ae oe
OSCE e ae Men

19900817

19900817
an oe eae

fi99008i8{ 1 |

19900816] 57A_ |

19900817
19900817
19900817

19900816
19900816] 4A |

(oa)

j-)

0

(oa)

3
2

Din | OE | De a i

q

2

oie es ey

Cy

Di

N wm

20

bo
NN

ene [Ea ons ea |

mee Ess
Ark ee EO

Tae ers ase

Bi Bie Gee ee ee

30
2 alban

SS
es ee

fon

2

AYN

2

iN

82
8
8
8
82
82
82
8
8

40
54

Esa)
Chas se7S
P20 [2 [21 |
ie SSS os
1200 | 1307 | 26 | 40 | 181

ECE ke ae

51
42

oe is

26
26
26

E2GS

£232-|-9%6
HE i
1014
1552

ivi ees
ets Rises eos

Os aos Rae a

| 1020 |
(NS PRES Bos as

Sie SOs
Boies

1002
lesisi2

Bis BIS Ease ae ee
eld Ops aor 26eaI

| 1118 | 1232
Byres
| 1048 |
| 1341 |

2

2 ate ee OE TCs
Gece oe ae eye et
aiken BECES
fess Laon

Dall
52
oe

fears acl Poses ar soleil
19900822 =a Ta

ees Sell asia
es
2)

19900822
19900823
19900823

Bei aes ae
Pi Ee
[5199008212 [> = Bee | ete
OOH O.8 22 sf ne tee
S199 008 224 2-59> li tea
Bh a ee
| 19900822 |

OOO S215 | ars YOR [ieee |
19900822] 9A | 1 |
| 19900822 | oR aes

19900818
19900818
19900822] 8 |

Page 2

1990)

Sighting Data

POSID!) BEST

CALF

CALF
POSID| BEST

C | POSID|) BEST

Bie Rae

=e
ey
13
ie
zo

“)

LONG
Ss

fon

Q
O

10

82

42

S)

0

18
6

fone ol

+

NTO

155 Seleeaes

he Wy?

es
Sarre

Q

18

NN

937 6
954 [| 26 |
t= rom eroads|

Ear
tarde

noes]

Boe

facie
32

19900823

199008 23

(oa) Kaa)
NIN
20] 90
ol >)
ol >)
NID
DIN

eon

50)
49
2:GbseAOrea leet Oa
45
52

Eva ays Eoce
1350) |et4nis 26h

i)
0
0

0

j=)

: cette i

co)

asa
dO |
0

S iN

Oss es ee

pana
0
ey ees eS Eee eae

ie Se Se es

N ny

Vie Ohees NO) OL a
0)
0
a

eagle EOL.
poh B

On
a es
13
2
ee One|
exes
ares
4

5

vt

12

Ere ees
15
SiO eins |e

a
18

2
| Dir]
oe iva
arma
8
fa ae ee ed ee ee ee ey eS

5

Ins

Sears eres
Sees Sas
i ee ees
Pa Eire aie
ES) 2

| 14 | 54
PdiOe Sp Bel

es fells |e ie Ee!

=o

exes
9
13
2

i) ayn

2

ayn eS N

82
82
82
8
82
8
8
82
8

8 2

8

8
18.25
| 82

Cos} fee)

OS Se
48
ete

et204% | 265) 145 |

ESE ner eee
Gav eeees See

Er cee
30

ee ees
(aie Ea eS
10

ECE an aed
Sie?

265 alia
| 1440 [ 1449 | 26 |

42
33
SUS Si See eS See

26

i148 | 26 | 44 | 54 |

1219

esitel

Eris re
P0528, | 22 6a

1205
1202

26
26
RES Eee Rey Bee RS Se

1500

407: ita sea: ees

937: | 10243)
| 1044 | 1052 |

Baie os eure
921
| 1046 |

25)

Slores|e Dee|
Pini Se Ro
Pe a

epee aires

19900824] 3. |
19900824
19900824

53
53

54

Gack pam ea

esas ee eized
54
IS St te ee |

6

aN

yoso0s2e 7 1 1450 [1454
2

19900823
19900823
199008

19900826

19900826

19900826) 2 |
| 19900826 |

PT9S00826r eal 2

199008 267/355 aie
ii nae es

| 19900823 |
19900823

a ee OE ee Ee PS a

0

0

eae ene Oe a Oe RE SR
Ee Ts a ee ee ES

AN

2 Be Be ee a Ps ee ee es

3
30

82

ie Gee ae LS
;

82

82

esis | Ea

52
ere re ey eee

Peta se le via7. |

al 329 | 26s |
Pans 9si| 26.5

EPA ries

fen Dies SOs,
Eee Ses
Haves

eels
ee
fester tte 12095)

19900826] 5B |
ae
=

19900827

19900827
19900827

19900827

E9900826 | SAS) - [953
19900827

19900827
19900828

Page 3

199]

Sighting Data

LAT
MIN

~ =
) as) Solo alolelo
~ 2
2
6 2 ololo
~
alae
=~
n
<a)

ALF} CALF
ID| B

(C5
S

POSID| BEST | PO

0

TOT

oe eee

“lo we
—_

TOT

eaten Bs 3
fae alee venuena
hema er heps

ersee| tort
(See Roa ei a (aor nee (cal le

Fsaiack Peeper (etree | Palere | -eoae
erGer

Fees [Re Ce eS (ST (PY Pea eer eee

.
a

5
2

1

2 Mil oink 8 sO E | SOE ROE [On
0
eae 0 | Oy ome ony

in Pe eas
Chas

45
3
82

3
ies eae

eee ea a ee

SEC

(ithe icles ecreate haw

Le?

raat aes

LONG| LONG
MIN

LES oe (eeAron | a
Sider | Port tt | Orr pase
3
49

Ex607ea:| PAR (pS Ste pelea ee

82

LAT | LONG
SEC
Seal Rn rea

2

Siar nee Pelle

6
Dae

Po ee ie Pee ea
260i [Pe sie |Frka

44

61
4 aE a oer a
(ESOC a (I | ee le ine
(ECs EDM Ca eed

aor

~
x

GRADE| BEGIN
BESO i ii aon i ees
7 Ca ea Feed as eal oo

2
26

LAT
DEC

e2iort iraaser | a3 Fier [Fes | Peeie | Easr

Peter tease Pesae Peso Pa
eriay Eee Boel eal eas

TIME
END

CREE Pad eel ea ees

E9952 95.00 7267 |es0e

(ial camel GO FO
ier a Ce

stv rias0r | rs00r|

(EK es ee
Pre Oser|

2 ee OOn Pitiar | 26e aa

| tf ida | tise | 26 | 44 |

fe pieeb ease (9990 [fe aew | branint
13085 [13297] 265°
Prns20F | F545 | Pe267 |
prone |

Sl pa aat a n4sot | 326 2
ROTO Ea Kee a Ee PR
[ied ae
NORA Sire. Fe aa os 8

Eis ROR OF 52-4 Par eae ode
(aa Ee

ar ee ee ee

[e532

1533
(sel) Find | based Pe sl

oh eal Eee eel
(ecw mr scl ws

ROS OS aa meri |
PLO ee

ONS

en ed hie ee
r=eort|

58
Eaont

19910812
19910812
| 19910812 |
19910812
| 19910812 |
| 19910814 |

19910812

19910811

Oni a a i on ee
19910811

LOS LOReS (f— sa |

19910812

COS me See

CONS meee
| 19910814 |
| 19910814 |
| 19910814 |

cr HRDEDES | 726 eee |rees Mea ered re seer sels Tesh

TT Ue mc i de De

PPPEEEEPEEEPETT EEE
PPPPPPPPPPPEPEPPP PPP Peee//

“PERSE MECC PEPE PEELE
PPPPEPPPE Elle

Heeler i

praia aes | 23 |

paniaat | 92i6rt es arart Peles ea ieek esae Pree

82

WAS 226 TSS |S Bee

19910815

~N
oo

~
oO

54

19910815
1991081
1991081
1991081
1991081

N
oo

oo
N

1334

13/21

ig2gs | Tig 0t| 26 Fao 7] 729 | a2 Tis [8s ty

19910815

Pe19OTORNS |= 1595]
| 19910815 | 160 |
| 19910815 |
| 19910815 |
| 19910817 |

Sse!

43

areas eavasent | ome madi ne03-t|-982 Pests

iF
ie he

ig0"3 blot aoe

82

sien | isa? 5] sai | 42 |

Lees eee

43
LSS GO 2E| v6 t| eds 7) leo) | aa | aes eet ee

162
al

0)
0)

bere

5

(peli eal ere
5

16

PaOGe1 | 926.1. 245, 1), TAG S| aa ee

Syke?

PSNOBIGg | Pini DOr raG=h| a4 Ont mart eRe

OTe eae

Page |

Sighting Data 1991

>
2) 4 fo) N ala
~ 3
=)
5 Z (j=) So S =)
=§
me
ra 4 N alo alia) n oa foal
Om
i 2
zs S =
VE
me

ial
fart eee

Tj 00 oo

2

2

2

7

2
iat lt
| 0
i

6

9

fs

loa)

LONG| TOT
SEC | PO
pA

LONG] LONG
DEG | MIN
;
4
pasa 0)

I)
he'd

Sell
Pad 2 ile) O-T Ora
1

(mee (ed fe fd

27

ine

eee ee
28
85
88

eo] ed 6

Gai) fee Wl Hae dee Or? da OS de ed

13
14
ars |

begs 208"i 26a 5 0" eof 14 |

ANTON

Yala) et 7s oe
Te StS re

82
82
82

iit oe Comet poe
faa
8 7
14

Gat 5 fours oe hd
| 68 |
62
50] 05 825
IZ

a ed ee Oe

ei ew ol
frat | es = eae |

NAITN
ie)

AT
C

E
26

4

L
S
ey)

aria Yel
ey ie SET a

T1050 | 1120 | 26 | 46 | 30

luge potas ea

io ea Ot |

LAT
MIN
fips ed (Geel fe de
padO tess f| 49" Od | -e201| 5 Ot |r

erie
ber Tiles

area 0a 1a 20- | on

26
26

LAT
DEG
26

a nores |= 10gs"| = 264s
Ga (ee s(n Gc 10

eae ee
ase a0 |= 26 sat] 63 f
P26 oe loner eet
(ee Ee |
foe oa eee Eo

TIME
END

i204 Bor ag [50 | se Sra]
1607 26"

1438" 26-40 | 245] 825i
tag e261 58]

eee Ren Pre ee ee ee

1g 085d | LG 2") = 2161 49-4

SD 959 | 26= 40) 226482 ete so el
eS
| 1600 |

L013") 1056" | 26" [5 46-4
| 1057 | 1200 |

| 1032 | 1041 |
| 1038 | 1049 |

Robe as mae eS a
26
= 2essroresisioay | 26") 49] 744

oO io
oa (SS
nN cc
waz Vo) ~ Vay co) fl a =) Ww] o
=O val Va) Va) atatlo =|
mm fo) _ N fon) Namo Win
— — _ —p | =)
=
os na ala N AlN N
=
mw O
—|N
wn) w

alae

Loos 2143
GER EOL ieee eae | eee eae |
Eee een aed leer ee |
fears Go com |e ree|
Sire]
Greely wand sci sew

19910821

199108231]
EOD ee ee ae
| 19910824 |

| 19910824 |

| 19910826 | 4 |

OO O8264| 55527

LO ONOR 264356" = 2
Sloonoszert S77" |

| 19910826 | 54 |
paooos2a 1

Ge 023 WW
| 19910825 |

nOotOs Ts =|—>52— "| 1s]
aos Te] S65 | 1 |
Peonne 1s |=

Bev Se ew ae (ome
19910819" StS
1900819735 ft
alton 19 ee 2s]
PaoOnOR 21S or

LIDTOR TSE | a
19910818 | 9 |
19910818" ]—25.2 |
19910818 [| 53 |
19910819751" |
19910820

Page 2

YOY
POSID
i Sie SS Se ied
fm oe eee Peele ed

BEST

YOY

pe 2aeee | et a
0)
piesa
fae
(oss
fasion
oS
EOE =
EO
Se)

Zz
4 | s/o nN °
=
m ©
<2 Sjelolslolololo
VE
=

Last

EC | POSID} B

85

va) So
+t Ta)

AAA N

ig
14

Poe

lB
20

Gil ea be ee
Pop 2
teal
al
iad
7
ater
oe lee|
2

ieee eve | BE air e

82
8
8
8
8

LONG] LONG] LONG
DEG | MIN | Ss
eaves |e loa

ei Fes ea eee

Sued
0
[Seba (aU Soe OSs

Sighting Data 1992
LAT

LAT
MIN

ESS ES aos aes

| 49 | 40 |
Ce Be

eA AO

LAT
DEG

(aa ee Oe os)
26 sil is4lon :

TIME
END

Lis 0S Ee Eas Ee
OOS GZS ae) es

ES EE EY Oe
SS ERE E008 aa ere Ss

iS Ei Sees
(Sec) SS es Pa
a ESS Ea oS aS
Res ors eae
ee es See ees)

Sas Eiour Ease

19920813] 6 |

199208 1elk |
iS Sa

19920811] 3
| 19920811 |
19920813.) —9 [Lt
| 19920813 |
| 19920813 |
| 19920817 |

19920813
19920813

SEP a0 ie ee SS Lor iis eS
| 19920813 |

DATE [SIGHT4 PHOTO] TIME
GRADE] BEGIN
Ca a

earl
ove eee

Heel

0

0

“Fe

9)
os
Pile
os
ar
a
Peo

So

2

6
etre tease
(aan ee

2 2
Pott i
tle
Sellfees Ge imed

Z 3

:

es Be ee eee

3

PBs le RDS |e Ot besos

40
Eade!
(eee ee oe ae

(Sees (ie ed (Se [Eee
CE FE i (i [se

2
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1239 | 1249 |
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19920818

19920818

19920819

Hee ee es
eer (Ey Ss aes

| 19920817 |

| 19920817 |
CROC Ee

| 19920817{ 54 |

| 19920817 |

| 19920817 |

NSS ZO era | pees Boa

| 19920818 |

| 19920818 |
EEOC ee ess
| 19920818 |

| 19920818 |
19920818, [eer o-¥|
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| 19920818 |

| 19920818 |
[19920818] 51 |

| 19920818 |
Rd ee es

YOY

CALF| YOY

So aaYyN

TOT | TOT | CALF

[Toe ee
7 24 3
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35
36
93
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82

LONG
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Sighting Data 1992
LAT
SEC

ie 2gk al abl
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Sa1es6e Dine iano] D3
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542

LAT
MIN

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Cree ee ee

Gea ee
Fe ee Ee

BONE Dior
e355

Dig | -45= —ie |
HOL0H|t-10270| 26>] —4 5-4-7 0ed
159-2264

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TIME
END

Bere es eee
Brie ars
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| 1500 |

| 1110 | 26 | 48 | 34 |

1235
BEECH ors
1042

LAT
DEG

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AOS 208d SAF 1 a a

SIGHT PHOTO] TIME
GRADE| BEGIN
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19920819
19920819
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19920819
19920819
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19920820

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19920821
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19920822
19920828

19920828

EST | POSID| BEST | POSID| BEST
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19920828

Page 2

1993

Sighting Data

BEST

seid
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YOY

YOY
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POSID)| BE

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LAT | LONG} LONG| L
SEC | DEG | MIN | SEC

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| 1000 | 1030 | 26 |
En Moe

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26

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mas
bt

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| 19930817] 106 |
| 19930817 |
| 19930817 |
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| 19930818
| 19930818 |

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19930818

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19930818
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19930818] 159 |

19930818
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19930818

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19930818
19930818
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19930818] 162 |

19930818

Page 1

YOY

PEPE
PeEEPee
HEE
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POSID| BEST

0
0)

SEC |POSID| BEST | POSID| BEST
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LONG| LONG| TOT | TOT | CALF| CALF| YOY

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19930819

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19930819

82

19930819
19930819
19930819

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19930819
19930819

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19930820| 4 | 2 [1005 [ 1015 [ 26 | 44 |
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| 19930820] 103 | 1 {1034 | 1043 | 26 |

-19930820)|' 104 |) i) |
[19930820] 105 [ 1 |

19930820{ 13 |
19930820[ 14 |
19930820] 101 |
19930820[ 151 |
19930820{ 152 |

19930820

Page 2

YOY
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0

CALF | CALF

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SEC | POSID| BEST | POSID} B

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LONG] LONG
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Boe Rs

LAT
SEC
98

| 40 | 82 |

Sighting Data 1993

LAT
MIN

45
525)

45

x
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26

26
2

LAT
DEC

TIME
END

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| 94D Soise.|
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Pi99308207 158) 2" a0 F205 |

| 19930820] 159 |
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19930820
19930820
19930820
19930822
19930822

DATE |SIGHT4 PHOTO] TIME
GRADE| BEGIN
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Sighting Data 1993

TIME
END

DATE |SIGHT# PHOTO) TIME
GRADE| BEGIN

45

aed
13

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51

82
8
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19930824
19930824
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19930825
19930825
19930825
19930825
19930825
19930825
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| 19930825 |
| 19930825 |
| 19930825 |
| 19930825 |
| 19930826 |
| 19930826 |

199308

| 19930826 |
| 19930827 |
| 19930827 |
| 19930827 |
| 19930827 |
| 19930827 |
| 19930827 |

——

YOY
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03/27/96 Appendix 5.- Animal Frequency by Year Page 1
1990-1994

Dolphin ID 90 91 92 93 94 total
AFTR 0.0.0 01 D 0:02.01 0, Oe OO sora Of 00 0 0 2
ANFO O05) OO 0s 2 010-00" 01 Oo 0 20.6 SB on
AOSC 00. 0 Olo © 0 Of 0 00 Oo 0 Ol o 4 0 2
APFA (10° 100.0, 1 O10 OC ONO aio, 0 1 Of 4
APLA 00 2 ol 0 0.1 O10 0 0 ON O01 01 oO Oo OES
BAGC G.0 O00 OF OOO OOO Core Of o-oo Of
BAGP 0.0 0 0) oO 0 oO Ol 0 0:1 Ol OO 1 oO] 0 0 14 0 PS
BASC 0 0 0 OO 0° 1 OO 0 OO oO 6 oO | oo Oo OF
BBGH 0.0. 0 Ol 0-00 OO 200 Ooo. 0°81 oo) © <0 O19, 2
BBUK 0.0 2.0) 0 0 5 0l0 0 0 0f 0 0 1: 0) 0 os 0 913
BEIC 0.0 1 00 0 0 O10 00 O10 0 0 O10 o O14
BE2C oOo 0 010 6 0 010 00 010 0 2 oO) 0 o-1 sOohs
BEAK O09 2 0) 00 0 O10 00 Ooo 2 ol ae oe? 80 Fe
BELC CW 0 oot OO 0 OOF oo or Oo) Oo 0 Lo 1
BELD 00. Cio oO 2 OO. 0 1 OO oO: ool uo 4 0 Ine
BELL C0 t C1 6.0 2 O10 0-0 Oly G2. 0] o oro 20 Ps
BFBT C6 4*oho 0 7 C10 0.0750) G 1. 0| oo o Os
BFLA 00 16/0 0f9% O10. 0001 O 0 2. O].0 0 3 of 7
BFMC G0 BONG 10-0) os O00" 10 “0 oN. oO a fo lo oor oes
BFMD O40) 26 OO: Oo 00>. 0 NSO Oo Bo. 6 | oO at. MO
BFMS 10 - “ROL oo Chore OS0 los 0 0 Or OOF lO 4p 3
BFSS 0 2, 0-0 + OL OVOLOLOT O40 gy ol eo 6 oO. 8 Ls
BFTB 0-0. 53-0 00 2h (Ol 0 3 FU. Oe go Ot Oo O40 2
BHNL OO Cie 0 05 0. 2> 01050 0 FON 05 0°20 ae] 70, 0.01, SOS
BITM 0 0° 20: Olaoe 0 26: 301 0 SO) 0 RON ‘oa or 0 | oo 18 MOC RsI
BITP 0-0 6 6130. of 4 OR 0 Jo) t You doco: 1% o|-o, @S2* sofa
BKBC C0. s0- 0) leOe 0". 2. Ol. 0. 0. 0 LON orton 3 20) 0, Gnade Ol SEEY
BKBS O00: 3 01 0 O39. Ol De) 0 SON o.10 43: Or Poro 4. 0 53

03/27/% Appendix 5.- Animal Frequency by Year Page 2

1990-1994
Dolphin ID 90 91 92. 93 94 total
BKTP OO e2er 0 OunO Mere 0,l On Onsen Onl On Om OM nOm 00" 1a O85
BLND ORO Psi e Oil Onto PonC0 CON 0. 2 FOr oF Om LOmmOna0s 0620.99
BLNT Oo Oe 8 Ol W 0h 22s KONO Ae OM), fe Oo Oe > Ve eo ] 14
BMBK O70 ono oto 08-0) 0" 07 07 Fol oF os Won ioe 0m ss Onl 6
BMST OROMNO LO OMOS OM OO O00 60 of 0 2 ORIOL CeO On pee
BMWC CAO Me ONO ZI OMOu 0210 IP O50 079012 Ol 0. ON 704/40) Ome ia2
BMWL ORO EO Lomo c i volvo of 07 oi of of or tos ion om om Ounas
BMWM OOM OL0 oar oma 020% 0) 0840 I of oF ool OL Om OEE2
BNSC O20) eo noulo oan ror holt om oso 1 oto o® “0, | on 0 Vom Oe eS
BOBN OO eS to iro ro Mee ooo oo 1th 0.0, 6 Soe Ou
BOFF Og uae co eaten sey Gol Voenor 1. 000 Fos ode on of on iss
BPNC 0 2 ono. oso t EO) Oe cree oO lSomoye it oe OOS SOs
BPNM OO On 0. OO; ea rtetO) Oe Ole 2er OA ows am Jos Ot 0.206
BRBU ORO Or ach oon eo sO Oe One tO Nano Uli iol to. 0 2B
BRDO 0:50) ror no) oto Ma fo leor conan for 0020) 0r 0.) 0) 0 Mowe 0. ft
BRLN 0) Mo Moe io Wo: "22 ONO MOO. Ole 0 oO ow 0 So 0 Nose. 0. hz
BRNB Oo foro: ao Yo. or! tol 0 ou oo so ome 01, oOo, 2
BRON On Oe Oy ta, |O. on tat 10/0 sO. sie Out 502700 col 0. oe ta 0.3
BSLC OL VOsw EO, n0 Oe, Zon [0,8 ork: Ou orn Bo: or oso eo. Nes
BSMA UetOu lor s0ulo. Mom oe 0.050, sO. Oni oo is Bio. || Loco ao seas
BSMC On On 20) 40nt Oo 6,"0)|- 0 0" 20" O05 0, 50. 0) 0 3 ae Rs
BTCC OnLOerOL Oults0, 60 = 022 0)| (0.290% 0 =O Mor io. 10,1) OL sO ome ue!
BTIT OLsOMmlpOu Oe Ono. 0 [Or 0: tL” OFRFOnO) te 10, |) On Ome Oa kiad
BTSC OO sR LOO Og 0 Oro) 07 OOF 0.7 1.2 OnLine Oe fied
BUBC OO OR CMO rOn eel OL Or nit SOM oo) ht a) OL Oat ee Of ad
BUBD OLE Mog OO FOunre eo Ol OL 0" Tt PON OG: fa Son 04 081. 20 | 4
IBUBO OL Ose iO. On Oc Ome ONlO t0 OP ON (0 Nig aLF Onl! 07 0.1, 0 3
BUCK Oe BOHM Ouro. BOON 0. 0 407 ON ip ng Oo." On|. oe 0 kn ONS
BULB OO R720 | 0 0, eae 0 01 FOO 00, 2 8 O10, 0.2, On gMatS

03/27/9% Appendix 5.- Animal Frequency by Year Page 3
1990-1994
Dolphin ID 90 91 92 93 94 total
BULM OHO” 0° QO): 0, FO AFC yR De Oe LO Why, YOO Or One O1lb0- Ogos Ox I
BUNB OO d22 0, M OG Orh are Oe GA Onl’ Oh NO ry Deli Ong Oke
BUST OVO 0, a0 Ope rOlp One Get O4N 0, 10m yOu 0. Opate, 0) §G5
BUUD ONUAL 4 FO) OdLO gO, 1 OOO HO Ole OOO Cel OO yt a OSS
BWDG OMA 2 20 Ox Oi 14) Oly Ore OOO OO Cay ill 0 Oyom O WPS
BXBK OLON 20 OY O— 10) OH CO Ol W404 340.0 sO .0 gy OS
BXLB OOF B20) On Oy ty) Ol On Oo OW 0405 24) Ol 105,03. oO PZ
CHIP OPO OANM Oy Ogsty: Oly O0y iO 1 0410 y 2 wy OU) 20 UOp ON So
CHKD CORON OF Oe Oy-O% Oy Oil) Op CO), ON On 20 2p il 10 Oya ON A
CHOF OPO Heol WOH Te Oh We OO WIO POs Ve Ou) 050.9) Of a
CHOL ONO OC ON On Og th O10» Op 04 01 F040, On OF 041 y 0 ie?
CHRG OOK 0 O71 0S OK Oe Ui, OW Ow 0), 01 0004 34 0440, 042 y ONES
CLAU OLOL W010. 09 04 Oe 0p 0, Oj05 0425 Of 1 040, OP 2
CLCA OOH, Ou0 0% 09 0, OOy O.. 05-01 090i, Oy, 0,10), 0424, ON ee
CLCC O04, O,OllPO% OG, 04 ONO} (O\40% ONO gO), Oe Gi) /05\0 42" Ont y2
CLTO O05. 2. Gill Oy 0% Te COs Oo 14 O11 09.0520 9 0) Oy Oly OA 4
GEUE LOM, Seve Ow, 04, 0), OHOy, Of 0% OL 0. 090 6 Onl Oy 0.605, On [ge
CMNK Oy O%, 12 OF OM Op, Tj, Odi Oly Op 0 Osi 0). 20) Oey 0, | Oy" WO. Ong?
CNFC Oy 08, 700 OP Or, 0 Oy GIL Oy OG CuO) Ons 0., 24 MOTO. 0, 205,00 et
CNFL O1{0%, Oe Oly Ory Ory, OA OVO) Op Oy, Ont O70, 2 Ola Os Oot OL Bes
CNOF OPO 45 Oi On 07), te OP Oy 0) Ory Oly 05.0). 04, Ol 0. Ont On fae
CRES O)0), 18 081,0), 0) 1 Ol) 0), OF Ws, Oy O41 0,5, 00/190, O50s4,-05 ks
CRNM OF 0%) 0 ONO), 0 Oy, OIL Os 04:0. 0, O40. 415.4 Oy ls Ov O40), ONE
CURL OF 20s Ae OLE Diy OF din OM) Us, Op 25, 20H Oy 35, Ohi |f OO), Se 5, Oy MAS
CVLS O02 1 Ob OF Or Oh Oil, Uh, 0) 2s ON) 10s) Oy os Op Ol; Oo y6y 9 Oy gd
DAR2 D Ohn, 0) G: OF KOM 40,0), 0. OF O40 07-0, 30. 70; |, 0, Oo) Ou Net
DARC OO 0), Glo Ory Oy, OW) Oy WOK) 0670; 6.0) 4 0: 1h 0, 0; 0 np OE
DASP OOo OO 0.0) hy Oh, O 1-0/0) 0M OVO: 40) 0, 0-0 40 Ol Bt

DBFL 0 O14: OO 007, OO: 4 Vy 2 Oak OO war 2 Onl, 0-0, ORO Ie

03/27/% Appendix 5.- Animal Frequency by Year Page

1990-1994
Dolphin ID 90 91 o2 93 94 total
DBNC O\0b SOL sal | tomone om con,..0 O08 COME OP 0k Cie ‘Olf fonl OF a4 Oy B02
DBNK On ONS 0/107 20 OM tev Oll 00" OF (0M 162 108.20 of lo) Od 24-009 cS
LDLG 0.0.) oN 070% 0% 208 01. O12 07-17 ‘0%. G4 0 36 -00] toy oF 00-0094
DEVL OL ON) onto 10% 077.0) 09 0) 0% 0%. (0% Os 0. On| JOY OF Ory Oy 02
DIPT ONO onl Om om 2% sol]. 0.0? 19 OM [O% oF ‘Oo. On] Foy 0) 3% On vs
DIAW QMO MELO Onl se OF OOO) OF 0 OF OM 102 OF 2 On| tod OP Oo Oy §02
DLHW On Ome Or cl for 0+ 6 Ol OY OF OF OM 10% Ov 1m On| fod OF 29H Op I>3
'DLRD Our a t0r OF (08 08 G0 Gl OF 0).0) OF 16? 08 20 05 (OL. Oy Oy 2
DLSN Ory tot ott fot GS or Ol: 09.08 2) Ol oF On1m On| fos 0) Iny Oy §o4
DNNK onion toy, oll Jou ot 2% of 107 0: 0} ofl Tov on 00 On] fos oF Wy Oy FD2
DOBS Ono4 52 oso" ot. 19 Ol 08 0 08 ON [OF OF tu Oo] for O md On fos
ILA On0-8 2 ol Jot 0% 00 Oi. 0% O01 OM sO? OF OM On| fos © Or Op Fr2
OTLT Oo) Or. Cfo 7 OF Ol OF OF.0) Ott tot ob OD Op) fo O 2!yOy IZ
EDSC Om oPt Yo) orl fod 0% 09, Ot O00 19 ON fof .0f Sq ON/4O) O 19 On Fe5
ENM] O01 “Ot OF] fOd.00 09 Ol OF OO) OU fo) 0% 20 Op] JO) O Oy 0, Jh2
ESCL Gio 4 oil toe OF 10 Oi] OF Oh M Ot 10) Oh Oy ON) LO! O Ory 0, fre
/ESDG OP of) Wo. 0) fos os oo Oi) 09 OF 1 atl fo} oO 26 Of fol O iy Oy fs
ETBP O07 13)- ofl Fok GF 20 10) 08 O 2: Ott fo} On Oy ‘O9] Hol. @ Op Oy 9e7
/ETCC oF dc! Sor Ol. 40? 0% OP Ol 108 OF OF Ol iol Ob OF Of fo} O My iO) f1
ETPC 0-0 0 Olio of oF Of OF O OD OO o of mI ho @ Hy Os fh
ETPL Oat tf oF Jot.o0 of 0 OF 0 0 Of Jo). 00-06 Oho © 2a) 4y3
‘ETPM 0) 0) 6 ol fo) Of 0 Oil 0% O OF OF io} OY Oo OI }Ol.O 2H Or ft
[FAFG Of O°. 2) OF JO? O> 1%. Ol 10% OF OF ON Go Os do Wi) hor O O41 4
|FANT OF 1G: 2) Ol fot of a? 0) OF Of th 0440) 06 24 O] HOO 2410. 7
FASC Oo O* Fo: oll. foe OF 4% Ol > OF 2) OU fob Ol a4) MOs} 40) 0 1 ns PS
FDLB O 0. “or 0] For o% ‘or Oil Or OO, ON 10h OW'Oy Os] FO! 0 22,0, ff 2
lec oO! 10) 0] Fos 04 30) Ol Ob ‘01.0 OF Io’ 0: 3a 403| $0) O 5 10. IPS
FHIC GY 06 oh ol for Os 2 0] OO 0: OU i 0) Oy 108] 1G -O Ono, |) 2

03/27/96 Appendix 5.- Animal Frequency by Year Page 5
1990-1994

Dolphin ID 90 91 22 93 94 total
FLAX 080 f Ow Ob iOg CH. 3H OP OW Oy OF ON Or OF OF Waly a 19-G 4
FLBU 09 0 2 2) Olion On 29 Ot Om OF Ty On) (09 OF OF OD.) jo) 0) 04 09S
FLDC of 0 w OF Of Om Of oF 10) Om 0] OF OY) fOr 04 2H 0.) (oy oO, 04.6, F 2
FLDM of 0 @ oi) Ol foe On oF 1 OF OF OF Of) OF08 28 Ol f0) O OY O, | 2
FLLS OF OD Oh tor oa 14 Of ON OF OV OA) OF O8 OF Hol joy OF 1% G8 4
FLPR G01. 1 Wlifor.on 16 OP OW OY OF OM ON IOF OF Dolijor a) OF Of 2
FLTB 08.0 S 2p | for on ow Oil 007 1p OF) On Og 2H Uol109 0) 0%, GES
FLXL 4-0 MOF 100. Ox OF Ol OOF ON Oi toy 08 OF OAljoy Oy 1), 0, 4
FMBB OF.0 1G Oito%-07 Om ON ON OF OF OC jor 0% DA Dolio? 0) 0. G2
FMBK ORO. f OW OF for OU OO) OOF OF 10 Del On ov, 2y Oy) /O; 0) 1 4 OF *
FMTC O80 f ter OF) f03.-0 1-30 Dat OH OF 2504 jor OF Gp Onl poy sot <3: 4 Ori 15
FMTH OR OU) Se OLonoo 32°01) Oc) OY 4° OLh toy 09 64 Os|'tOr OF 3.4 0, 19
FNTP oh.0 D+ se) op)yon: On: 06" Oil’ OF".09.0F OM jos OF 1yO)P10; OF 04 OF 2
FRTK OF Oo © 1) @fow O09! 25 OL OG OF 27 OF lov On OF Os]'/0) OF 14 OE ©
FTHS OOF 1) Glo OF vow OI 0G" OF 0% ON 10} 00 OM Op|Of OF 0% Oh Et
FTLB Oo Ne f. OTE UO or Oil) 00! OF OY OCI oy OF OM Gyro Oh. OL
FTMB veo 1 ak oO uP os cod Ol On" oF OP GA jon OM! 10) OA yos oy 1.8 OWE 3
FTNK Geos Oa bier Ockow Ol Or Or ON OW) lov OF 1g! Oy top 0%-2 f-O, 3
FTPN 0%.0 Bi TO O ow Ow! OF DION” OY I OU ON OF 17 On| FO OF 14 OT 4
FTSE G0 1) 2 O Moron? 1 DIS Oy! OF I On joy Oa sy Oh yong 1 2.0) 10
GOAT GHG 52.20 W/O. Obi 07 Ol) 094.0) Oy Oat top Oy On On |¥Or Oo 0% OF 2
GOFG aot OOO oF on) QF on? 0% OF Oo) ox ae 03 [ 40; OF 1 FOL ES
GROV G2 0. UG Oh ox OF! 20 O00" Or OY ONC TOF, 0; 1-4" 0 MOp Oy! Of 3. 4) On: 9
GSDS 0:0: 54.00 [dort or 08° Oi 00 OF OF DIMOMOn 25 ON) OF" Op 1-405 73
HAIG oho 7 Dito iow or on Glow oF wodtlotvoy ta on or of ah OE 7
HFFN Gro 2 wo} {os oro coe oF! 10" Oo otow Ou onlay of 0405 F 2
HFTP Hoe hol fon oLe 10° OP b On Oy MOLINO OFF Ot oar os oF Op 2
HICC 2) 0 WOE Oho OO) TOON OF Oi Oo ow On. 2x} o,[FORiOn 3-4) OL I

03/27/9% Appendix 5.- Animal Frequency by Year Page 6
1990-1994

Dolphin ID 90 91 92 93 94 total
HIPF ORO 1550. PO) HOO. MO OG-08 O% O1IOm 0). 60-a OF y20e-0r 4 Oo 3
HIPL 0) JO: On Gily-o; Lom 08 Ol Om OF 0.0 OF 0in:0; corm 0) |) On 022 0 Jp 2
HIS2 0) Onn gO ly 0s OL 505 Oly Oly Op te Ohlp-O7.0..60. 6:0))|p 09.0) 10 gO I)2
HISC Ony0) i 58 OG lp Oe 0 gS Olli Ohy Or 2.q 0} ly Oye Ohm: H Oly Oe 0) ay yO, If 19
HISP O40) ee 2p Oly Oh 0; lO OflO.e Oy O/H O}ly 0; Op 504 Oly OF 0540.60 fh 2
HLBU Oj TsO Or 0) Og OilsOPy Op 1, 4 Ofly 0) Onn 1) wy Obly Op 0242 oO, PS
HLDN 0240, 6 On Gli O pO, (0G Oly Oy Oy Op Oly OO, ot, g OF, Oy On 30) 9% 1
HLSB O40) § 29,04) 0; 90.9 ho OGG Oy hoOily 6-0 oon Oly Op 0, ad 6% IS
HNMI 0). 10). 60 by 6.00) phe WleyO. £0 OD BOM) 0.400 9 Oly Oy 0 O yO IA
HOLO 0,540,490 Orly 01 0s wo Oily Oy.) 05) POM) 0.50, at 4 OF) Og O i OO. 3
HOSP 0, 0) 6:05 Orlix 0 n0e4 3.4 Oil Ot Om Org Oily 0/0. 0,2 Ol, Oc 0. ind 3
HRMN 0; Od tay Oily O, 0 Ot ONO. 4 Om OG Oly 0,90) 92: 4 Oily Oy ©. 2.90 FES
HSLI 0, 10) 2) Oh ly, 0: 5 1.4y OnloO) 2. Op. 0 ROT: 0.40.00, Ol 0; 0 0: 0% 3
HSLR 0: 0) 06 Oly. 0 20; #0, 5 OO, 4095: H0fn 0.40 0 poh 0nd 6 9% | 2
HSML 0:0) 7 09 Olh0, oO. 20 fF OiloO, w Oy, O GOily 0, 20, 42) n Oil Oy Oa pO 3
HSOC 0.G 2 Ole 0 10; pdip Oiled ¢: Op O-HONs O00. gt) 5 Os Op 0..10 yO ILS
HSPE 0, 0, & te-O}ln0,. 0, 40, yOilnd, ¢ On 0, cONle 0) 201.409 0Klp Og 0 0..4,% [Et
HSRE 0; 0) 4 Op Olp.G,90, ging OlinO. p O00 BOMe 0, £0. 0: eth On Oy ae 9 0, Ih 2
HSWS 0 O go OE OKO £0 JOrg Oia, 6 Oy 0; HOY 0, pO: wt, Ula Oe Or ts HO HL2
HWCS 0, 0: 465 Oly 0) 10-492 4 OillnO, 1 O40 BOjly'o, pO; ni o OF) Or 0. dy yO FO
HWPD 0.0 6 06. OleO; <0’ GO » Ole, 6 On 2 YOM pO, #0: 62; GO| OO: 8.4% Ne?
|ALW 0, O bon Glpo. 10: no H:OileO, 1060 Woe O00; ao GOs Om O02 gO IP2
|AMS 0.0 6 Oo OilO: 10, GO; 5010 OOo 0 cUAigO, <0; 0 OOslpOm 0) a yO et
KBFN 0) 0 bo Aled 0) 60) Used, HOGO MMR Opsd) co gos on od oO I 3
KEYL 0. Or 5-0 Oflod; 10). sty oOdNGy GOGO; CONGO, 20, 0: gOT0%0 oF50) Ih 1
KNBK 0,0 4 LarOthyd) 20, 20) 9 Olin: £0.90) GOO: go. pt, AOU Oy, 0. G, 0. 2
KNHL 0 0 Fy OuligO: x0v wl wOsO? WOO) FOU Oy a0) 20 Oyls0. 10. 0 og 3
LAHS 0) 0, 43: cOfhg0; 40, 40) sOl0, 50:00, © lad go 3 cOlydind 4 10. J 10

03/27/96 Appendix 5.- Animal Frequency by Year Page 7
1990-1994

Dolphin ID 90 91 92 93 94 total
LATP O19! O12 .0:[2 O5.0)0. 0 010.0000 OF CHD OH ORAM OOF OIL Od FFs
LB2C oor Ob ON. OM OM.OR O19 0 OO OTOH OMGNe kr 'o/4 OF <GemHOG OF IP 2
LBLC 0) 90-08 cal! Om O08 4W) OllF oct 08 OM! OF GMigmh ee oti of og 08 IRs
LBLT Ou toil: 29 onl L.och oF 3 OE 0% 0% 01" OFM GP ONR DRE Gilt of so tgott.O8 IE 10
LBTC ou foo 19 oi: 099.09? 110-0120 oF 2) OF” OR OSE) oFfi 0% oo. Or IRS
LBTM @2 Jou 12 oP ott osO110- 0117.04 oF 2 ott Mo eat ont of of OF EZ
LCLG GR O22 18 oltou tgs 97.) Ol voe OY oO: Mort oto: Boreorlt 0% o° foo on ft 2
LDAB Ontos 708 onlF og) O14) CPO)" O80 OP OO Oe orf + 0° 2: 8-0" FS
LDAL oO. ok oF wlP orto: Toe OVO o% 1 Yor oF o Posto 07 oe Ge 907 92
LDCC Oo" 80% 0.0: toe So olleo?= oF 1° ONO OF Ma mart OF Olt0 0 [1
LDHN ov foe #20 of19 of 90: 4 oar Bory o'0 MON gt on 0g") ob) OF oe ie ONES
LDKB foe o> OF Orso: Go -olP oO: V OF 184 0Ny Or On Coe Oro oO 4 VO AF2
LDLS pe for 9 TP ofl? or Bod Noe or] Fool OF 20 oro fa: Corl? of 0) 070.0 Pa
LDMB oO fo: 8 oP oF or 80! Fon OlHONe OF OPO OOOr 42" Ob) OF oro: LOT BF2
LDMV On 0. 3 Gt/F0 Sor 2.2 OO OF 6 OIA GAigr DoD UGE Ly OW on foo Bor IRS
LDRO 0° for 9 OF on]? o> fo. 80 7 Oa Om 3° O49 Oobon i129 OF) 0% o 'o0 MON IRS
LDTP Oo Oe) oulBior Vos OUP Ort OM 2 HONE oignt3. Go|) Ot OT. Gor IR 17
LDTS of 0 21 ol] #0 Cor atoll VOTO 1 COND onto” Sot Bone Ov Oo He GO IFS
LEHN O2.072-OF O81Fo" tot. FOL Oe Oe OF 40? O MO> S07 L.o8|8 ot-oy oO) HO Ih 1
LEHT On OF." 3% Ord oy toy. Gish ool FOF 2) VOne oko CoLDoFf Ow.o Bo: ATS
LEMC or or Vow olor to: Bo PON DOS 08 OOP OO! M32 LOTW Ol 05.40" PS
LEMO Oi 0° DOT ON HOD Gor MMF ON POLY OW 1ONE OR.08 152 LOOM Of 0" GT 805 B10
LETR 0:0 0 oD ON102.40" f2=0 Of 10: POO ON ons cor 002|t 0 O71 oO} HOO REZ
LEVC 60 Oo Moe al] For ton Sanh oN DON ONO Nom qevO I? KOR] P oF 0. OL 10 FS
LEVM 62.0: Dov! oll on tou (200i For otior SoNPO® for Oy Vol Roulor Ge TOA NES
LGAF OG ool] Hor ton fo Coll hon 4011) Mot o. Non ton Not] Dont on. on MONET
LGSL 0.0) Srtoultor foe Yor Gor) Moo. on onto: foe Go Mom os Ge Yor IF 4
LGSN 0 Oo Noll Yo io ( “Od Or 70% GOARE Yo. > Yol[how-ar Ta 0 [1
LHLA 08 Se FO] Por fo. ia: Bo Mor Comte Soul Bon Moy G0 Lon Pow oe a Norge

03/27/96 Appendix 5.- Animal Frequency by Year 8
1990-1994
Dolphin ID 90 91 92 93 94
LLSR GWG, ProWoyfar Topo. foilowt0. ae Foo: toy ar Go) |: ‘or io) OB 2
LN2C Q 70,0 Foro: 90) Mo. Foill¥o. Fo to. IO oO cor at FON som io A
NDE O00 10 Foul oO; coum FOO) Yo) Oy fOrI0-o) 40 vty Moro cor a 90 8
LNSC Op OM i FoslO Coy a Foy Oto V0 TOsI" G Woh eit Vo} Jo? Gi 0.4
LNSE OL 0,5) 3 FOU 0) 207 5 MOO WO (SF AON) O €0)73) Ao) O Yo) a4 oO B16
LOFL oon © Forl/0) 809 Fo! aol Xo Cor VO @ O80) Tod O-vore 0 9 4
LOMA Oneoue 0 foul? o) Cone th) UO O OO <o (ON .@ Sones Yoo]! o odode oO {2
LONC oon 0 foul) Oop.) AdIP CO oi FON) © CORO aod © volutYoO | 4
LONS OOG” ar FouMonvogl og POMPE UO 1p “DOT o Coneré sol) 0 novia) 0 G7
LOSC Owoue B Foul 090000 37 Kode OF 0. Zr SObI Or wow) 19Glou) @ Lodmat Oo If 15
LOSO Gao! dt Toulon 'on! oy C01? 00. Yop 04) oO). vooeON ou} 0, vodio0) 0 jf 1
LOWV Oog>: Mosh 0s 20) 2)-0'l* GF" 0 CON HOM). 7007 09.00), .0 eoMo 0458
LPSP owoM a Foul) Octow 2) MONON" O MOVOM O) JONroN. ON]: G Kowod)0 FB
LSBZ opioid! Oo: IO OM Om OHO? OOP G: MOMOM Jo. Vote 100 ON) oO BOMLM 0 4 8
LSFC ono o Soi Ort ow 19° Ol) OOF Oo MINOM! ‘OV0m OMLOd) G Hof d 0 PB
LSFL Ouse TOd? OF Om aollt-o18 O MIMO OOM OW OU} G.LoTsar 0G
LSFM OfOe oO 100) OPO o1¢ Ol OFF 0 KOM ON QAO ON 04.0 Bots” 0 if
LSHB OFo8 5) "Oi oP o* 190 Of O87 0 “1M 01) ‘CHOW Of Hi) 9 NoMOR-0.K§
LSLB o¥oe TY of oF 07 OF OF OVoW OF loMo® 180%] O Looe oN
LSMN 0809 _ oF oih of oF 1 O1OW OOM OV Oo 14 OM OVORON 04]
LSPN OOF Bi bd-ov 08 16: Ol.0F 6 1900 Grot of O1| O00 809 0.4)
LSPO OfO8 OVO oF 08 10) Ol OF OF10 OF OOOOH ON OZ ONIe ONF
LTAB 030 80) OF 06 oc Of OF OFM OT De 08 1% Ol foe0e1.8 OW
LTHL toe ceo} 08 of 09 Oh ov CMO OD lomo 0-08 6] Orolo 0 of
LTLA 080% Of OL OP odoe OOF oF 00.0 000012 04 loo v0 0 OUR
LTVc ato 8 ov ohioy of oe ohlot of 14% 0 b7209 0976 04 foM0 909 0 Pz
LTVL 404 oF Ob OLO 18 OO? OF 1 BON o% 0874 Op or O01 8 0.9 4
MAIN oot. of oo to tog Oho OMOD UPigs 089% Oy) (ol ow S079 A
MALC ORO 'h Oo Bo 08 OOF vl oe OM os OmMoe Oo ot 0 1)

03/27/96 Appendix 5.- Animal Frequency by Year Page 9
1990-1994

Dolphin ID 90 91 92 93 94 total
MALD Oro oFoliG Lovo LoOhrortoto noo orl oe Soll e on =o gta
MATT Ow0; OF) (FO toy FO VOC! ana Fiori o hon) oy toro B Posies
MCBT Ody woydhro so 30 Vallw Sy Aoleo 0120 Too doom COR et
MDLB OF Oy B24 Ovo 40) +3 VO 0 ROO Hoylso em en jo)" o Vora oss
MFLA ONO TH Ovo Oy TON NC) QOPI MOMo 90) 1.01 jo:| 0 Vow?) VORP Ss
MICO OmOn 10 Galea NO; 12 KOlIo OS PEO To F0x20> to \| 0 ov on YORI.3
MIDT ON0H 10 WOs100)00) FO) MONO) SO Sy MONO soul ol Gor] Oo “od od OR IAI
MLDG OOy HO foul soon ht MOTP Or BO OF ON. cou C09 Soho Yor 1) 708 9F2
MLSC Oh Oy. U2. Gan Gor ion 0) Koll oy 1802-23 Abe co sou oO? Mon) to YoY 10 "ORES
MLTE OpOn 10 Aor] wor 80g wy HOU GOL YO WH SOUL o. (9 208 Hohl "Oo YoPol YOGI) 2
MOUC 00d 20 doslvon cogs) AOU ia) “0 OI Yt os OO oa MOR VO, sot oe OG IE2
MOUN OPO oi od horrog da: Od %O) 20 20; 20K Uo, on 24 Von “oO Yolge VOR Irs
MPIC OsOu 10) /0r] On lOn Vor LOM Or 0) “04.00% “or om! 2H *Os] 10 Codiay “OFNE
MPIN O570% CO Oy] Oy 04 82: Od MO YO! 200 OI For OG 226 “oul Vo Con 44 Po BESS
MSBC OOH 22 “Oil “oes0U O71 CONOOr OO 90500" Yo; JonGoN Cok So: CoO “0 ENF2
MSBH Ops0h «a LOU ONCOH 20) TOMO! CO HY Od Morag ton TOE So Savon “oO Fy
MSBU ONO <% “Oil OeL0s Oy OM0N 10) 240M voy ows1 1) LOR] SO COMT HNO RI YS
MSCC OMiOg yO GOKl Onur 105 Od CO; VO! 1298014 Hoy OG Oy Oe] NO NO Hoy 0.2
MSMA Of04 10) On) 07706 ig ON 0p 90 1HI04l V0, 710.034 S| LO’ 0 V3.4 FONE *S
MSMC 000m 10 LO ON S04 ty KO Oy “OTH LON spy Oy Zu VO] 0, 0.3.4 "0 AS
MSPC OeOw. 202 Onl oOo HO LO, 201160 ior 0.) 74 Ol “Oo oe Koy ONT 2
MSPD OO 70) VOW P07 20.4 10) SONOS YO; 0001 Os (Ou Ou 0%] Vor 0 F140 I
MSPN 0: F0:(y th COM Cooney HO:[ 202 Yor “SasON) convo HOG Veil Yor VO 172.00 UB °8
MTAB O FOS LON 20. G20 6 206 OL 0H FOF) LOMO O10) OM CO) YO. 92 "0 AE 74
MTAC 0:60 4 40) “Or fo.y'0- cade Colinas ore Loh Yodo wo uA) vos Yo Go. {0 I
MTLA 0 40 p00) Oil, 0 70 poy WhO, Lor Ooh COKto a Ae) Oi Lo HetO IS
MTMS 0:20 « Oto 1.0 afd CRO s.0) (Oh Cox io: us2 ath Kon Ko Mi 80.5
MTSC © 10° 1G yp VOlL, tO KO: ola GAO O G 0) OYUN ogo T pial Moy do. 0 B22

MTSP 0 f0 4 te:OlO PO 96H Oh/0 UOT ORDO n'y ws. hol iou “0: 03. 40 514

03/27/96 Appendix 5.- Animal Frequency by Year Page 10
1990-1994
Dolphin ID 90 91 92 93 94 total
MUNI Ou. moll omowool OF CLO ON oo of od..0° 680° fo (p31
MWMA OROM Vor ormoiom2 B0lt oF ob nS Oto io os2o0i| 020010 0g.
MWMC Ox 0 SOMONE ONO 2)8.0)))08 0%, WOM o" oto. "Roy) 0860" Jo 3
NALS OO Amol Rowe mov PO1.0F 08 APout 8.01 or Sod. oo P42 0 3
NBSB OOM. CONE: Lomo} P0109 OF OND o M924 OF Fo] 6-90 Yor 0h 4
NDLA 0100/0) SollZoyfomoP0:l-08 08440 15 ol Nose on tof o'%G %19 0 ig 2
NELA 0/00, 24 H0'( 0.03 Holiso® Hoilf0® OF 0) 80.45.01 100018 Mo. 0 So Yo! 0 5 3
NELS O10 M2: 601160) Hon 2 HoilF os! O.08 FON 0) Cor UOE Yo o> So Yo! 0 Na
NESE On HO Psp Hollow dome 18 Loi! fod) Oa M01" oF Hot ik Bo Po) Yo PO IN 12
NIBB 0 £0 a0) 40) Sopeopmibtoto® O02 FolPouwto Sok fo Fo: Co ho 6 2
NIPE 0) fo (hoo do Tomtio# foil Sow 0,808 f0718.0)F02% 81 fou 0) Yo 0 65 3
NODM Oia: Sob foul for fo/LGud foil Hom on tito. Toe foe ie fo). of fo. fo? 0 2
NODY 0) {0:46 26 Tol ton, fovwo? Foil tom) on Bitte Mon tow Yat fo, IP 0: fo, "ol 6
NOTW 0) W: (Qi0} foil. Cox @p VO Fo: GO" O FOO 10? 08 Soul fo [oS for" oF Ea
NTMS 0) @ Wo} Ol 0 1 G04 Yl (0: OL 808 10 Irtoe OF S040; |) 0 to) 38 oO 3
NTSB O) 0: a1) 0) On @0C02 0) OM 0) (ONT IPoy 0% tO 0 [Lot e608 Gis
OBLA O80) wat!) 0.) 0a rrtod 10} “0 Bor (OO thon Ge fod 7 od OF fo" Oo
OCAC ov.0. scot 0) On 020" 0) OOD 8 0 1\or Oy 04. 0 Mon O12 0 hz
OCAR 0.0. Hg Ol Oe Oxto8 0h 0 Wo1 2AO 1) o> 0) O80 Bot 0.9.0 O fe
ODTP 0p 0: shod 0,100 0.00 PO) 0 90 Ort 6.4 on Os 4 06 (Mo) Gn. 1% OL 2
OPUS OPO Bao Op. pio Ml) 0 Mor ORO 1) or Oe 12 0 [Moe Te 2! OUR ¢
PACC ono shod OF On O42 FOO Hoo ONG I OxO» 0.9 CMOS 02.0 9 or?
PACH OO Modo); O00.) 2 FOlLO “oo 0.10 1b 05,02 6.40 [00.0.0 BoE 2
PACM O00 MILO OF en Ol MOT OOO 69 Oo 1 LollPox oF oF 0 | 3
PELW Ob OD Modo oe Oyo FOO GW Ten 60 oP eo. Ge OF Oo) MS2
PFLB ChE 03, HOF OFM Cp 0) oO MONT 0) 00 0 NO Ge Cie OF HO [010.0 oF 12 0 j3
DIGN Oprop. 2 hodlpostals GOI Ges PHO Os O84 Culp OnOs O° OLS

03/27/% Appendix 5.- Animal Frequency by Year Page 11

1990-1994
Dolphin ID 90 91 92 93 94 total
PMCH GnOy Mah Oo Oy 2u0h H.% Cool Cuong bol Ooont “0.5 4
PMID O10, tiOh Op 0, OVO OF OHdn0t Onoda vod ovonl o 9 2
PNTC On0r- O10, 040n O40) & O) Codh ogont vo] ovone oft
PNTP 0105 2500 yOu V GON Oy 00040 hogan sof olgns 0 5
POT2 000g 140 ly Ou 0'o O aol 09 05.0 40k OGO NO VO) Odour Of 2
POTP On y 2 001s 0 10.6 2eOl On On Nels Ogonay oo | Oo vous 0 J13
PRLN 0 60 2°00 IO 60.4 1 D0 On ONT O01 od yO w3) 10 O10 2 0. fs
PRNK 0 (0 0 010. 90 40! HO lnOy 004) 01h 0 oO 2500 fo Woo 0 6
PRNU 04.0) 4 0 AO bp0 10) gO: GON 0% OPT NOt) oO oO. col do | O eo 1H 20 J
PTBK O10 °n 320 110 Wiel: OloOy Onl olro (0 lobo om ofs
PTCS 0 0 p 2 Ol 0.0 501 Ol 04 O00 loo so. nolso he ©. Of 2
PTMS 0.0 ¢O O10. oO pty OlO4 001 0l)0 0 aloho om 0 93
RCHS 00 40 Ol @ 0 60: ©110'1 001.0150 10 le leo co a 0 2
RFMB 610 9 O10 O rOlm vO wll © .0j@]s0 © a O44
RHNO 06 pti Glo Oo 101 o10 diol w © a! olvo © 0 @ § 4
RLBK 00 61, 010 O11 010.0 00h @ Biolie o 3 O88
RMRL 00 62-01 oO 0 010l0 40 O1Ol.o @ 110110 0 0-0 § 3
RNTR 6.0 pO Clo 0 H1010 60 01010 @ wlolco oo oO § 1
ROMN 00 s0lOlO O wn iol0 90 OL0l 0-0 0 lolno 0 yO 2
RORQ 00 ~0i0) @ 0 2i0l0 von 1016 0 OG) Oo 2 0 55
RP14 dO. 1019010 oO O10! or jolo @ 0 jo| oo 0 9
RPPL 00 .o;olo o 1;010 0 OOo1o 0 O}o|,0 o o Of 1
RPPR 00 S101 0 9 2 1OlO 0 OJOlo Oo 5 jG) oe oO fe
RTLS 60 210) 0 0 1:01 0° (0 OjOl oO Oo jolie Goo fs
RTLV 0 01610 a 1401-0 © © 1Olo oO © Jolo oO HO f2
RTPM 0, Oat o 0 o 101 0 © O Jol Oo Oo Hh to} o oO a0 ff 3
RY34 OO. 41010 oO 3 01-0 © 2 fol o 0) 3: io3| o oF 1 Of 48
SADB 0, Or 0 JO) O%) 0 01% © O Dt Oo O& + iol O oF O f 2

SBBS On 0, 1 01.0, 0, 8 Of O 0 O DAG o%. OF ‘Oc O-on oy O | 4

03/27/% Appendix 5.- Animal Frequency by Year Page 12

1990-1994
Dolphin ID 90 91 92 93 94 total
SBKB Of0 20 NEO! GO yy 2 qOiligO: WOO HOO Wore TS OL OO 2-KO 7
SBLS 0: 40 Be Ouro [po cog wOlKO Hojp0 HONy'o wo AT Koy Og0 yo 40 2
SBMS 0:40. 10) igo G0 wie ORO. GF Om: GON.O.g0 AI) Hols Op0 B HO G7
SBSR 0. 10. 1b CO: 6 O-g OFC HOKO BOIL AO ot Work e0 4040 2
SBIM 0.80: OMG 6D: HO. GO OPO MOM LOY O GO H2 4 Oh OO sO yO 4p 2
SCDS O90 wr OMG) lO GOW, OG CON Ogi (Oj O 60-43 G0) Ov0 @ gO Fe
SCOO OBO Om OHO GO G1 gOlyO ¢ Og GOjl, Oo go 40-40 |, 04040 40 Gt
SCPC Ono Ore IFO €O HO MOL 9 OO {Oil O pO 1 Oh, Oo gogo | A
SCPD OO 20 0 lpO GO 60 g ONPO OOO GOI oO gO yt SO, 0 0 1 », 0 if 2
SCRH ap hy O90) [AO WO 0g CONGO g Oy 0 HOily 10 gO gt giOyl O_O gd» 0 of ©
SCSC O-dOnp OM Ol) O PO Yo goillnO 4 Ops? YOMyO yO W2 gop |yoeo wt yO PS
SCST O40 ew Sela koa 6 OKO § Om? GOUWe gOi9, 2:8 OO g 0 tg ONS
SE2C 0 G0. OO 10 0 a0: g OAD G00 goth oO Ko gon OF 0n 0 3-40 1S
SEAC 0: 10 Gi Ogio fp O HOBO g OHO @ Opt Osho BO. HO y 0b [h10 pO.yo ap 0 ae
SEAL 0.40: B10 HO. tp OilNO | 02 HOI, 0. gO HO KOjiOg. 0-43 BOM Y
SEMA C404 Ugo; yO HO Wy. 0a OBO H Opt BOMLIO HO HO Wop Ogio qi yp, 0 of
SEMC Oo. OMolkio Co go'e Oleo vO” KOMt0>40 40 LoOpkiOogo gi o OZ
SFPN Opp OG O1h0 yo Hog OHO HUMO KOLO go GOR OOO 4s pou
SH06 Odo. 08 Ob Go HO g.0le0 Hy 04-1 JOth,o go Ri HOO e0 Gi g_ouls
SH2¢ 00 Cgc Ol lbw %0 1.0.9 ONTO 7 01-0 GO} 0 GO,4 & OO NO 44 40 UNS
SHC1 OO) SHO A0 wo y OlyO) 040 POfy 10 GO 4,0 WOE OM O 90 4, OOF
SHO? 0 RO Or OgCOLIAO: QO dOH OilHO y OqeO HOP 10 FO LS pOrORO 45 RO CIBC
SHDE 0 HO Om Oly lO 70. ity OO @ yO HOMO £0: HO y Onl) 10 pO go yO aha
SHFL 0: (90'eas OM ONE 10 40 pio: gf Oil fO |p OiyiO HOMO .0.g.0 4, 04), 10-pO, G2 yO. 2
SHLO OO <p 3 HOhlsfoigso nya. me OVO QO? BOM OK 0) nS 4s Oj [0p 0 p5-a, 0 Vf Ms
SHSC © 0 ey SOM alo OW de Orllso 1p, OBO: 1,0 yh y:0: 4.0/4, 08], 50 #0 40,0
SHSP CoO sy 3h Obl ONO 1g ONGO 00 GOTO a0 H.4 » Ol 0'4 O14 9 On
SHTS ONO og On ONORHO M2 2 OO g OO KONO 401.04 OF] 10y O01 40002

03/27/96 Appendix 5.- Animal Frequency by Year Page
1990-1994

Dolphin ID 90 91 92 93 94 total
SILM O:.0..000, Oto how oo oF a oN obo Bor oF Lot ots op fh 2
SIMN 0.10508 010.0 Lo Bot ols) oF ON 0Nt oop 320 OF ft Of oF Mt G02 M7
SKAD 0.10208 0.18 0-10 0.0% o'l20r 2.08.0 NON 0 Ly 42) oF) oF OC Cor OO? fh 2
SKTH O40 Bal e0. Po fo.) ot Oo) OPtr Koro lo Pit oF | 08 oF ae WO IE
SLIT O02 Te 0LIe. 0. 201,40. 0 Gt OOM OMONIe oo Va! or |} ole: to! GO) Tt
SLMS 01,20.1.0. 000.80 02) Oe OF Om 2k UMM oto: Borat it 00.0) te Vor 7
SLST O.s0. 080) 0.0. Ua Reon Monitor or Oa) 0 Gt |b oto’ @ 0 ON 9
SMCO OAC 0 IR0 Fo. BS OP Oro Out oo a: Poth ob of 00° fF 5
SMFT O,./0,.8 1 oP .o fo Go ONO: 9 oto Font oOo: Ca wolp oto) or OO f} 2
SMHS 6. fo, 2 07 oo to Bo. GPa © o) 1 Son oho! ii hol on 0 @ Or f2
SMRF G0. 52° oo So Bo ooo +00 3 Hol OGo G1: Vol ol g G OG hs
SNRM OO cde OL 0 20 G0, Oo - ON NO OO fo Vell ot @ a Oo 95
SNST 0.20. 0006.2 oo! Of Yo gg U2 oh qe @ Ge Fs
SOAR 0.10.2 t,o. Yo So ols o. Fo 1 ou og Ye lot oF o 2 oo (4
SOAS 000 Ooo. 20! alo = 01 Fo oto Ht Vol ol ¢ oye § 2
SOLN 00, 6! oo Yoo foo! oo Vol oto OF bored @ tO '§ 3
SOTT O00 62.0.[ 0 50 Me Lolo § On 3 "Ol of) vol evo O FO. 9 te
SPTP 0.20.8 22 ooo CoB Olio Yo" OOM Gg So DOUG Ooo 1 UO f2
SQFC One tee OL 6.16 2 s0l"0, (69 0 BORG 06 So AO Ooo Oho f'4
SQFL 620,913.00 $0 Bolo oa ! oF 1 PON OO M7 Yo Ono @ 10 53
SQFY CiOenOs OO 0. UO OO 2 0 1 POU o Oo tal ot) GL Oo 80. § 2
SQGL 00.52.5050. 0.1 Ole 0" 0 Bolg fo Ko Yoho 6 OOO § 3
SQUA O20 whol Oe0 0.20150 ¥ oo Yoyo to 51 Foe 0 6 6.00 5 2
STBK 0:40. 0h 0 uo. aol 4 oir ort 9 Bo. Uo) of oO WO, § 5
STIM 0.0.05. ule 0.50, 0 Vol 0 0) 2 Dolo to to Vollio* 0 & 0 8s
STPN O09 2.000. Yo. Yo Noo Oo Son? Go: io D0: Vorll ot ® 6 Wo I 2
STWC O10; Noe. 0.12 0. 80" 26.9 Ol 0 9 OY 1 Volvo fo, 00. Voll oro @ OO 1p 1

03/27/96 Appendix 5.- Animal Frequency by Year Page 14

1990-1994
Dolphin ID 90 91 G2 93 94 total
SWAS OM 0p. Ok On One Ou Oy 0% OF 09) 0 FO 0) ty Ole Oy Os 6/0 I, S
TAAS GUO OF OO COR ONO) 0) OD Ol Oho Om OE OF op y-0" It
TAGC OVC em th Ors ONO 2a OOO. ONL ON O02 Oe On ONsi-n O: IS
TAGL OHO eNO POM Ol Pe. Ol, On ION 1% OO On 2ey Olkor Oral» OIL 7
TALB Os ORC LO gO On OURO Os VEO O80 pte Cleon rad) y. OP 2
TALK OO on O MOO a0 OIOn, O00, 01 OO nO pn Ol) Ol sO eI yy O° Le
TAPR CROs AD OIL09. 02, ORO ION 0) (01.0) 05.0 4:0 OI. 0), 0 A046 0 ft
TATT OREO G24 Oc17 © PO Om OO Ob 0 e080 0 p00 [e080 6080" Ir 2
TBLS Oro 16 OOO og 2y OU) Oh.2U. 00k 0 10 e [1.0% 0 porn O° ELS
TBMM OFLO'd) OFC OO OM OEO SO) OMDON, OF Ory Oln 0 [L.oF vo gike 0 fp?
TBMP HuOw te OO COR OD Olh Or OF THO) OF 0 43h Olt On 0 ~0%g-0* IES
TBNN OO 08 OO nO 50% Oly Orr 04 10 OFF 04,0502 p Olt) 0% 0 fa” ge OLN?
TBTN OFO 2m OO NOY) Oily e040 OF} 0%, Og. 2 00) 0: 10; 627 5 0 20
TBTS G nOn6 4 0 W004 3'q Ol) 0%) Oh OT 016 0 n.0'e. 011) 00 0 Or 0) IRS
TDLB Ore 4 On GO yon Os OlLO'e Of 1 0M Or 0) te 0h On i0% 00" Ne2
TDTN O40: 20h) 61.0 BO oO O1h0% Of 2-H 011) 07.054 0g Oh 04 0.10" 4 02 RZ
TFLN O70) G3 Och, 0 0%) Oy OU Ory Oly 0 Oy 0 Oh ye Ol Of OP 10) 5.0" fis
THUV O10" te Sh GN 0 0! 2) ONO 4.000 OIE 0/50 gi 0% 4.0) [h 0m Or ooeO” IZ
TINW 040" 6-16 ONL0. 90g Ou OO" Of 0 WOT) 01):075 0m ON ly OD, 0; oo I?
TLC O10 06 OIA.) oO) nO yp OO yw On OF ONE Oyo ya! pO 04.0. at ORE
TLCM Oo Obi lk OO 6.09 OlhO.n Oy 0 OU OO" 29) 0) Or, Oly g OR
TLLA OOis 0.0 OO. 0. ONL OC Ol 14/071) OO) 4:24, OF lk Org 0" 40! a0 ES
TLLC OL OL OM 0) POF GO" GONE ONKO'S 01, O09) -0'7-0' 42) OF) On 0" 10; 9 0" I 2
TMBC O40 OX OIRO Ot 6376 ONGO' Oo Oh 7 AON OO 46 o OF [On 0 ao 0 17
TMBK 0.0 OL Oh 0 <0 A6'm 0140 s Oh 0 HO}ID.0, 0 jt Oh OG: O 2 40° HR 3
TMBL 0. 10".6.1'4. O01. 40 435 ONO! 10%, 7 pOlh o'LWO not (Ol l.0s.0 a oO Its
TMDC O10. OO l.Or B07 a4! e.0Nl,0" 10. 0 90RD. 080 44 0) [0% 0.3" gO) 1
TMPN O10 9 3 On) 20..ot BONGO HOUT PONL 6 do.20t oud a: oO fe
TMS( OO kon olive co 62° 0ld poo WO) G gO 0 eoilh oie o.10 J 7

03/27/96 Appendix 5.- Animal Frequency by Year Page 15

1990-1994
Dolphin ID 90 91 92 93 94 total
TMWC 0.40% Oro otod 00 O10? OOO rog OF 12 Od ton OMmOn Oath
TMWV 000 Fo OPi0800 09 O00 OLS O09 OW 3 dil (oroto On| ke
TNLS O00 4 dit06 00 16-0P0F ON TR OOs ON GD Ci) Or Otto 005 F6
TNSB oso 2% OPios 00 08 Olt0s- 05 09 OM 08 0. 02 of (of vin OUF 2
TNSS odo) oo 070009 C10) O08 Oboe Ow 1? op oF 001 00% F2
TOHA Osod! on opie ot 16 ONO OOF OP OR Ow oO Os) 00.0005 0
TOLD otod uF dibiove Gob HINOF UFO CONMOs ob0n Oi On: 0: 2b 0 1 2
TPCC O00 OF Of joo O8 CIMOS 0% 28 Oh 00 0.01 D Or) (02 0 ain Ov %
TPLN ovo 04 OOD OD Ob TOL OKOr-OFi 04 0.20 Or ioy O20 Cul
TPLO 6-100 39 ClNOMOd 21 ClO OM2 TOON OW2 1 Of lor.o tao] 3
TPMC oto) 04 Gioo-0 30 Ol-0d 0% 3 9 OFI9 0 O02) Off Oh Oa ONE I
TPMI Guo Te oftoto Osh O09 0h 3 OM od Obs » ON. OF OMta 20 O'tf Hs
TPNH foe 18 oDorotol OOF 0% 25.008 0:1 -0O Pos) onan O95 7
TPTS ovo 24. dkotoNoh OFOe 08 0 OM oF orto! op low O@o 09 f2
TRIP 6fouw of OMotol 14 Oltos Oh2 OOP OTD Gp ioe oon OOPS
TRLI oon! of oWiolo210 OO. oF OPFOR Oo B20 oO piom aa “Onde
TRTH ovo of diet ours OHO! 000M O4 000 » OLfion oa mOU
TRTP auton of ailsoto 21 O14O# 0% 0.7 ONlio < ory OKlor 0.18 OUT
TRTR oe. 208 0 Pa 0.008 -olow 0% OP 0M oF 00-4 okion ore. «OUT 2
TS1C oo.) oF oor octo# OO OF OOOH 98 O80 0 or lsfot one 0 2 f2
TSC1 oto) 7) ole to 097 OMOY 0% 0} OM ORO e700 Oboe 0 0 EE
TSEC ocfon oo ako so POF OOd 08 270080. 00d OL)0d.0 coin 02) 72
TSCS Oyoct 24 ONOKO. Jas OO s 04 OVO 080.021 Oo fijoe ote 00.029
TSLD 0501909 OO MOUNT» ONO. 70% POS O £0 AT DOr PiOt Ota Ou] 2
TSMA 6. fo.0 18 ohontd 0.0 oo! oy 2 DOWo Oo 2 For biON 0. 190 Ouf fe
TSMC 0.06 20-ollGo A080 VOLO F001 COI o-.00 Wolo Oo CNON IES
TSMD OO 70 OLL40: F094 DONO ONT HORS o's DOOR 0 Ua nog) i!
TSMS 0:0) 0-00-0100. 10G002 0140 | 00-0 MON Otos Solos ono avon 3

TSNN OO OC OL/F0 10. Ko. 10THOH 0 OF OIRO Co snLeso Oe ONG MOVE M

03/27/96 Appendix 5.- Animal Frequency by Year Page 16

1990-1994
Dolphin ID 90 91 92 93 94 total
TTBK O70 e200] 20) (0) ate 0: Om ORL BOI WoO) 10,50 [\N0) <0. Oe 0,9
TTIM OiLOPNOR Olle (02850) 0 10 Ole ROO, Ona0 we OOO cr Or sr2
TTST QuOM ON OL nO, 10h coup Ole OO 10) HON! MO) OR LO. | Ono. 2. 0) 3
TTWS Od. wO 2 Os somo! v0, F:0/0- O10" FOR) fo Oma Lon| so Osa 0. 2
TWPF OO) BO m0) 90 10s, oO 10s 10. sf FOO FOUR Ono 0-0: 0" Fis
TWsc OO) 2 OOO) Or Ol ONO 0. FO (0 NO nO soul vod 00) 08 52
TWSP On eoe ONO On 40 HONS ONO 0 PON iO co” 3) Po [sono i ONS
UBLV GeeoreOreO) (20. (Or, jis 7 Ol 70? 10 40, Fort 0! 00 ONO! 0.0, 10° va
UBPN OF.0) 2" O10). On Be eOll 20 FOr 0 ONO! Or 92y pou|"omon 2; fons, s
UDSP OnGoy 0. LOM Oy 0k ON ON 20) 10 0° F010: 1) ab 20: [20 O- Og-2
ULSM OpaO KOMVON LO, Low OL ONO) LOL Os 2ONL O10) 90,90) [ S04 Op: ar, 0 3
UPS2 OL Ow 2p MOtlNO:-20) eaewOll 0? fous 10M Oo: “OL 40, Ropll (0% toy ty. OF PRS
USBK TOL pal SOMO. sOe) to LOU ORION 25 ION Or 10; Toul! sr Os Ope Of es
USMS Cite 0 OO. 0," ae NOLL (0) FOr On OA 0.0; Oh 207 | FO" Oy tee 2
USMV Oni0y 2 S04! 0) 04,08 401 0) GO 08 (071 “Oa; 40; op] 90) 0K ae ONES
UTCC OL Oe 40 SOA FO) (0) 20? 20) xO) JOP Ty Ojo) (00), 10)|/407, 0) 28 LONE S
UTLC OhOr wOreOe120. O. Or Oil: 10% 2 {041-0 0) 45¢ 40") 1004, SON
UTLD OraUy On ONO 0) For (ONO. Ove 2t 04s Ono 20" mono 2 Online
UTLS GeO ste Onl OnmO mr Or Ole Oe OF alae Onl) 010.93: 4 10°||,10) 00 eater ORNS
UTRS Um On OMOOl On 0y Ol Omx0" 2) Olson 0; 51 Obl ue Oat. JO
UWMN OeiOwe ade COnlOL 10) ONO Oke OF TeaONl ON ONLY ul, Orne PORES
VAMP O20, 36012000, 410. 01/0, 0 70 O10 100) 0) | ooo tno [es
VARS MOF sc OMOM Os 40> =e O I tOU0. 10: AOPL' “0: 04X08 Or OL 0" Oye Ont
VAVM Oe eal LOsO. NO! 0ge Oil, 30. BeOS ON FO" One On, LOn IO 0, 07 2 One
VCUC 0 Oe OO) OL Ose Om ONO 00. UeNor Om ane OalkeOe 0.0 OME et
VCUT OF SO et ORO: SOR . OM UMN Oia OOOO Onemae (ONO. 10rd OME 4
VNAB OO oO SUMO HOe MMO On ws Ork Low Oy OF ORO, OsnO» Oat
VNKS OF Og 2500.0 SOOO Oc VON oo Or Tol) 0 Not at 0S es
VOLT (enO Se ln On WO. cOs 0! LO OeeO. KOE Onfion 0.208 oN tow a." Osh 4

03/27/96 Appendix 5.- Animal Frequency by Year Page 17

1990-1994
Dolphin ID 90 91 92 93 94 total
VOss 0. 0 20) O} ©, 0),%0,) 10), 0 host000'I\ 10. 0) dO hon Oo Fa Ns
WAVY 0) 0 £21 0) Oy 0), O40 0 POLO 01 oy OF f J .0)Fo0 0) Oo Ps
WBCC 0) 0 804 0), 0) Oy BAi0l fo MOTO oy Oy) 0) © \ion 01.0.8 ONS
WBMA 6, 0 Dil Oh 0, 0) BIOL, CMO IE Gh Gn Ox) 0 [Mon G55 Oat
WBMC 0, © s804 O10 0) WAN, OMPOMO NON Goo. 2 0 |0) OF Se oe
WHMR 6, 0 P11 ol, 0, 0; OPO) @ WO, OOO. 0.0 20 | Foy OL Oe ot
WHTP 0: O p51) Ol Oy O, OF Ol, 0 0, OM ONO OG 2.0) | Fon 0:02 OF
WING OO BIOL O, 6, OV Oh ONO; ON Ol OL OF Ry Of O. Oh te OS
WIZA GO 04 di 0 Oy O Ol 0 sete tO Oy Os Toto son oO 38 OS
WIZC Os O WI Oh Gob» Oo Ol 0 pWe OO 0s Oy 6.1 0' | Om Oy 3) McOp ps3
YAFT OO p2AGk Oy Oy OGG) OO) By 100. Oy Del) On Ok a Oh AS
YALN Oy © 0 Oh OF OF 0. AO), @ nO, O10), 05 Oe TANG) On On Bre Oy es
YAPL GF ONO On Or B'Oh Oy l05°2, 10. Oe. Oy Tato |, Oe OF OFg OF es
YAWT OOF OS Oy Oy Tah O 410) 2p Ill GC, Oy 2 tOMlOs On nO IES
ZAMS Oh, OF . O10, 0, GO, DO) Oy Oy O_O, Oy On Onto) |, 0), Chg OZ
ZENN OO, OLOl, , OF, OelOl 6-0) Or, O.. Oy CLIO) 0» OF Se OES