Density per Km

10

@ 200 meters from shore
e @ 400 meters from shore
8 4 800 meters from shore
Vv 1200 meters from shore
6 200M
44
e
|
2-74
a > a
1200 M
0- —A 9
T T T T T T
6 8 10 12. 14 16 18 20
Time of day

Figure 7. Summer density of Marbled Murrelets in relation to
time of day along the outer Strait of Juan de Fuca


Percent

60

|

(_] Observations
50 - Total birds

40 4

20

Group Size

Figure 1. Frequency of Marbled Murrelets in relation to their group size


Density per Km?

(~~) 400 meters
800 meters
45 ] P =0.03
3 4
}
2 - |
1 4
0

Distance (meters from shore)

Figure 11. Summer density of Marbled Murrelets in relation to
distance from shore along the northern outer coast


Executive Summary

The mandate of the Tenyo Maru Trustee’s Council is to restore resources damaged by the
Tenyo Maru oil spill. Marbled Murrelets, Brachyramphus marmoratus, and Common
Murres, Uria aalge, were documented by U. S. Fish and Wildlife Service and Washington
Department of Fish and Wildlife to have been negatively impacted in the area of the outer
coast of Washington affected by the Tenyo Maru oil spill. As a result, the Council funded
us to accomplish two tasks with respect to these two species: (1) determine their at-sea
distribution and abundance, and (2) determine their habitat preferences. To do so, it is
necessary to be able to accurately count these species on the water. Unfortunately,
methodologies for accurately counting these species at sea are poorly developed.
Therefore, to accomplish the stated tasks, it is first necessary to validate a methodology
for counting them at sea. In turn, in addition to obvious necessary logistical support (e.g.,
boats, personnel, etc.), one first must also (a) have appropriate computer software for
collecting and analyzing field data, and (b) determine how their distribution and abundance
is affected by biotic and abiotic environmental factors such as time of day, distance from
shore, water depth, and prey abundance.

We have largely completed task one (development of computer software) and are
well on the way to completing task two. Specifically, in collaboration with Ecological
Consulting, Inc. (Portland, OR), we developed a very sophisticated set of computer
programs specifically designed for collecting and analyzing at-sea distribution and
abundance data with respect to biotic and abiotic environmental variables (geographic
coordinates, habitat, water depth etc.). We currently are in the final stages of testing these
programs and implementing minor modifications to them to improve their performance.

One goal of all censusing or sampling methodologies is to reduce sources of
variability within treatments (e.g., species, locations, seasons, etc.) in order to maximize
the probability of discriminating differences between or among treatment groups with a
minimum of time, effort, and expense. Thus, for the purpose of designing a sampling
methodology, the most important factors to understand are those that investigators have
the most control over, and thereby can reduce within-treatment variability. Two such
factors are time of day and distance from shore. Therefore, from 31 July through 27
September 1995, we conducted strip transects from boats (26 to 58 feet in length) at
different times of day (early and late morning, early and late afternoon) and different
distances from shore (200, 400, 800, and 1200 meters) along the outer Strait of Juan de
Fuca and outer coast of Washington. Our results indicate that, independent of distance
from shore, Marbled Murrelets are most abundant early in the morning and decrease
throughout the day whereas Common Murres show no detectable change in abundance
with time of day. Similarly, independent of time of day, Marbled Murrelets are most
numerous close to shore (200 meters), and are rarely found at or beyond 1200 meters
whereas Common Murre abundance is not correlated with distance from shore between
200 and 1200 meters. Since counts of murres are equally accurate at all times of day and
distances from shore, our results suggest that accurate indices of both murres and
murrtelets can be obtained by conducting transects close to shore (200 or 400 meters) early
in the morning. Our data also show that both species are much more abundant along the
northern outer coast and outer Strait of Juan de Fuca than along the southern outer coast,


I

!
Lo Common Murre Density I
i Gray's Harbor South

I I
I = |
a i
I ( __ .0000-8.587 I
: ne __| 8.587-12.60
I __ 12.60-15.45 l
l = _ | 15.45-20.63 I
“ ” __| 20.63-22.61
I ~ I
I 0 I
Co \ I
|
I | I
Me na |
I ° “ 1
l I
| 1
|

2s I
I
Coo Ot

'
Py
L.
I |
I
ro
I
L.
I
I
r ~

Figure 22. Summer density distribution map of Common
Murres along the southern outer coast.


Density per Km

10

|
3
Y= 8.982 - 0.315X
2
e R “=0.751
6 P = 0.065
4 4
e
2 4
04
T T T T T T
8 10 12 #414 «24116 #8618
Time of day

Figure 8. Summer density of Marbled Murrelets at 400 meters from
shore in relation to time of day along the northern outer coast


MARBLED MURRELET
At~Sea Distribution

1995 Transect Data

20.0-0.10 /km2
0.10-0.25 /km2
0.25-0.50 /km2
0.50-1.00 /ki
1.00-2.50 /km2

Figure 14. Summer density distribution map of Marbled Murrelets along the
southern outer coast of Washington.



Density per Km2

10
e
8 4
Y= 5.89 - 0.005X
6 2
e R “= 0.624
P<0.001
4 4
°
e
2 a
e
o- 8
T T T T T

0) 200 400 600 800 1000 1200
Distance (meters from shore)

Figure 10. Summer density of Marbled Murrelets in relation to
distance from shore aiong the outer Strait of Juan de Fuca.


aa Outer Coast
vn Boat Surveys
Area North of Gray's Harbor

; ;
i
|
|
|
|
|

[

Figure 5. Transects conducted along the southern outer
coast from Hoh Head south to Gray’s Harbor.


10

OBJECTIVE 2: Differential Use of Marine Habitats by Common Murres and
Marbled Murrelets

Specific tasks funded:

(1) Survey effort will be designed to determine how abundance, distribution and
behavior are correlated with habitat (shoreline type, submergent/surface
vegetation) and other biotic and abiotic variables such as bathymetry (water
depth), distance from shore, time of day, water salinity, temperature,
weather conditions, tide, and prey abundance.

(2) Boat transects and land-based surveys will quantify use of (and behavior in)
different habitats by murres and murrelets along the outer coast.

(3) Remote sensing will be examined to evaluate its effectiveness in identifying
important seabird habitats.

PROGRESS TO DATE

Tasks 1 and 2

Understanding how to collect and analyze seabird abundance and distribution data is only
the first step in successfully monitoring the at-sea component of a seabird restoration plan.
Determining how murres and murrelets use the Washington outer coast ocean habitat (
and how to define that habitat), and whether any component of this habitat can be
manipulated as part of a restoration plan was the primary objective of this part of our pilot
Project. We defined “habitat” as any environmental variable that can influence murre or
murrelet distribution, and includes bathymetry, distance from shore, water salinity and
temperature, weather conditions, type and amount of surface and/or submergent
vegetation, etc. How these seabird species use these habitats is just as important as
whether they use these habitats.

Based on a review of the literature on seabird censusing methodology, murres, and
murrelets, I identified time of day, distance from shore, water depth and tide as the most
important and tractable factors that may influence the distribution and abundance of
murres and murrelets. From 31 July through 27 September 1995, we conducted 60
surveys (figures 4-6) of the nearshore coastal waters of Washington. The location and
timing of these surveys were designed to measure the influence of these variables on the
distribution and abundance of murres and murrelets.

The results indicate that the density of murrelets decreases with both time of day (figures
7-9) and distance from shore (figures 10-11). Because depth is correlated, of course, with
distance from shore, it is not surprising that murrelets are found most frequently at a water
depth of about 40 feet (figure 12). The effect of distance from shore also is reflected in the
density distribution maps below (figures 13-14). Conversely, however, neither time of day
(figures 15-17) nor distance from shore (figures 18-20) had any significant effect on
distribution and abundance of murres. This also is reflected in the density distribution
maps below (figures 21-22).


40

[~~] 400 meters
1200 meters
P = 0.386

L

35

30

1

25 5

Density per Km?

15 +

Distance (meters from shore)

Figure 20. Summer density of Common Murres in relation to distance
from shore along the southern outer coast.


Density per km?

60

50 -| P=0.418

-
oO
L

oO
o
f
a

nN
fo}
1

10 =

—

) T T T T
early AM late AM early PM _ slate PM

Time of Day

Figure 17. Summer density of Common Murres in relation to time
of day along the southern outer coast.


INTRODUCTION

Washington Department of Fish and Wildlife (WDFW) was provided funds by the Tenyo
Maru Trustee’s Council to address two questions of concern: (1) what is the at-sea
distribution and abundance of Common Murres, Uria aalge, and Marbled Murrelets,
Brachyramphus marmoratus, on the “outer coast” of Washington (here defined as Port
Angeles west to Neah Bay and Tatoosh Island, and south to the Columbia River), and (2)
what at-sea habitats are preferred by Common Murres and Marbled Murrelets.

Objective 1: At-Sea Distribution and Abundance of Common Murres and Marbled
Murrelets

Specific tasks identified in the original project proposal include:

(1) Identify sampling locations in impact area by reviewing relevant literature and
interviewing biologists that have worked in the area.

(2) Develop Geographical Information System (GIS) software for the outer coast
similar to the system developed for the Puget Sound Ambient Monitoring
Program.

(3) Estimate abundance and distribution of murres and murrelets by both aerial and
boat transects in summer and winter.

(4) On the NOAA ship McArthur collect seabird abundance and distribution data.

PROGRESS TO DATE

Task 1

We have corresponded extensively with biologists that have experience working on (1)
Marbled Murrelets (hereafter murrelets) and/or Common Murres (hereafter murres), (2)
Pacific seabirds in general (from California to Alaska, including British Columbia), and (3)
biological issues regarding coastal Washington. This includes communications with most
state and federal natural resource agency biologists, academia, Pacific Seabird Group,
Colonial Waterbird Society, various Indian tribes (e.g., Makah), Northwest Indian
Fisheries Commission, and private environmental consultants (e.g., Steve Speich, Terry
Wahl, Tom Hamer). We have nearly completed an extensive search for relevant literature
on murres, murrelets, Pacific seabirds in general, and other literature regarding aspects of
data collection and analysis (for a list of bibliographic sources consulted to date, see Table
1). Most of this literature I either owned prior to joining WDFW or I have obtained in the
last few months.

Task 2

We also have developed appropriate GIS computer software for collecting and analyzing
abundance and distribution data. Dr. R. Glenn Ford of Ecological Consulting Inc.,
Portland, Oregon, was contracted by WDFW to develop this software. In fall of 1995,
prior to development of this software, WDFW consulted with Glenn about capabilities
that we wanted designed into the software. After he completed a preliminary version of
the software, we tested it in the field in January and February 1996 at which time we


including Gray’s Harbor and Willapa Bay. This pattern of abundance is correlated with
the distribution of rocky vs. sandy coastline and benthic substrate, and with the proximity
to nesting areas (old growth forest and Tatoosh Island for Marbled Murrelets and
Common Murres, respectively).

Future plans are discussed to (1) improve methodology by investigating effects of
other biotic and abiotic factors on Murre and Murrelet distribution and abundance, (2) use
GIS kelp, shoreline/benthic substrate structure, and bathymetry (water depth) databases to
determine the extent to which distribution and abundance of murres and murrelets are
correlated with these factors, and (3) evaluate the potential value and limitations of aerial
surveys.


Outer Coast
Boat Surveys
Gray's Harbor to
Columbia River

Figure 6. Transects conducted along the southern outer
coast from Gray’s Harbor south to the Columbia River.


Implications for Restoration

Repeatable and statistically valid sampling methods are essential in the analysis of at-sea
distribution of seabirds. If Tenyo Maru restoration activities are to include an at-sea
component, in terms of either monitoring changes in abundance, distribution, or habitat
use, or relating seabird recovery to fish abundance and distribution, valid methods for
counting and monitoring seabirds along the outer coast of Washington need to be tested
and established. We have begun to develop methods specifically designed for counting
murres and murrelets (discussed further under Objective 2 below). We anticipate that our
future research will allow us to improve and refine our preliminary methods into an
acceptable protocol suitable for long-term at-sea censusing of murres and murrelets in
Washington state and analyses of those distribution and abundance data. We suggest that
all future at-sea seabird work associated with the Zenyo Maru restoration should follow
these protocols, regardless of whether the work is being conducted by a trustee agency or
by other public or private organizations.

Data collected from planes should not be combined with data collected from boats unless
a substantially more accurate correction method than currently exists can be empirically
derived. Further, planes are not well suited for collecting at-sea data to address most
questions regarding at-sea abundance and distribution. However, use of planes may be
preferable for addressing large scale questions/problems, and in situations where it is
logistically prohibitive to use boats.

Future Plans

We will conduct aerial surveys in winter to get instantaneous overviews of the distribution
of murres and murrelets in February and March. Regardless of whether we can
quantitatively combine these data with our boat data, these data are a valuable
complement to our boat data and allow us to address many questions that can not
addressed from a single boat.

We also will study the seabird data collected on the McArthur in July 1995, and
incorporate it if possible into our database and analyses.

Although the analyses presented in this report are adequate in many respects, and are
statistically valid, more refined and statistically powerful analyses are possible. We will
complete these analyses this winter. In response to a presentation given at the 1995
annual meeting of Pacific Seabird Group in Victoria, B.C., WDFW was solicited by two
peer-reviewed journals, Colonial Waterbirds and Pacific Seabirds, to submit papers to
each for review and possible publication. Thus, we plan to do so.

Last, we will prepare a schedule indicating dates by which final products will be
completed.


Percent

30

25 4 (——) Observations
7 Total birds

20

15 +

10 4

“41-50. 61-70 81-100
31-40. 51-60 71-80 >100

Depth (feet)

Figure 12. Frequency of occurrence of Marbled Murrelets
in relation to water depth.



Distribution and Abundance of Marbled Murrelets and Common Murres in
Relation to Marine Habitat on the Outer Coast of Washington - An interim report

to the Tenyo Maru Trustee Council
February 1996

Christopher W. Thompson

Washington Department of Fish and Wildlife
600 Capitol Way North

Olympia, WA 98501


Future Plans

Using the software developed by Glenn Ford as well as WDFW GIS capabilities, we will
overlay our abundance and distribution data for murres and murrelets on GIS databases of
the distribution and abundance of (1) old growth forest, (2) shoreline/substrate structure,
(3) kelp, and bathymetry (water depth) data (available from NOAA). These analyses will
quantitatively indicate the strength of the correlation between abundance and distribution
of murres and murrelets and these physical/biotic parameters. We also will design our
winter sampling methodology to allow us to determine the extent to which these species,
especially murrelets, occur in or near kelp (Macrocystis and/or Nereocystis).

Weather permitting, during our winter field season (January through March), we will
repeat the transects we conducted along the outer Strait of Juan de Fuca to see if time of
day and distance from shore have similar effects on the density of murrelets and murres
that we observed during the summer. We also will survey as best we can the entire outer
coast, including Gray’s Harbor and Willapa Bay, to determine whether the winter
distribution and abundance of these species differs significantly from the patterns we
observed in summer and fall. In addition, it has been suggested that juvenile murrelets
prefer to stay in or near kelp. Thus, we will address this through analyses of our data
collected during (1) general sampling, (2) sampling designed specifically to look at
possible habitat preference by adults or juveniles for kelp, and (3) adult/juvenile ratio
sampling.


11

Task 3

Our data also indicate that murrelets are more numerous along the northern outer coast
and strait of Juan de Fuca than along the southern outer coast (figures 13-14). The reason
for this is unknown. However, this pattern of abundance appears to be correlated with (1)
proximity of old growth forest, (2) the distribution of rocky shoreline/substrate vs. sandy
shoreline/substrate, and (3) abundance of kelp (based on data in the kelp GIS database
provided to me by Tom Mumford, Washington Department of Natural Resources). More
sophisticated and detailed analyses of these relationships are currently underway in
collaboration with Tom Owens (WDFW, GIS specialist). The pattern of distribution and
abundance of murres is more complicated. This is likely due, at least partly, to northward
immigration in summer and fall of murres from Oregon (and possibly elsewhere). Murres
fledge from breeding colonies in Oregon in late June or early July, on average, and
disperse as far north as Cape Flattery by late July. In contrast, Washington murre colonies
do not fledge until early August or later.

Implications For restoration

Restoration of murres and murrelets requires an understanding of (1) resources that are
important to these species, and (2) the biological and physical environments in which these
resources are found. The potential influence of these resources and their physical and
biological environments, on seabird abundance and distribution must be understood before
a valid sampling methodology can be designed. If this is not done, the effects of these
factors on bird distribution and abundance will likely cause bird counts to vary much more
than they would in a sampling methodology that controlled for these factors. This has two
serious negative impacts: (1) Differences among counts may reflect differences among
counts in the factors mentioned above and not true differences in numbers of birds, and (2)
the large variation in the data reduces the probability of statistically detecting differences
in bird counts among treatment groups (e.g., seasons, years, locations, habitats).

Our results indicate that murrelets are most numerous early in the morning and close to
shore whereas murre densities do not change in relation to time of day or distance from
shore. However, because counts of murres are equally accurate (i.e., unbiased) at all
times of day and distances from shore, our results suggest that accurate indices of both
murres and murrelets can be obtained by conducting transects close to shore (200 or 400
meters) early in the morning.

In addition, both murrelets and murres occur at higher densities along the northern outer
coast and the Strait of Juan de Fuca than along the southern outer coast. In addition,
neither species occurs in substantial numbers in Gray’s Harbor or Willapa Bay - at least at
the time we sampled (September).

The analyses described above document the relative importance of some physical and
biological variables to these species. This provides us an preliminary guide for prioritizing
our restoration efforts for managing these resources accordingly.


90

80
7 (~~) 400 meters

1200 meters
P =0.564

70

60

1

50

1

40

L

Density per Km?

L

30

1

20

10 +

Distance (meters from shore)

Figure 19. Summer density of Common Murres in relation to distance
from shore along the northern outer coast.


Density per Km2

12
e
10 4
| Y = 0.002X + 0.814
eo R?=0.120
P =0.189
6 4
e
4 4
24
s 8 e 8
) T T T T
0 200 400 800 1200

Distance (meters from shore)

Figure 18. Summer density of Common Murres in relation to distance
from shore along the outer Strait of Juan de Fuca.


identified some changes that we wanted made to the data collection part of the software.
The modified software will be further evaluated in the field in February and March. If
necessary, the software will be modified further until it meets our requirements. The data
analysis portion of the program is very powerful (specific aspects discussed below). It
allows one to generate maps in various formats of the density and distribution of species
(e.g. Figures 13-14, 21-22). Data files can be imported directly into ARCINFO for
Geographic Information System (GIS) analyses (also discussed below).

Task 3

A necessary prerequisite for determining the distribution and abundance of any bird,
terrestrial or marine, is a valid methodology for counting them. This past summer, we
began to develop a preliminary protocol for counting murres and murrelets (discussed
further under section on “Differential Habitat Use” below). One of the most important
issues is whether to count birds from boats, planes, or both. The answer to this question
depends on the species of birds being counted, the questions for which the data are being
collected, and whether it is necessary to apply “correction factors” to plane data in order
to combine it with boat data. In general, for many reasons the use of planes to count
murrelets may not be advisable except in rare circumstances. This is so because murrelets
(1) are small and wary, often diving before they can be spotted from planes, (2) typically
do not associate with other species and usually occur as single birds or pairs (figure 1),
thereby making them more difficult to see than birds which tend to congregate in larger
groups, and (3) are often difficult to distinguish from other similar species (e.g., Pigeon
Guillemots) depending on the season.

T have analyzed bird count data collected simultaneously from boats and planes for the
Puget Sound Ambient Monitoring Program (provided by David Nysewander, Janet Stein
and Matthew Nixon). These empirical data clearly demonstrate that boat and air data can
not simply be combined for most, if any, species, including murres and murrelets. For
example, data on murrelets indicates that the ratio of birds counted on boats vs. planes
ranges from 24:1 to 0.5:1 (figure 2), and that the variation in this ratio differs with the
length of the transect (figure 3). This variation may be far too high to allow one to
combine boat and air data in a meaningful fashion, and indicates an urgent need for
additional research to address this issue.

Task 4

WDFW personnel other than myself and my crew conducted surveys of seabird
distribution and abundance on the NOAA ship McArthur in the summer of 1994 and had
already scheduled to do so again in July of 1995 prior to the beginning of our research
program on the outer coast. Therefore, we did not conduct surveys on the McArthur in
1995 because we thought to do so would simply duplicate already existing WDFW efforts
and would be an unwise use of Tenyo Maru funds.


Density per Km?

Morning
| [=] Afternoon
P=0.09
3 4
2 4
1-
0 -

Time of day

Figure 9. Summer density of Marbled Murrelets in relation to
time of day along the southern outer coast.


Density per Km?

12
e
10 4
R2=0.031
8 P=0.514
6 -
e
a4
e e
e
2-4 .
e e
8 ° e
0 T T T T

early AM lateAM~ earlyPM late PM

Time of Day
Figure 15. Summer density of Common Murres at four distances

from shore in relation to time of day along the outer
Strait of Juan de Fuca.


List of Figures and Tables

Table 1. Bibliographic sources consulted to identify literature regarding seabirds
(especially Common Murres and Marbled Murrelets) in Washington state and
measurement of their distribution and abundance.

Figure 1. Frequency of Marbled Murrelets in relation to their group size.

Figure 2. Ratio of number of Marbled Murrelets counted on transects conducted
simultaneously from both a boat and a plane.

Figure 3. Deviations of air:boat ratios from mean air:boat ratio data presented in figure 2.

Figure 4. Transects conducted along the outer Strait of Juan de Fuca and northern outer
coast from Cape Flattery south to Cape Alava.

Figure 5. Transects conducted along the southern outer coast from Hoh Head south to
Gray’s Harbor.

Figure 6. Transects conducted along the southern outer coast from Gray’s Harbor south
to the Columbia River

Figure 7. Summer density of Marbled Murrelets at four distances from shore in relation to
time of day along the outer Strait of Juan de Fuca.

Figure 8. Summer density of Marbled Murrelets in relation to time of day along the
northern outer coast of Washington.

Figure 9. Summer density of Marbled Murrelets in relation to time of day along the
southern outer coast of Washington.

Figure 10. Summer density of Marbled Murrelets in relation to distance from shore along
the outer Strait of Juan de Fuca.

Figure 11. Summer density of Marbled Murrelets in relation to distance from shore along
the northern outer coast of Washington.

Figure 12. Frequency of occurrence of Marbled Murrelets in relation to water depth.

Figure 13. Summer density distribution map of Marbled Murrelets along the outer Strait
of Juan de Fuca and the northern outer coast of Washington.

Figure 14. Summer density distribution map of Marbled Murrelets along the southern
outer coast of Washington.

Figure 15. Summer density of Common Murres at four distances from shore in relation to
time of day along the outer Strait of Juan de Fuca.

Figure 16. Summer density of Common Murres in relation to time of day along the
northern outer coast of Washington.

Figure 17. Summer density of Common Murres in relation to time of day along the
southern outer coast of Washington.

Figure 18. Summer density of Common Murres in relation to distance from shore along
the outer Strait of Juan de Fuca.

Figure 19. Summer density of Common Murres in relation to distance from shore along,
the northern outer coast of Washington.

Figure 20. Summer density of Common Murres in relation to distance from shore along
the southern outer coast of Washington.

Figure 21. Summer density distribution map of Common Murres along the outer Strait of
Juan de Fuca and the northern outer coast of Washington.

Figure 22. Summer density distribution map of Common Murres along the southern outer
coast of Washington.


Ratio of Marbled Murrelets Counted

(air:boat)

2.0 = e e

R*=0.043 |
1.5 5 P=0.044
e

e

e?
1.0 4 e 3 e
0.5 4
0.0 ~

0.0 0.5 1.0 1.5 2.0

Transect Coverage (km*)

Figure 2. Ratio of Marbled Murrelets counted on simultaneous air
and boat transects.


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Table of Contents

Cover Page..........cccccccccccecsecsesssesesetssecsssestsesuecsnecinssnecsuequisenceretssesssesseuecreeeaneestees 1
Acknowledgments.
Table of Contents
List of Figures and Table:
Executive Summary.
Introduction.........
Implications for Restoratio
Objective 1: At-Sea Distribution and Abundance of Common Murres

and Marbled Murrelets.. .7
Progress to Date. 7
Implications for restoration 9
Future Plans... : 9

Objective 2: Differential Use of Marine Habitats by Common Murres

and Marbled Murrelets 10
Progress to Date. 10
Implications for Restoration. ll
Future Plans. 12

13



MARBLED MURRELET
At-Sea Distribution

ly¥> Transect Data

0.0-0.10 /km2
010-0.25 /km2
025-050 /kime
| 0.50-1.00 /km2
1.00-2.50 /km2

Figure 13. Summer density distribution map of Marbled Murrelets along the
outer Strait of Juan de Fuca and northern outer coast of Washington.


Acknowledgments

First and foremost, I am extremely grateful to my crew: Bucky Barnett, Kirsten
Brennan, and Monique Wilson - all extremely dedicated, skilled, responsible, resourceful,
and personable. I also am indebted to the many other people in Washington Department
of Fish and Wildlife (WDFW) for their help in various aspects of this study: D. John
Pierce, Research Manager for WDFW, provided extensive logistical support and advice
throughout this study; the enforcement division generously allowed us to use their
enforcement vessel, the “G.H. Corliss,” stationed in Westport and captained by Dan
O’Hagen who was tremendously cooperative and helpful; Steve Jeffries very generously
allowed us use of his research vessel (“Research 4"), his vehicle for towing it, and all
associated equipment (e.g., computers) necessary for recording observations in the field;
his advice and cooperation were invaluable; Tom Owens, Tom Mumford, Dave
Nysewander, Ken Warheit, Matt Vander Haegen and many others also provided valuable
logistical support, advice and/or information. The Olympic Coast National Marine
Sanctuary (Todd Jacobs and Ed Bowlby) kindly allowed us use of their research vessel,
the “Tatoosh,” captained by George Galasso, to conduct seabird surveys. The U.S. Coast
Guard stations at Neah Bay, LaPush, and Westport all were extremely cooperative and
helpful by providing us with housing (Neah Bay), moorage and logistical support
(weather data, mechanical help, fuel, etc.). Drs. John Wingfield and Dee Boersma of the
University of Washington Department of Zoology (UW) generously provided me with
office space and logistical support (computers, phone, Fax, e-mail, postage/mail, supplies).
Dr. Julia Parrish (UW) has been a constant and reliable source of help and advice.


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Density per km

140

120 -
P =0.682

100 +

ie)
oO
i

60 +

40 4

20 +

T T T T

earlyAM late AM earlyPM late PM
Time of Day

Figure 16. Summer density of Common Murres in relation to time
of day along the northern outer coast.


Table 1. Bibliographic sources consulted to identify literature regarding seabirds
(especially Common Murres and Marbled Murrelets) in Washington state and
measurement of their distribution and abundance.

1, Biological Abstracts (1971 to present).

2. Zoological Record (1978 to present).

3. Wildlife Review (1971 to present).

4. Water Resources Abstracts (1967 to present).

5. Aquatic Sciences and Fisheries Abstracts (1978 to present).

6. Life Sciences Abstracts (1986 to present)

7. National Technical Information Service (1978 to present).

8. Dissertation Abstracts.

9. Duckdata (10,000+ references on ducks compiled by Don Delnicky, USFWS).

10. Strong, R. (1939-1959) A bibliography of birds. Vols. 1-4. Field Museum of Natural
History, Chicago, IL.

11. Coues, E. 1879. American ornithological bibliography, Third Installment
(taxonomically indexed).

8. Auk, American Ornithologists’ Union Monographs, Wilson Bulletin, Condor, and
Bird-Banding / Journal of Field Ornithology (1955 to present).

9. Ibis (1955 to present).

10. Cormorant / Marine Ornithology (Journal of the South African Ornithological
Society: Vol. 1 1976 to present).

11. Notornis (Journal of the New Zealand Ornithological Society, 1955 to present).

12. Recent Ornithological Literature (supplements to the Auk, Ibis and Emu: 1976 to
present), and annual lists of recent seabird literature published in Cormorant /
Marine Ornithology.

13. Journal of Wildlife Management (1937 - present), Wildlife Monographs (1958 -
present) and Wildlife Society Bulletin (1973 - present).

14. Transactions of the North American Wildlife and Natural Resources Conference (from
vol. 1, 1936 to present) .

15. Canadian Journal of Zoology, Ecology, Ecological Monographs, and Ecological
Applications (1945 - present), and Conservation Biology (from vol. 1, 1986 -
present).

16. Most major books and government documents (published and unpublished) regarding
seabird biology.


Deviation of air:boat ratio

from mean air:boat ratio

1.75 7

1.50 + e °
R?=0.037
1.25 5 P = 0.057
1.00 4
e
0.75 + ee
e
e e
0.50 — cece 8 oh e
ee
0.25 4 Zz)
0.00 +
t 1 T T T T
0.0 0.2 0.4 0.6 0.8 1.0

Relative transect length

Figure 3. Deviation of air:boat ratio from mean air:boat ratio data
presented in figure 2.