**Final Study Plan for**

**Estimating the Size of the Pacific Walrus Population**

![](media/image1.jpeg){width="5.75in" height="3.21875in"}

**March 2006**

**Marine Mammals Management, U.S. Fish and Wildlife Service**

**Alaska Science Center, U.S. Geological Survey**

**GiproRybFlot, Research and Engineering Institute for the Development
and Operation of Fisheries**

**ChukotTINRO, Pacific Research Institute of Fisheries and
Oceanography**

**Summary**

A critical requirement for conservation and management of the Pacific
walrus (*Odobenus rosmarus divergens*) is to estimate abundance with
sufficient precision to track population trends. The Marine Mammals
Management office of the U.S. Fish and Wildlife Service, in cooperation
with the Alaska Science Center of the U.S. Geological Survey, the
Chukotka branch of TINRO (Pacific Research Institute of Fisheries and
Oceanography, Russia), and GiproRybFlot (Research and Engineering
Institute for the Development and Operation of the Fisheries, Russia),
will estimate the size of the Pacific walrus population with an infrared
(thermal) scanner survey and associated aerial photography and satellite
telemetry. The survey will be done in U.S. and Russian waters in the
spring, when the walrus population is distributed near the southern edge
of the Bering Sea ice pack.

The Bering Sea will be partitioned into survey blocks, and a systematic
sample of transects within each block will be sampled with airborne
thermal scanners using standard strip-transect survey methodology.
Thermal signature intensities will be recorded for each detected walrus
group, and a sample of the detected groups will be aerially photographed
with digital cameras. Counts of walruses in photographed groups will be
used to model the relationship between the amount of heat measured by
the thermal scanner (thermal signature) and the number of walruses in
the same group. Only walruses that are hauled out on the pack ice are
detectable in thermal imagery. Therefore, the population estimate
derived from thermal scanning will be corrected for walruses that are in
the water and unavailable to the thermal scanner. Immediately prior to
the aerial survey, satellite transmitters will be deployed on a
representative sample of walruses distributed across the Bering Sea pack
ice in both the U.S. and Russia. Transmitters will record the proportion
of time each tagged walrus is hauled out on the ice or in the water,
enabling estimation of an in-water correction factor. The final
population estimate will be developed cooperatively by U.S. and Russian
scientists.

**TABLE OF CONTENTS**

Summary i

List of Figures 3

I. Introduction and Background 4

II\. Goal and Objectives 7

III\. Overall Approach to Population Estimation 8

> A. Study area 8
>
> B. Basic study design 8

IV\. Aerial Survey 8

> A. U.S. approach to thermal imagery 8
>
> A1. Thermal imagery equipment 9
>
> A2. Details: thermal imagery 9
>
> A3. Calculation of thermal index 9
>
> A4. Limitations or unknowns 10
>
> B. U.S. approach to aerial digital photography 10
>
> B1. Digital photography equipment 10
>
> B2. Photography/thermal scanning coordination 10
>
> B3. Details: counting digital photographs 10
>
> C. Russian approach to thermal imagery 11
>
> C1. Thermal imagery equipment 11
>
> C2. Details: thermal imagery 11
>
> C3. Calculation of thermal index 11
>
> C4. Limitations or unknowns 12
>
> D. Russian approach to aerial digital photography 12
>
> D1. Digital photography equipment 12
>
> D2. Details: counting digital photographs 12

V. Group Size Assessment: correcting for walrus groups too small to be
detected 12

VI\. Satellite Radio-Tagging: correcting for walruses in the water 13

> A. Tagging equipment 13
>
> B. Details: tagging 14
>
> C. Aircraft/ship coordination 15

VII\. Timing of Survey Efforts 17

**TABLE OF CONTENTS, cont.**

VIII\. Survey Design and Statistical Analysis 18

A. Survey transect design 18

B. Statistical methods 18

> B1. Relating thermal signature intensity to group size 18
>
> B2. Estimating proportion hauled out 19
>
> B3. Estimating totals for surveyed transects 19
>
> B4. Estimating totals for blocks and the population 19
>
> B5. Accounting for walruses on ice in groups too small to be detected
> 20
>
> B6. Estimating variance 21

IX\. Statistical Assumptions 22

Literature Cited 24

Appendix I List of statistical notation 41

Appendix II List of cooperators by agency 43

**LIST OF FIGURES**

**Figure Number Page**

1 Approximate ice coverage in the Bering Sea in late spring 27

2 Example of thermal image and matching digital photo 28

3 Example of frequency histogram of AMS thermal imagery 29

4 Example walrus heat/number regression 30

5 Walrus haul-out chronology data from 2004 31

6 Specifications of the icebreaker *Magadan* 32

7 Specifications of the *Stimson* 33

8 Specifications of the walrus satellite tag 34

9 The three study areas where tagging of walruses will take place 35

10 Example of aerial reconnaissance track lines 36

11 Example of ice conditions during walrus tagging from skiffs 37

12 Temperature and wind chill analysis 38

13 Chronological order of the tagging and aerial survey missions 39

14 Example of transect and survey block layout 40

**I. Introduction and background**

The Pacific walrus (*Odobenus rosmarus divergens*) is a sea
ice-dependent pinniped that faces an uncertain future if the arctic pack
ice continues to decrease in both extent and duration. Pacific walruses
are an important subsistence and economic resource, with total harvests
in the U.S. and Russia estimated at about 6,000 animals per year (U.S.
Fish and Wildlife Service 2001). The current size and trend of the
Pacific walrus population is unknown, and recent changes in the Bering
Sea ecosystem (e.g., Hunt and Stabeno 2000) make it more important than
ever that we develop a precise population estimate for monitoring and
managing this species. A precise population estimate of Pacific walrus
is critical for successfully fulfilling the U.S. Fish and Wildlife
Service's mandate under the Marine Mammal Protection Act for
conservation and management of this species. The Marine Mammal
Protection Act recognizes the important role that marine mammals play in
marine ecosystems, and directs that marine mammal species, including
Pacific walruses, are maintained at an "optimum sustainable population."

Pacific walrus inhabit the continental shelf waters of the Bering and
Chukchi seas, and occasionally move into the eastern East Siberian Sea
and the western Beaufort Sea. In late winter and early spring, they are
found in the Bering Sea where open leads, polynyas, or thin ice occur
(Fay et al. 1984). There are three regions where walruses are
concentrated at this time of year (U.S. Fish and Wildlife Service
unpublished data, GiproRybFlot unpublished data). One region ranges from
northwestern Bristol Bay to south of Nunivak Island. A second region is
found to the southwest of St. Lawrence Island, and a third region is
found in Russian waters of the Gulf of Anadyr. Preliminary genetic
analyses provide no evidence of separate stocks within the Pacific
walrus, but the need for further genetic studies is recognized (Scribner
et al. 1997).

Based on large, sustained harvests in the 18th and 19th centuries, Fay
(1982) speculated that the pre-exploitation population was represented
by a minimum of 200,000 animals. Since that time, population size is
believed to have fluctuated markedly in response to varying levels of
human exploitation (Fay et al. 1989). Large-scale commercial harvests
reduced the population to an estimated 50,000-100,000 animals in the
mid-1950s (Fay et al. 1997). The population is believed to have
increased rapidly in size during the 1960s and 1970s in response to
reductions in hunting pressure (Fay et al. 1989). Between 1975 and 1990,
aerial surveys were carried out by the United States and the former
Soviet Union at five year intervals, producing minimum population
estimates ranging from 201,039 to 234,020 animals. The estimates
generated from these surveys are considered conservative population
estimates and are not useful for detecting trends (Hills and Gilbert
1994, Gilbert et al. 1992). Efforts to survey the Pacific walrus
population were suspended after 1990 due to unresolved problems with
survey methods that produced population estimates with unknown bias and
unacceptably large confidence intervals for tracking population trends
(Gilbert et al. 1992, Gilbert 1999).

In March 2000, the U.S. Fish and Wildlife Service (USFWS) and U.S.
Geological Survey (USGS) hosted a workshop on walrus survey methods
(Garlich-Miller and Jay 2000). Workshop participants reviewed past
efforts to survey the Pacific walrus population and discussed various
approaches to estimating population size and trend. The amount of survey
effort required to achieve a population estimate with an acceptably
small variance to track trends (CV ≤ 0.3) using the existing methodology
was prohibitive. Workshop participants recommended investing in research
on walrus distribution and haul-out patterns, and exploring new survey
tools, including remote sensing systems and development of satellite
transmitters, prior to conducting another aerial survey.

A grant from the National Aeronautics and Space Administration (NASA) in
2002 allowed the USFWS Marine Mammals Management office to initiate a
study on remote sensing applications in Alaska. This study demonstrated
the feasibility of using airborne thermal imagery to detect walrus
groups as they rest on the pack ice in the Bering Sea. Over a two-week
study period in April 2002, Marine Mammals Management staff collected
thermal imagery and matching aerial digital photography of more than 30
walrus groups ranging in size from 1 to 256 animals. In order to
determine the limits of this technique, thermal imagery was collected at
spatial resolutions ranging from 1-4 meters per pixel. Digital
photographs of a subset of walrus groups were taken concurrently. By
matching photographs with thermal images, a clear relationship was
demonstrated between the number of walruses present in a group and the
amount of heat they produced (Burn et al. in press). This relationship
existed across all spatial resolutions tested, and demonstrated that the
number of walruses present can be estimated using the amount of heat
they produce, or their thermal signatures.

Based on the successful results of the 2002 study, a second pilot survey
was conducted in the area of St. Lawrence Island in the Bering Sea. In
April 2003, nearly 30,000 square kilometers of sea ice habitat were
surveyed -- an area larger than that covered in any previous visual
aerial survey of Pacific walruses. A statistical approach was developed
for estimating the number of walruses present on the sea ice within the
study area (Udevitz 2005). Results from the pilot survey (Udevitz et al.
in prep.) have been used in development of this study plan for a
complete survey of the Pacific walrus population.

Also following the 2000 workshop on walrus survey methods
(Garlich-Miller and Jay 2000), the USGS Alaska Science Center began
developing a system for remotely deploying satellite transmitters on
walruses, eliminating the need for animal capture and making it possible
to deploy a large number of transmitters quickly and safely. In most
previous walrus telemetry studies, walruses were chemically immobilized
while telemetry devices were attached to a tusk. This latter method of
deploying tags is time-consuming and dangerous to the animal because
darted walruses can enter the water and drown while the immobilizing
drug takes effect. This is particularly true when walruses are on ice
floes where they can escape quickly into the water.

In 2004 and 2005, USGS staff conducted field trials on three remotely
deployed tag designs in collaboration with the USFWS and the Greenland
Institute of Natural Resources (Jay et al. in press). The satellite tags
were deployed with crossbows and air guns, and were fitted with
conductivity sensors that continuously recorded wet and dry intervals,
which corresponded to periods when the animal was in seawater or hauled
out. These data can be used to derive an estimate of the proportion of
walruses that are hauled out on sea ice during a given time period. Data
from satellite tags ensure that the estimate of walrus numbers derived
from thermal scanning of the pack ice can be corrected for walruses that
are in the water and unavailable for detection by the scanner. The
attachment method for tags and data collection software were
specifically developed for use in a spring survey of the Pacific walrus
population.

**II. Goal and objectives**

**Goal: Estimate the size of the Pacific walrus population with
acceptable precision**

**Objectives:**

\(1\) Survey pack ice in the Bering Sea in spring with thermal scanners
to detect groups of walruses hauled out on ice and measure their thermal
signatures

\(2\) Collect high-resolution digital photographs of a sample of the
thermally detected walrus groups to determine the relationship between
thermal signatures and the number of walruses in a group

\(3\) Estimate the number of walruses hauled out on ice

\(4\) Deploy satellite radio tags on a representative sample of walruses
in the Bering Sea to estimate the proportion of time that walruses were
in the water and unavailable to be detected by the thermal scanners

\(5\) Use haulout data from tagged walruses to correct the estimate of
the number of walruses hauled out on ice for the proportion of walruses
that were in the water and undetected during thermal scanner surveys

\(6\) Estimate total size of the Pacific walrus population with
confidence intervals

**III. Overall approach to population estimation**

**A. Study area**

The survey will cover the extent of the pack ice in the Bering Sea,
where the sea floor depth is less than 200 m. Walruses usually feed at
depths of 100 m or less (Fay 1982, Fay and Burns 1988), so under this
criterion all potential spring walrus habitat will be included in the
survey. Ice coverage varies among years, but in U.S. waters ice
generally extends to the southeast into Bristol Bay and to the south of
St. Lawrence Island (Figure 1). In Russia, ice covers the Gulf of Anadyr
and may extend along the shore as far south as Karaginskiy Island
(Figure 1).

Satellite images of ice coverage in 2005 show that open water existed
along the Chukchi Sea coast in the area of Point Hope. If this occurs
again in 2006, our study area will be expanded to include areas of open
water that could be walrus habitat. The approximate area to be surveyed
ranges among years from 171,000 to 237,000 km^2^ in Russia and from
130,000 to 507,000 km^2^ in the U.S.

**B. Basic study design**

The range of the Pacific walrus in spring in both the U.S. and Russia
will be surveyed, and American and Russian scientific crews will survey
their respective sides. The Bering Sea will be partitioned into survey
blocks of a size that can be surveyed within a single day. A systematic
sample of transects within each block will be surveyed with airborne
thermal scanners using standard strip-transect survey methodology. The
amount of heat produced, or thermal signature, will be recorded for each
walrus group that is detected by a thermal scanner. A sample of the
detected groups will be aerially photographed with digital cameras.
Counts of walruses in photographed groups will be used to model a
relationship between thermal signatures and the number of walruses in a
group. Only walruses that are hauled out on the pack ice are detectable
in thermal imagery. Therefore, the population estimate derived from
thermal scanning will be corrected for walruses that are in the water
and unavailable to the thermal scanners. Immediately prior to the aerial
surveys, satellite radio transmitters will be deployed on a
representative sample of walruses distributed across the Bering Sea pack
ice in both the U.S. and Russia. Transmitters will record the proportion
of time each tagged walrus is hauled out on the ice or in the water,
allowing estimation of a correction factor for walruses in the water.
The final population estimate will be developed cooperatively by U.S.
and Russian scientists.

**IV. Aerial surveys**

For surveys in both the U.S. and Russia, aerial surveys will be
comprised of two major components, a thermal scanner survey and digital
aerial photography. Differences in available equipment necessitate that
data collection methods will differ between the U.S. and Russia.

**A. U.S. approach: thermal imagery**

Thermal (infrared) imagery will be the primary data collection method.
Walruses are generally warmer than the background environment of ice and
snow, and groups of walruses hauled out on ice are therefore detectable
with thermal imagery (Figure 2). Walruses in the water cannot be
detected. A systematic sample of strip transects will be surveyed with
the scanner in each survey block. The amount of heat, or thermal
signature, of each detected group will be recorded.

**A1. Thermal imagery equipment.** The remote sensing system is a
Daedelus Airborne Multispectral Scanner (AMS), built by Argon ST of Ann
Arbor, Michigan. The system has a 0.625 milliradian instantaneous field
of view (IFOV), and collects imagery across a sensor array 3,000 pixels
wide. The AMS system records a thermal infrared channel (8.5 -- 12.5 µm)
with 12-bit radiometric resolution. Scanner data will be recorded on
removable hard drives and archived on DVDs.

An Applanix unit will be used to correct thermal imagery for distortion
resulting from movement (pitch, yaw, and roll) of the aircraft. Movement
by the aircraft on one or more of its axes results in duplicate or
dropped scan lines, the measurements of scanned surface areas below the
aircraft. If not corrected for in the data set, these excess or dropped
measurements would distort in two dimensions the shape and size of
features such as walrus groups, increasing the variability in the
thermal signature/group size relationship and ultimately, in the overall
estimate of walrus abundance. Addition of the Applanix unit will
increase precision of the abundance estimate. The Applanix unit will
also geo-reference the thermal images.

Thermal imagery will be collected from an Aero Commander 690B turbine
engine aircraft. The Aero Commander is a twin-engine craft with high
wings and bubble windows that allow lateral and downward visibility on
both sides. The AMS control panel will be mounted within the cabin of
the aircraft, with the scan head in the tail section.

**A2. Details: thermal imagery.** Thermal imagery data will be collected
as the aircraft flies along transect lines within a survey block.
Spatial resolution of the AMS system varies linearly with the altitude
of the aircraft. Surveys will be conducted at 6,400 m (21,000 ft) Above
Ground Level (AGL), yielding a resolution of 4 m and a 12 km wide survey
swath (strip width) along each transect. A thermal signature will be
recorded for each walrus group that is detected within the 12-km wide
scanned strip.

**A3. Calculation of thermal index.** To determine the threshold
temperature value between walrus and the background environment, a
frequency histogram of temperature values in the entire image will be
examined. Within each image, the point at which the histogram rapidly
decreases from thousands of pixels at each value to fewer than ten
pixels is identified as the temperature threshold value (Figure 3).

Pixels with temperatures warmer than the threshold value are classified
as having some portion of their area covered by walruses. After
determining the threshold temperature for each image, an index of the
total amount of heat produced by each walrus group will be calculated
as:

$h_{i} = a\ \sum_{}^{}{(t_{ij} - T_{i}})\ $ (1)

where h~i~ is the index for group i, a is the pixel area (m^2^), t~ij~
is the temperature for pixel j of group i, T~i~ is the threshold
temperature for group i, and the summation is over all pixels with
temperature values above the threshold (i.e., pixels with t~ij~ \>
T~i~).

**A4. Limitations and unknowns.** Surveys must be conducted within
weather constraints. Thermal scanning can only take place during periods
of good weather. Skies must be clear, the ambient air temperature must
be above -12º C (10º F), and the wind chill factor must be above -18º C
(0º F).

**B. U.S. approach: aerial digital photography**

A sample of the thermally detected walrus groups on each transect will
also be photographed with low elevation, high resolution digital
photography. Counts of aerially photographed walrus groups will be used
to model the relationship between the amount of heat measured by the
thermal scanner and the number of walruses in a group (Figure 4). A
generalized linear model will be used to estimate this relationship (see
Section VIII B1, Relating thermal signature intensity to group size).
The relationship between walrus thermal signature and group size appears
to vary with weather conditions such as wind and temperature (USFWS
unpublished data), and methods are being developed to address this (see
Section V, Group Size Assessment).

**B1. Digital photography equipment.** The digital camera will be
mounted within the cabin of a second aircraft. The camera is a Nikon D2X
12 megapixel format camera that produces images with dimensions of 4,288
x 2,848 pixels. Digital photographs will be taken using a 200 mm camera
lens from an altitude of about 700 m AGL.

**B2. Photography/thermal scanning coordination.** The photography plane
will follow the general course of the thermal scanning plane, with the
objective of photographing as many walrus groups as possible within the
12 km swath surveyed by the scanner. Effort will be made to photograph
groups on each transect where they occur, so that photographed groups
are representative of the environmental conditions that were encountered
during the survey.

When a walrus group is detected by the thermal scanning plane, observers
will record the group's position and note its general location in
relation to the transect line (e.g., 2 km to the west of the transect).
Observers in the thermal scanning plane will communicate by radio to
notify the photography plane of the detected group and its coordinates.
This protocol was developed and worked well during pilot studies.

**B3. Details: counting digital photographs.** Prior to counting,
photographs of walrus groups will be matched with the corresponding
thermal images of the same group. Locations of walrus groups in each
photograph and in each thermal image can be identified by their GPS
positions and times. Matching of photographs and thermal images will be
done using position, time, and visual inspection of the ice field around
each walrus group, which tends to have unique features that may be used
for orientation.

Thermal images will be used to define walrus groups. A group will be
considered distinct when it is separated from nearby groups by 20 m (5
pixels) or more. The number of walruses in a group will be counted on
all photographs collected within the thermally scanned area. It is
important that groups of walruses in photographs reflect the same groups
that were recorded by the thermal scanner (Figure 4). Therefore, only
walruses that are hauled out completely on an ice floe will be counted.

Walruses will be counted using the software ERDAS Imagine (Leica
Geosystems, Atlanta, Georgia), which summarizes animals that were marked
in each photograph by the user. Walrus groups will be counted three
times by the same observer, and each count will be temporally separated
by at least one day. If the three independent counts differ, a fourth
count will be conducted by a different observer. Two observers will then
compare counts to reconcile differences and reach a "best count" by
consensus.

**C. Russian approach: thermal imagery.**

Thermal (infrared) imagery will be the primary data collection method,
as for the U.S. portion of the survey. A systematic sample of strip
transects will be surveyed with the thermal scanner in each survey
block. The amount of heat, or thermal signature, of each detected group
will be recorded.

**C1. Thermal imagery equipment.** The remote sensing system is a
"Malachite" Airborne Multispectral Scanner (AMS). The system has a 1.5
milliradian instantaneous field of view (IFOV), and collects imagery
across a sensor array 2048 pixels wide. The angle of view is 82 degrees.
When flight altitude is 1500 m, the width of the thermal view band is
2400 m. The Malachite Scanner records a thermal infrared channel (f 8 --
13 µm) with12-bit radiometric resolution. Due to specific features of
the thermal imagery system used by the Russian side (i.e., absence of
absolute temperature referencing), an infrared radiometer will be
installed. It will be used for continuous temperature calibration of the
thermal scanner. Scanner data will be recorded on hard drives.

Thermal imagery will be collected from a turbine engine aircraft, the
L-410. The aerial laboratory is a twin-engine aircraft with high wings
and bubble windows that allow lateral and downward visibility on both
sides.

**C2. Details: thermal imagery**. Thermal imagery data will be collected
as the aircraft flies along transect lines within a survey block.
Spatial resolution of the AMS system varies linearly with the altitude
of the aircraft. Surveys will be conducted at 1,500 m (4,921 ft) Above
Ground Level (AGL). The view band will be 2,400 m with spatial
resolution of 2 m. A thermal signature will be recorded for each walrus
group that is detected within the 2.4 km wide scanned strip.

[]{.mark}

**C3. Calculation of thermal index.** The thermal index will be
calculated by the same method used by the U.S. side (see A3 above).

**С4. Limitations and unknowns.** To correct geometric distortions of
thermal images, an additional digital 35-mm photo camera will be used,
and data on spatial position of the aircraft will be recorded. Thermal
images will then be adjusted by ratio-comparisons with photographs of
the same areas.

**D. Russian approach: aerial digital photography**

Each thermally detected walrus group will be photographed with high
resolution digital photography. Counts of aerially photographed walrus
groups will be used to model the relationship between the amount of heat
measured by the thermal scanner and the number of walruses in a group.

**D1. Digital photography equipment.** Two digital photo cameras will be
mounted within the aircraft cabin. Both are Nikon D1X 6 megapixel format
digital cameras that produce images with dimensions of 3008 х 1960
pixels. Digital photographs will be taken using 210 mm and 35 mm camera
lenses from an altitude of about 1500 m AGL. The camera with the 35 mm
lens will be mounted on a platform in a photo hatch in the floor of the
aircraft. A Control PC (personal computer) will be connected to the
local network in the immediate vicinity of the photo camera using a
FIREWARE interface. The camera will be switched on at the command given
by the leader of survey and will continuously take photos every 3-5
seconds. The second digital photo camera will be used within the
guidance system, and will be used for detailed aerial photography of
walrus groups. Aiming of the photo sight at walrus groups will be
accomplished by using thermal images to locate walrus groups and
indicate their current positions within the camera field of view. The
operator will combine photo sight indicator with walrus heat spots on a
thermal image and take a picture.

**D2. Details: counting digital photographs** Walruses on digital
photographs will be counted using counting methods similar to those used
by the U.S. side (see B3 above).

[]{.mark}

**V. Group size assessment: correcting for walrus groups too small to be
detected**

Pilot studies in 2002 and 2003 suggested that the detection limit of the
thermal scanner could be treated as fixed at a group size of 4 walruses,
i.e., that group sizes of 3 or fewer walruses are not detectable. A
subsequent pilot study in 2005 suggested that the detection limit is
temperature dependant and groups of more than 4 animals may not be
detectable at colder temperatures. Therefore, additional sampling and
analytical procedures are being developed to allow estimation of the
scanner detection limit as a function of temperature, and to estimate
the proportion of the population that is hauled out but occurs in groups
too small to be detected at the time of the survey.

This additional survey effort will involve dedicating the photography
plane for some time each day to conduct low-level systematic line
transect surveys of walruses hauled out on ice. All visually detected
groups or single walruses will be photographed for later counting, to
assess the distribution of group sizes. Data from areas that were both
visually surveyed and thermally scanned will be compared to determine
group size detection limits of the thermal scanner under varying
temperatures, which will be measured from thermal images.

**VI. Satellite radio-tagging: correcting for walruses in the water**

The estimate of walrus numbers hauled out on pack ice derived from
thermal scanning must be corrected for walruses that are in the water
and unavailable for counting (sighting availability). As walruses spend
the majority of their time in water (Jay et al. unpublished data), this
correction factor is critical for an accurate estimate of population
size.

Walruses will be tagged with satellite radio transmitters to obtain
continuous haul-out data from individual animals so that the proportion
hauled out onto sea ice during a given time period can be estimated. The
tags have conductivity sensors that record wet and dry intervals,
corresponding to swimming/diving in seawater in contrast to hauling out
(Figure 5). Knowing the proportion of walruses in the water and
unavailable to the thermal scanner will allow correction of the
population estimate derived from thermal scanning of walruses hauled out
on ice. Satellite transmitters are necessary to obtain these data
because walruses move about and are dispersed over vast areas of sea ice
in the Bering Sea during the proposed survey period (spring).
Successfully attached tags are designed to transmit for a minimum of 28
days after attachment.

**A. Tagging equipment**

Tagging will be done from two vessels, the 88 m Russian icebreaker
*Magadan* (Figure 6) and the reinforced crabber operated by the Alaska
Department of Fish and Game, the *Stimson* (Figure 7).

The *Magadan* can accommodate a scientific crew of up to 12 people. This
vessel will board Russian scientists and 3 skiffs in
Petropavlovsk-Kamchatski, Russia, and then sail to St. Paul, Alaska,
where U.S. scientists will board. The *Magadan* will tag walruses in the
U.S. waters of the St. Lawrence Polynya and in Anadyr Gulf, Russia.

The *Stimson* can accommodate a scientific crew of at least 8 people.
This vessel will work out of Adak, and tag walruses from 2 skiffs in the
southeastern Bering Sea, near Nunivak Island.

A shore-based twin-engine aircraft will conduct reconnaissance surveys
for walruses in support of the ships' tagging objectives. The aircraft
crew will locate walruses for tagging and direct the ships to areas of
unconsolidated ice to facilitate travel.

Tagging of walruses will take place from a total of 5 ship-based skiffs.
Skiffs will be used to approach walruses within 15 m so that
approximately 90 tags can be implanted with crossbows.

The tag is a puck-shaped transmitter that attaches to the walrus with a
harpoon head mounted on a 6.0 cm × 0.6 cm stainless steel post (Figure
8). The harpoon head has broad flexible backward-projecting stainless
steel fins and a cutting blade at the tip to facilitate entry through
the skin and into the blubber layer. Each tag will be delivered with an
arrow (2315 Lite Easton aluminum shaft filled with a solid fiberglass
rod) that fits loosely into the back of the transmitter and is shot from
a recurve crossbow (Excalibur, Exocet model, approximately 1.06 Joules
work).

To infer whether the animal is in water or hauled out, the tag has a
conductivity sensor that senses every 10 seconds whether the transmitter
is submerged in seawater (Figure 5). At 30 minute intervals these sensor
readings are summarized and recorded as one of two percentage classes
(0-90% dry, and \>90% dry). Each satellite transmission contains data of
the most recent 240 30-minute intervals (5 days of data). Transmissions
are suspended whenever the tag is submerged to conserve battery life.
The tag currently has a battery capacity and transmission schedule that
allows transmissions for at least 4 weeks. Planned modifications to the
transmission schedule of the transmitters may extend longevity to ≥ 5
weeks.

**B. Details: tagging**

The satellite tags will be deployed on walruses from small skiffs. The
skiffs will carry 3-person crews and approach walruses to within 15 m.
The animal's mid-dorsal line, slightly forward of the shoulders, will be
targeted for tag attachment (Figure 8). Five skiffs will be used to
deploy a total of about 90 tags in the three primary walrus breeding
regions: the Southeastern Bering Sea, St. Lawrence Island Polynya, and
Anadyr Gulf (Figure 9; Fay 1982, Mimrin et al. 1990). Tagging will take
place in the Southeast Bering Sea and the St. Lawrence Island Polynya
simultaneously from the two ships. These areas will then be aerially
surveyed first, as conditions permit, while tagging takes place in
Anadyr Gulf.

The amount of time spent hauled out on ice can vary among walruses due
to factors related to foraging effort, thermoregulation, and animal
movements. These factors may be influenced by regional differences in
prey abundance, weather, ice dynamics, and walrus age, gender, and
reproductive status (e.g., pregnant, lactating, non-pregnant, breeding).
It is assumed (see Section IX, Statistical Assumptions) that tagged
walruses are a random sample of walruses in the population, or at least,
that the haul-out behavior of the tagged sample is representative of the
population.

To meet this assumption, tags should be distributed throughout the range
of the population and in proportion to the size of age and sex classes
in the population. This assumption cannot be fully met because walruses
tend to have a clumped distribution, animals of all age, sex, and
reproductive classes are not equally accessible, and only animals ≥ 6
years old have blubber and skin that is thick enough for tagging.

In an effort to obtain a sample of haul out behaviors that is
representative of the population, three spatial scales will be
considered in selecting animals for tagging within a region: 1)
selection among several aggregations of walruses that can be separated
by ≥1 day transit by ship, 2) selection among groups of walruses on
individual ice floes within an aggregation, and 3) selection of an
individual walrus among members of a group.

If possible, larger aggregations of walruses will be allocated a greater
proportion of tags; however, time constraints may preclude deployments
in some aggregations. Aerial reconnaissance will be used to determine
the approximate sizes and locations of aggregations in a given region
(e.g., Figure 10). This information will be communicated to the ship and
used to determine roughly the number of tags to deploy in each
aggregation within the constraints of available ship time. Time
constraints will probably limit tagging to only a few aggregations
within each region.

Tags will be deployed among different groups of walruses as they are
encountered throughout each day, with an effort to spread the tags
across an aggregation; however, some groups will not be accessible from
a skiff. Within a group, there are usually only 1-2 animals that are
properly positioned for tagging because the skiff must approach from
downwind and the animal's dorsal surface must be exposed and
perpendicular to the shooter. Tagging one animal usually results in the
entire group of animals fleeing into the water.

Daily tag allocations may be modified slightly to target animals in
under-represented sex, age, and reproductive classes as determined from
cumulative tallies of animals from opportunistic observations from the
skiffs each day. Only walruses at close range will be classified, and
only into very broad age categories. Age is estimated primarily from the
ratio of the length of the tusk to the width of the muzzle, and sex is
determined by tusk and animal morphology (Fay and Kelly 1989). Some
classification of local walruses may be possible from the ship, but
shipboard classification often competes with tagging efforts for ship
time and access to walruses.

The ship may support other projects on the same research cruise if these
additional research efforts are not in conflict with the primary tagging
mission. However, success of the walrus tagging crew will have
precedence over other data collection efforts.

**C. Aircraft/ship coordination**

Reconnaissance will not be required every day, but on an as-needed basis
depending on the needs of the ship to locate new walrus groups. Aerial
reconnaissance for tagging in U.S. waters will be based out of Bethel
and Nome during the two tagging cruises. In Russian waters, the Russian
aerial survey team will provide one or two days of reconnaissance, based
out of Anadyr.

Communication protocols between the reconnaissance and tagging crews,
including satellite phone, marine radio, e-mail, and data logging, are
detailed in cruise plans for work accomplished in the spring of 2004 and
2005 (Jay and Fischbach 2004, 2005). Each day, the aerial reconnaissance
team will collect walrus and ice information over the prescribed study
area. In the evening, the data will be transmitted to the ship by e-mail
in text format. On the ship, the data will be imported into a GIS
database. Each morning, the reconnaissance information from the previous
evening and current weather and ice conditions will be assessed to plan
the day's tagging mission.

**VII. Timing of survey efforts**

The timing of the survey will be critical for success. There are four
main issues constraining the timing:

> **1) The survey must take place during a period of clear skies (no or
> minimal cloud cover) when air temperatures are above -12º C (10º F).**
>
> **2) A sample of walruses throughout the study area must be tagged
> with satellite radio transmitters immediately before the aerial
> portion of the survey.**
>
> **3) The survey must take place while walruses are associated with the
> pack ice, before they begin their migrations toward summering areas or
> before they begin using terrestrial haulouts. Migration and movement
> toward land have historically begun in April (Fay 1982).**
>
> **4) Both the U.S. and Russia portions of the survey must take place
> as synchronously as possible to minimize walrus movements between
> regions during the survey.**

Assessment of Bering Sea air temperatures in March and April from 1980
to 2005 indicates that temperatures continue to rise through March and
April (Figure 12). Temperatures from approximately 01 to 21 April are
warm enough, on average, to ensure a high likelihood of successfully
completing the survey within a three-week period. Analyses of cloud
cover and wind chill factor are ongoing, and the final determination of
survey timing is not yet complete.

The chronological order of the survey components is fixed. Walruses must
be tagged before the aerial survey takes place, so that tags are
recording ice haul-out behavior during the aerial survey. The tags have
a life expectancy of approximately 4 to 5 weeks. For example, in order
for the tags to be functioning during a U.S. aerial survey from 01 to 21
April, both ships must leave their respective ports on about 22 March
(Figure 13). Walruses will be tagged in U.S. waters from approximately
23 March to 28 March. Once walruses in U.S. waters are tagged, the U.S.
aerial survey will begin as the *Magadan* heads to Russia for further
tagging in the Gulf of Anadyr (Figure 13). Under this scenario, aerial
surveys in Russia will begin in early April after completion of tagging.

One aircraft will assist with searching for walruses and assessing ice
conditions for the ship-based tagging crew while it is in U.S. waters
(approximately 22 to 28 March). Once tagging operations in U.S. waters
are complete, the same aircraft will then begin duty as the thermal
scanning plane. The second aircraft will arrive in Nome or Bethel to
begin the aerial photography at the same time. By beginning aerial
surveys as soon as possible after walruses are tagged, the number of
walruses whose tags will still be working will be maximized, since some
tags fail earlier than others.

**VIII.** **Survey design and statistical analysis**

**A. Survey transect design**

Transect midlines will be spaced 12 km apart, to give a strip width that
matches the area covered by the thermal scanner, and will be oriented in
a north-south direction so they are predominantly perpendicular to the
ice edge (see Figure 14 for example). Transects will be grouped into
survey blocks of the approximate area that can be surveyed in one day of
good survey conditions at the specified intensity, when flying time to
and from the survey block is considered. A systematic sample of
transects will be surveyed within each block. The final configuration of
transects and survey blocks will be determined shortly before the survey
takes place, when the extent of the pack ice is known. Surveys will be
done only in areas where the sea floor depth is ≤200 m.

**B. Statistical methods**

Statistical analysis of the data collected in the U.S. and Russia will
be done cooperatively, so that a single total population estimate is
calculated.

Estimating the size of the Pacific walrus population from the survey
data will involve the following sequence of steps: (1) estimating the
relation between thermal signature intensities and numbers of walruses
in thermally detected groups, (2) estimating the proportion of the
population hauled out on the ice during the survey, (3) estimating the
total number of walruses on surveyed transects, (4) estimating the total
number of walruses in each survey block and summing to estimate the
total population size, (5) adjusting this estimate to account for
walruses hauled-out on the ice but in groups too small to be detected by
the scanner, and (6) estimating the variance and confidence intervals
for the population estimate. Each of these steps is described in more
detail below.

**B1. Relating thermal signature intensity to group size.** Data from
photographed groups will be used to develop a regression model relating
thermal signature intensity to group size (Figure 4). This model will be
used to estimate the number of walruses in each thermally detected group
that was not photographed. Pilot studies conducted near St. Lawrence
Island in 2002 and 2003 indicated that variances of the photographic
counts were proportional to the mean, or the square of the mean, counts.
Therefore, we will use a generalized linear model (McCullagh and Nelder
1989) with an identity link and a Poisson or gamma distribution to
estimate the relation between numbers of individuals and thermal
signatures in the photographed groups. Notation is summarized in
Appendix I. The form of this model is

$E(y_{gtb}) = \alpha + \beta\ h_{gtb}\ ,\ \text{Var}(y_{gtb}) = \phi\ (\alpha + \beta\ h_{gtb})\ ,$
(2)

with the Poisson distribution, or

$E(y_{gtb}) = \alpha + \beta\ h_{gtb}\ ,\ \text{Var}(y_{gtb}) = \phi\ (\alpha + \beta\ h_{gtb})^{2}\ ,$
(3)

with the gamma distribution. Here, *h~gtb~* is the thermal index for
group *g* on transect *t* of block *b*, *α* is the minimum size group
that can be detected by the scanner, and *β* and *φ* are parameters that
are estimated by maximum likelihood. The estimators for these parameters
and their variances do not have explicit forms, so they have to be
determined numerically. Estimation will be accomplished with SAS PROC
GENMOD software (Statistical Analysis Systems, Cary, North Carolina,
USA).

**B2. Estimating proportion hauled out.** The proportion of the
population that was hauled out on the ice and therefore potentially
available to be detected during the thermal scanner survey will be
estimated with the satellite telemetry data from the tagged walruses as

$\hat{p} = \frac{1}{w}\sum_{i = 1}^{w}{p_{i}\ ,}$ (4)

where *p~i~* is the proportion of the relevant time period that walrus
*i* was available to be detected. In practice, we expect to estimate
separate availability proportions for different sets of blocks using
only data from restricted areas or time periods. Here we consider only a
single overall estimate that will be used for all blocks. Modifications
required for using separate estimates are straightforward.

**B3. Estimating totals for surveyed transects.** The number of walruses
on a surveyed transect will be estimated by summing the counts of
individuals in all the photographed groups and the estimated counts in
all the detected groups that were not photographed and then dividing
this total by the estimated proportion of the population that was
available to be detected. For transect *t* in block *b*, we have:

${\hat{N}}_{tb} = \ \frac{\sum_{g = 1}^{c_{tb}}{y_{gtb} + \sum_{g = c_{tb} + 1}^{G_{tb}}{(\alpha + \hat{\beta}\ h_{gtb})}}}{\hat{p}}\ ,$
(5)

where *y~gtb~* is the number of walruses in group *g* on transect *t* of
block *b*, photographed groups are indexed 1, \... , *c~tb~*, and groups
that were not photographed are indexed *c~tb~*+1, \..., *G~tb~*. If
there are no photographed groups on a transect, then *c~tb~* = 0.

**B4. Estimating totals for blocks and the population.** The total
population size is estimated as a sum of separate ratio estimators
(Cochran 1977) of the totals for each block:

$\hat{N} = \sum_{b = 1}^{B}{\left( {\hat{R}}_{b}\sum_{t = 1}^{T_{b}}A_{tb} \right) =}\sum_{b = 1}^{B}{\hat{N}}_{b}\ ,$
(6)

where

${\hat{R}}_{b} = \frac{\sum_{t = 1}^{t_{b}}{\hat{N}}_{tb}}{\sum_{t = 1}^{t_{b}}A_{tb}}\ ,$
(7)

*A~tb~* is the area of transect *t* in block *b*, *T~b~* is the number
of transects in block *b*, *t~b~* is the number of surveyed transects in
block *b*, and *B* is the number of blocks.

We anticipate that estimates for Russian survey blocks will be obtained
using similar methods, modified as necessary to accommodate any
differences in scanner function. Estimated totals for Russian survey
blocks will be included in sum (6) to obtain the total population
estimate.

**B5. Accounting for walruses on ice in groups too small to be detected
by the scanner.** The population estimator (6) assumes that the number
of walruses hauled-out on the ice but in groups too small to be detected
by the infrared scanner was negligible. We will use data from a low
level line-transect survey conducted with the photography plane on a
subsample of the transects covered in the scanner survey to assess this
assumption and to adjust the population estimate as necessary. The
adjusted population size will be estimated as

${\hat{N}}^{} = \sum_{b = 1}^{B}\left( {\hat{N}}_{b} + \frac{{\hat{u}}_{b}}{\hat{p}} \right)\ ,$
(8)

where ${\hat{u}}_{b}$ is the estimate of the number of hauled-out
walruses in groups of size \< *s~b~* obtained with standard
line-transect methods (Buckland et al. 1993), and *s~b~* is the
detection limit for the scanner (i.e., the smallest group size that can
be detected in the scanner survey) for block *b*.

We note that to adjust the total population estimate, it is not
necessary to estimate the numbers undetectable hauled-out walruses from
the low-level survey in each block. Rather, it would be sufficient to
estimate just the ratios *u~b~*/*d~b~*, where *d~b~* is the number of
detectable hauled-out walruses in block *b*. If enough groups were
observed, these ratios could estimated directly from the observed groups
in narrow strips where it could be assumed that all groups were detected
in the low-level survey. The adjusted population size could then be
estimated as

${\hat{N}}^{} = \sum_{b = 1}^{B}{{\hat{N}}_{b}\left( 1 + \frac{u_{b}}{d_{b}} \right)}\ \text{.}$
(9)

Methods for estimating this ratio directly while accounting for the
likely dependency of detection probability on group size at greater
distances would have to be developed.

**B6. Estimating variance.** The variance and confidence intervals for
the population estimate will be obtained with a bootstrap procedure
based on the general approach of Booth et al. (1994) for finite
populations. The procedure involves generating a series of simulated
populations, estimating statistics of interest by resampling from each
simulated population, and then averaging these statistics over the
simulated populations.

We generate simulated populations of transects (with associated walrus
observations and low level line-transect survey segments) for each block
by first replicating the complete set of surveyed transects in the block
as many times as possible without exceeding the total number of
potential transects in the block. We then add a random sample without
replacement from the surveyed transects to complete the population of
potential transects. Bootstrap survey samples are obtained by drawing
random samples without replacement from the simulated populations to
give the same number of transects as in the original survey. For each
bootstrap survey sample, we also obtain a bootstrap sample of
photographic counts for fitting the regression model by taking a random
sample with replacement from the photographed groups to give the same
sample size as for the original survey. We also obtain a bootstrap
sample of transmitter data to go with each bootstrap survey sample by
taking a random sample with replacement from the tagged walrus data to
give the same number of tagged walruses as in the original sample. If
there is any stratification used for estimating region or time-specific
regression parameters or haul-out proportions in the original survey,
then bootstrap resamples are obtained with the same stratification.

Estimation for each bootstrap sample follows the same procedure as for
the original sample. We obtain *K~1~* bootstrap samples and the
associated estimates of population size for each simulated population
and then calculate the standard error and 2.5 and 97.5 percentiles of
these *K~1~* estimates. We repeat this process for *K~2~* simulated
populations, taking the averages of the standard errors and 2.5 and 97.5
percentiles as our estimates of standard errors and 95% confidence
limits for the estimates from the original survey. *K*~1~ and *K~2~*
need to be large enough for the estimates to converge. Pilot study
results suggest that *K~1~* = 100 and *K~2~* = 500 should be sufficient,
but this should be checked and the number of simulated populations and
bootstrap samples per population increased as necessary to obtain
convergence in any particular application.

We may also consider a second type of approach for estimating variance
based on modeling the spatial structure of the data (Cressie 1991).
Properly accounting for this spatial structure may ultimately give more
precise estimates of the population size.

**IX. Statistical assumptions**

The following is a partial list of assumptions required for unbiased
estimation of population size and its variance for this study design.
Also included is some discussion of survey design features related to
these assumptions.

> **1. The data collected cover the entire range of the population at
> the time of the survey.** A preliminary delineation of this area will
> be based on historical walrus distributions and bathymetry, but a
> final delineation will be made immediately before the survey based on
> the current ice distribution.
>
> **2. Survey blocks form a complete partition of the study area and
> strip transects form a complete partition of each block.** This means
> that blocks completely cover the study area with no overlap and that
> strip transects completely cover the area of each block with no
> overlap. Blocks will be the smallest areas beyond the surveyed
> transects for which we will estimate population size. Each block will
> be sized so it can be surveyed in a single day at the specified survey
> intensity. Transect widths are determined by the width of the scanner
> coverage, so block boundaries will have to be adjusted to the nearest
> whole transect. One other criterion to be considered in designing
> blocks is that variance of the population estimate will be minimized
> by making transects within a block as homogenous as possible with
> respect to walrus density.
>
> We use the terms "transect" and "strip transect" interchangeably. The
> survey aircraft will fly along the midlines of the selected strip
> transects.
>
> **3. There is no net movement of walruses among transects or blocks
> while they are being surveyed.** Block boundaries will be located in
> areas expected to have relatively low walrus density and the survey
> will be completed as rapidly as possible to minimize potential for net
> movement.
>
> **4. Surveyed transects are a random sample of transects in each
> block.** This assumption is required to minimize bias of the variance
> estimators. We will actually use a systematic sample of transects
> because that will likely provide a more accurate estimate of
> population size, but this may result in the variance estimates being
> somewhat conservative (Wolter 1984). An approximate (100/*k*)%
> systematic sample of transects in a block is obtained by randomly
> selecting one out of the first *k* transects and then every *k*'th
> transect beyond that. Bias due to systematic sampling of transects
> would not be a problem for spatial estimates of variance.
>
> **5. Satellite radio-tagged walruses are a random sample of walruses
> in the population or at least, the haul-out behavior of the tagged
> sample is representative of the population.** To meet this assumption,
> transmitters will need to be distributed throughout the range of the
> population and in proportion to age and sex class proportions in the
> population. We expect that, at minimum, this will require separate
> transmitter deployment efforts in three regions, the Southeast Bering
> Sea, the St. Lawrence Island Polynya, and Anadyr Gulf (Figure 9).
>
> **6. Photographed groups are randomly distributed throughout the
> survey area and time period or at least, are obtained under conditions
> representative of those during the survey.**
>
> **7. All groups detected by the scanner contain only walruses.** Other
> ice seals are not likely to form groups large enough to be detected by
> the scanner.

**Literature Cited**

Booth, J.G., Butler, R.W., and Hall, P. 1994. Bootstrap methods for
finite populations. Journal of the American Statistical Association
89(428):1282-1289.

Bowden, D.C., White, G.C., Franklin, A.B., and Ganey, J.L. 2003.
Estimating population size with correlated sampling unit estimates.
Journal of Wildlife Management 67(1):1-10.

Burn, D.M., Webber, M.A., and Udevitz, M.S. In press. Application of
airborne thermal imagery to surveys of Pacific walrus. Wildlife Society
Bulletin.

Cochran, W.G. 1977. Sampling techniques, third edition. John Wiley &
Sons, New York.

Cressie, N. 1991. Statistics for spatial data. John Wiley & Sons, New
York.

Efron, B. 1982. The jackknife, the bootstrap and other resampling plans.
Society for Industrial and Applied Mathematics, Philadelphia,
Pennsylvania.

Fay, F.H. 1982. Ecology and biology of the Pacific walrus, *Odobenus
rosmarus divergens* Illiger. North American Fauna 74:1-279.

Fay, F.H. and Burns, J.J. 1988. Maximal Feeding Depth of Walruses.
Arctic 41(3):239-240.

Fay, F.H., Eberhardt, L.L., Kelly, B.P., Burns, J.J., and Quakenbush,
L.T. 1997. Status of the Pacific walrus Population, 1950-1989. Marine
Mammal Science 13(4):537-565.

Fay, F.H., and Kelly, B.P. 1989. Development of a method for monitoring
the productivity, survivorship, and recruitment of the Pacific walrus
population. Final Report, OCSEAP Study MMS 89-0012. Minerals Management
Service, Anchorage, Alaska. 51 pp.

Fay, F.H., Kelly, B.P., Gehnrich, J.L., Sease, J.L., and Hoover, A.A.
1984. Modern populations, migrations, demography, trophics, and
historical status of the Pacific walrus. Final Report R.U. #611. NOAA
Outer Continental Shelf Environmental Assessment Program, Anchorage,
Alaska. 142 pp.

Fay, F.H., Kelly, B.P., and Sease, J.L. 1989. Managing the exploitation
of Pacific walruses: a tragedy of delayed response and poor
communication. Marine Mammal Science 5:1-16.

Garlich-Miller, J. and Jay, C.V. 2000. Proceedings of a workshop
concerning walrus survey methods. USFWS R7/MMM Technical Report 00-2. 92
pp.

Gilbert, J.R., Fedoseev, G.A., Seagars, D., Razlivalov, E., and
LaChugin, A. 1992. Aerial census of Pacific walrus, 1990. USFWS R7/MMM
Technical Report 92-1. 33 pp.

Gilbert, J.R. 1999. Review of previous Pacific walrus surveys to develop
improved survey designs. *In* Garner, G.W., Amstrup, S.C., Laake, J.L.,
Manly, B.F.J., McDonald, L.L., and Robertson, D.G. (eds), Marine Mammal
Survey and Assessment Methods. A. A. Balkema, Rotterdam. 287 pp.

Hills, S. and Gilbert, J.R. 1994. Detecting Pacific walrus population
trends with aerial survey - a review. Transactions of the North American
Wildlife and Natural Resource Conference.

Hunt, G.L., Jr. and Stabeno, P.J. 2000. Ecosystem responses to weather
patterns in the Southeastern Bering Sea. Arctic Research of the United
States 14:17-24.

Jay, C.V. and Fischbach, A.S. 2004. Cruise Plan for Walrus Tagging
Aboard the P/V Stimson Bering Sea, April 2004. U.S. Geological Survey,
Alaska Science Center, Anchorage, Alaska. Unpublished internal document.
22 pp. Available at
<http://www.absc.usgs.gov/research/walrus/population.html>.

Jay, C.V. and Fischbach, A.S. 2005. Cruise Plan for Walrus Tagging
Aboard the P/V Stimson Bering Sea, March 2005. USGS, Alaska Science
Center, Anchorage, Alaska. Unpublished internal document. 19 pp.
Available at <http://www.absc.usgs.gov/research/walrus/population.html>.

Jay, C.V., Heide-Jørgensen, M.P., Fischbach, A.S., Jensen, M.V.,
Tessler, D.F., and Jensen, A.V. In press. Comparison of remotely
deployed satellite radio transmitters on walruses. Marine Mammal Science
22(1):000-000.

McCullagh, P. and Nelder, J.A. 1989. Generalized linear models, second
edition. Chapman and Hall, Boca Raton, Florida.

Mimrin, N.I., Smirnov, G.P., Gaevsky, A.S., and Kovalenko, V.E. 1990.
The distribution and abundance of walruses in the Anadyr Gulf of the
Bering Sea. Zoologichesky Zhurnal 69:105-113. (Translated from Russian).

Scribner, K.T., Hills, S., Fain, S.R., and Cronin, M.A. 1997. Population
genetics studies of the walrus (*Odobenus rosmarus*): a summary and
interpretation of results and research needs. *In* Dizon, A.E., Chivers,
S.J., and Perrin, W.F. (eds). Molecular Genetics of Marine Mammals.
Marine Mammal Science 3:173-184.

Seber, G.A.F. 1982. The estimation of animal abundance, second edition.
Oxford University Press, New York, New York.

Udevitz, M.S. 2005. Statistical procedures for estimating Pacific walrus
population size. Technical report, Alaska Science Center, U.S.
Geological Survey, Anchorage, Alaska. 9 pp.

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walrus (*Odobenus rosmarus divergens*).

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systematic sampling. Journal of the American Statistical Association
79(388):781-790.

![](media/image2.wmf){width="4.711111111111111in"
height="3.522222222222222in"}

![](media/image3.wmf){width="4.711111111111111in"
height="3.522222222222222in"}

Figure 1. Approximate ice coverage in the Bering Sea in late spring.
Shown are the approximate coverages for a heavy ice year (1997, top,
835,000 km^2^) and a light ice year (2002, bottom, 521,000 km^2^). The
blue line indicates the U.S.-Russian border.

![](media/image4.jpeg){width="6.120138888888889in"
height="3.997916666666667in"}

Figure 2. Example of an aerial digital photograph of walrus groups
hauled out on ice and the matching thermal image of the same walruses.
Data were collected in April 2004.

![](media/image5.jpeg){width="6.25in" height="4.447222222222222in"}

Figure 3. Example of frequency histogram of AMS thermal imagery showing
temperature threshold between the background environment and walruses
that occurs at

-2.81° C. Pixels to the right of the threshold value have some portion
of their area covered by walruses.

![](media/image6.wmf){width="6.509722222222222in"
height="4.502777777777778in"}

Figure 4. Example gamma regression of walrus group size as a function of
thermal signature for AMS thermal imagery at 4 m spatial resolution
(Burn et al. in press). Dashed lines represent 95% confidence intervals.
Data were collected in April 2002.

![](media/image7.wmf){width="6.34375in" height="2.9277777777777776in"}

Figure 5. Walrus haul-out chronology data from 2004, collected from
satellite tags which are of similar design to those that will be used in
the 2006 walrus population survey (\* = anomalously long dry period at
the end of the haul out chronology, which suggests the tag may have
malfunctioned or became detached from the animal on land or ice).

![](media/image8.jpeg){width="5.9875in" height="3.861111111111111in"}

  ----------------------------------- -----------------------------------
  Name:                               ***Magadan***

  Nationality (Flag state):           **Russian**

  Owner:                              **Russian Federation**

  Owner Address:                      **103685,6, Nikolskiy pereulok,
                                      Russia**

  Operator:                           **Far Eastern Shipping Company**

  Operator Address:                   **15, Aleutskaya Street,
                                      Vladivostok, 690990, Russia**

  Overall length (meters):            **88.49**

  Maximum draught (meters):           **6.5**

  Displacement (metric tons):         **6200**

  Main Engines:                       **WARTSILA SULZER Type, 8R 32 4 x
                                      2685 kW**

  Cruising & Maximum speed (knots):   **14, 17.5**

  Call sign:                          **UIFQ**

  Method and capability of            **VHF, SSB, INMAR-SAT**
  communication:                      

  Name of master:                     **Roman Nikolayevich Mogilyan**

  Number of crew:                     **37**

  Number of scientists on board:      **10-15**
  ----------------------------------- -----------------------------------

Figure 6. Specifications of the icebreaker *Magadan*.

![](media/image9.jpeg){width="5.996527777777778in"
height="3.7895833333333333in"}

+-----------------------------------+-----------------------------------+
| Name:                             | ***PV Stimson***                  |
+-----------------------------------+-----------------------------------+
| Nationality (Flag state):         | **American**                      |
+-----------------------------------+-----------------------------------+
| Owner:                            | **State of Alaska**               |
+-----------------------------------+-----------------------------------+
| Operator:                         | **Dept of Public Safety, Fish and |
|                                   | Wildlife Protection**             |
+-----------------------------------+-----------------------------------+
| Overall length (feet):            | **156**                           |
+-----------------------------------+-----------------------------------+
| Maximum draught (meters):         | **4**                             |
+-----------------------------------+-----------------------------------+
| Displacement/Gross tonnage:       | **443 tons**                      |
+-----------------------------------+-----------------------------------+
| Propulsion:                       | **Diesel Electric**               |
+-----------------------------------+-----------------------------------+
| Cruising & Maximum speed:         | **8, 11**                         |
+-----------------------------------+-----------------------------------+
| Call sign:                        | **PV Stimson**                    |
+-----------------------------------+-----------------------------------+
| Method and capability of          | **AV Radio: channel 129**         |
| communication (including          |                                   |
| emergency frequencies):           | **Marine VHF: channel 16**        |
|                                   |                                   |
|                                   | **Sat phone: 011- 881- 631- 459 - |
|                                   | 136**                             |
+-----------------------------------+-----------------------------------+
| Name of master:                   | **Troy Magnuson**                 |
+-----------------------------------+-----------------------------------+
| Number of crew:                   | **1 state trooper, 4 crew**       |
+-----------------------------------+-----------------------------------+
| Number of scientists on board:    | **6-7**                           |
+-----------------------------------+-----------------------------------+
| Onboard helicopter support:       | **None**                          |
+-----------------------------------+-----------------------------------+

Figure 7. Specifications of the Patrol vessel Stimson.

![](media/image10.jpeg){width="5.593700787401575in"
height="1.4409448818897639in"}

![](media/image12.jpeg){width="2.990972222222222in"
height="2.0243055555555554in"}

+-----------------------------------+----------------------------------+
| > **Manufacturer**                | Telonics Inc., Mesa, Arizona,    |
|                                   | U.S.A.                           |
+-----------------------------------+----------------------------------+
| > **Model**                       | ST-24                            |
+-----------------------------------+----------------------------------+
| > **Transmitter dimensions**      | 5.2 × 2.8 cm (puck-shaped disc)  |
| >                                 |                                  |
| > **(excluding antenna)**         |                                  |
+-----------------------------------+----------------------------------+
| > **Approximate transmitter       | 91 g                             |
| > weight in air**                 |                                  |
+-----------------------------------+----------------------------------+
| > **Transmission duty cycle       | 18 hrs on, 6 hrs off             |
| > (daily)**                       |                                  |
+-----------------------------------+----------------------------------+
| > **Transmission output power**   | 0.25 W                           |
+-----------------------------------+----------------------------------+
| > **Transmission repetition       | 60 sec                           |
| > interval**                      |                                  |
+-----------------------------------+----------------------------------+
| > **Argos message length**        | 31 bytes                         |
+-----------------------------------+----------------------------------+
| > **Argos transmission            | 401.618 to 401.680 MHz           |
| > frequency**                     |                                  |
+-----------------------------------+----------------------------------+
| > **Modulation (BPSK)**           | -1.1 to +1.1 ±0.1 Radians        |
+-----------------------------------+----------------------------------+
| > **Quiescent current (typical)** | 3 μA                             |
+-----------------------------------+----------------------------------+
| > **Spurious emissions**          | -45 dB                           |
+-----------------------------------+----------------------------------+
| > **Transmitter delivery system** | crossbow                         |
+-----------------------------------+----------------------------------+

Figure 8. Specifications of the walrus satellite tag that will collect
haul-out behavior data for estimating sighting availability during the
walrus aerial survey.

![](media/image14.png){width="5.772222222222222in"
height="4.042361111111111in"}

Figure 9. The three study areas (Anadyr Gulf, St. Lawrence Island
Polynya, and Southeastern Bering Sea) where tagging of walruses will
take place.

![](media/image15.png){width="6.739583333333333in"
height="5.206944444444445in"}

Figure 10. Examples of aerial reconnaissance track lines, plotted during
walrus tagging in April 2004.

![](media/image16.jpeg){width="4.543055555555555in"
height="3.0506944444444444in"}

![](media/image17.jpeg){width="4.645833333333333in"
height="3.4895833333333335in"}

Figure 11. Example of ice conditions during walrus tagging from skiffs
in spring 2004 and 2005, Southeastern Bering Sea.

![](media/image20.wmf){width="9.5in" height="5.804166666666666in"}

Figure 12. Percentage (y axis) of temperatures for April and May (x
axis) from 1980-2005 that falls within each of 5 temperature categories:
green, \>30º F; blue, 20-30º F; yellow, 10-20º F; orange 0-10º F; red,
\<0º F.

![](media/image21.wmf){width="6.195138888888889in"
height="8.503472222222221in"}

Figure 13. Chronological order of the tagging and aerial survey
missions, and estimated life expectancy of the satellite tags.

![](media/image22.jpeg){width="6.551388888888889in"
height="4.745833333333334in"}

Figure 14. Example of transect and survey block layout used for pilot
surveys in 2005. Transects were spaced 12 km apart, and numbered blocks
defined areas that could be surveyed within one day. Surveys took place
only over areas where the depth of the sea floor was ≤200 m.

**Appendix I. List of statistical notation used in this report.**

*N* = walrus population size

*α* = smallest group of walruses detectable with the scanner (i.e.,
detection limit)

*β* = slope parameter for the generalized linear model relating thermal
signature intensity to walrus group size

*φ* = dispersion parameter for the generalized linear model relating
thermal signature intensity to walrus group size

*w* = number of transmitters deployed (i.e., number of tagged walruses)

*p~i~* = proportion of time during the survey period that tagged walrus
*i* was hauled out on the ice and therefore available to be detected

*p* = proportion of the walrus population available to be detected
during the survey

B = number of blocks

*A~b~* = area of block *b*

*N~b~* = number of walruses in block *b*

*u~b~* = number of walruses hauled-out on the ice but in groups to small
to be detected by the scanner in block *b*

*d~b~* = number of walruses hauled-out on the in groups large enough to
be detected by the scanner in block *b*

s~b~ = smallest group size that can be detected by the scanner

*T~b~* = total number of transects in block *b*

*t~b~* = number of surveyed transects in block *b*

${\overline{a}}_{b}$= average area per transect for surveyed transects
in block *b*

*R~b~* = ratio of total number of walruses on surveyed transects to
total area of surveyed transects in block *b*

*A~tb~* = area of transect *t* in block *b*

*N~tb~* = number of walruses on transect *t* of block *b*

*G~tb~* = number of walrus groups detected by the scanner on transect
*t* of block *b*

*c~tb~* = number of walrus groups photographed on transect *t* of block
*b*

*y~gtb~* = number of walruses in group *g* on transect *t* of block *b*

*h~gtb~* = thermal signature intensity for walrus group *g* on transect
*t* of block *b*

**Appendix II. List of cooperators by agency.**

**Marine Mammals Management, U.S. Fish and Wildlife Service**, 1011 E.
Tudor Road, Anchorage, AK 99503, U.S.A. Phone: (907) 786-3800

> **Rosa Meehan**, Ph.D. Chief. Rosa_Meehan@fws.gov
>
> Management of marine mammals, Alaska Native relations, human impacts
> on marine systems, coordination with Russia
>
> **Brad Benter**, B.S. Biological Science Technician.
> Brad_Benter@fws.gov
>
> Aerial digital photography, subsistence harvest assessment
>
> **Douglas Burn**, M.S. Supervisory Wildlife Biologist.
> Douglas_Burn@fws.gov
>
> Thermal imagery systems design and development, survey design, sea
> otters, marine mammal conservation
>
> **Charles S. Hamilton**, M.S. Wildlife Biologist.
> Charles_Hamilton@fws.gov
>
> Management of marine mammals, regulatory development, international
> relations and conservation
>
> **Joel Garlich-Miller**, M.S. Wildlife Biologist.
> Joel_GarlichMiller@fws.gov
>
> Pacific walrus life history, ecology, conservation, and management
>
> **Suzann G. Speckman**, Ph.D. Wildlife Biologist.
> Suzann_Speckman@fws.gov
>
> Development of Study Plan, coordination among U.S. and Russian
> specialists, marine ecology, oceanography, fisheries acoustics
>
> **John Trent**, Ph.D. Supervisory Wildlife Biologist.
> John_Trent@fws.gov
>
> Pacific walrus management, Alaska Native relations, subsistence
> harvest assessment

**Alaska Science Center, U.S. Geological Survey,** 4230 University
Drive, Suite 201, Anchorage, AK 99508, U.S.A. Phone: (907) 786-3512

> **Chadwick V. Jay**, Ph.D. Research Ecologist. Chad_Jay@usgs.gov
>
> Walrus natural history and ecology, radio telemetry, benthic ecology
>
> **Anthony Saul Fischbach**, M.S. Wildlife Biologist.
> AFischbach@usgs.gov
>
> Arctic marine mammals, GIS, radio telemetry, aerial surveying, animal
> behavior
>
> **Mark S. Udevitz,** Ph.D. Research Statistician, Biology.
> Mark_Udevitz@usgs.gov
>
> Methods for sampling, estimating parameters, modeling dynamics of
> wildlife populations

**GiproRybFlot, Research and Engineering Institute for the Development
and Operation of Fisheries,** 18-20 Malaya Morskaya str., St. Petersburg
190000, Russia

# Chernook Vladimir, Ph.D. in Geography, Head of Department. <chernook@grf.spb.ru>, <chernook@mail.ru> 

# Development of Study Plan, coordination among Russian and U.S. specialists, supervision of Russian aerial surveys, development of walrus aerial survey method, participation in air surveys and data analysis 

> **Melentyev Vladimir,** Ph.D. in Physics and Mathematics, Leading
> Researcher. <vladimir.melentyev@niersc.spb.ru>
>
> Ice parameters of the Bering Sea studies, walrus-ice correlation
>
> **Vasiliev Alexander,** Chief Specialist, <vasilev_grf@list.ru>

Technical and software support of aerial surveys, participation in
aerial surveys, software development for walrus survey data processing

> **Shubina Marina,** M.S., researcher.
>
> Aerial survey data processing
>
> **Chelintsev Nikita**, Ph.D. in Biology, Leading Researcher.
> <nchelin@mail.ru>
>
> Mathematic support of aerial surveys, mathematic processing and
> analysis of aerial survey data.
>
> **Krukova Natalia,** Engineer. <sea-walrus@list.ru>
>
> Processing of images of walrus aggregations

**ChukotTINRO, Pacific Research Institute of Fisheries and
Oceanography,** **Laboratory of Marine Mammals Study**, P.O. Box 29,
Anadyr, Chukotka 689000, Russia

> **Myasnikov Vladimir**, M.S. in Biology, Director.
> <tinro@pitcon.asc.ru>
>
> Organization and financial support of aerial surveys in Chukotka

# 

> **Kochnev Anatoliy,** Head of Laboratory. <kochnev@anadyr.ru>
>
> Organization of walrus tagging from the Russian side, walrus tagging
> onboard of icebreaker, processing and analysis of walrus aerial survey
> data
>
> **Litovka Denis,** Researcher. <d-litovka@yandex.ru>
>
> Participation in aerial surveys, preliminary aerial survey data
> processing
>
> **Kudryavtsev Alexander,** Junior Researcher. <tinro@pitcon.asc.ru>
>
> Participation in aerial surveys, preliminary aerial survey data
> processing