U.S. Department of the Interior

U.S. Geological Survey

Open File Report 2006–1387

Status Review of the Marbled Murrelet (Brachyramphus

marmoratus) in Alaska and British Columbia
COVER PHOTOGRAPH

A stylized form of a Marbled Murrelet (Brachyramphus marmoratus) adorns the top of a Tlingit Murrelet Hat, with feathering of human 

hair, and wings and tail cocked as if ready to dive. Two more murrelet images are carved onto the hat surface, each on opposite sides of a 

human face, and all upside down. Clan hats such as this one represent the history and strengths of the Kaagwaantaan Clan of southeast 

Alaska, the most powerful of the Tlingit Wolf moiety. This particular hat was acquired by Louis Shotridge from Daqu-tonk, the leader of the 

Kaagwaantaan Clan’s Drum House at the Alaskan village of Klukwan in the spring of 1917. The hat is much older. 

The Marbled Murrelet represents an important figure in Tlingit clan history and mythology. As a result, the Murrelet is represented on Tlingit 

clan regalia or clan at.oow (such as clan hats), and in Tlingit artwork. Some accounts that share the significance of the bird (who is often a 

being that combines animal and human forms) for the Tlingit people are available in English. “The First War in the World”, by J.R. Swanton in 

his Tlingit Myth and Texts (1909), is but one example. 

Even a cursory glance at just a few Tlingit resources indicates that today, as in the past, the Murrelet is a significant crest for several clans 

of the Eagle Moiety. The Naasteidí Clan of Kooyu Kwáan or Kuiu Island, holds the Murrelet and the Flicker as their crests, and has a house 

named the Ch’eet Hit (Murrelet House); the Nees.ádi Clan of Kake holds the Flicker, Killer Whale, and the Murrelet as their primary crests; the 

Wooshkeetaan Clan (in several Tlingit communities) holds the Shark, Wolf, Murrelet, Mud Shark, and Dog Fish as their important crests; the 

Yanyeidi Clan holds the Wolf, the Murrelet, Halibut, Hawk, Bear, Shark, and Marten as their important crests, and may have a Murrelet hat 

today. In addition, the Kagwaantaan (Wolf) Clan of Sitka has a house named Ch’eet Hit (Murrelet House). 

According to the Federal Register, another Murrelet Hat was repatriated in 1996 by the Eiteljorg Museum of Indianapolis. The hat was 

returned to the Brown Bear House of the Kaagwaantaan Clan. 

Information contributed by Lucy Fowler Williams, The Jeremy A. Sabloff Keeper, American Collections, University of Pennsylvania Museum.
Status Review of the Marbled Murrelet 

(Brachyramphus marmoratus) in Alaska 

and British Columbia

By J.F. Piatt, U.S. Geological Survey, K.J. Kuletz, U.S. Fish and Wildlife Service, 

A.E. Burger, University of Victoria, S.A. Hatch, U.S. Geological Survey, V.L. 

Friesen, Queen’s University, T.P. Birt, Queens University, M.L. Arimitsu, U.S. 

Geological Survey, G.S. Drew, U.S. Geological Survey, A.M.A. Harding, Alaska 

Pacific University, and K.S. Bixler, U.S. Geological Survey

Open-File Report 2006–1387

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

DIRK KEMPTHORNE, Secretary

U.S. Geological Survey

Mark D. Myers, Director

U.S. Geological Survey, Reston, Virginia: 2007

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reproduce any copyrighted materials contained within this report.

Suggested citation:

Piatt, J.F., Kuletz, K.J., Burger, A.E., Hatch, S.A., Friesen, V.L., Birt, T.P. , Arimitsu, M.L., Drew, G.S., Harding, A.M.A., 

and K.S. Bixler, 2007, Status review of the Marbled Murrelet (Brachyramphus marmoratus) in Alaska and British 

Columbia: U.S. Geological Survey Open-File Report 2006-1387, 258 p.
iii

Contents

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................2

Objectives and Focus of This Status Review ...................................................................................3

Background – Previous Studies of Marbled Murrelets in Alaska and British Columbia..........3

Conservation Status of Taxon......................................................................................................................4

Rangewide .............................................................................................................................................4

Canada....................................................................................................................................................4

National .........................................................................................................................................4

Provincial.......................................................................................................................................6

Other Designations in Canada...................................................................................................6

United States .........................................................................................................................................6

National .........................................................................................................................................6

State-Level....................................................................................................................................7

Other Designations in the United States..................................................................................7

Population Ecology and Characteristics of Murrelets in Alaska and British Columbia.....................7

Taxonomy ...............................................................................................................................................7

General Description..............................................................................................................................8

Geographic Distribution.......................................................................................................................8

North Pacific.................................................................................................................................8

British Columbia...........................................................................................................................9

Alaska. ...........................................................................................................................................9

Feeding Ecology....................................................................................................................................9

Food Habits ...................................................................................................................................9

Foraging Behavior......................................................................................................................13

Migration and Seasonal Movements .............................................................................................14

Molt. ..................................................................................................................................................15

Breeding Biology.................................................................................................................................15

Reproductive Success..............................................................................................................15

Timing of Breeding.....................................................................................................................19

Post-Breeding Dispersal ..........................................................................................................21

Site Fidelity and Natal Dispersal .............................................................................................21

Overwinter Occupation of Nesting Habitat ...........................................................................21

Natural Mortality ................................................................................................................................22

Disease........................................................................................................................................22

Predation.....................................................................................................................................22

Population Genetics ....................................................................................................................................22

Background..........................................................................................................................................22

New Analyses Using Samples from Washington and Oregon and Multiple Loci....................23

Methods................................................................................................................................................23

Sampling......................................................................................................................................23

DNA Preparation........................................................................................................................23

Introns. .........................................................................................................................................25
iv

Contents—Continued

Population Genetics–Continued

Methods–Continued

Microsatellites............................................................................................................................25

Population Genetic Structure ..................................................................................................27

Contemporary Gene Flow.........................................................................................................27

Results. ..................................................................................................................................................27

Genetic Variability......................................................................................................................27

Population Genetic Structure ..................................................................................................38

Contemporary Gene Flow.........................................................................................................41

Discussion............................................................................................................................................42

Genetic Viability .........................................................................................................................42

Population Genetic Structure ..................................................................................................42

Contemporary Gene Flow.........................................................................................................43

Genetic Units of the Marbled Murrelet..................................................................................43

Population Status and Trends....................................................................................................................43

Methods Used to Survey Murrelets ................................................................................................43

Sources of Error Associated with Boat-Based Surveys.....................................................44

Alaska Population...............................................................................................................................45

Alaska Population Estimates ...................................................................................................45

Alaska Population Trends.........................................................................................................47

British Columbia Population .............................................................................................................50

British Columbia Population Estimates ..................................................................................50

British Columbia Population Trends........................................................................................50

Demographics and Population Dynamics ...............................................................................................54

Survivorship, Fecundity, and Age at Maturity................................................................................54

Population Models..............................................................................................................................55

Previous Studies ........................................................................................................................55

A Deterministic Model of Population Growth—Program LIFE...........................................56

A Flexible Model of Population Growth—Program MATRIX..............................................57

Marine Habitat: Characteristics and Threats .........................................................................................68

Characteristics of Marine Habitats Used by Marbled Murrelets...............................................68

Meso-Scale Characteristics....................................................................................................68

Small-Scale Characteristics ....................................................................................................69

Marine Ecosystem Change ...............................................................................................................71

Threats in Marine Habitats ...............................................................................................................72

Oil Pollution.................................................................................................................................72

Incidental Take in Fisheries......................................................................................................78

Effects of Commercial Fishing on Prey ..................................................................................93

Effects of Vessel Disturbance..................................................................................................95

Vessel Activity in Alaska...........................................................................................................97

Effects of Research Activities .................................................................................................98
v

Contents—Continued

Nesting Habitat: Characteristics, Threats, and Trends .........................................................................99

Methods for Surveying Use of Terrestrial Habitats by Marbled Murrelets ............................100

General Nesting Habitat Characteristics......................................................................................101

Ground Nests............................................................................................................................103

Tree Nests .................................................................................................................................103

Stand-Level Habitat Characteristics ....................................................................................104

Landscape-Level Habitat Characteristics ...........................................................................105

Amount and Distribution of Nesting Habitat in Alaska and British Columbia.........................105

Southeast Alaska ....................................................................................................................107

South-Central Alaska ..............................................................................................................113

Southwest Alaska ...................................................................................................................115

British Columbia ......................................................................................................................116

Threats to Nesting Habitats ............................................................................................................118

Losses of Suitable Nesting Habitat from Timber Harvest .................................................118

Predation Effects .....................................................................................................................126

Effects of Natural Forest Processes ....................................................................................128

General Land Management Practices ........................................................................128

Habitat Reserves.............................................................................................................129

Nesting Habitat Projections...................................................................................................130

Southeast Alaska............................................................................................................130

South-Central Alaska .....................................................................................................130

British Columbia..............................................................................................................130

Ongoing Conservation Efforts..................................................................................................................132

Alaska. ................................................................................................................................................132

State of Alaska Efforts ............................................................................................................132

Efforts in the Tongass and Chugach National Forests ......................................................132

Oil Spill Prevention and Response........................................................................................133

Fisheries and Marine Habitat Conservation........................................................................133

Exxon Valdez Oil Spill Trustee Council .................................................................................133

Non-Governmental Entities....................................................................................................134

British Columbia................................................................................................................................134

Recovery Planning...................................................................................................................134

Provincial Recovery Actions..................................................................................................136

Other Efforts to Maintain Habitat in British Columbia .......................................................137

Discussion...................................................................................................................................................137

Factors Relevant to Definition of Distinct Population Segments .............................................137

Population Genetics ................................................................................................................138

Distribution................................................................................................................................138

Morphological, Behavioral, and Ecological Factors..........................................................138

International Boundary...........................................................................................................138
vi

Figures

Figure 1. Map showing distribution of Marbled Murrelets ....................................... 5

Figure 2. Diagram of breeding phenology of Marbled Murrelets from Alaska to California 

showing estimated onset, median dates, and endpoints of the incubation and 

nestling periods.............................................................................. 19

Figure 3. Graphs showing breeding phenology of Marbled Murrelets in Southeast Alaska 

deduced from observations of fish-holding adults and chicks at-sea ............... 20

Figure 4. Map showing approximate breeding distribution (shaded coastal areas), and 

origins and numbers of Marbled Murrelets sampled for genetic analyses ......... 24

Figure 5. Graph showing correlation between Wright’s linearized FST (=FST / [1 - FST])

and the natural logarithm of the shortest geographic distance between 

sampling sites (km) for Marbled Murrelets ............................................. 40

Figure 6. Graph showing probability of assignment of individual Marbled Murrelets 

(represented by vertical bars) to each of four genetic populations (represented 

by different colors) ........................................................................ 40

Contents—Continued

Discussion–Continued

Population Status and Trends in Alaska and British Columbia.................................................139

Anthropogenic Factors Influencing the Marbled Murrelet ..............................................141

Natural Factors Influencing the Marbled Murrelet ...........................................................142

Conclusion.................................................................................................................................143

Acknowledgments.....................................................................................................................................143

References Cited........................................................................................................................................145

Appendix A. Annotated Bibliography of Historical Information on Diet of the Marbled 

Murrelet in Alaska........................................................................................................................165

Appendix B. Source Code Listing (Javascript) for the Demographic Model LIFE.......................173

Appendix C. Source Code Listing (Fortran) for the Population Model MATRIX...........................177

Appendix D. Current Population Estimates—British Columbia......................................................189

Appendix E. Population Trends of the Marbled Murrelet Evident from At-Sea Surveys in 

British Columbia............................................................................................................................197

Appendix F. Comparison of Two Large-Scale Surveys for Brachyramphus Murrelets in 

Southeast Alaska..........................................................................................................................211

Appendix G. Population Trend of the Marbled Murrelet in Icy Strait, Southeast Alaska...........217

Appendix H. Population Trend of Brachyramphus Murrelets in Glacier Bay, Alaska ...............223

Appendix I. Change in Abundance of Brachyramphus Murrelets Along the Outer Gulf 

of Alaska Coast, Adjacent to Malaspina Glacier....................................................................231

Appendix J. Population Trend of Kittlitz’s and Marbled Murrelets in Prince William Sound ....233

Appendix K. Population Changes of Marbled Murrelet at Adak Island, Alaska..........................249

Appendix L. Probability of Assignment of Individual Marbled Murrelets to Each of Four 

Genetic Populations.....................................................................................................................253

Appendix M. U.S. Forest Service Nearshore Surveys, 1991 to 1995: Summary and 

Recommendations .......................................................................................................................257
vii

Figures—Continued

Figure 7. Map showing six Conservation Regions established by the Canadian Marbled

Murrelet Recovery Team (Bertram and others, 2003) for surveying and

managing Marbled Murrelets in British Columbia....................................... 51

Figure 8. Map showing location of sites where at-sea surveys were undertaken in

British Columbia ........................................................................... 52

Figure 9. Graphs showing examples of projected numbers for a population of 3,000

Marbled Murrelets with and without stochastic variation in survival and

fecundity .................................................................................... 60

Figure 10. Graphs showing variability of extinction times for a small population of

Marbled Murrelets (No = 3,000) when survival and fecundity are subject to

stochastic variation ........................................................................ 61

Figure 11. Graphs showing contributions of stochastic and density-dependent effects to

variability in population size ............................................................... 62

Figure 12. Graph showing stable-age distributions calculated by MATRIX for a stationary 

population of Marbled Murrelets (λ = 1) and another declining at the rate of 

2 percent per year ........................................................................... 63

Figure 13. Graphs showing expected distributions of trends over 10-, 20-, and 30-year 

intervals arising stochastically from interannual variation in the fecundity and 

survival of Marbled Murrelets, as modeled in program MATRIX ..................... 65

Figure 14. Graphs showing expected distributions of trends arising stochastically over 

10-, 20-, and 30-year intervals when interannual variation in fecundity and 

survival is comparatively high ............................................................ 66

Figure 15. Graphs showing expected distributions of trends arising stochastically over 10-, 

20-, and 30-year intervals when interannual variation in fecundity and survival 

is comparatively low ........................................................................ 67

Figure 16. Map showing Brachyramphus murrelet distribution in lower Cook Inlet in 

June 1993, relative to salmon fishing districts in the Cook Inlet area ............... 70

Figure 17. Graphs showing number of spills in coastal Alaska waters by month (top) and 

year (bottom), 1995–2005, for vessel-related spills and other spill sources ......... 76

Figure 18. Maps showing Alaska Department of Fish and Game salmon fishing districts 

for Aleutian Islands, Alaska Peninsula, Kuskowim, Bristol Bay, Cook Inlet, Kodiak, 

Prince William Sound, Yakutat, Juneau, Sitka, and Ketchikan Areas ............... 79

Figure 19. Diagrams showing commercial salmon fishing seasons in Alaska, for those 

fisheries using gillnets ..................................................................... 81

Figure 20. Graph showing salmon harvest in Alaska, 1878–2005 ................................. 83

Figure 21. Map showing Brachyramphus murrelet distribution in Prince William Sound 

in July 2005, relative to salmon fishing districts in the Prince William Sound 

Area .......................................................................................... 84

Figure 22. Map showing Brachyramphus murrelet distribution in Southeast Alaska in 

June and July 1994, relative to salmon fishing districts in the Southeast Areas ... 85

Figure 23. Map showing Department of Fisheries and Oceans salmon gillnet license Area 

C—areas 1–10, subarea 101–107 ......................................................... 91

Figure 24. Map showing Department of Fisheries and Oceans salmon gillnet license Area 

D—areas 11–15 and 23–27 ............................................................... 91

Figure 25. Map showing Department of Fisheries and Oceans salmon gillnet license Area 

E—areas 16–22, 28, 29 and 121 ............................................................ 92
viii

Tables

Table 1. Studies of Marbled Murrelet diet in Alaska ............................................. 11

Table 2. Diet of Marbled Murrelet in Alaska ...................................................... 12

Table 3. Percent frequency of occurrence of three primary prey types in adult seabird

diets in Prince William Sound in 1977–79, and in Prince William Sound and

Kachemak Bay in 1989–91 .................................................................. 12

Table 4. Marbled Murrelet nesting success based on directly observed outcomes at

nest sites in Alaska, British Columbia, Washington, Oregon, and California......... 16

Figures—Continued

Figure 26. Map showing outline of the Aleutian Islands Habitat Conservation Area and

other areas with trawl restrictions ...................................................... 95

Figure 27. Graph showing statistics on the fishery for euphausiids (krill) in British

Columbia .................................................................................... 96

Figure 28. Maps showing vessel traffic in western Prince William Sound, based on

studies by the U.S. Forest Service and the U.S. Fish and Wildlife Service ......... 98

Figure 29. Map showing forested and nonforested areas within the breeding range of

Marbled Murrelets in coastal Alaska ...................................................106

Figure 30. Map showing land management within the breeding range of Marbled

Murrelets in coastal Alaska ...............................................................108

Figure 31. Map showing Forest Inventory and Analysis (FIA) plot data from

south-central (n = 2,533) and Southeast Alaska (n = 2,463) ...........................110

Figure 32. Map showing Marbled Murrelet habitat suitability and marine density for

Southeast Alaska ...........................................................................112

Figure 33. Graph showing area of low nesting potential habitat (black) and high nesting

potential habitat (gray) for six habitat modeling scenarios in Prince William

Sound .......................................................................................116

Figure 34. Map showing land use of Afognak Island ................................................121

Figure 35. Map showing areas of logged and old growth forest on Afognak and Shuyak

Islands, Kodiak Archipelago as of 2000 ...................................................122

Figure 36. Satellite imagery showing loss of old seral rainforest in coastal British

Columbia by 1999 ...........................................................................124

Figure 37. Satellite imagery showing loss of old seral rainforest on Vancouver Island

(Sierra Club of Canada)......................................................................124

Figure 38. Maps showing estimated areas of suitable nesting habitat for Marbled

Murrelet on Haida Gwaii (Queen Charlotte Islands), showing the likely

changes between 1800 and 2000 .........................................................125

Figure 39. Graphs showing trends in numbers of murrelet predators observed on

Christmas Bird Counts in southern coastal British Columbia (Campbell River,

Comox, Deep Bay, Duncan, Ladner, Nanaimo, Pender Islands, Squamish,

Sunshine Coast, Vancouver, Victoria, White Rock) and in Southeast Alaska

(Craig, Glacier Bay, Haines, Juneau, Sitka) .............................................127

Figure 40. Map showing timber management and old-growth reserve land use

designations (LUD) in southern Southeast Alaska relative to density of

murrelets at sea..............................................................................131
ix

Tables—Continued

Table 5. Estimated probability that breeding radio-marked Marbled Murrelets from

Desolation Sound, British Columbia (1998–2001) reached successive stages

of reproduction .............................................................................. 17

Table 6. Nest outcomes (through mid-chick-rearing stage) inferred from activity

patterns of radio-marked murrelets in Desolation Sound and Clayoquot

Sound, British Columbia, 1998–2002 ...................................................... 17

Table 7. Marbled Murrelet abundance and productivity at three sites in Prince

William Sound, Alaska ..................................................................... 18

Table 8. Number of adult and juvenile Marbled Murrelets counted on survey routes in

Kachemak Bay, Alaska, August 1996...................................................... 18

Table 9. Genetic loci, PCR primer sequences, and annealing temperatures employed

in Marbled Murrelet population genetic analysis ....................................... 26

Table 10. Sample sizes (N), allele frequencies, allelic richness estimates (AR , corrected

for the minimum per-locus sample size), observed and expected heterozygosities 

(HO and HE , respectively) and Wright’s inbreeding coefficients (FIS) for 23 loci 

within 12 populations of Marbled Murrelets ............................................. 28

Table 11a. Number of pairs of loci (N) showing significant deviations from linkage

equilibrium for each of 12 sampling sites ................................................ 38

Table 11b. Number of sampling sites with significant deviations from linkage equilibrium

at a Bonferroni corrected a = 0.05 for pairwise comparisons of loci.................. 39

Table 12. Locus-specific estimates of global ΦST (for introns) or FST (for introns and

microsatellites) for Marbled Murrelets ................................................... 40

Table 13a. Estimates of shortest geographic distance (km; above diagonal), and FST for

all loci except Ald, Bma10-18 and Bma553 (below diagonal) for pairwise

comparisons of sampling sites ............................................................ 41

Table 13b. Estimates of ΦST for introns (below diagonal) and FST for microsatellites (above

diagonal) for pairwise comparisons of sampling sites ................................. 41

Table 14. Maximum value of ln Pr (X | k) from multiple runs of STRUCTURE for each

value of k (number of populations) from one to twelve ................................. 41

Table 15. Proportion of birds from different sites that were assigned to each of four

genetic populations by STRUCTURE ...................................................... 42

Table 16. Brachyramphus murrelet population estimates for areas in Alaska that have

been surveyed systematically ............................................................ 46

Table 17. Summary of changes in Brachyramphus murrelet populations at eight

different trend sites during summer in Alaska .......................................... 48

Table 18. Population estimates for British Columbia as reported by Burger (2002b) and

updated with new information (2006)...................................................... 50

Table 19. Summary of trends of Marbled Murrelet counts and densities at eight marine

transect routes in British Columbia ...................................................... 53

Table 20. Predicted population growth rates of Marbled Murrelets in Alaska using the

demographic model LIFE .................................................................. 57

Table 21. Summary of spills between 1979 and 2005 in coastal Alaska, by substance

category .................................................................................... 73

Table 22. Estimates of direct mortality of Brachyramphus murrelets from the Exxon

Valdez oil spill in Alaska in 1989............................................................ 74

Table 23. Summary of spills between 1979 and 2005 in Alaska, by subarea ..................... 75
x

Tables—Continued

Table 24. Recent 5-year average harvests, value, and permits fished for selected

Alaska commercial salmon fisheries...................................................... 86

Table 25. Salmon gillnet fishing regions, the 5-year average (2000–04) for number of

permits by region, and available data on Marbled Murrelet incidental take in

those fisheries .............................................................................. 87

Table 26. Summary of Marbled Murrelet tree nests in Alaska ....................................102

Table 27. Characteristics of Marbled Murrelet ground nests in Alaska ........................102

Table 28. Additional evidence of Marbled Murrelet nests in Alaska ...........................102

Table 29. Area (thousands of ha) and land ownership for areas within 60 km of of the

shore in southeast (SEAK), south-central (SCAK) and southwest (SWAK)

Alaska .......................................................................................109

Table 30. Generalized classification of vegetation and land cover in Southeast Alaska ......109

Table 31. Land area and management status (percent of current distribution) of

large-tree old growth forests among provinces in Southeast Alaska ...............111

Table 32. Habitat variables and suitability factors used to estimate the relative value of

Marbled Murrelet nesting stands in Southeast Alaska .................................111

Table 33. Habitat suitability for Southeast Alaska, based on forest cover and topology ......111

Table 34. Current condition and management status of nesting habitat for Marbled

Murrelets in Southeast Alaska ............................................................113

Table 35. Percent forest structural classes for the Chugach National Forest ..................114

Table 36. Nesting habitat variables used in the Prince William Sound Marbled Murrelet

habitat suitability model.....................................................................115

Table 37. Definition of polygon features that provide suitable nesting habitat for

Marbled Murrelet in British Columbia, as recommended by the Canadian

Marbled Murrelet Recovery Team.........................................................117

Table 38. Estimates of areas of likely nesting habitat for Marbled Murrelets in British

Columbia, 2000 ..............................................................................117

Table 39. Rate of logging for forest types potentially suitable for Marbled Murrelets on

the Tongass National Forest in Southeast Alaska .......................................119

Table 40. Distribution of productive old-growth forest types and percent of timber

harvest within 20 biogeographic provinces in Southeast Alaska .....................120

Table 41. Estimated timber harvest volume (million board feet, scaled post harvest) by

year and owner group, south-central Alaska, 1988 to 2001 ...........................121

Table 42. Changes in forest size class distribution of the Chugach National Forest

portion of the Kenai Peninsula from 1974–99.............................................122

Table 43. Area of old growth forest and logged land on Shuyak and Afognak Islands as

of 1999–2000 .................................................................................123

Table 44. Likely changes in the availability of moderate to very high quality nesting

habitat (habitat classes 1-3 combined; see Burger, 2002) for Marbled Murrelets 

in each forest district, and for the entire British Columbia coast .....................123
xi

Conversion Factors and Abbreviations, Acronyms, or 

Symbols 

Conversion Factors

SI to Inch/Pound

Multiply By To obtain

centimeter (cm) 0.3937 inch (in.)

cubic meter (m3

) 0.0008107 acre-foot (acre-ft) 

gram (g) 0.03527 ounce, avoirdupois (oz)

hectare (ha) 0.003861 square mile (mi2)

kilometer (km) 0.6214 mile (mi)

meter (m) 3.281 foot (ft) 

metric ton (Mt) 1.102 ton, short (2,000 lb)

millimeter (mm) 0.03937 inch (in.)

square kilometer (km2

) 247.1 acre

Inch/Pound to SI

Multiply By To obtain

acre 4047 square meter (m2

)

barrel (bbl), (petroleum, 

1 barrel = 42 gal) 0.1590 cubic meter (m3

)

cubic foot (ft3

) 0.02832 cubic meter (m3) 

foot (ft) 0.3048 meter (m)

gallon (gal) 3.785 liter (L) 

gallon (gal) 0.003785 cubic meter (m3

) 

gallon (gal) 3.785 cubic decimeter (dm3

) 

mile (mi) 1.609 kilometer (km)

mile, nautical (nmi) 1.852 kilometer (km)

pound, avoirdupois (lb) 0.4536 kilogram (kg) 

square mile (mi2

) 259.0 hectare (ha)

square mile (mi2

) 2.590 square kilometer (km2) 

ton, short (2,000 lb) 0.9072 megagram (Mg) 

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32.
xii

Conversion Factors and Abbreviations, Acronyms, or 

Symbols—Continued

Abbreviation, Acronym, or Symbol

Abbreviation, 

Acronym, or Symbol Meaning

ADEC Alaska Department of Environmental Conservation

ADFG Alaska Department of Fish and Game

ADNR Alaska Department of Natural Resources

AHY After-hatching-year (adult birds)

ANCSA Alaska Native Claims Settlement Act

ANILCA Alaska National Interest Lands Conservation Act

AOU American Ornithologists’ Union

BLM Bureau of Land Management (U.S.)

bp Base pair

CBC Christmas Bird Count

CLMP Chugach Land Management Plan

CMMRT Canadian Marbled Murrelet Recovery Team

COSEWIC Committee on the Status of Endangered Wildlife in Canada

CWS Canadian Wildlife Service

DBH (Tree) diameter at breast height

DFO Department of Fisheries and Oceans (Canada)

DPS Distinct Population Segment (U.S.)

EC Environment Canada

ENSO El Niño-Southern Oscillation

ESA Endangered Species Act (U.S.)

EVOS Exxon Valdez oil spill

EVOSTC EVOS Trustee Council

FAO Food and Agriculture Organizaiton (UN)

FIA Forest Inventory and Analysis

FPB Forest Practices Board (British Columbia)

FR Federal Register (U.S.)

FRPA Forest and Range Practices Act (British Columbia)

GBNPP Glacier Bay National Park and Preserve

HSI Habitat suitability index

HY Hatching-year (juvenile birds)

IUCN World Conservation Union

IWMS Identified Wildlife Management Strategy (British Columbia)
xiii

Conversion Factors and Abbreviations, Acronyms, or 

Symbols—Continued

Abbreviation, Acronym, or Symbol—Continued

Abbreviation, 

Acronym, or Symbol Meaning

KFNPP Kenai Fjords National Park and Preserve

LRMP Land and Resources Management Plan (Canada)

LUP Land Use Plans (Canada)

MMBF Million board feet

MMS Minerals Management Service (U.S.)

mtDNA Mitochondrial DNA

NFMA National Forest Management Act (U.S.)

NGO Non-governmental organization

NFMA National Forest Management Act (U.S.)

NGO Non-governmental organization

NMFS National Marine Fisheries Service (NOAA)

NOAA National Oceanographic and Atmospheric Administration (U.S.)

NPPSD North Pacific Pelagic Seabird Database

OCSEAP Outer Continental Shelf Environmental Assessment Program

OGMA Old Growth Management Area (British Columbia)

PCR Polymerase chain reaction

RIC Resource Inventory Committee (Canada)

SARA Species at Risk Act (Canada)

SSPC Single-stranded conformation polymorphism

TFL Tree Farm License

TLMP Tongass Land Management Plan

TTRA Tongass Timber Reform Act

USCG U.S. Coast Guard

USDOT U.S. Department of Transportation

USFS U.S. Forest Service

USFWS U.S. Fish and Wildlife Service

USGS U.S. Geological Survey

USNPS U.S. National Park Service

WHA Wildlife habitat area (British Columbia)
xiv

Marbled Murrelet in summer breeding (alternate) plumage (top, © Gerry 

Sanger/Sound Expressions), winter (basic) plumage (middle, Martin Renner), 

and juvenile plumage (bottom, Rich MacIntosh).
Abstract

The Marbled Murrelet (Brachyramphus marmoratus) 

is a small, diving seabird inhabiting inshore waters of the 

Northeastern Pacific Ocean. This species feeds on small, 

schooling fishes and zooplankton, and nests primarily on the 

moss-covered branches of large, old-growth conifers, and 

also, in some parts of its range, on the ground. We reviewed 

existing information on this species to evaluate its current 

status in the northern part of its range—Alaska (U.S.) and 

British Columbia (Canada). Within the southern part of 

its range (Washington, Oregon, and California, U.S.), the 

Marbled Murrelet was listed as a threatened species under 

the Endangered Species Act (ESA) in 1993, and the U.S. 

Fish and Wildlife Service (USFWS) needed information on 

the species throughout its range for ESA deliberations. We 

compiled published information on the conservation status, 

population biology, foraging ecology, population genetics, 

population status and trends, demography, marine and nesting 

habitat characteristics, threats, and ongoing conservation 

efforts for Marbled Murrelets in Alaska and British Columbia. 

We conducted a new genetic study using samples from a 

segment of the range that had not been included in previous 

studies (Washington, Oregon) and additional nuclear intron 

and microsatellite markers. We also analyzed available at-sea 

survey data from several locations for trend. To understand 

the reasonableness of the empirical trend data, we developed 

demographic models incorporating stochasticity to discern 

what population trends were possible by chance. The 

genetic studies substantially confirmed previous findings on 

population structure in the Marbled Murrelet. Our present 

work finds three populations: (1) one comprising birds in 

the central and western Aleutian Islands; (2) one comprising 

birds in central California; and (3) one comprising birds 

within the center of the range from the eastern Aleutians to 

northern California. Our knowledge of genetic structure within 

this central population is limited and it requires additional 

study. Compiling available abundance information, we 

estimated that in the recent past, Marbled Murrelets in Alaska 

numbered on the order of 1 million birds. We were unable 

to generate a similar estimate for historical population size 

in British Columbia. Using trend information from at-sea 

surveys spanning a wide geographic range in Alaska, murrelet 

numbers declined significantly at five of eight trend sites at 

annual rates of -5.4 to -12.7 percent since the early 1990s. 

Applying these rates of decline to the historical population 

estimate, the current murrelet population in Alaska is projected 

to be on the order of 270,000 birds. This represents an overall 

population decline of about 70 percent during the past 25 

years. In British Columbia, available trend data indicate that 

murrelet populations there have experienced similar declines. 

We updated a recent (2002) population estimate for British 

Columbia, concluding that there are now between 54,000 and 

92,000 murrelets in British Columbia. The rates of decline we 

observed are within, but at the high end of, a range of rates 

expected by chance. Given that declines were estimated for 

sites over essentially the entire northern range of the species, 

there is cause for concern about the species’ status. In their 

marine habitats, Marbled Murrelets overlap with salmon 

(Oncorhynchus sp.) gillnetting operations in British Columbia 

and in Alaska (especially in Prince William Sound and 

Southeast Alaska), and annual bycatch mortality is likely in 

the low thousands per year, although bycatch rates are difficult 

to measure. The species’ inshore distribution coincides 

with high levels of vessel traffic and makes them especially 

vulnerable to both chronic oil pollution and to catastrophic 

spills (e.g., the 1989 Exxon Valdez oil spill [EVOS] in southcentral Alaska, which is estimated to have killed 12,000 to 

15,000 murrelets). In their forested nesting habitats, Marbled 

Murrelets have lost about 15 percent of their suitable nesting 

habitat in Southeast Alaska, and 33 to 49 percent in British 

Columbia, from industrial-scale logging within the past half 

century. Increased predation also may be a threat to murrelet 

populations, related to fragmentation and edge effects from 

logging and development, and recent population increases 

Status Review of the Marbled Murrelet (Brachyramphus 

marmoratus) in Alaska and British Columbia

By J.F. Piatt1 , K.J. Kuletz2 , A.E. Burger3, S.A. Hatch1, V.L. Friesen4, T.P. Birt4, M.L. Arimitsu1, G.S. Drew1, A.M.A. 

Harding5

, and K.S. Bixler1

1

U.S. Geological Survey.

2 U.S. Fish and Wildlife Service.

3

University of Victoria, Victoria, British Columbia, Canada.

4

Queen’s University. Kingston, Ontario, Canada.

5

Alaska Pacific University, Anchorage, AK.
observed for some important murrelet predators, including 

Bald Eagles (Haliaeetus leucocephalus), Common Ravens 

(Corvus corax), and Steller’s Jays (Cyanocitta stelleri). 

Nesting habitat losses cannot explain the declines observed 

in areas where industrial logging has not occurred on a large 

scale (e.g., Prince William Sound) or at all (Glacier Bay). 

The apparent change in population size and rates of decline 

reported for the Marbled Murrelet are large, and we therefore 

considered alternative explanations and precedents for changes 

of similar magnitude in other marine wildlife populations 

in the Northeastern Pacific Ocean. The declines are likely 

real, and related to combined and cumulative effects from 

climate-related changes in the marine ecosystem (most likely 

the 1977 regime shift) and human activities (logging, gillnet 

bycatch, oil pollution). Much uncertainty about the decline 

could be alleviated by continuing to repeat boat surveys in 

Prince William Sound and lower Cook Inlet, and by repeating 

the boat survey of Southeast Alaska that was conducted 

in 1994. This survey used a statistically sound design and 

covered the region that has been and likely remains the center 

of the species’ abundance. Important questions remain to be 

addressed about methods for measuring population status and 

change, adult mortality (major sources, density dependence, 

seasonal concordance), and the movements of wintering 

populations. 

Introduction

The Marbled Murrelet is a member of the Auk family of 

diving seabirds. Like other members of this family, it feeds 

on schooling fishes in coastal waters, defers breeding until 

several years of age, and has a long life span. A successful 

breeding pair fledges only one chick per year. This species 

breeds from central California to the Aleutian Islands of 

Alaska, and is found in greatest abundance between Vancouver 

Island, British Columbia, and the Alexander Archipelago in 

Southeast Alaska. In contrast to other members of its family 

such as puffins (Fratercula sp.), the Marbled Murrelet does not 

breed on cliffs or in burrows on predator-free offshore islands. 

Rather, camouflaged adults nest on mossy-limbed branches of 

large conifers such as coast redwood (Sequoia sempervirens), 

western hemlock (Tsuga heterophylla), Douglas fir 

(Pseudotsuga menziesii), and Sitka spruce (Picea sitchensis), 

usually in mainland old-growth stands located within 60 km 

of marine waters. Some murrelets nest on the ground at higher 

altitudes, on mossy cliff ledges in British Columbia, and on 

treeless islands of Alaska, laying eggs on bare talus slopes in 

mountainous terrain. 

Marbled Murrelet populations are believed to be 

threatened by logging of old-growth nesting habitat, oil 

pollution, and bycatch in fishing gear (Nelson, 1997), and 

also are influenced by natural changes in marine ecosystems 

(Becker and Beissinger, 2005). Current populations in 

Washington, Oregon, and California are small (tens of 

thousands) relative to the combined historical population of 

British Columbia and Alaska (hundreds of thousands). Owing 

to small population size, threats, and negative population 

trends, the U.S. Fish and Wildlife Service (USFWS) listed 

the Washington, Oregon, and California population of 

Marbled Murrelet as threatened under the ESA in 1993. In 

British Columbia, the murrelet was listed as threatened by 

the Canadian Federal government in 1990 because of loss of 

breeding habitat and declining populations, and that status 

was renewed in 2000. The status of populations in Alaska 

and British Columbia has been less clear and is the subject 

of this review. The USFWS did not list the Alaska murrelet 

population when it listed the Washington, Oregon, and 

California murrelet population because, in relation, Alaska had 

a large murrelet population and there was no information on 

murrelet population trends. 

In 2003, the USFWS initiated a 5-year review of the 

status of the murrelet population in Washington, Oregon, and 

California. This work was conducted by EDAW, Inc., with 

the assistance of Hamer Environmental, L.P., and consisted of 

a review of available scientific information plus a regulatory 

review (McShane and others, 2004). Based on the EDAW, 

Inc., report, the USFWS concluded that the population of 

Marbled Murrelets in Washington, Oregon, and California 

did not satisfy the criteria for designation as a Distinct 

Population Segment (DPS) under the USFWS’s 1996 DPS 

policy. The original listing determination for the Marbled 

Murrelet was made prior to the USFWS’s 1996 DPS policy. 

That policy states that DPS designations made prior to the 

1996 policy would be reviewed as a part of any 5-year review. 

In September 2004, the USFWS announced its intention to 

pursue delisting the murrelet in Washington, Oregon, and 

California.

Based on its analysis that the Washington, Oregon, and 

California murrelet population did not qualify as a DPS, the 

USFWS decided to conduct a status review of the species 

throughout its range. The questions of whether the population 

in Washington, Oregon, and California constitutes a significant 

portion of the species’ population throughout its entire range, 

or whether the species as a whole is at risk of extinction, 

must be addressed before any action is made to change the 

status of the murrelet as a Threatened Species under the ESA. 

Delisting or reclassifying the Marbled Murrelet under the ESA 

will require a separate rulemaking, involving public notice 

and comment. In September 2006, the USFWS removed 

94 percent of previously designated Critical Habitat in 

Washington, Oregon, and California from that protective status 

provided under the ESA (U.S. Fish and Wildlife Service, 

2006).

2 Status Review of the Marbled Murrelet in Alaska and British Columbia
Objectives and Focus of This Status Review

In March 2006, we were asked by the USFWS to review 

the status of the Marbled Murrelet in Alaska and British 

Columbia using existing information available from published 

papers, finalized agency reports, and pertinent archived 

datasets. We were asked to address the following specific 

topics:

1. Conservation status of the species; 

2. Population ecology and characteristics of the 

species; 

3. Habitat characteristics and trends; 

4. Range and distribution; 

5. Population status and trends, including information 

on genetic diversity; 

6. Threats to populations; and 

7. Ongoing conservation efforts. 

Under the category of population ecology, we were asked 

to include descriptions of populations that may qualify as 

DPSs under the ESA, and to address any geographic, genetic, 

or other barriers relative to the Discreteness Test within the 

ESA DPS Policy.

Background – Previous Studies of Marbled 

Murrelets in Alaska and British Columbia

Prior to this report, the most recent compilation of 

information on Marbled Murrelets in Alaska was the U.S. 

Forest Service (USFS) status assessment, “Ecology and 

Conservation of the Marbled Murrelet” (Ralph and others, 

1995a). That volume included several chapters on Marbled 

Murrelets in Alaska, including chapters on population 

status (Piatt and Naslund, 1995), inland habitat use (Kuletz 

and others, 1995c), inland activity patterns (Naslund and 

O’Donnell, 1995), food habits (Burkett, 1995), and threats 

to populations (Carter and Kuletz, 1995; Carter and others, 

1995; Fry, 1995). That volume also contained assessments 

of marine and inland habitat use by Marbled Murrelets in 

British Columbia (Burger, 1995a, 1995b). At that time, we 

knew far more about the ecology of murrelets in Alaska than 

British Columbia because a large effort to study murrelets 

was initiated in Prince William Sound after the 1989 Exxon 

Valdez oil spill (EVOS) (e.g., Kuletz, 1996; and dozens of 

reports and publications associated with this work; see Piatt, 

2005). Little research continued in Alaska after direct support 

for Marbled Murrelet research by the EVOS Trustee Council 

(EVOSTC) ended in 1995, except for work on population 

genetics (Friesen and Piatt, 2003) and their marine ecology 

(Kuletz, 2005). Murrelets also were surveyed by the USFWS, 

the U.S. Geological Survey (USGS), and the U.S. National 

Park Service (USNPS) in various at-sea survey programs (e.g., 

Irons and others, 2000; Stephensen and Andres, 2001; Robards 

and others, 2003; Lindell, 2005). Recent investigations by the 

Alaska Department of Fish and Game (ADFG) have resulted 

in new insights on vessel disturbance (Agness, 2006) and 

foraging behavior (M. Kirchoff, Alaska Department of Fish 

and Game, unpub. data, 2006) in Southeast Alaska. Research 

was initiated in the Tongass National Forest during the early 

1990s (e.g., Brown and others, 1999; Smith and Harke, 

2001), but because the bird was not listed as Threatened in 

Alaska at the time of listing of populations in Washington, 

Oregon, and California (1993), and with apparently abundant 

populations in Alaska, no conservation strategy was developed 

for murrelets in the Tongass (DeGange, 1996). We found a 

few reports of U.S. Forest Service (USFS) work on murrelets 

(Piatt, 2005), but much data resides at the district level, largely 

unanalyzed. 

In contrast to Alaska, little was known about the 

biology of Marbled Murrelets in British Columbia prior 

to the 1995 Conservation Assessment (Ralph and others, 

1995a), but much has been learned since that time. Early 

research was summarized by Rodway (1990), Rodway and 

others (1992), and Burger (1995a, 1995b). The first Canadian 

Marbled Murrelet Recovery Strategy (Kaiser and others, 

1994) was primarily an analysis of research needs and data 

gaps. Following the listing as Threatened by the Canadian 

Federal government, and as Red-Listed by the provincial 

government, research and monitoring activities increased 

greatly in British Columbia in the 1990s. This included 

notable contributions from the Centre for Wildlife Ecology 

at Simon Fraser University, the Canadian Wildlife Service 

(CWS), the University of Victoria, the British Columbia 

ministries of Environment and Forests, Parks Canada, and 

several non-governmental organizations (NGOs). The 

British Columbia forest industry initiated large inventory 

and monitoring programs in many of the coastal forests. 

Much of the research in British Columbia followed methods 

developed in Washington, Oregon, and California, or Alaska 

(e.g., audio-visual surveys, at-sea transects, forest vegetation 

analysis), but there also has been pioneering work on radiotelemetry, demographics, movements at-sea, using radar for 

landscape-level habitat analyses and population monitoring, 

interpretation of aerial photography, and low-level helicopter 

assessments of forest habitat. Following a review by Hull 

(1999b), the murrelet’s Threatened Status in Canada was 

confirmed in 2000, as noted above. This was followed by a 

Conservation Assessment in 2001–03 comprising a biological 

review (Burger, 2002), management guidelines published by 

the Canadian Marbled Murrelet Recovery Team (CMMRT; 

Bertram and others, 2003), and a risk model (Steventon 

and others, 2003). Information from British Columbia also 

was included in the McShane and others (2004) review. To 

meet the requirements of Canada’s 2002 Species at Risk Act 

(SARA), a new Canadian Marbled Murrelet Recovery Strategy 

has been completed and is under review, and Recovery Action 

Plans are being developed. 

Introduction 3
In summary, most of what is known about the terrestrial 

ecology and breeding biology of murrelets in Alaska and 

British Columbia is derived from work started in the early 

1990s. Much of that work has been reported or published. We 

reviewed those findings in this document, and synthesized 

it with more recent knowledge from studies in Washington, 

Oregon, and California. We reconsidered historical diet 

information in light of extensive new data from the 1990s 

that has never been published. We conducted a new analysis 

of genetic information, including samples from birds in 

Washington and Oregon, and information from additional 

markers. Most data on murrelet population abundance and 

trends have not been compiled or published since 1995 in 

Alaska or since 1999 in British Columbia. We compiled, 

verified, and analyzed several relevant datasets, to develop 

new and current population estimates for Alaska and British 

Columbia, and we examined trends in those populations. 

We created the first explicit models of murrelet population 

dynamics in Alaska. We reviewed knowledge of the marine 

ecology of the species, and compiled information on threats 

in the marine environment. We also compiled information on 

forest habitat use and trends in forest habitat for the major 

forested areas occupied by murrelets. We reviewed ongoing 

conservation efforts. We conclude the report with discussion 

that focuses on two topics: (1) factors relevant to designation 

of DPSs for the Marbled Murrelet; and (2) factors that could 

explain the widespread population declines we observed. 

We refer to many place names in Alaska and British 

Columbia throughout the document, as we cite the various 

studies on murrelets and their habitats. To aid the reader, we 

provide a general locator map in figure 1. 

Conservation Status of Taxon

Rangewide

There are two primary NGOs that evaluate the 

global status of animal populations by using a number of 

scientific criteria: the World Conservation Union (IUCN) 

and NatureServe (Gardenfors and others, 1999). For the 

last four decades, the IUCN, through its Species Survival 

Commission, has been assessing the conservation status of 

species and subspecies on a global scale to highlight taxa 

threatened with extinction. The IUCN “Red Data Book” was 

produced to provide scientists with objective, scientifically 

based information on the current status of globally threatened 

biodiversity. The IUCN “Red List of Threatened Species” 

provides taxonomic, conservation status, and distribution 

information on taxa that have been evaluated globally 

using the IUCN “Red List Categories and Criteria” (World 

Conservation Union, 2001, 2004). The evaluations are 

designed to determine the relative risk of extinction. Those 

taxa facing a higher risk of global extinction are listed as 

Critically Endangered, Endangered, and Vulnerable.

The Marbled Murrelet was listed as Vulnerable in 2000 

and the status changed to Endangered in 2004. The species 

was last assessed in 2005 and is still considered Endangered 

(World Conservation Union, 2004; BirdLife International, 

2005). This species was still considered abundant, but was 

treated as Endangered because its population was estimated 

to have undergone a very rapid reduction, greater than 50 

percent in the last three generations (36 years), owing to a 

variety of threats. The assessment states that the decline was 

likely to continue and therefore the population was considered 

to be facing a very high risk of extinction in the wild. Some 

of the major threats listed for the population included habitat 

loss from timber harvest, accidental mortality from fisheries 

bycatch, and water pollution (oil spills).

NatureServe is a non-profit conservation NGO that 

provides scientific information to help guide conservation 

actions. NatureServe and its network of natural heritage 

programs provide information concerning rare and endangered 

species, and threatened ecosystems. NatureServe uses alphanumeric codes to rank the vulnerability of species it evaluates. 

The global status of the Marbled Murrelet was listed as G3G4 

in January 2001 (NatureServe, 2006). A G3G4 rank indicates 

that there was roughly an equal chance of G3 or G4 rank 

and that other ranks were much less likely. A G3 rank means 

the population was considered vulnerable and at a moderate 

risk of extinction due to a restricted range, relatively few 

populations, recent and widespread declines, or other factors. 

The G4 rank means the population was considered secure, 

uncommon but not rare, but there were some cause for longterm concern due to population declines or other factors. 

Threats listed for the population included habitat loss due to 

logging, oil spills, and gillnet fisheries (NatureServe, 2006).

Canada

National

In Canada, the Marbled Murrelet is protected under the 

Migratory Birds Convention Act, which affords protection to 

the bird itself and active nest sites, but nesting and foraging 

habitats are not otherwise protected by this act. The species 

was first listed as Threatened by the Committee on the 

Status of Endangered Wildlife in Canada (COSEWIC) in 

1990, following a review by Rodway (1990). This status was 

confirmed by COSEWIC in 2000, following a review by Hull 

(1999b). The first Recovery Strategy was completed in 1994 

(Kaiser and others, 1994) and focused primarily on identifying 

knowledge gaps for research. Loss of nesting habitat in forests 

was identified as the primary threat in Canada, and oil spills 

and gillnets were identified as significant secondary threats 

(Rodway, 1990; Hull, 1999; Bertram and others, 2003).

4 Status Review of the Marbled Murrelet in Alaska and British Columbia
Figure 1. Distribution of Marbled Murrelets.

Breeding

At Sea

0 400km200

Scale

British

Columbia

Cook

Inlet

Kodiak

Island

Prince

William

Sound

Glacier Bay

Icy Strait

Juneau

Vancouver

Vancouver

Island

Haida Gwaii

(Queen Charlotte

Islands)

Aleutian

Islands

Bering

Sea

Kenai

Fjords

Pacific

Ocean

Alaska

Alaska

Peninsula

Seattle

San Francisco

Anchorage

Southeast

Alaska

SARA came into effect in June 2003 and applies to all 

Federal lands in Canada, all wildlife species listed as being 

at-risk, and their critical habitat. The Marbled Murrelet was 

included on Schedule 1, the official list of wildlife species 

at-risk, because it was listed as Threatened by COSEWIC. 

Once listed, the measures to protect and recover a listed 

wildlife species are implemented. Under SARA, the Canadian 

Federal government has to approve a Marbled Murrelet 

Recovery Strategy by 2007, which will identify critical habitat 

and define the species’ “residence,” which are the two key 

elements afforded to habitat protection in this act.

The Recovery Strategy has been drafted, largely based 

on the guidelines published by the CMMRT (Bertram and 

others, 2003), but the Recovery Strategy is still under review 

by the Canadian and British Columbia governments. Under 

SARA, the Recovery Strategy has to identify one or more 

Conservation Status of Taxon 5
Recovery Action plans that will provide the details and timing 

of recovery implementation. The CMMRT has decided to draft 

three Recovery Action plans: (1) Population Status and Trend 

Monitoring; (2) Nesting Habitat Retention; and (3) Marine 

and Mortality Issues. By November 2006, the Nesting Habitat 

Retention Action Plan had been drafted and was under review 

by the Canadian and British Columbia governments. The other 

two Recovery Action plans have yet to be drafted and are not 

anticipated to be completed within the next year. Details of 

the Recovery Strategy, associated Recovery Action plans, and 

their implementation schedules are not available. 

In Canada, the Marbled Murrelet also is protected by the 

Canada National Parks Act (2000), where the species occurs 

in Gwaii Haanas, Pacific Rim, and Gulf Islands national park 

reserves.

Provincial

Marbled Murrelet is on the British Columbia Red List 

(i.e., a species legally designated or being considered for 

legal designation as Endangered or Threatened), and is one 

of the Identified Wildlife species within the British Columbia 

Forest and Range Practices Act (FRPA). The FRPA contains 

a number of provisions that contribute to managing Marbled 

Murrelet nesting habitat. FRPA Section 5 requires forest 

stewardship plans to be consistent with objectives set by 

the provincial government for a range of values including 

wildlife, biodiversity, soils, visual quality, water, and fish, 

all of which may contribute in part to managing Marbled 

Murrelet nesting habitat. FRPA Section 7 further defines the 

amount, distribution, and attributes of areas for the survival 

of species at-risk and regionally important wildlife. Notices 

under FRPA Section 7 are established for each forest district 

by the British Columbia Minister of Environment, and 

include objectives for Marbled Murrelet habitat. In practice, 

protection of Marbled Murrelet nesting habitat under FRPA is 

applied through the Identified Wildlife Management Strategy 

(IWMS). This establishes measures for selected species and 

plant communities that have been designated under the Forest 

Practices Code as Identified Wildlife.

Based on recommendations from the CMMRT (Bertram 

and others, 2003), IWMS measures for the maintenance of 

nesting habitat for Marbled Murrelets were adopted in 2004 

(Identified Wildlife Management Strategy [British Columbia], 

2004). The IWMS measures are the principal regulations 

governing maintenance of murrelet nesting habitat within 

forests designated as timber lands in British Columbia and 

provide fine-filter management of habitat. Identified Wildlife 

are managed through the establishment of wildlife habitat 

areas (WHAs), general wildlife measures, and wildlife habitat 

area objectives, or through other management practices, such 

as Old Growth Management Areas (OGMAs). Application 

of the IWMS is greatly hampered by the limit placed on 

its timber impacts by the Provincial Chief Forester: only 

1 percent of mature forest, by area, of each forest district 

is allocated to the IWMS. As of November 2006, 124 

Marbled Murrelet WHAs had been established, amounting to 

18,400 ha1, which amounts to about 2 percent of the habitat 

required to maintain 70 percent of the provincial population 

(Dechesne-Mansiere, 2004).

Much larger areas of habitat have been protected in 

parks under the 1996 British Columbia Parks Act, the 2000 

Protected Areas of British Columbia Act, and the regional 

Land and Resources Management Plans (LRMPs). These 

include extensive tracts in Carmanah-Walbran Provincial and 

Strathcona parks, and recently protected areas proclaimed 

under the north and central coast LRMPs. Currently about 

25-30 percent of estimated area of suitable nesting habitat in 

British Columbia falls within protected areas (T. Chatwin and 

M. Mather, British Columbia Ministry of Environment, unpub. 

data, 2006).

Other Designations in Canada

The species is ranked by NatureServe (2006) as N2 

(Imperiled) within Canada, and as S2B (Imperiled – Breeding 

Population) and S4N (Apparently Secure – Non-Breeding 

Population) within British Columbia.

United States

National

In September 1992, the Washington, Oregon, and 

California population of Marbled Murrelets was listed as 

Threatened under the ESA of 1973, as amended (57 FR 

45328). The listing decision was based on the determination 

that the Marbled Murrelet was Threatened from: (1) loss and 

modification of nesting habitat (older forests), primarily due 

to commercial timber harvesting; (2) mortality associated with 

gillnet fisheries off the Washington coast; and (3) mortality 

resulting from oil pollution. In 1996, the USFWS designated 

Critical Habitat in Washington, Oregon, and California. 

Critical Habitat included 32 Critical Habitat Units in 

Washington, Oregon, and California that were considered 

essential to the conservation of the species (U.S. Fish and 

Wildlife Service, 1996). Most of these Critical Habitat Units 

were located on Federal lands and almost entirely within LateSuccessional Reserves. A recovery team was formed in 1993, 

with a recovery plan produced in 1997 (U.S. Fish and Wildlife 

Service, 1997). A primary objective of the Marbled Murrelet 

recovery plan was to stabilize the population at or near current 

levels by maintaining and/or increasing productivity, and 

removing and/or minimizing threats to survivorship (U.S. Fish 

and Wildlife Service, 1997). 

1

Available at http://www.env.gov.bc.ca/cgi-bin/apps/faw/wharesult.

cgi?search=show_approved.

6 Status Review of the Marbled Murrelet in Alaska and British Columbia
State-Level

On a State government-level, the species is considered 

Threatened in Washington and Oregon, and Endangered in 

California. At this time, the Marbled Murrelet in Alaska has 

no special status with the State of Alaska. 

Within Alaska, there is an additional conservation status 

rating of Marbled Murrelets, which relates specifically to the 

species’ recovery from the EVOS. As part of the Restoration 

Plan, the EVOSTC maintains a list of resources and services it 

considers to have been injured by the spill (“Injured Resources 

and Services List”), and they periodically update the list 

when new information becomes available to show which 

species or services they consider to be: (1) Recovered; (2) Not 

Recovering; (3) Recovering; or (4) Unknown. Based on the 

initial impact of the spill, which killed an estimated 7 to 12 

percent of the murrelets in the spill area (Kuletz, 1996), the 

Marbled Murrelet was listed as an Injured Species. Recently, 

the recovery status of Marbled Murrelet was changed to 

Unknown (Exxon Valdez Oil Trustee Council, 2006) from the 

Recovering status on the 2002 List. The EVOSTC finds that 

breeding Marbled Murrelet populations in Prince William 

Sound (the main spill area) are in decline, but that the relation 

of the declines to the spill are unclear. They noted that there 

are no differences in population trends between populations in 

oiled and unoiled areas, and that other factors, such as climate 

and shifts in prey, are the most likely drivers of murrelet 

population dynamics (Integral Consulting, Inc., 2006).

Other Designations in the United States

The National Audubon Society developed a WatchList 

that identifies bird species that are facing population declines 

and/or threats such as habitat loss on their breeding and 

wintering grounds, or those species with limited geographic 

ranges (National Audubon Society Watchlist, 2002). The 

WatchList is an independent conservation status assessment of 

bird species that occur within the U.S. and some protectorates. 

Audubon has used two independent assessments published 

by BirdLife International (2005) and Partners In Flight 

(Panjabi and others, 2005) to place species in one of three 

conservation categories: Red, Yellow, or Green. The Marbled 

Murrelet was placed in the Red category, which represents 

species considered to be declining rapidly, having very small 

populations or limited ranges, and facing major conservation 

threats.

The National Audubon Society Watchlist (2002) states 

that Marbled Murrelets face three major threats. The greatest 

threat was considered to be logging of old-growth nesting 

habitat along the Pacific Coast. Because of its habit of feeding 

close to shore, this species also was considered to be highly 

vulnerable to oil spills. In addition, the WatchList states that 

large numbers of murrelets also are killed in Alaska on an 

annual basis as the result of gillnet fishing mortality.

Population Ecology and 

Characteristics of Murrelets in 

Alaska and British Columbia

In this section, we review the literature on the general 

biology and population ecology of Marbled Murrelets, 

focusing where possible on information derived from studies 

in Alaska and British Columbia. We provide a general 

description of the species, and review taxonomy, geographic 

distribution, migration and seasonal movements, and molt. We 

summarize feeding ecology, describing what is known about 

diets, spatial and temporal variability in diets, and foraging 

behavior and habitats. We turn then to a detailed description of 

breeding biology and natural mortality factors. 

Taxonomy

Marbled Murrelets belong to the family Alcidae 

(Auks), within the order Charadriiformes (Strauch, 1985). 

Phylogenetic relations within the Alcidae have been described 

using both genetic and morphological evidence (Strauch, 

1985; Moum and others, 1994; Pitocchelli and others, 1995; 

Friesen and others, 1996a). There are now three recognized 

species within the genus Brachyramphus: the Marbled, LongBilled (B. perdix), and Kittlitz’s (B. brevirostris) murrelets. 

The Marbled Murrelet breeds only in western North America, 

from California north to Alaska (wintering rarely to Baja, 

California and in only one recorded instance, wintering in 

northeastern Russia); the Long-Billed Murrelet breeds only in 

eastern Russia (wintering south to Japan, Korea, and China, 

with vagrants occurring widely in North America and rarely 

to Europe); and the Kittliz’s Murrelet breeds only in Alaska 

and eastern Russia, rarely wintering south to California and 

Northern Japan (Sealy and others, 1982; Brazil, 1991; Nelson, 

1997; Gaston and Jones, 1998; Day and others, 1999; Burger, 

2002; Nelson and others, 2002).

There has been an interesting classification history of 

the Long-Billed and Marbled Murrelet. Although originally 

considered separate species in the 18th and 19th centuries, 

with the Long-Billed Murrelet known as the “Partridge 

Murrelet,” the American Ornithologists’ Union (American 

Ornithologists’ Union, 1957) later declared them conspecifics. 

They remained as two subspecies until the mid-1990s, when 

molecular studies showed them to be distinctly different and 

probably genetically isolated for 5 to 6 million years (Friesen 

and others, 1996a, 1996b). These studies prompted recognition 

as separate species again in 1997 (American Ornithologists’ 

Union, 1997) and this status remains today.

Population Ecology and Characteristics of Murrelets in Alaska and British Columbia 7
General Description

The Marbled Murrelet is a fairly small alcid. Body length 

is 23-25 cm, wing length 122-149 mm, and adults typically 

weigh 188-269 g (Nelson, 1997; McShane and others, 2004). 

There is no pronounced difference in size between sexes (i.e., 

adults are sexually monomorphic in size). Marbled Murrelets 

are similar in appearance and size to Kittlitz’s and LongBilled Murrelets. Compared to Kittlitz’s Murrelets, Marbled 

Murrelets have a longer bill and darker plumage. They are 

much lighter in color with a shorter bill than the Long-Billed 

Murrelet (Friesen and others, 1996b).

Marbled Murrelets have a small black bill, dark brown 

eyes, and legs and toes that range from pink to dark gray with 

black webbing in between (Carter and Stein, 1995; Nelson, 

1997). Adults are sexually monomorphic. The species has 

distinctly different Basic (winter), Alternate (breeding), 

and Juvenal plumages (Carter and Stein, 1995). Breeding 

(Alternate plumaged) birds are dark brownish-black above, 

with rusty margins on the back feathers (Carter and Stein, 

1995). The underparts and sides are lighter and mottled 

brown. Rectrices (tail feathers) and upperwing-coverts are 

dark brown. Underwing-coverts and axillaries are gray-brown, 

and undertail coverts are white (Nelson, 1997). This cryptic 

speckled-brown plumage is almost certainly an adaptation for 

their solitary nesting habits, and need for camouflage against 

both mammalian and aerial predators when at nest sites. In 

contrast, winter-plumaged (Basic) birds have gray margins on 

their back-feathers and predominantly white scapulars. The 

underparts of wintering birds are pale, usually white, although 

brown / gray flecking may still be present on the flanks and 

sides. Wintering birds have white sides of the head, a nearly 

complete white collar, and white on the scapulars (Carter and 

Stein, 1995; Nelson, 1997).

Juvenal plumage is very similar to adult winter plumage, 

but the underparts are speckled with thin blackish-brown 

spots, and the gray margins are less visible. The white collar 

and scapular-patch of juveniles also are less distinct than in 

winter adults. Individuals that have recently fledged are darker 

overall, and it takes 2 weeks to 2 months for the juveniles to 

become lighter, the dark neck-band to disappear, and the dark 

brown flecking on the feather margins to become replaced by 

gray. During this stage, it is difficult to distinguish juveniles 

from winter-plumaged adults (Carter and Stein, 1995; Nelson, 

1997). The single chick has thick yellow to grayish-yellow 

down that is spotted with black and brown on its upperparts, 

and gray on its underparts. It remains in this downy state until 

just prior to fledging (Binford and others, 1975; Gaston and 

Jones, 1998). 

There is considerable diversity in nesting habitat and 

degree of coloniality among the Alcids (Gaston and Jones, 

1998). For example, whereas Common Murres (Uria aalge) 

usually breed at high density in exposed habitat such as 

cliff-ledges or low-lying flat islands, the Marbled Murrelet 

typically nests solitarily in older trees, on the open ground, on 

cliffs, and, rarely, in deciduous trees (Day and others, 1983; 

DeGange, 1996; Bradley and Cooke, 2001). From British 

Columbia to California, nesting occurs primarily in old-growth 

forest. In southern Alaska, breeding habitats are varied but 

are primarily trees in forested areas of that coastline. On 

the Alaska Peninsula and in the Aleutian Islands, however, 

all nesting is on the ground because trees are absent. Their 

secretive behavior and dispersed nest sites have made Marbled 

Murrelets hard to study, and most of our current understanding 

stems from work conducted since the 1990s when there was 

an explosion of studies related to the economic significance of 

their old-growth nesting habitat (Carter and Morrison, 1992; 

Ralph and others, 1995a; Nelson, 1997; Gaston and Jones, 

1998).

All alcids pursue their prey beneath the water using 

wing-propelled diving, but, unlike penguins (family 

Spheniseiformes), they have retained their ability to fly. 

The shape of their wing and body structure reflect this 

compromise, with wing area reduced to decrease underwater 

drag, breast muscles well-developed for underwater 

“flight,” and wing-loading (ratio of body mass to wing area) 

consequently high. To overcome this constraint, alcids have 

a characteristic rapid, flapping aerial flight. Although their 

wings are longer, narrower, and more pointed than other alcids 

(Nelson, 1997), Marbled Murrelets have high wing-loading, 

and use high flight speeds to maintain lift and stay airborne 

(Nelson, 1997; Burger, 2002). In their radar study of murrelets 

on the Olympic Peninsula (Washington), Cooper and others 

(2001) calculated a mean flight speed of 92.2 ± 19.1 km/hr 

(n = 311; range = 56-153 km/hr). The Marbled Murrelet is 

one of the most vocal alcids at sea, with four general types of 

vocalization: a piercing ‘keer-like call;’ a ‘whistle-like call;’ a 

‘groan-like call;’ and short ‘chip’ calls (Nelson, 1997; Gaston 

and Jones, 1998).

Geographic Distribution

North Pacific

Marbled Murrelets are distributed along the Pacific coast 

of North America, with birds breeding from central California 

through Oregon, Washington, British Columbia, southern 

Alaska, westward through the Aleutian Island chain, with 

presumed breeding as far north as Bristol Bay (Nelson, 1997; 

Gaston and Jones, 1998; Burger, 2002; fig. 1). Historically, 

most of the murrelet population was located in British 

Columbia (8 percent) and Southeast Alaska (71 percent; 

McShane and others, 2004). Current population estimates 

suggest a much lower proportion for Southeast Alaska (about 

42 percent) and a higher proportion for British Columbia 

(about 19 percent; see section, “Population Status and 

Trends”). The wintering range encompasses the breeding 

range but also extends into southern California, and rarely to 

Baja California, Mexico (Nelson, 1997; McShane and others, 

2004).

8 Status Review of the Marbled Murrelet in Alaska and British Columbia
British Columbia

Marbled Murrelets appear to breed throughout coastal 

British Columbia, although in varying densities (Burger, 

1995b, 2002b). High densities of murrelets occur at-sea during 

the breeding season on the west coast of Vancouver Island, 

in Desolation Sound on the southern mainland, in some of 

the inlets along the central and northern mainland coast, and 

on Haida Gwaii (Queen Charlotte Islands; Burger, 2002). 

Breeding populations are greatly reduced in the Georgia 

Depression (east coast of Vancouver Island and southern 

mainland) due to reductions in nesting habitat associated with 

urbanization, agriculture, and forestry (Burger, 2002). The 

long fjords that characterize the British Columbia mainland 

do not appear to be used by many murrelets, with higher 

concentrations found in nearshore waters at the mouths of 

inlets that are more exposed to the open sea. 

The winter range in British Columbia is poorly known. 

There is certainly some seasonal migration within the 

province, and between British Columbia and Washington, but 

the extent of movements is unclear, with variable numbers 

of murrelets found in nearshore waters near the breeding 

grounds all year (Rodway and others, 1992; Carter and Stein, 

1995; Burger, 1995b, 2002b; Beauchamp and others, 1999). 

Year-round counts in Barkley Sound, southwest Vancouver 

Island show consistently low numbers (less than 10 percent 

of summer mean) from late July through March. Numbers in 

more sheltered waters in the Strait of Georgia and surrounding 

inlets show increases in winter (Burger, 1995b, 2002b). 

Murrelets do not overwinter in the open ocean off British 

Columbia in significant numbers (Morgan and others, 1991; 

Burger and others, 2004b). The Strait of Georgia appears to be 

an important wintering ground (G. Kaiser, Canadian Wildlife 

Service, unpub. data, 2006), and might include murrelets from 

Alaska, although this has not been proven.

Alaska

Marbled Murrelets breed on the Aleutian Islands, from 

the Near (Attu), Andreanof (Adak, Atka, Kagalasta), and Fox 

(Unalaska) island groups east to the Alaska Peninsula, Cook 

Inlet, Kodiak, the Kenai Peninsula, and Prince William Sound, 

and south through the Alexander Archipelago in Southeast 

Alaska (Nelson, 1997). Limited breeding is presumed to occur 

as far north as northern Bristol Bay. Despite that broad range, 

breeding areas are largely concentrated in three important 

areas: the Kodiak Archipelago, Prince William Sound, and 

the Alexander Archipelago (Piatt and Ford, 1993). There are 

a few spring and summer records of birds observed north 

and west of the Alaska Peninsula – Bristol Bay, and Pribilof, 

St. Lawrence, Diomede, and Idlidlya (northern coast of 

Chukotski Peninsula, Russia) islands (Bédard, 1966; Bartonek 

and Gibson, 1972; Sealy and others, 1982). The wintering 

range is poorly known (see section, “Migration and Seasonal 

Movements”). Many birds appear to remain near breeding 

sites throughout the year, whereas others move offshore or to 

other inshore protected waters. Wintering areas include the 

Kodiak Archipelago, Cook Inlet, Prince William Sound, and 

the Alexander Archipelago, and out to 300 km in the Gulf of 

Alaska (Piatt and Naslund, 1995). It is a casual winter visitor 

to the Pribilof Islands (Hanna, 1920; Kessel and Gibson, 

1978).

Feeding Ecology

Food Habits

The diets of Marbled Murrelets have been previously 

summarized by Sanger (1983), Carter (1984), Burkett (1995), 

DeGange (1996), Nelson (1997), and McShane and others 

(2004). Major differences in diet between summer and 

winter have been recorded, with birds preying primarily on 

small schooling fish such as Pacific sand lance (Ammodytes 

hexapterus), northern anchovies (Engraulis mordax), Pacific 

herring (Clupea harengus), capelin (Mallotus villosus), and 

osmerids during the summer season. Invertebrates (e.g., 

euphausiids and mysids) become more common in their diets 

during the winter and spring (Munro and Clemens, 1931; 

Sanger, 1987; Vermeer, 1992; Burkett, 1995; Nelson, 1997). 

Seasonal changes in diet may reflect both prey availability and 

preference (DeGange, 1996). Marbled Murrelets in some areas 

also forage to some degree on salmon smolt (Oncorhynchus 

spp.) in freshwater lakes during the summer. Freshwater 

foraging most likely occurs in British Columbia and Southeast 

Alaska, where there are large coastal lakes with relatively 

large numbers of small fish near nesting habitat (Carter and 

Sealy, 1986; Hobson, 1990; McShane and others, 2004).

In addition to seasonal variation in prey choice, there also 

are striking differences between adult and chick diets (Sealy, 

1975; Carter, 1984; Carter and Sealy, 1987; Mahon and others, 

1992; Burkett, 1995; Jones, 2001; Kuletz, 2005). Chicks 

typically are fed single large subadult or adult fish (typically 

larger sand lance, immature herring, and occasionally salmon 

smolt) that have higher energy value than juvenile and larval 

age classes of fish (Robards and others, 1999c). For example, 

Marbled Murrelets in Prince William Sound selected larger 

fish of higher energy content (81-135 mm, 1+ age class) for 

their chicks, whereas they fed themselves on large numbers 

of smaller (< 80 mm, 0+ age class) prey items (Kuletz, 2005). 

This pattern also was found for murrelets in Barkley Sound, 

British Columbia (Carter, 1984; Carter and Sealy, 1987, 1990). 

This foraging behavior is consistent with optimal foraging 

theory (McArthur and Pianka, 1966) and is observed in many 

other fish-eating alcids (e.g., Wilson and others, 2005). Chicks 

may require high-value prey for growth and development, 

and it is more beneficial for parents to deliver fewer, highquality meals to their offspring because of the transport costs 

associated with provisioning in central place foragers (Orians 

and Pearson, 1979). In addition, Marbled Murrelets face a 

significant risk of predation when delivering food to their 

Population Ecology and Characteristics of Murrelets in Alaska and British Columbia 9
offspring (Marks and Naslund, 1994; Nelson, 1997; Kuletz, 

2005), so it is to their advantage to minimize the number of 

trips to feed young. Despite predation risk, however, some 

adults will make multiple feeding trips in one morning to feed 

the chick (Carter and Sealy, 1986; Nelson, 1997).

Seasonal and age-related sources of variability must 

be taken into account when comparing Marbled Murrelet 

dietary studies. Prey destined for the chick versus parental 

consumption usually can be distinguished based on the fishcarrying behavior of individuals (Carter and Sealy, 1990). 

Parents feed themselves early in the day before flying to other 

areas to find food specifically for their chick (Carter and Sealy, 

1990). Large prey items destined for the chick are usually 

caught at dawn, dusk, and possibly at night, when they are 

more abundant and easily caught near the surface of the water 

(Carter and Sealy, 1990; Kuletz, 2005). Most trips to the nest 

to feed chicks occur in the early morning, mainly pre-dawn, 

but as much as 1 to 2 hours after sunrise. Parents sitting in 

nearshore waters with prey in the bill during the evening 

hours may either wait until early morning or occasionally 

may make an evening trip to provision their chick (Carter and 

Sealy, 1987; Bradley and others, 2002; Speckman and others, 

2004; Kuletz, 2005). In contrast, adults rarely hold prey for 

themselves at the surface of the water, and mostly ingest their 

prey under water (Mahon and others, 1992; Kuletz, 2005). 

Sightings of adults holding prey for themselves are therefore 

brief and sample sizes minimal.

Most studies on chick diet have focused on field 

observations of prey held by parents on the water prior to 

delivery to the nest (Carter, 1984; Kuletz, 2005), although 

some prey have been viewed on video cameras at nests. 

Studies of adult diet have used a variety of methods including: 

(1) analysis of stomach contents from collected birds (e.g., 

Sealy, 1975; Carter, 1984); (2) stable isotope analysis (e.g., 

Hobson, 1990); and (3) sampling of fish at foraging sites 

(e.g., Ostrand and others, 2004; Henkel and Harvey, 2006). 

There are inherent biases and problems associated with all 

three methods. Observation and species identification of 

fish-holding individuals at-sea are likely to be biased towards 

larger prey items that protrude farther from the bill. Stomach 

analysis often involves empty stomachs and digested prey 

remains, especially when birds are collected later in the day. 

Larval fish and soft-bodied invertebrate species may not be 

detected because of rapid digestion. Stable-isotope analysis 

enables a time-integrated estimate of assimilated food, and can 

provide a powerful, non-lethal tool to assess and compare the 

proportion of prey taken from different trophic levels (Hobson 

and others, 1994). This method is most useful when used in 

unison with other conventional methods that allow for species 

and age class determinations of prey. Finally, the interpretation 

of co-occurrence of fish schools and foraging murrelets 

involves assumptions about actual prey selection. Given these 

important sources of variation, we include details of season 

(winter vs. summer) and age class of murrelet (adult vs. chick) 

in reviewing the Alaska diet studies shown in table 1.

Alaska Diet

There have been a number of systematic and 

opportunistic studies on murrelet diet in Alaska (table 1), 

and these studies are described in detail in appendix A. The 

adult diet of Marbled Murrelets in Alaska is highly diverse 

(appendix A). The important prey species include Pacific 

herring, Pacific sand lance, pollock, and cod (Gadidae). 

Although sample sizes are minimal and murrelets in many 

areas have not been sampled at all, there is growing evidence 

for spatial, temporal, and age-related differences in diet. 

Similar to conclusions made in other summaries (e.g., Burkett, 

1995), Alaska studies demonstrate differences in Marbled 

Murrelet diet between winter and summer months, with 

birds feeding more on invertebrates during the winter and 

fish during the summer (e.g., Krasnow and Sanger, 1982). 

Differences between the diet of adults and chicks also were 

found, with chicks having lower prey diversity and larger, 

more high quality prey items than adults (e.g., Carter, 1984; 

Kuletz, 2005).

Spatial Variability

Probably the most comprehensive spatial comparison 

of Marbled Murrelet diet in Alaska comes from collections 

of birds in the early to mid-1990s (Piatt and Anderson, 

1996; J. Piatt, U.S. Geological Survey, unpub. data, 2006; 

table 2). Pollock, cod, and sand lance generally were the 

most important prey taken by murrelets collected across a 

wide geographic range. Despite this generalization, there also 

were geographic differences in diet. For example, myctophid 

fishes were an important component of the diet of birds from 

Icy Strait (Southeast Alaska) in the 1990s (J. Piatt, U.S. 

Geological Survey, unpub. data, 2006), presumably because 

of their abundance in this region (Abookire and others, 2002; 

J. Piatt, U.S. Geological Survey, unpub. data, 2006). Marbled 

Murrelet diet also differs on a more local scale. For example, 

Krasnow and Sanger (1982) found that adult Marbled 

Murrelets were eating very different prey in two areas of the 

Kodiak Archipelago. In Izhut Bay at Afognak Island, birds 

were feeding primarily on capelin, while birds in northern 

Sitkalidak Strait at Kodiak Island (about 120 km to the south), 

were feeding mostly on Thysanoessa inermis. Similarly, 

Kuletz (2005) found that Prince William Sound murrelets 

were feeding their chicks primarily on sand lance near Naked 

Island, whereas birds near Jackpot Bay (about 50 km away) 

fed their chicks mostly herring (appendix A). These studies 

highlight the breadth, flexibility, and generalist nature of adult 

murrelets’ diet, and the influence that local prey availability 

has on diet.

10 Status Review of the Marbled Murrelet in Alaska and British Columbia
Table 1. Studies of Marbled Murrelet diet in Alaska.

[Details of each study are provided in appendix A. Abbreviations: vis. obs., visual observation]

Study Study year(s) Location Month Murrelet 

age class Sample size Method

Sangster and others (1978) 1977 Prince William Sound May to Sept. Adult 8 Stomach

Oakley and Kuletz (1979) 1978 Prince William Sound May to Aug. Adult 14 Stomach

Krasnow and Sanger (1982) 1976–1977 Chiniak Bay, Kodiak Dec. to Apr. Adult 18 Stomach 

Krasnow and Sanger (1982) 1978 Chiniak Bay, Kodiak February Adult 16 Stomach 

Krasnow and Sanger (1982) 1978 Izhut Bay, Kodiak Apr. to Aug. Adult 25 Stomach 

Krasnow and Sanger (1982) 1978 North Sitkalidak Strait, Kodiak May to Aug. Adult 17 Stomach 

Sanger (1983) 1969–1978 Overview

Sanger (1987) 1977–1978 Katchemak Bay Jan. to Apr. Adult 18 Stomach

Day and Nigro (2000) 1996–1998 Prince William Sound May to Aug. Adult/nestling 40 vis. obs.

Kuletz and Labunski (U.S. Fish and 

Wildlife Service, unpub. data, 2006)

2004–2006 Katchemak Bay June to Aug. Adult 57 vis. obs.

Kuletz and Labunski (U.S. Fish and 

Wildlife Service, unpub. data, 2005)

2005 Katchemak Bay August Chick 16 vis. obs.

Kuletz (2005) 1997–1999 Naked, Prince William Sound June to Aug. Chick 62 vis. obs.

Kuletz (2005) 1997–2000 Jackpot, Prince William Sound June to Aug. Chick 310 vis. obs.

Piatt (U.S. Geological Survey,

 unpub. data, 2006)

1989–1996 Central-West Aleutians June to Sept. Adult 19 Stomach

Piatt (U.S. Geological Survey, 

unpub. data, 2006)

1989–1997 East Aleutians June to Sept. Adult 23 Stomach

Piatt (U.S. Geological Survey, 

unpub. data, 2006)

1989–1998 Alaska Peninsula June to Sept. Adult 52 Stomach

Piatt (U.S. Geological Survey, 

unpub. data, 2006)

1989–1999 Cook/Kodiak June to Sept. Adult 58 Stomach

Piatt (U.S. Geological Survey, 

unpub. data, 2006)

1989–2000 Prince William Sound June to Sept. Adult 43 Stomach

Piatt (U.S. Geological Survey, 

unpub. data, 2006)

1989–2001 Southeast Alaska June to Sept. Adult 35 Stomach

Newman and others (2006) 2005 Port Snettisham, SE Alaska June Chick 4 Dipnet during 

prey school 

Temporal Variability

Seasonal and spatial variability in Marbled Murrelet 

diets complicates our ability to detect dietary change over 

time—ideally, diets should be compared from the same sites 

and during the same times of year. For example, Krasnow 

and Sanger (1982) were able to show inter-annual variability 

in the diet of Marbled Murrelets on Kodiak Island. In winter 

1976 –77, diet was dominated by capelin, and smaller amounts 

of euphausiids and smelts, whereas the diet of winter 1978 

was dominated by mysids (Krasnow and Sanger, 1982; 

appendix A). Changes in Marbled Murrelet diet among years 

and across broad regions in Alaska are thought to reflect the 

‘regime shift’ that occurred in the North Pacific Ocean during 

the late 1970s (Anderson and Piatt, 1999; see section, “Marine 

Habitat: Characteristics and Threats”). For example, there was 

a near absence of capelin in the diet of Marbled Murrelets 

collected along the Alaska Peninsula and around Kodiak in 

the early 1990s (J. Piatt, U.S. Geological Survey, unpub. data, 

2006; table 2). In contrast, capelin were a common component 

of diets during the summer for murrelets collected along the 

Alaska Peninsula and around Kodiak in the 1970s–1980s (Piatt 

and Anderson, 1996; appendix A). Similarly, there is evidence 

that changes in the Prince William Sound marine ecosystem 

in the 1980s negatively affected fish-eating birds (DeGange, 

1996; Kuletz and others, 1997). Marbled Murrelets ate mostly 

sand lance during the late 1970s, whereas they started to feed 

almost entirely on lipid-poor gadids from 1989 to 1991, with 

capelin disappearing as a dietary item (DeGange, 1996; Kuletz 

and others, 1997; table 3).

British Columbia Diet

In British Columbia, murrelets have a diverse diet, 

but small schooling fish and large pelagic crustaceans 

(euphausiids, mysids, and amphipods) are the main prey 

items (see summaries by Sealy, 1975; Carter, 1984; Vermeer 

and others, 1987; Burkett, 1995; Nelson, 1997; Day and 

Nigro, 2000). The most common fish are Pacific sand lance, 

northern anchovy, immature Pacific herring, capelin, and smelt 

(Hypomesus sp.). Squid (Loligo spp.), immature salmon, and 

eulachon (Strongylura exilis) also are taken in some areas.

In British Columbia, the most common prey species is 

sand lance (Burkett, 1995). In many areas, the distribution, 

abundance, and movements of murrelets seem closely linked 

to those of sand lance, especially during the murrelet’s 

breeding season (Sealy, 1975; Carter; 1984; Mahon and 

others, 1992; Haynes and others, 2004). Little is known about 

Population Ecology and Characteristics of Murrelets in Alaska and British Columbia 11
Table 2. Diet of Marbled Murrelet in Alaska.

[From Piatt and Anderson 1996; J. Piatt, U.S. Geological Survey, unpub. data, 2006. Percent: Percent number examined and number empty are calculated 

using the total number of birds examined. Percent frequency of occurrence, number of individuals, and estimated wet weight are calculated using the number of 

birds containing prey items. Invertebrates: Includes copepods and squid. Other: Includes sculpin (Cottidae), flatfish (Pleuronectidae), and unidentified fish; 

Abbreviations: g, gram]

Central-Western 

Aleutians

Eastern

Aleutians

Alaska

Peninsula

Cook/

Kodiak

Prince

William

Sound

Southeast 

Alaska Total

n Percent n Percent n Percent n Percent n Percent n Percent n Percent

Number examined 19 8 23 10 52 23 58 25 43 19 35 15 230 100

Number empty 0 0 11 5 22 10 2 1 15 7 5 2 55 24

Frequency of Occurrence

Invertebrates 0 0 2 17 0 0 2 4 0 0 1 3 5 3

Capelin (Mallotus villosus) 0 0 0 0 0 0 10 18 0 0 2 7 12 7

Lanternfishes (Myctophidae) 0 0 0 0 0 0 0 0 0 0 17 57 17 10

Pollock and cod (Gadidae) 7 37 8 67 13 43 6 11 24 86 2 7 60 34

Sand lance (Ammodytes 

hexapterus)

11 58 2 17 9 30 31 55 2 7 7 23 62 35

Other 1 5 0 0 8 27 7 13 2 7 1 3 19 11

Numbers of Individuals

Invertebrates 0 0 30 44 0 0 2 1 0 0 1 1 33 4

Capelin (Mallotus villosus) 0 0 0 0 0 0 22 14 0 0 2 1 24 3

Lanternfishes (Myctophidae) 0 0 0 0 0 0 0 0 0 0 174 88 174 23

Pollock and cod (Gadidae) 25 31 35 51 90 70 20 13 122 96 5 3 297 39

Sand lance (Ammodytes 

hexapterus)

54 68 3 4 14 11 92 60 3 2 15 8 181 24

Other 1 1 0 0 25 19 17 11 2 2 1 1 46 6

Estimated Wet Weight (g)

Invertebrates 0 0 <1 3 0 0 4 1 0 0 2 <1 7 <1

Capelin (Mallotus villosus) 0 0 0 0 0 0 43 10 0 0 4 <1 47 3

Lanternfishes (Myctophidae) 0 0 0 0 0 0 0 0 0 0 406 87 406 28

Pollock and cod (Gadidae) 31 28 18 64 175 83 15 4 194 87 3 <1 435 30

Sand lance (Ammodytes 

hexapterus)

80 72 9 33 25 12 354 83 30 13 50 11 548 37

Other <1 <1 0 0 11 5 9 2 <1 <1 <1 <1 20 1

Table 3. Percent frequency of occurrence of three primary prey types in adult seabird diets in Prince William 

Sound in 1977–79, and in Prince William Sound and Kachemak Bay in 1989–91.

[From Kuletz and others, 1997. Prey type: Other prey types or unidentified items not included]

Prey type

1977–79 1989–91

Prince William Sound Prince William Sound Kachemak Bay

Pigeon 

guillemot

Marbled 

Murrelet

Blacklegged 

Kittiwake

Tufted 

Puffin

Common 

Murre

Marbled 

Murrelet

Marbled 

Murrelet

n = 40 n = 27 n = 10 n = 8 n = 8 n = 27 n = 13

Ammodytes hexapterus 20 41 40 0 50 7 92

Osmeridae and Clupeidae 0 11 40 100 0 0 0

Gadidae 18 15 10 13 75 89 15

12 Status Review of the Marbled Murrelet in Alaska and British Columbia
the distribution, densities, diurnal and seasonal movements, 

or, in fact, any aspect of the biology of this important feed 

fish within British Columbia (Haynes, 2006). Robards and 

others (1999c) have compiled a comprehensive annotated 

bibliography on Pacific sand lance. Some aspects of its 

biology can be inferred from general reviews (Field, 1988; 

Robards and others, 1999b) and work done elsewhere in the 

North Pacific (Robards and others, 1999a, 1999b, 1999c). 

Immature herring, and to a lesser extent, salmon smolts and 

immature rockfish (Scorpaenidae) are important alternative 

prey in British Columbia. Hay and others (1989, 1992) and 

Gillespie and Westrheim (1997) review data on forage fish 

important to seabirds in British Columbia, and Grosse and Hay 

(1988) and Hay and McCarter (1997) review herring biology.

Foraging Behavior

Diving Behavior

As discussed above, Marbled Murrelets are wingpropelled pursuit-divers that forage both during the day and 

at night (Carter and Sealy, 1986; Gaston and Jones, 1998). 

Little is known about the diving depths of Marbled Murrelets 

because their dispersed, tree-nesting habit makes it difficult 

to deploy and retrieve the time-depth-recorder devices used 

successfully with other alcids (e.g., Falk and others, 2002). 

Given their mass, Marbled Murrelets should be able to dive 

to depths of about 47 m (Mathews and Burger, 1998). Despite 

this ability, there is evidence that suggests that Marbled 

Murrelets usually make shallower dives. Carter and Sealy 

(1984) examined accidental gillnet mortalities, and concluded 

that most Marbled Murrelets were caught within 3-5 m from 

the surface, and Mathews and Burger (1998) observed a bird at 

a depth of 13.7 m near Vancouver Island. The deepest gillnet 

mortality record is 27 m off the California coast (Carter and 

Erickson, 1992).

Groups of two birds often forage together, vocalizing 

at the surface and diving simultaneously (Nelson, 1997). 

Dives are short (mean = 20-44 s; range 2-115; n = 6-119 

dives; Thoresen, 1989; Carter and Sealy, 1990; Strachan and 

others, 1995; summarized in Nelson, 1997). The mean surface 

time between dives is 26.9 s ± 53.8 SD (n = 181 dives of 20 

individuals; K. Kuletz, unpub. data; summarized in Nelson, 

1997). Juveniles generally have shorter dives than adults 

(K. Kuletz, unpub. data; summarized in Nelson, 1997).

Foraging Strategy

Marbled Murrelets most often forage in pairs, although 

single birds are more common in the winter and birds tend to 

aggregate more in the summer (Sealy, 1974; Carter and Sealy, 

1990; Strachan and others, 1995; Kuletz, 2005). Kuletz (2005) 

found that most birds in Prince William Sound (1997–99) 

occurred as singles or pairs (n = 11,280 birds; 22 percent = 

singles, 53 percent = pairs). Mean group size ranged among 

years from 2.11 (± 0.07) to 1.75 (± 0.03). Day and Nigro 

(2000) reported similar flock sizes of Marbled Murrelets 

feeding in Prince William Sound (mean = 1.7 ± 0.8; n = 4,636 

birds).

Hatch-year (HY) birds generally forage alone (Kuletz and 

Marks, 1997; Kuletz, 2005). Subadults may feed alone during 

the spring and then join foraging adults in the summer (Sealy, 

1975). Although chick-feeding Marbled Murrelets primarily 

forage as individuals, they are fairly flexible when self-feeding 

and in Prince William Sound, showed a tendency to forage in 

larger groups when prey availability was low (Kuletz, 2005). 

This suggests that there is a benefit to foraging in larger 

groups when foraging conditions are poor and food is harder 

to locate (Kuletz, 2005). Marbled Murrelets also may forage 

in large groups when prey are aggregated (see below; Kuletz, 

2005). Marbled Murrelets often return to known feeding sites, 

perhaps encouraged by the presence of other birds or a reliable 

and predictable occurrence of prey (Carter and Sealy, 1990). 

Radio-tagging also has suggested that Marbled Murrelets 

exhibit fidelity to forage sites in Southeast Alaska (Quinlan 

and Hughes, 1992), British Columbia (Hull and others, 2001; 

Lougheed and others, 2002b; Bradley and others, 2004), and 

Prince William Sound (Kuletz, 2005). 

Marbled Murrelets tend to aggregate where food is 

clumped, concentrated, or predictable, but within those 

aggregations murrelets tend to feed primarily in pairs or as 

singles. Murrelets are more aggregated in areas of protected 

water (Chilton and Sealy, 1987; Carter and Sealy, 1990; 

Mahon and others, 1992; Hunt, 1995; Strachan and others, 

1995). They may avoid other individuals while foraging to 

reduce intra-specific competition. 

Marbled Murrelets sometimes occur in mixed-species 

feeding flocks in Alaska and British Columbia (Chilton and 

Sealy, 1987; Carter and Sealy, 1990; Mahon and others, 1992; 

Hunt, 1995; Strachan and others, 1995; Day and Nigro, 2000). 

In Prince William Sound, murrelets composed an average of 

17.3 percent (± 2.1) of all mixed-species flocks, ranging from 

7 to 33 percent (Kuletz, 2005). Feeding flocks consisting only 

of murrelets were significantly smaller than mixed-species 

feeding flocks (Kuletz, 2005). In British Columbia, murrelets 

seem to avoid larger mixed-species flocks, especially those 

dominated by larger alcids and cormorants (Porter and Sealy, 

1981, 1982), but will readily form mixed-flocks with gulls 

(Mahon and others, 1992). 

There has been considerable work conducted in Alaska 

on mixed feeding flocks and the role Marbled Murrelets play 

in initiating these aggregations (Mansicalco and Ostrand, 

1997; Ostrand, 1999; Day and Nigro, 2000). Ostrand 

(1999) studied feeding flocks in Prince William Sound, and 

concluded that all observed feeding flocks were initiated 

by pursuit-diving seabirds, and that 76.5 percent of the 

initiators were Marbled Murrelets. Murrelets therefore play an 

Population Ecology and Characteristics of Murrelets in Alaska and British Columbia 13
important role in increasing the foraging efficiency of Blacklegged Kittiwakes (Rissa tridactyla) and Glaucous-winged 

Gulls (Larus glaucescens; Maniscalco and Ostrand, 1997), 

and may be an important component in the transfer of energy 

from the marine ecosystem to other avian predators (Ostrand, 

1999). However, murrelets are vulnerable to kleptoparasitism 

by gulls (Maniscalco and Ostrand, 1997), and mixed-species 

feeding flocks that include larger, kleptoparasitic birds may 

be detrimental to murrelet foraging success (Maniscalco and 

Ostrand, 1997; Kuletz, 2005).

According to optimal foraging theory (McArthur and 

Pianka, 1966), central place foragers should travel long 

distances to forage if the probability of energy gain is high. 

Murrelets breeding in northern Southeast Alaska fly an 

average of 78 km to forage in Icy Strait (Whitworth and 

others, 2000), whereas birds breeding in Prince William Sound 

fly much shorter distances (mean = 16 km; Kuletz, 2005). Icy 

Strait is an area of upwelling, which concentrates prey and 

provides an important area of predictable prey availability 

for murrelets and other marine predators. It may therefore be 

more beneficial for birds breeding near Auke Bay (Southeast 

Alaska) to fly longer distances to Icy Strait for predictable 

prey than to forage locally on patchy and unpredictable prey 

(Whitworth and others, 2000). In contrast, Prince William 

Sound has relatively low productivity, low fish biomass, 

and small, dispersed fish schools (Ostrand and others, 1998; 

Haldorson and others, 1999), and it may be more beneficial for 

murrelets to be familiar with foraging grounds within a short 

distance of nesting areas versus flying longer distances in 

search of food (Kuletz, 2005). 

Foraging Habitat

Marbled Murrelets are usually found within 5 km from 

shore, and in water less than 60 m deep (Sealy, 1975; Ainley 

and others, 1995a; Burger, 1995b; Strachan and others, 

1995; Nelson, 1997; Day and Nigro, 2000). In general, 

birds occur closer to the shore in exposed coastal areas, and 

farther offshore in protected coastal areas (Nelson, 1997). A 

large scale modeling exercise using British Columbia data 

concluded that murrelet densities were highest near sandy 

substrates and estuaries, and lower near glaciers (Yen and 

others, 2004a). In Alaska, murrelets frequent glacial-fed 

waters, although finer scale habitat use in Prince William 

Sound fjords indicated that Marbled Murrelets were more 

prevalent in waters less than 200 m from shore than offshore, 

and preferred waters with no ice that were greater than 60oC 

and salinity greater than 17 percent (Day and Nigro, 2000; 

Day and others, 2003). Compared to their congener, the 

Kittlitz’s Murrelet, Marbled Murrelets preferred clearer water, 

and avoided waters of high turbidity that limited visibility to 

less than 2 m (Day and others, 2003). 

Physical and biological oceanographic processes that 

concentrate prey (such as upwellings and rip currents) have an 

important influence on the foraging distribution of Marbled 

Murrelets (Kaiser and others, 1991; Ainley and others, 1995b; 

Burger, 1995b, 2002b; Strong and others, 1995; Nelson, 1997; 

Day and Nigro, 2000; Kuletz, 2005). For example, although 

birds in Prince William Sound generally forage in water 

less than 30 m deep, birds breeding near deep water fjords 

feed on predictable concentrations of prey associated with 

glacial sills, sites of upwelling, and currents, rather than travel 

longer distances to shallower water (Kuletz, 2005). These 

bathymetric and oceanographic features may be especially 

important for Marbled Murrelets nesting near deep waters in 

Prince William Sound (Kuletz, 2005). 

To examine the prey selection of Marbled Murrelets, 

Ostrand and others (2004) quantified the at-sea distribution 

of Marbled Murrelets in conjunction with hydroacoustic 

measurements of forage fish in Prince William Sound. 

Murrelets exhibited a highly flexible foraging strategy, 

responding to changes in food availability by switching their 

prey choices to maximize energy gain. For example, despite 

the higher abundance of low-lipid schooling fish during one 

year of the study, murrelets selected less abundant, higher 

value Pacific herring.

Migration and Seasonal Movements 

Many studies have shown seasonal changes in the 

distribution of Marbled Murrelets. Studies in the northern 

part of their range have suggested that large proportions of 

birds move south from breeding areas, either from outer 

coastal to protected waters, or from breeding areas out to 

more open ocean (Sealy, 1974; Carter, 1984; Rodway and 

others, 1992; Burger, 1995b; Carter and Stein, 1995; Piatt 

and Naslund, 1995; Speich and Wahl, 1995; Kuletz, 1996). In 

California, most birds appear to be year-round residents near 

breeding areas (Naslund, 1993). The degree of residency and 

the distance of movements likely reflects the availability of 

suitable prey resources during the non-breeding season. There 

also is an increasing north to south trend of visiting nest sites 

during the non-breeding season through the species range 

(Carter and Sealy, 1986; Naslund, 1993; Beauchamp and 

others, 1999; Burger, 2002). 

Patterns of movement in Alaska are largely unknown. 

Some birds may remain near their breeding sites, whereas 

other birds move south or offshore, or to unknown areas 

(Nelson, 1997). Wintering birds have been recorded as far as 

300 km offshore in the Gulf of Alaska (Piatt and Naslund, 

1995). 

In British Columbia, migration from exposed coasts 

on Vancouver Island into more sheltered waters of Georgia 

Strait and Puget Sound has been inferred from at-sea counts 

(Rodway and others, 1992; Burger, 1995b, 2002b). Some 

birds remain all year along the outer coast, hence, the extent 

of movements is not known. Beauchamp and others (1999) 

14 Status Review of the Marbled Murrelet in Alaska and British Columbia
obtained the only direct evidence to date of migration. An 

adult banded in Desolation Sound, southern British Columbia 

mainland, was recaptured where it wintered in the San Juan 

Islands, Washington, and recaptured again during the breeding 

season in Desolation Sound. Other marked murrelets from 

Desolation Sound, however, appeared to remain there after 

breeding (Beauchamp and others, 1999).

Most movements occur after the breeding season has 

ended (August and September), and again prior to the next 

breeding season (March-May; Bent, 1963; Burger, 1995b; 

Kuletz, 1996; Campbell and others, 1997). For example, no 

Marbled Murrelets are seen in Auke Bay, Southeast Alaska, 

from the middle of September through the end of October 

(G. van Vliet, Alaska Department of Fish and Game, oral 

commun., 2006), and numbers in Kachemak Bay in lower 

Cook Inlet increase during April, reach peak numbers in early 

May, and decrease again in August to a low in September 

(K. Kuletz, U.S. Fish and Wildlife Service, unpub. data, 2006). 

Some post-breeding movements occur prior to the flightless 

pre-basic molt, and may reflect the need for safe molting areas 

with minimal predation, low surf associated with storms, 

and reliable food resources (Carter and Stein, 1995). Other 

movements occur in autumn after the molt and may reflect 

shifts in prey availability and/or a need to winter in more 

protected waters. 

In addition to larger scale movements before and after 

the breeding season, there is some evidence for changes in the 

foraging distribution of Marbled Murrelets during the breeding 

season. For example, summer changes in the foraging 

distribution of birds around Adak (Aleutian Islands) probably 

reflect shifting prey availability and the timing of candlefish 

(Thaleichthys pacificus), capelin, and Pacific sand lance 

spawning (Meehan, 1996).

Molt

The plumages and molts of the Marbled Murrelet have 

been described in detail by Carter and Stein (1995), and 

summarized by Nelson (1997) and Gaston and Jones (1998). 

The juvenile plumage is retained through the first winter, but 

the neck ring and speckling of their white underparts wears 

quickly. Within a month of fledging, juveniles and adults 

in winter plumage are hard to distinguish (Carter and Stein, 

1995). Definitive Alternate (breeding) plumage is attained 

in an incomplete molt that takes place before the breeding 

season. The timing of initiation of the Pre-Alternate molt 

can occur as early as February (California) and as late as 

May (parts of Alaska). During this period, birds lose their 

contour feathers but retain their flight feathers. Birds undergo 

a complete Pre-Basic molt after breeding, when all flight 

feathers are dropped simultaneously and birds are flightless 

for about 1 to 2 months. The initiation of Pre-Basic molt can 

occur as early as June (California) and as late as October 

(Alaska). Adults retain their white Definitive Basic (winter) 

plumage until Pre-Alternate molt in February–May.

Breeding Biology

Reproductive Success

Marbled Murrelets, being solitary nesters with secretive 

breeding habits and remote, often inaccessible nest sites, 

present unique challenges to anyone attempting to measure 

reproductive success. The era of conventional observations of 

nest sites and breeding activities of this species dates only to 

1974, when the first discovery of a nest containing a downy 

young murrelet was made in central California (Binford and 

others, 1975). Following listing of murrelets as Threatened in 

British Columbia, Washington, Oregon, and California, a large 

and systematic effort was mounted to locate and monitor nest 

sites of the species throughout its listed range and in Alaska. 

It was known from examination of collected females that 

murrelets had a characteristic clutch of one egg (Sealy, 1974), 

and no later information has altered that conclusion (DeSanto 

and Nelson, 1995). Upon losing their first clutch, however, 

some pairs are able to produce a replacement egg in the 

same season and may raise a chick successfully (McFarlane 

Tranquilla and others, 2003b; see more below).

By the mid-1990s, Nelson and Hamer (1995) were 

able to report at least fragmentary information on breeding 

activity and outcomes at 65 tree nests of murrelets observed 

from Alaska (n = 18) to California. Table 4 is a condensed 

version of their compilation with the addition of two ground 

nests observed in Alaska (Simons, 1980; Hirsch and others, 

1981). The outcome (chick fledged or failed) was known for 

11 of the 20 Alaska nests, and only 2 (18 percent) produced 

a fledgling. Outside of Alaska, 39 percent of 23 nesting 

attempts with known fate ended successfully, giving a rangewide estimate of mean nesting success of 32.4 percent (n = 

34 nesting attempts). Subsequently, Manley (1999) studied 68 

nesting attempts in British Columbia with ground observations 

and tree climbing, and reported a similar estimate of success 

of 0.33 percent. Those are low values in comparison to most 

other alcid species (Hudson, 1985; Gaston and Jones, 1998). 

There is a tendency for the frequency of nest failure 

to increase from incubation to chick-rearing in Marbled 

Murrelets. Range-wide, hatching success was 67 percent 

(n = 20) and fledging success was 45 percent (n = 19) for nests 

with known outcomes (Nelson and Hamer, 1995; Nelson, 

1997). Such estimates, which are obtained through direct 

observation of nests discovered in trees or on the ground, 

tend to be low (i.e., compare results from telemetry studies 

below). The most frequently reported cause of nest failure 

was depredation of the egg or chick by a known or presumed 

avian predator, but other observed outcomes included egg 

abandonment, chicks falling out of nests, and chicks dying 

in the nest before fledging (Nelson and Hamer, 1995). In 

Prince William Sound, murrelet productivity (as gauged by 

density of recently fledged juveniles at sea) has been studied 

Population Ecology and Characteristics of Murrelets in Alaska and British Columbia 15
in relation to the abundance of prey such as herring and sand 

lance (Kuletz and others, 1995a; Kuletz and Kendall, 1998, 

1999; Kuletz, 2005). The relationship appears to be complex, 

however, the density of juveniles at-sea generally declined 

over the course of Kuletz’s study despite an increasing trend 

in fish school abundance, but the highest murrelet productivity 

occurred when local fish abundance was highest. Kuletz 

(2005) suggested the association may be non-linear, with 

a threshold level of local fish abundance required before a 

consistent and measureable response in murrelet productivity 

would occur.

Because of the difficulty in finding and monitoring 

adequate numbers of nests, other approaches have been 

devised to quantify the nesting success and productivity of 

Marbled Murrelets. A possible bias arises from sampling nests 

primarily in accessible locations (Naslund and others, 1995), 

and there also is the possibility that human observers influence 

nest outcomes by attracting predators (Naslund and others, 

1995). Alternative methods for quantifying nesting outcomes 

include: (1) radio-telemetry, where the success or failure of 

nesting attempts is inferred from the behavior of radio-tagged 

individuals; and (2) counts of recently fledged juveniles atsea. In the latter case, the value reported usually is a ratio of 

juveniles to adults counted concurrently on the water during 

the latter part of the breeding cycle (Andersen and Beissinger, 

1995; Ralph and Long, 1995; Kuletz and Kendall, 1998; 

Lougheed, 1999; Lougheed and others, 2002a).

To date, the most extensive study employing radiotelemetry is work conducted at two locations in British 

Columbia (Bradley, 2002; Bradley and others, 2004; Zharikov 

and others, 2006). In a sample of 265 murrelets tagged before 

or during incubation in 1998–2001, nesting success (laying to 

fledging in 108 identified nests) was estimated at 48 percent in 

Desolation Sound (table 5). From a smaller effort in Clayoquot 

Sound (2000–02), Zharikov and others (2006) determined that 

17 of 29 nests (58.6 percent) were successful to the “midrearing” stage (chicks surviving through day 20 post-hatch), 

a value slightly lower but not significantly different from the 

comparable measure of nesting success (65.7 percent survival 

to mid-chick stage) in Desolation Sound (Zharikov and others, 

2006; table 6). 

The strengths of the British Columbia telemetry study 

included large sample sizes, wide geographic and temporal 

scope (two study sites observed over several years), and the 

fact that nests were sampled without pre-selection (i.e., the 

capture of birds on the water ensured that nests were identified 

Table 4. Marbled Murrelet nesting success based on directly observed outcomes at nest sites in Alaska, British 

Columbia, Washington, Oregon, and California.

[Condensed from Nelson and Hamer, 1995. Percent success: Nest success calculated as percentage of nests fledging a chick of all nests 

with known outcome. Source(s): (1) Quinlan and Hughes (1990); (2) Naslund and others (1995); (3) Nelson and Hamer (1995); (4) Ford and 

Brown (1995), Ford (1995); (5) Simons (1980), Hirsch and others (1981)]

Location Years n

Outcome

Successful Failed Unknown Percent

 Success (n) Source(s)

Alaska

Kelp Bay 1984 1 0 1 0 0 (1) (1)

Naked Island 1991–92 10 0 7 3 0 (7) (2)

Kodiak Island 1992 2 0 0 2 – (2) 

Afognak Island 1992 2 0 0 2 – (2) 

Chugach Island 1992 1 0 0 1 – (3)

Prince of Wales Island 1992–93 2 0 1 1 1

0 (1) (4)

East Amatuli Island 1978–79 2 2 0 0 1

100.0 (2) (5)

Alaska total 20 2 9 9 18.2 (11) 

British Columbia 1990–93 9 1 0 8 100.0 (1) (3)

Washington 1991–93 6 3 1 2 75.0 (4) (3) 

Oregon 1990–93 22 3 7 12 30.0 (10) (3) 

California 1989–93 10 2 6 2 25.0 (8) (3) 

Outside–Alaska total 46 9 14 24 39.1 (23) (3)

All areas total 67 11 23 33 32.4 (34) (3)

1

One (failed) nest on Prince of Wales Island and two (successful) nests on East Amatuli Island were ground nests.

16 Status Review of the Marbled Murrelet in Alaska and British Columbia
independently of inland locations or accessibility). One 

weakness was the likelihood of missing an unknown number 

of early failures, because it was necessary to complete several 

days of successful radio-tracking to verify nesting behavior 

(Bradley and others, 2004).

The third approach to measuring murrelet productivity 

focuses on juvenile (HY) to after-hatching-year (AHY) ratios 

observed among birds on the water. The standard approach 

involves counting juveniles and adult-plumaged birds at a 

strategically chosen time in the breeding season (generally 

mid-July to mid- or late August in Alaska), and expressing 

the presumed productivity of the local breeding population 

as a ratio of the two (HY:AHY). In Alaska, Andersen and 

Beissinger (1995) found low ratios on five surveys conducted 

in Auke Bay during July–August 1993. They recorded only 

12 juveniles in total, against 940 AHY birds, for a mean ratio 

of 0.013 (or 0.016 if they restricted their analysis to nearshore 

transects, where all juveniles occurred). At a number of sites 

surveyed within Prince William Sound, HY:AHY ratios 

ranged from 0.02 to 0.08 in 4 years, averaging 0.043 (Kuletz, 

2005; table 7). Both studies imply low breeding success. 

The low values are partly due to the later stage at which 

HY:AHY ratios are determined—the cohort of juveniles on 

the water has been reduced to an unknown extent by losses 

incurred during the act of fledging and by early post-fledging 

mortality. However, HY:AHY ratios also are subject to 

several important biases that are difficult to control (Ralph 

and Long, 1995; Burger, 2002; McShane and others, 2004). 

The counts of AHY individuals include unknown proportions 

of subadult nonbreeders. Moreover, juveniles cannot be 

reliably distinguished from AHY murrelets once the latter 

have started their pre-basic molt (Carter and Stein, 1995). In 

Prince William Sound, however, Kuletz and Kendall (1998) 

found that adults left the area in August, apparently before 

molting, which thus minimized this source of bias. Additional 

surveys in Prince William Sound (Kuletz, 2005) showed the 

same pattern of adult departure prior to pre-basic molt. In 

Alaska, fledglings typically stay closer to shore than do adults 

(Andersen and Beissinger, 1995; Kuletz and Kendall, 1998), 

and differential movements of juveniles and AHY birds into or 

out of surveyed areas is a known problem (see section “PostBreeding Dispersal”).

Variations and refinements have been proposed as 

improvements on the standard “concurrent” HY:AHY ratio. 

Kuletz and Kendall (1998) found that a “sequential” ratio 

of HY density in July–August and AHY density measured 

in June produced an index that was more consistent among 

survey sites than a concurrent ratio taken in July–August. They 

advised sequential ratios whenever feasible, but recognized 

that the method may not be available to all workers because of 

the added time and expense required to obtain the additional 

data. Sequential ratios in Prince William Sound ranged from 

0.03 to 0.26 juveniles per adult, averaging 0.098 in 4 years 

(table 7). As an alternative to either type of ratio, a simple 

count of juveniles within a suitably defined area may provide 

a useful index of production that avoids the problem of AHY 

dispersal during surveys (Kuletz and Kendall, 1998; Kuletz, 

2005; table 7).

In British Columbia, Lougheed and others (2002a) 

obtained a sequential ratio (à la Kuletz and Kendall, 1998) that 

also corrected for the turnover of juveniles and proportion of 

the fledging period covered by the surveys. The refinement 

required information on the dispersal of radio-tagged HY 

birds, so widespread adoption of their approach is unlikely. 

The “corrected” ratios for Desolation Sound averaged three 

times higher than simple concurrent ratios in 3 years, 1996–98 

(0.131 vs. 0.042), but they still were lower than measures of 

productivity obtained from nest monitoring.

Juvenile murrelets may at times congregate in “nursery 

areas” (Kuletz and Piatt, 1999), a behavior that would lend 

itself to better monitoring of year-class strength if the locations 

Table 5. Estimated probability that breeding radio-marked 

Marbled Murrelets from Desolation Sound, British Columbia 

(1998–2001) reached successive stages of reproduction.

[From Bradley and others, 2004. n = 116]

Stage

Probability of 

success at 

each stage

Cumulative 

probability 

(Kaplan-Meier 

estimates)

Estimate 95-percent 

CI Estimate 95-percent CI

Incubation (= hatching) 0.86 0.79–0.92 0.86 0.79–0.92

Mid-chick 0.81 0.73–0.88 0.69 0.61–0.77

Fledging 0.69 0.63–0.75 0.48 0.41–0.55

Table 6. Nest outcomes (through mid-chick-rearing stage) 

inferred from activity patterns of radio-marked murrelets in 

Desolation Sound and Clayoquot Sound, British Columbia, 

1998–2002.

[Source of data: Zharikov and others, 2006]

Location Years n

Outcome

Successful

(percent) Failed

Desolation Sound 1998–2001 108 71 (65.7%) 37

Clayoquot Sound 2000–02 29 17 (58.6%) 12

Population Ecology and Characteristics of Murrelets in Alaska and British Columbia 17
Table 7. Marbled Murrelet abundance and productivity at three sites in Prince William Sound, Alaska.

[Data from Kuletz (2005). Means (±SE) are shown for adult densities (birds/km2) in June (incubation phase) and July 18–August 10 (early fledging period). 

Juvenile densities are shown for July 27–August 24 (when sites had reached 75th percentiles) and for the core surveys (five highest juvenile counts), 

Concurrent ratio: Early fledging period was used to minimize the effect of post-breeding adult dispersal. Sequential ratios: Mean core juvenile density 

divided by the mean June adult density was used, providing one value per year]

 Year Site

June surveys July 18–August 10 July 27–

August 24 Core surveys (n=5) Sequential ratio

n

Adult

density n

Adult 

density

Concurrent 

ratio

Mean 

ratio n

Juvenile 

density

Juvenile 

density Mean Site/year

Mean

1995 Galena 3 5.87 (1.53) 5 10.69 (1.55) 0.02 (0.01) 0.04 5 0.23 (0.07) 0.23 (0.07) 0.98 0.04 0.08

Naked 4 13.10 (3.63) 5 22.26 (2.37) .06 (0.02) 6 1.47 (0.28) 1.67 (0.25) 0.13 

Jackpot 4 16.58 (1.31) 5 18.71 (2.62) .04 (0.01) 5 1.02 (0.17) 1.04 (0.16) 0.06 

1997 Galena 3 15.55 (7.60) 4 34.12 (12.4) .04 (0.02) 0.04 6 0.64 (0.08) 0.68 (0.09) 0.96 0.04 0.03

Naked 3 65.50 (15.32) 4 29.83 (7.02) .05 (0.02) 6 1.38 (0.14) 1.51 (0.05) 0.02

Jackpot 3 33.05 (1.69) 5 12.71 (2.73) .04 (0.02) 6 0.58 (0.18) 0.68 (0.19) 0.02

1998 Galena 3 11.86 (2.92) 4 6.59 (2.09) .02 (0.01) 0.03 5 0.19 (0.07) 0.19 (0.07) 0.65 0.02 0.03

Naked 3 28.19 (3.84) 4 23.90 (3.02) .06 (0.03) 6 1.23 (0.30) 1.37 (0.32) 0.05

Jackpot 3 17.65 (1.88) 4 21.10 (5.95) .02 (0.01) 7 0.26 (0.06) 0.38 (0.05) 0.02

1999 Naked 5 3.16 (1.04) 4 13.93 (1.08) .08 (0.02) 0.06 6 1.07 (0.25) 1.42 (0.15) 0.95 0.45 0.26

Jackpot 6 6.37 (1.12) 4 15.16 (2.76) .04 (0.01) 7 .39 (0.09) 0.48 (0.11) 0.07

and temporal use of such areas were adequately known. The 

only described example is from Kachemak Bay, where HY 

murrelets occurred at high densities on 2 of 10 transects 

(Kuletz and Piatt, 1999). Within the “nursery” itself, juveniles 

outnumbered AHY birds in a ratio of 1.3 to 1 (table 8). That 

is obviously an index of an altogether different kind than the 

standard HY:AHY ratios reported elsewhere. Nursery areas 

have not been identified at other locations in Alaska (Kuletz, 

2005). In British Columbia, concurrent HY:AHY ratios from 

0.2 to 0.4 occurred in some years off southwestern Vancouver 

Island (Bellefleur and others, 2005). Those are higher values 

than reported from anywhere else outside of Kachemak Bay, 

suggesting a possible, if less pronounced, “nursery” effect. 

Of the several methods available to gauge the 

reproductive success of Marbled Murrelets, radio-telemetry 

seems to offer the best means of characterizing breeding 

success accurately and with reasonable efficiency. Such data 

are vital for demographic analyses, but much work remains to 

be done to refine the estimates, especially in Alaska. HY:AHY 

ratios will continue to be important as indices of productivity 

because they are relatively easy and inexpensive. In some 

situations, it may be possible to calibrate the information from 

at-sea surveys against other, more direct measures of nesting 

success, but a substantial commitment of resources will be 

required.

Table 8. Number of adult and juvenile Marbled Murrelets 

counted on survey routes in Kachemak Bay, Alaska, August 1996.

[From Kuletz and Piatt (1999). Survey segments i and j were perceived as 

“nursery areas” for juvenile murrelets]

Location/segment Date

Number of murrelets

Ratio

Adults Juveniles

Inner Bay

Segment a 13 72 0 0

Segment b 24 83 1 0.012

Segment c 13 19 0 0

Segment d 24 12 1 0.083

 Inner Bay total 186 2 0.011

Outer Bay

Segment e 13 37 1 0.027

Segment f 7 43 2 0.047

Segment g 7 7 3 0.429

Segment h 12 3 0 0

Segment i 12 7 23 3.286

Segment j 23 34 30 0.882

 Outer Bay total 131 59 0.450

 Total 317 61 0.192

18 Status Review of the Marbled Murrelet in Alaska and British Columbia
Timing of Breeding

Marbled Murrelets have an asynchronous and protracted 

breeding season (Lougheed and others, 2002b). At a given 

nest, incubation lasts from 28 to 30 days and chick fledging 

occurs from 27 to 40 days after hatching (Hirsch and others, 

1981; Nelson, 1997). Hamer and Nelson (1995) assumed 

modal values of 30 days for incubation and 28 days for chick 

age-at-departure in back-calculating or projecting the timing 

of events in the nesting cycle from observations of laying, 

hatching, nestling development, or fledglings at-sea. Their 

compilation of observed and calculated events for 86 nesting 

attempts from Alaska to California reveals a breeding period 

(first laying to last fledging) of about 106 days in Alaska—

mid-May through late August or early September (fig. 2). 

Hatching begins around June 15 and the earliest juveniles 

arrive on the water in mid-July. A latitudinal cline is evident, 

with Alaska murrelets having a shorter and later breeding 

season than do populations to the south. Hamer and Nelson 

(1995) estimated that the overall breeding season averages 

64 days fewer in Alaska than in California.

Few data on the breeding phenology of murrelets in 

Alaska have emerged since the summary depicted in figure 2

was prepared by Hamer and Nelson (1995). During at-sea 

surveys in Prince William Sound, Kuletz and Kendall (1998) 

noted a peak in fish-holding (i.e., chick-provisioning) adults 

on July 26, which agrees closely with the median date for 

chick-rearing in figure 2. The peak of fledging appeared to 

occur during the first or second week of August in 4 years 

(Kuletz, 2005), suggesting the median date is a week or two 

later in Prince William Sound than is depicted in figure 2. 

Newly fledged birds were seen as early as July 4 in Southeast 

Figure 2. Breeding phenology of Marbled Murrelets from Alaska to California showing estimated onset, 

median dates, and endpoints of the incubation and nestling periods (from Hamer and Nelson, 1995).

Population Ecology and Characteristics of Murrelets in Alaska and British Columbia 19
Alaska (Doerr and Walsh, 1994) and in Kachemak Bay 

(K. Kuletz, U.S. Fish and Wildlife Service, unpub. data, 

2004–06). Speckman and others (2000) inferred breeding 

phenology from the timing and behavior of adults and 

juveniles on the water in Auke Bay and Fritz Cove near 

Juneau. Their summary (fig. 3) corroborates in general the 

conclusions of Hamer and Nelson (1995; fig. 2), although it 

suggests that breeding commences in the first week of May 

in some locations or seasons in Alaska. Speckman and others 

(2000) estimated that breeding began about 19 days earlier in 

1993 than in 1992, indicating that considerable interannual 

variation in nesting phenology can be expected. In Prince 

William Sound, the date when 50 percent of the season’s 

juveniles were counted generally varied consistently among 

three sites (45–90 km apart) by as much as 1 to 2 weeks, 

suggesting local environmental influences on phenology 

(Kuletz, 2005). Elsewhere, McFarlane Tranquilla and others 

(2003c, 2005) reported annual variation of about 10 days in 

the onset of nesting by murrelets in Desolation Sound. The 

same study found that nesting began about 1 month earlier 

in Desolation Sound, a mainland site, than in Clayoquot 

Sound on the west coast of Vancouver Island (McFarlane 

Tranquilla and others, 2005). Thus, although the breeding 

phenology of murrelets at the northern end of their range has 

been documented in general, additional work in Alaska may 

discover interannual and among-site variation beyond what is 

currently known.

Figure 3. Breeding phenology of Marbled Murrelets in Southeast Alaska deduced from observations of fish-holding 

adults and chicks at-sea (from Speckman and others, 2000).

20 Status Review of the Marbled Murrelet in Alaska and British Columbia
Post-Breeding Dispersal

Marbled Murrelets are common to abundant throughout 

the year over most of their range in Alaska (Mendenhall, 

1992; DeGange, 1996). However, major shifts in seasonal 

distribution occur, primarily from the northernmost portions 

of the breeding range to wintering areas farther south. In 

Prince William Sound, numbers declined nearly 80 percent 

between summer and the nonbreeding period (Klosiewski and 

Laing, 1994; Agler and others, 1999), and a marked exodus in 

winter also is reported for Glacier Bay (DeGange, 1996). Piatt 

and Ford (1993) suggested that many murrelets from Prince 

William Sound winter in the Kodiak Archipelago or along the 

Alaska Peninsula, where numbers increase in the nonbreeding 

period (Forsell and Gould, 1981; Zwiefelhofer and Forsell, 

1989; Piatt and Naslund, 1995). Murrelets favor sheltered 

waters such as bays and fjords in winter, but some seaward 

movement also occurs, as individuals are seen as much as 

300 km offshore in the Gulf of Alaska (Piatt and Naslund, 

1995).

Kuletz and Marks (1997) tracked the movements of a 

radio-tagged juvenile murrelet for 2 weeks after it departed 

its nest in Prince William Sound (Port Nellie Juan). The 

bird initially moved about 12 km from the nest site, then 

remained in a confined (12 km2) area of nearshore waters 

for the duration of the study. During surveys at several 

additional sites in Prince William Sound, Kuletz and Kendall 

(1998) determined that recently fledged murrelets remained 

in nearshore waters for several weeks, whereas the postbreeding adult population rapidly vacated the area during 

the same period. A similar pattern may occur in Southeast 

Alaska, where radio-tagged adults from the Port Snettisham 

area moved as much as 200 km north and 160 km south in the 

early postbreeding dispersal period, July–August (Newman 

and others, 2006). Age-specific timing of dispersal may 

vary by location, because a different pattern—rapid juvenile 

dispersal and adult residency near the breeding sites through 

late summer—was reported for Desolation Sound, British 

Columbia (Lougheed, 1999). However, the apparent difference 

in juvenile behavior was likely due in part to a difference in 

scale between the relatively large survey areas in Alaska and 

the smaller, fjord area examined in British Columbia (Kuletz, 

2005).

Site Fidelity and Natal Dispersal

Nest sites of Marbled Murrelets often go unused 

in consecutive years, possibly as a way of reducing the 

likelihood of detection by predators (Divoky and Horton, 

1995). Consistent use of the same or nearby nest trees is 

well-documented, however, which suggests a high degree of 

fidelity to a given locality by nesting murrelets in different 

years (Naslund and others, 1995; Nelson, 1997; Manley, 

1999). On Naked Island (Prince William Sound), Naslund and 

others (1995) found no indication that five nest sites located 

in 1991 were reused the following year, although observations 

of murrelets using the same trees for landing or nesting in 

both years confirmed the pattern of repeated activity in a given 

vicinity. Because adult murrelets have not been banded at the 

nest, it remains an assumption that reuse of the same trees 

involves one or both of the same individuals. 

There are too few data—and none from Alaska—to say 

anything definitive about natal dispersal in Marbled Murrelets. 

In the long-term study in Desolation Sound, only 2 of 106 

murrelets banded as nestlings were recaptured in subsequent 

years, suggesting that most young murrelets emigrated to other 

areas to breed (Lank and others, 2003). Divoky and Horton 

(1995) reasoned that natal dispersal may be high in Marbled 

Murrelets considering the overlap between their wintering and 

breeding areas, the distances that individuals are known to 

move in winter, and the fact that murrelet nesting is dispersed 

over a wide band of forest habitat extending at least 60 km 

inland from the coast.

Overwinter Occupation of Nesting Habitat

Marbled Murrelets may be unique among alcids in 

Alaska in that at least some individuals visit their nesting 

habitats during most months of the year. The behavior is best 

documented for Southeast Alaska (Doerr and Walsh, 1994; 

DeGange, 1996; Brown and others, 1999), but also has been 

observed in Chiniak Bay, Kodiak Island (Dick, 1979). From 

December 1992 through November 1996, Brown and others 

(1999) conducted dawn surveys at 2-week intervals at four 

sites within the Alexander Archipelago. Excluding a 2 month 

hiatus in September and October, when no birds occurred 

inland, and another period of reduced activity in April, 

murrelets were detected on 90 percent of surveys conducted 

throughout the year. The two periods of relative inactivity 

corresponded to the murrelets’ complete Pre-Basic molt in the 

autumn and their Pre-Alternate molt in the spring (Carter and 

Stein, 1995). The number of detections per survey was lower 

by one-half or more in winter as compared to peak numbers 

in July and August, but forest visitation was fairly consistent 

during all nonbreeding months that were unconstrained by 

molt. The patterns observed in Alaska closely parallel those 

reported by Naslund (1993), who studied the year-round 

attendance of murrelets in old-growth forests of central 

California. Naslund (1993) suggested that winter occupation 

of nesting habitat may be important for retention of nest sites 

and pair bonds.

Population Ecology and Characteristics of Murrelets in Alaska and British Columbia 21
Natural Mortality 

Disease

Information on the kinds and incidence of diseases 

experienced by Marbled Murrelets is lacking, both in Alaska 

and elsewhere in the species’ range. Newman and others 

(1997) analyzed the blood of 11 murrelets collected in the 

Shumagin Islands, and reported reference ranges for standard 

parameters of hematology and plasma biochemistry in 

presumed healthy individuals. That information may prove 

useful for the future detection and characterization of disease 

in this species.

Predation

Current knowledge of predator effects on Marbled 

Murrelets in Alaska is briefly summarized below. Readers 

should refer to the section, “Nesting Habitat: Characteristics, 

Threats, and Trends,” for more information on predator-prey 

interactions involving Marbled Murrelets.

Predation on adult murrelets, eggs, and nestlings is 

well-documented outside of Alaska (Nelson and Hamer, 

1995; Nelson, 1997; Burger, 2002; Burger and others, 2004c; 

McShane and others, 2004). Known or suspected avian 

predators on adults include Bald Eagles, Peregrine Falcons 

(Falco peregrinus), Northern Goshawks (Accipiter gentilis), 

Sharp-shinned Hawks (A. striatus), and Common Ravens. 

Common Ravens, Steller’s Jays, Northwestern Crows (C. 

caurinus), Sharp-shinned Hawks, and Great Horned Owls 

(Bubo virginianus) are likely nest predators that occur 

commonly within the Alaska breeding range of Marbled 

Murrelets. Nest predation by mammals is unconfirmed but 

strongly suspected. Potential mammalian predators in Alaska 

include forest mustelids (marten, Martes americana, and 

fisher, M. pennanti), red squirrels (Tamiasciurus hudsonicus), 

mice (Peromyscus spp.), and raccoons (Procyon lotor; Nelson, 

1997; Raphael and others, 2002b; Bradley and Marzluff, 

2003).

Direct or indirect observations of murrelet depredation 

in Alaska are few. Marks and Naslund (1994) witnessed one 

incident of a female Sharp-shinned Hawk killing an adult 

murrelet at or near its nest site on Storey Island in Prince 

William Sound. Based on damaged eggshells remaining in 

failed nests, Naslund and others (1995) believed Steller’s Jays 

were likely predators at several nests on nearby Naked Island. 

Burger (2002b) summarized unpublished data supplied 

by the State of Alaska (S. Lewis, Alaska Department of Fish 

and Game, 2001–01) on the occurrence of Marbled Murrelets 

in the prey remains of Northern Goshawks in Southeast 

Alaska. Murrelets composed 2.8 percent of the material 

collected at goshawk nests (10 of 361 prey remains) and 

3.1 percent of prey items identified in pellets (12 of 382). 

Murrelets were only 0.8 percent of all prey deliveries (11 of 

1,451) at goshawk nests, but were brought at least once to 6 

of 10 nests observed. Iverson and others (1996) reported as 

much as 20 percent frequency of occurrence of alcids (mostly 

Marbled Murrelets) in goshawk nests in the Tongass National 

Forest as a whole. Ralph and others (1995b), citing a personal 

communication from Jeff Hughes (Alaska Department of Fish 

and Game), noted that murrelet wings were the most common 

prey remains found at Peregrine Falcon nests in coastal 

Alaska. 

Nelson and Hamer (1995) proposed that murrelets 

become more vulnerable to predators as a result of habitat 

fragmentation and the creation of forest “edge” habitat 

through clear-cutting. They suggest this as an explanation for 

lower nesting success in sites located closer to forest edges. 

Follow-up work by Burger and others (2004c) on Vancouver 

Island found that predation risk at Marbled Murrelet nests 

was higher near clearcuts and roads than in interior forests, 

and higher in fragmented landscapes than in relatively intact 

old-growth forests. In contrast, however, Zharikov and others 

(2006) concluded that murrelets bred as successfully in forests 

fragmented by logging as they did in undisturbed habitats.

Population Genetics

In this section, we briefly review the literature on 

population genetic variation in Marbled Murrelets, and present 

new information that includes analysis of birds from locations 

in Washington and Oregon. The result of this new analysis 

is a more complete picture of the population genetics of the 

species.

Background

Several studies of genetic variation have been published 

for Marbled Murrelets. Pitocchelli and others (1995) analyzed 

restriction fragment length polymorphisms in mitochondrial 

DNA (mtDNA) from murrelets collected from tree- versus 

ground-nesting ecoregions in Alaska; they found no evidence 

22 Status Review of the Marbled Murrelet in Alaska and British Columbia
of differentiation between the two types. Subsequently, Friesen 

and others (1996b) compared variation in the mitochondrial 

cytochrome b gene and 39 allozyme loci from 43 birds 

sampled between the western Aleutian Islands and Oregon. 

They reported evidence for low but significant population 

genetic structure, but could not determine how the populations 

differed. Based on variation in nine nuclear introns in 120 

birds from the western Aleutian Islands to southern British 

Columbia, Congdon and others (2000) found that murrelets 

from mainland Alaska and British Columbia are similar, but 

differ from those in the western and central Aleutian Islands. 

Most recently, Friesen and others (2005) surveyed variation 

in four introns and three microsatellite loci from murrelets 

from Alaska, British Columbia and California. They reported 

significant differentiation of birds from peripheral sites, 

i.e., California and the Aleutian Islands, but little genetic 

structuring in the central area. Friesen and others (2005) also 

analyzed variation in a 547 base pair (bp) fragment of the 

mitochondrial control region, and found significant population 

genetic structure as well as weak phylogeographic structure 

(i.e., geographical segregation of related genotypes). Both 

Congdon and others (2000) and Friesen and others (2005)

found evidence for a genetic cline, and Friesen and others 

(2005) argued for the recognition of three to five genetic 

management units. However, these studies were limited in 

the number of either sites (Congdon and others, 2000) or loci 

(Friesen and others, 2005) that were sampled.

New Analyses Using Samples from Washington 

and Oregon and Multiple Loci

A definitive analysis of population genetic structure in 

Marbled Murrelets requires a range-wide sampling of birds 

and analysis of multiple genetic loci. With this objective 

in mind, we recently completed an analysis of variation in 

9 nuclear introns and 15 microsatellites for 282 murrelets 

sampled from throughout the species’ range, i.e. the western 

Aleutian Islands to central California (Friesen and others, 

Queens University, unpub. data, 2006). Here we incorporate 

previously published intron data for murrelets from Alaska, 

British Columbia, and California (Congdon and others, 2000; 

Friesen and others, 2005) with new data on intron variation for 

murrelets from California, Oregon, Washington, and Unalaska 

Island, and new microsatellite data for all samples. Combining 

results from mtDNA, rapidly evolving microsatellites, and 

more slowly evolving introns permits analysis of recent as 

well as more ancient population parameters. We apply both 

traditional and state-of-the-art methods of data interpretation 

to estimate the extent of genetic differentiation and gene 

flow among birds from multiple sampling sites. This study 

constitutes the most comprehensive genetic analysis of 

Marbled Murrelets to date, and provides a robust picture of 

global genetic structuring of the species.

Methods

Sampling

The present data set includes DNA samples from 282 

birds collected between 1989 and 2005 (fig. 4). Sampling 

for Alaska, British Columbia, and California was described 

in detail previously (Congdon and others, 2000; Friesen and 

others, 2005). Briefly, solid tissue was sampled from murrelets 

collected (under USFWS permit) for dietary analysis in Alaska 

between 1989 and 1995. Breeding status was determined 

after collection from total external evidence (plumage [adult 

vs. subadult or juvenile] and brood patch [usually but not 

always partially or fully developed during breeding season]), 

and internal evidence (Bursa of Fabricus present or absent, 

development of gonads, evidence for recent passing of 

egg [expanded oviduct], or presence of egg). All but four 

specimens used for genetic analyses were determined to be 

breeders. For British Columbia and California, blood samples 

were collected from birds caught for banding and/or telemetry 

between 1996 and 2004. Recently, we obtained samples from 

33 birds from Washington and 18 birds from Oregon. These 

samples comprised blood or solid tissue collected either from 

individuals netted at-sea at night or from carcasses on beaches 

between 1990 and 2005. All these samples were from adults 

with brood patches and/or were collected during the breeding 

season (May through August).

DNA Preparation

DNA was prepared using standard proteinase k/phenol/

chloroform extraction (Sambrook and others, 1989) or DNeasy 

kits® (Qiagen, Mississauga, Ontario). For the former method, 

approximately 20 mg solid tissue or the equivalent of 5 μL 

of whole blood was incubated for 4 hr at 65oC in 500 mL of 

buffer containing 100 mM Tris pH 8.0, 100 mM NaCl, 10 

mM EDTA, 0.1 percent SDS, and 0.2 mg proteinase k. Tissue 

digests were then extracted twice with equal volumes of Trissaturated phenol (pH 8.0) and once with chloroform/isoamyl 

alcohol (24:1). DNA extracts were diluted 10-fold with 

distilled water before use. DNeasy preparations were done 

according to the manufacturer’s instructions.

Population Genetics 23
Figure 4. Approximate breeding distribution (shaded coastal areas), and origins and numbers of Marbled 

Murrelets sampled for genetic analyses.

Abbreviations: CCA, central California; NCA, northern California; OR, Oregon; WA, Washington; BC, British 

Columbia; Alex, Alexander Archipelago; PWS, Prince William Sound; Cook, Cook Inlet; Shum, Shumagin Islands, 

Unal, Unalaska Island, Andr, Andreanof Islands, Near, Near Islands. 

24 Status Review of the Marbled Murrelet in Alaska and British Columbia
Introns

Variation in introns was assessed using analysis of singlestranded conformational polymorphisms (SSCPs) and direct 

sequencing (Friesen and others, 1997, 1999, 2005; Congdon 

and others, 2000; table 9). Polymerase chain reaction (PCR) 

amplifications were done in 15 μL volumes containing 10 

mM Tris pH 8.4, 50 mM KCl, 1.5 mM MgCl2, 0.01 percent 

gelatin, 0.06 mg/mL bovine serum albumin, 0.2 mM dNTPs, 

1 μCi 33P-α-dATP, 0.4 μM each primer, and 0.5 units Taq

DNA polymerase (Qiagen). Products were subjected to 

electrophoresis through 0.5 percent MDE® (J.T. Baker) 

nondenaturing acrylamide gels at 4oC. Tentative genotypes 

were assigned, and samples were ordered by genotype and 

rerun to confirm scoring. Representative individuals that 

were homozygous for common alleles, individuals with 

unique alleles, and individuals with ambiguous genotypes 

were re-amplified without 33P-α-dATP, and PCR products 

were sequenced either manually with Thermosequenase® 

kits (GE Healthcare, Montreal, Quebec) according to the 

manufacturer’s suggested protocol, or using an automated 

platform (3730XL DNA Analyzer®, Applied Biosystems) 

operated by Genome Quebec (McGill University, Montreal, 

Quebec). Tropomyosin did not amplify reliably, and so was 

excluded from all analyses. Introns also did not amplify 

reliably for samples from Unalaska Island due to sample 

degradation; this site was therefore excluded from populationlevel analyses involving introns. Note that sample sizes for the 

Andreanof Island also are low for introns.

Hayashi (1991) reported that analysis of SSCPs detects 

about 99 percent of sequence variation for DNA fragments 

about 100–300 bp in length and about 89 percent of variation 

for fragments 300–450 bp in length. Previously, we reported 

that analysis of SSCPs missed one bp substitution in one of 

ten Marbled Murrelets screened for a about 500 bp fragment 

of cytochrome b (Friesen and others, 1996b). To determine the 

level of undetected variation in the present study, we compared 

genotype scores from direct sequencing with genotype scores 

from SSCPs for 37 birds representing ten genotypes for OD. 

(Note that OD is the largest intron analyzed.) Only one new 

allele was found among 74 screened. Whereas, this level of 

undetected variation may lead to slight underestimates of 

effective population size (that we deliberately did not generate 

in the present study), it should have minimal effect on indices 

of population differentiation.

Microsatellites

Microsatellite loci were amplified using PCR buffers 

and cycle profiles given in Ibarguchi and others (2000) 

and annealing temperatures from Rew and others (2006; 

table 9). Briefly, reactions were conducted in 10–15 μL 

reaction volumes under standard conditions after one PCR 

primer was end-labeled with 33P-γ-dATP. PCR products were 

subjected to electrophoresis through 6 percent denaturing 

polyacrylamide gels and visualized on X-ray film. Allele 

sizes were determined using sequencing ladders as standards. 

This ‘manual’ approach tends to be more repeatable and 

accurate than capillary-based automated methods because it 

is not affected by differences in running conditions (e.g., gel 

density) between capillaries. ‘Stuttering’ was minor. A subset 

of 26 samples from central California also was analyzed at the 

University of California on an automated sequencer using Rew 

and others (2006) protocols; genotype scores were identical 

to those obtained manually. Variability for Bma14b29 did 

not fit the usual pattern for a microsatellite: only three alleles 

were found (one of which occurred only in homozygous form 

in a single individual), and alleles did not differ by 2 bp as 

expected for a dinucleotide repeat. This locus was therefore 

eliminated from further analyses. 

Population Genetics 25
Table 9. Genetic loci, PCR primer sequences, and annealing temperatures employed 

in Marbled Murrelet population genetic analysis.

Locus Primer Sequences Annealing

temperature

Introns

Ald1 F: 5’-ATCATCAAAGAAAAAGGCATGGTGGTGGG-3’ 59oC

R: 5’-AGCACCATCTTTCTTGTACTGGGCACAGCG-3’

Enolase1 F: 5’-CCAGGCACCCCAGTCTACCTGGTCAAA-3’ 60oC

R: 5’-TGGACTTCAAATCCCCCGATGATCCCAGC-3’

Gpd1 F: 5’-CATCAAGTCCACAACACGGTTGCTGTA-3’ 65oC

R: 5’-ACCTTTAATGCGGGTGCTGGCATTGC-3’

LDH2 F: 5’-GGAAGACAAACTAAAAGGAGAAATGATGGA-3’ 57oC

R: 5’-TTCCTCTGAAGCAGGTTGAGACGACTCTC-3’

Lamin1 F: 5’-CTGCCGCCCGTTGTCGATCTCCACCAG-3’ 70oC

R: 5’-CCAAGAAGCAGCTGCAGGATGAGATGC-3’

MPP2 F: 5’-TTGCAGATGGAGAGCAGGTTGGAGCC-3’ 65oC

R: 5’-TACATCTACTTTAACACCTGGACCACCTG-3’

OD2 F: 5’-GACTCCAAAGCAGTTTGTCGTCTCAGTGT-3’ 72oC

R: 5’-TCTTCAGAGCCAGGGAAGCCACCACCAAT-3’

RP402 F: 5’-GCTTTCTCAGCAGCAGCCTGCTC-3’ 65oC

R: 5’GGGCCTGATGTGGTGGATGCTGGC-3’

Tropomyosin2 F: 5’-CGGTCAGCCTCTTCAGCAATGTGCTT-3’ 72oC

R: 5’-GAGTTGGATCGGGCTCAGGAGCG-3’

Microsatellites

Cco5-213 F: 5’-TCAAGATGATGAAGACCCTAAT-3’ 52oC

R: 5’-AGAGTTGCACAGGTTAAATACC-3’

Bma10-183 F: 5’-GGTAGGAGCGGAGTAGGAGG-3’ 60oC 

R: 5’-GCAAAATAAGGGTGAAGGCA-3’

Ulo14b294 F: 5’-GTATTATGTTCCGGAAAACTGT-3’ 57oC

R: 5’-TACCCCTATATACAAACCCAAG-3’

Bma3015 F: 5’-AGATCTATCCCTTGGCTGGA-3’ 59oC

R: 5’-TATCTGCCAAAATCTGCTGAA-3’

Bma3565 F: 5’-GTCCACTGAGTTTAGCAGCAA-3’ 58oC

R: 5’-TGCAGCTCACTATACCAAGGA-3’

Bma3655 F: 5’-GCTTTATCTGTGGCAACACTG-3’ 62oC

R: 5’-GCTGTAGGGAGGATATGATGC-3’

Bma3685 F: 5’-AATCACCAAGGATAAAGGATGATA-3’ 62oC

R: 5’-AGGGGACCTGCCCATATATTA-3’

Bma3715 F: 5’-GTCCCCTTTCTAACAGGCACT-3’ 62oC

R: 5’-GTAAAGGTGGGGGAGCATATT-3’

Bma4335 F: 5’-TCAGAAGATCCTTCTCCCTCA-3’ 59oC

R: 5’-CCAAAGGCCAAAGAATGATTA-3’

Bma4395 F: 5’-GAGGGGAGGGTGTATCTTTTC-3’ 62oC

R: 5’-ATGTCACTCTGGTGGAGAACC-3’

Bma4435 F: 5’-TGCCAGGCCATCTACTTTAAT-3’ 59oC

R: 5’-GCTTATCTTTCCCTCCATCCT-3’

Bma4535 F: 5’-TCCTCCACATGTTTTGCAGTA-3’ 59oC

R: 5’-CAGGAGCACCATGTATGTTTG-3’

Bma5235 F: 5’-TGAATCCAGTGGAACAAAACA-3’ 59oC

R: 5’-AATGAACTAATGAGGGCGATG-3’

Bma5535 F: 5’-TTGTGAGAGGGTCACTTATCAAAT-3’ 59oC

R: 5’-CATCTCTCTTTCAGAAGAGCAGTC-3’

Bma5555 F: 5’-GACAGAATATAAATGGAGACATGG-3’ 59oC

R: 5’-AGGCAGAGATGAGAAGGCTAA-3’

1

Friesen and others, 1997.

2

Friesen and others, 1999.

3

Friesen and others, Queens University, unpub. data, 2005–06.

4

Ibarguchi and others, 2000.

5

Rew and others, 2006.

26 Status Review of the Marbled Murrelet in Alaska and British Columbia
Population Genetic Structure

Genotype frequencies were tested for deviations from 

Hardy-Weinberg expectations and for evidence of inbreeding 

(significantly negative FIS estimates) within sampling sites 

by randomization (10,000 replications) using ARLEQUIN 

(version 3.1; Schneider and others, 2000) and FSTAT (version 

2.9.3.2; Goudet, 1995), respectively. Multilocus genotypes 

also were tested for linkage disequilibrium within sampling 

sites using ARLEQUIN with 10,000 permutations of the data. 

For introns, global (species-wide) and pairwise estimates 

of population differentiation were indexed using ΦST, an 

analog of Wright’s FST that incorporates sequence differences 

among alleles. Wright’s FST (assuming an infinite alleles 

model of sequence evolution) also was used because: (1) 

no currently available program can incorporate sequence 

variation for multiple loci into an analysis of molecular 

variance; (2) most intron alleles differ by only one or two 

substitutions (see “Results”); and (3) pairwise estimates of 

ΦST were similar to pairwise estimates of FST for individual 

introns (see “Results”). Whereas an analogue of Wright’s FST

that incorporates stepwise mutations has been developed for 

microsatellites (RST; Slatkin, 1995), FST was used to index 

population differentiation for murrelets because the latter 

index is preferable when the number of samples and/or loci 

is moderate to small, as in the present study (Gaggiotti and 

others, 1999). All estimates were tested for significance by 

randomization (10,000 replications).

To test for isolation by distance, the shortest geographic 

distance between sampling sites was estimated using either the 

most common sampling site (e.g., Dutch Harbor for Unalaska 

Island) or the mid-point of mutliple sampling sites (e.g., the 

mid-point of Kachemak Bay and Shuyak Island for Cook 

Inlet). The correlation between genetic distance (Wright’s 

linearized FST) and the natural logarithm of geographic 

distance was assessed using Mantel’s tests as implemented in 

ARLEQUIN with 1,000 randomizations of the data. 

To help determine the nature of population genetic 

structure in Marbled Murrelets, genetic variation was analyzed 

using the program STRUCTURE, which uses a Bayesian 

approach to find the grouping of individuals that minimizes 

deviations from Hardy-Weinberg and linkage equilibrium 

(Pritchard and others, 2000). The program was run under the 

admixture model with correlated allele frequencies, a burn-in 

of 5,000 iterations, and 50,000 replications after the burnin. (These numbers were first determined to be sufficient 

for likelihood values to stabilize.) Sampling location was 

not used as a priori information. Each value of k (number 

of populations) between 1 and 12 was run six times, and 

significance was calculated from the posterior probabilities 

following the protocols suggested by Pritchard and Wen 

(2003) and Evanno and others (2005). Note that this program 

makes no assumptions about the mutation model of the 

markers, so data for introns and microsatellites were pooled.

Contemporary Gene Flow

Estimation of gene flow from FST or its analogues is 

not valid for this species because: (1) populations may not 

have attained equilibrium between migration and genetic 

drift following recession of the Pleistocene glaciers; (2) gene 

flow may not be symmetrical and may not follow an n-island 

model; (3) effective population sizes may not be equal and 

stable; and (4) mutation rates are high for several molecular 

markers (especially the microsatellites; Hedrick, 1999). Use 

of the program MIGRATE (Beerli and Felsenstein, 1999) 

also is not valid because populations may not be in migration/

drift equilibrium. We attempted to estimate contemporary 

migration rates using a maximum likelihood based Bayesian 

approach (specifically, using the program BAYESASS; 

Wilson and Rannala, 2005), but reliable results could not 

be obtained, probably because of high gene flow within the 

central part of the species’ range (see “Results”). We therefore 

used probabilities of assignment from STRUCTURE as a first 

approximation of contemporary gene flow.

Results

Genetic Variability

All loci were variable, with the number of alleles per 

locus ranging from 5 (Ald) to 35 (Bma453; table 10). Most 

intron alleles differed by only one or two substitutions 

(Congdon and others, 2000; Friesen and others, Queens 

University, unpub. data, 2006). Significant heterozygote 

deficiencies were found for Ald in British Columbia, 

Washington, and northern California samples (table 10), 

suggesting the possible existence of a null (non-amplifying) 

allele. Further analyses were therefore conducted both with 

and without this locus; results are reported without Ald, but do 

not differ qualitatively if Ald was included. Otherwise, only 

two heterozygote deficiencies were found (table 10). 

Population Genetics 27
Table 10. Sample sizes (N), allele frequencies, allelic richness estimates (AR , corrected for the minimum per-locus sample size), 

observed and expected heterozygosities (HO and HE , respectively) and Wright’s inbreeding coefficients (FIS) for 23 loci within 12 

populations of Marbled Murrelets. 

[Heterozygosity estimates in bold indicate significant deviations from Hardy-Weinberg expectations. Inbreeding coefficients in bold are significantly less than 

zero. Blank cells indicate allele not found. Population abbreviations as in figure 4]

Locus/allele Near Andr Unal Shum Cook PWS Alex BC WA OR NCA CCA

Ald

 N 10 10 3 24 25 10 21 28 31 8 34 29

2 0.042

3 0.042 0.040 0.100 0.024 0.143 0.145 0.059 0.086

4 1.000 1.000 1.000 0.917 0.960 0.900 0.881 0.821 0.855 1.000 0.912 0.914

5 0.029

6 0.095 0.036

AR 1.000 1.000 na 1.754 1.363 1.763 1.917 2.144 1.819 1.000 1.753 1.626

HO na na na 0.167 0.000 0.000 0.143 0.000 0.033 na 0.059 0.172

HE na na na 0.160 0.078 0.189 0.220 0.309 0.252 na 0.167 0.160

FIS NA NA na -0.045 1.000 1.000 0.355 1.000 0.874 NA 0.651 -0.077

Enol

 N 10 8 3 20 26 10 24 29 33 15 36 36

1 0.100 0.375 0.167 0.150 0.192 0.200 0.083 0.103 0.106 0.067 0.028 0.069

2 0.600 0.500 0.167 0.425 0.288 0.150 0.313 0.328 0.318 0.133 0.389 0.528

3 0.300 0.125 0.667 0.400 0.519 0.650 0.583 0.569 0.545 0.800 0.556 0.361

4 0.028 0.014

6 0.025

7 0.015 0.014

8 0.014

9 0.021 0.015

AR 2.758 2.875 nc 3.092 2.885 2.851 2.815 2.685 2.990 2.386 2.516 2.946

HO 0.500 0.625 0.667 0.550 0.462 0.600 0.458 0.620 0.606 0.400 0.528 0.444

HE 0.568 0.633 0.600 0.653 0.622 0.542 0.566 0.568 0.599 0.349 0.546 0.594

FIS 0.126 0.014 -0.143 0.161 0.262 -0.113 0.194 -0.094 -0.013 -0.151 0.034 0.254

Gpd

 N 11 9 3 24 25 10 21 30 26 7 36 31

1 0.019

2 0.021 0.020 0.048 0.083

3 0.364 0.438 0.360 0.350 0.357 0.517 0.404 0.214 0.403 0.468

4 0.045 0.111 0.500 0.042 0.080 0.200 0.119 0.017 0.115 0.028 0.016

6 0.136 0.556 0.500 0.354 0.340 0.450 0.381 0.183 0.346 0.500 0.444 0.371

6 0.227 0.111 0.042 0.060 0.071 0.067 0.058 0.143 0.069 0.032

7 0.021 0.020 0.017

8 0.136 0.111 0.042 0.040 0.024 0.050 0.058 0.143 0.014 0.032

9 0.045 0.111 0.020 0.028

10 0.042 0.040 0.014 0.081

11 0.020

12 0.017

13 0.017

14 0.017

15 0.017

21 0.045

AR 5.046 4.268 nc 3.916 4.610 2.955 3.984 4.458 3.885 3.857 3.330 3.350

HO 0.727 0.778 1.000 0.625 0.760 0.900 0.240 0.700 0.692 0.571 0.750 0.677

HE 0.810 0.680 0.600 0.690 0.755 0.668 0.722 0.695 0.710 0.714 0.642 0.645

FIS 0.106 -0.155 -1.000 0.096 -0.007 -0.373 0.280 -0.007 0.026 0.213 -0.170 -0.051

28 Status Review of the Marbled Murrelet in Alaska and British Columbia
Locus/allele Near Andr Unal Shum Cook PWS Alex BC WA OR NCA CCA

Ldh

1 0.045 0.021 0.019 0.068 0.040 0.056 0.097

2 0.091 0.100 0.063 0.212 0.167 0.091 0.161 0.160 0.192 0.097 0.056

4 0.864 0.900 0.750 0.792 0.769 0.833 0.795 0.821 0.640 0.769 0.750 0.847

5 0.083 0.045 0.018

6 0.250 0.021 0.080 0.038 0.028

7 0.021 0.020 0.056

8 0.020 0.014

9 0.040

AR 2.169 2.000 nc 2.758 2.121 1.931 2.614 2.033 3.586 2.318 2.981 2.124

HO 0.273 0.200 0.500 0.375 0.385 0.111 0.409 0.286 0.600 0.308 0.333 0.167

HE 0.255 0.200 0.500 0.369 0.370 0.294 0.360 0.305 0.566 0.385 0.427 0.273

FIS -0.071 0.000 0.000 -0.017 -0.040 0.636 -0.139 0.063 -0.062 0.207 0.222 0.394

Lam

 N 10 8 3 24 25 10 24 27 33 6 36 36

1 0.042

2 0.050 0.037

3 0.850 0.500 0.833 0.792 0.900 0.700 0.750 0.759 0.758 0.917 0.764 0.694

4 0.083 0.040 0.100 0.021 0.037 0.045 0.069 0.097

6 0.021 0.100 0.083 0.056 0.045 0.042

6 0.150 0.500 0.167 0.104 0.060 0.050 0.146 0.111 0.152 0.083 0.083 0.181

7 0.028

AR 1.895 2.000 2.536 1.859 3.526 2.658 2.871 2.620 1.833 2.876 2.809

HO 0.300 0.500 0.333 0.375 0.120 0.200 0.417 0.407 0.364 0.167 0.389 0.583

HE 0.268 0.533 0.333 0.363 0.189 0.511 0.418 0.413 0.405 0.167 0.407 0.482

FIS -0.125 0.067 0.000 -0.035 0.368 0.621 0.002 0.014 0.104 0.000 0.045 -0.215

MPP

 N 8 5 0 22 24 10 20 27 32 10 36 36

1 0.023 0.031 0.042

2 0.563 0.500 0.750 0.854 0.700 0.750 0.778 0.609 0.800 0.764 0.556

3 0.100 0.045 0.104 0.150 0.100 0.130 0.047 0.100 0.069 0.069

4 0.438 0.400 0.159 0.042 0.150 0.100 0.074 0.172 0.056 0.278

5 0.023 0.050 0.019 0.063 0.056 0.069

6 0.050 0.014 0.028

7 0.078 0.050

AR 2.000 3.000 na 2.721 2.084 2.789 2.843 2.540 3.654 2.763 2.958 3.306

HO 0.625 0.600 na 0.318 0.208 0.600 0.400 0.407 0.531 0.400 0.389 0.583

HE 0.525 0.644 na 0.419 0.263 0.489 0.426 0.379 0.595 0.383 0.409 0.712

FIS -0.207 0.077 na 0.244 0.212 -0.241 0.062 -0.075 0.109 -0.108 0.050 0.048

OD

 N 11 10 3 24 26 10 24 27 33 15 36 36

1 0.682 0.350 0.667 0.458 0.673 0.400 0.521 0.519 0.439 0.500 0.444 0.486

2 0.050 0.146 0.019 0.150 0.042 0.074 0.091 0.067 0.056

3 0.227 0.050 0.167 0.167 0.192 0.150 0.292 0.222 0.167 0.233 0.208 0.264

4 0.063 0.038 0.200 0.042 0.037

5 0.045 0.350 0.063 0.058 0.021 0.093 0.015 0.033 0.028 0.042

6 0.045 0.050 0.042 0.100 0.021 0.056

8 0.063 0.019 0.021 0.076 0.056

9 0.045 0.028 0.014

10 0.014

11 0.014

12 0.050 0.030 0.083 0.167

Table 10. Sample sizes (N), allele frequencies, allelic richness estimates (AR , corrected for the minimum per-locus sample size), 

observed and expected heterozygosities (HO and HE , respectively) and Wright’s inbreeding coefficients (FIS) for 23 loci within 12 

populations of Marbled Murrelets.—Continued

[Heterozygosity estimates in bold indicate significant deviations from Hardy-Weinberg expectations. Inbreeding coefficients in bold are significantly less than 

zero. Blank cells indicate allele not found. Population abbreviations as in figure 4]

Population Genetics 29
Locus/allele Near Andr Unal Shum Cook PWS Alex BC WA OR NCA CCA

OD—Continued

 N 11 10 3 24 26 10 24 27 33 15 36 36

13 0.014

14 0.033 0.014

15 0.042 0.076 0.033 0.028

16 0.028

17 0.033 0.014

18 0.030

19 0.015

21 0.167

22 0.067

23 0.015

AR 2.879 4.760 nc 4.612 3.123 4.509 3.735 3.971 5.060 4.422 4.897 3.605

HO 0.636 0.900 0.667 0.708 0.538 0.800 0.625 0.667 0.758 0.600 0.750 0.667

HE 0.502 0.774 0.600 0.743 0.514 0.784 0.651 0.676 0.766 0.706 0.753 0.673

FIS -0.284 -0.174 -0.143 0.048 -0.048 -0.021 0.040 0.014 0.012 0.154 0.004 0.010

RP40

 N 9 5 0 23 26 10 22 28 31 11 36 36

1 0.200 0.283 0.288 0.150 0.364 0.232 0.323 0.318 0.292 0.542

2 0.444 0.500 0.435 0.192 0.350 0.273 0.321 0.177 0.409 0.306 0.167

3 0.056 0.174 0.212 0.300 0.205 0.196 0.226 0.227 0.208 0.153

4 0.500 0.300 0.058 0.045 0.071 0.048 0.014

5 0.022 0.058 0.050 0.018 0.032 0.042

6 0.022

7 0.022 0.096 0.050 0.045 0.054 0.081 0.042 0.056

8 0.043 0.096 0.100 0.068 0.107 0.097 0.045 0.111 0.069

9 0.016

AR 2.556 3.000 na 3.903 5.121 4.651 4.257 4.741 4.950 3.419 4.326 3.825

HO 0.667 0.600 na 0.696 0.731 0.900 0.818 0.679 0.806 0.636 0.806 0.583

HE 0.582 0.689 na 0.713 0.826 0.789 0.760 0.799 0.807 0.710 0.773 0.656

FIS -0.157 0.143 na 0.025 0.117 -0.149 -0.078 0.153 0.001 0.108 -0.043 0.113

Cco5-21

 N 7 4 6 24 29 10 21 28 0 7 32 36

101 0.063 0.017 0.024 0.018 0.016

105 0.357 0.625 0.083 0.292 0.276 0.200 0.214 0.143 0.214 0.250 0.167

107 0.083 0.021 0.034 0.024 0.018 0.031

109 0.143 0.125 0.500 0.479 0.534 0.650 0.524 0.607 0.786 0.609 0.694

111 0.034 0.018

113 0.071 0.125 0.250 0.042 0.034 0.050 0.119 0.054 0.078 0.042

117 0.021

121 0.214 0.125 0.083 0.063 0.052 0.050 0.095 0.143 0.016 0.083

123 0.071

125 0.143 0.021 0.017 0.050 0.014

AR 4.755 4.000 3.982 3.615 3.355 3.098 3.521 3.273 na 1.945 2.900 2.719

HO 0.571 0.750 0.500 0.750 0.552 0.600 0.571 0.607 na 0.429 0.594 0.444

HE 0.835 0.643 0.727 0.689 0.642 0.558 0.671 0.597 na 0.363 0.567 0.488

FIS 0.333 -0.200 0.333 -0.091 0.143 -0.080 0.152 -0.017 na -0.200 -0.047 0.090

Bma10-18

 N 7 5 7 24 26 10 22 30 0 8 36 36

1 0.100 0.125 0.058 0.050 0.091 0.056 0.153

4 0.019 0.017 0.063

5 0.143 0.100 0.042 0.077 0.068 0.033 0.125 0.111 0.139

6 0.071 0.100 0.214 0.167 0.231 0.300 0.205 0.217 0.125 0.306 0.264

Table 10. Sample sizes (N), allele frequencies, allelic richness estimates (AR , corrected for the minimum per-locus sample size), 

observed and expected heterozygosities (HO and HE , respectively) and Wright’s inbreeding coefficients (FIS) for 23 loci within 12 

populations of Marbled Murrelets.—Continued

[Heterozygosity estimates in bold indicate significant deviations from Hardy-Weinberg expectations. Inbreeding coefficients in bold are significantly less than 

zero. Blank cells indicate allele not found. Population abbreviations as in figure 4]

30 Status Review of the Marbled Murrelet in Alaska and British Columbia
Locus/allele Near Andr Unal Shum Cook PWS Alex BC WA OR NCA CCA

Bma10-18—Continued

 N 7 5 7 24 26 10 22 30 0 8 36 36

7 0.200 0.143 0.063 0.135 0.200 0.045 0.100 0.042 0.069

8 0.286 0.071 0.104 0.077 0.200 0.205 0.217 0.125 0.139 0.028

9 0.071 0.100 0.214 0.208 0.173 0.050 0.136 0.083 0.313 0.125

10 0.071 0.200 0.071 0.063 0.038 0.045 0.100 0.063 0.097

11 0.038 0.023 0.050 0.056 0.056

12 0.143 0.100 0.021 0.000 0.045 0.017 0.063 0.028 0.014

13 0.083 0.058 0.050 0.023 0.067 0.028

14 0.014 0.028

15 0.143 0.100 0.214 0.104 0.038 0.100 0.091 0.017 0.125 0.028 0.208

16 0.021 0.050 0.017

17 0.071 0.017

18 0.038 0.033

19 0.071 0.019

20 0.017

22 0.014

23 0.023

AR 5.776 6.756 5.385 5.615 5.671 5.024 5.599 5.566 na 5.554 5.157 4.953

HO 1.000 0.800 1.000 0.760 0.846 0.900 0.909 0.967 na 0.625 0.861 0.722

HE 0.901 0.956 0.890 0.900 0.891 0.853 0.889 0.883 na 0.883 0.852 0.845

FIS -0.120 0.179 -0.135 0.115 0.051 -0.059 -0.023 -0.096 na 0.307 -0.011 0.148

Bma301

 N 11 12 12 27 31 9 22 30 33 15 36 36

134 0.015

136 0.042 0.042 0.185 0.097 0.111 0.068 0.133 0.076 0.067 0.153 0.139

140 0.227 0.250 0.042 0.185 0.274 0.389 0.182 0.333 0.227 0.267 0.361 0.194

144 0.136 0.042 0.208 0.259 0.274 0.111 0.250 0.100 0.197 0.233 0.181 0.139

148 0.545 0.542 0.542 0.278 0.242 0.278 0.409 0.317 0.288 0.300 0.250 0.222

152 0.091 0.083 0.125 0.093 0.081 0.111 0.068 0.067 0.197 0.100 0.056 0.306

156 0.042 0.042 0.016 0.050 0.033

160 0.016 0.023

AR 3.922 4.898 4.971 4.797 5.142 4.980 4.849 5.123 4.960 5.232 4.562 4.836

HO 0.636 0.750 0.500 0.667 0.742 0.889 0.727 0.700 0.818 0.867 0.611 0.722

HE 0.654 0.659 0.670 0.793 0.787 0.778 0.744 0.767 0.794 0.795 0.759 0.792

FIS

0.028 -0.145 0.263 0.162 0.059 -0.153 0.023 0.088 -0.031 -0.093 0.197 0.089

Bma356

 N 11 12 12 28 31 9 23 30 33 15 36 36

119 0.018 0.022 0.045 0.014

123 0.048 0.056 0.022 0.017 0.014

127 0.016 0.056 0.033 0.015 0.014

131 0.036 0.017 0.030

135 0.042 0.018 0.065 0.111 0.043 0.033 0.015 0.033 0.014

139 0.045 0.042 0.143 0.065 0.109 0.083 0.030 0.100 0.056 0.014

143 0.273 0.292 0.125 0.036 0.065 0.167 0.087 0.083 0.061 0.100 0.056 0.194

147 0.136 0.125 0.125 0.125 0.113 0.217 0.083 0.258 0.100 0.306 0.153

151 0.227 0.250 0.125 0.179 0.145 0.278 0.152 0.233 0.182 0.167 0.181 0.236

155 0.136 0.125 0.167 0.143 0.129 0.222 0.152 0.183 0.197 0.333 0.111 0.083

159 0.091 0.042 0.250 0.232 0.161 0.056 0.022 0.100 0.091 0.067 0.153 0.056

163 0.125 0.054 0.097 0.056 0.152 0.117 0.061 0.067 0.069 0.042

167 0.083 0.042 0.065 0.022 0.017 0.015 0.033 0.014 0.181

171 0.091 0.042 0.032 0.014 0.014

Table 10. Sample sizes (N), allele frequencies, allelic richness estimates (AR , corrected for the minimum per-locus sample size), 

observed and expected heterozygosities (HO and HE , respectively) and Wright’s inbreeding coefficients (FIS) for 23 loci within 12 

populations of Marbled Murrelets.—Continued

[Heterozygosity estimates in bold indicate significant deviations from Hardy-Weinberg expectations. Inbreeding coefficients in bold are significantly less than 

zero. Blank cells indicate allele not found. Population abbreviations as in figure 4]

Population Genetics 31
Locus/allele Near Andr Unal Shum Cook PWS Alex BC WA OR NCA CCA

Bma356—Continued

 N 11 12 12 28 31 9 23 30 33 15 36 36

175 0.018 0.014

AR 6.571 6.843 7.216 7.269 8.709 7.549 7.578 7.865 7.297 7.365 6.928 6.757

HO 1.000 0.833 0.833 0.893 1.000 0.778 0.956 0.967 0.848 0.933 0.889 0.833

HE 0.857 0.844 0.880 0.867 0.909 0.869 0.879 0.879 0.855 0.848 0.838 0.850

FIS

-0.176 0.013 0.056 -0.031 -0.103 0.111 -0.090 -0.102 0.007 -0.104 -0.062 0.020

Bma365

 N 11 12 12 28 29 9 23 30 33 14 36 36

196 0.015

200 0.318 0.125 0.125 0.143 0.155 0.222 0.196 0.250 0.167 0.036 0.139 0.167

204 0.045 0.042 0.232 0.103 0.111 0.130 0.083 0.152 0.143 0.111 0.083

208 0.136 0.125 0.208 0.107 0.241 0.278 0.065 0.150 0.106 0.179 0.278 0.056

212 0.167 0.042 0.125 0.121 0.222 0.152 0.133 0.121 0.214 0.264 0.417

216 0.318 0.500 0.500 0.214 0.224 0.111 0.239 0.333 0.197 0.286 0.083 0.181

220 0.091 0.042 0.054 0.052 0.087 0.106 0.107 0.042 0.056

224 0.018 0.086 0.043 0.017 0.106 0.056

228 0.054 0.056 0.017 0.030 0.028 0.042

232 0.045 0.042 0.042 0.036 0.017 0.087 0.017 0.036

236 0.042

240 0.045 0.018

AR 6.104 5.271 5.638 7.083 6.444 5.876 6.858 5.479 7.092 6.041 6.177 5.550

HO 0.636 0.750 0.500 0.750 0.862 0.667 0.870 0.867 0.879 0.929 0.861 0.806

HE 0.801 0.717 0.714 0.860 0.846 0.843 0.862 0.792 0.874 0.836 0.820 0.762

FIS

0.213 -0.048 0.309 0.130 -0.019 0.220 -0.009 -0.097 -0.005 -0.116 -0.050 -0.058

Bma368

 N 11 12 9 25 30 9 23 30 33 15 35 36

158 0.015

174 0.020 0.100 0.083 0.061 0.133 0.014 0.111

178 0.056 0.017 0.056 0.017 0.121 0.100 0.100 0.083

186 0.015

190 0.017

194 0.045 0.111 0.100 0.067 0.056 0.087 0.050 0.015 0.100 0.086 0.028

198 0.045 0.000 0.020 0.050 0.056 0.022 0.050 0.076 0.033 0.043 0.014

202 0.167 0.100 0.050 0.111 0.109 0.033 0.076 0.100 0.014 0.056

206 0.017 0.130 0.067 0.061 0.033 0.014 0.014

210 0.100 0.050 0.043 0.017 0.000 0.033 0.029

214 0.045 0.042 0.056 0.060 0.083 0.056 0.022 0.050 0.030 0.014 0.014

218 0.056 0.040 0.033 0.056 0.022 0.014

222 0.056 0.020 0.017 0.056 0.022 0.017 0.061 0.029 0.083

226 0.227 0.250 0.056 0.060 0.017 0.056 0.043 0.050 0.015 0.033 0.071 0.056

230 0.318 0.208 0.222 0.040 0.083 0.065 0.050 0.086 0.014

234 0.136 0.250 0.040 0.017 0.056 0.065 0.017 0.045 0.133 0.057 0.028

238 0.045 0.125 0.056 0.020 0.087 0.100 0.045 0.057 0.028

242 0.045 0.083 0.060 0.067 0.111 0.050 0.076 0.067 0.043 0.139

246 0.042 0.160 0.083 0.056 0.130 0.067 0.045 0.033 0.114 0.153

250 0.111 0.060 0.033 0.111 0.065 0.067 0.045 0.033 0.029 0.042

254 0.045 0.056 0.060 0.083 0.056 0.043 0.033 0.045 0.033 0.057 0.069

258 0.045 0.020 0.083 0.111 0.022 0.067 0.030 0.033 0.071 0.069

262 0.020 0.017 0.022 0.017 0.076 0.100 0.057

266 0.017 0.083 0.030

274 0.015

Table 10. Sample sizes (N), allele frequencies, allelic richness estimates (AR , corrected for the minimum per-locus sample size), 

observed and expected heterozygosities (HO and HE , respectively) and Wright’s inbreeding coefficients (FIS) for 23 loci within 12 

populations of Marbled Murrelets.—Continued

[Heterozygosity estimates in bold indicate significant deviations from Hardy-Weinberg expectations. Inbreeding coefficients in bold are significantly less than 

zero. Blank cells indicate allele not found. Population abbreviations as in figure 4]

32 Status Review of the Marbled Murrelet in Alaska and British Columbia
Locus/allele Near Andr Unal Shum Cook PWS Alex BC WA OR NCA CCA

Bma368—Continued

 N 11 12 9 25 30 9 23 30 33 15 35 36

278 0.017

AR 8.078 6.202 10.209 10.592 11.211 12.863 10.457 11.557 11.357 10.626 10.905 9.707

HO 0.727 0.750 1.000 0.920 0.867 1.000 1.000 0.933 0.970 0.933 0.971 0.944

HE 0.853 0.841 0.928 0.838 0.950 0.974 0.938 0.955 0.952 0.943 0.945 0.923

FIS

0.153 0.112 -0.083 0.020 0.089 -0.029 -0.068 0.023 -0.019 0.010 -0.028 -0.023

Bma371

 N 11 12 11 28 30 9 23 30 33 15 36 36

224 0.017

232 0.017

234 0.033

236 0.018 0.017 0.033

240 0.045 0.018

242 0.017 0.015

246 0.015 0.042

248 0.045 0.017

250 0.050 0.017 0.015 0.014 0.028

252 0.017

254 0.033 0.065 0.050 0.045 0.033 0.042 0.042

258 0.018 0.083 0.111 0.043 0.033 0.061 0.100 0.042 0.014

262 0.045 0.042 0.071 0.083 0.056 0.130 0.150 0.045 0.100 0.250 0.097

264 0.017

266 0.091 0.208 0.273 0.232 0.167 0.111 0.196 0.217 0.152 0.067 0.097 0.139

268 0.033

270 0.318 0.458 0.455 0.250 0.233 0.222 0.283 0.183 0.273 0.400 0.236 0.250

274 0.136 0.125 0.045 0.232 0.117 0.222 0.174 0.250 0.242 0.167 0.194 0.167

278 0.273 0.042 0.091 0.107 0.083 0.167 0.109 0.067 0.061 0.028

282 0.091 0.125 0.015 0.033 0.069 0.111

286 0.017 0.056 0.014 0.056

290 0.018 0.017 0.030 0.028

294 0.045 0.018 0.056 0.017 0.030 0.014 0.028

298 0.045 0.018

386 0.017

AR 6.312 5.277 5.844 6.331 8.743 7.654 6.108 6.515 7.275 7.264 6.672 7.744

HO 0.727 0.750 0.636 0.679 0.900 0.778 0.870 0.867 0.939 0.867 0.917 0.972

HE 0.823 0.743 0.736 0.826 0.892 0.889 0.835 0.840 0.842 0.809 0.836 0.872

FIS

0.121 -0.010 0.141 0.181 -0.009 0.132 -0.043 -0.033 -0.117 -0.074 -0.097 -0.117

Bma433

 N 9 12 11 26 24 8 22 30 33 14 35 36

137 0.019

147 0.019 0.036

149 0.045 0.058 0.250 0.063 0.159 0.117 0.121 0.036 0.071 0.194

153 0.222 0.250 0.318 0.077 0.104 0.188 0.227 0.117 0.106 0.107 0.343 0.292

157 0.056 0.167 0.227 0.212 0.271 0.063 0.136 0.233 0.258 0.250 0.243 0.097

159 0.038 0.021 0.045 0.050 0.015 0.014 0.014

161 0.063 0.063 0.023 0.033 0.030 0.036 0.014

163 0.063

165 0.500 0.375 0.091 0.135 0.063 0.023 0.017 0.045 0.014 0.167

169 0.167 0.091 0.038 0.042 0.188 0.023 0.100 0.015 0.071 0.029

171 0.023

172 0.015

Table 10. Sample sizes (N), allele frequencies, allelic richness estimates (AR , corrected for the minimum per-locus sample size), 

observed and expected heterozygosities (HO and HE , respectively) and Wright’s inbreeding coefficients (FIS) for 23 loci within 12 

populations of Marbled Murrelets.—Continued

[Heterozygosity estimates in bold indicate significant deviations from Hardy-Weinberg expectations. Inbreeding coefficients in bold are significantly less than 

zero. Blank cells indicate allele not found. Population abbreviations as in figure 4]

Population Genetics 33
Locus/allele Near Andr Unal Shum Cook PWS Alex BC WA OR NCA CCA

Bma433—Continued

 N 9 12 11 26 24 8 22 30 33 14 35 36

173 0.045 0.038 0.021 0.068 0.050 0.076 0.071 0.071

175 0.017

177 0.045 0.077 0.063 0.067 0.045 0.036 0.057

181 0.019 0.125 0.045 0.033 0.045 0.071 0.071 0.014

185 0.045 0.038 0.068 0.033 0.091 0.036 0.014 0.139

189 0.056 0.021 0.063 0.030 0.179 0.029 0.042

191 0.038

193 0.038 0.125 0.045 0.017 0.030 0.029

197 0.019 0.042 0.045 0.030

201 0.038 0.033 0.036

205 0.038 0.015

209 0.042 0.045 0.017

213 0.125 0.015

217 0.019 0.036

221 0.019 0.021 0.023 0.014

225 0.023 0.017

229 0.021 0.023

233 0.063 0.028

237 0.042 0.033

241 0.019 0.015

257 0.017

277 0.045

AR 4.778 5.299 8.234 10.522 7.804 10.000 9.363 9.529 9.248 9.400 7.001 6.318

HO 0.889 0.833 0.909 0.885 0.875 0.875 0.955 0.967 0.879 0.929 0.800 0.833

HE 0.706 0.783 0.857 0.925 0.854 0.933 0.904 0.907 0.896 0.902 0.813 0.829

FIS

-0.280 -0.068 -0.064 0.045 -0.025 0.067 -0.058 -0.067 0.020 -0.030 0.017 -0.005

Bma439

 N 11 12 11 26 31 9 23 30 33 15 35 36

252 0.038 0.067

268 0.016

276 0.019 0.016

280 0.042 0.038 0.016 0.056 0.043 0.050 0.100 0.097

284 0.038 0.129 0.056 0.117 0.045 0.067 0.014 0.042

288 0.182 0.250 0.182 0.115 0.177 0.000 0.174 0.183 0.182 0.133 0.114 0.153

292 0.318 0.125 0.045 0.115 0.113 0.111 0.065 0.050 0.121 0.133 0.114 0.028

296 0.182 0.000 0.045 0.154 0.065 0.043 0.100 0.106 0.067 0.157 0.111

300 0.000 0.208 0.182 0.154 0.097 0.111 0.239 0.133 0.167 0.133 0.086 0.042

304 0.227 0.292 0.364 0.231 0.242 0.333 0.174 0.167 0.197 0.200 0.200 0.208

308 0.091 0.083 0.136 0.096 0.065 0.278 0.196 0.117 0.136 0.167 0.171 0.208

312 0.045 0.032 0.056 0.043 0.067 0.030 0.014 0.042

316 0.032 0.017 0.015 0.033 0.014 0.069

320 0.014

324 0.022

AR 4.931 5.536 6.165 7.400 7.724 6.654 6.758 7.750 6.877 7.777 7.256 7.377

HO 0.818 0.833 0.818 0.741 0.968 0.667 0.783 0.833 0.788 1.000 0.800 0.889

HE 0.810 0.819 0.814 0.881 0.874 0.824 0.852 0.889 0.866 0.894 0.874 0.869

FIS

-0.011 -0.019 -0.006 0.156 -0.109 0.200 0.083 0.063 0.091 -0.123 0.086 -0.023

Table 10. Sample sizes (N), allele frequencies, allelic richness estimates (AR , corrected for the minimum per-locus sample size), 

observed and expected heterozygosities (HO and HE , respectively) and Wright’s inbreeding coefficients (FIS) for 23 loci within 12 

populations of Marbled Murrelets.—Continued

[Heterozygosity estimates in bold indicate significant deviations from Hardy-Weinberg expectations. Inbreeding coefficients in bold are significantly less than 

zero. Blank cells indicate allele not found. Population abbreviations as in figure 4]

34 Status Review of the Marbled Murrelet in Alaska and British Columbia
Locus/allele Near Andr Unal Shum Cook PWS Alex BC WA OR NCA CCA

Bma443

 N 11 12 11 28 30 9 23 30 33 13 35 36

146 0.036

150 0.022

154 0.018 0.017

158 0.042 0.091 0.018 0.033 0.111 0.050 0.015 0.077 0.043

162 0.182 0.208 0.045 0.107 0.150 0.111 0.022 0.033 0.076 0.115 0.214 0.153

166 0.273 0.083 0.227 0.214 0.100 0.174 0.233 0.106 0.115 0.100 0.014

170 0.318 0.083 0.091 0.179 0.117 0.111 0.152 0.083 0.212 0.192 0.143 0.528

174 0.136 0.125 0.273 0.125 0.133 0.111 0.152 0.267 0.136 0.115 0.100 0.014

178 0.091 0.125 0.091 0.196 0.167 0.167 0.174 0.183 0.242 0.154 0.100 0.069

182 0.125 0.089 0.183 0.111 0.109 0.100 0.121 0.192 0.171 0.097

186 0.208 0.136 0.018 0.083 0.167 0.174 0.033 0.045 0.043 0.083

190 0.045 0.033 0.111 0.022 0.045 0.038 0.071 0.042

194 0.014

AR 4.920 7.378 7.247 6.930 7.319 7.961 6.796 6.439 6.841 7.317 7.513 5.292

HO 0.818 0.917 0.909 0.786 0.833 0.778 0.870 0.833 0.879 0.769 0.886 0.722

HE 0.801 0.888 0.866 0.862 0.880 0.922 0.869 0.833 0.855 0.889 0.878 0.684

FIS

-0.023 -0.034 -0.053 0.090 0.054 0.164 -0.001 -0.001 -0.029 0.140 -0.009 -0.056

Bma453

 N 11 12 11 28 31 9 23 30 33 14 35 36

216 0.016

220 0.018 0.014

224 0.014

228 0.054 0.016 0.087 0.050 0.015 0.036 0.043

230 0.022 0.036

232 0.042 0.045 0.054 0.081 0.065 0.017 0.061 0.071 0.071

234 0.032 0.056

236 0.071 0.065 0.043 0.150 0.030 0.107 0.029 0.014

238 0.042 0.045 0.036 0.022 0.014

240 0.091 0.054 0.032 0.111 0.043 0.100 0.152 0.071 0.086 0.069

242 0.045 0.018 0.016 0.036

244 0.045 0.083 0.091 0.054 0.097 0.167 0.130 0.017 0.091 0.143 0.057 0.333

246 0.083 0.045 0.036 0.016 0.017 0.030 0.036

248 0.273 0.042 0.091 0.054 0.145 0.167 0.022 0.050 0.091 0.036 0.186 0.153

250 0.018 0.022 0.017 0.029

252 0.182 0.292 0.227 0.089 0.048 0.111 0.109 0.100 0.076 0.071 0.143 0.069

254 0.091 0.036 0.016 0.033 0.061 0.071 0.029

256 0.227 0.250 0.091 0.036 0.081 0.167 0.065 0.083 0.076 0.107 0.071 0.153

258 0.018 0.032 0.022 0.050 0.045 0.036

260 0.125 0.125 0.145 0.056 0.065 0.083 0.030 0.036 0.057 0.042

262 0.087 0.017 0.036 0.057

264 0.045 0.036 0.032 0.043 0.045 0.029 0.014

266 0.045 0.018 0.043 0.067 0.015 0.042

268 0.054 0.032 0.056 0.034 0.045 0.071 0.014 0.014

270 0.016 0.043 0.033 0.061 0.014 0.028

272 0.091 0.054 0.016 0.022 0.045 0.029 0.014

274 0.000 0.018 0.016 0.033 0.015

276 0.045 0.045 0.018 0.016 0.022

278 0.036 0.056 0.022 0.014

280 0.042 0.045 0.016 0.033 0.014

282 0.017 0.015

284 0.045 0.056 0.014

Table 10. Sample sizes (N), allele frequencies, allelic richness estimates (AR , corrected for the minimum per-locus sample size), 

observed and expected heterozygosities (HO and HE , respectively) and Wright’s inbreeding coefficients (FIS) for 23 loci within 12 

populations of Marbled Murrelets.—Continued

[Heterozygosity estimates in bold indicate significant deviations from Hardy-Weinberg expectations. Inbreeding coefficients in bold are significantly less than 

zero. Blank cells indicate allele not found. Population abbreviations as in figure 4]

Population Genetics 35
Locus/allele Near Andr Unal Shum Cook PWS Alex BC WA OR NCA CCA

Bma453—Continued

 N 11 12 11 28 31 9 23 30 33 14 35 36

286 0.028

296 0.016

AR 7.569 7.436 10.766 11.965 10.724 9.431 11.376 10.761 10.712 11.540 10.118 7.554

HO 0.818 0.750 0.909 0.929 0.903 0.778 0.913 0.867 0.970 1.000 0.914 0.917

HE 0.861 0.851 0.935 0.958 0.936 0.928 0.951 0.941 0.940 0.955 0.924 0.838

FIS

0.053 0.124 0.029 0.032 0.036 0.170 0.040 0.079 -0.032 -0.049 0.010 -0.095

Bma523

 N 11 12 11 27 30 9 23 30 33 14 35 36

100 0.042 0.111 0.030 0.036 0.071

104 0.017 0.017 0.015 0.036 0.057 0.042

108 0.045 0.111 0.083 0.056 0.130 0.133 0.045 0.071 0.057 0.056

112 0.273 0.208 0.182 0.111 0.133 0.222 0.196 0.067 0.182 0.107 0.114 0.069

116 0.136 0.208 0.318 0.093 0.217 0.111 0.065 0.183 0.197 0.071 0.057 0.097

120 0.318 0.125 0.091 0.074 0.183 0.056 0.196 0.217 0.167 0.179 0.100 0.347

124 0.045 0.208 0.227 0.185 0.167 0.222 0.283 0.167 0.182 0.250 0.200 0.069

128 0.125 0.091 0.278 0.150 0.167 0.087 0.117 0.152 0.143 0.300 0.083

132 0.182 0.083 0.091 0.111 0.050 0.056 0.043 0.067 0.030 0.107 0.043 0.208

136 0.033 0.028

140 0.019

144 0.019

AR 5.439 6.506 5.803 6.858 6.498 7.654 6.054 6.942 6.522 7.626 6.975 6.650

HO 0.818 1.000 1.000 0.926 0.767 1.000 0.826 0.833 0.970 0.786 0.743 0.889

HE 0.805 0.866 0.827 0.853 0.856 0.889 0.831 0.864 0.853 0.881 0.842 0.816

FIS

-0.017 -0.163 -0.222 -0.088 0.106 -0.134 0.006 0.037 -0.139 0.112 0.120 -0.091

Bma553

 N 10 12 11 26 26 9 22 30 33 14 35 36

119 0.028

121 0.450 0.208 0.091 0.038 0.096 0.067 0.106 0.107 0.029 0.083

125 0.050 0.208 0.182 0.019 0.057 0.111 0.091 0.083 0.076 0.029 0.042

129 0.083 0.091 0.115 0.019 0.056 0.083 0.045 0.036 0.014 0.069

133 0.058 0.038 0.050 0.061 0.071 0.014

137 0.083 0.182 0.115 0.096 0.056 0.159 0.067 0.152 0.107 0.157 0.097

141 0.350 0.333 0.273 0.288 0.346 0.389 0.273 0.317 0.273 0.214 0.214 0.139

145 0.091 0.192 0.288 0.278 0.091 0.183 0.152 0.286 0.314 0.375

149 0.050 0.083 0.091 0.135 0.038 0.205 0.150 0.061 0.179 0.200 0.153

153 0.038 0.019 0.056 0.182 0.061 0.029

157 0.056 0.015 0.014

AR 4.568 5.693 6.736 6.763 6.051 6.549 5.639 6.587 7.390 6.252 5.606 6.401

HO 0.600 1.000 0.909 0.885 0.769 0.889 0.909 0.867 0.848 0.714 0.857 0.806

HE 0.695 0.815 0.866 0.845 0.788 0.791 0.828 0.832 0.862 0.841 0.799 0.804

FIS

0.143 -0.239 -0.053 -0.048 0.022 -0.133 -0.101 -0.042 0.016 0.156 -0.074 -0.002

Bma555

 N 11 12 10 28 30 9 23 30 33 15 36 36

114 0.017 0.033 0.014

118 0.042 0.050 0.143 0.150 0.111 0.152 0.183 0.167 0.133 0.153 0.194

122 0.018 0.017 0.014

134 0.150

138 0.042 0.100 0.143 0.083 0.167 0.087 0.067 0.030 0.100 0.014 0.097

142 0.091 0.050 0.018 0.067 0.111 0.022 0.033 0.030 0.056

144 0.017

Table 10. Sample sizes (N), allele frequencies, allelic richness estimates (AR , corrected for the minimum per-locus sample size), 

observed and expected heterozygosities (HO and HE , respectively) and Wright’s inbreeding coefficients (FIS) for 23 loci within 12 

populations of Marbled Murrelets.—Continued

[Heterozygosity estimates in bold indicate significant deviations from Hardy-Weinberg expectations. Inbreeding coefficients in bold are significantly less than 

zero. Blank cells indicate allele not found. Population abbreviations as in figure 4]

36 Status Review of the Marbled Murrelet in Alaska and British Columbia
Locus/allele Near Andr Unal Shum Cook PWS Alex BC WA OR NCA CCA

Bma555—Continued

 N 11 12 10 28 30 9 23 30 33 15 36 36

146 0.364 0.542 0.150 0.071 0.100 0.109 0.017 0.033 0.056 0.042

150 0.227 0.250 0.000 0.036 0.050 0.043 0.050 0.091 0.100 0.014

154 0.022 0.017 0.033 0.111 0.014

158 0.136 0.042 0.050 0.054 0.067 0.043 0.017 0.061 0.067 0.069 0.069

162 0.091 0.083 0.250 0.089 0.133 0.222 0.043 0.067 0.136 0.133 0.153 0.028

166 0.150 0.179 0.100 0.111 0.109 0.117 0.106 0.100 0.111 0.125

170 0.045 0.125 0.117 0.111 0.152 0.117 0.121 0.133 0.111 0.278

174 0.045 0.071 0.067 0.056 0.043 0.133 0.197 0.100 0.069 0.056

178 0.018 0.033 0.056 0.130 0.100 0.045 0.067 0.069 0.042

182 0.050 0.036 0.056 0.022 0.017 0.015 0.042

186 0.022

190 0.017

AR 6.311 4.898 8.158 8.605 9.079 8.641 9.195 9.156 7.836 9.180 8.793 7.435

HO 0.818 0.417 1.000 0.929 0.967 1.000 0.957 0.900 0.879 1.000 0.889 0.861

HE 0.814 0.659 0.895 0.903 0.917 0.915 0.916 0.911 0.886 0.923 0.909 0.856

FIS -0.006 0.379 -0.125 -0.029 -0.055 -0.099 -0.045 0.013 0.009 -0.082 0.022 -0.006

Mean AR for 

introns

2.538 2.863 na 3.162 2.896 3.122 3.103 3.180 3.571 2.750 3.205 2.949

Mean AR for 

microsatellites

5.717 5.857 6.882 7.453 7.462 7.424 7.154 7.324 7.784 7.366 6.897 6.378

Mean AR for all 

loci

4.561 4.768 6.882 5.893 5.802 5.860 5.681 5.818 6.099 5.687 5.555 5.131

Overall FIS 0.005 0.003 -0.033 0.071 0.051 0.036 0.025 0.020 0.014 0.041 0.008 0.006

Table 10. Sample sizes (N), allele frequencies, allelic richness estimates (AR , corrected for the minimum per-locus sample size), 

observed and expected heterozygosities (HO and HE , respectively) and Wright’s inbreeding coefficients (FIS) for 23 loci within 12 

populations of Marbled Murrelets.—Continued

[Heterozygosity estimates in bold indicate significant deviations from Hardy-Weinberg expectations. Inbreeding coefficients in bold are significantly less than 

zero. Blank cells indicate allele not found. Population abbreviations as in figure 4]

Population Genetics 37
Most sampling sites only had significant deviations from 

linkage equilibrium for 5 or fewer pairs of loci (of a possible 

231 pairs; table 11a). However for Oregon, 31 pairs of loci 

showed significant deviations from linkage equilibrium, 

suggesting the possibility of nonrandom sampling and/or 

non-random mating at this site. After excluding samples from 

Oregon, only 3 pairs of loci (of a possible 231 pairs) showed 

evidence of linkage disequilibrium within 2 or more sites: 

(1) Bma10-18 and Cco5-21; (2) Bma365 and Bma553; and 

(3) Bma433 and Bma553 (table 11b). Subsequent analyses 

were therefore conducted both with and without Bma10-18

and Bma553 to reduce potential complications from linkage. 

Results are reported without these loci, but do not differ 

qualitatively if they are included. 

With one exception (Ald, which was invariant in the 

three Aleutian Islands sites), all loci were variable in all 

sites. Allelic richness did not differ among sites for introns 

(F11,76 = 0.48, P = 0.91), microsatellites (F11,154 = 1.49, P = 

0.14), or all loci combined (F11,242 = 1.07, P = 0.39; table 10). 

Several estimates of Wright’s inbreeding coefficient (FIS) 

were significantly less than zero after Bonferroni corrections 

(table 10). However, these low values tended to occur in sites 

with small sample sizes (e.g., Near and Unalaska islands), 

suggesting they represent a sampling artifact. Allelic richness, 

observed heterozygosity and FIS did not differ significantly 

among sites (analyses of variance, all P > 0.10; table 10).

Population Genetic Structure

All sampling sites except the Andreanof Islands had 

private alleles at one or more nuclear loci (table 10). However, 

only one of these alleles occurred at a frequency higher than 

0.10. No evidence was found for phylogeographic structuring 

of intron alleles (data not shown). 

Table 11a. Number of pairs of loci (N) showing significant 

deviations from linkage equilibrium for each of 12 sampling sites.

Site N Site N

Near 0 Alex 10

Andr 2 BC 3

Unal 3 WA 0

Shum 0 OR 31

Cook 6 NCA 0

PWS 2 CCA 0

Global estimates of ΦST or FST were low but significantly 

greater than zero for most loci, and averaged 0.022 over all 

loci (SE = 0.002; max = 0.047; table 12). Estimates of ΦST

and FST were similar for each intron (table 12). In pairwise 

comparisons of sampling sites, estimates of ΦST or FST ranged 

as much as 0.109, and were significantly greater than 0 for 

most comparisons involving birds from the Near Islands 

and/or central California as well as for several comparisons 

involving birds from the Andreanof Islands and/or northern 

California (table 13). 

Mantel’s tests indicated a low but significant correlation 

between Wright’s linearized FST and the natural logarithm of 

geographic distance both for all loci combined (r = 0.45, P = 

0.001; fig. 5), and for introns and microsatellites separately 

(r = 0.30, P = 0.015; and r = 0.28, P = 0.007; respectively). 

Note however that almost all comparisons involving the 

Near Islands, Andreanof Islands and/or central California 

have positive values of Wright’s linearized FST whereas 

few comparisons within the central area do, and that the 

correlation loses significance if any of the peripheral sites are 

removed. Thus, the correlation does not appear to be a simple 

effect of isolation by distance, but a result of differentiation 

of murrelets in the Near and Andreanof Islands and central 

California. 

Results from STRUCTURE provided strong support 

for four genetic populations (P < 0.0001; table 14; fig. 6). 

Genetic Population 1 (represented by red on fig. 6) 

primarily comprised samples from the Near and Andreanof 

Islands; Genetic Population 4 (yellow on fig. 6) primarily 

comprised samples from central California. Individuals 

sampled between Unalaska Island and northern California 

were assigned with varying probabilities to two additional 

genetic populations (green and blue on fig. 6), which did 

not appear to be geographically segregated. To resolve these 

latter two populations, the analysis was re-run: (i) under 

the no-admixture model; (ii) with introns only; (iii) with 

microsatellites only; and (iv) without samples from the Near 

or Andreadnof Islands or central California (see Evanno and 

others, 2005). Introns alone did not resolve any population 

genetic structure, presumably because of low power (only 

seven loci). Microsatellites alone yielded results similar to 

the full data set (i.e., four genetic populations) but with lower 

probabilities of assignment. For the analysis involving samples 

from the central region only, the most probable value of k

was 1 (P < 0.0001), suggesting that murrelets from Unalaska 

Island to northern California comprise a single genetic 

population. 

38 Status Review of the Marbled Murrelet in Alaska and British Columbia
Table 11b. Number of sampling sites with significant deviations from linkage equilibrium at a Bonferroni corrected a = 0.05 for pairwise comparisons of loci.

[Numbers below the diagonal include all populations; numbers above the diagonal exclude samples from Oregon. Blank cells = no populations exhibit linkage disequilibrium.]

Ald Eno Gpd Ldh Lam MPP OD RP40 Cco 5-21 Bm 10-18 Bma 301 Bma 356 Bma 365 Bma 368 Bma 371 Bma 433 Bma 439 Bma 443 Bma 453 Bma 523 Bma 553 Bma 555

Ald 1 1Enol 1GpdLdh 1Lam 1 1MPP 1 1OD 1 1RP40 1 1Cco5-21 3Bma10-18 4Bma301 1 1Bma356 1 1Bma365 1 2 1Bma368 1 1 1 1

Bma371 1 1 1 1 1 1 1 1

Bma433 1 2

Bma439 1 1 1 1 1 1

Bma443 1 1 1 1 1 1

Bma453 1 1 2

Bma523 1 1 1 1 1

Bma553 1 1 3 3 1 1 1 1

Bma555 1 1 1 1 1 2 1

Population Genetics 39
Table 12. Locus-specific estimates of global ΦST (for introns) or 

FST (for introns and microsatellites) for Marbled Murrelets.

[ns, not significant] 

Locus ΦST P FST P

Ald 0.018 ns 0.016 ns

Enol 0.045 <0.001 0.047 <0.0001

GPD 0.028 <0.001 0.021 <0.01

LDH 0.001 0.1 0.006 ns

Lam 0.021 <0.01 0.019 <0.05

MPP 0.041 <0.0001 0.036 <0.0001

OD 0.034 <0.0001 0.018 <0.01

RP40 0.043 <0.0001 0.033 <0.0001

Cco5-21 0.027 <0.01

Bma10-18 0.015 <0.01

Bma301 0.033 <0.0001

Bma356 0.004 ns

Bma365 0.030 <0.0001

Bma368 0.015 <0.0001

Bma371 0.010 <0.05

Bma433 0.033 <0.0001

Bma439 0.004 ns

Bma443 0.035 <0.0001

Bma453 0.017 <0.0001

Bma523 0.020 <0.0001

Bma553 0.025 <0.0001

Bma555 0.028 <0.0001

Mean 0.029 0.022

SE 0.005 0.002

Figure 5. Correlation between Wright’s linearized 

FST (=FST / [1 - FST]) and the natural logarithm of the shortest 

geographic distance between sampling sites (km) for Marbled 

Murrelets. Crosses indicate comparisons involving the Near or 

Andreanof Islands; open symbols indicate comparisons involving 

central California.

Figure 6. Probability of assignment of individual Marbled Murrelets (represented by vertical bars) to each of four genetic populations 

(represented by different colors). 

AK20-0056_fig05

F / (1-

F ) ST ST

ln (Geographic Distance [km])

hic Distance [km])

0.10

0.05

-0.05

-0.10

4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0

0.00

40 Status Review of the Marbled Murrelet in Alaska and British Columbia
Table 13a. Estimates of shortest geographic distance (km; above diagonal), and FST for all loci except Ald, Bma10-18 and Bma553

(below diagonal) for pairwise comparisons of sampling sites. 

[Site abbreviations as in figure 4. Values in bold are significantly greater than 0. Negative values indicate that variation within sites is greater than variation 

among sites. ~, insufficient data. Samples from Unalaska were too degraded for introns to amplify reliably]

Near Andr Unal Shum Cook PWS Alex BC WA OR NCA CCA

Near 750 1,380 1,770 2,300 2,340 3,270 4,260 4,440 4,620 4,890 5,340

Andr 0.012 740 1,140 1,710 1,780 2,690 3,600 3,770 3,910 4,160 4,500

Unal ~ ~ 400 990 1,070 1,960 2,860 3,030 3,200 3,470 3,830

Shum 0.045 0.036 ~ 600 700 1,560 2,470 2,640 2,830 3,120 3,480

Cook 0.049 0.030 ~ 0.002 120 980 1,990 2,200 2,450 2,800 3,170

PWS 0.059 0.027 ~ -0.002 -0.008 930 1,990 2,200 2,470 2,930 3,200

Alex 0.047 0.027 ~ 0.000 -0.001 0.000 1,140 1,370 1,730 2,140 2,520

BC 0.048 0.039 ~ 0.003 -0.001 -0.002 0.000 240 660 1,110 1,450

WA 0.032 0.029 ~ -0.021 -0.028 -0.023 -0.021 -0.015 440 890 1,220

OR 0.038 0.048 ~ -0.033 -0.036 -0.066 -0.049 -0.051 -0.051 440 800

NCA 0.060 0.034 ~ 0.004 0.001 -0.001 0.007 0.013 -0.009 -0.051 380

CCA 0.060 0.043 ~ 0.031 0.029 0.029 0.028 0.039 0.011 -0.017 0.033

Table 13b. Estimates of ΦST for introns (below diagonal) and FST for microsatellites (above diagonal) for pairwise comparisons of 

sampling sites.

[Site abbreviations as in figure 4. Values in bold are significantly greater than 0. Negative values indicate that variation within sites is greater than variation 

among sites. ~, insufficient data. Samples from Unalaska were too degraded for introns to amplify reliably]

Near Andr Unal Shum Cook PWS Alex BC WA OR NCA CCA

Near 0.001 0.026 0.041 0.041 0.046 0.045 0.039 0.008 0.039 0.056 0.061

Andr 0.053 0.005 0.026 0.022 0.021 0.021 0.023 0.034 0.035 0.038 0.053

Unal ~ ~ -0.008 -0.009 0.002 -0.004 -0.016 -0.022 0.020 0.008 0.029

Shum 0.043 -0.017 ~ -0.002 0.003 0.002 0.004 -0.058 -0.038 0.012 0.038

Cook 0.067 0.031 ~ 0.010 -0.007 0.005 -0.001 -0.062 -0.038 0.006 0.030

PWS 0.084 -0.004 ~ 0.001 0.009 0.007 -0.005 -0.078 -0.034 -0.001 0.018

Alex 0.062 0.021 ~ -0.001 0.001 -0.005 -0.000 -0.061 -0.024 0.012 0.032

BC 0.056 0.036 ~ 0.003 0.010 0.002 -0.003 -0.063 -0.045 0.016 0.041

WA 0.053 -0.017 ~ 0.005 0.010 0.005 -0.004 0.003 -0.041 -0.051 -0.033

OR 0.060 0.109 ~ -0.095 -0.089 -0.187 -0.116 -0.111 -0.101 -0.035 -0.017

NCA 0.062 -0.012 ~ -0.002 0.007 0.002 -0.008 0.003 0.001 -0.122 0.033

CCA 0.052 -0.022 ~ 0.017 0.042 0.055 0.016 0.029 0.025 -0.041 0.023

Contemporary Gene Flow

Individual murrelets from the Near and Andreanof 

Islands had a high probability of being assigned to Genetic 

Population 1 by STRUCTURE (mean P = 0.97, SE = 0.021); 

those from central California had a high probability of being 

assigned to Genetic Population 4 (mean P = 0.93, SE = 0.036; 

table 15; appendix L). At least one bird in central California 

(indicated by an arrow on fig. 6) had a high probability 

(P > 0.90) of being an immigrant from Genetic Population 2, 

and four individuals between Unalaska Island and northern 

California had high probabilities of being immigrants from 

Genetic Populations 1 or 4. Lower probabilities of assignment 

may result from difficulties by the program in assigning 

individuals due to errors around population-specific genotype 

frequencies and/or interbreeding between individuals from 

Table 14. Maximum value of ln Pr (X | k) from multiple runs of 

STRUCTURE for each value of k (number of populations) from 

one to twelve.

k ln P(X|k) P (k)

1 -21334 <0.0001

2 -21212 <0.0001

3 -21219 <0.0001

4 -20909 >0.9999

5 -21622 <0.0001

6 -21530 <0.0001

7 -22842 <0.0001

8 -21603 <0.0001

9 -23071 <0.0001

10 -21830 <0.0001

11 -22877 <0.0001

12 -22256 <0.0001

Population Genetics 41
different genetic populations (i.e., second or third generation 

immigrants). Thus, assignment of individuals to specific 

populations when their probability of assignment to that 

population is less than 0.80 (a standard value for β in 

statistical tests) is tenuous. 

Discussion

Genetic Viability

In theory, declining populations suffer increasing 

inbreeding, which may lead to inbreeding depression. They 

also lose genetic variation, which may compromise their 

ability to adapt and evolve. No strong evidence for either 

inbreeding or low genetic variation was found within any 

sampling site in the present study (table 10). Thus, inbreeding 

and loss of genetic variation do not appear to be a concern for 

Marbled Murrelets at this time. 

Population Genetic Structure

Estimates of FST or ΦST both for all loci combined and 

for introns or microsatellites separately indicated that low but 

significant population genetic structure exists within Marbled 

Murrelets (tables 12, 13, 14, and 15). These results agree 

with findings of previous studies, which reported estimates of 

global FST or ΦST between 0.05 and 0.09 based on allozymes, 

mtDNA, introns and/or microsatellites (Friesen and others, 

1996b, 2005; Congdon and others, 2000). Previous studies 

(Congdon and others, 2000; Friesen and others, 2005) as well 

as the present results (fig. 5) suggested that genetic variation 

changes clinally in this species. However, the present results 

indicate that variation does not change gradually but may 

instead represent a step cline. Specifically, several lines of 

evidence indicate that murrelets in the central and western 

Aleutian Islands (Near and Andreanof islands) and central 

California differ significantly from those in central parts of the 

species’ range:

1. Pairwise estimates of FST or ΦST were significant for 

most comparisons involving the Near and Andreanof 

islands and central California, with estimates 

ranging as high as 0.109 (table 13). This finding was 

consistent across loci, and is supported by results of 

previous studies (Friesen and others, 1996b, 2005; 

Congdon and others, 2000);

2. Although Mantel’s tests indicated isolation by 

distance, significance was lost when peripheral sites 

were eliminated from the analysis; and 

3. STRUCTURE placed samples into four genetic 

populations, with most samples from the Near and 

Andreanof islands, and central California being 

placed in distinct genetic populations (fig. 6). 

 As in previous studies (Friesen and others, 1996b, 

2005, Congdon and others, 2000), no evidence was found 

for differentiation among sampling sites between the Alaska 

Peninsula and British Columbia (table 13). Although the 

sample size for Unalaska Island was low, results of the present 

study suggest that murrelets from the eastern Aleutian Islands 

(Unalaska Island), Washington and Oregon also do not differ 

genetically from mainland Alaska and British Columbia birds 

in that: (1) birds from these areas generally did not differ 

from birds from the central region in pairwise comparisons of 

sites (table 13); and (2) most samples from these sites were 

assigned to Genetic Populations 2 or 3 by STRUCTURE. 

Previously, Friesen and others (2005) suggested that: 

(1) birds from the Near and Andreanof islands may differ 

genetically from each other; and (2) birds from northern 

California may differ both from those in central California and 

from those in British Columbia north. However, they argued 

that these possibilities require further investigation. Results of 

the present study did not consistently separate samples from 

the Near versus Andreanof islands, or those from northern 

California versus central regions (table 13; fig. 6).

Congdon and others (2000) argued that genetic 

differences between Marbled Murrelets from the Aleutian 

Islands versus mainland Alaska and British Columbia are a 

result of historical fragmentation, probably by Pleistocene 

Table 15. Proportion of birds from different sites that were 

assigned to each of four genetic populations by STRUCTURE. 

[Population abbreviations as in figure 4]

Sampling 

site

Genetic population

1 2 3 4 Number of 

individuals

Near 0.957 0.017 0.025 0.001 11

Andr 0.986 0.005 0.003 0.005 12

Unal 0.37 0.337 0.262 0.031 13

Shum 0.028 0.472 0.485 0.014 28

Cook 0.067 0.403 0.406 0.124 31

PWS 0.008 0.434 0.437 0.121 10

Alex 0.052 0.312 0.583 0.052 25

BC 0.056 0.533 0.401 0.011 30

WA 0.02 0.469 0.414 0.098 33

OR 0.116 0.358 0.491 0.035 18

NCA 0.001 0.319 0.489 0.19 36

CCA 0.003 0.043 0.023 0.931 36

42 Status Review of the Marbled Murrelet in Alaska and British Columbia
glaciers. Although population genetic structure has been 

attributed to Pleistocene glaciers in several species in this 

region (Harlin-Cognato and others, 2006), more recent results 

for Marbled Murrelets do not support this interpretation. 

Specifically, the Aleutian samples lack private nuclear alleles 

at high frequency (Friesen and others, 2005, and present 

results), and there is no evidence of historical fragmentation 

from mtDNA data (e.g., deep branches in the gene tree; 

Friesen and others, 2005). Population genetic structure in this 

species may instead be a product of genetic drift and selection 

in situ following recession of the glaciers. Resolution of this 

problem will require additional analyses (e.g., nested clade 

analysis, Templeton, 1998).

Contemporary Gene Flow

Molecular assignments indicated that gene flow among 

Marbled Murrelets in Near / Andreanof islands versus 

central part of the range versus central California is very 

low. Specifically: (1) most birds in the Near or Andreanof 

islands and central California had very high probabilities 

of assignment to Genetic Populations 1 or 4, respectively 

(table 15; appendix L); (2) none of 23 birds from the Near or 

Andreanof islands had even a modest probability (> 0.70) of 

assignment to a population other than Genetic Population 1; 

and (3) only 1 of 36 birds from central California had even 

a modest probability of originating from a population other 

than Genetic Population 4. Nonetheless, these regions are not 

completely isolated genetically: one bird sampled between 

Unalaska Island and northern California had a high probability 

(> 0.90) of assignment to Genetic Population 1, and three 

birds sampled in this region had a high probability (> 0.90) 

of assignment to Genetic Population 4 (fig. 6). Although 

some of these assignments may represent Type II Errors, 

they suggest that gene flow does occur among the regions. 

In contrast, Genetic Populations 2 and 3 did not correspond 

with any geographic region, few birds sampled between 

Unalaska Island and northern California could be assigned 

with confidence to any genetic population, and analysis 

only of samples from Unalaska to northern California using 

STRUCTURE indicated a single genetic population. Thus, 

gene flow appears to occur among sites within the central 

region.

Note that these results do not contradict recent telemetry 

studies and population modeling studies which indicate 

potentially high dispersal between central California and 

other sites (Peery and others, 2006b). First, dispersal does 

not necessarily result in gene flow (e.g., movements could 

represent seasonal dispersal or prospecting juveniles). 

Second, although migration rates could not be estimated 

with the present data, STRUCTURE identified several 

potential migrants both into and out of central California, 

which is compatible with telemetry studies and population 

modeling. Other migrants may exist but not be identified 

with high confidence using molecular assignments. Third, 

migration may be naturally sporadic (i.e., periods of little or 

no gene flow may be interspersed with occasional periods of 

gene flow). Finally, gene flow requires time to homogenize 

populations (Birky and others, 1989); thus, if populations 

were historically isolated but are now exchanging migrants 

(e.g., due to anthropogenic disturbance), they will display 

both population genetic differences and gene flow for a length 

of time that depends on the initial level of differentiation, the 

effective population sizes and the migration rates. 

Genetic Units of the Marbled Murrelet

Marbled Murrelets appear to comprise three genetic units: 

(1) western and central Aleutian Islands; (2) eastern Aleutian 

Islands to northern California; and (3) central California. 

These units were first identified by Congdon and others (2000) 

and Friesen and others (2005), and have been upheld by 

analyses of additional samples and loci. They are supported 

by both traditional (e.g., Wright’s FST) and state-of-the-art 

analyses (e.g., coalescent theory), and three types of molecular 

markers (mtDNA, introns, and microsatellites). Loss of any 

of these populations would result in loss of a portion of the 

species’ genetic resources and/or local adaptations, and may 

compromise its long-term viability. Due to their generally 

small size, relative isolation, and often marginal habitat, 

peripheral populations are expected to be more vulnerable to 

extinction (reviewed in Lessica and Allendorf, 1995; Vucetich 

and Waite, 2003). Our analyses confirm that murrelets in the 

western and central Aleutian Islands, and central California 

are genetically distinct, peripheral populations. 

Population Status and Trends

Methods Used to Survey Murrelets

Marbled Murrelets are difficult to census compared to 

a variety of related seabird species such as Common Murres 

or Tufted Puffins (F. cirrhata), which conveniently gather 

in densely populated breeding colonies, where they may be 

counted in whole or on a selected sample survey of plots. On 

land, murrelets disperse over vast areas of old-growth forest 

habitat to nest, and they fly to and from nest sites before dawn. 

It is possible to monitor audio-visual detections of Marbled 

Murrelets during these flights, and relate the frequency of 

Population Status and Trends 43
those detections to habitat (Ralph and others, 1995b) or 

obtain relative indices of abundance within and between years 

(Naslund, 1993), but detections are highly variable and their 

use for estimating population abundance is limited. In recent 

years, radar technology has greatly improved the ability of 

investigators to count and monitor murrelet numbers in forest 

habitat (Burger, 2001b), and is becoming a standard tool for 

this purpose (Burger and others, 2004a). When positioned at 

the mouth of a watershed, radar provides a relatively consistent 

count of murrelets entering the watershed, and counts can then 

be applied to analyze landscape-level associations between 

murrelets and habitat (Burger, 2001b; Raphael and others, 

2002b; Bigger and others, 2006). Although radar counts are 

now routinely used to estimate sizes of populations in British 

Columbia (see below), there has been only one pilot study on 

using radar for this purpose in Alaska (Cooper, 1993). 

The most common source of information on the 

distribution and abundance of murrelets in Alaska is derived 

from surveys at-sea. When they are not attending nest sites, 

murrelets are found at-sea where they forage on small 

schooling fish (see section, “Feeding Ecology”). In general, 

abundance at-sea is often not well-correlated with numbers 

nesting in adjacent terrestrial breeding habitat (Marks and 

others, 1995; Speckman, 1996; Whitworth and others, 2000), 

but on a landscape- or regional-scale, murrelets are most 

abundant in waters within foraging range of old-growth forests 

(Hull and others, 2001; Meyer and others, 2002; Miller and 

others, 2002). Therefore, broad-scale surveys for murrelets 

at-sea can provide good information on regional population 

trend, status, and distribution. This has been shown especially 

well for the semi-enclosed marine waters of Prince William 

Sound (Agler and others, 1998; Lance and others, 2001), 

where murrelet populations have been repeatedly estimated 

from counts on sample surveys since 1989, counts show 

relatively low variation from one year to the next (trends 

notwithstanding), and spatial variability within a year is low 

(CVs of 20–40 percent are not unusual). 

In Alaska, surveys for marine birds generally employ 

strip-transect methods, whereby all birds observed within a 

fixed-width strip (e.g., 200–300 m) around a moving vessel 

are recorded (Gould and Forsell, 1989; Klosiewski and Laing, 

1994). In Washington, Oregon, and California, murrelets are 

now usually counted using line-transect methods without 

fixed widths, and the distance to every bird also is recorded 

so that detection functions may be calculated to adjust for 

conservative negative bias (under estimate) due to the drop-off 

in visibility of birds with distance (Bentivoglio and others, 

2002). This method has not been adopted in Alaska yet, in 

part because of concerns about comparability with historical 

data and because it might be difficult to collect line-distance 

data on the large number of murrelets and other species 

typically found in Alaska during summer. In any case, small 

boat surveys in Alaska generally employ 200-m strip widths 

(Agler and others, 1998), i.e., 100 m to either side of the 

vessel. There is a small conservative bias in strip-transect 

methods (Klosiewski and Laing, 1994), where most murrelets 

(and other species) observed out to the full 100 m are counted. 

The bias is likely to be consistent over time (Evans Mack and 

others, 2002), but contributes to conservative, underestimates 

of the population size (see below).

Sources of Error Associated with Boat-Based 

Surveys

Several sources of error are associated with using boatbased survey data to estimate populations (Gould and Forsell, 

1989; Agler and others, 1998; McShane and others, 2004). In 

general, these sources of error tend to be consistently present 

among studies and years, and tend to cancel out when making 

inferences about trend using data that are collected in a similar 

way each year. With respect to estimating population size, 

however, these sources of error tend to bias the estimate either 

high or low, and include:

1. Strip-transects tend to underestimate densities for small 

seabirds like murrelets because the visibility of birds 

drops off with distance from the transect line (see above). 

It appears likely, however, that under a range of typical 

viewing conditions, observation teams of 2 or more 

people see 80–95 percent of all murrelets within 100 m 

(Evans Mack and others, 2002). Detection rates may be 

higher in the more protected waters of Prince William 

Sound and Southeast Alaska. 

2. Counting of all flying birds on strip (and line) transects 

tends to overestimate actual densities because of the 

continuous flux of incoming birds (Gould and Forsell, 

1989) leading to overestimates of actual density by 25–40 

percent for fast-flying birds (Spear and others, 1992). 

McShane and others (2004) thought this might not be a 

serious problem in Washington, Oregon, and California 

because <2.5 percent of murrelets were thought to fly 

during observations on transect (citing Strong and others, 

1995). In contrast, we have found that 20 to 40 percent 

of murrelets may be observed flying on marine bird 

surveys in some areas of Alaska (J. Piatt, U.S. Geological 

Survey, unpub. data, 1999–2005). In Southeast Alaska, for 

example, 31 percent of all birds were flying on surveys 

conducted in Icy Strait by Lindell (2005). Similarly, 28.3 

percent of all murrelets observed by Agler and others 

(1998) during 6 weeks of sampling throughout Southeast 

Alaska were flying. Agler and others (1998) addressed 

this uncertainty by estimating the abundance of murrelets 

with counts of flying birds excluded (reducing the 

44 Status Review of the Marbled Murrelet in Alaska and British Columbia
population estimate by about 200,000 birds). However, 

that approach overcompensates for this source of error. 

Preliminary analysis of experimental surveys (G. Drew, 

U.S. Geological Survey, unpub. data, 1999–2993) where 

continuous counts of flying birds in Glacier Bay were 

compared with periodic scan counts that compensate for 

flux (Gould and Forsell, 1989) suggests that counts of 

flying murrelets should be reduced by about 60 percent 

to compensate for flux. This is similar to the ratio for 

medium-sized alcids calculated by Gaston and others 

(1987). Using this ratio, it appears that Agler and others 

(1998) would have overestimated murrelet abundance in 

Southeast Alaska by 13 percent, or by about 92,000 birds. 

3. Other factors that may bias counts are inter-observer 

variability, poor viewing or sea conditions, doublecounting of birds that move ahead of the vessel, and 

missing of birds diving underwater. In general, these 

are well-recognized problems (Agler and others, 1998; 

Evans Mack and others, 2002) that may be minimized 

with thorough training of observers and a commitment 

to survey only under specific conditions (e.g., Agler 

and others, 1998). It is possible to assess errors arising 

from these factors on an experimental basis (e.g., Evans 

Mack and others, 2002), but more difficult to assign error 

retroactively to any given survey. 

4. The total number of murrelets on the water in any given 

location varies throughout summer (DeGange, 1996; 

Speckman and others, 2000; Kuletz, 2005). The number 

of birds found on the water must be a fraction of the 

total population during incubation when one member 

of each pair remains at the nest site during day (Kuletz, 

1996). Ironically, we should probably survey murrelets 

during incubation to assess population trends because 

numbers at-sea are less variable at this time (Speckman 

and others, 2000), but clearly that is a bad time to survey 

for population size because one-half the active breeders 

should be attending nest sites. Numbers on the water 

increase after incubation (May–June) and by as much as 

20 to 40 percent during late July and early August (Kuletz 

and Kendall, 1998; Speckman and others, 2000; Lindell, 

2005).

5. Changes in the environment can have large effects on 

local and even regional populations. At small scales, 

bird numbers are significantly affected by tide and time 

of day (Speckman and others, 2000). In theory, this 

variability is balanced out by sampling at all times of day 

and over periods of weeks (Agler and others, 1998). At 

larger scales, evidence suggests that regional abundance 

may vary with water temperatures, for example during 

El Niño-Southern Oscillation (ENSO) events, leading 

to unusual fluctuations in abundance (Burger, 2002; 

Kuletz, 2005). Care must be taken interpreting trends or 

population estimates that include such anomalous years 

(Burger, 2002).

The assumption that all murrelets within the strip-transect 

are counted will tend to underestimate ‘actual’ population 

size by perhaps 15 to 20 percent, while inclusion of counts of 

flying birds tends to overestimate abundance by perhaps 13 

percent [see (1) and (2) above]. In most cases, we restricted 

analysis to surveys conducted before July 15 so that some 

fraction of the populations probably would still be attending 

nest sites [see (4) above]. In general, these analysis methods 

are expected to yield conservative under-estimates of the 

‘actual’ population sizes. The effects of other sources of 

error [see (3) and (5) above] contribute to variance (SEs) and 

potential biases of the estimates, but these are well-recognized 

problems (Agler and others, 1998; Mack and others, 2002) 

that we assume were reasonably dealt with through training 

of observers and a commitment to survey only under specific 

conditions (e.g., Agler and others, 1998). The potential large 

scale effects of water temperature and regime shifts are 

discussed below and in conclusions.

Alaska Population

Alaska Population Estimates

Marbled Murrelets range widely in Alaska (see section, 

“Geographic Distribution”). From the border with British 

Columbia in Southeast Alaska to Attu Island in the western 

Aleutians, there are only a few gaps in distribution (e.g., island 

passes in the Aleutians). However, the majority of murrelets 

are concentrated during the breeding season in just three 

main areas: Southeast Alaska (the Alexander Archipelago), 

Prince William Sound, and in the area of lower Cook Inlet – 

Kodiak Archipelago (Piatt, 1994; Piatt and Naslund, 1995; 

Agler and others, 1998). Historical estimates from these three 

areas (table 16) are believed to account for about 95 percent 

of the total Alaska population. In these areas, Marbled 

Murrelets ovelap in distribution with Kittlitz’s Murrelets. 

Whenever possible, murrelets were identified to species on 

population surveys, but a significant proportion were recorded 

as unidentified Brachyramphus murrelet. Identification of 

murrelets in the field can be difficult, even for experienced 

observers, and the fraction of birds that were categorized as 

unidentified Brachyramphus sometimes exceeded 50 percent 

Population Status and Trends 45
Table 16. Brachyramphus murrelet population estimates for areas in Alaska that have been surveyed systematically. 

[Historic population estimates are made from the earliest reliable survey data for each area and provide an estimate of the historic maximum size of the murrelet 

population. Few population-scale surveys have been repeated. Using data from eight trend sites within or near these areas, we can project what the population 

would be if populations followed the observed linear trends to 1999 and leveled off after a weak regime shift, or if they continued to follow linear trends to 

summer 2006. In these scenarios, areas with no trend data are assumed to remain constant. Data sets used to estimate trends always include more than just the 

population-scale survey data presented in this table and so differ in apparent percent change over time (see text for detail)]

Area

Historic population 

survey estimate Most recent population survey estimate Projected population in 1999 Projected population in 2006

Year N LCL UCL Year N LCL UCL Percent 

change1 Trend2 N Percent 

change3 Trend4 N Percent change5

Southeast 

Alaska

1994 687,061 485,899 888,223 --- -19.2 236,620 -66 -12.2 144,188 -79

 (Glacier 

Bay)6

1991 75,486 59,721 92,627 2003 16,178 12,851 20,070 -79% --- --- --- --- --- ---

 (Icy Strait)6 1993 44,993 30,032 61,804 2003 15,880 8,966 23,654 -65% --- --- --- --- --- ---

Yakutat 2000 8,344 3,740 12,948 --- n/a 8,344 --- -5.4 5,980 ---

Outer Coast7 ~2003 16,785 8,689 24,881 --- 16,785 --- -5.4 13,442 -20

Prince William 

Sound

1989 107,354 88,145 126,563 2005 43,061 34,498 51,624 -60% -5.5 60,973 -43 -6.7 33,745 -69

GOA (to 

300 km)8,9

~1984 9,820 2,455 17,185 --- -5.5 4,203 -57 -6.7 3,240 -67

Kenai Fjords10 2002 9,554 2,315 22,164 2006 5,264 3,776 7,338 -45% n/a 9,554 --- n/a 5,264 ---

Cook Inlet 1993 58,227 42,169 74,285 1996 29,127 21,076 40,255 -50% -3.7 46,438 -20 -3.7 35,666 -39

Kodiak 

Archipelago8

~1984 23,722 12,067 35,377 --- -3.7 13,475 -43 -3.7 10,349 -56

Alaska 

Peninsula

2003 7,389 2,098 17,708 --- n/a 7,389 --- n.d. 7,389 ---

Unalaska Island 2005 7,486 5,936 9,439 --- n/a 7,486 --- n.d. 7,486 ---

Atka Island 2004 724 353 1,485 --- n/a 724 --- n.d. 724 ---

Adak Island 2006 1,674 1,015 2,333 --- n/a 1,674 --- n.d. 1,674 ---

Attu Island 2000 75 19 131 --- n/a 75 --- n.d. 75 ---

Bering Sea8,9 ~1984 1,960 490 3,430 --- n/a 1,960 --- n.d. 1,960 ---

TOTAL11 940,175 655,390 1,236,152 415,700 -56 271,182 -71

1

 Percent change calculated between historic population estimate and most recent estimate.

2

 Trend calculated from date of earliest trend survey (see “Trends” table) to 1999 only.

3

 Percent change calculated between the population size estimated from historic surveys and population size projected for 1999 from trend data.

4

 Trend calculated from data of earliest trend survey to most recent trend survey (up to 2003–06, see “Trends” table).

5

 Percent change calculated between the population size estimate from historic surveys and population size projected for 2006 from trend data.

6

 Glacier Bay and Icy Strait are subareas of Southeast Alaska, and murrelet populations are subsets of the above total estimated from a region-wide survey in 

1994. 7

 Estimated from ship-based surveys conducted in 2002–04, with 2003 as mid-point (M. Kissling, U.S. Fish and Wildlife Service, unpub. report, 2006).

8

 Estimated from ship surveys conducted in 1975–93, with 1984 as mid-point (Piatt and Ford, 1993).

9

 Confidence limits approximated as ±75 percent.

10

Trend estimated from coastal survey initiated in 1976. First population survey of all habitats in 2002.

11

Total does not include estimates from Glacier Bay or Icy Strait because these are included in the overall Southeast Area estimate.

46 Status Review of the Marbled Murrelet in Alaska and British Columbia
of all birds observed. For purposes of analyses and discussion 

here, all Marbled, Kittlitz’s and Unidentified murrelets were 

combined as Brachyramphus murrelets. Because usually 

only a fraction of these were Kittlitz’s Murrelets in glaciated 

regions (as much as about 10 percent in Prince William Sound 

and about 15 percent in Glacier Bay), overall trends discussed 

here can be attributed mostly to the Marbled Murrelet. Its 

should be noted, however, that Kittlitz’s murrelet also appears 

to be declining rapidly throughout its range, and so contributes 

to the overall declines in Brachyramphus murrelet reported 

here (Kuletz and others, 2003b). All murrelets recorded on 

surveys in British Columbia were Marbled Murrelets, as were 

virtually all murrelets observed south of Icy Strait in Southeast 

Alaska. 

Isleib and Kessel (1973) provided the first published 

estimate of Marbled Murrelet abundance in Alaska, suggesting 

that the northern Gulf of Alaska population might be “several 

hundred thousands, probably millions.” This was conjectural, 

but based on first-hand observations of large numbers of 

murrelets in Prince William Sound and elsewhere. Analysis of 

the earliest of all quantitative surveys for murrelets in Alaska 

indicated a population of 304,000 murrelets in Prince William 

Sound during summer 1972 (Klosiewski and Laing, 1994). 

A 1989 survey indicated a population estimate of 107,300 

birds (table 16; Klosiewski and Laing, 1994). Piatt and Ford 

(1993) estimated Marbled Murrelet populations in Alaska 

at about 160,000 based on greater than 18,000 km of shipbased surveys in offshore marine waters of Alaska. However, 

the ship-based surveys poorly sampled the inside waters of 

Prince William Sound and Southeast Alaska, and so must be 

considered minimum estimates (Agler and others, 1998). Piatt 

and Naslund (1995) revised that estimate upwards to 280,000 

after considering other survey results from Prince William 

Sound and lower Cook Inlet. With the addition of subsequent 

detailed surveys of Southeast Alaska, the estimate for murrelet 

populations in the three areas of concentration (Southeast 

Alaska, Prince William Sound, and lower Cook Inlet) 

increased to about 859,000 (± approx. 203,000) birds (Agler 

and others, 1998). Independent surveys of local concentrations 

of murrelets in subareas of Southeast Alaska (Glacier Bay and 

Icy Strait) corroborate the high abundance of murrelets in this 

region (Robards and others, 2003; Lindell, 2005).

Some areas remain poorly surveyed, and we still rely 

on the earlier ship-based surveys (Piatt and Ford, 1993) to 

estimate population sizes for the Kodiak Archipelago, open 

waters of the Gulf of Alaska, and coastal and shelf waters of 

the southeastern Bering Sea (table 16). However, other areas 

of Alaska have been surveyed more recently (table 16) using 

small boat-based survey methods similar to those used in 

Prince William Sound. Moving north from the inside waters 

of Southeast Alaska, Stephensen and Andres (2001) estimated 

that about 8,300 Brachyramphus murrelets resided in waters 

of Yakutat and adjacent bays, while Kissling and others (U.S. 

Fish and Wildlife Service, 2006) estimated that about 17,000 

murrelets used outer coast waters from Cross Sound to Icy 

Bay along the outer coast. Prince William Sound has been 

surveyed eight more times since 1989, the year that surveys 

were initiated to assess damages from the EVOS (McKnight 

and others, 2006). Owing to the long time span between the 

first (1972) and second (1989) surveys of Prince William 

Sound, and uncertainty about what the population may have 

been doing in the intervening 17 years, the latter estimate of 

about 107,000 murrelets is often used for comparison with 

other studies and for examination of trend (Agler and others, 

1998; Kuletz, 2005; see appendixes F-K). All remaining 

areas, including Kenai Fjords (Van Pelt and Piatt, 2003), the 

Alaska Peninsula (Van Pelt and Piatt, 2005), and Unalaska 

(Romano and others, 2005a), Atka (Romano and others, 

2005b), Adak (J.F. Piatt, U.S. Geological Survey, unpub. data, 

2006), and Attu (Piatt and others, 2005) islands, have been 

surveyed in the 2000s as part of an ongoing effort to fill in 

gaps in our knowledge about the distribution and abundance of 

Brachyramphus murrelets in Alaska.

Adding together all the earliest possible population 

estimates from different areas of Alaska, and acknowledging 

that dates of census vary widely, mostly from 1989 to 2006, 

we can estimate that the total Alaska population was once in 

the order of 940,000 birds, with an approximate 95 percent 

CI of 655,000–1,236,000 birds (table 16). If we used the 

earliest estimate of Prince William Sound populations from 

1972, the estimate would include almost 200,000 more 

birds, but because it used a slightly different design and was 

only a single survey, it would be more conservative to use 

data after 1989. Despite an intensive effort to survey many 

new areas, this current estimate represents only a modest 

increase (9 percent) over the previous estimate of 859,000 

Brachyramphus murrelets by Agler and others (1998). This 

underscores the importance of the three primary areas of 

Southeast Alaska, Prince William Sound, and lower Cook 

Inlet for murrelet populations in Alaska. It is unlikely that any 

significant new populations will be found in Alaska (at least 

from the numerical perspective).

Alaska Population Trends

We can examine population trends in two ways: (1) by 

direct comparison of recent population-level surveys with 

historical surveys; and, (2) by using trend site data to estimate 

change within surrounding areas and over uniform periods of 

time. 

Population Status and Trends 47
We have repetitive population survey data from only 5 

of 16 areas in Alaska (table 16). Three areas (Glacier Bay, Icy 

Strait, Prince William Sound) have been surveyed multiple 

times over many years (see table 17), and two areas (Kenai 

Fjords and Cook Inlet) were surveyed only twice, with only 

a few-year interval between surveys. Historical and recent 

population estimates for Glacier Bay, Icy Strait and Prince 

William Sound are provided in appendixes H, G, and J, 

respectively. Estimates from Kenai Fjords are from Van Pelt 

and Piatt (2003), and updated with data collected in 2006 

(M. Romano, U.S. Fish and Wildlife Service, unpub. data, 

2006). Estimates from Cook Inlet are from Agler and others 

(1998) and a reanalysis of 1996 data collected (Piatt, 2002) 

and compared over the same spatial scale (S. Speckman, U.S. 

Fish and Wildlife Service, unpub. data, 2006). 

When we compare historical survey data with the most 

recent survey data in each area, it appears that murrelets 

have declined by 45–79 percent in these areas. As one might 

expect, the magnitude of change is larger where the interval 

between first and last surveys is greatest— and perhaps more 

trustworthy. For example, while numbers declined on the 

population-level surveys conducted at Kenai Fjords 2002–06, 

shoreline trend counts at this location extend much further 

back in time (1976) and they have been extremely variable. 

The long-term trend is actually positive (table 17). 

Another way to analyze these data is to examine trends, 

standardized as percent change per year (table 17). Population 

trend data are available from a limited number of locations. 

For Southeast Alaska, we examined four different datasets to 

establish population trends in three ways: 

1. We examined changes in abundance of murrelets over 

the entire Southeast Alaska region by comparing the 

Southeast Alaska-wide population survey of Agler and 

others (1998) with a series of Southeast Alaska-wide 

coastal surveys conducted by the USFWS (J. Hodges, 

U.S. Fish and Wildlife, unpub. data, 2006) over several 

years (1999–2001); 

2. We examined trends in Icy Strait by combining data from 

surveys conducted by the USFWS in 1993–99 (Lindell, 

2005) with identical surveys of the same area from 1999 

to 2003 conducted by the USGS (Robards and others, 

2003; and 

Table 17. Summary of changes in Brachyramphus murrelet populations at eight different trend sites during summer in Alaska.

[See appendixes F-K. Weighted linear regressions were performed on log transformed annual means. t-tests conducted using Welch’s correction for unequal 

variances. Significant (p<0.05) changes are in bold. The percent change in counts between years was calculated from the difference between actual counts in the 

first and last years of the range sampled (which does not always reflect the overall trend from multiple years of sampling)]

Site or 

transect 

route

Region Range of 

years

Number 

of years 

sampled

Test Statistic df P

Percent 

change 

between all 

years

Avg rate 

of change 

(percent 

per year)

Southeast Southeast 

Alaska

1994–2001 1

2 t-test t=2.71 1060 <0.01 -46 -11.5

Icy Strait Southeast 

Alaska

1993–2001 8 regression F=8.52 2

1,10 0.015 -65 -12.7

Glacier Bay Southeast 

Alaska

1991–2001 7 regression F=128.5 1,6 <0.0001 -79 -11.8

Malaspina Outer Coast 1992–2002 2 regression F=111.4 2

1,2 0.009 -43 -5.4

Prince 

William 

Sound

South-central 

Alaska

1989–2005 9 regression F=18.7 1,8 0.003 -60 -6.7

Kenai Fjords South-central 

Alaska

1976–2006 5 regression F=0.43 1,4 NS -17 +1.8

Kachemak 

Bay

South-central 

Alaska

1993–2006 3 regression F=0.49 1,1 NS -14 -3.7

Adak Island Aleutians 1995–2006 2 t-test t=1.04 37 NS -57 -7.4

1

Comparison made using 1999 as mid-point for sampling of the Southeast area in 1997–2001 (see appendixes).

2

Surveys replicated within some years, so degrees of freedom larger than expected from number of years sampled.

48 Status Review of the Marbled Murrelet in Alaska and British Columbia
3. We examined trends in Glacier Bay by comparing surveys 

conducted in 1991 (Piatt and others, 1991), with surveys 

conducted by Lindell (2005) in 1993 and the USGS in 

1999–2003 (Robards and others, 2003). 

The paper by Agler and others (1998) is published 

and provides some of the comparisons. For the remaining 

comparisons, we have included descriptions of the surveys 

and details of our analyses in appendixes F-H. Table 17 shows 

results of these trend assessments. 

Outside of Southeast Alaska, we have trend data from 

five other locations:

1. Kissling (U.S. Fish and Wildlife Service, unpub. data, 

2006) surveyed murrelets on the outer Gulf of Alaska 

coast for several years, and compared their survey of the 

Malaspina Forelands with a similar survey conducted 

in 1992 by Kozie (1993). Details of this unpublished 

comparison are found in appendix I; 

2. Our best trend data are from Prince William Sound, 

which has the longest time series (1972 / 1989–2005) 

of murrelet population surveys. This dataset has been 

analyzed specifically for trends in Marbled and Kittlitz’s 

murrelet populations by Kuletz (2005), and that analysis 

is included here in appendix J; 

3. Trends in Kenai Fjords populations were examined by 

Van Pelt and Piatt (2003) using data collected on four 

coastal surveys conducted between 1976 and 2002, and 

we updated that trend with data collected in summer 2006 

(M. Romano, U.S. Fish and Wildlife Service, unpub. data, 

2006); 

4. In Kachemak Bay during 2005 and 2006, Kuletz 

resurveyed 46 random transects located within the bay 

that were originally used in the estimate of the murrelet 

population of Lower Cook Inlet (Agler and others, 1998), 

and we estimated trend from the original survey data 

collected in 1993 (K. Kuletz, U.S. Fish and Wildlife 

Service, unpub. data, 2005–06). We opted not to use the 

Cook Inlet population surveys of 1993 and 1996 to assess 

trends owing to the brief time interval between surveys 

(and unlikely trend of -18 percent per year); and 

5. Part of the coast of Adak Island was surveyed for 

murrelets in 1995 (Meehan, 1996) and we surveyed the 

entire island in 2006 to obtain a whole-island population 

estimate and evaluate trends. Details of this survey 

and comparison with the 1995 census are provided in 

appendix K. 

Results of these analyses indicate that there has been 

a rapid and widespread decline in Brachyramphus murrelet 

populations throughout Alaska (table 17). The evidence for 

major declines in abundance is strongest from Southeast 

Alaska and Prince William Sound owing to the good timeseries of data in both locations. In Southeast Alaska, there is 

good agreement with rates of decline estimated from Icy Strait 

and Glacier Bay (-12.7 vs. -11.8 percent), and these estimates 

are supported by observed trends from a region wide survey 

(-11.5 percent). Declines in Prince William Sound were less 

extreme, but still large at -6.7 percent per year. Numbers along 

the Malaspina Forelands, in Kachemak Bay, and at Adak 

Island were all negative, and slightly positive at Kenai Fjords, 

but small sample sizes and highly variable data limit our 

ability to reach definite conclusions about trends. 

Consequences of these rates of population change 

are indicated in table 16. We considered two scenarios 

based on the duration and form of long-term trends (see 

appendixes D-K) observed in Alaska and British Columbia: 

(1) that populations declined at a linear rate until about 1999, 

when the decline leveled off (as suggested at one trend site 

in Alaska and British Columbia), possibly owing to effects 

of a weak oceanic “regime shift” in 1999 (see section, 

“Discussion”); and, (2) that populations declined in linear 

fashion all the way to summer of 2006. We calculated rates 

of decline for each trend site under each scenario (table 16). 

We then applied those rates of decline to historical population 

estimates (and used rates from adjacent areas for Yakutat, 

Kodiak, and Gulf of Alaska) and projected what the size of 

populations should be in 1999 or 2006 under each scenario. 

The trend rate for Southeast Alaska was calculated as the 

average between Glacier Bay and Icy Strait (the Agler-Hodges 

trend estimate was excluded). 

In making these projections, we are assuming that rates 

of decline from smaller areas are representative of a larger 

area and population. In Southeast Alaska, there is evidence 

to support that assumption. In Prince William Sound, 

the population level survey data are the same as used for 

estimating trends, so there is no uncertainty about the real 

extent of these projections. Finally, it is worth noting that 

we are not projecting far outside of our temporal window of 

certainty, since trend survey data in most areas were collected 

as recently as 2001–06 (table 17). 

Taken together, the trend and population survey data 

suggest that populations may have declined by 56 percent 

between the time of original surveys and 1999, or by as much 

as 71 percent by 2006 (table 17). We have no trend data from 

one-half of the areas surveyed, and these may have decreased 

or increased during the same time periods. However, numbers 

in these areas are relatively small, and changes one way or 

the other would have little impact on the overall estimate. 

Conversely, Southeast Alaska has the largest impact on any 

analysis of population and trends owing to its large historic 

population size.

Population Status and Trends 49
British Columbia Population 

British Columbia Population Estimates

Burger (2002b) summarized at-sea and radar counts 

for British Columbia to estimate the provincial population 

(table 18). Most of the vast coastline of British Columbia 

did not have count data and estimates were based on several 

methods of extrapolating from at-sea or radar counts covering 

portions of each of the six conservation regions established 

by the CMMRT (see fig. 7). More than 32,500 birds were 

actually counted, and the likely population was estimated to be 

55,000–78,000 birds (median 66,000 birds). Burger (2002b) 

stressed that there was much uncertainty in these estimates

because large areas of the British Columbia coast had not 

been censused, many of the census data were out of date and 

often based on single boat transects, and extrapolations from 

the patchy census data were necessarily crude. There is little 

new information with which to update and improve the crude 

population estimates made by Burger (2002b). Nevertheless, 

we have tried to improve the population estimates in two 

ways: (1) by updating, where possible, the information used 

by Burger (2002b); and (2) by making a new estimate by 

applying densities derived from radar studies to estimates of 

total habitat area within British Columbia. Neither of these 

approaches is highly satisfactory and an accurate estimate of 

the British Columbia population remains elusive.

The total British Columbia population of Marbled 

Murrelets based on the most recent information is estimated 

to be in the range of 54,300–92,600 birds (median 73,000 

rounded to the nearest thousand). This is slightly higher 

than the previous estimate (55,000–78,000 birds; median 

66,000 birds; Burger, 2002). It must be emphasized that both 

the current and the previous estimates are crude, based on 

extrapolations from rather sparse information in most regions 

and with large margins for error. It also must be emphasized 

that the slightly higher population estimate produced in 2006 

does not indicate that the numbers of murrelets in British 

Columbia have risen since the last estimate or since the 

original estimate made by Rodway (1990; 45,000–50,000 

breeding birds or about 53,000–59,000 birds—see Burger, 

2002). Rather, the higher numbers reflect somewhat improved 

data and greater geographical coverage of surveys. All 

available evidence points to declining populations in British 

Columbia (see below). 

Population estimates from the central and northern 

mainland, and the Haida Gwaii (Queen Charlotte Islands) are 

probably the least reliable. In the two mainland regions, the 

populations were estimated from a single year of radar counts 

extrapolated using correlates with areas of apparently suitable 

habitat. Radar surveys are underway that will improve our 

knowledge of these populations and their trends (D. Bertram, 

Canadian Wildlife Service). In all three of these regions, the 

numbers of murrelets per thousand ha of suitable habitat 

varied considerably among the sampled watersheds, and the 

interpretation of suitable habitat from the GIS data also has 

considerable scope for error. GIS mapping to improve the 

estimates of areas of suitable habitat across British Columbia 

is nearing completion (T. Chatwin and M. Mather, British 

Columbia Ministry of Environment), which also will help 

improve population estimates.

British Columbia Population Trends

Population trends of Marbled Murrelets are assessed 

here from surveys made at-sea in British Columbia during the 

breeding season (late April–mid-July). Data were available 

from six transect routes which were repeatedly sampled (but 

not in every year) within the period 1979 to 2006, and two 

routes sampled in 1996–2000. Most of the data cover the 

years 1995–2006. Seven of the transects were off southwest 

Vancouver Island (Clayoquot and Barkley Sounds, and the 

West Coast Trail) and one was in Laskeek Bay off Haida 

Gwaii (Queen Charlotte Islands). Methods varied somewhat 

among the studies but generally murrelets were counted 

on both sides of a small vessel running at constant speed 

along a fixed route, and densities were estimated either 

using an unlimited distance line-transect (giving densities as 

birds per km) or within 300 m-wide strip-transects (giving 

Table 18. Population estimates for British Columbia as reported 

by Burger (2002b) and updated with new information (2006).

[See Appendixes D and E for details. Birds, not breeding pairs or nests, are the 

measure of population used here]

Conservation region1

Population 

estimate made 

in 2002 (birds)2

Updated estimate 

(birds)3

West and North Vancouver 

Island

19,400–24,500 18,700–23,600

East Vancouver Island 700–1,000 1,000–2,000

Southern Mainland Coast 6,000–7,000 6,000–7,000

Central Mainland Coast 10,000–21,000 10,000–21,000

Northern Mainland Coast 10,100–14,600 10,100–14,600

Haida Gwaii (Queen 

Charlotte Islands)

8,500–9,500 8,500 – 25,000

Total for British Columbia 54,700–77,600 54,300 – 92,600

1

For details on the conservation regions see Canadian Marbled 

Murrelet Recovery Team (2003) available at http://www.sfu.ca/

biology/wildberg/bertram/mamurt/links.htm. 2

Range indicates the pessimistic and optimistic population estimates 

(Burger, 2002). 3

See text for details on new population data and updated estimates. 

Note that these estimates remain relatively crude for most of the 

conservation regions.

50 Status Review of the Marbled Murrelet in Alaska and British Columbia
densities as birds per km2

). More details on how surveys were 

conducted, and the results of each survey, can be found in 

appendixes D-E. 

We recognize that the available data have severe 

limitations in their geographical scope (five of the sites are 

close together in Barkley Sound and adjacent West Coast 

Trail and the sixth is in Laskeek Bay off Haida Gwaii (Queen 

Charlotte Islands); fig. 8). We also include a reanalysis of 

previously published data from the Tofino and Flores transects 

done in Clayoquot Sound over 4 years (Mason and others, 

2002), which help to explain the long-term trends seen in 

that area (Kelson and others, 1995; Burger, 2002). Although 

there are gaps and inconsistent survey effort in all data sets, 

sampling effort was sufficient to reveal likely trends. Because 

all six data sets were derived from fixed transect routes, spatial 

variation within study areas is not an issue when analyzing 

long-term temporal variations in these data. Portions of these 

data sets have been used to summarize interannual variations 

in earlier reviews (Burger, 1995b, 2000, 2002b; Bellefleur 

and others, 2005), but appendixes D-E are the most complete 

analysis of these data.

Figure 7. Six Conservation Regions established by the Canadian Marbled Murrelet Recovery 

Team (Bertram and others, 2003) for surveying and managing Marbled Murrelets in British 

Columbia. 

Population Status and Trends 51
Figure 8. Location of sites where at-sea surveys were undertaken in British Columbia. 

52 Status Review of the Marbled Murrelet in Alaska and British Columbia
Overall we found declines in densities or counts of 

Marbled Murrelets in all six of the data sets covering the 

period 1979–2006, and the two data sets covering much 

shorter periods 1996–2000. Despite considerable withinand among-year variations in densities, these trends were 

statistically significant in five data sets (table 19). Statistically 

significant trends emerged from the three data sets with the 

most consistent sampling (Laskeek Bay, Broken Group Islands 

Inner, and West Coast Trail) and we feel the lack of significant 

trends in three data sets might be due to having insufficient 

sample sizes to overcome the natural variation in these at-sea 

data. The annual rates of decline in these data covering more 

than 10 years ranged from -5.8 to -14.6 percent (6.1–14.6 

percent in the statistically significant data sets; table 19), and 

was much higher in the Tofino and Flores transects covering 

1996–2000 (table 19). These estimated rates of decline are not 

intrinsically precise and the addition of another year or two of 

data will undoubtedly change the calculated rate. Nevertheless, 

these are high rates of decline for any population and indicate 

a potentially serious problem for the populations that they 

represent. In the four data sets with adequate sampling in 

recent years, we found no significant trends in densities since 

1999, suggesting that the major changes occurred prior to this 

year.

Although some of the survey sites (Trevor Channel, 

Trevor-Beale-Seabird Rocks) were selected as study areas 

because of high densities of murrelets (Carter, 1984), there is 

no evidence that selection of sites with initial high densities 

produced a biased measure of trend. The high densities in 

the Trevor Channel area were well known to local residents 

for many years prior to Carter’s (1984) study and Carter’s 

unpublished data shows consistent high densities in both 

1979 and 1980. Most of the other transects were long enough 

that they encompassed a wide range of habitats and murrelet 

densities (see Gaston, 1996; Mason and others, 2002; 

Bellefleur and others, 2005), reducing the likelihood that high 

counts in early years were spatial anomalies. Furthermore 

the large spatial coverage of seven transect routes on the 

west coast of Vancouver Island, all of which show declines, 

reduces the likelihood that the trends observed were due to 

local movements. We cannot, however, rule out larger scale 

emigration to other parts of the murrelet’s range.

Burger (2002b) reviewed evidence for population trends 

of murrelets in British Columbia and the main points are 

briefly summarized here. Rodway and others (1992) found no 

clear trends in Christmas Bird Count (CBC) data from 1957 

through 1988. This analysis has not been expanded to include 

more recent data, because few count areas overlap with 

significant wintering populations in British Columbia, and 

CBC data seem to be poor indicators of widespread population 

trends in this species (Hayward and Iverson, 1998b; Piatt, 

1998). 

There is anecdotal evidence that populations of Marbled 

Murrelets in the Strait of Georgia declined significantly in 

the early 1900s. Brooks (1926) commented on the scarcity of 

Marbled Murrelets along the east coast of Vancouver Island 

in 1925–26 compared with numbers observed in 1920 and 

earlier. Pearse (1946) reported a decline in numbers around 

Comox between 1917 and 1944, concomitant with the loss 

of large tracts of the surrounding coniferous forests. In more 

recent times, counts of birds along a 6 km stretch of shoreline 

at Boundary Bay, south of Vancouver, between November 

and August showed a decline from an average of 66 Marbled 

Murrelets in 1980–81 to 2 in 1994–95, and no birds in 1996 

and 1997 (Cooke, 1999). Murrelets appear to have disappeared 

from Burrard Inlet near Vancouver since 1990 (G. Kaiser, 

quoted by Hull, 1999). 

Table 19. Summary of trends of Marbled Murrelet counts and densities at eight marine transect routes in British Columbia.

 [See appendixes D and E for details. Linear regressions were conducted on log-transformed annual means weighted by their variance. Statistically significant 

trends (P<0.05) are shown in bold. Sites are listed from south to north]

Site or transect 

route Region Range of years

Number 

of years 

sampled

Number 

of 

surveys

Slope

Rate of 

change 

percent 

per year

R-squared F df P

West Coast Trail West Vancouver Island 1994–2006 10 32 -0.063 -6.1 0.53 9.02 1, 8 0.017

Trevor Channel West Vancouver Island 1980–2000 10 61 -0.060 -5.8 0.58 4.93 1, 7 0.046

Trevor/Beale/SBR West Vancouver Island 1979–2005 6 20 -0.097 -9.3 0.48 3.72 1, 4 0.126

BGI Inner West Vancouver Island 1991–2006 14 65 -0.087 -8.3 0.72 30.85 1, 12 0.000

BGI Outer West Vancouver Island 1995–2006 10 41 -0.062 -6.0 0.17 1.67 1, 8 0.232

Tofino transect West Vancouver Island 1996–2000 4 19 -0.375 -31.2 0.89 16.58 1, 2 0.055

Flores transect West Vancouver Island 1997–2000 4 15 -0.240 -21.3 0.98 86.03 1, 2 0.011

Laskeek Bay Haida Gwaii (Queen 

Charlotte Islands)

1992–2004 14 56 -0.158 -14.6 0.39 7.79 1, 12 0.016

Population Status and Trends 53
Burger (2002b) analyzed data from audio-visual surveys 

made from 1991 through 1999 at 11 stations within the forest 

nesting habitat in the Carmanah and Walbran watersheds 

adjacent to the West Coast Trail on southwest Vancouver 

Island. A subset of the audio-visual detections, which indicate 

site occupancy, provided indirect measures of relative murrelet 

abundance. Mean frequencies of occupied detections showed 

a significant negative correlation with sea temperature 

(Burger, 2000), but Burger’s (2002b) analysis, using analysis 

of covariance with sea temperature as a covariant, showed 

a significant negative trend over the 9 years (adjusted r2 = 

0.347, P < 0.001; see appendixes D and E). Since 1990, there 

has been no logging in the Carmanah valley, but parts of 

upper Carmanah were logged in the late 1980s and logging 

continued in the upper Walbran close to the observation 

stations. 

Radar counts made during the breeding season at the 

mouth of the Bedwell-Ursus Watershed in Clayoquot Sound 

showed a significant decline in the years 1995–98, which 

corresponded to declines in annual mean detections in audiovisual surveys made in the same drainage (Burger, 2000). 

This could not be attributed to logging because there had not 

been any logging in that drainage for 40 years. There was 

a weak non-significant negative correlation with local sea 

temperatures in both the radar and audio-visual detections 

(Burger, 2000). 

Overall, these published data and reviews show a 

consistent pattern of decline in numbers of Marbled Murrelets 

wherever there are reasonable data to test trends in British 

Columbia.

Demographics and Population 

Dynamics

This section presents an in-depth treatment of 

demography and population dynamics of the Marbled 

Murrelet. We first review the history of previous efforts to 

model Marbled Murrelet populations. Then, using what we felt 

to be reasonable vital rate estimates (for fecundity and adult 

survival) for Marbled Murrelets, we present potential resultant 

population growth rates using two models: (1) a deterministic, 

life table model; and (2) a matrix model incorporating 

stochasticity. We use the models to explore how variations in 

vital rates affect population trends. These modeling exercises 

provide context for understanding the likely significance and 

need for conservation concern about murrelet population 

trends observed empirically.

Survivorship, Fecundity, and Age at Maturity

Knowledge of a species’ survival rates is essential 

for demographic analyses, but rates of survival of Marbled 

Murrelets at every life stage are poorly known. Adult survival 

has been estimated in two ways: (1) as a prediction from 

the literature based on allometric relationships observed in 

other alcids (Nur, 1993; DeSanto and Nelson, 1995); and 

(2) using data from two field investigations that used markrecapture methods in Desolation Sound (Cam and others, 

2003) and central California (Peery and others, 2006b). From 

the relationships among survival rate, body size, and clutch 

size in the alcid family, Nur (1993) predicted the survival of 

adult murrelets should be about 0.85. Cam and others (2003) 

reported two estimates derived from samples of murrelets 

captured by different techniques. For a sample obtained with 

night-lighting and dip-nets, they calculated an adult survival 

rate of 0.83 (95 percent CI: 0.716–0.903), whereas birds 

captured with a mist-net deployed over water produced a 

higher value, 0.93 (95 percent CI: 0.629–0.990). Trap shyness 

may have contributed to lower recapture rates by dip-netting. 

The sample was thought to include a larger proportion of 

subadults than the mist-netted group, which also would affect 

the estimation of survival if pre-breeders had lower survival 

or lower fidelity to the study area (Cam and others, 2003). 

Finally, the authors’ estimated rate of population growth was 

0.86 in conjunction with the 0.83 estimate of survival, i.e., a 

decline of 14 percent per year. That amounts to a 95 percent 

population decline in 20 years, or 75 percent in 10 years—the 

duration of the field study reported by Cam and others (2003). 

The authors make no mention of a large (and presumably 

noticeable) population decline during their study, which 

suggests the 0.83 estimate of adult survival is too low. 

In central California, Peery and others (2006a) obtained 

estimated annual survival rates of 0.868 (SE = 0.074) for 

males and 0.896 (SE = 0.067) for females (all birds captured 

by dip-netting at night). Those estimates incorporated the 

survival of subadults (ages > 1 year), because adults and 

subadults could not be distinquished in the field. Survival of 

subadults probably is lower than adult survival, but breeding 

success was poor in central California (Peery and others, 

2004b; Peery and others, 2006b), thus the representation of 

subadults in the marked sample may have been small.

Little is known about juvenile survival in Marbled 

Murrelets. Parker and others (2003) estimated a survival rate 

of 0.862 for the first 80 days post-capture among recently 

fledged juveniles in Desolation Sound. The extrapolated 

annual rate of survival over the first year of life was 0.51, 

but that calculation assumes no change in daily survival 

54 Status Review of the Marbled Murrelet in Alaska and British Columbia
between the first 80 days and subsequently, which is probably 

unrealistic (Parker and others, 2003). In the following section, 

“Population Models,” we will model murrelet populations 

using survival rates for first-year juveniles (0-1 years of age) 

and second-year subadults (1-2 years of age) estimated by 

the levels (expressed as proportions of adult survival) seen in 

other alcids. Nur’s (1993) review suggested that reasonable 

estimates would be 70.1 and 88.8 percent of adult survival for 

first- and second-year birds, respectively.

In addition to survival, fecundity, the annual production 

of female offspring per adult female in a population, is an 

essential input to population models. To estimate fecundity, 

nesting success is divided in one-half, and further adjustments 

may be needed to account for adults that skip breeding 

(breeding propensity) and for multiple breeding attempts 

within a year (double clutching or renesting). Double clutching 

(production of more than one brood per year) is unknown in 

Marbled Murrelets, but replacement laying (a second clutch 

following a failed first attempt) has been estimated at 13–63 

percent annually (McFarlane Tranquilla and others, 2003a). 

The difference, if any, between the average success of first 

and second nesting attempts is unknown. The percentage of 

non-breeding adults was estimated at 22 percent in Desolation 

Sound (McFarlane Tranquilla and others, 2003c), whereas 

McShane and others (2004) suggested that it should be less 

than 10 percent for most Marbled Murrelet populations in 

most years, as is seen in other alcids. For our models, in the 

absence of definitive data, we will assume that the effect of a 

breeding propensity <1 is offset by successful renesting, and 

that uncorrected nesting success (divided by 2) is a reasonable 

approximation of fecundity.

At-sea ratios of juveniles to adults are an alternative 

measure of fecundity, but they suffer from a number of 

potential biases, as discussed earlier. The ratios also will differ 

from estimates of nesting success because they incorporate 

early post-fledging mortality. 

The age of first breeding is unknown for Marbled 

Murrelets, but is thought to occur anywhere from age 2 

to 5 and most commonly at age 3 (DeSanto and Nelson, 

1995; Burger, 2002). Other studies have modeled murrelet 

populations using various assumptions about the breeding 

propensities of murrelets between 2 and 5 years of age 

(Beissinger, 1995b; McShane and others, 2004). In the 

absence of specific data, we will use a uniform value of 3 

years for purposes of modeling population dynamics, below.

Population Models

When a population is monitored over a substantial period 

of time it typically exhibits trends – sometimes it increases, at 

other times it declines. Two technical elements are key when 

monitoring and then interpreting subsequent results:

1. Much attention is given to the issue of statistical 

significance. We want to be sure of statistically detecting 

a trend. Statistical power analysis is a helpful tool in 

designing sampling protocols with known probabilities 

of detecting trends (Kuletz and Kendall, 1998; Jodice and 

others, 2001; Smith and Harke, 2001; Hatch, 2003); and

2. Once a statistically significant trend is detected, how are 

the biological factors controlling the population trend 

understood? In other words, what is the biological (as 

opposed to statistical) significance of the trend? Is the 

population on a trajectory that would be unlikely to occur 

as an outcome of natural fluctuations in fecundity and 

survival? 

In this section, we explore population growth outcomes 

for different scenarios of published biological metrics using 

two model approaches. These models help inform possibilities 

for evaluating the biological significance of trends detected 

through monitoring. We preface that discussion with an 

overview of prior efforts to model the population dynamics of 

Marbled Murrelets, and we demonstrate a convenient method 

for calculating the expected growth rate of a population.

Previous Studies

Modeling efforts pertaining to murrelet populations 

outside of Alaska are reviewed by Burger (2002b), Lank 

and others (2003), and McShane and others (2004). Briefly, 

models created prior to the latest review (McShane and others, 

2004) used some version of a three-stage (juveniles, subadults, 

adults) projection model to predict population growth 

deterministically (i.e., no allowance for stochastic variation) 

given the best available estimates of fecundity, survival rates, 

and age at first breeding (Beissinger, 1995b; Beissinger and 

Nur, 1997; Boulanger and others, 1999; Boulanger; 2000; 

Peery and others, 2002). None of the models incorporated 

population density as a possible influence on birth and death 

rates. McShane and others (2004) developed a stochastic 

matrix model with multiple adult age classes to address 

assumptions implicit in the earlier models—namely, unlimited 

maximal longevity, and invariant rates of productivity and 

survival. All models pertaining to murrelets in the southern 

portion of their range (Washington, Oregon, and California) 

have predicted population declines of 2 to 6 percent per year. 

McShane and others (2004) found extinction in less than 

100 years is likely within some of the conservation zones 

delineated in the species recovery plan.

In Desolation Sound, British Columbia, Cam and others 

(2003) concluded that their study population probably was 

declining slowly (replacement rate 0.985), but the range of 

model estimates included the possibility of a stable or slightly 

increasing trend. These results were due in part to the higher 

estimates of productivity and survival they obtained from their 

field studies. 

Demographics and Population Dynamics 55
A Deterministic Model of Population Growth—

Program LIFE

The timing and magnitude of population growth 

(defined as a positive or negative change in population size) 

is an outcome of the mean values of population vital rates 

(fecundity, survival, age at first breeding) and the variability 

of those parameters. Variability can be age-related—e.g., 

individuals may become more productive with breeding 

experience, old individuals and subadults may survive at 

different rates than young adults –and it also can arise from 

environmental variation or the influence of population density. 

Whereas age-structured models with time-varying inputs are 

required to examine the complexities of population growth, it 

is often desired simply to calculate the expected growth rate 

of a population for a given set of known or hypothetical values 

of key demographic parameters—i.e., the question is simply 

whether the population of interest would be expected to grow, 

decline, or remain relatively stable. A tool for doing this is 

described below.

The expected growth rate of a population with discrete 

but overlapping generations can be calculated from the 

following equation (adapted from Fisher, 1966, p. 37):

	 λδ

 = α-1 + α β δ, (1)

where,

λ = population growth rate (also called ‘net replacement rate’);

α = fecundity;

γ = adult survival (proportion of adults surviving from time t

to time t+1);

β = juvenile survival (proportion of subadults surviving from 

time t to time t+1); and

δ = age at first breeding (years expressed as integer value).

This relationship applies when there is no upper limit 

on adult longevity (i.e., no senescence), no variation in the 

demographic parameters α, γ, β, and δ, and production 

is considered to occur in a pulsed, simultaneous manner 

annually (i.e., the breeding season takes “zero” time). The last 

assumption can be relaxed by subtracting from δ a quantity 

representing the fraction of a year taken up by one complete 

breeding cycle (about 70 days, or 0.19 year in Marbled 

Murrelets; Fisher, 1966). That refinement makes little sense 

in the present context, however, because the discrepancy is 

incorporated in the value of β, which is only crudely estimated 

anyway.

An intuitive grasp of equation (1) can be gained by 

considering how it applies to a stationary population. When λ

= 1, the left side reduces to unity and the first term on the right 

reduces to γ (which also could be expressed as 1 – m, where m

is the annual mortality rate of adults). The second term on the 

right expresses the number of young recruited in year δ from 

an initial cohort of α young per adult (i.e., it is the cohort size 

at fledging reduced by the juvenile survival rate applied over 

δ years). Thus, in the special case where λ = 1, the equation is 

satisfied when adult mortality is exactly offset by recruitment.

Equation (1) is unrealistic insofar as survival in each of 

the prebreeding years is assumed to be equal to the mean value 

for ages 0 to δ. It generally is thought that juvenile mortality 

in seabirds is concentrated in the first year or two of life, after 

which the survival rate approximates that of adults (Lack, 

1966; Nelson, 1966; Potts and others, 1980). Thus, a more 

realistic model is:

	 λδ

 = γλδ-1 + α b1b2γδ-2, (2)

where b1 is first year survival (age 0–1), b2 is second-year 

survival (age 1–2), and the other parameters are defined as 

before. 

Because λ is exponentiated on both sides of equation 

(2), the growth rate is most readily evaluated by iterative 

interpolation using a computer. This solution has been 

implemented as a short Javascript program (appendix B), 

which can be used for estimating population growth rate when 

the other parameters are entered as known or hypothetical 

values. Using program LIFE, we calculated the expected 

growth rate of the Alaska population of Marbled Murrelets 

under various scenarios, ranging from the worst to the best 

combination of available estimates for adult survival and 

fecundity. For adult survival, we used the lower and higher 

estimates (and their mean) obtained in the mark-recapture 

study of murrelets in Desolation Sound (Cam and others, 

2003). For fecundity, we used raw and adjusted HY:AHY 

ratios reported for Kachemak Bay (Kuletz and Piatt, 1999), 

and the estimated nesting success of murrelets in Desolation 

Sound, as determined by Bradley and others (2004) from 

radio-telemetry. 

Given the amount and quality of demographic data 

currently available, and considered appropriate to Alaska 

murrelets, we can say only that predicted population growth 

ranges from strongly negative (about –9 percent per year) to 

strongly positive (about 5 percent per year), with intermediate 

values of the input parameters producing a population that is 

approximately stable (table 20).

56 Status Review of the Marbled Murrelet in Alaska and British Columbia
 If M = 

f fff f f f f

s

s

s

0 1 2 3 4 5 k k 1

0

1

2

000 0 0 0 0

0 0 0 0 0 0 0

0 0

⋅⋅⋅

⋅⋅⋅

⋅⋅⋅

−

0 0 0 0 0

0 0 0 0 0 0 0

0 000 0 0 0

0

3

4

⋅⋅⋅

⋅⋅⋅

⋅⋅⋅ ⋅ ⋅⋅⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅⋅⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅⋅⋅ ⋅ ⋅ ⋅ ⋅

s

s

000 0 0 0 1

0

1

2

3

4

⋅⋅⋅













































=

− s

N

N

N

N

N

N

k

 and t





 

N

N N

k

t t













































 then M = +1

A Flexible Model of Population Growth—

Program MATRIX

The deterministic life table equation (2) and program 

LIFE are useful for calculating the expected growth rate 

of a population when estimates of the basic demographic 

parameters are available. To project actual population levels 

over finite periods of time, however, it is necessary to model 

the demographic parameters not as constants but as variables, 

subject to change over time for the whole population or with 

the age of an individual. The common approach for doing this 

uses some version of the matrix model of population growth 

introduced by Leslie (1945). Briefly, the basic set-up is as 

follows:

Scenario1 Adult Survival2 Fecundity3 Population Growth Rate (λ)

4

Pessimistic 0.83 0.19 0.911 (0.901)

↓

0.24 0.929 (0.923)

0.26 0.936 (0.930)

0.88 0.19 0.966 (0.961)

0.24 0.985 (0.981)

0.26 0.992 (0.988)

0.93 0.19 1.021 (1.021)

0.24 1.041 (1.039)

Optimistic 0.26 1.047 (1.044)

1

Age at first breeding 3 years for all calculations, with first- and second-year survival estimated at 0.701(adult rate) and 0.888(adult rate), respectively.

2

High, low, and mean values of Marbled Murrelet adult survival, as estimated by Cam and others (2003) using mark-recapture methods in British Columbia.

3

Fecundity estimated by HY:AHY ratios in Kachemak Bay (low value; Kuletz and Piatt, 1999), the same estimate adjusted for possible inclusion of 

nonbreeding subadults in the ratio (high value; see text), and fecundity based on nesting success of murrelets in Desolation Sound, British Columbia (Bradley 

and others, 2004).

4

Values in parentheses are corresponding rates calculated by program MATRIX for comparison; they differ from the LIFE estimates because of differing 

assumptions about maximal longevity (see text).

Table 20. Predicted population growth rates of Marbled Murrelets in Alaska using the demographic model LIFE.

Demographics and Population Dynamics 57
The f

i

 are age-specific fecundities (number of offspring 

produced in each time interval t by a female of age i) and the 

si are age-specific survival rates. Maximal longevity is denoted 

by k—all individuals surviving at age k-1 are assumed to die 

within the next time interval. Nt is a column vector expressing 

the number of individuals in age class i alive at time t, and 

the sum of the Ni is equal to population size. The square 

array of fecundity values and survival rates M is often called 

the “projection matrix” because it contains the information 

necessary to project the population into the future. When the 

vector Nt is multiplied by matrix M, the result is a new vector 

Nt+1, potentially with a new sum (population size) and age 

distribution (proportions of individuals in the age classes No to 

Nk). Mathematically, the age distribution tends toward a fixed 

array (called a stable age distribution) that is characteristic 

for any fixed set of f

i

 and si. As long as the f

i

 and si remain 

unchanged, a population that has reached its stable age 

distribution retains that distribution indefinitely, even as the 

population grows or declines.

Originally, population biologists viewed the Leslie matrix 

model as a simple heuristic tool, limiting its application to 

cases where the f

i

 and si were modeled as constants. With the 

aid of a computer, however, it is possible to let the parameters 

change according to any hypothetical scheme and thus to 

model population behavior more realistically (e.g., Pollard, 

1966; Searle, 1966; Goodman, 1969).

We implemented the Leslie matrix model of population 

growth in a Fortran program called MATRIX (appendix C). 

The user enters proposed mean values and SDs for α (annual 

fecundity), γ (adult survival), b1 and b2 (first and second-year 

survival expressed as proportions of adult survival), and δ, the 

age of first breeding (modeled here as a constant in MATRIX). 

Program outputs include:

•	 λ, the expected population growth rate (as in program 

LIFE);

•	 αadj, the adjusted rate of fecundity needed to achieve 

a stationary population (λ = 1) given the survival 

schedule entered by user;

•	 The stable age distribution calculated for the

demographic parameters as entered;

•	 The stable age distribution for a population with α = 

αadj and λ = 1;

•	 The population trajectory that results when parameters

in the projection matrix are held constant at their userentered mean values;

•	 Examples of population trajectories that result when

parameters in the projection matrix are allowed to vary 

stochastically;

•	 Mean time to population extinction and a distribution

of extinction times for the calculated λ and for the 

special case λ = 1; and

•	 Trend frequencies over intervals of 10, 20, and 30 years

that result when input parameters are allowed to vary 

stochastically.

By allowing stochastic variation in the values of most 

demographic parameters, the projection of population size 

through time is made more realistic than is possible using 

a strictly deterministic model such as LIFE. As no data are 

available on the age-specific rates of fecundity or survival 

of adult murrelets, our simulations use best estimates of 

mean rates for all f

i

 and si. Cam and others (2003) reported 

two estimates of local survival. The first (0.829) they 

considered probably was biased low (as an estimate of adult 

survival) because it included subadult birds in the sample. 

The second estimate (0.929) they suggested possibly was 

biased high because it sampled primarily the successful 

breeding component of the population. The mean of the two 

estimates is 0.879. Peery and others (2006b) reported separate 

estimates for male (0.868) and female (0.896) murrelets, the 

mean of which is 0.882. We therefore used a value of 0.88 

annual adult survival for applications of the matrix model. 

Following Beissinger (1995b) and McShane and others 

(2004), we assumed that first-year survival is 0.701 times the 

adult survival rate and second-year survival is 0.888 times 

the adult rate—values based on what has been reported for 

other alcids (Beissinger, 1995b). We included all murrelets 3 

years of age or older in the adult (breeding) population, and 

the initial conditions for each simulation included a stable age 

distribution (calculated initially by MATRIX for the given 

set of parameter inputs). We used a mean fecundity of 0.24, 

corresponding to the mean nesting success (0.48) of radiotagged murrelets over a 4-year study in Desolation Sound, 

British Columbia (Bradley and others, 2004; table 5).

Stochastic variability at each iteration of the model 

(i.e., annually) is simulated by drawing random values from 

distributions of annual productivity and survival, which in turn 

are dictated by the means and SDs supplied as inputs. The CV 

in annual nesting success of Marbled Murrelets was 0.357 in 

the study by Bradley and others (2004). In our simulations, we 

calculated the fecundity required of murrelets for λ = 1 (with 

annual survival of 0.88) to be 0.295 (see below). Applying 

the observed CV to a fecundity of 0.295 provides an estimate 

of 0.105 (SD) for interannual variation in fecundity. Annual 

estimates of murrelet survival (n = 6) in California ranged 

from about 0.83 to 0.97 (fig. 3 in Peery and others, 2006b), 

with an SD of 0.059. Thus, on the information currently 

available, we took 0.1 as the best estimate of interannual 

variation (SD) in fecundity (α), and 0.06 as the SD of survival 

rates (γ, b1

, and b2) in Marbled Murrelets. To gauge the 

sensitivity of model results to the accuracy of those inputs, we 

also ran simulations using SDα = 0.2 and SDγ

 = 0.1 (a “high 

variability” example) as well as SDα = 0.05 and SDγ = 0.02 (a 

“low variability” example).

58 Status Review of the Marbled Murrelet in Alaska and British Columbia
A final technical note is necessary concerning our 

parameterization of the MATRIX model. In a Leslie matrix 

model, the f

i

 assume that the youngest cohort includes only 

females that survive until the time interval in which they 

were produced has passed. At the end of that interval, they 

are all considered to be of age 0 (Batschelet, 1971). Similar 

to the LIFE model (see above), we make the simplifying 

assumption that all young are produced simultaneously, and 

the concomitant assumption that the first-year survival rate of 

juveniles applies over an entire year. The approach is sensible 

when juvenile survival is poorly known, and the effect on 

model behavior is negligible when the input parameters are 

set to produce an expected λ equal to 1. That special case 

(expected λ = 1) is the focus in the discussion to follow.

Our approach is essentially the one employed by 

McShane and others (2004). Their analysis predicted 

extinction for the California population(s) of murrelets within 

100 years. McShane and others (2004) used demographic 

parameters considered appropriate for California Marbled 

Murrelets, which had been shown by Beissinger (1995b) 

to result in rapid population decline. One effect of adding 

stochasticity is that it hastens, on average, the inevitable 

outcome, which is extinction. It is important to realize, 

however, that stochastic variation of birth and death rates in 

such a model (with birth rates < death rates) ensures that the 

simulated population eventually goes extinct, even when the 

means of the input parameters are set to produce an expected 

λ equal to 1.

To illustrate this, we ran a relatively small population of 

murrelets (starting population size 3,000) repeatedly through 

a simulated future using MATRIX. We set fecundity and 

survival such that the expected λ is equal to 1 (γ = 0.880, b1

= 0.701, b2 = 0.888, and α = 0.295 as calculated by MATRIX 

for λ = 1). We resampled values for fecundity (α) and survival 

(γ, b1, and b2) annually from normal distributions of those 

parameters, as described above. We applied the same random 

variates to juvenile and adult survival on the assumption that 

those parameters are likely to vary concordantly. However, for 

this (and subsequent) applications of MATRIX, we considered 

two scenarios, termed ‘seasonal independence’ and ‘seasonal 

concordance.’ The first option models the situation in which 

annual survival and annual productivity vary independently—

those two parameters do in fact reflect environmental factors 

that impinge primarily at different seasons, winter and summer 

—while the alternative (seasonal concordance) is a scenario in 

which “good” and “bad” years affect both parameters equally.

In all cases in which birth and death rates are allowed to 

vary stochastically, the simulated population (with expected 

λ = 1) goes exinct (fig. 9). That outcome happens sooner on 

average with seasonal concordance, because the effect of low 

and high values of fecundity and survival is accentuated. The 

reason why a “stochastic” population (with expected λ = 1) 

always goes extinct has to do with the multiplicative nature 

of birth and death rates. The population is on a “random 

walk.” Early on there can be large changes, up or down, but 

eventually the population will wander to low levels from 

which it is simply not possible to recover because the absolute 

number of individuals (as opposed to percentage) being added 

or subtracted each year is too small to reverse the trend (given 

the SDs of the input parameters).

It should be noted that we took a threshold value of 

5 percent of No as our definition of extinction. This assumption 

seems reasonable when starting with a small population (such 

as 3,000), because with a 95 percent reduction there are only 

150 individuals remaining. From a practical standpoint, that 

equates to extinction, especially given the likelihood of an 

Allee effect, whereby a population that reaches a low threshold 

experiences negative density dependence (for logistic and 

behavioral reasons) and proceeds rapidly to extinction (Boyce, 

1992). Mathematically, however, it may take considerably 

longer for a population to walk randomly to its literal 

extinction (i.e., less than one individual remaining) than what 

is suggested by the end points depicted in figure 9.

By running a large number of simulations, it is possible 

to show the expected distribution of extinction times (fig. 10). 

As mentioned, extinction occurs sooner with seasonal 

concordance – the mean time to extinction is 616 years versus 

1,030 years in the alternative model – but is highly variable in 

either case. There is a small possibility of a population with No

= 3,000 going extinct in fewer than 100 years. To reiterate, this 

outcome applies to a population with mean rates of fecundity 

and survival that predict a stationary population.

The concept of inevitable extinction in a stochastic 

model may be unfamiliar, so it is worth mentioning that this 

outcome is well-grounded in mathematical theory (Pielou, 

1969; Krebs, 1978). For a population with instantaneous birth 

and death rates (denoted b and d, with d = 1 - γ ) that are 

subject to stochastic variation, the probability of extinction 

is a finite value that approaches (d/b)

No as time becomes very 

large (Krebs, 1978). That is, extinction probability depends 

on initial population size and the ratio of birth and death 

rates. For the special case in which birth and death rates are 

equal, the expression reduces to 1, regardless of population 

size. Given enough time, extinction is the inevitable fate of 

such a population. [Readers who try the formula in relation to 

murrelet population models will find that the relatively rapid 

extinction observed in many simulations seems inconsistent 

with theory. There are two reasons for this discrepancy: (1) the 

formula predicts literal extinction (<1 individual remaining), 

whereas we use a threshold of 5 percent of No remaining as 

our functional definition of extinction; and (2) the theory is 

expressed in terms of instantaneous rates, whereas the model 

rates are finite—i.e., birth and death are measured on time 

intervals of 1 year. The principle is the same, but extinction 

will occur sooner on average in a discrete time population 

model.

Demographics and Population Dynamics 59
Years

0 200 400 600 800 1000

Population size

0

1000

2000

3000

4000

5000

6000

7000

   sto

   det

Seasonal independence

Years

0 200 400 600 800 1000 1200 1400

Population size

0

2000

4000

6000

8000

10000

12000

Run 2

Run 1

Years

0 500 1000 1500 2000

Population size

0

2000

4000

6000

8000

Run 3

Years

0 100 200 300 400 500

Population size

0

1000

2000

3000

4000

Run 4

Seasonal concordance

Years

0 50 100 150 200 250 300

Population size

0

1000

2000

3000

4000

5000

Run 4

Years

0 100 200 300 400

Population size

0

1000

2000

3000

4000

5000

Run 3

Years

0 20 40 60 80 100 120 140

Population size

0

1000

2000

3000

4000

5000

6000

Run 2

Years

0 100 200 300 400 500

Population size

0

2000

4000

6000

8000

10000

Run 1

Figure 9. Examples of projected numbers for a population of 3,000 Marbled Murrelets with and 

without stochastic variation in survival and fecundity. Mean values of demographic parameters 

are the same for the “deterministic” (det) and “stochastic” (sto) populations. “Seasonal 

concordance” and “seasonal independence” indicate linkage or absence of linkage between 

the annual variations in fecundity and survival. Initial conditions and model procedures are the 

same for all runs.

60 Status Review of the Marbled Murrelet in Alaska and British Columbia
Years to "extinction" (95% decline) 1100 2100 3100

4100

100

Seasonal independence

Frequency

350

300

250

200

150

100

50

0

SD = 806

Mean = 1030

N = 1000

Years to "extinction" (95% decline) 1100 2100 3100

4100

100

Seasonal concordance

Frequency

350

300

250

200

150

100

50

0

SD = 498

Mean = 616

N = 1000

Years to "extinction" (95% decline) 1100 2100 3100

4100

100

Seasonal independence

Frequency

350

300

250

200

150

100

50

0

SD = 806

Mean = 1030

N = 1000

Years to "extinction" (95% decline) 1100 2100 3100

4100

100

Seasonal concordance

Frequency

350

300

250

200

150

100

50

0

SD = 498

Mean = 616

N = 1000

Figure 10. Variability of extinction times for a small population of Marbled Murrelets (No = 3,000) 

when survival and fecundity are subject to stochastic variation. Distributions reflect the frequency of 

outcomes in 1,000 trials under conditions of seasonal independence and seasonal concordance.

In natural populations, birth and death rates often vary 

in a manner that appears outwardly to be stochastic, yet those 

populations ordinarily do not go extinct over observable 

periods of time. The explanation of this paradox lies in 

density dependence—variation in birth and death rates is in 

fact not entirely stochastic, but is mediated to some extent by 

population size, or density. The interplay of stochastic and 

deterministic controls on demographic parameters is shown 

schematically in figure 11. It would seem like a good idea to 

model density dependence by superimposing on the stochastic 

variation a certain amount of density dependent regulation. 

The problem is that we know virtually nothing about the 

functional relationships between birth and death rates and 

population density for most natural populations, and Marbled 

Murrelets are no exception. We could achieve different 

outcomes using the models, depending on what we are 

inclined to believe about density dependence. Unfortunately, 

our applications of MATRIX omit this essential, but unknown 

effect, as have previous models for murrelets.

We point out that the estimates of λ from programs LIFE 

and MATRIX are not identical for the same inputs (table 20). 

This is because an upper bound is placed on longevity in 

the matrix model but not in the life table equation. In our 

implementation, the size limit of the projection matrix is 

established by the age at which fewer than 5 percent of a 

cohort remain alive—all adults of that age are assumed to 

die within 1 year. The resulting maximal longevity (with 

an age-constant γ = 0.880) is 27 years. This difference in 

model assumptions affects the predicted λ to a small degree, 

even when birth and death rates are modeled as constants in 

MATRIX.

Applying a matrix model to Marbled Murrelets is a 

qualitatively different exercise in Alaska than in California, 

because the subject population is much larger in Alaska. 

If we use the same model inputs as before but start with a 

population of 300,000 individuals (as an example), the mean 

time to extinction (5 percent of original population remaining) 

is unchanged—all populations, regardless of size, have the 

same distribution of “extinction” times depicted in figure 10. 

However, when our hypothetically large population declines 

to 5 percent of original numbers, it still contains some 15,000 

individuals, which is not a reasonable definition of extinction. 

The population would likely exhibit episodes of recovery, 

perhaps repeatedly, before reaching a realistic measure of 

extinction, such as 150 individuals remaining.

When dealing with a large population of murrelets, 

as in Alaska, the issue is not so much whether or when the 

population will become extinct. A more practical application 

of MATRIX in this situation is the estimation of stableage distributions. When any combination of inputs (α, γ, 

b1

, b2, and δ) are entered, MATRIX reports the stable-age 

distribution that results from those parameters, and also the 

stable-age distribution that would occur at λ = 1 (α having 

been adjusted to achieve that outcome). This information 

can be used to estimate the size of the subadult population 

—an important statistic about which little is known directly. 

Although the estimates are no better than the quality of inputs 

for productivity and survival, they can be useful as a working 

approximation. In the present case, an Alaska population with 

α = 0.24 and γ = 0.880 is expected to be slowly declining 

(table 20) and to have about 26 percent of total numbers in 

the subadult year classes (fig. 12). MATRIX calculates that 

Demographics and Population Dynamics 61
• Density dependence

absent

• Stochasticity as modeled, 

or absent

Population density

Fecundity & survival

Population density

Population density Population density

Population density

Fecundity & survival

Stochasticity

high

Density dependence weak Density dependence strong

Stochasticity

low

Fecundity & survival

Fecundity & survival Fecundity & survival

Murrelet population models:

)a( )b(

)c( )d(

Figure 11. Contributions of stochastic and density-dependent effects to variability in 

population size. A population in long-term equilibrium exhibits large deviations when birth 

and death rates are highly variable but unresponsive to density (a), or small deviations when 

stochastic effects are slight and density dependence is strong (b). Intermediate conditions 

are depicted in (c) and (d). 

62 Status Review of the Marbled Murrelet in Alaska and British Columbia
a fecundity of 0.295 is required for a stationary population, 

given γ = 0.880, b1 = 0.701, b2 = 0.888, and δ = 3. In that 

case, the cohorts of subadults are 18.3 percent 1-year-olds and 

11.3 percent 2-year-olds (fig. 12), for a total of 29.6 percent 

subadults in the population. Therefore, subadults (excluding 

juveniles, age 0) compose an estimated 22–25 percent of AHY 

murrelets. Applying that information to field data, a HY:AHY 

ratio can be adjusted for the proportion of AHY birds that are 

non-breeding subadults, giving a better estimate of fecundity. 

A necessary assumption is that adults and subadults are 

distributed similarly with respect to the areas surveyed. For 

Kachemak Bay (Kuletz and Piatt, 1999), the juvenile index 

of 0.192 (all transects combined) means that productivity was 

not 19 young per 100 adults, but something closer to 19 young 

per 75 adults (0.255) or 19 young per 78 adults (0.245). That 

is the basis for the most “optimistic” scenarios considered in 

table 20. 

In Alaska, the most important application of MATRIX 

concerns the problem of interpreting the biological 

significance of trends. When we consider the variability of 

animal numbers from a conservation perspective, we have 

only two options for deciding what is normal, or natural: (1) 

we can monitor populations under natural conditions for a 

sufficient period of time that the range of natural variation 

Figure 12. Stable-age distributions calculated by MATRIX for a stationary population of Marbled Murrelets 

(λ = 1) and another declining at the rate of 2 percent per year.

Age class

0 3 6 9 12 15 18 21 24 27

% of population

0

5

10

15

20

         

        

Demographics and Population Dynamics 63
(in trends, not numbers) has been observed and quantified 

statistically—in the case of long-lived animals such as 

seabirds, a study duration of hundreds, or even thousands 

of years may be needed to do the job; or (2) we can model 

populations in ways that predict the frequency of trends of any 

given duration and magnitude. In that case, we would compare 

an observed trend with the expected distribution of trends and 

judge its biological significance in a manner analogous to the 

conventional use of probability in statistics. This is where a 

program such as MATRIX can contribute, because it allows 

us to calculate for the modeled population the frequencies 

of trends to be expected purely by chance. In the stochastic 

model, trends arise from the chance juxtaposition in time of 

high and low levels of productivity and survival and, especially 

in the case of seasonal concordance, the chance concatenation 

of “good” and “bad” years into runs that produce either 

favorable or unfavorable trends in a population.

For Marbled Murrelets, we calculated the distributions of 

trends arising by chance in a population with its demographic 

parameters set so that λ = 1, but with stochastic variation in 

fecundity and survival causing variability around a short-term 

equilibrium value (short-term, that is, in relation to the mean 

extinction time, as discussed previously). The input values, 

as before, were γ = 0.880, α = 0.295, b1

 = 0.701, b2 = 0.888, 

and δ = 3. The stochasticity arises from SDs of 0.1 and 0.06 

in fecundity and survival rates, respectively. This was done for 

study intervals of 10, 20, and 30 years, which may be thought 

of as typical benchmarks in a monitoring program for wildlife 

populations. Distributions are generated by running the same 

starting population to extinction (<5 percent remaining) a large 

number of times (n = 1,000) and calculating for every interval 

of 10, 20, or 30 years the percentage change in population that 

occurs from beginning to end of the interval.

On average, the change over any 10-, 20-, or 30-year 

period is approximately 0 (as expected), but ranges from more 

than +100 percent (a population doubling) to declines greater 

than 60 percent that arise solely from the stochastic variation 

in birth and death rates (fig. 13). The probability (biological 

significance) of an observed trend can be interpreted from the 

graphs. The sensitivity of this analysis to the SDs of survival 

and fecundity (SDγ and SDα) is characterized in figure 14 (a 

higher variance example) and figure 15 (a lower variance 

example). One general conclusion from these simulations of 

random-walking effects may be counterintuitive—the longer 

a population has been observed, the more likely it is that any 

observed trend is due to chance.

What should be the rarity of a given trend before we 

would consider it biologically significant, i.e., what is an 

appropriate action threshold? Should we follow the usual 

convention in statistics and label a trend as significant only if 

it would be expected to occur by chance fewer than 5 times 

in 100 trials? Probably not—from a conservation standpoint, 

we may prefer to err on the safe side, treating trends of lower 

magnitude as probably unnatural and requiring attention. 

Also, there is a built-in tendency for the distributions depicted 

in figures 13, 14, and 15 to be wider than they are in nature, 

because no effect of density dependence is included in the 

model. In that sense, this application of the MATRIX program 

can be viewed as “non-alarmist” – the possibility of accepting 

a trend as normal, when in fact it is not, is more likely than 

deciding that a trend requires action, when in fact it reflects 

normal population dynamics. As always, the conclusions one 

derives from modeling are only as sound as one’s assumptions 

and inputs. The approach described here may be applied with 

increasing confidence as our knowledge of the means and 

variability of vital parameters, including their responses to 

population density, increases for species of concern – such as 

Marbled Murrelets—through further research.

To conclude this section on demographic models, we 

offer the following perspective on the relevance of models 

that pay only indirect homage to habitat availability to 

conservation issues. If a population is declining, not because 

of relatively subtle changes in birth and death rates of the 

kind considered here, but rather because some portion of its 

living space is being modified by humans or nature so as 

to become wholly unsuitable for reproduction or survival, 

then the population will decline in direct proportion to the 

amount of habitat that becomes unusable. In that situation, no 

mathematical models are really necessary to understand the 

process.

64 Status Review of the Marbled Murrelet in Alaska and British Columbia
Figure 13. Expected distributions of trends over 10-, 20-, and 30-year intervals arising stochastically 

from interannual variation in the fecundity and survival of Marbled Murrelets, as modeled in program 

MATRIX.

Seasonal independence Seasonal concordance

% Change

120150180

306090

0

-90-60-30

10-YEAR INTERVALS

Frequency 10000

8000

6000

4000

2000

0

% Change

120150180

306090

0

-90-60-30

20-YEAR INTERVALS

Frequency 10000

8000

6000

4000

2000

0

% Change

120150180

306090

0

-90-60-30

30-YEAR INTERVALS

Frequency 10000

8000

6000

4000

2000

0

SD = 22.2

Mean = 0.1

N = 46325

% Change

120150180

306090

0

-90-60-30

10-YEAR INTERVALS

Frequency 5000

4000

3000

2000

1000

0

SD = 30.1

Mean = 1.0

N = 29710

SD = 32.2

Mean = 0

N = 46325

% Change

120150180

306090

0

-90-60-30

20-YEAR INTERVALS

Frequency 5000

4000

3000

2000

1000

0

SD = 42.9

Mean = 1.2

N = 29710

SD = 40.3

Mean = -0.3

N = 46325

% Change

120150180

306090

0

-90-60-30

30-YEAR INTERVALS

Frequency 5000

4000

3000

2000

1000

0

SD = 52.7

Mean = 0.8

N = 29710

Seasonal independence Seasonal concordance

% Change

120150180

306090

0

-90-60-30

10-YEAR INTERVALS

Frequency 10000

8000

6000

4000

2000

0

% Change

120150180

306090

0

-90-60-30

20-YEAR INTERVALS

Frequency 10000

8000

6000

4000

2000

0

% Change

120150180

306090

0

-90-60-30

30-YEAR INTERVALS

Frequency 10000

8000

6000

4000

2000

0

SD = 22.2

Mean = 0.1

N = 46325

% Change

120150180

306090

0

-90-60-30

10-YEAR INTERVALS

Frequency 5000

4000

3000

2000

1000

0

SD = 30.1

Mean = 1.0

N = 29710

% Change

120150180

306090

0

-90-60-30

10-YEAR INTERVALS

Frequency 5000

4000

3000

2000

1000

0

SD = 30.1

Mean = 1.0

N = 29710

SD = 32.2

Mean = 0

N = 46325

% Change

120150180

306090

0

-90-60-30

20-YEAR INTERVALS

Frequency 5000

4000

3000

2000

1000

0

SD = 42.9

Mean = 1.2

N = 29710

% Change

120150180

306090

0

-90-60-30

20-YEAR INTERVALS

Frequency 5000

4000

3000

2000

1000

0

SD = 42.9

Mean = 1.2

N = 29710

SD = 40.3

Mean = -0.3

N = 46325

% Change

120150180

306090

0

-90-60-30

30-YEAR INTERVALS

Frequency 5000

4000

3000

2000

1000

0

SD = 52.7

Mean = 0.8

N = 29710

% Change

120150180

306090

0

-90-60-30

30-YEAR INTERVALS

Frequency 5000

4000

3000

2000

1000

0

SD = 52.7

Mean = 0.8

N = 29710

Demographics and Population Dynamics 65
Seasonal independence Seasonal concordance

% Change

120150180210240270300330360

306090

0

-90-60-30

10-YEAR INTERVALS

Frequency

12000

10000

8000

6000

4000

2000

0

SD = 37.6

Mean = 0.6

N = 84055

% Change

120150180210240270300330

360

306090

0

-90-60-30

10-YEAR INTERVALS

Frequency

5000

4000

3000

2000

1000

0

SD = 54.2

Mean = 3.7

N = 48849

% Change

120150180210240

270300330360

306090

0

-90-60-30

20-YEAR INTERVALS

Frequency

12000

10000

8000

6000

4000

2000

0

SD = 54.0

Mean = -0.2

N =84055

% Change

120150180210240270300

330360

306090

0

-90-60-30

20-YEAR INTERVALS

Frequency

5000

4000

3000

2000

1000

0

SD = 78.1

Mean = 4.4

N = 48849

% Change

120150180210240270300330360

306090

0

-90-60-30

30-YEAR INTERVALS

Frequency

12000

10000

8000

6000

4000

2000

0

SD = 67.3

Mean = -1.8

N = 84055

% Change

120150

180210240

270300330

360

306090

0

-90-60-30

30-YEAR INTERVALS

Frequency

5000

4000

3000

2000

1000

0

SD = 102.9

Mean = 3.5

N = 48849

Seasonal independence Seasonal concordance

% Change

120150180210240270300330360

306090

0

-90-60-30

10-YEAR INTERVALS

Frequency

12000

10000

8000

6000

4000

2000

0

SD = 37.6

Mean = 0.6

N = 84055

% Change

120150180210240270300330

360

306090

0

-90-60-30

10-YEAR INTERVALS

Frequency

5000

4000

3000

2000

1000

0

SD = 54.2

Mean = 3.7

N = 48849

% Change

120150180210240

270300330360

306090

0

-90-60-30

20-YEAR INTERVALS

Frequency

12000

10000

8000

6000

4000

2000

0

SD = 54.0

Mean = -0.2

N =84055

% Change

120150180210240

270300330360

306090

0

-90-60-30

20-YEAR INTERVALS

Frequency

12000

10000

8000

6000

4000

2000

0

SD = 54.0

Mean = -0.2

N =84055

% Change

120150180210240270300

330360

306090

0

-90-60-30

20-YEAR INTERVALS

Frequency

5000

4000

3000

2000

1000

0

SD = 78.1

Mean = 4.4

N = 48849

% Change

120150180210240270300

330360

306090

0

-90-60-30

20-YEAR INTERVALS

Frequency

5000

4000

3000

2000

1000

0

SD = 78.1

Mean = 4.4

N = 48849

% Change

120150180210240270300330360

306090

0

-90-60-30

30-YEAR INTERVALS

Frequency

12000

10000

8000

6000

4000

2000

0

SD = 67.3

Mean = -1.8

N = 84055

% Change

120150180210240270300330360

306090

0

-90-60-30

30-YEAR INTERVALS

Frequency

12000

10000

8000

6000

4000

2000

0

SD = 67.3

Mean = -1.8

N = 84055

% Change

120150

180210240

270300330

360

306090

0

-90-60-30

30-YEAR INTERVALS

Frequency

5000

4000

3000

2000

1000

0

SD = 102.9

Mean = 3.5

N = 48849

% Change

120150

180210240

270300330

360

306090

0

-90-60-30

30-YEAR INTERVALS

Frequency

5000

4000

3000

2000

1000

0

SD = 102.9

Mean = 3.5

N = 48849

Figure 14. Expected distributions of trends arising stochastically over 10-, 20-, and 30-year intervals 

when interannual variation in fecundity and survival is comparatively high.

66 Status Review of the Marbled Murrelet in Alaska and British Columbia
Seasonal independence Seasonal concordance

% Change

15304560

0

-90-75-60-45-30-15

10-YEAR INTERVALS

Frequency

50000

40000

30000

20000

10000

0

SD = 8.6

Mean = 0.1

N = 413134

% Change

105

153045607590

0

-90-75-60-45-30-15

10-YEAR INTERVALS

Frequency

40000

30000

20000

10000

0

SD = 11.8

Mean = 0.1

N = 214151

% Change

15304560

0

-90-75-60-45-30-15

20-YEAR INTERVALS

Frequency

50000

40000

30000

20000

10000

0

SD = 12.2

Mean = 0.1

N = 413134

% Change

15304560

0

-90-75-60-45-30

-15

30-YEAR INTERVALS

Frequency

50000

40000

30000

20000

10000

0

SD = 15.0

Mean = 0.1

N = 413134

% Change

105

153045607590

0

-90-75-60-45-30-15

20-YEAR INTERVALS

Frequency

40000

30000

20000

10000

0

SD = 16.9

Mean = 0.2

N = 214151

% Change

105

153045607590

0

-90-75-60-45-30-15

30-YEAR INTERVALS

Frequency

40000

30000

20000

10000

0

SD = 21.0

Mean = 0.3

N = 214151

Seasonal independence Seasonal concordance

% Change

15304560

0

-90-75-60-45-30-15

10-YEAR INTERVALS

Frequency

50000

40000

30000

20000

10000

0

SD = 8.6

Mean = 0.1

N = 413134

% Change

105

153045607590

0

-90-75-60-45-30-15

10-YEAR INTERVALS

Frequency

40000

30000

20000

10000

0

SD = 11.8

Mean = 0.1

N = 214151

% Change

15304560

0

-90-75-60-45-30-15

20-YEAR INTERVALS

Frequency

50000

40000

30000

20000

10000

0

SD = 12.2

Mean = 0.1

N = 413134

% Change

15304560

0

-90-75-60-45-30-15

20-YEAR INTERVALS

Frequency

50000

40000

30000

20000

10000

0

SD = 12.2

Mean = 0.1

N = 413134

% Change

15304560

0

-90-75-60-45-30

-15

30-YEAR INTERVALS

Frequency

50000

40000

30000

20000

10000

0

SD = 15.0

Mean = 0.1

N = 413134

% Change

15304560

0

-90-75-60-45-30

-15

30-YEAR INTERVALS

Frequency

50000

40000

30000

20000

10000

0

SD = 15.0

Mean = 0.1

N = 413134

% Change

105

153045607590

0

-90-75-60-45-30-15

20-YEAR INTERVALS

Frequency

40000

30000

20000

10000

0

SD = 16.9

Mean = 0.2

N = 214151

% Change

105

153045607590

0

-90-75-60-45-30-15

20-YEAR INTERVALS

Frequency

40000

30000

20000

10000

0

SD = 16.9

Mean = 0.2

N = 214151

% Change

105

153045607590

0

-90-75-60-45-30-15

30-YEAR INTERVALS

Frequency

40000

30000

20000

10000

0

SD = 21.0

Mean = 0.3

N = 214151

% Change

105

153045607590

0

-90-75-60-45-30-15

30-YEAR INTERVALS

Frequency

40000

30000

20000

10000

0

SD = 21.0

Mean = 0.3

N = 214151

Figure 15. Expected distributions of trends arising stochastically over 10-, 20-, and 30-year intervals 

when interannual variation in fecundity and survival is comparatively low.

Demographics and Population Dynamics 67
Marine Habitat: Characteristics and 

Threats

Marbled Murrelets spend most of their lives in the coastal 

marine environment, although they will feed occasionally 

in freshwater lakes near suitable nesting habitat (Carter 

and Sealy, 1986; Hobson, 1990). Our knowledge of the 

marine habitat of this species, though limited, has increased 

dramatically during the past few decades. In this section, we 

first describe the general features of marine habitats used 

by Marbled Murrelets in Alaska and British Columbia. We 

then consider the potential effects of climate-driven changes 

in marine food webs on murrelet prey species. Finally, this 

chapter examines anthropogenic threats to murrelets in their 

marine habitats, including oil pollution, incidental take in 

fisheries, effects of commercial fishing on their prey, vessel 

disturbance, and research activities.

Characteristics of Marine Habitats Used by 

Marbled Murrelets

The marine range of the Marbled Murrelet is primarily 

in coastal waters of southern Alaska, British Columbia, 

and Washington, Oregon, and California. In Alaska, these 

marine waters include the Aleutian Islands (from Attu to 

Unalaska islands), the south side of the Alaska Peninsula, the 

Kodiak Archipelago, Cook Inlet, Prince William Sound, and 

throughout Southeast Alaska (Piatt and Naslund, 1995). Small 

numbers of Marbled Murrelets also occur on the southeast 

Bering Sea shelf and along the north side of the Alaska 

Peninsula to Bristol Bay. Two major offshore current systems 

affect marine habitats of the Marbled Murrelet: (1) the Alaska 

Current/Alaska Stream (from northern British Columbia to 

the western Aleutian Islands); and (2) the California Current 

(from southern British Columbia to California). On the north 

side of the eastern Aleutian Islands, the smaller Aleutian North 

Slope Current acts as an extension of the Alaska Stream in the 

eastern Bering Sea. 

Two major atmospheric pressure systems, the North 

Pacific High and the Aleutian Low, create major currents in 

the North Pacific Ocean (Weingartner, 2005). The Aleutian 

Low, strongest between September and January, creates 

a counter-clockwise current flow in the Gulf of Alaska, 

dominated by the Alaska Stream which follows the shelf-edge 

westward. This flow, combined with the onshore movement 

of water caused by the Coriolis Force, causes downwelling 

along the northern Gulf coasts of Alaska (Weingartner, 

2005). Storms generated by the Aleutian Low result in high 

precipitation in the coastal mountains bordering the Gulf 

of Alaska (Mundy and Olsson, 2005), which in turn create 

conditions suitable for the coastal rainforests of this region. 

Outflow from the numerous coastal rivers feeds and defines 

the Alaska Coastal Current (Weingartner, 2005), which flows 

north and then west along the inner third of the continental 

shelf from northern British Columbia to about Samalga Pass 

in the eastern Aleutian Islands (Mundy and Olsson, 2005). 

The current is highly productive in spring and summer, and 

delivers plankton to nearshore waters, inlets, and fjords. 

Waters to the west of Samalga Pass are more oceanic and 

more strongly influenced nearshore by the Alaska and 

Aleutian North Slope Currents (Weingartner, 2005). South of 

the Gulf of Alaska, the North Pacific High creates clockwise 

winds and a current that travels south along the coasts of 

British Columbia, and Washington, Oregon, and California 

(Freeland, 1992; Benson and Trites, 2002), and winds 

produce upwelling along the coast (Freeland, 1992). 

The coasts of southern Alaska and British Columbia 

have consistently high rainfall throughout most of the year 

(Weingartner, 2005). In Washington, Oregon, and California, 

rainfall becomes more seasonal with decreasing latitude. 

Major ENSO events can dramatically affect marine habitats 

used by murrelets in Washington, Oregon, and California 

(McShane and others, 2004). Every 4 to 7 years, warm water 

flows along the coast and changes the depth of the mixed 

layer as well as local weather. During ENSO events, many 

seabirds experience reduced reproduction if they reproduce 

at all (Ainley and others, 1995b). Fewer Marbled Murrelets 

are seen at-sea and inland during events, suggesting that 

reproductive success is reduced to some extent (Ainley and 

others, 1995a; Burger, 1995b, 2000; Strong and others, 

1995). However, murrelet productivity may be impacted less 

than many other seabirds, because they can use prey that 

are less affected by ENSO conditions (Kelson and others, 

1995; U.S. Fish and Wildlife Service, 1997). Timing of 

major ENSOs can vary by year between central-northern 

and southern parts of the California Current. Major ENSOs 

do not appear to project into the Alaska Current System 

nor have much effect on murrelets there (Piatt and Naslund, 

1995), however, the impact of such periodic climatic-driven 

events on murrelets remains largely unknown.

Meso-Scale Characteristics

With respect to seabirds and their prey, oceanic 

processes at the meso-scale are defined as occurring spatially 

at 100–1,000 km (Hunt and Schneider, 1987). This spatial 

scale is used here to define ‘regions’ of murrelet populations 

within Alaska and British Columbia. Marine habitat varies 

considerably among regions, and the distribution of murrelets 

relative to shoreline, water depth, and other physical 

characteristics also varies among regions. For example, 

Marbled Murrelets in the Aleutian Islands use protected 

waters in large bays and inlets around the islands but do not 

use deeper waters in major passes between islands. Most 

68 Status Review of the Marbled Murrelet in Alaska and British Columbia
murrelets occur in nearshore waters, generally within 5 km 

of shore (Piatt and others, 2005; Romano and others, 2005a). 

The shelf break is very narrow along the Aleutians and water 

surrounding the islands remains ice-free year-round. Water 

flowing between and around islands creates tidal fronts 

and currents that create upwelling, water mixing, and high 

productivity. In contrast, the marine habitat of the northern 

Gulf of Alaska shelf (including Prince William Sound), 

Southeast Alaska, and British Columbia is extremely complex. 

Numerous forested islands, fjords, inlets, and estuaries 

all provide sheltered, stratified coastal waters favored by 

murrelets. Most murrelets occur within 5–10 km of shore in 

these regions (Burger, 1995b; Piatt and Naslund, 1995). 

Between Prince William Sound and Southeast Alaska, 

there are only a few large bays and a large shallow shelf, and 

Marbled Murrelets were found along exposed coasts out to 

at least 5 km (M. Kissling, U.S. Fish and Wildlife Service, 

unpub. data, 2003). However, Marbled Murrelets have been 

found as much as 300 km from the coast in the central Gulf of 

Alaska during summer and winter (Piatt and Naslund, 1995; 

North Pacific Pelagic Seabird Database, 2005), and it may be 

that some post-breeding birds move to offshore waters during 

winter (Nelson, 1997). A modeling exercise using only marine 

environmental parameters for British Columbia murrelet 

distribution found murrelets associated with sandy substrates, 

estuaries, and cooler sea temperatures (Yen and others, 

2004a). South of British Columbia and along the outer coasts 

of Washington, Oregon, and California, marine habitats used 

by Marbled Murrelets are more homogeneous. There are no 

major islands, relatively few coastal rocks, and little shallow, 

nearshore water. Murrelets tend to use nearshore waters and 

numbers decline rapidly with distance from shore. 

A description of murrelet use of marine habitats must 

consider the distribution of their nesting habitat, because 

throughout most of their range, Marbled Murrelets occur 

in waters adjacent to old-growth forest (Piatt and Naslund, 

1995; Nelson, 1997; Miller and others, 2002). For example, 

in California, the most important variable influencing 

Marbled Murrelet abundance at-sea was proximity to large, 

unfragmented tracts of old-growth conifers bordered by 

second-growth forest (Miller and others, 2002). In Alaska, 

most (about 95 percent) murrelets are found in association 

with large coastal old-growth forests in Southeast Alaska, 

Prince William Sound, and Kodiak Island (Piatt and Ford, 

1993). At a smaller scale, however, in Alaska and British 

Columbia abundance at-sea is often not well correlated with 

adjacent terrestrial breeding habitat (Marks and others, 1995; 

Speckman, 1996; Whitworth and others, 2000; Burger, 2002). 

Small-Scale Characteristics

Throughout much of their range, most Marbled Murrelets 

are observed during summer within 5 km of shore and in 

shallow (less than 60 m) water (Nelson, 1997; Day and others, 

2003). However, in Cook Inlet (Agler and others, 1998) and 

Kachemak Bay (Kuletz, U.S. Fish and Wildlife Service, 

unpub. data, 2006), Marbled Murrelets are often found 5–30 

km from shore (fig. 16) and in water greater than 100 m deep. 

In Southeast Alaska and Prince William Sound, murrelets 

are more closely associated with the shoreline, but murrelets 

also can be found in waters 100–600 m deep in some bays 

and fjords (Agler and others, 1998; Kuletz, 2005). But for 

the most part, Marbled Murrelets in Alaska use sheltered 

waters in bays, fjords, leeward sides of islands, and island 

passes (Piatt and Naslund, 1995; Kuletz, 2005). In British 

Columbia, similar marine habitats are used, and murrelets also 

are found in exposed or channel habitats (Sealy and Carter, 

1984; Savard and Lemon, 1992). Within British Columbia, 

murrelet numbers in the protected Strait of Georgia region 

(i.e., east coast of Vancouver Island and adjacent mainland 

British Columbia) are low compared to other similar areas, 

which may reflect removal of most old-growth forests around 

the Strait. 

From British Columbia to California, feeding 

aggregations of murrelets tend to occur in similar areas 

over multiple years, and their occurrence may be related to 

persistent local prey availability (Carter, 1984; Sealy and 

Carter, 1984; Carter and Sealy, 1990). There is some evidence 

that murrelets have some forage site fidelity and stay more 

or less within ‘home ranges’ (Lank and others, 2003; Kuletz, 

2005). In Prince William Sound, the minimum-area polygons 

of 33 radio-tagged Marbled Murrelets averaged 143 ± 37 km2

(counting the nest sites), but most relocations of individuals 

on the water were usually within a 5-km radius (Kuletz, 

2005). Consistent use of a bay also has been recorded for 

radio-tagged Marbled Murrelets in Southeast Alaska (Quinlan 

and Hughes, 1992) and in British Columbia (Hull and others, 

2001; Lougheed and others, 2002a). The evidence for site 

fidelity shown by murrelets in these studies suggests that 

familiarity with an area and learned behavior may influence 

the use of certain marine habitats.

The characteristics of Marbled Murrelet foraging habitat 

appear to vary depending on location. In general, Marbled 

Murrelets in Alaska were considered to be most abundant in 

cooler water, and in stratified, rather than strongly tidallymixed, coastal water (Piatt, 1994; Piatt and Naslund, 1995). 

Marine Habitat: Characteristics and Threats 69
Figure 16. Brachyramphus murrelet distribution in lower Cook Inlet in June 1993, relative to salmon fishing 

districts in the Cook Inlet area.

However, murrelets also are often associated with areas of 

upwelling created by underwater shelves, mouths of bays, and 

island passes and wakes, which may serve to aggregate prey 

(Carter, 1984; Sealy and Carter, 1984; Day and Nigro, 2000; 

Day and others, 2003; Kuletz, 2005). Murrelets are associated 

with sand and gravel substrate, also habitat of the Pacific sand 

lance, an important prey item (Carter, 1984; Burger, 1995b; 

Speckman and others, 2000). There is evidence that juvenile 

Marbled Murrelets have a more limited range of habitats, 

at least in the first weeks or months following fledging 

(Andersen and Beissinger, 1995; Kuletz and Kendall, 1998; 

Speckman and others, 2000). Juveniles tend to be found close 

to shore in well protected, shallow waters or in nearshore areas 

with kelp beds (Kuletz and Piatt, 1999). 

In Alaska, Marbled Murrelets are often found in waters 

adjacent to glaciers, where they co-occur with Kittlitz’s 

Murrelets (Agler and others, 1998; Day and others, 2003; 

Kuletz and others, 2003b; Robards and others, 2003), but 

they are less likely to be associated with glaciers in British 

Columbia (Burger, 2002; Yen and others, 2004a). In Barkley 

Sound, British Columbia, murrelets aggregated in traditional 

juvenile herring rearing areas that were near spawning areas 

(Carter, 1984), although murrelets generally are not found in 

other herring spawning areas of British Columbia (Yen and 

others, 2004a). 

Use of foraging habitat may vary temporally. Carter and 

Sealy (1990) suggested that murrelets forage in productive 

waters at considerable distance from breeding sites in morning 

hours, but later shift to feeding areas that are closer to nest 

sites where they can capture prey for delivery to chicks (Carter 

and Sealy, 1990), and evidence was found for this pattern of 

behavior in Southeast Alaska (Speckman and others, 2000) 

and British Columbia (Bradley, 2002; Rodway and others, 

1995). Murrelets may choose some feeding areas where they 

can feed on fish that migrate vertically to the surface at dawn 

or dusk (Speckman and others, 2000; Kuletz, 2005). Ostrand 

and others (1997) noted changes in the depth of water and 

distance from shore used by murrelets in apparent response to 

changes in habitat use by their prey. Major changes in murrelet 

habitat use occur after the breeding season is completed, 

although the characteristics of the autumn and winter habitats 

are not well known. Details on the seasonal dispersal of 

murrelets were addressed under the section, “Breeding 

Biology.”

70 Status Review of the Marbled Murrelet in Alaska and British Columbia
Marine Ecosystem Change

The abundance of forage fishes is known to fluctuate 

in response to oceanographic conditions such as water 

temperature (Chavez and others, 2003; Rose, 2005), salinity 

and depth (Abookire and Piatt, 2005), daylight (Beamish and 

others, 1999), tidal influences (Zamon, 2003), and frontal 

mixing (Maravelias and Reid, 1997). For example, Speckman 

and others (2005) found that turbidity, temperature, salinity 

and interannual variability in marine climate (e.g., ENSO and 

La Niña events) played an important role in structuring forage 

fish communities in lower Cook Inlet. Similarly, the seabird 

community reflected the physical and biological structure of 

the Cook Inlet ecosystem (Speckman and others, 2005). 

Large-scale shifts in marine climate have been linked 

to biological regime shifts (Benson and Trites, 2002; Chavez 

and others, 2003) that resulted in changes in the abundance 

of forage fish important to Marbled Murrelets and other 

seabirds in the North Pacific (Anderson and Piatt, 1999). The 

1977–78 regime shift was driven by decadal-scale changes 

in atmospheric forcing of the Aleutian Low, which affected 

current flow and ocean temperatures (Francis and others, 

1998). Coincident with fluctuations in seawater temperatures 

and changes in primary and secondary productivity, 

populations of small forage species (e.g., capelin, shrimp, 

and Pacific sandfish) declined after the late 1970s, whereas 

populations of large predatory fish (walleye pollock [Theragra 

chalcogramma], Pacific cod [Gadus macrocephalus], and 

flatfish) increased (Anderson and Piatt, 1999). Marbled 

Murrelets have a fairly generalist diet and show an ability to 

switch prey when the availability of some prey changes (e.g., 

Ostrand and others, 2004). Nontheless, there is evidence that 

changes in prey affect murrelet distribution and productivity 

(Peery and others, 2004b; Becker and Beissinger, 2005). 

Population and diet data from a variety of marine birds 

suggest that an ecosystem change occurred in Prince William 

Sound in the 1980s that negatively affected fish-eating birds 

(DeGange, 1996; Kuletz and others, 1997; Agler and others, 

1999). Marbled Murrelets ate mostly sand lance during the late 

1970s, whereas they started to feed almost entirely on lipidpoor gadids from 1989 to 1991, with capelin disappearing 

as a dietary item (DeGange, 1996; Kuletz and others, 1997; 

table 3). Linked with these changes in diet, Marbled Murrelets 

and other piscivorous seabird populations declined, although 

not all the declines were significant (Klosiewski and Laing, 

1994; Agler and others, 1999). However, mortality from 

oil spills and fisheries also occurred during these decades 

(Carter and Kuletz, 1995; Carter and others, 1995; Piatt and 

Naslund, 1995; see below). Recent data indicate that Marbled 

Murrelets were feeding primarily on herring and sand lance 

in the late 1990s (Kuletz and others, 1997; Day and Nigro, 

2000; appendix A), and suggest that ecological conditions in 

Prince William Sound may have changed to a more productive 

environment for fish-eating birds. 

A shift in diet also appears to have occurred along the 

Alaska Peninsula and around Kodiak Island. In these areas, 

Marbled Murrelets collected in the 1970s–1980s during 

summer were feeding largely on capelin (Piatt and Anderson, 

1996; appendix A). In contrast, capelin were nearly absent 

in Marbled Murrelets collected in the same areas during the 

1990s (appendix A). 

The effects of marine ecosystem change on Marbled 

Murrelets also have been observed in British Columbia, 

with warmer ocean temperatures associated with the ENSO 

negatively affecting Marbled Murrelet reproduction (Burger, 

2000; Becker and Beissinger, 2003). More recently, Becker 

and Beissinger (2005) have demonstrated a large change in 

the trophic level and diet of Marbled Murrelets in California 

over the last century, with birds shifting to lower trophic level 

prey items (such as krill, rockfish, and sand lance) in response 

to a decrease in the abundance of higher trophic level prey 

species associated with declines in fisheries. High predation 

rates and limited nesting habitat also likely contribute to 

poor reproduction in central California (Hamer and Nelson, 

1995; Nelson and Hamer, 1995), and more work is needed 

to assess fully the reasons for their poor reproduction. These 

studies highlight the important effects that changes in marine 

community composition (whether due to over-fishing or 

natural variation in the marine environment and patterns 

of upwelling) can have on the prey base and demographic 

response of Marbled Murrelets.

Although there are possible links between climate and 

murrelet reproductive success or population trends, we do not 

know the mechanisms involved. There is, however, growing 

understanding of climate effects on the lower trophic levels on 

which murrelets depend. 

A major reorganization of the marine food web occurred 

in the Gulf of Alaska during the decade following a 1977 

regime shift (Hollowed and Wooster, 1995; Hare and Mantua, 

2000; Hollowed and others, 2001). The 1980s to 1990s 

is approximately the period when murrelet populations 

showed evidence of declines (this volume), which supports 

the hypothesis that changes in the marine environment have 

been one component of the conditions leading to murrelet 

declines (Burger, 2000; Peery and others, 2004b; Becker and 

Beissinger, 2005; Kuletz, 2005). However, climate-driven 

shifts in marine food webs are not new. In the North Pacific, 

regime shifts may have occurred in 1925, 1947, 1977, and 

1989, with a weaker shift in 1998–99 in the Gulf of Alaska 

(King, 2005). Paleo-ecological records suggest that the 

duration of regime shifts have diminished from 50 –100 years 

to 20–30 years (in historical times), and more recently to 10 

years. Thus, it is possible that changes in the North Pacific 

climate and ocean ecosystems have increased in frequency 

(King, 2005), which could stress even generalist foragers such 

as the Marbled Murrelet. 

Marine Habitat: Characteristics and Threats 71
Most of the fish species used by Marbled Murrelets (this 

volume) feed on macro-zooplankton, primarily copepods and 

euphausiids, and thus are linked to environmental fluctuations 

that influence zooplankton abundance, distribution, and 

species composition (Zebdi and Collie, 1995; Williams and 

Quinn II, 2000). In the Gulf of Alaska, zooplankton timing, 

abundance, and community composition has changed on a 

decadal scale, with apparent links to changes in ocean and 

climate conditions (Mackas and others 1998, 2001; Boldt and 

others, 2005). Concurrently, fish communities have changed 

(McGowan and others, 1998), followed by changes in seabird 

prey species, notably after the 1970s (Piatt and Anderson, 

1996; Anderson and Piatt, 1999). 

One of the most important prey for murrelets in British 

Columbia and Alaska, particularly for birds raising chicks, is 

Pacific herring. Juvenile herring feed on copepods, and after 

their first year, they eat more euphausiids. Survival of juvenile 

herring depends on their ability to acquire enough food during 

summer and autumn to survive their first winter (Foy and Paul, 

1999). Warm water and poor body condition from insufficient 

food can facilitate the spread of diseases that may be limiting 

recovery of the herring population in Prince William Sound 

(Marty and others, 1998). Warmer water temperatures between 

the 1970s and 1990s also may have been responsible for 

declines in capelin in the Gulf of Alaska (Anderson and Piatt, 

1999) and the subsequent disappearance of capelin from the 

diet of Marbled Murrelets (Piatt and Anderson, 1996). In 

contrast, walleye pollock abundance increased in the Gulf 

of Alaska during this period (Boldt and others, 2005) and 

also in the diet of murrelets. Although adult murrelets will 

eat juvenile pollock, they select higher quality prey for their 

chicks (Kuletz, 2005). 

There are substantial differences among forage fishes 

in the fat content, energy density, and quality of forage 

fish (Anthony and others, 2000). In addition, there can be 

differences in energy density within the same fish species, 

depending on sex, breeding condition, season, location, or 

annual changes in environmental conditions (Robards and 

others, 1999a; Anthony and others, 2000). As a result, birds 

provisioning their chicks may show delivery rates and prey 

species selection similar to historical records, yet show 

lower chick growth and survival, such as occurred in the 

North Atlantic (Wanless and others, 2005). Providing highquality prey has been shown to increase chick growth and 

improve fledging success in seabirds in Prince William Sound 

(Golet and others, 2000; Suryan and others, 2002) and under 

laboratory conditions (Romano and others, 2006). 

Prey quality may be more important than quantity for 

chick growth in seabirds (Kitaysky and others, 1999; Wanless 

and others, 2005), and thus the body condition of forage fish, 

as well as their abundance, could impact murrelet productivity. 

For example, Kuletz (2005) used published energetic values 

to estimate the number of fish deliveries required daily to 

raise a Marbled Murrelet chick. The daily rate varied from 

approximately two 1-year old herring to nine male capelin. 

Over the course of the 27–40 day nestling period (with 

presumably longer fledging periods where food is more 

scarce), estimated total fish deliveries could range from less 

than 60 herring to more than 250 capelin to raise a chick. 

Hypothetically, if a murrelet pair had access to high-quality 

prey while raising their chick, they would work less to capture 

and deliver prey, risk fewer trips inland past avian predators, 

and be more likely to fledge the chick by reducing exposure to 

nest predators. 

In California, murrelets have been shown to alter 

their foraging locations in response to ocean conditions 

(Becker and Beissinger, 2003), and they spent more time 

foraging when food availability was low (Peery and others, 

2004b). The murrelet’s ability to adapt to changes in ocean 

conditions appeared to have costs to reproductive success 

(Peery and others, 2004b). There also may be costs to adult 

body condition. In Prince William Sound, during a period of 

population decline, mean adult murrelet body mass declined 

between 1977 and 1999 (Kuletz, 2005).

Threats in Marine Habitats

Anthropogenic activities that could affect Marbled 

Murrelets in the marine environment include oil and other 

contaminant pollution, incidental take in commercial fisheries, 

secondary or indirect effects of commercial fisheries (such as 

displacement or impacts on murrelet prey), vessel disturbance, 

and research activities. Here we review these threats using 

available information from various sources. Anthropogenic 

effects may not drive large-scale population changes in 

murrelets, but their cumulative effects, in conjunction with 

natural events (as discussed above), could be significant. We 

attempted to be thorough in evaluating anthropogenic threats, 

and the amount of information provided on each topic does 

not necessarily reflect the potential impact on the murrelet 

population. 

Oil Pollution

Alaska

Marbled Murrelets are considered highly vulnerable to 

oil spills in Alaska (King and Sanger, 1979) and the Pacific 

Northwest (Carter and Kuletz, 1995), because they remain 

on the sea for most of their lives, forage by diving, and 

prefer nearshore habitats (usually less than 5 km offshore). 

Throughout the range of the Marbled Murrelet, oil pollution 

has been and remains a significant problem (Carter and 

Kuletz, 1995; McShane and others, 2004), and this has been 

particularly evident in Alaska. The 1989 EVOS was the 

72 Status Review of the Marbled Murrelet in Alaska and British Columbia
single largest mortality event for Marbled Murrelets, killing 

a minimum of 8,400 murrelets (Carter and Kuletz, 1995; 

Kuletz, 1996). In addition to catastrophic events, smaller spills 

(i.e., chronic oil pollution) frequently kill large numbers of 

murrelets in Washington, Oregon, and California (McShane 

and others, 2004). Based on reports from regions with larger 

human populations, it is possible that tens to hundreds of 

murrelets per year are killed in Alaska and British Columbia 

by chronic oil pollution without documentation. Where 

rehabilitation of oiled murrelets has been attempted, there was 

little success. During the EVOS, only 3 of 33 treated Marbled 

Murrelets survived to be released (Carter and Kuletz, 1995).

In the cold waters of Alaska, even small amounts of oil 

can cause mortality or metabolic problems for seabirds (Nero 

and Associates, Inc., 1987). During the EVOS, Ford and others 

(1996) found that about 25 percent of the small alcid carcasses 

retrieved (primarily murrelets) had no discernable oiling on 

their bodies. Although crude oil is most often associated 

with seabird mortality from spills, diesel also is a common 

contaminant (table 21). Diesel is lighter and disperses more 

quickly than crude oil, and there is no evidence that its 

effect on plumage and thermoregulation on seabirds is less 

problematic. 

Exxon Valdez Oil Spill

The EVOS began with the grounding of the oil tanker 

in northwestern Prince William Sound on March 24, 1989 

and release of 11 million gallons of crude oil. Over the next 

2 months oil spread southwest with prevailing currents, 

covering 30,000 km2 of coastal and offshore waters (Piatt and 

others, 1990). Alcids were the avian taxon most affected by 

the spill, and Marbled Murrelets had the highest mortality 

among six species of small alcids that were identified from 

carcass recoveries (Piatt and others, 1990; Ford and others, 

1991, 1996). The EVOS occurred when most murrelets had 

not yet entered Prince William Sound for the breeding season, 

and thus estimated mortality for regions farther south were 

actually higher than for Prince William Sound (table 22). 

Estimating mortality of Marbled Murrelets was 

complicated by the large number of unidentified murrelets 

and other small alcids, but the minimum estimate of direct 

mortality was 8,400 Brachyramphus murrelets, most of 

which were Marbled Murrelets (table 22). This represented 

approximately 7 percent of the known population in the spill 

zone (Kuletz, 1996). However, based on re-examination of 

a sample of carcasses of murrelets and ‘unidentified’ small 

alcids, larger numbers of Marbled Murrelet carcasses were 

identified (Ford and others, 1991, 1996). Using revised 

carcass counts, murrelet mortality was 10,000–22,000, with a 

best approximation of 12,800–14,800 (Kuletz, 1996). These 

latter estimates represented 7 to 12 percent of the murrelet 

population in the spill zone. Details of the estimates of 

murrelet mortality and subsequent damages are available in 

Carter and Kuletz (1995) and Kuletz (1996).

Windy Bay Oil Spill

Although relatively small, the Windy Bay oil spill was 

the largest spill in Prince William Sound since the EVOS, 

and provided information on the types of risks posed by small 

spills. On August 4, 2001,the fishing tender F/V Windy Bay

struck a reef and sank in northern Prince William Sound. The 

vessel held 35,000 gal of diesel fuel, 100 gal of lube oil, and 

300–500 gal of hydraulic fluid. An estimated 60 percent of the 

fuel evaporated and 11,000 gal were recovered by response 

operations. Light sheen was observed over approximately 

40 mi2. By August 9, approximately 10–20 gal of diesel per 

Substance Vessel spills Other sources

Number Gallons Pounds Number Gallons Pounds

Agricultural Chemical 14 1,530 25,008,957 132 1,210 303,332

Chemical—Other 10 37 179 221 131,710 20,822

Fuel—Diesel, Gasoline, Aviation 1,145 245,040 649 113,573 502

Fuel—Other 9 148 43 22,213 212

Oil—Crude 24 8,924 231 23,361

Oil—Marine, Other 528 589,026 586 9,914

Other or Unknown 90 45,182 44,000 331 155,380 46,078

Water—Oil, Refinery, Ballast 11 79 119 174,172

Total 1,831 889,966 25,053,136 2,312 631,533 370,946

Table 21. Summary of spills between 1979 and 2005 in coastal Alaska, by substance category.

[Data from Alaska Department of Environmental Conservation. These records include those that occurred in marine areas, and do not include the Exxon Valdez

oil spill. The amount of substance spilled was recorded as gallons or pounds, depending on the substance or environmental conditions]

Marine Habitat: Characteristics and Threats 73
day were still leaking from the vessel, and between August 10 

and 16, an estimated 60–100 gal/d leaked from the vessel. A 

large and rapid response to the event limited the damage.

Surveys that were done the week prior to the spill, 

and days afterwards, showed that Marbled Murrelets were 

abundant throughout the spill zone, and murrelets were the 

species most often observed in oil sheen (Kuletz, 2001). Of 

seven bird carcasses retrieved during response operations, 

six were Marbled Murrelets, and these were retrieved from 

oil-containment booms that had skimmed heavily oiled 

waters. Two of the dead murrelets were adults and four were 

newly fledged juveniles. The six murrelet carcasses probably 

represent a very low proportion of total mortality (Kuletz, 

2001). Several hundred murrelets were observed in waters 

with some sheen present, and six others were obviously 

impaired but eluded captors (K. Brenneman, U.S. Fish and 

Wildlife Service, oral commun., 2001). Based on recovery 

estimates for small alcids and local conditions, Kuletz (2001) 

suggested that a conservative estimate of direct mortality for 

this spill was 100 murrelets. 

The Windy Bay spill occurred when both adult and 

juvenile murrelet numbers in Prince William Sound were at 

their peak (Kuletz and Kendall, 1998). Juvenile murrelets 

appeared to be more vulnerable to oiling and direct mortality 

than adults. During pre-spill surveys, juveniles represented 

about 3–7 percent of all murrelets, but 4 of the 6 oiled 

murrelets found dead were juveniles. Juveniles prefer, and 

often aggregate at, shallow, rocky locations with kelp (Kuletz 

and Piatt, 1999), such as existed in the primary spill zone 

(Kuletz, 2001). Fledgling physiology and behavior likely 

contributed to the disproportionate juvenile murrelet mortality. 

Juvenile murrelets typically have less than 70 percent adult 

body mass (Nelson, 1997), do not dive well, and rarely fly 

(Kuletz and Kendall, 1998). Newly fledged juvenile murrelets 

would not likely fly away from the presence of diesel, nor 

escape from skimming booms. 

Secondary and Long-Term Effects

A secondary impact from spills is the extremely high 

number of vessels that concentrate in the affected area during 

response, clean-up, and monitoring activities. This was 

noted following the 1989 EVOS, during which boat presence 

appeared to displace Marbled Murrelets from key foraging 

areas (Carter and Kuletz, 1995; Kuletz, 1996). Similarly, in 

2001, the highest number of boats encountered during surveys 

occurred while conducting post-Windy Bay spill surveys in 

the spill zone (Kuletz, 2001). Spills affect bird distribution, as 

evidenced by increased seabird abundance in un-oiled bays 

and inlets of the spill-affected areas of Prince William Sound 

(Piatt and others, 1990). A similar pattern was observed during 

the Windy Bay spill (Kuletz, 2001). 

Oil spills and contaminants can potentially cause 

immediate and long-term damage to forage fish populations. 

Herring and sand lance, both key prey species for murrelets 

in Alaska (this volume), may have been impacted in Prince 

William Sound by the EVOS (among other stressors) and may 

still be experiencing perturbations from the EVOS (Petersen 

and others, 2003). Perhaps related to impacts to forage species, 

and direct mortality prior to the breeding season, there was 

evidence of fewer fledged juveniles at Naked Island, Prince 

William Sound in 1989 and 1990 (Kuletz, 1996). 

Herring spawn nearshore and juvenile herring aggregate 

in protected bays (Norcross and others, 2001). In oiled areas 

of Prince William Sound, herring showed sublethal damage 

and larval malformations, and did not spawn in some historical 

spawning locations (Norcross and others, 2001). Herring in 

Prince William Sound peaked in estimated adult biomass 

in 1988, at 100,000 metric tons, followed by an erratic but 

ultimately dramatic decline. The herring stock collapsed in 

1993, declining to an estimated 16,082 metric tons in 1993 and 

by 2001 to a low of 6,384 metric tons (Thomas and Thorne, 

2003). There is no agreement on the cause of the collapse, and 

Region

Estimated 

recovery 

rate

Marbled Murrelets Kittlitz’s Murrelets Unidentified murrelets Estimated1

total

mortality

Number of 

carcasses

Estimated 

mortality

Number of

 carcasses

Estimated

mortality

Number of 

carcasses

Estimated 

mortality

Prince William Sound 0.35 289 826 23 66 21 60 952

Kenai Peninsula 0.14 113 807 23 164 73 521 1,492

Barren Islands 0.49 17 35 4 8 14 29 72

Kodiak Island 0.06 64 1,066 1 17 71 1,183 2,266

Alaska Peninsula 0.02 45 2,250 0 0 27 1,350 3,600

Total 528 4,984 51 255 206 3,143 8,382

1

Excludes Ancient Murrelets, based on carcasses identified to species.

Table 22. Estimates of direct mortality of Brachyramphus murrelets from the Exxon Valdez oil spill in Alaska in 1989. 

[Reprinted from Kuletz (1996)]

74 Status Review of the Marbled Murrelet in Alaska and British Columbia
it could have been due to a combination of factors in addition 

to the EVOS (Paine and others, 1996; Spies and others, 

1996). There is less information on sand lance because it is 

not a commercially fished species. Sand lance is a valuable 

prey species for seabirds because of their high energydensity (Van Pelt and others, 1997), and in Prince William 

Sound it comprises 50 percent of the prey fed to murrelet 

chicks (Kuletz, 2005). Sand lance occupy nearshore waters 

and burrow daily into sandy substrates, where they may be 

exposed to contaminants settled into benthic habitats (Robards 

and others, 1999b). 

Chronic Oiling and Other Types of Contaminant Spills

Small spills are more frequent, and though limited 

spatially, have the potential to cause mortality under different 

wind and sea conditions, particularly when spills occur in 

preferred foraging locations during sensitive periods in the 

breeding season. In addition to the Windy Bay spill, the fishing 

vessel Vanguard sank in northern Prince William Sound 

in July 2001, releasing 3,000 gal of fuel. The cumulative 

effects of incidents like these fishing-related spills could be 

significant in areas with high vessel activity. Records of vessel 

spills in coastal Alaska from 1979 to 2005 (Alaska Department 

of Environmental Conservation, unpub. data, 2005) indicate 

that vessel-related spills of oil and other contaminants peak 

slightly during the summer, as recreational, tourist, and fishing 

activities increase (fig. 17). This also is when murrelets 

occupy inshore waters of Alaska. During autumn and winter 

months, spills into coastal waters from other sources (such as 

oil rigs, harbor operations, fish processors, mining, logging, 

etc.) contribute a higher percentage of total spills. 

The spills recorded by the ADEC ranged from a single 

gallon to tens of thousands of gallons, and include a variety 

of contaminants (table 21). Records were scarce prior to 

1995, and thus we used 1995–2005 to examine annual trends 

in spills. In terms of numbers of spills, vessel-related spills 

peaked in 1999, declined sharply in 2000, and remained 

relatively stable in 2001–05 (fig. 17). Other sources of spills 

peaked in 1996, also declined in 2000, and increased again 

during 2002–04. 

Southeast Alaska had the highest number of vesselrelated spills, followed by the Aleutian Islands, with the latter 

having the largest total gallons of contaminants between 1979 

and 2005. However, a single incident in Cook Inlet in 1997, 

the rollover of the Crowley Oregon barge resulted in more than 

25 million lb of solid urea being released into coastal waters. 

Spills from non-vessel sources were highest in numbers in 

Cook Inlet, followed by Southeast Alaska, which had the 

largest total release of contaminants (table 23). Southeast 

Alaska is much larger in area than the other regional categories 

used by ADEC, which may partly account for the larger 

number of spills in Southeast Alaska. There are no records of 

murrelet mortality in Southeast Alaska from spills of oil or 

other contaminants, but there also is not generally a damage 

assessment response to small spills. Total spill levels also were 

high in Prince William Sound and Cook Inlet (table 23), both 

important murrelet breeding areas. Southeast Alaska has the 

largest proportion of Marbled Murrelets throughout their range 

(Agler and others, 1998; McShane and others, 2004), and 

thus the high incidence of spills in this region is of concern. 

While the oil-tanker traffic through Prince William Sound is 

well-known, tankers also traverse along the outer coasts of 

Southeast Alaska. To date, there have been no tanker accidents 

in this region. 

The U.S. Coast Guard (USCG) is another source 

of information on contaminant spills, however, reports 

summarizing spill events, locations, or amount of discharge 

per event requires a Freedom of Information Act request of 

USCG internal reports. A summary of marine water spills 

(petrochemical and chemicals) for 2005 and 2006 shows 255 

and 229 cases, respectively, occurred between Dixon Entrance 

and Cook Inlet (USCG Marine Safety Office, December 5, 

2006). Of these spills, 31 were more than 100 gal. 

DEC subarea

Vessels Other sources

Number Gallons Pounds Number Gallons Pounds

Aleutian 351 583,128 5,700 88 26,665 2

Bristol Bay 57 7,308 35 15,999

Cook Inlet 179 10,465 25,044,220 1,079 137,122 315,671

Kodiak Island 136 16,962 179 119 2,450

Prince William Sound 231 86,914 2 255 35,940 6,326

Southeast Alaska 877 185,189 3,035 736 413,357 48,947

Grand Total 1,831 889,966 25,053,136 2312 631,533 370,946

Table 23. Summary of spills between 1979 and 2005 in Alaska, by subarea.

[Data from Alaska Department of Environmental Conservation (ADEC). These records include those that occurred in marine areas. Only 35 records were made 

prior to 1995, and the data file did not include the 1989 Exxon Valdez Oil Spill. The amount of substance spilled was recorded as gallons or pounds, depending 

on the substance or environmental conditions]

Marine Habitat: Characteristics and Threats 75
Spills from non-vessel sources included a high proportion 

of those related to oil-rig operations and transport activities 

(Alaska Department of Environmental Conservation, unpub. 

data, 2005). Spills related to oil extraction are reflected in 

the high number of spills from non-vessel sources in Cook 

Inlet, where 12 to 15 production platforms operate. Cook Inlet 

oil production peaked at 230,000 bbl/d in 1970, declined to 

30,000 bbl/d by 1999, and since 2003 has been about 7,000 

bbl/d (Historical and Projected Oil and Gas Consumption, 

Alaska Department of Natural Resources [ADNR], May 

1999). These fields are expected to continue operations into 

the next century. Cook Inlet oil is refined in Nikiski, Alaska, 

and produces a variety of fuel types. Nikiski refineries include 

gas liquefaction and fertilizer plants, and therefore are another 

potential source of contaminants that could threaten murrelets 

in Cook Inlet. 

Marbled Murrelets are not common in upper Cook 

Inlet, where most oil-related operations occur, but prevailing 

currents may carry spills into lower Cook Inlet and Kachemak 

Bay, where murrelet densities can be locally high. The 

estimated Brachyramphus population in lower Cook Inlet in 

1993–94 was approximately 58,000 in summer and 12,000 in 

winter (Agler and others, 1998). A 2005 survey in Kachemak 

Bay estimated approximately 9,000 Marbled Murrelets present 

in July (Kuletz, U.S. Fish and Wildlife Service, unpub. data, 

2006). Plans to open lower Cook Inlet to oil exploration 

have been debated for decades, with fishery, tourism, and 

conservation stake-holders attempting to exempt the region 

from further development. In 2002, the Secretary of the 

Interior issued a Final 5-Year Offshore Oil and Gas Leasing 

Program for lower Cook Inlet (2002–07), for which lease 

sale bids have been accepted and future operations are being 

negotiated (Minerals Management Service [MMS], 2003). 

0

50

100

150

200

250

300

350

199519961997199819992000

20012002

200320042005

Year

Number of spills

0

50

100

150

200

250

Jan

Feb

Mar

Apr

May

Jun

July

Aug

Sept

Oct

NovDec

Month

Number of spills

Vessel spills

Other Spills

Figure 17. Number of spills in coastal Alaska waters by month (top) and year 

(bottom), 1995–2005, for vessel-related spills and other spill sources. 

76 Status Review of the Marbled Murrelet in Alaska and British Columbia
The shipment of crude oil and gas from Alaska 

production and transfer sites, and the high level of cargo 

or container ship traffic, result in frequent port visits to 

Alaska’s four main industrial ports. In 2005, Valdez (Prince 

William Sound) had 399 tanker visits, and 81 percent of 

those contained crude oil (U.S. Department of Transportation 

[USDOT], 2006). That same year, Anchorage (Cook Inlet) 

received 215 cargo ships and barges. The ports of Nikiski and 

Homer (Cook Inlet), ranked 7th and 15th in the Nation in Gas 

Carrier visits, with 51 and 18 port calls, respectively, in 2005 

(U.S. Department of Transportation, 2006). Three of these 

sites have year-round glacial (Valdez) or seasonal pack ice 

(Anchorage, Nikiski) that increase shipping risks. The Nikiski 

port has had several major spills or accidents that posed high 

pollution risks. The risk of spills from tankers or large vessels 

entering or exiting ports is thus greatest in Cook Inlet and 

Prince William Sound, both of which have sizable murrelet 

populations (Agler and others, 1998). 

Documenting Mortality and Damages

Documenting murrelet mortality from oil spills is 

difficult; murrelets are less likely than larger seabirds to be 

retrieved during rescue operations because of their small 

size, high sink rate offshore, and high rate of carcass loss 

to scavengers on shorelines (Piatt and others, 1990; Carter 

and Kuletz, 1995; Ford and others, 1996). Scavenger rates 

are particularly high in Alaska, because of large populations 

of carnivores and avian predators (Ford and others, 1996). 

In a Prince William Sound study, the rate of daily loss to 

scavengers was 30–50 percent, with no carcass lasting more 

than 4 days (Ford and others, 1996). More recent studies 

of carcass persistence on beaches in California and Oregon 

determined average persistence time on beaches for smallbodied carcasses similar to Marbled Murrelets of 1.17 and 

3.70 days (Ford and Ward, 1999). 

Ability to document murrelet mortality from catastrophic 

events will depend on weather, and marine and coastal habitat. 

Length of time at sea greatly increases carcass loss due to 

sinking, but in the relatively calm waters of Prince William 

Sound bird carcasses stayed adrift longer than in the Gulf of 

Alaska, with some floating birds kept adrift for 15 to 20 days 

(Ford and others, 1996). For all bird species combined, the 

carcasses found during the EVOS were estimated to represent 

10 to 30 percent of actual mortality (Piatt and others, 1990). 

Murrelets, however, were more difficult to find than other 

birds on rocky, boulder beaches common in Prince William 

Sound (Ford and others, 1996). More recent studies (Ford 

and Ward, 2000) found that small birds such as murrelets also 

had the lowest ratio (1:25) of found to oiled carcass retrieval 

during searches of flat, sandy beaches. Thus, it would be 

difficult to document murrelet morality from a spill even if 

it occurred near large, sandy beaches (i.e., the Copper River 

Delta to the Yakutat region).

British Columbia

The risks and actual mortality from catastrophic and 

chronic oil spills to seabirds in British Columbia were 

reviewed by Burger (1992) and Burger and Fry (1993), but 

these data are somewhat out of date. There likely has been 

an increase in the volume and rates of shipping in British 

Columbia waters, but perhaps balanced by improved handling 

and shipping techniques, increased vigilance, and better 

monitoring of oil pollution.

Recent major spills affecting British Columbia murrelets 

included the Nestucca spill off Grays Harbor, Washington, in 

December 1988, which killed at least 145 Marbled Murrelets 

off northern Washington and Vancouver Island (Burger, 

1993a), and the Tenyo Maru spill at the entrance to the Strait 

of Juan de Fuca on the British Columbia–Washington border 

in July 1991, which killed at least 45 murrelets and likely 

many more (Carter and Kuletz, 1995). These are almost 

certainly underestimates, because the small carcasses of 

murrelets are easily missed in clean-up operations. 

The risks of large, catastrophic spills within areas used by 

murrelets in British Columbia are high. Annually in the early 

1990s there were more than 7,000 transits of freighters and 

tankers in British Columbia waters, including at least 1,500 

tanker trips to or from Alaska, and more than 350 loaded 

tankers entered the Strait of Juan de Fuca (Burger, 1992). The 

volume of shipping is certainly higher now. Risk models for 

southern British Columbia and northern Washington predicted 

that spills exceeding 1,000 bbl could be expected every 2.5 

years for crude oil and every 1.3 years for all petroleum 

products, with longer intervals between larger spills (Cohen 

and Aylesworth, 1990). The actual frequency of large spills 

affecting British Columbia between 1974 and 1991 was fairly 

close to that predicted (Burger, 1992). 

In addition to well-publicized catastrophic spills, many 

seabirds are killed by small, often unreported spills. Many 

hundreds of small spills occur each year in British Columbia, 

from fishing vessels, recreational craft, marinas, and fueling 

barges (Burger, 1992). Monthly beached bird surveys between 

1989 and 1997 showed that oiled birds composed 12.3 percent 

of the 198 carcasses with reported causes of mortality (Burger, 

2002). This percentage is undoubtedly an underestimate of the 

actual number of oiled birds because evidence of oiling might 

be easily missed in carcasses that had been partly scavenged 

or were decomposed. Small quantities of oil were reported on 

the beaches in 8 percent of all surveys in British Columbia 

and for 17 percent of surveys on west Vancouver Island 

(Burger, 2002). Marbled Murrelets were not among the oiled 

birds identified to species in the beach surveys. Murrelets 

should experience similar risks of being oiled as other coastal 

alcids, but because they are one of the smallest seabirds their 

carcasses are likely to be overlooked in beach surveys. 

Marine Habitat: Characteristics and Threats 77
Most (77 percent) of the oiled birds in the beach surveys 

were from West Coast Vancouver Island (9 beaches), with 

10 percent each from southern Vancouver Island (2 beaches) 

and Strait of Georgia (1 beach), and a single bird (3 percent) 

from Langara Island, Haida Gwai (Queen Charlotte Islands) 

(Burger, 2002). Oiling was the most common cause of death 

reported for carcasses found on West Coast Vancouver Island 

and was attributed to 56 percent of the 54 carcasses with 

reported causes of death there. Oiling was responsible for 13 

and 12 percent of carcasses with known causes of death in 

southern Vancouver Island and Strait of Georgia, respectively, 

and was the sole cause of death reported for Haida Gwaii 

(Queen Charlotte Islands). Taking all years into account, the 

density of oiled birds was highest for West Coast Vancouver 

Island (0.041 oiled birds per km surveyed), followed by 

Haida Gwaii (Queen Charlotte Islands) (0.015), Strait of 

Georgia (0.010), and southern Vancouver Island (0.007). All 

other regions reported no oiled birds. The mean density of 

oiled birds (0.014 per km surveyed) was low compared to 

most other coasts surveyed in North America and Europe 

(Burger, 1993b, 2002b), but the high volumes of logs and 

other wrack on local beaches reduced the chances of finding 

oiled birds. Annual mean oiled carcass density declined on 

west Vancouver Island between 1990–95, but showed no trend 

in other regions or for British Columbia as a whole (Burger, 

2002). The percentage of oiled birds showed no changes over 

the years in any region. 

A major concern in British Columbia is the relatively 

high frequency of chronic oiling on the west coast of 

Vancouver Island and possibly also for Haida Gwaii (Queen 

Charlotte Islands) (which was not adequately sampled; Burger, 

2002). Both of these regions support high densities of Marbled 

Murrelets. 

Overall, chronic oil pollution is likely to kill small 

numbers of Marbled Murrelet in British Columbia each year, 

although the actual number is not known, and the impact 

on the population thus remains unknown. The risks from 

a large catastrophic oil spill, similar to the Nestucca spill 

(Burger, 1993a) or the EVOS (Piatt and others, 1990), are, 

however, significant and if such a spill coincided with seasonal 

aggregations of murrelets it could cause a serious local 

population decline. Oil spills would kill a large proportion 

of adult birds, resulting in significant demographic impacts 

(Boulanger and others, 1999).

Monitoring of marine oil pollution has improved in 

British Columbia water over the past 5 years, with increased 

surveillance flights and the use of satellite radar to track large 

spills (P. O’Hara, University of Victoria, oral commun., 2006).

Incidental Take in Fisheries

Alaska

Commercial fishing is an important component of 

Alaska’s economy and is critical to many communities. 

Commercial, subsistence, and recreational fisheries occur 

in Alaska, including gillnet fisheries. Incidental capture of 

Marbled Murrelets in gillnets is the best-documented effect 

of fisheries on Marbled Murrelets and has been documented 

widely in Alaska, British Columbia, Washington, and 

California (Carter and Sealy, 1984; Carter and others, 1995; 

Melvin and Parrish, 2001). In British Columbia, an estimated 

6 percent of the breeding population of Marbled Murrelets 

in Barkley Sound was taken annually in gillnets in 1980, 

although mortality was likely lower in preceding years (Carter 

and Sealy, 1984; Carter and others, 1995). Brachyramphus

murrelets are susceptible to mortality in gillnet fisheries 

due to their nearshore feeding using pursuit-diving behavior 

(Carter and others, 1995; Day and others, 1999). McShane 

and others (2004) indicated that gillnet mortality has been 

reduced in Washington and California due to highly reduced 

fisheries in recent years, but they used demographic models 

and conservative estimates of mortality to show that gillnet 

mortality has significantly impacted some populations in 

the past. Below, we review murrelet-fisheries interactions in 

Alaska, with an emphasis on salmon gillnet fisheries.

Salmon Fisheries

Salmon fisheries are managed by the ADFG, with nine 

salmon regional districts that potentially overlap with Marbled 

Murrelets (fig. 18). Regional districts are managed separately 

by local offices, with each region divided into subdistricts and 

statistical areas for management of fishery openings. The two 

types of gillnet fisheries used for salmon in Alaska are drift 

gillnets and setnets, both of which currently use multifilament 

mesh. Total gillnet length (generally 150 fathoms) per permit 

varies among fisheries. Drift gillnets are deployed from boats 

(typically <12 m), and are deployed for 15 min to 4 hr at a 

time (Wynne and others, 1991). Setnets are stationary surfacehanging nets anchored to shore or the bottom substrate, and 

usually are checked and picked, but not always removed, 

during slack tides.

Most salmon gillnet fisheries operate from early JuneAugust, although seasons vary locally and with the target 

salmon species (fig. 19). These summer months span the 

breeding season of the Marbled Murrelet in Alaska, and late 

July through early August is when peak numbers of birds are 

in nearshore waters, including newly fledged juveniles (Kuletz 

and Kendall, 1998; Kuletz, 2005). Fisheries that extend into 

late August–October also may overlap with the murrelet’s 

pre-basic molt period. The molt period for these murrelet 

populations extends throughout this late summer and early 

autumn period, and individual murrelets are flightless for 

about 1 month (Carter and Stein, 1995). 

78 Status Review of the Marbled Murrelet in Alaska and British Columbia
Figure 18. Alaska Department of Fish and Game salmon fishing districts for Aleutian Islands, Alaska Peninsula, 

Kuskowim, Bristol Bay, Cook Inlet, Kodiak, Prince William Sound, Yakutat, Juneau, Sitka, and Ketchikan Areas. 

Within each district, multiple statistical areas are delineated, and these may be opened or closed on different 

schedules to manage the fishery.

Marine Habitat: Characteristics and Threats 79

OFR2006_1387_fig18A
Figure 18. Continued. 

80 Status Review of the Marbled Murrelet in Alaska and British Columbia

OFR2006_1387_fig18B
Figure 19. Commercial salmon fishing seasons in Alaska, for those fisheries 

using gillnets.

Marine Habitat: Characteristics and Threats 81
Figure 19. Continued.

82 Status Review of the Marbled Murrelet in Alaska and British Columbia
Figure 20. Salmon harvest in Alaska, 1878–2005. From Alaska Department of 

Fish and Game. 

The number of salmon permits held throughout the 

State (including gillnet, seine, and troll fisheries) has a 5-year 

(2000–04) average of 7,432 permits (Woodby and others, 

2005; table 24). Of these permits, 3,438 (46 percent) are in 

regions with substantial populations of Marbled Murrelets, 

including Southeast Alaska—Yakutat, Prince William Sound, 

Cook Inlet, and Kodiak Island. Smaller murrelet populations, 

and thus lower densities and potentially lower encounter rates, 

may overlap with gillnet fisheries in Bristol Bay, the Aleutian 

Islands, and along the Alaska Peninsula (fig. 18). 

The number of salmon permit holders and salmon 

landings increased dramatically in the 1980s, and remains 

strong today (fig. 20). In Prince William Sound, this growth 

in the salmon fishery was facilitated by Pink salmon 

(O. gorbuscha) hatcheries, which began in 1977 and reached 

full production in the mid-1980s (Pearson and others, 1999; 

Thomas and Thorne, 2003). 

Murrelet and Gillnet Fisheries Overview

For three of the major ADFG fishing areas, Cook Inlet, 

Prince William Sound, and Southeast Alaska, the USFWS 

has survey data (1993, 2005, 1994, respectively) on murrelet 

distribution (North Pacific Pelagic Seabird Database [NPPSD], 

2006). We mapped the numbers of Brachyramphus murrelets 

(93–99 percent Marbled Murrelets) with respect to fishing 

district boundaries2. Not all areas of a fishing district are 

fished, and annual and seasonal differences in fishing effort 

are dramatic, thus these maps are only for general reference.

In Cook Inlet, murrelets occur throughout the central 

portion of central Cook Inlet, with the heaviest concentrations 

in the Southern District, which includes Kachemak Bay 

(fig. 16). In Prince William Sound, murrelets tend to be in 

2

District maps available at http://www.cf.adfg.state.ak.us.

nearshore waters, are fairly evenly distributed, and overlap 

with all districts to some degree (fig. 21). Numbers of 

murrelets are high in the Southwestern District, including 

the southern Eshamy District, but this is partly an artifact of 

more USFWS transects in this region (U.S. Fish and Wildlife 

Service, unpub. data, 2006). Murrelets are locally abundant 

in the upper fjords of the Coghill District as well. There is no 

murrelet survey data for the Copper River, Bering River, or 

the outer waters of Southeastern and Montague districts, all of 

which are considered part of the Prince William Sound Area. 

Southeast Alaska is divided by the ADFG into the 

northernmost Juneau Area, the central Sitka Area, and 

the southernmost Ketchikan Area, totaling 16 subdistricts 

(fig. 22). Areas that are traditionally fished include Districts 

15 (Lynn Canal and adjoining inlets), District 11 (Stephens 

Passage and adjacent inlets), Districts 6 and 8 (passages 

between northeastern Prince of Wales Island, southern 

Kupreanof Islands, and the mainland). Marbled Murrelets 

occur throughout Southeast Alaska, but the 1994 survey shows 

high concentrations in the southern portion of District 15, 

District 11, and the northern portion of District 10 (fig. 22). 

Murrelets were scattered throughout District 6, with a large 

concentration near the confluence of the Sumner and Stikine 

straights (northwestern Prince of Wales Island). Similar 

overlap between murrelets and gillnet fisheries in the inside 

waters were described by Carter and others (1995), based 

on non-standardized surveys conducted by fisher-biologist 

Mike McAllister. In the 1994 survey, murrelets also occurred 

along the outer coast, particularly in District 3 (northeastern 

Prince of Wales Island) and the northern portion of District 

13 (northern Baranof Island). District 14, which includes Icy 

Straight, also has large numbers of murrelets (this volume), 

and may attract murrelets nesting as much as 100 km to the 

south (Whitworth and others, 2000). 

Marine Habitat: Characteristics and Threats 83
Figure 21. Brachyramphus murrelet distribution in Prince William Sound in July 2005, relative to salmon fishing 

districts in the Prince William Sound Area. Surveys for murrelets were not conducted in the outer waters of the 

Sound, nor in the Copper River and Bering River districts.

Gillnet Mortality

Prior to 1990, records of murrelet mortality in gillnets 

were mostly anecdotal, and suggested that total murrelet 

mortality in gillnets in Alaska was in the low thousands 

annually (Mendenhall, 1992; Carter and others, 1995). Carter 

and others (1995) report observations by fisher-biologist 

Pete Isleib, that ‘several hundreds’ of murrelets were killed 

annually in Prince William Sound (including the Copper 

River district). Isleib also estimated, based on his estimates 

of fishing effort, locations, and what he observed in Prince 

William Sound, that as many as 1,000 Marbled Murrelets 

were killed annually in gillnet fisheries of Southeast Alaska 

(DeGange and others, 1993). Isleib reported that gillnet 

mortality of birds was rare in the Bristol Bay area, and he had 

not encountered murrelets as bycatch in that fishery. 

Because distribution of fishing effort, habitat types, and 

murrelet abundance varies among regions, differences in 

encounter rates between murrelets and gillnet fisheries would 

be expected. Based partly on the results of the Prince William 

Sound studies, and anecdotal reports of murrelet mortality 

in gillnets, Piatt and Naslund (1995) estimated that as many 

as 3,300 Marbled Murrelets were killed in gillnets annually 

in Alaska during the 1990–91 period. This estimate assumed 

similar encounter rates between gillnet fishers and murrelets in 

all fishing areas, and operation of all available fishing hours, 

and thus could have inflated the murrelet bycatch estimates. 

However, additional information for Cook Inlet and Kodiak 

Island suggest that the Piatt and Naslund (1995) estimate 

was at least within the same order of magnitude. Based on 

the estimated take of murrelets in Prince William Sound, 

south Unimak, Cook Inlet, and Kodiak Island (table 25), 

and assuming that declines in murrelet populations since the 

1990–91 studies have reduced encounter rates, it is likely that 

at least 500 birds are taken annually in those four fisheries. 

Because of the larger area, higher number of permits, and 

larger murrelet population in Southeast Alaska, it is possible 

that twice that number is taken annually there. However, 

a proper estimate would require a monitoring effort for 

Southeast Alaska–Yakutat areas, and an update for the Prince 

William Sound–Copper River areas. 

84 Status Review of the Marbled Murrelet in Alaska and British Columbia
Figure 22. Brachyramphus murrelet distribution in Southeast Alaska in June and July 1994, relative to salmon 

fishing districts in the Southeast Areas.

The number of ADFG commercial salmon permits 

provides an indication of relative fishing effort among areas, 

but not all permits are used in a given year, and fishers may 

not fish during all openings. Daily, seasonal, and annual 

fishing vessel-hours can vary dramatically depending on 

achievement of escapement goals, and actual fishing effort 

is not tracked by the ADFG (Wynne and others, 1991, 1992; 

Manly and others, 2003). For example, a 2006 pilot study 

of the Yakutat gillnet fishery by West, Inc. (B. Manly, oral 

commun., 2006), found that roughly one-third of the maximal 

potential net-hours (based on number of permits and openings) 

were actually fished. Thus, estimates of fishing effort should 

be based on surveys of fishing effort conducted concurrent 

with studies of incidental take. Tracking of actual fishing 

effort during gillnet bycatch studies was conducted for the 

Cook Inlet and Kodiak studies. Extrapolating total bycatch 

mortality for murrelets throughout Alaska would require more 

detailed knowledge of fishing effort, local fishing patterns, and 

would ideally include data on current murrelet distribution and 

abundance. 

Marine Habitat: Characteristics and Threats 85
Fishery Harvest

(number of fish)

Harvest

(lb)

Value($)1 Permits

Southeast and Yakutat 61,727,291 286,506,541 $72,573,000 1,781

Prince William Sound 40,563,838 169,733,170 $43,841,000 680

Cook Inlet 5,337,269 28,301,597 $14,657,800 982

Kodiak 21,262,985 87,729,099 $19,744,000 322

Chignik 1,856,583 11,593,697 $6,978,000 62

Alaska Pen. and Aleutians 8,476,735 40,999,253 $13,668,000 285

Bristol Bay 18,070,428 112,058,010 $56,097,000 2,285

Kuskokwim 430,566 3,274,628 $1,149,800 491

Yukon River2 50,182 682,624 $1,268,800 465

Norton Sound 64,026 298,277 $71,600 42

Kotzebue 91,401 786,247 $129,000 37

Statewide 157,931,303 741,963,142 $230,178,000 7,432

1

Exvessel value of landed catch.

2

No Yukon fishery in 2001.

Table 24. Recent 5-year average harvests, value, and permits fished for selected Alaska commercial salmon fisheries. 

[From Commercial Fisheries in Alaska, Woodby and others, 2005, with updated data. http://www.cf.adfg.state.ak.us/geninfo/finfish/salmon/catchval/blusheet/

salmon_00-04table.php. Averages are for 2000–04]

Although the Alaska salmon fishery is managed by 

the State, the National Oceanographic and Atmospheric 

Administration (NOAA)-Fisheries is responsible for 

monitoring threats to marine mammals, which also are 

caught in gillnets. In 1990, the NOAA-Fisheries initiated the 

Alaska Marine Mammal Observer Program. The original 

intent was to rotate among state gillnet fisheries, sampling a 

given fishery with an observer program for 2 years. However, 

funding of NOAA gillnet studies is allocated at the National 

level, and depends on the status of mammals at risk and costs 

of monitoring a fishery. In Alaska, with a large, dispersed 

fishery and remote locations with difficult access, the cost of 

conducting bycatch studies has hindered adequate coverage, 

even when a study was implemented (Wynne and others, 

1991). 

Between 1990 and 2006, gillnet fisheries were monitored 

during six seasons at south Unimak on the Alaska Peninsula 

(1990), Prince William Sound (1990, 1991), Cook Inlet 

(1999, 2000), and Kodiak Island (2002, 2005; see table 25). 

The NOAA-Fisheries estimated that ideally 20–35 percent of 

a fishery should be sampled, but where this is not possible, 

they accept 5 percent coverage as a minimum for adequate 

statistical analyses (Wynne and others, 1991). In Alaska 

salmon fisheries, observer coverage has been limited because 

of the use of small boats, distribution of boats over large areas, 

and potentially dangerous seas (Wynne and others, 1991). The 

1990 study was estimated to have sampled 2.7–4.1 percent 

of three fisheries that year, and 5 percent in 1991 (Wynne 

and others, 1991, 1992). In Cook Inlet, less than 2 percent of 

the fishery was monitored, resulting in wide CIs and suspect 

mortality estimates (Manly, 2006a). Manly determined that 

adequate sampling of most fisheries would require observation 

of approximately 5 to 7 percent of the fishing effort (Manly 

and others, 2003). However, based on results from the Kodiak 

fishery, power to detect significant differences in bycatch of 

Marbled Murrelets between regions or years would take four 

times that level of coverage (Manly and others, 2003). The 

wide CIs of the resulting bycatch estimates (table 25) illustrate 

the relatively rare occurrence of seabird bycatch to individual 

fishers. Nonetheless, the size and geographic extent of 

Alaska’s salmon fisheries could make it a conservation issue.

86 Status Review of the Marbled Murrelet in Alaska and British Columbia
Region 

5-year 

average 

number of 

permits

Year of 

study

Percent 

of total 

birds

Incidental take of Marbled Murrelets

Source of bycatch data Bycatch

rate

per year 

take

95-percent 

confidence 

limit

Southeast and Yakutat 1,781 nd nd nd nd nd

PWS / S. Unimak 680 Wynne and others, 1991

PWS driftnet1 1990 91.9 0.020 1,350 768–1,930

PWS setnet1 1990 0 0 0 0

S. Unimak driftnet1 1990 6.3 0.003 21 10–33

PWS driftnet2,3 1991 32.1 0.012 318 107–671 Wynne and others, 1992

Cook Inlet4 982 Manly, 2006a

Upper CI setnet4 1999 0 0 0 (author notes insufficient coverage 

Lower CI setnet to determine bird bycatch) 4 1999 0 0 0

Central driftnet4 1999 0 0 0

Upper CI setnet 2000 33.3 0.001 37 0–111

Lower CI setnet 2000 0 0 0

Central driftnet 2000 0 0 0

Kodiak Island 322

setnet 2002 11.4 0.013 56 3–110 Manly and others, 2003

setnet 2005 10.9 0.011 143 8–277 Manly, 2006b

AK Penin / Aleutians 285 nd nd nd nd nd

Bristol Bay 2,285 nd nd nd nd nd

1

Based on data in Wynne and others, 1991, using weekly bycatch rates for all birds, and percent Marbled and unidentified murrelets.

2

Based on data in Wynne and others, 1992, using 17 birds taken during 22 percent of 5,875 sets (not total net hours).

3

Includes one unidentified murrelet, but not the Kittlitz’s Murrelets.

4

Less than 1 or 2 percent of fishery was observed; insufficient for sampling bird bycatch, and estimates not reliable (Manly, 2006a).

Table 25. Salmon gillnet fishing regions, the 5-year average (2000–04) for number of permits by region, and available data on Marbled 

Murrelet incidental take in those fisheries. 

[Bycatch rate for PWS and Unimak were derived from data in report, using number of birds taken per net hauls observed. Bycatch rate for Kodiak and Cook 

Inlet were calculated by the source author, using number of birds taken per net-hour fished. nd, no data]

Bycatch Estimates

Murrelet bycatch in the 1990 south Unimak fishery was 

relatively low, with murrelets composing about 6 percent of 

total bird bycatch and annual take ranging from 10 to 33 birds 

(95 percent CI). The low proportion of murrelets among the 

bird bycatch likely reflects the relatively low murrelet density 

in the Alaska Peninsula Area (Van Pelt and Piatt, 2005). 

In the Prince William Sound-Copper River drift 

gillnet fishery, estimated incidental take of Brachyramphus

murrelets ranged in magnitude from approximately 2,000 

to several hundred in 1990 and 1991. Different treatment 

of data in Wynne and others (1991, 1992) have resulted in 

differences in annual estimated bycatch of murrelets for 

Prince William Sound. Piatt and Naslund (1995) estimated 

that Brachyramphus murrelet mortality was 923 and 714 

murrelets in 1990 and 1991, respectively. However, using 

Wynne’s more detailed analysis of total bird bycatch in 1990 

using mean bycatch rates per week and gillnet effort (Wynne 

and others, 1991) resulted in an estimated 1,468 (95 percent 

CI, 813–2,043) total bird take, which would equate to 1,423 

Brachyramphus murrelets (Piatt and Naslund, 1995). Based 

on the percentage of bird bycatch in 1990, Marbled Murrelets 

composed 84 percent of the total bycatch, or 92 percent if 

unidentified murrelets were included, which equated to 1,350 

murrelets (table 25). In 1991, Marbled and unidentified 

Brachyramphus were 32 percent of total bird bycatch, or 318 

birds. Estimated mortality of Kittlitz’s Murrelets added an 

additional 79 birds in 1990 and 133 birds in 1991. 

Marine Habitat: Characteristics and Threats 87
In both 1990 and 1991, bycatch was highest in the 

Copper River District, but there also was greater coverage in 

that district, and bycatch occurred regularly in the Coghill 

District (Wynne and others, 1991). Anecdotally, fishers 

reported that murrelet abundance and bycatch in the Copper 

River District were much higher than normal in 1990 (Wynne 

and others, 1991). Wynne and others (1991) observed that 

murrelets were taken in all Prince William Sound districts, 

mortality occurred throughout the summer, but was highest in 

late July, and was most frequent in nearshore sets. Estimates 

of seabird bycatch are highly variable among years even at the 

same site (Melvin and others, 1999, 2001). The high variance 

is believed to be partly the result of changes in environmental 

or fishery-related factors, but also reflects the generally low 

probability of detecting bycatch (Manly and others, 2003).

Seabird bycatch in the three Cook Inlet fisheries was 

very low, with the exception of the Upper Cook Inlet setnet 

fishery in 2000 (table 25). However, the 2000 estimate of 37 

murrelets was based on a single bird taken in a study with very 

low observer coverage. The low coverage level in this fishery 

compromised estimates of bird bycatch (Manly, 2006a). 

In the Kodiak setnet fishery, Marbled Murrelets composed 

about 10–11 percent of total bird bycatch, with estimated 

per annum mortality of murrelets of 56 and 143 in 2002 and 

2005, respectively (table 25). The higher estimated morality of 

murrelets in 2005 appeared to be due to greater fishing effort, 

not a higher bycatch rate (Manly, 2006b). 

Murrelets taken in the Kodiak fishery were examined by 

University of Alaska and USFWS researchers. The Marbled 

Murrelets all had brood patches (in various stages), and 

thus were likely breeding adults, with equal proportions of 

males and females (Manly, 2006b). Piatt and Naslund (1995) 

reported that 18 murrelets examined from the Prince William 

Sound study included 16 adults and 2 juveniles. However, 

based on anecdotal reports from Alaska, Carter and others 

(1995) reported that juvenile murrelets may be particularly 

susceptible to gillnet mortality when fishing occurs later in the 

breeding season.

Other Coastal Fisheries

Some components of the sac-roe (herring eggs) fishery 

also use gillnets, although the majority of herring are taken 

by purse-seine. The herring fishery has not been monitored 

for bycatch, but it is not likely to be a significant contributor 

to murrelet mortality. Compared with salmon fisheries, 

herring gillnet fisheries are relatively brief, and occur in 

spring (primarily April), before many murrelets aggregate in 

nearshore waters in parts of Alaska. However, some birds are 

resident over the winter and could be impacted in Southeast 

Alaska. The mesh used for herring typically is about one-half 

the size of that used for salmon, which may reduce or preclude 

murrelet entanglement. Murrelets also can become trapped 

inside purse-seine nets as they are encircled and hauled in 

during salmon and herring fishing operations, but anecdotal 

observations suggest murrelets can escape (Carter and others, 

1995). 

Efforts to Reduce Gillnet Mortality

There is considerable evidence that where murrelets 

overlap with gillnet fisheries, mortality occurs at some level. 

Although monitoring bycatch is a useful management tool, 

the best approach at this stage would be to determine how best 

to mitigate incidental take in these fisheries. Area closures 

have proven to be successful for reducing seabird bycatch in 

central California and Washington. Between 1979 and 1990, a 

series of fishing closures gradually reduced gillnet mortality of 

seabirds and marine mammals throughout the breeding range 

of the Marbled Murrelet in central California (i.e., Marin to 

northern Monterey County) where murrelet mortality had 

been documented (Wild, 1990; Carter and Erickson, 1992; 

Carter and others, 1995). Alternative fishing gear (modified 

otter trawls) were investigated and used for several years by 

a few fishers but later abandoned. By the mid-1990s, fishing 

effort shifted farther south off the coasts of southern Monterey 

and San Luis Obispo Counties, and seabird and marine 

mammal mortalities resumed (Forney and others, 2001). In 

1997, radio-marked Marbled Murrelets were first found to 

disperse to this area (E. Burkett, California Department of Fish 

and Game, unpub. data, 1997), and concern about possible 

gillnet mortalities to murrelets resumed but no carcasses 

were recovered. In 2000, gillnet fishing was banned from all 

nearshore waters (i.e., waters <100 m deep; McShane and 

others, 2004). 

In Washington, several studies in 1993–96 found low 

entanglement of seabirds; however, fishing effort already had 

been reduced to less than 50 percent of levels in the 1980s 

(McShane and others, 2004). Area and temporal closures were 

implemented in 1995, and alternative gear was investigated 

and later implemented. Bycatch of birds, primarily Common 

Murres and Rhinoceros Auklets (Cerorhinca monocerata), in 

the gillnet fishery in Washington has been reduced by as much 

as 75 percent (Melvin and others, 1999; Melvin and Parrish, 

2001). However, whether or not Marbled Murrelet mortality 

was reduced by alternative gear was not determined (McShane 

and others, 2004). Very reduced fishing effort after 1997 has 

likely led to low levels of gillnet mortality in Washington over 

the last decade. 

88 Status Review of the Marbled Murrelet in Alaska and British Columbia
In British Columbia, restrictions to prevent fishing in 

murrelet aggregation areas or to prevent crepuscular and 

night-time fishing have been proposed to reduce incidental 

take of murrelets in gillnets (Carter and Sealy, 1984; Burger, 

2002). Carter and others (1995) also recommended daylight 

fishing and proposed that area restrictions might reduce 

murrelet bycatch in Alaska. It is unknown whether the gear 

modification or temporal restrictions would work in Alaska, 

where daylight patterns differ from lower latitudes, water 

clarity varies tremendously among fishing areas, and fishers 

are dispersed over larger areas. However, Isleib did report that 

as much as 80 percent of the mortality he observed in Prince 

William Sound occurred during night sets. Murrelets have 

been observed diving and foraging near gillnets, and they 

have been entangled at various depths, from the surface to 10 

m below the surface (Carter and others, 1995). In the Kodiak 

fishery, Manly and others (2003) did not find time of day to 

be a significant factor for all alcid bycatch combined. Manly 

will be conducting a more detailed analysis with the inclusion 

of 2005 data, and will attempt to examine murrelets separately 

(B. Manly, WEST, Inc., oral commun., 2006). 

Alaska Groundfish Fisheries

This is Alaska’s largest fishery, in biomass harvested 

and monetary value, and is one of the largest in the world 

(National Oceanic and Atmospheric Administration, 2004). 

The NOAA-Fisheries Observer Program deploys observers 

onboard selected ships to monitor bycatch, including seabirds. 

At the request of the USFWS, the NOAA-Fisheries trains 

observers to identify marine birds taken incidentally in fishing 

gear and record opportunistic observations of presence or 

interactions with fishing operations. The Marbled Murrelet is 

one of seven bird ‘species of special interest,’ meaning that 

observers are requested to record observations of the birds, and 

to salvage carcasses for species confirmation. Most of these 

fisheries operate in offshore waters where interactions with 

murrelets are rare. The estimated take for all alcids in these 

fisheries averages less than 400 birds annually, primarily in 

the trawl fisheries of the Gulf of Alaska (National Oceanic and 

Atmospheric Administration, 2006). No identified Marbled 

Murrelets have been caught incidentally, although between 

1993 and 2005 incidental takes of ‘small unidentified alcid’ 

were recorded on 20 occasions (S. Fitzgerald, Alaska Fisheries 

Science Center, oral commun., 2006). 

Separate from the official incidental take records, 

fisheries observers opportunistically record bird observations, 

which are entered into the Seabird Observer Notes Database 

maintained by the USFWS in Anchorage, Alaska. A query of 

the 4,249 records in Seabird Observer Notes between 1993 

and 2003 (U.S. Fish and Wildlife Service, unpub. data, 1993–

2003), found 12 records of Marbled Murrelets, and 11 of 

unidentified murrelets. Of these, 13 were sightings of birds on 

the water, 2 were diving near gear lines, 7 were on the vessel 

and unable to fly away without assistance, and 1 was a vessel 

strike that died. These records suggest that Marbled Murrelet 

interactions with groundfish fisheries are rare, but may include 

vessel strikes on occasion. Vessel strikes in Alaska are more 

common for small auklets and shearwaters, and are often 

associated with lighted vessels during stormy nights or high 

winds (e.g., Dick, 1979).

British Columbia

Information on interactions between fisheries and 

Marbled Murrelets in British Columbia was summarized by 

Burger (2002b), but a new report (Smith and Morgan, 2005) 

provides additional data. Of the more than 15 types of fisheries 

operating in British Columbia, salmon gillnets appear to be 

the greatest threats to Marbled Murrelets. Possible impacts 

of sports fishing (angling), the purse-seine fishery, and 

aquaculture remain poorly known. Based on the review and 

data provided by Smith and Morgan (2005), murrelets appear 

to be at low risk to being caught in long-line fisheries (either 

for halibut or rock cod), the salmon troll fishery, the sablefish 

trap fishery, or the trawl net fishery. 

In Canada, two Federal agencies have regulatory 

authority with regards to the issue of bycatch—Environment 

Canada (EC) and the Department of Fisheries and Oceans 

(DFO). EC has a mandate for seabird conservation and 

the responsibility to enforce the statutes of the Migratory 

Bird Convention Act and the SARA. Nationally, seabird 

management priorities are set by EC headquarters, with 

input from the various regions; and management activities 

are implemented regionally (e.g., through the CWS). The 

DFO is the Federal authority over all fishing activities, and 

is responsible for the enforcement of the Fisheries Act, the 

Oceans Act, and Canada’s role in implementing International 

fisheries agreements. Canada is a signatory to the UN 

International Plan of Action for Reducing the Incidental Catch 

of Seabirds in Longline Fisheries (UN Food and Agriculture 

Organization [FAO], 1999) and the UN Code of Conduct for 

Responsible Fisheries (Food and Agriculture Organization, 

1995). The DFO also is responsible for implementing a Pacific 

Region Selective Fisheries Policy and the Canadian Code of 

Conduct, an industry led initiative. 

There is currently a modest effort to study bycatch 

issues in British Columbia, beginning with the formation of 

the interagency Pacific Seabird Bycatch Working Group in 

2000. The group’s goals were to increase the understanding of 

seabird bycatch in longline and net fisheries, and to promote 

the use of mitigation measures to reduce seabird bycatch in 

British Columbia. Efforts have been made to train fisheries 

observers to identify seabirds and a seabird salvage program 

was initiated in 2000 to collect birds killed by the gillnet 

fisheries. The review and analysis by Smith and Morgan 

(2005) is the first step in identifying the scope of the bycatch 

problem in British Columbia. A more detailed effort is 

underway to document fisheries interactions with Marbled 

Murrelets (D. Bertram and K. Charleton, Candian Wildlife 

Service), but results from this study are not yet available.

Marine Habitat: Characteristics and Threats 89
Gillnets

Bycatch in gillnets was cited as one of the major threats 

to murrelets in British Columbia when they were listed as 

Threatened (Rodway, 1990) and in subsequent reviews (Hull, 

1999; Burger, 2002). The main salmon species targeted in 

the commercial gillnet fishery in British Columbia are pink, 

sockeye (0. nerka), and chum (O. keta) salmon. The DFO 

statistical areas are combined into eight License Areas, of 

which three (Areas C, D, and E; figs. 23, 24, and 25) pertain 

to gillnet fisheries. Areas of the British Columbia coast where 

gillnetting activity might overlap with Marbled Murrelet 

aggregations were identified by Carter and others (1995) and 

Burger and others (1997), but fishing effort changes frequently 

from year to year making it difficult to predict where problems 

might arise. 

Gillnet vessels in British Columbia generally are less 

than 15 m in length and are operated by a crew of one or 

two. Gillnets are set below the surface and typically have a 

multi-strand mesh comprised of 30 or more filaments in each 

twine. In recent years, Alaska Twist mesh has been tested in 

some fisheries. This mesh is made from six or more filaments 

twisted together in each twine. 

The first detailed study on gillnet mortality of murrelets 

in British Columbia was by Carter and Sealy (1984), who 

reported bycatch of Marbled Murrelets during gillnetting 

in June–August for sockeye salmon in Barkley Sound in 

1979–80. Carter and Sealy (1984) estimated that a minimum 

of 175–250 murrelets was killed in 1980, which represented 

6.2 percent of the local breeding population, or 7.8 percent 

of the potential autumn population (taking into account 

the additional loss of chicks whose parents had died). 

Most mortality occurred at night at depths of 2.0–8.5 m. 

Approximately 90 percent of the dead birds were breeding 

adults, 5 percent non-breeding, and 5 percent HY birds. In the 

1980s and early 1990s there typically were 300–400 gillnet 

vessels fishing 24 hours per day, 1-4 days per week, in Barkley 

Sound (Burger, 2002; Smith and Morgan, 2005). Gillnetting 

of this intensity which overlaps with the time of maximal 

numbers of murrelets (April–August) is now rare in Barkley 

Sound, although some bycatch mortality continues (Carter and 

others, 1995; Alan E. Burger, University of Victoria, personal 

observation). Since the mid- to late-1990s, the fishing effort 

has been about 100 gillnet vessels fishing only in daylight, 

only for 1–2 days per week (Smith and Morgan, 2005). 

In their analysis of more recent data, Smith and Morgan 

(2005) found bird mortality to be highly variable in the British 

Columbia salmon gillnet fisheries; bycatch rates ranged 

between 0.019 and 0.219 birds per hour fished. Common 

Murres and Rhinoceros Auklets were the species most often 

reported caught, composing about 90 percent of the bycatch. 

Marbled Murrelets were reported caught in at least three 

fisheries. A high proportion of the birds caught was left 

unidentified and not salvaged. Smith and Morgan (2005) 

stressed that species-specific bycatch may be underestimated 

due to the high number of unidentified and non-salvaged birds.

The most detailed recent analysis of seabird bycatch 

from salmon gillnets in British Columbia is from the 7-

year (1995-2001) test fishery for chum salmon in Area 

21 off Nitinat Lake, southwest Vancouver Island in late 

September to early October (Smith and Morgan; 2005; J. 

Mitchell, Department of Fisheries and Oceans, unpub. data, 

1995–2001). Concentrations of murrelets are high in this area 

during summer but tend to be low during the months of the 

test fishery (Alan E. Burger, personal observation, 1995). The 

Nitinat fishery area is within 40 km of the Barkley Sound 

sockeye fishery studied by Carter and Sealy (1984). In total, 

the 1995–2001 data cover 106 days of fishing using 4–8 

vessels, 5,425 sets, and 10,248 hours of soaking (Smith and 

Morgan, 2005). A total of 392 birds were caught. Bycatch 

rates varied greatly among the years but averaged 0.092 ± 

0.063 (SD) birds per set (range = 0.040–0.183) or 0.054 ± 

0.042 (SD) birds per net-hour (range = 0.019–0.117). Out of 

295 identified birds, 6 were recorded as Marbled Murrelets 

(i.e., 2.03 percent). Most (89 percent) of the identified birds 

were Common Murres. If we assume that 2.03 percent of all 

birds, including those not identified, were Marbled Murrelets, 

then the estimated rate of mortality in this test fishery would 

be 0.0019 ± 0.0013 birds per set or 0.0011 ± 0.0008 murrelets 

per net-hour. Test fisheries probably do not reflect mortality 

rates in commercial openings (Smith and Morgan, 2005). 

More vessels are present in commercial fisheries, which may 

cause fewer birds to remain in the area, resulting in lower 

bycatch rates. However, commercial vessels generally do not 

use gear that might reduce fish bycatch (e.g., drop weed-lines, 

Alaska twist), some of which also might reduce incidental 

seabird mortality (J. Smith, Canadian Wildlife Service, oral 

commun., 2006). 

Smith and Morgan (2005) also summarize less-detailed 

data from other test, selective, or commercial gillnet fisheries. 

During an 11-day test fishery for coho salmon in Area 4, 1,834 

sets gave bycatch rates of 0–0.01 birds per set (average 0.004) 

of which 2 of the 5 identified birds were Marbled Murrelets 

(Smith and Morgan, 2005). This translates roughly to a mean 

catch rate of 0.0016 murrelets per set. In a sockeye salmon 

selective fishery in Area D, a total of 417 sets were made in 

9 days, representing 416 hours of fishing. Overall, 91 birds 

were caught giving an overall bycatch rate of 0.219 birds per 

net-hour, but none of the 86 identified birds was a Marbled 

Murrelet. Finally, in the Barkley Sound sockeye salmon 

commercial fishery, 126 sets were observed from a possible 

256 licensed vessels during two 1-day openings. Observers 

reported no bird bycatch and no other fishery data were 

available.

90 Status Review of the Marbled Murrelet in Alaska and British Columbia
Figure 23. Department of Fisheries and Oceans salmon gillnet license Area C—areas 1–10, subarea 

101–107 (from Smith and Morgan, 2005).

Figure 24. Department of Fisheries and Oceans salmon gillnet license Area D—areas 11–15 and 23–27 

(from Smith and Morgan, 2005). OFR2006_1387_fig23

Marine Habitat: Characteristics and Threats 91
OFR2006_1387_fig25

Figure 25. Department of Fisheries and Oceans salmon gillnet license Area E—areas 16–22, 28, 29 and 

121 (from Smith and Morgan, 2005).

Smith and Morgan (2005) estimated the total bycatch 

from the entire commercial gillnet fishery in British Columbia 

taking into account the total hours fished in 2001–04 (annual 

mean = 167,206 ± 7,369 [SD] set-hour) and the mean of the 

bycatch data from the three observed fisheries in 1995–2001 

(annual mean = 0.0723 ± 0.0652 [SD] seabirds caught per 

hour of fishing). This resulted in a predicted annual bycatch of 

12,085 seabirds (range = 1,129–24,002), of which 95 percent 

died. Assuming that the proportions of birds identified and the 

predicted total number of seabirds caught, are representative of 

‘normal’ commercial fishing, their analysis predicted as many 

as 552 Marbled Murrelets could become entangled each year. 

Increasingly, salmon gillnet fisheries in British Columbia 

are under pressure to be more selective and reduce the 

bycatch of non-target salmon species, marine mammals, and 

other taxa, including seabirds (Smith and Morgan, 2005). 

The DFO regulates fishery time, location, target species, net 

configuration, and soak time (the length of time that the net 

fishes). Most commercial salmon fisheries in British Columbia 

have very little observer coverage, with the exception of test 

(stock assessment), experimental (gear testing), and selective 

(species selectivity) fisheries, where observer coverage is 

high (approaching 100 percent in some cases), and all collect 

seabird bycatch data (Smith and Morgan, 2005).

There has not been the same intensive research effort 

made to reduce seabird bycatch in gillnet fisheries in British 

Columbia as there has been for gillnet fisheries in Washington 

(Melvin and others, 1999). Currently in British Columbia, 

the DFO is testing gillnets with no mesh in the upper 2 m, 

as well as other modifications aimed at reducing bycatch 

of marine mammals and sockeye salmon, but which also 

are likely to reduce seabird bycatch (Smith and Morgan, 

2005). Eliminating night and crepuscular gillnetting seems 

to have reduced bycatch of seabirds in the chum fishery off 

southwestern Vancouver Island (Smith and Morgan, 2005). 

The reduction in the abundance of target species and increased 

closures, have caused a decline in the annual salmon fishing 

effort and landings, and a series of commercial license 

retirement programs has has contributed to a decrease in the 

number of vessels fishing for salmon (Smith and Morgan, 

2005).

In summary, the available evidence suggests that risks 

of widespread and significant mortality to Marbled Murrelets 

from gillnets are currently low in British Columbia, but there 

are few data. The high mortality recorded in Barkley Sound in 

1979–80 (Carter and Sealy, 1984) and the strong impacts of 

bycatch in population simulation models (Beissinger,

1995a; Boulanger and others, 1999) are reminders that 

murrelets are highly vulnerable to gillnet fisheries. 

92 Status Review of the Marbled Murrelet in Alaska and British Columbia
Purse-Seiners

In Washington, two Marbled Murrelets were entangled 

in seine nets during a pilot study (Pierce and others, 1994). 

Purse-seine fisheries in Barkley Sound killed hundreds of 

Common Murres in 1979–82, but occurred in areas with few 

Marbled Murrelets, and no dead murrelets were recovered 

from this fishery (Carter and others, 1995). In July–August 

2000, fisheries observers recorded data for 135 purse-seine 

sets in four subareas in Area 4 off the Skeena River on the 

northern mainland (Smith and Morgan, 2005). No birds were 

reported caught, but observers were not trained to do bird 

observations and many did not report seabird bycatch data. 

Purse-seining in areas with high murrelet concentrations might 

cause significant mortality, but again there are too few data to 

make any conclusions on its impact. Murrelets tend to avoid 

boats and are therefore less at risk than Common Murres and 

Rhinoceros Auklets. 

Sports Fishery

There are anecdotal reports of Marbled Murrelets 

hooked on sports-fishing lures off Campbell River, in Barkley 

Sound, and in Clayoquot Sound (Campbell, 1967; Carter and 

others, 1995; Alan E. Burger, University of Victoria, personal 

observation, 2005). Many of these birds are released alive, but 

may suffer mortal injuries when removed from hooks. The 

numbers of birds caught and the likely impact of this fishery in 

British Columbia remains unknown, but requires investigation 

in areas where there is overlap between sports fishing areas 

and murrelet concentrations (e.g., in Barkley, Clayoquot, and 

Desolation sounds, off the West Coast Trail, and off Haida 

Gwaii [Queen Charlotte Islands]). Increased disturbance 

caused by the growing number of fast recreational fishing 

boats in nearshore waters is another concern (see section, 

“Effects of Vessel Disturbance”).

Aquaculture

Aquaculture within the nearshore waters frequented 

by Marbled Murrelets is increasing in British Columbia. 

Murrelets may be affected negatively by shellfish and 

finfish farms when these facilities are built in sheltered 

waters normally used for foraging and resting by murrelets. 

Disturbance from people and boats is the greatest problem, 

although there also might be highly localized reductions in 

prey due to fecal pollution from finfish facilities (Vermeer and 

Morgan, 1989 or mortality to prey fish (e.g., salmon smolts) 

caused by disease and parasites emanating from the fish 

pens (Krkosek and others, 2006). Potential conflicts between 

seabirds and aquaculture through disturbance and habitat 

changes were identified in Sechelt-Sunshine Coast, Campbell 

River-Desolation Sound, Barkley Sound-Alberni Inlet, 

Clayoquot Sound, Kyuquot Sound, and Queen Charlotte Strait, 

but in most coastal areas it was difficult to assess the degree 

of interference (Booth and Rueggeberg, 1989; Rueggeberg 

and Booth, 1989). Marbled Murrelets are common in all these 

identified areas, either seasonally or year-round. The numbers 

and size of aquaculture facilities in the British Columbia coast 

has increased greatly since the reviews done in the late 1980s.

Effects of Commercial Fishing on Prey

Alaska

The secondary effects of commercial fisheries on 

murrelets are mostly speculative and inferential. Several 

important forage fishes are not commercially fished in Alaska, 

and are barred from future commercial exploitation. The ban 

on exploitation of forage fishes, and the regulated take of 

‘protected’ species such as Pacific herring in the groundfish 

fisheries, were implemented following passage of the 

Magnuson-Stevens Fishery Conservation and Management 

Act in 1976 (Witherell and Pautzke, 1997; Witherell and 

others, 2000). The lack of a targeted fishery on forage fishes 

removes, at a minimum, direct competition between humans 

and murrelets for those resources. For regulation purposes, the 

NOAA-Fisheries considers forage species to include (among 

others) sand lance, capelin, and myctophids, all of which are 

important prey species for murrelets (this volume). However, 

other important prey consumed as juveniles by murrelets are 

fished commercially as adults, in particular Pacific herring, 

walleye pollock, and Pacific cod. 

One of the most important prey for Marbled Murrelets in 

Alaska is Pacific herring, and juvenile herring may be essential 

to successful chick rearing in some areas of Alaska (Kuletz, 

2005). The commercial herring fishery could have an impact 

on murrelets by reduction of local populations and harvest of 

herring roe on kelp. Harvest of herring in Alaska peaked in 

the 1930s at 125,000 metric tons per year, and this level of 

harvest may have contributed to a stock decline between the 

1950s and 1960s. Between the 1960s and 1970s, a foreign 

fishery in the Bering Sea created a second peak in herring 

harvest levels (Woodby and others, 2005). Since the 1980s, 

the primary fishery has focused on sac-roe and bait fisheries. 

Herring are an important food for a variety of marine species 

in Alaska. As a result, harvest levels have been managed 

conservatively by the State, but conflicts with other fisheries 

and marine mammals continue (Woodby and others, 2005). 

Another potential impact to herring stocks include discharges 

from pulp mills, which have been linked to herring mortality, 

particularly in Southeast Alaska (Woodby and others, 2005). 

In Prince William Sound, the murrelet population has 

declined in tandem with the herring biomass (Kuletz, 2005), 

and the cause of the herring decline in this region is not clear. 

The Prince William Sound herring population has fluctuated 

widely, with a peak estimated adult biomass in 1988 of about 

100,000 metric tons. The herring stock collapsed in 1993, 

Marine Habitat: Characteristics and Threats 93
declining from an estimated 16,082 metric tons in 1993 to a 

low of 6,384 metric tons in 2001 (Thomas and Thorne, 2003). 

There is no agreement on the cause of the collapse. In addition 

to the hypothesized competition with hatchery-raised salmon 

smolts, other perturbations include overharvest when stocks 

were low (Thomas and Thorne, 2003) and the 1989 EVOS 

(Paine and others, 1996; Spies and others, 1996).

Murrelets will feed on salmon smolt (Carter and Sealy, 

1986), and murrelet numbers increased at a fish hatchery 

in Prince William Sound for 4 days after release of smolts 

(Scheel and Hough, 1997). Salmon are not likely to be an 

important prey, at least for chick-rearing, because they are not 

an energetically high quality food (Van Pelt and others, 1997). 

Further, at least in Prince William Sound, salmon smolts 

have only a brief period of availability in bays and nearshore 

waters (Willette and others, 2001). The instigation of salmon 

hatcheries in Prince William Sound may have exacerbated the 

apparent decline of natural prey species such as herring and 

sand lance (Pearson and others, 1999). Beginning in 1977 and 

increasing throughout the 1980s, hatchery-reared pink salmon 

smolts were released in April to coincide with the spring 

plankton bloom. Since 1988, more than 500 million smolts 

have been released annually (Thomas and Thorne, 2003). 

Hatchery-reared salmon could potentially compete with other 

forage fish that feed on zooplankton, such as juvenile herring, 

and juvenile and adult sand lance (Pearson and others, 1999; 

Purcell and Sturdevant, 2001). 

Juvenile pollock are not often fed to murrelet chicks in 

Alaska (Kuletz, 2005), likely because of their low caloric 

value (Van Pelt and others, 1997). However, they are a 

common prey species consumed by adults (this volume). 

Pollock adults may reduce survival of juvenile pollock because 

of their cannibalistic feeding habits (National Oceanic and 

Atmospheric Administration, 2004). The largest fishery in 

Alaska is the pollock fishery, primarily in the Bering Sea, but 

they also are harvested in the Gulf of Alaska. Because adult 

pollock consume juvenile pollock as well as other forage 

species, and because adult pollock are a large proportion of the 

biomass in Alaska’s waters, one hypothesis is that harvesting 

pollock could reduce competition with other predators for 

forage species. This hypothesis was suggested by Hunt and 

Stabeno (2002), who found a positive relationship between 

Black-legged Kittiwake productivity and pollock catch levels 

in the Pribilof Islands. Energetic models for the Bering Sea 

suggested that reduction of the adult pollock biomass by 

10 percent could result in increased populations of many other 

species, including murres (National Oceanic and Atmospheric 

Administration, 2006). Such an effect would be less likely to 

have a noticeable impact on murrelet populations, since areas 

of pollock harvest generally are not frequented by murrelets.

Bottom trawling is one of the gear types used in Alaska 

groundfisheries, and has the potential to damage benthic 

habitats (Heifetz, 1997). Damage of benthic substrates could 

impact nearshore forage fishes, particularly sand lance, which 

burrow into sandy substrates (Robards and others, 1999b). 

However, bottom trawling does not occur in most state waters 

(within 3 nmi of shore), and no-trawl restrictions apply to 

haul-outs sites used by Steller’s sea lions, as well as areas near 

selected seamounts (Woodby and others, 2002). In addition, 

in July 2006, the Aleutian Islands Habitat Conservation Area, 

covering 279,114 mi2, was established (71 FR 36694, June 28, 

2006). This area (fig. 26) will be managed to protect benthic 

habitats, with sections closed to certain types of bottomcontact fishing. Together, these measures could be beneficial 

to murrelets in the Aleutian Island regions, and potentially 

other nearshore habitats throughout Alaska.

British Columbia

Of the common prey items taken by Marbled Murrelets, 

only Pacific herring are commercially exploited on a large 

scale in British Columbia. Herring populations were seriously 

depleted through over-fishing in the 1960s in many parts of 

British Columbia, but the impacts on bird populations were 

not studied. Herring stocks have recovered in some areas 

but remain low in other areas, and the effects of herring 

availability on Marbled Murrelets should be assessed in more 

detail. Quotas for the roe herring fishery (gillnets and seine) 

in 1997–2005 ranged from 26,200 to 30,497 tons (Department 

of Fisheries and Oceans Canada, 2006a). Most of this fishery 

occurs in the Strait of Georgia with smaller amounts off the 

west coast of Vancouver Island, the Prince Rupert area, the 

central coast, and Haida Gwaii (Queen Charlotte Islands) 

(Department of Fisheries and Oceans Canada, 2006a). A 

further 1,050 metric tons are harvested in the food and bait 

herring fishery in the Prince Rupert and Strait of Georgia areas 

(Department of Fisheries and Oceans Canada, 2006b). Herring 

eggs also are harvested by First Nations as spawn-on-kelp. 

Small baitfish, First Nations, and recreational 

fisheries also occur for anchovy, eulachon, and surf smelt 

(H. pretiosus), which are known to be taken as prey by 

murrelets (Burkett, 1995). There are no stock assessment 

programs for some of these species (e.g., surf smelt) and it is 

unclear how large the stocks are in British Columbia.

One of the most important prey species for murrelets 

in British Columbia is Pacific sand lance. There is no 

commercial fishery for this species in British Columbia, but 

Ammodytes spp. are fished to produce fish-meal in many other 

parts of the world, and demand for fish-meal used in finfish 

aquaculture might lead to a fishery in British Columbia. There 

is currently no restriction on exploitation of forage species in 

British Columbia.

94 Status Review of the Marbled Murrelet in Alaska and British Columbia
Murrelets also take euphausiids (krill) and there is a 

small krill fishery in British Columbia taking five species, but 

dominated by Euphausia pacifica (Department of Fisheries 

and Oceans Canada, 2004). The krill are frozen and used 

primarily in the manufacture of fish food. The fishery is 

centered in the Strait of Georgia and nearby coastal inlets (e.g., 

Bute, Knight, Toba Inlet, Howe Sound) and usually involved 

seven to eleven vessels (Department of Fisheries and Oceans 

Canada, 2004). The quota and landings have been stable 

around 500 tons for many years (fig. 27). Given the increase in 

salmon-pen aquaculture in British Columbia, and the support 

given to this industry by the provincial government, there are 

likely to be pressures to expand the krill fishery and increase 

quotas. An intensive euphausiid fishery might affect murrelets 

directly, because they eat large euphausiids, or it could disrupt 

the food webs on which they depend.

Effects of Vessel Disturbance

Kuletz (1994) and Piatt and Naslund (1995) first raised 

concern about the potential effects of vessel disturbance on 

Marbled Murrelets in Alaska. This issue was not addressed in 

the Marbled Murrelet Recovery Plan for Washington, Oregon, 

and California (U.S. Fish and Wildlife Service, 1997), but 

was briefly mentioned in other recent status reviews (Burger, 

2002; McShane and others, 2004). Concerns about the effects 

of vessel disturbance have developed in recent years, due to 

increases in vessel traffic in many remote areas of Alaska and 

British Columbia. However, it has been difficult to determine 

rates and degree of potential impacts to seabirds, including 

Marbled Murrelets. Preliminary studies have documented 

limited effects (see below) but more work is needed to study 

this problem. Because boat traffic is inevitable in many areas 

frequented by murrelets, it will be useful to determine to 

what degree murrelets can habituate to boat traffic. Anecdotal 

reports suggest that murrelets may habituate in some locations 

(McAllister, unpub. data; cited by Strachan and others, 1995). 

However, other species have shown only limited ability to 

habituate to disturbances (Burger and Gochfeld, 1990; Bleich 

and others, 1994). 

Studies on a variety of birds indicate that disturbance 

from motorized vessels can result in decreased reproductive 

success (e.g., brooding waterfowl; Keller, 1991; Mikola and 

others, 1994), behavior changes with consequent energetic 

impacts (e.g., shorebirds; Burger and Gochfeld, 1991; or 

waterbirds; Schummer and Eddleman, 2003), habitat loss (e.g., 

Figure 26. Outline of the Aleutian Islands Habitat Conservation Area and other areas with trawl 

restrictions. 

OFR2006_1387_fig26

170°0'0"E

175°0'0"E

175°0'0"E

180°0'0"

180°0'0"

175°0'0"W

175°0'0"W

170°0'0"W

45°0'0"N

50°0'0"N

50°0'0"N

55°0'0"N

°

Aleutian Islands Habitat Conservation Area

Aleutian Islands Coral Habitat Protection Areas

Bowers Ridge Habitat Conservation Zone

Open to Bottom Trawling

Areas shown in yellow are closed to bottom trawling (279,114 nm2)

Areas shown in green are open to bottom trawling (12,423 nm2

)

Areas shown in red are closed to all bottom contact fishing gear (110 nm2

)

Areas shown in purple are closed to mobile bottom contact fishing gear (5,286 nm2

)

0 40 80 120 160Nautical Miles

Marine Habitat: Characteristics and Threats 95
stop-over sites associated with waterfowl migration; Kaiser 

and Fritzell, 1984), or reduced access to favored foraging 

areas (Ronconi and Cassady St. Clair, 2002). However, some 

marine and waterbird species eventually habituate to the 

operations of vessels and noise (e.g., gulls; Burger and Galli, 

1987, or wading birds; Stolen, 2003). Some studies which 

reported boating impacts to marine and waterbird species 

were located in areas with high levels or rates of boat traffic 

(e.g. Mississippi River; Korschgen and others, 1985; or Great 

Lakes; Knapton and others, 2000). In general, large, loud, 

or fast boats have been shown to have greater impacts than 

smaller, quieter, or slower boats. Responses to disturbance also 

vary with environmental factors such as habitat type, tides, 

time of day, and weather (review in Agness, 2006).

Studies of Vessel Disturbance and Murrelets

Responses to vessel disturbance are species-specific, 

and there is little empirical data on the influence of vessels on 

Marbled Murrelets. Several studies reviewed below indicate 

that Brachyramphus murrelets are displaced by vessel traffic, 

and possibly impacted energetically. However, the long-term, 

population-level, or regional implications of this immediate 

impact remain unknown. 

During USFWS boat-based surveys in south-central 

Alaska, 93–95 percent of murrelets were initially observed on 

the water (Kuletz and others, 2003a; U.S. Fish and Wildlife 

Service, unpub. data, 1989–2004), indicative of the diving 

and surface-resting behavior that make murrelets susceptible 

to disturbance from vessel traffic. For 2 years following the 

1989 EVOS, areas which previously had little vessel activity 

saw relatively high vessel traffic during response operations 

and damage assessment studies. Within the spill zone, Kuletz 

(1996) found significant, negative relationships between 

numbers of boats and Marbled Murrelet densities at Naked 

Island in Prince William Sound and Kachemak Bay in Cook 

Inlet. Low-flying aircraft also were negatively correlated 

with murrelet counts in two bays frequented by float planes 

and helicopters participating in the spill response (Kuletz, 

1996). In Southeast Alaska, Speckman and others (2004) 

observed that the approach of small boats caused Marbled 

Murrelets holding fish (presumably meant for their chicks) to 

dive and then swallow the fish. This behavioral response has 

implications for reproductive success as well as energetic cost 

of chick-rearing for murrelets. 

In Alaska, recent studies of vessel disturbance on 

murrelets have focused on Kittlitz’s Murrelets because 

this species is a candidate for listing under the ESA 

(71 FR 53755). Kittlitz’s are physically and behaviorally 

similar to Marbled Murrelets, thus study results provide 

insights into possible disturbance effects on both species. For 

example, in Prince William Sound, a 2001 pilot study found 

that Kittlitz’s Murrelets were at least temporarily displaced 

by boat traffic. When boats were present, fewer birds made 

foraging dives and more birds flew off the water compared to 

undisturbed focal groups (Kuletz and others, 2003a). 

In Prince William Sound, S. Stephensen (U.S. Fish 

and Wildlife Service, unpub. data, 2005) tested the effects 

of small boat transit on Brachyramphus murrelet density 

(93 percent Marbled Murrelets). Stephensen conducted 

paired comparison counts of murrelets from a 25-ft vessel in 

Harriman Fjord, Prince William Sound, Alaska, in July 2004. 

Each pair of murrelet counts consisted of an initial and return 

transits (n = 23 pairs). For all paired transects, there was a 

significant decrease (t = 2.58, df = 22, P = 0.02) in the number 

of murrelets between initial ( = 27.7 ± se 5.0 murrelets) and 

return ( = 18.9 ± 3.0) runs, suggesting that murrelets had left 

Euphausiid fishery in British Columbia

0

100

200

300

400

500

600

700

800

900

19831984198519861987198819891990199119921993

199419951996

1997199819992000

20012002

Tonnes .

Quota

Landings

* landing data 

witheld

*** *

Figure 27. Statistics on the fishery for euphausiids (krill) in British Columbia (data from Department of 

Fisheries and Oceans Canada, 2004).

96 Status Review of the Marbled Murrelet in Alaska and British Columbia
the immediate area. In Washington, Hamer and Thompson 

(1997) also found displacement of Marbled Murrelets during 

vessel activity, with 68 percent (n = 50 birds) of murrelets 

moving a short distance as a vessel approached. Of these, 11 

percent of the birds moved more than 30 m. 

A more extensive study was conducted in Glacier Bay 

National Park and Preserve (GBNPP; Agness, 2006). Agness 

found that vessel activity overlapped spatially and temporally 

with Kittlitz’s Murrelets in Glacier Bay; since Marbled 

Murrelets coincide with Kittlitz’s, they would face the same 

influences in those areas, as well as other areas not occupied 

by Kittlitz’s. Declines in nearshore density of murrelets 

attributed to vessel disturbance, though significant, were 

temporary, typically recovering within the day. Behavioral 

changes of Kittlitz’s Murrelets during vessel activity included 

increased flight, with a mean of 30 percent of birds taking 

flight. On days with high vessel traffic, birds showed an 

increase in diving behavior, which Agness (2006) suggested 

was due to lower energetic costs of diving compared to flying 

from disturbance. Based on models of murrelet behavior 

and energetics, Agness (2006) concluded that Kittlitz’s had 

a net energy loss due to vessel disturbance, but the impact 

may only be significant under ‘maximal vessel conditions.’ 

In her models, maximal vessel conditions were based on the 

2004 daily vessel limit imposed by the USNPS in Glacier 

Bay (see below). Birds not holding fish for their chicks 

were more likely to fly in response to vessels, and thus the 

model indicated significant energetic costs (equivalent to 6.5 

Pacific sand lance per day) to most Kittlitz’s Murrelets during 

maximal vessel activity. 

A recent study (Hentze, 2006) off southwestern 

Vancouver Island, British Columbia, an area with high 

volumes of recreational fishing activity, examined the impacts 

of vessel disturbance on four seabird species, including 

the Marbled Murrelet. Marbled Murrelets tended to react 

(dive or take flight) more readily to approaching boats than 

Common Murres and Rhinoceros Auklets, but less so than 

Pelagic Cormorants. Murrelets showed a rapid increase in the 

proportion of birds reacting as the boat approached starting 

at 40 m, until almost 90 percent of the birds reacted when the 

boat was within 5 m. Overall, at all passing distances 59.8 

percent of murrelets showed no reaction, 31.0 percent dived 

and 0.2 percent took flight (n = 3,080 observations from a 

moving boat). From a small sample of six birds flushed by a 

boat and tracked with a surveyor’s theodolite, Hentze (2006) 

showed that the mean flight distance was 116 m (range = 

51–208 m), mean flight time was 40 s (range = 8–130 s), and 

the time to resume foraging after landing was 65 s (range = 

24–171 s). In this study, the tendency of murrelets to leave a 

site when disturbed by boats depended on sea state, group size, 

and average bird density. Rougher seas and higher densities 

of murrelets in the surrounding area increased departure rates 

for murrelets, whereas larger group sizes reduced departures 

following disturbances. Because single birds were more likely 

to flush, and single birds may be more likely to be breeding 

individuals (Mack and others, 2002), Hentze suggested that 

boat disturbance would disproportionately affect breeding 

birds. Hentze (2006) concluded that 150 m buffer zones might 

be sufficient to reduce boat disturbance effects on Marbled 

Murrelets. 

In an overlapping study made in the same place and time 

as Hentze’s (2006) study, Bellefleur and others (2005) showed 

that boat speed had a significant effect on the reactions by 

Marbled Murrelets. On average, murrelets flushed at 40 m 

when approaching boats were traveling at speeds greater than 

29 km/h (16 knots) but flushed at 28 m at speeds of less than 

12 km/h (7 knots). Size of boat (7 m vs. 5 m hull length) had 

no significant effect at the speeds tested.

Vessel Activity in Alaska

Boat traffic in Alaska varies seasonally, regionally, and 

in vessel size and activity (i.e., commercial fishing, oil rig 

support, cargo, recreational, cruise ships). In National Parks, 

some restrictions on vessel activity have been established to 

minimize impact to wildlife. Areas with relatively high vessel 

activity that overlap with relatively high murrelet densities 

include Kachemak Bay–lower Cook Inlet, areas of Kodiak 

Island, Kenai Fjords National Park and Preserve (KFNPP), 

Prince William Sound, GBNPP, and areas adjacent to coastal 

cities in Southeast Alaska. In addition to commercial shipping 

patterns at industrial ports (see section, “Oil Spills”, above), 

specific information on vessel activity is available for Prince 

William Sound, KFNPP, and GBNPP. 

Prince William Sound

Both fishing and tourism-related vessel activity increases 

during the summer months in Prince William Sound, and 

thus coincides with peak murrelet densities in Prince William 

Sound during their breeding season. Fishing vessel activity 

in Prince William Sound increased during the 1980s with the 

establishment of salmon hatcheries. In addition, tourism has 

increased since the 1980s, with related vessel traffic heaviest 

in the fjords with tidewater glaciers (Murphy and others, 

2004). During summer 2001, Kuletz and others (2003a) 

examined boat traffic and murrelet density in five fjords of 

Prince William Sound. During their surveys, they found three 

times more boats in shoreline waters (<200 m from shore) than 

in mid-inlet waters (>200 m offshore), but relative to kilometer 

traveled (because of highly convoluted shoreline routes), boat 

density (boats per km) was actually slightly higher in mid-inlet 

waters. Boat activity increased after May and peaked in July. 

Boat traffic patterns were similar in a USFS study in 2001 

(U.S. Fish and Wildlife Service, unpub., data, available in 

Kuletz and others, 2003a), and corroborate the USFS results 

from earlier 1996–98 studies (Murphy and others, 2004). 

Vessel traffic leaving Whittier is heaviest in Passage Canal and 

Port Wells, and generally decreased with distance from ports 

such as Whittier (fig. 28). 

Marine Habitat: Characteristics and Threats 97
Between 1996 and 1998, cruise ship and State ferry 

activity was highest in Passage Canal, but also was heavy 

(769–1,151 trips between May–September) in College Fjord, 

and Long, Columbia, and Heather bays (Murphy and others, 

2004). Harriman Fjord cruise ship and ferry traffic was slightly 

lower at 385–768 trips during the same time period. Most 

commercial fishing trips departing from Whittier traveled to 

College Fjord (526–2,623 trips between June and September; 

Murphy and others, 2004). 

National Parks

In Alaska, bays and fjords with tidewater glaciers are 

popular tourist destinations. Two such sites occur in the 

KFNPP and GBNPP. The southern Kenai Peninsula is difficult 

to access, but KFNPP was established in 1980, and at least two 

of the park’s fjords, Aialik Bay and Northwestern Fjord, have 

become primary destinations for park visitors. Vessel traffic 

from Seward to these bays has increased to more than 75,000 

people per annum, with travel modes ranging from kayak to 

100-ft tour-vessels to cruise ships. 

In 1979 and 1980, studies documented one to two vessels 

per day in upper Aialik Bay. By 1996, multiple vessels visited 

Aialik Bay daily (U.S. National Park Service, 2004). Concerns 

about disturbance of harbor seals (Phoca vitulina) prompted 

study of the potential impacts of vessel traffic on seals in 

KFNPP (Tetreau, 1998). Voluntary operating guidelines for 

tour vessels were adopted based on study results. Viewing 

guidelines for marine mammals were adopted in 2001, and 

following further study, more stringent guidelines were 

established in 2003 (U.S. National Park Service, 2004). These 

guidelines reduced vessel speed in the upper portions of bays, 

benefiting all marine wildlife.

Glacier Bay became a National Monument in 1925 

and a National Park in 1965. Glacier Bay was designated 

a Biosphere Reserve in 1986, which supported efforts to 

regulate activities in the park. Visitation in Glacier Bay grew 

to more than 100,000 people annually by the 1970s. Most 

tourists visit GBNPP by cruise ship. Commercial fishing 

also increased during the 1980s, but was phased out in the 

late 1990s (Catton, 1995). Currently, GBNPP regulates the 

numbers of boats allowed into the park and restricts entrance 

to designated areas. In 2004, the daily limit into GBNPP 

between May and September was 2 cruise ships, 9 large tour 

boats, and 25 private recreational motor vessels (Agness, 

2006). In 1999, a tour boat accident resulted in a multi-agency 

response that involved a large number of boats in the affected 

bay for several weeks (K. Kuletz, U.S. Fish and Wildlife 

Service, personal observation, 1999).

State Ferry System

The Alaska State Marine Highway provides ferry service 

to remote communities throughout southeast and south-central 

Alaska, typically operating eight ferries. Two new high-speed 

ferries were recently added to the fleet, and both have operated 

in Southeast Alaska. The M/V Fairweather started service 

in 2004, and the M/V Chenega, launched in 2005. Four high 

speed ferries were originally designed, but as of February 

2006, plans for completion the remaining two were on hold. 

Effects of Research Activities

Studies of Marbled Murrelets typically are conducted in 

the marine environment. Studies involve surveys from boats, 

but also more intrusive activities, involving collections, and 

capture and handling. The total murrelet mortality attributed to 

research activities is small, but is reviewed here for the record. 

Figure 28. Vessel traffic in western Prince William Sound, based on studies by the U.S. Forest Service and 

the U.S. Fish and Wildlife Service. 

OFR2006_1387_fig28

98 Status Review of the Marbled Murrelet in Alaska and British Columbia
Marbled Murrelets have been collected by shotgun 

for diet and contamination studies in Alaska, for a total of 

346 birds collected between 1969 and 2001 (this volume). 

Capture and banding of murrelets is a potentially disruptive 

activity to individual birds and their breeding success (Bradley 

and others, 2004). In Alaska, capture of murrelets has been 

attempted with dip-nets and spotlights (Quinlan and Hughes, 

1992; Whitworth and others, 2000; Newman and others, 

2006), mist-nets set above the water (Burns and others, 1994; 

Kuletz and others, 1995a), gillnets set below the water’s 

surface (Quinlan and Hughes, 1992), and net guns (Quinlan 

and Hughes, 1992). Some known and suspected mortality 

occurred from these studies. 

The first radio-telemetry study in Alaska was in Southeast 

Alaska, in 1983 and 1984, when 17 Marbled Murrelets were 

captured and fitted with radio tags (Quinlan and Hughes, 

1992). During this study, only seven birds survived beyond 

release. Attempts at surgically implanting radios or use of 

external harnesses were unsuccessful. Excessive preening 

after release also may have led to predation by Bald Eagles 

immediately after release. During radio-telemetry studies 

in 1993 (Burns and others, 1994) and 1994 (Kuletz and 

others, 1995a), 60 birds were captured and fitted with radio 

transmitters. No birds were lost during capture and handling, 

but the remains of three were found, and predation by Bald 

Eagles was suspected. During the 1999 study, at least one 

radio-tagged murrelet death was associated with Bald Eagle 

predation or scavenging (Whitworth and others, 2000).

In 2005, in Port Snettisham, Southeast Alaska (Newman 

and others, 2006), 45 Marbled Murrelets were captured and 

fitted with radio transmitters and another 11 were sampled 

for blood-health assessments. At least one tagged bird was 

believed to be killed by predation. During the continuation 

of this study in 2006, another 40 birds were captured. At 

least 15 were found dead, again with predation by Bald 

Eagles suspected or documented (K. Nelson, OSU Wildlife 

Cooperative Research Unit, oral commun., 2006). This level 

of mortality was unusual for murrelet telemetry studies, and 

similar efforts have successfully tagged hundreds of murrelets 

from British Columbia to California. The researchers 

speculated that murrelets were compromised by the unusually 

high numbers of Bald Eagles present in the capture area, and a 

late, cold spring (K. Nelson, oral commun., 2006).

The total number of murrelets known or potentially 

affected by capture and tagging is not significant relative to 

the Alaska population. However, the large population of avian 

predators in Alaska may make radio-telemetry more risky 

than farther south, where predation has not been reported as a 

frequent problem (Bradley and others, 2004; Peery and others, 

2004a). Future research in Alaska may need to consider 

ways to mitigate the apparently high predation rate of radiotagged murrelets in Alaska. Another consideration is that the 

predation of radio-tagged murrelets reflects a generally higher 

avian predation on murrelets in Alaska.

Nesting Habitat: Characteristics, 

Threats, and Trends

Marbled Murrelets’ dependence on large, old-growth 

coniferous trees for nesting habitat has been well-documented 

(Ralph and others, 1995; Burger, 2002; McShane and others, 

2004). In this section, we review what is known about the use 

of terrestrial habitats by Marbled Murrelets in Alaska and 

British Columbia. We briefly review the methods by which 

terrestrial habitat use patterns of Marbled Murrelets have been 

studied. We then describe how our understanding of nesting 

habitat characteristics has grown, as more nests have been 

found, and more sophisticated modeling studies have been 

undertaken. We then synthesize existing information about 

the amount and distribution of habitats suitable for nesting. 

We consider threats to nesting habitats from anthropogenic 

sources, and briefly address natural ecological processes. 

Finally, we address the general land management practices 

that may affect the future of Marbled Murrelet nesting habitat. 

Defining nest habitat for murrelets in Alaska has proven 

challenging. There is little information available compared 

to what is known for murrelets in the southern portion of 

their range. Although few murrelet nests have been found 

and documented in Alaska, Marbled Murrelets appear to use 

a broader range of habitats in Alaska than at lower latitudes. 

For example, ground-nesting birds occur in both forested 

and unforested areas, and tree-nests have been found within 

a greater range in tree sizes. Because ground nests of the 

Kittlitz’s Murrelet can be mistaken for those of Marbled 

Murrelets, the relative occurrence of ground nesting for 

Marbled Murrelets may have been underestimated (Day and 

others, 1983). 

Within Alaska, offshore surveys of murrelets suggest that 

about 97 percent of the population occurs near lands with at 

least some old-growth forest cover, and thus Piatt and Ford 

(1993) estimated that about 3 percent of the Marbled Murrelet 

population nests on the ground. The northernmost extension of 

the north temperate rain forest extends from Southeast Alaska, 

north along the Gulf of Alaska, and throughout south-central 

Alaska. However, the extent of forested habitat is highly 

variable in the more northern and western edges of this biome. 

Areas considered “forested” include unforested habitat, and 

tree line may extend only 200 m above sea level and a few 

kilometers inland (Kuletz and others, 1995a). The coastal 

areas of the northern Gulf of Alaska, including Prince William 

Sound, the Kenai Peninsula, and Kodiak Island, appear to be 

zones where both tree- and ground-nesting occur, although 

evidence suggests that forested habitat is preferred (Kuletz 

and others, 1995a; Marks and Kuletz, 2001). The remainder of 

the murrelet population in southwestern Alaska including the 

Alaska Peninsula and the Aleutian Islands, have only groundnesting opportunities because most of the area is unforested 

(see section “Amount and Distribution of Nesting Habitat in 

Alaska and British Columbia” below), and murrelet densities 

are comparatively low in these regions (Piatt and Ford, 1993). 

Nesting Habitat: Characteristics, Threats, and Trends 99
Methods for Surveying Use of Terrestrial 

Habitats by Marbled Murrelets

Two methods have been used to systematically study 

terrestrial habitat use of Marbled Murrelets: (1) audio-visual 

dusk/dawn watches; and (2) radar surveys. The audio-visual 

surveys are useful for providing a stand-scale presence/

absence determination (Kuletz and others, 1995b), however, 

they may underestimate the number of birds using an area by 

75 percent or more (Cooper and Blaha, 2002; Lank and others, 

2003). Furthermore, they are biased towards landscapes easily 

accessible to observers (Lank and others, 2003) and this may 

be important in remote Alaska. Radar surveys, although not 

yet widely used in Alaska, have been used to assess movement 

between marine and terrestrial sites at the landscape-scale 

(reviewed in Burger, 2002). Radar counts of murrelets 

indicate the value of each watershed as nesting habitat and 

show watershed-level habitat associations (Burger, 2001b). 

However, the steep and rugged topography in Alaska has 

caused problems with using the radar method. Both methods 

are reviewed below.

Audio-visual surveys used to assess inland activity at 

dusk or dawn has been a standard method used to determine 

if murrelets were ‘occupying’ an area for nesting (Rodway 

and others, 1993; Nelson, 1997). During their inland flights, 

murrelets often vocalize, allowing aural detection, or they 

may be visually identified flying above or below the canopy 

(each observation is termed a ‘detection’). Murrelets usually 

exchange incubation duties with their mate before dawn, but 

also make inland flights to nesting areas prior to breeding and 

post-breeding (Nelson, 1997), or even during winter (Naslund, 

1993). 

Dawn watches for murrelet activity have been conducted 

sporadically in Alaska, partly because lack of roads and 

remote, difficult terrain make large-scale studies expensive 

and logistically complicated. Two major efforts have occurred. 

The first concerted effort to monitor dawn murrelet activity 

occurred from 1990 to 1993. This study was implemented 

following the EVOS to identify lands for possible purchase as 

a means of protecting habitats used by injured species, such as 

the Marbled Murrelet (Kuletz, 1997). The goals of the study 

were to define murrelet nesting habitat in south-central Alaska, 

and to identify specific tracts of land of high value to murrelets 

(see section, “General Nesting Habitat Characteristics”). 

The other major effort was in the 1990s by the USFS in the 

Tongass National Forest. The USFS conducted dawn watches 

as part of an effort to categorize forest lands for management 

and planning purposes. 

In Southeast Alaska, four sites were surveyed over the 

course of 2-3 years to detect seasonal patterns of Marbled 

Murrelet activity and to assess the efficiency of survey 

protocols (Brown and others, 1999). They detected Marbled 

Murrelets throughout the year, however, detection rates were 

highest in July, which corresponded with the breeding season, 

and there were no detections in September and October, 

which corresponds with the molting period. Their analysis 

showed that a revised survey protocol for Southeast Alaska 

would optimize detection rates for the amount of effort spent. 

They also found that winter surveys were hardest to perform 

accurately because birds were more likely to be absent from 

the forest and because surveys are harder to conduct in harsh 

weather.

Smith and Harke (2001) conducted point count surveys 

along forested sections of road in Southeast Alaska to quantify 

spatial and temporal variability in Murrelet detections and to 

estimate the effort required to detect changes in detections 

over time. They observed a high degree of spatial and temporal 

variability in Murrelet detections. They found there was a 

90 percent probability of documenting a 10 percent annual 

decline in detections in 6 years by making 12 annual visits to 

22 dawn survey stations spaced ≥1.6 km apart. The authors 

suggested that sampling effort could be reduced without 

reducing power by sampling every second or third year. 

The second method used to study inland murrelet activity 

has been radar surveys. Marine radar has proven more accurate 

than dawn watches to monitor inland flights of murrelets. 

Audio or visual observations can drastically underestimate the 

numbers of murrelets flying into a watershed (Cooper, 1993; 

Burger, 2001b; Cooper and others, 2001; Cooper and Blaha, 

2002). Radar surveys also are more accurate at detecting 

changes in murrelet abundance among years, and thereby 

may indicate changes in the proportion of birds attempting to 

breed (Burger, 2001b; Cooper and others, 2001). Cooper and 

others (2006) found that small annual declines in murrelet 

populations were harder to detect with certainty using radar 

surveys. A sampling period of 11–15 years would be needed 

to detect an annual decline of 2–4 percent with ≥80 percent 

power.

In Alaska, Cooper (1993) used marine radar in July 1993, 

at six bays in the KFNPP. In paired comparisons with standard 

visual observers, radar detected as much as 1.7 times as many 

murrelets as the human observer (Cooper, 1993). The radar 

was limited, however, in detecting murrelets once they flew 

past the shoreline. Because of the area’s steep topography, 

conditions were not ideal for using radar. Typically, marine 

radar is used where a wide river mouth creates an open 

viewing area at the base of a watershed (Cooper and others, 

2001). Because the sites in Kenai Fjords were randomly 

selected, the radar operator, based on an anchored vessel, 

could not select the optimum site from which to conduct 

surveys (Cooper, 1993). With improved radar units and proper 

selection of sites (Burger, 2001b), marine radar could be a 

useful and cost effective tool in the remote coastal areas of 

Alaska. 

Five radar studies in British Columbia (reviewed by 

Burger and others, 2004a) showed significant positive 

correlations between numbers of murrelets and areas of 

suitable habitat per watershed, although the measures of 

100 Status Review of the Marbled Murrelet in Alaska and British Columbia
habitat differed among the studies. These data provided 

the first strong evidence that the watershed populations of 

Marbled Murrelets are directly proportional to the areas 

of old-growth forest available. There was no evidence that 

murrelets pack into remnant old-growth patches in higher 

densities as areas of old growth are reduced by logging. 

Breeding populations of murrelets were therefore predicted to 

decline as areas of old-growth decrease. Densities (murrelets 

per area of habitat) derived from the radar counts were 

significantly higher on the west of Vancouver Island (0.090 

± 0.060 SD birds per ha of likely habitat) than on the British 

Columbia mainland coast (0.045 ± 0.039 birds per ha) when 

the habitat classified as good was considered in each study 

(Burger and others, 2004a). These density estimates are 

useful for management, either for estimating areas of habitat 

needed for specific populations of murrelets, or conversely for 

estimating the numbers of birds a specific area can support. 

General Nesting Habitat Characteristics

Prior to the early 1980s, only eight Marbled Murrelet 

nests had been found throughout its range, and all but two 

were ground nests (Day and others, 1983). As of 1996, well 

documented nests in Alaska include 19 tree nests (table 26) 

and 15 ground nests (table 27; DeGange, 1996). The relatively 

high number of ground nests was likely due to the greater 

possibility of finding a ground nest opportunistically. A few 

nests have been on or under large tree roots, with mossy 

substrates, and near a cliff ledge (Ford and Brown, 1995).

Between 1991 and 1993, 15 murrelet nests were found in 

Prince William Sound, Kenai Fjords, Kodiak, and Afognak 

Island using dawn watch methods (Naslund and others, 1995; 

Marks and Kuletz, 2001). Between 1983 and 2006, radio 

telemetry was used to locate 6 nests and 10 suspected nest 

sites (Quinlan and Hughes, 1990; Kuletz and others, 1995b; 

Whitworth and others, 2000; K. Nelson, oral commun., 2006). 

In addition, DeGange (1996) compiled 30 records of potential 

nest sites (summarized in table 28). Of these, five were 

unconfirmed ground nests and 11 were unconfirmed tree nests; 

the remaining observations had no supporting information as 

to nest type. 

The most recent effort to locate Marbled Murrelet nests 

in Alaska has been in the Snettisham area of Southeast Alaska, 

using radio telemetry (Newman and others, 2006). In 2005, 

this study found one potential nest site in a forested area. 

In 2006, two potential nest sites were found on cliffs near 

forested habitat, but the nests could not be reached because of 

terrain (K. Nelson, Oregon State University, oral commun., 

2006). 

The most geographically extensive examination of 

potential nesting habitat in Alaska relied on dawn activity 

levels of murrelets as an index of habitat suitability (Kuletz 

and others, 1995a). Between 1991 and 1993, dawn watches 

were conducted in Prince William Sound, Kenai Fjords 

National Park and Afognak Island, Alaska (n = 262 sites). 

The highest activity levels were associated with the heads of 

bays where there were large trees with high epiphyte cover. 

The best model predicting nesting behavior (circling above or 

flying below canopy) included location relative to the head of 

a bay, tree diameter and number of potential nesting platforms 

per tree. 

Among the three subregions, Prince William Sound 

sites had the lowest detection level, with 23.8 ± 3.11 

detections/survey (± SE); followed by Kenai Fjords, with 

29.9 ± 5.78 detections/survey (± SE); while Afognak Island 

had exceptionally high detection levels, with 38.4 ± 5.27 

detections/survey (± SE) (Kuletz and others, 1995a). The 

lower inland detections in Prince William Sound were 

attributed to the greater amount of available habitat there, 

compared to Kenai Fjords. Trees on Afognak Island had 

the largest number of mossy potential nest platforms. The 

surrounding waters also had relatively high numbers of 

Marbled Murrelets; 1992 boat surveys on the northern 

and western sides of Afognak Island estimated more than 

5,000 Marbled Murrelets were present on the water (Fadely 

and others, 1993).

Analysis of a subset of the above data (n = 72 sites), 

from three islands in the Naked Island group in central Prince 

William Sound, showed that murrelet activity was significantly 

higher in stands of large trees and moderate to high volume 

classes, with 0.50 (± 0.22) to 1.00 (± 0.34) subcanopy 

behaviors/site at moderate volume classes compared to 0.06 

(± 0.06) and 0.32 (± 0.22) subcanopy behaviors/site at low 

and high volume classes, respectively (Kuletz and others, 

1995c). Occupied behaviors were in forests with average tree 

diameter greater than 46 cm. Although these trees were not 

large compared to trees in regions farther south (McShane and 

others, 2004), the trees were more than 200 years old (U.S. 

Forest Service, Glacier Ranger District, Anchorage, Alaska, 

unpub. data, 2006), and typically were the largest in the forest 

stand. Analysis of another subset of the data, encompassing 84 

sites throughout the entirety of Prince William Sound, found 

that murrelet activity levels were highest in forests with trees 

greater than 28 cm diameter (the cut-off size in a timber type 

land coverage). Murrelet activity levels were significantly 

higher at the heads of bays, with the exception of glaciated or 

recently deglaciated bays (Marks and others, 1995). 

In Kenai Fjords, which is undergoing recent and rapid 

deglaciation, more of the coastal land base is unforested. 

Thus, the randomly selected dawn watch sites in Kenai Fjords 

occurred more frequently in non-forested habitats. Unlike in 

Prince William Sound and Afognak, murrelet detection levels 

in Kenai Fjords were highest near the outer promontories 

and lowest in the inner bays (Marks and Kuletz, 2001). This 

was likely because more forests and larger trees occur near 

the promontories, whereas the inner bays were often treeless, 

having been glaciated until after 1900 (Marks and Kuletz, 

2001). Among the non-forested sites, murrelet activity was 

higher in areas that had been ice-free since 1900, where there 

was more ground cover such as lichen and alder (Alnus spp). 

Nesting Habitat: Characteristics, Threats, and Trends 101
Characteristics Southeast Prince William Sound Kenai Peninsula Cook Inlet and Kodiak

Number of nests 2 3 5 5

Slope (°) 54 (38-70) 49 (25-85) 44 (19-90) 10

Elevation (m) 198 (195-200) 62 (7-180) 238 (20-710) 239 (68-690)

Aspect W,SW SW,W,NW N,NW,S,SE N,NE,SE,SE/S

Distance to coast (km) 7.8 (2.5-13.0) 0.47 (0-1.0) 0.33 (0-1.0) 1.6 (0.08-6.2)

Located near forest Yes 1-Yes, 2-No 1-Yes, 4-No 1-Yes, 4-No

Table 27. Characteristics of Marbled Murrelet ground nests in Alaska.

[Adapted from data in DeGange, 1996. Range of values in parentheses] 

Summary of suspected nest site characteristics Southeast Prince William 

Sound

Kenai

Peninsula

KodiakAfognak

Total number of reports 9 10 2 9

Nest type Unconfirmed ground nest1 0 4 1 0

Unconfirmed tree nest2 3 5 0 3

Evidence Adult observed3 1 5 0 3

Chick found4 2 3 1 6

Egg or eggshell fragments found 7 2 0 1

Records where information on forest cover was available

General cover type Area was forested 4 5 1 9

Not forested (grass or shrub) 4 1

Tree types (where noted) Sitka spruce tree 7

Western red cedar 1

Spruce-hemlock forest 1

Conifer forest 3

1

Found by flushing adult, or eggs found, and one via telemetry.

2

Found by radio-tagged birds flying into area or tree, bird on ground below trees, or fallen from felled tree.

3

Following radio-tagged adult, or adult on ground, or fallen to ground after tree felled.

4

Chick found on the ground (foreseted and non-foreseted areas), or found dead.

Table 28. Additional evidence of Marbled Murrelet nests in Alaska.

[Summarized from DeGange, 1996. Reports did not always include information on forest cover. Of the 30 reports of possible nesting, 24 had information on 

forest type or cover]

Nest characteristics

Regions

Prince William Sound Kodiak Southeast Alaska 

Mountain 

Hemlock

Western 

Hemlock

Sitka 

Spruce

Sitka 

Spruce

Mountain 

Hemlock

Western

Hemlock

Number of nests 8 2 1 4 1 3

Average tree diameter (cm) 56 (45-71) 53 (30-76) 72 80 (61-104) 120 74 (69-79)

Average tree height (m) 22 (16-30) 21.5 (21-22) 30 25 (21-27) 25 29.7 (26-34)

Average branch diameter (cm) 15.9 (10.5-27.1) 15.4 (14.6-16.2) 12.7 80 (61-104) 19 19.2 (17.5-24)

Average distance to coast (km) 0.52 (0.25-1.04) 0.38 0.1 0.8 (0.4-1.2) 1.2 2.6 (0.5-6.4)

Average canopy closure (percent) 63 (40-75) 85 75 40 na 70 (60-80)

Average elevation (m) 143 (75-305) 95 (75-115) 70 60 (100-305) 348 121 (30-274)

Table 26. Summary of Marbled Murrelet tree nests in Alaska.

[Adapted from data in DeGange, 1996. Range of values in parentheses] 

102 Status Review of the Marbled Murrelet in Alaska and British Columbia
Presumably, the distance between nesting and foraging 

area is a factor in defining potential murrelet nesting habitat, 

at least in a general way (Bradley and others, 2004; Kuletz, 

2005). Murrelets may nest as much as 75 km inland (Nelson, 

1997), suggesting that “commuting” is not a critical factor. 

Although the sample size was small, Bradley and others 

(2004) study of radio-tagged birds showed no significant 

relationship between distance to foraging areas and 

reproductive success. In Prince William Sound, birds radiotagged in different marine habitat types had similar foraging 

distances, and birds nesting above a deep-water fjord did not 

fly farther to forage in shallow habitat, but rather foraged 

primarily in the fjord in areas of upwelling (Kuletz and others, 

1995b; Kuletz, 2005). 

In Prince William Sound, the distances from the coast 

for 15 confirmed nests (DeGange, 1996) were all <1 km and 

for six potential nest sites discovered through radio telemetry, 

all were <6 km from water. Mean over-water distance from 

suspected nest to forage site was 20 km. This was considerably 

less than distances recorded in SEAK (75 km, and as much 

as 100 km; Whitworth and others, 2000) or British Columbia 

(39 km; Hull and others, 2001). Kuletz (2005) suggested 

that the steep topography and low tree-line in Prince William 

Sound may restrict murrelets to near shore nest sites, greatly 

reducing flight distances to the water, compared to sites farther 

south. In contrast, potential nest locations in SEAK were 

4–9 km from the sea (Whitworth and others, 2000), and in 

British Columbia were on average 4–15 km inland although 

some nests have been found farther inland (Hull and others, 

2001). In Oregon, mean distance inland for nests was 17 km, 

with a maximum of 40 km (Nelson, 1997). 

Ground Nests

The number of documented ground nests includes two in 

SEAK to five in the Cook Inlet–Kodiak region (table 27). The 

two ground nests SEAK were on steeper slopes than farther 

north, and distance to the coast was greater. In total, 5 of the 

15 ground nests were located near a forest (table 27). Most 

ground nests included some form of vegetative cover, such as 

alder or willow (Kuletz and Marks, 1997; Marks and Kuletz, 

2001). 

Ground nesting is rare in British Columbia. Bradley 

and Cooke (2001) report one confirmed and two probable 

nest sites on cliffs used by radio-tagged birds on the central 

mainland (Desolation Sound and Mussel Inlet). All three were 

on steep slopes (70–90o

) offering open flyways, at relatively 

high elevations (800–1,300 m), within 15–21 km of the ocean, 

and were confirmed or suspected of being on moss-covered 

platforms surrounded by shrubby vegetation. At all three sites, 

the mossy ledges and crevices provided many more potential 

nest platforms than available in adjacent trees. The high 

elevation and position on cliffs suggested that risk of ground 

predators was low. Bradley and Cooke (2001) suggested that 

ground/cliff nests were relatively rare in their study area, 

and comprised 3 percent (1/30) of confirmed nests, and 3 

percent (2/78) of suspected nest sites. Additional ground nests 

were found in Desolation Sound and on Vancouver Island in 

2001, but details are not available. Rodway and others (1991, 

1993) searched alpine areas in Haida Gwaii (Queen Charlotte 

Islands) but found no evidence of nests or near-nest activity. 

No ground or cliff nests have been found south of British 

Columbia (Nelson, 1997; McShane and others, 2004). 

Tree Nests

Of the 19 documented tree nests in Alaska, 4 were in 

SEAK, 2 were on Kodiak Island, 2 were on Afognak Island, 

and 11 were in Prince William Sound (table 26). In SEAK 

and Prince William Sound, nest tree species were primarily in 

mountain hemlock (Tsuga mertensiana) or western hemlock 

(T. heterophylla). The four nests found on Kodiak Island and 

one nest from Prince William Sound were in Sitka spruce 

(Picea sitchensis). Nest tree diameter and height generally 

decreased on average at the higher latitudes (table 26), which 

would be expected because tree size decreases with increasing 

latitude (Viereck and Little, 1972). Elevation of tree nests was 

highest in SEAK. Naslund and others (1995) found that the 

14 tree nests in south-central Alaska were all on large mosscovered platforms in trees >30 cm in diameter. Nest trees were 

among the largest trees in the immediate area. 

The moss platforms of the tree nests found in Alaska 

have been composed of the hanging moss, Antitrichia 

curtipendula (Quinlan and Hughes, 1990; Kuletz and others, 

1994b). This moss also was the most common epiphyte found 

on five of six nest branches used by Marbled Murrelets in 

British Columbia (Burger, 1995a). Recent studies of epiphyte 

distribution and biomass in canopies of old-growth coastal 

forests in B.C., Washington, Oregon show that A. curtipendula

typically is the dominant moss species, found on branches 

(axes) primarily in the sheltered lower to mid crowns (Peck 

and others, 1995; McCune and others, 1997; McCune and 

others, 2000; Sillett and Rambo, 2000). McCune (1997) found 

that bryophyte biomass was greatest in old-growth stands, 

and he hypothesized that bryophytes encroached gradually 

upward from the forest floor. Similarly, Sillett (1995) found 

that bryophyte biomass increased with increasing stand 

age. These observations reinforce that the nest platforms of 

Marbled Murrelets are dependent on the old-growth nature of 

the forests, which allows development of a thick moss layer in 

mid-canopy over long periods of time—i.e., centuries. 

Nesting Habitat: Characteristics, Threats, and Trends 103
Burger (2002b) reviewed the inland breeding habitats 

of Marbled Murrelets in British Columbia at three spatial 

scales: nest sites (microhabitat), stand-level, and landscapelevel. Based on the British Columbia review, Burger (2002b) 

concluded that, given a choice, murrelets will select nest sites 

on boughs with the following five characteristics: 

•	 Sufficient height to allow stall-landings and jump-off

departures; 

•	 Openings in the canopy for unobstructed flight access;

•	 Sufficient diameter to provide a nest site and landing

platform; 

•	 Some soft substrate to support a nest cup; and

•	 Overhead foliage cover.

The first four conditions are almost always found in oldgrowth trees, which explains why the overwhelming majority 

of nests are in such trees, although the birds are obviously 

adaptable and might nest in suboptimal sites, which do not 

meet these conditions. The proximal cues used by the birds 

to select nest sites are not known, but seem likely to be a 

combination of these five features. Murrelets frequently land 

in trees in which no nests are found, indicating that several 

sites are considered by prospecting birds before deciding on a 

nest site. One consistent pattern is that murrelets tend to nest 

in trees with many suitable platforms even though only one is 

needed for a nest site. They might be attracted to trees offering 

several possible nest sites.

At the nest site level, most nests were on large limbs 

(15–75 cm diameter) in older conifers (Burger, 2002). Tree 

species preference varied among study areas in British 

Columbia and was not a reliable indicator of suitable habitat. 

In a sample of 123 nests from British Columbia, all were 

in old conifers except one (0.8 percent) found in a red alder 

(A. rubra). Most nests have been found in yellow cedar 

(Chamaecyparis nootkatensis; 50 percent), western hemlock 

(15 percent), Douglas fir (11 percent), western red-cedar 

(Thuja plicata; 10 percent), and Sitka spruce (9 percent), 

with fewer in mountain hemlock (2 percent) and amabilis 

(silver) fir (Abies amabilis; 2 percent; Burger, 2002). The 

high proportions of yellow cedar and Douglas fir among nest 

trees are artifacts of the large number of nests found in the 

Sunshine Coast on the southern mainland, where these species 

are common. These tree species tend to be less common or 

absent in many other parts of the murrelet’s range in British 

Columbia.

With the exception of the single alder mentioned above, 

all trees containing nests in British Columbia were old-growth 

conifers, based on their size, structure, epiphyte loads and, 

in many cases, evidence of senescence. All were likely more 

than140 years old, and most were less than 200 years old 

(Burger, 2002). Nest trees typically were larger and often 

provided more platform limbs than other trees nearby (Manley, 

1999). 

Estimates of nest density were made from three 

studies in British Columbia (Burger, 2002). In fragmented 

and heavily logged habitat on the Sunshine Coast, Manley 

(1999) estimated the nest density as 0.3–0.7 nests per ha, 

which apparently included nests active in previous years. In 

Clayoquot Sound, western Vancouver Island, Conroy and 

others (2002) reported density as 0.66 ± 0.29 (SD) visible 

nests per ha. Considering only nests active in the year they 

were found, the density was 0.11 ± 0.12 nests per ha. In 

valley-bottom habitat in Carmanah and Walbran valleys 

on southwest Vancouver Island, A.E. Burger and V. Bahn 

(University of Victoria, unpub. data, 2002) estimated densities 

of 0.60 ± 0.35 (SD) nests per ha, which was equivalent to 0.15 

± 0.09 active nests per ha per year. All three of these studies 

appear to have sampled areas with higher nest densities than 

expected across the British Columbia range, because the mean 

densities recorded with radar (birds per ha), which might 

sometimes include both members of a breeding pair plus an 

unknown proportion of non-breeding birds, were much lower 

(0.090 and 0.045 birds per ha for west Vancouver Island and 

Desolation Sound, respectively; Burger and others, 2004a; see 

also below).

Stand-Level Habitat Characteristics

Burger (2002b) reviewed many studies of stand level 

habitat associations in British Columbia, either comparing 

stands with nests with randomly selected stands, comparing 

occupied stands with those showing no occupancy, or using 

audio-visual detections as indicators of relative abundance. 

There was considerable variability among these studies but 

murrelet nesting, occupancy and high levels of activity were 

frequently positively associated with:

•	 Tree diameter at breast height (DBH);

•	 Density of large trees (DBH >80 cm) per ha;

•	 Variation in tree size (DBH or height);

•	 Epiphyte (moss, ferns and lichens) cover on branches

and thickness;

•	 Density of potential platforms per ha; and

•	 Density of trees with platforms;

and generally negatively associated with:

•	 Elevation (below 600–900 m preferred);

•	 Forests on the coastal fringe (within ca. 500 m of

exposed coasts); and

•	 Slope and aspect showed variable effects—positive in

some areas and neutral or negative in other areas.

An analysis of 45 nests located by telemetry in 

Desolation Sound indicated some important stand-level 

features (Bradley, 2002; Burger, 2002). Forest polygons 

containing nests were compared with randomly selected 

104 Status Review of the Marbled Murrelet in Alaska and British Columbia
bordering polygons with trees (treed) or with platform limbs. 

Polygons with nests were found in older stands of trees, in 

areas with larger mean basal area of trees, and in areas with 

greater vertical complexity in canopy structure.

Models of these data indicated that, relative to random 

polygons (treed or with potential platforms), nest polygons 

tended to be less uniform with more canopy gaps, and greater 

vertical complexity in the canopy. These habitat models gave 

similar results to other models derived from audio-visual and 

forest structure data.

Landscape-Level Habitat Characteristics

Burger (2002b) reviewed studies which had considered 

habitat associations at the landscape scale (considering entire 

watersheds or larger land units). Data came from studies 

using audio-visual surveys, nest sites located by telemetry, 

radar counts, and vegetation mapping. In most cases, studies 

compared measures of murrelet occupancy, nest sites or 

relative abundance with GIS habitat features derived from the 

interpretation of forest cover data, satellite imagery, or aerial 

photography. 

At the landscape level, areas with evidence of occupancy 

tended to have higher proportions of large, old-growth forest, 

larger stands and greater habitat complexity, but distance to 

the ocean (as much as about 60 km) did not seem important, 

apart from some avoidance of coastal fringes. Elevation had 

significant negative effects in some studies but not all.

There is considerable interest in British Columbia on 

whether and how elevation and slope affect the probability 

of nesting by murrelets. Burger (2002b) therefore reviewed 

these in detail and found optimal nesting conditions in British 

Columbia are likely to be found at 0–900 m elevation (perhaps 

0–600 in watersheds with more intact old-growth stands), 

less suitable conditions are found at 900–1,500 m, and areas 

above 1,500 m are unlikely to be used. In all cases, elevation 

should not be the sole criterion for establishing suitability, and 

evidence of nesting, occupancy and/or suitable habitat (e.g., 

potential nest platforms) is needed for establishing habitat 

suitability. Furthermore, given the inconsistency in data on 

slope, it seems prudent to avoid including slope as a strong 

predictor (+ve or –ve) of suitable habitat in British Columbia. 

Instead, management and mapping should focus on forest 

structure, measures of canopy accessibility, and nest site 

attributes known to be reliable indicators (e.g., presence of 

platform limbs and epiphyte cover). Additionally, aspect does 

not appear to have a strong effect on the placement or success 

of nests, although south-facing slopes in drier areas appear to 

have fewer mossy platforms than other aspects.

Zharikov and others (2006) compared habitats at known 

nest sites located with telemetry in Desolation Sound (heavily 

logged; 121 nests) and Clayoquot Sound (relatively intact; 

36 nests) with randomly located points in these same areas. 

Using logistic and multiple regression models, they examined 

which landscape features best predicted the occurrence of nest 

sites. Murrelets tended to occur in patch sizes proportional to 

their occurrence in Clayoquot Sound but in smaller patches 

than expected in Desolation Sound. Streams, steeper slopes, 

and lower elevation were identified as features more likely 

to be associated with nest sites. They also reported that nests 

were closer to clearcut edges than expected, but this cannot 

be interpreted that the murrelets had an affinity to forest 

edges or clearcuts, because the distances that were reported 

(mean distance to forest edge was 1.9 and 2.4 km at nest sites 

and randomly chosen points, respectively), were far greater 

than the distances that forest edge-effects are normally found 

(about 50–100 m). Their conclusion that murrelets show no 

ill effects from breeding in old-growth forests fragmented by 

logging is somewhat in conflict with results of several other 

studies from British Columbia and elsewhere (Burger, 2002; 

see below).

Amount and Distribution of Nesting Habitat in 

Alaska and British Columbia

Even with the increased effort to study murrelet nesting 

biology in recent years, it continues to be a challenge to 

characterize nesting habitat. During the last decade, several 

landscape-scale models have been developed that use a 

variety of techniques to assess the importance of habitat 

characteristics to nesting Marbled Murrelets (Lank and others, 

2003). In some areas within the breeding range, occupancy 

was most related to the availability of low-elevation, 

unfragmented old-growth forests that were near productive 

marine areas (Meyer and others, 2002). However, given 

the variability in vegetation characteristics, biogeoclimatic 

influences and landscape conditions, individual models likely 

can only be used at the regional level (McShane and others, 

2004). In this section, we review the amount and distribution 

of potential nesting habitat within the breeding range of 

Marbled Murrelets within major regions of Alaska and British 

Columbia.

Three general areas of coastal Alaska are important to 

breeding Marbled Murrelets: SEAK, south-central Alaska 

and part of southwest Alaska including the Alaska Peninsula 

and the Aleutian Islands. The region was strongly influenced 

by the Pleistocene glaciation. Within these areas, nearly 

29 million ha fall within 60 km of shore (fig. 29), the typical 

maximum range for murrelets flying inland from the ocean 

Nesting Habitat: Characteristics, Threats, and Trends 105
(Lank and others, 2003). The Tongass National Forest in 

SEAK may be the single most important forest habitat for 

Marbled Murrelets as it encompasses the center of distribution 

for the species and the majority of the old growth western 

hemlock and Sitka spruce forests in the State. In the wake 

of EVOS, however, Prince William Sound in south-central 

Alaska has been the focus of most of the Marbled Murrelet 

research in the State. Much less is known about nesting habitat 

and nesting ecology in the Alaska Peninsula and the Aleutian 

Islands regions as little work has been done to examine 

distribution or habitat use.

Attempts to evaluate the amount and distribution of 

murrelet nesting habitat in Alaska are confounded by the 

fact that an unknown proportion of the Murrelet population 

nests on the ground. Piatt and Ford (1993) estimated that 3 

percent of the population in Alaska nests on the ground on 

the basis of marine distribution and at-sea densities relative 

to unforested regions. Lank and others (2003) suggest there 

may be a larger fraction of ground-nesters (20–30 percent) 

at some sites based on inland detections at unforested sites 

(Marks and Kuletz, 2001). DeGange’s (1996) review of 

34 nests in Alaska identified 15 as ground nests and 19 as 

tree nests. However, the high proportion of ground to tree 

nests was likely an artifact of the higher probability of finding 

ground nests compared to tree nests (DeGange, 1996). Further 

confusing the situation, an overlap in ground-nesting and 

tree-nesting Marbled Murrelets occurs between Kodiak and 

Prince of Wales Islands (Nelson, 1997). Marks and Kuletz 

(2001) suggest that limited forest cover and/or limited prey 

availability near forested areas could play a role in the 

selection of ground nests. Bradley and Cooke (2001) believe 

that large-scale removal of original old growth forests is a 

Figure 29. Forested and nonforested areas within the breeding range of Marbled Murrelets in coastal Alaska.

106 Status Review of the Marbled Murrelet in Alaska and British Columbia
factor in the selection of ground nest sites in British Columbia. 

In any case, the vast majority of Marbled Murrelets nest in 

trees within old-growth forests are found within 60 km of the 

coast (Lank and others, 2003; McShane and others, 2004), 

and therefore we focus here on forested habitat except in areas 

where murrelets occur in wholly unforested regions. 

Common approaches for evaluating nesting habitat 

suitability include assessing landscape, stand or tree-scale 

characteristics relative to use or non-use of a particular 

habitat (Burger, 2002; Lank and others, 2003; McShane 

and others, 2004; Raphael and others, 2006). Compared to 

British Columbia and the western U.S. coastal states, very 

little work has been done to assess occupancy and habitat use 

on a regional scale in Alaska. Inaccurate habitat maps and 

ever-changing knowledge of nesting habitat requirements at 

the site, tree, plot and landscape scales makes it difficult to 

determine habitat suitability (McShane and others, 2004). 

Although information on habitat classification is available for 

much of the Tongass and Chugach National Forests, current 

and comprehensive information for other parts of coastal 

Alaska, including private and locally owned lands, is scarce or 

nonexistent. 

The CMMRT (Bertram and others, 2003) outlined a 

recommended sequence of analytical methods for predicting 

stand and landscape-level habitat features as follows:

1. Identify areas under consideration using GIS and habitat 

maps;

2. Assess and rank habitat suitability using habitat 

algorithms and habitat indicators;

3. Assess evidence of suitable nesting habitat with 

interpretation of aerial photography;

4. Select potential polygons to be considered as suitable 

nesting habitat; and

5. Confirm that potential polygons are suitable habitat using 

a variety of ground-truthing techniques.

Albert and Schoen (2006) have recently begun the 

development of a Marbled Murrelet habitat suitability index 

(HSI) for Alaska. In their conservation assessment for SEAK, 

they employed the first steps for assessing habitat suitability 

by modeling vegetation and topographic characteristics 

such as stand age, tree size, slope and distance from shore 

(see section, “Southeast Alaska”). A modeling effort for 

Prince William Sound (R. DeVelice, U.S. Forest Service, 

oral commun., 2006) went further to select the best habitat 

suitability model by ground-truthing habitat characteristics 

and incorporating known occupancy. Still, nesting habitat 

requirements are debated among experts and regional variation 

in habitat quality requires that each area be considered 

separately. As ground-nesting habitat requirements are 

not well understood, there have been no attempts to assess 

occupancy or habitat suitability for ground-nesting Marbled 

Murrelets in unforested regions of Alaska such as the Alaska 

Peninsula and Aleutian Islands.

Forest Inventory and Analysis (FIA) data provide highquality forest data for much of the forested area in southern 

Alaska. As part of a nationwide census, the USFS conducts 

annual and periodic surveys to determine the extent, condition, 

volume, growth and depletions of timber on forest land 

across all ownerships. We obtained FIA plot data collected in 

1995–2003 for south-central and SEAK. FIA sampling used 

a systematic-grid sample with a grid spacing of 4.8 km. They 

used high resolution orthophotographs and satellite imagery to 

classify land cover and vegetation type, and to determine plot 

locations. Sampling intensity was chosen to meet sampling 

error guidelines of ±3 percent per million acres for productive 

forest area and ±10 percent per billion ft3

 for net volume. 

Unforested areas or those within reserved areas were not 

ground-truthed (van Hees and Mead, 2005).

We used general land cover and land-status datasets 

available the State of Alaska to estimate the amount and 

distribution of nesting habitat in Alaska when plot data or 

published material were not available. Land-cover data were 

digitized by the USGS Earth Resources Observation and 

Science (EROS) program using AVHRR satellite imagery 

(1-km resolution). Land status coverages were compiled by the 

BLM and ADNR and are current as of March 2006.

British Columbia has made more progress towards 

identifying suitable habitat compared to Alaska. Several 

models or algorithms have been developed that combine 

habitat measures to classify and map large areas in British 

Columbia (reviewed by Tripp, 2001; Burger, 2002). Some 

algorithms combined measures derived from canopy structure, 

elevation, distance from ocean and from forest edges. Others 

used biogeoclimatic units (e.g., Broad Ecosystem Units) 

and forest cover maps, either separately or in combinations. 

Several studies have done ground-truthing to assess the 

validity of their algorithms and found them to be reasonably 

reliable in predicting suitable nesting habitat. The reviews 

concluded habitat classification was most reliable using 

regionally specific algorithms, combined with confirmation of 

habitat suitability using helicopter and/or ground surveys.

Southeast Alaska 

SEAK is approximately 840 km long by 190 km wide 

spanning from the Yakutat Bay to the north and Dixon 

Entrance to the south. The area includes coastal mountain 

peaks reaching 3,000 m on a narrow strip of mainland and the 

island chain that makes up the Alexander Archipelago. 

Nesting Habitat: Characteristics, Threats, and Trends 107
Figure 30. Land management within the breeding range of Marbled Murrelets in coastal Alaska. Data are based on 2006 BLM and 

ADNR sources.

The upland forests in SEAK are dominated by western 

hemlock and mixed hemlock-Sitka spruce stands. Alaskan 

yellow cedar, western red cedar, shore pine and mountain 

hemlock also are present. Western hemlock trees average 

37–75 cm in DBH and 27–36 m in height. In contrast, Sitka 

spruce trees in mature stands average 75–100 cm in DBH and 

36–67 m in height. Mountain hemlock trees usually occur 

near tree line and average 38–50 cm in DBH and 18–25 m 

in height. Well developed moss layers are characteristic of 

these stands (Viereck and others, 1992). Rainfall, moderate 

temperature and relatively low levels of disturbance contribute 

to the maintenance of the productive old growth characteristics 

of southeast forests. 

The Federal government holds 8.3 million ha of land 

in SEAK, of which 6.8 million ha are within the Tongass 

National Forest (fig. 30). Other major landholders include 

Glacier Bay National Park and Preserve (1.1 million ha), 

the State of Alaska, who manages the Haines State Forest 

(216,000 ha) and other smaller holdings, and the Alaska 

Native Corporations (274,000 ha; table 29).

SEAK covers about 9.3 million ha of land area. Recent 

forest inventory work found that 48 percent of the land area 

is forested (van Hees and Mead, 2005), while the rest is 

comprised of fen, sphagnum bogs, rock, glaciers, ice fields 

and water. Timberland, or the forested area that can produce 

108 Status Review of the Marbled Murrelet in Alaska and British Columbia
1.4 m3 of wood per ha per year and is accessible and available 

for production of wood products, comprises about 1.6 million 

ha (18 percent) of land area in all SEAK. Most forested areas 

are considered old-growth and are limited to elevations less 

than 750–900 m (Everest, 2005). Seventy-three percent of 

the timberland in SEAK is 150 years or older (van Hees 

and Mead, 2005). Of 2,463 plots visited in SEAK, 995 (40 

percent) had a stand age greater than 150 years covering an 

estimated 2.1 million ha of land area (fig. 31).

As discussed above, Albert and Schoen (2006) have 

recently completed a comprehensive analysis of productive old 

growth stands in Southeast Alaska. They used a combination 

of Forest Service data, Landsat ETM and orthophotographs 

to classify vegetation and land cover. They assessed the 

amount of productive old growth using a classification 

system developed by Caouette and DeGayner (2005), based 

on tree size and stand density to categorize large tree (>53 

cm), medium tree (43–53 cm) and small tree stands (<43 

cm). Using these guidelines, they estimated that there are 

roughly 2.3 million ha of productive old growth forest in 

SEAK (table 30). Productive old-growth stands make up about 

52 percent of the forest. Large, medium, and small tree stands 

comprise 10, 75, and 15 percent, respectively, of old-growth 

forest in SEAK. Northern Prince of Wales Island contains 

nearly 24 percent of all large-tree forests in SEAK. Other 

areas that contain considerable amounts of large-tree oldgrowth include Admiralty Island, South Prince of Wales, East 

Chichagof, Kuiu, and Yakutat Forelands (table 31). 

A nesting habitat capability model for several focal 

species including the Marbled Murrelet in SEAK (Albert and 

Schoen, 2006) was based on several factors that contribute 

to nesting habitat including stand age, forest structure, slope, 

and distance from shore (table 32). Although the model was 

based on a team of Murrelet experts’ professional judgment 

on important habitat requirements, and they used the best 

Landowner SEAK SCAK SWAK All areas

U.S.Forest Service 6,609

(72%)

2,087

(27%)

0

(0%)

8,697

(30%)

National Park 

Service

1,626

(18%)

875

(11%)

2,308

(19%)

4,810

(17%)

National Wildlife 

Refuge

0

(0%)

1,313

(17%)

4,333

(36%)

5,645

(19%)

Other Federal 149

(2%)

557

(7%)

714

(6%)

1,420

(5%)

Native 274

(3%)

876

(11%)

1,794

(15%)

2,943

(10%)

State 346

(4%)

1,501

(19%)

2,540

(21%)

4,387

(15%)

Private, local, other 231

(3%)

608

(7%)

244

(2%)

1,083

(4%)

Total 9,235 7,817 11,933 28,985

Table 29. Area (thousands of ha) and land ownership for areas 

within 60 km of of the shore in southeast (SEAK), south-central 

(SCAK) and southwest (SWAK) Alaska. 

[Data are based on 2006 land-status estimates compiled by the Bureau of Land 

Management and State of Alaska Department of Natural Resources] Land cover Area (ha) Percent

 of total

Productive Old Growth

POG-Large Tree 238,308 2.69

POG-Medium Tree 1,754,073 18.91

POG-Small Tree 357,691 4.04

Other Forest

Clear-cut and 2nd growth 318,198 3.60

Conifer < 150 yrs 119,931 1.36

Conifer forest (other) 183,162 2.07

Deciduous forest 27,540 0.31

Mixed forest 6,187 0.07

Muskeg forest 477,633 5.40

Muskeg woodland 522,375 5.90

Sub-alpine forest 483,749 5.47

Non-forest vegetation 

Alpine tundra 220,268 2.49

Slide zone 326,990 3.69

Shrubland 389,298 4.40

Herbaceous nonforest 428,703 4.84

Freshwater wetlands 

Muskeg meadow 105,857 1.20

Emergent wetlands 19,275 0.22

River bar 22,219 0.25

Lake 82,777 0.94

River channel 58,347 0.66

Coastal wetlands 

Algal bed 33,334 0.38

Rocky shore 15,663 0.18

Salt marsh 13,540 0.15

Sand and gravel beach 2,345 0.03

Tideflat 5,090 0.06

Unconsolidated sediments 45,254 0.51

Unvegetated lands 

Ice and snow 1,455,348 16.44

Unvegetated 1,213,659 13.71

Urban 3,978 0.04

Total1 8,930,793 100.00

1

Discrepancies between FIA and Albert and Schoen (2006) area estimates 

are because FIA plots covered the area north of Yakutat to Icy Bay, but 

excluded reserves and unforested lands.

Table 30. Generalized classification of vegetation and land cover 

in Southeast Alaska.

[From Albert and Schoen, 2006. Abbreviations: ha, hectare; POG, productive 

old growth; <, less than]

Nesting Habitat: Characteristics, Threats, and Trends 109
forest cover data available, the authors recognized that further 

research will help refine the model parameters. For example, 

the model did not differentiate among small, medium, and 

large tree old-growth, and it therefore may be an overestimate 

of suitable habitat. Likewise, the optimum value for slope 

also is disputed among experts. Moreover, the model lacks 

occupancy data, which are required to better assess the actual 

extent of nesting habitat (Lank and others, 2003). We caution 

that the model should be tested when occupancy data are 

available, however, to date, it is the best attempt to quantify 

habitat suitability for Marbled Murrelets.

Albert and Schoen’s (2006) modeling efforts found 

that 413,900 ha (4.7 percent) in SEAK have high potential 

(suitability index ≥ 75), 409,879 ha (4.7 percent) have 

medium potential (suitability index = 50–74), 1,220,640 ha 

(13.9 percent) have low potential (suitability index = 1-49) and 

6,755,785 ha (76.8 percent) are unsuitable (suitability index = 

0) for nesting Marbled Murrelets (table 33). The areas with the 

highest nesting habitat suitability are Revilla Island/ Cleveland 

Peninsula, Admiralty Island, North Prince of Wales and 

E. Chichagof Island (fig. 32). Areas of high marine density 

include the area near Admiralty Island, the northeast end of 

Chichagof Island and the area near Northern Prince of Wales 

Island including Zarembo and Kupreanof Islands. In contrast, 

the areas with the lowest potential for suitable habitat are the 

Fairweather Ice fields, Yakutat Forelands, and W. Chichagof 

Figure 31. Forest Inventory and Analysis (FIA) plot data from south-central (n = 2,533) and Southeast Alaska (n = 2,463).

110 Status Review of the Marbled Murrelet in Alaska and British Columbia
Province Land area 

(ha)

Management status (percent of current distribution)

Watershed-scale 

reserves

Sub-watershed 

reserves

Buffers Timberbase

E. Baranof Island 816 43.9 8.0 25.1 23.1

W. Baranof Island 1,940 59.1 15.9 6.0 19.0

Etolin/ Zarembo Island 4,908 23.6 24.2 12.1 40.1

Kupreanof/ Mitkof Island 8,621 15.1 25.0 14.7 45.2

Dall Island Complex 3,907 42.6 43.3 1.5 12.6

Revilla Island/ Cleveland 12,968 41.7 20.8 7.5 30.1

N. Prince of Wales 56,514 13.5 31.4 13.8 41.3

E. Chichagof Island 15,287 42.9 14.7 16.6 25.7

Outside Islands 5,493 41.9 17.7 12.0 28.4

Chilkat River Complex 8,492 0.9 9.6 0.0 89.5

Taku River/ Mainland 9,678 18.0 33.5 9.4 39.1

Kuiu Island 14,703 31.6 15.3 10.6 42.5

Stikine River/ Mainland 8,582 51.0 12.4 11.4 25.1

Yakutat Forelands 11,160 52.1 10.5 1.3 36.1

S. Prince of Wales Island 17,600 42.5 17.9 10.9 28.7

Lynn Canal/ Mainland 6,778 41.9 16.1 7.6 34.5

Admiralty Island 40,443 88.1 7.7 0.1 4.1

N. Misty Fjords 6,657 90.1 2.6 2.7 4.6

S. Misty Fjords 5,735 99.7 0.0 0.0 0.3

W. Chichagof Island 819 99.3 0.0 0.0 0.7

Grand total1 241,098 43.0 18.5 8.4 30.0

1

Does not include Glacier Bay or the Fairweather Icefields. 

Table 31. Land area and management status (percent of current distribution) of large-tree old growth forests 

among provinces in Southeast Alaska.

[Adapted from Albert and Schoen, 2006. Watershed-scale reserves includes areas where non-development land-use designations 

encompass the entire watershed. Sub-watershed scale reserves are areas that include a portion of entire watersheds within nondevelopment land-use designations. Buffers include stand-level protections under the Alaska State Forest Practices Act as well as 

the Tongass Land Management Plan standards for riparian, estuary, and beach fringe forests]

Variable Habitat type Habitat 

suitability index

Age class <150 years 0.00

≥150 years 1.00

Tree size Small POG 0.50

Medium POG 0.75

Large POG 1.00

Slope (degrees) 0-5 0.20

5-10 0.40

10-15 0.60

15-20 0.80

>20 1.00

Distance from shore (m) <300 0.30

>300 1.00

Table 32. Habitat variables and suitability factors used to 

estimate the relative value of Marbled Murrelet nesting stands in 

Southeast Alaska.

[From Albert and Schoen, 2006. Abbreviations: POG, productive old growth; 

<, less than; >, greater than; ≥, equal to or greater than; m, meter]

Habitat potential Habitat 

suitability index Area (ha) Percentof total

Unsuitable 0 6,755,785 76.8

Low 1-49 1,220,640 13.9

Medium 50-74 409,879 4.7

High 75-100 413,900 4.7

Table 33. Habitat suitability for Southeast Alaska, based on 

forest cover and topology.

[From Albert and Schoen, 2006. ha, hectare]

Nesting Habitat: Characteristics, Threats, and Trends 111
Figure 32. Marbled Murrelet habitat suitability and marine density for Southeast Alaska. Data are based on 

the Albert and Schoen (2006) habitat suitability model. Densities at sea in birds per square kilometer.

112 Status Review of the Marbled Murrelet in Alaska and British Columbia
Island. An analysis of the change in habitat suitability from 

1954, when industrial logging began in the region, to the 

present found a 14-percent degradation of murrelet habitat 

relative suitability scores for the region. Furthermore, about 

30 percent of currently existing suitable habitat (based on 

the sum of habitat suitability index scores within the region) 

occurs on managed state, federal or private lands with 

potential for harvest (table 34). 

South-Central Alaska

The south-central Alaska region includes Kodiak, the 

Kenai Peninsula, Chugach National Forest, and Icy Bay. A 

part of the Kenai Peninsula and all of Prince William Sound 

are located within the Chugach National Forest. 

The Kodiak Island Archipelago is located in the Gulf 

of Alaska approximately 30 mi across Shelikof Strait from 

the Alaska Peninsula. The island group is an extension of 

the Chugach-St. Elias Mountains and was nearly completely 

Province

Habitat capability index Current condition Management status and scale 

(percent of current habitat value)

Original 

(1954)

Current 

(2002)

Percent of 

original habitat 

value

Watershedscale 

reserves

Subwatershed 

reserves

Buffers Managed 

lands

N. Prince of Wales 229,309 138,269 60.3 17.7 28.0 7.3 47.0

Kupreanof/ Mitkof Island 96,196 76,516 79.5 14.6 21.4 4.8 59.2

E. Chichagof Island 131,045 104,324 79.6 33.4 16.6 6.0 44.0

Etolin/ Zarembo Island 69,743 55,968 80.2 20.7 24.2 6.6 48.5

E. Baranof Island 26,185 21,216 81.0 38.8 14.1 6.4 40.7

Yakutat Forelands 10,788 9,008 83.5 65.4 15.4 1.1 18.0

Outside Island 30,343 26,016 85.7 67.2 11.2 4.4 17.2

Dall Island Complex 30,233 25,995 86.0 33.7 34.1 2.3 29.8

Revilla Island / Cleveland Pen. 177,284 153,666 86.7 48.8 14.5 3.6 33.1

S. Prince of Wales 51,442 45,145 87.8 46.8 15.9 5.9 31.3

W. Baranof Island 54,306 48,136 88.6 64.9 15.0 1.7 18.4

Kuiu Island 81,973 72,720 88.7 55.3 10.4 4.4 30.0

Chilkat River Complex 46,220 41,653 90.1 1.4 8.5 0.4 89.7

Taku River/ Mainland 103,942 96,974 93.3 41.5 18.6 4.4 35.5

Admiralty Island 160,117 151,858 94.8 89.3 8.4 0.0 2.3

Stikine River/ Mainland 96,527 92,493 95.8 54.8 11.6 3.8 29.7

Lynn Canal/ Mainland 56,045 54,238 96.8 53.5 15.4 3.2 27.9

Glacier Bay 26,789 26,693 99.6 92.9 6.5 0.0 0.5

S. Misty Fjords 82,636 82,636 100.0 99.8 0.0 0.0 0.2

N. Misty Fjords 62,528 62,528 100.0 94.0 2.9 0.3 2.8

W. Chichagof Island 15,939 15,943 100.0 98.7 0.0 0.0 1.3

Fairweather Icefields 8,047 8,051 100.0 99.9 0.0 0.0 0.1

All provinces 1,647,637 1,410,046 85.6 52.2 14.4 3.5 29.9

Table 34. Current condition and management status of nesting habitat for Marbled Murrelets in Southeast Alaska.

[From Albert and Schoen, 2006. Watershed-scale reserves include areas where legal or administrative protections encompass the entire watershed 

(VCU). Sub-watershed scale reserves are areas that include a portion of entire watersheds (VCU) within legal or administratively protected 

status. Buffers include stand-level protections under the Alaska State Forest Practices Act as well as the Tongass Land Management Plan 

standards for riparian, estuary, and beach fringe forests. Managed lands include U.S. Forest Service timber base as well as all State, private, 

and Federal lands lacking explicit legal of administrative protection]

Nesting Habitat: Characteristics, Threats, and Trends 113
ice scoured during the Pleistocene glaciation. This region 

is characterized by alpine tundra at the higher elevations, 

forb/grass meadows with willow and alder at lower elevations 

and the northern area, including Afognak and Shuyak Islands, 

is forested with Sitka spruce and black cottonwood (Nowacki 

and others, 2001). 

The Kenai Peninsula is an ecologically diverse region and 

includes the Cook Inlet Basin, Chugach-St. Elias Mountains 

and Gulf of Alaska coast. Forest type in the Cook Inlet Basin 

area generally is composed of black spruce, paper birch, and 

quaking aspen. The forests on the Gulf coast of the Kenai 

Peninsula are dominated by mountain hemlock and Sitka 

Spruce, while the lowland areas are characterized by boreal 

forests of white spruce, paper birch, and black spruce. The 

Kenai Peninsula has recently (late 1990s) been devastated 

by a Spruce Bark Beetle infestation that resulted in the loss 

of mature spruce trees on about 429,000 ha, or more than 

50 percent of the forested land in the region (Boucher and 

Mead, 2006). 

The Chugach National forest is the Nation’s second 

largest national forest covering approximately 2.1 million ha. 

It is situated between the Kenai Peninsula and the Copper 

River Delta and it includes Prince William Sound. Oldgrowth forests in the region provide important fish and 

wildlife habitat, due to the unique structural attributes such as 

multilayered canopies, diverse forb and shrub layers, coarse 

woody debris, and large diameter trees (Ricketts and others, 

1999). For this region, these attributes begin to appear when 

a forest reaches 150 years, although this may vary by plant 

association (Capp and others, 1992). 

Collectively, non-forested cover types dominate the 

landscape of the Chugach Forest, accounting for about 

78 percent of the gross area. The amount of forested land is 

about 22 percent (483,200 ha). Within the forested component, 

conifer forest types dominate, accounting for about 91 percent 

of forested lands, followed by unclassified forest (about 

4 percent), hardwood forest (about 3 percent) and mixed 

hardwood-conifer forest (about 1 percent; U.S. Forest Service, 

2002a).

The distribution of forested land on the Chugach National 

Forest differs greatly between the three geographic landscapes 

which make up the forest. Prince William Sound has 

63 percent of the total forested land on the Forest (304,790 ha) 

with the remainder almost evenly split between the Copper 

River Delta (19 percent or 90,720 ha) and the Kenai Peninsula 

(18 percent or 87,690 ha). Of the forest structure classes 

available, Prince William Sound has the majority of old 

mature stands (47.44 percent) on the Forest with the remainder 

found on the Copper River Delta (11.44 percent) and the 

Kenai Peninsula (7.61 percent; table 35). 

For the south-central FIA area, more than 1.6 million ha 

(22 percent) are forested (van Hees, 2005). Of the forested 

lands, more than 750,000 ha (47 percent) were classified as 

timberland (unreserved productive forest land; Campbell 

and others, 2005). The volume of timber on timberland was 

estimated at 5,087 million ft3; with most of the volume on 

State and local government lands (44 percent), with the 

remaining volume primarily on private lands (28 percent) 

and National forest lands (23 percent). The study found that 

the Sitka spruce forest type was the dominant forest type in 

the region. They also reported that most timberland in southcentral Alaska was of relatively low productivity, producing 

less than 50 ft3 per acre per year. For timberland acres on 

State and private lands, average annual mortality and harvest 

exceeded average annual growth (Campbell and others, 2005).

FIA researchers visited 2,533 plots in south-central 

Alaska and 148 plots (6 percent) contained stands more than 

150 years old. Plots containing old growth stand (>150 years) 

conditions covered an estimated 281,000 ha of land within the 

study area. Prince William Sound has the most abundant old 

growth forest stands in south-central Alaska, although forested 

areas of Afognak and Shuyak Islands, just north of Kodiak, the 

Gulf coast of the Kenai Peninsula, and scattered coastal areas 

between Prince William Sound and Icy Bay also contain oldgrowth stand conditions (fig. 31).

Marbled Murrelet nesting habitat suitability was 

assessed for the 245,000 ha of forest (32 percent of the total 

land area) in the Northern Gulf section of Prince William 

Sound and a portion of the Kenai Peninsula north of Seward 

(R. DeVelice, U.S. Forest Service, unpub. data, 2006). This 

approach used a combination of field sampling to validate 

vegetation classification and predictive modeling for suitable 

habitat based on existing geographic databases and landform 

characteristics. At each ground site, they recorded detailed 

information including landform, vegetation type, elevation, 

slope and aspect, and information about individual trees 

including number of mossy platforms present, and tree 

diameter. Vegetation types were classified within 1 km radius 

of field sites using interpretation of aerial photography, and 

Structural 

class

Percent of forest structural classes

Copper River 

Delta

Kenai 

Peninsula

Prince William 

Sound Total

Seed/sap 0.09 2.82 0.51 3.42

Pole timber 1.75 18.9 1.63 22.28

Young mature 5.12 1.69 1.01 7.8

Old mature 11.44 7.61 47.44 66.49

Total 18.4 31.02 50.58 100

Table 35. Percent forest structural classes for the Chugach 

National Forest.

[From U.S. Forest Service, 2002b. Does not include ANILCA additions and 

forest stands with no structural attributes.

114 Status Review of the Marbled Murrelet in Alaska and British Columbia
Variable Habitat type Suitability 

index Scenario

Mossy platform1 Elevation >200 m 1 I-VI

Elevation 50-200 m 5

Elevation ≤50 m 10

Tree size2 Flat portions of rolling hills 3 II-VI

Mountain sideslopes, valley bottoms or rolling hills not on 

southerly aspect

5

Mountain sideslopes and rolling hills with southerly aspects, 

valley bottoms not on southerly aspect

7

Valley bottoms with southerly aspects 10

Forest patch size <3 ha 1 III-VI

3-100 ha 7

>100 ha 10

Distance to shoreline <300 m 5 IV-VI

≥300 m 10

Slope <15, or >35 5 V-VI

15-35 10

Proximity to foraging area Outside grid 5 VI

Within grid 10

1

 Mossy platforms were inversely related to elevation.

2

 Tree size was related to aspect and landform.

Table 36. Nesting habitat variables used in the Prince William Sound Marbled Murrelet habitat suitability model. 

[From DeVelice, U.S. Forest Service, unpub. data, 2006. Higher suitability index values indicate higher nesting potential. Model 

complexity increased with each scenario, i.e., scenario I included only mossy platforms and model VI included all variables]

these classifications also were compared to classifications 

made from satellite images. Nesting potential was assigned for 

six scenarios (i.e., different modeling exercises) using mossy 

platform abundance, which was inversely related to elevation 

(P<0.0001), tree size, which was related to aspect and 

landform (P<0.02 and P<0.0005, respectively), forest patch 

size, distance to shore, proximity to foraging areas (based on 

bathymetry) and slope. Each modeling scenario increased 

in habitat complexity with each variable added (table 36). 

They found that land-cover characterization based on satellite 

imagery was very effective for distinguishing forests from 

other vegetation, and interpretation of aerial photography 

differed from satellite image interpretation by only 3 percent. 

Six scenarios found high nesting potential more than 20–83 

percent of the available forest (fig. 33). Scenario III, which 

included mossy platform abundance, tree size, and forest 

patch size, was selected as the best model because sites of 12 

of 14 known nests were classified correctly under this model 

scenario. Scenario III included 133,000 ha of high potential 

nesting habitat and 104,200 ha of lower potential nesting 

habitat.

Southwest Alaska 

The Alaska Peninsula is formed by the Aleutian Range, 

which contains some of the most active volcanoes on the 

continent. The north side, which includes Bristol Bay, is 

characterized by smooth glacial moraines that act as dams 

for lakes that have filled in behind them. The south side has 

rugged, deep fjordlands. Low shrub lands of willow, birch, 

and alder dominate, with heath and lichen communities 

interspersed. Alpine tundra and glaciers characterize the 

highlands (Nowacki and others, 2001).

The Aleutian Archipelago reaches from the Alaska 

Peninsula to the Kamchatka Peninsula and spans 

approximately 2,000 km. There are 12 relatively large 

islands and about 50 smaller islands, with summits reaching 

2,800 m near the Alaska Peninsula and 1,000 m on Attu. The 

islands are treeless with lowland shrubs and inland meadow 

communities. Exposed upland areas between 125 and 270 m 

are characterized by mats of heath as a result of frost and 

high wind, and above 270 m sparse plants are scattered 

among boulder fields and barren ground. Heterogeneity 

in the plant community is maintained through disturbance 

caused by the harsh climate and volcanic activity (Heusser, 

1990). 

Nesting Habitat: Characteristics, Threats, and Trends 115
The Alaska Peninsula and Aleutian Islands together 

comprise 41 percent of the entire southern coastal Alaska 

study area covering about 12 million ha of land area (fig. 29). 

The Federal government manages 61 percent of the land and 

more than one-half of Federal holdings are National Wildlife 

Refuge lands. The State of Alaska manages 21 percent of 

the land, Native allotments comprise another 15 percent 

while private, local and other owners make up the remainder 

(table 29).

FIA data for the southwest Alaska inventory area were 

not available because they are not comparable to southcentral Alaska and SEAK inventory data (B. van Hees, U.S. 

Forest Service, oral commun., 2006). Only 8 percent of the 

area is forested, all of which occurs on the Alaska Peninsula. 

Although Marbled Murrelets undoubtedly breed in the 

Aleutians, based on their abundance, no nests have been 

documented there so far. 

British Columbia 

Based on a synthesis of available evidence and mapping 

trials, the CMMRT (Bertram and others, 2003) derived 

regionally specific algorithms to assist the mapping of 

terrestrial murrelet habitat throughout the British Columbia 

range (table 37). These algorithms also were adopted as the 

method for identifying likely nesting habitat by the provincial 

IWMS (Burger, 2004). The table also summarizes current 

knowledge of mappable features thought to be important for 

murrelets in British Columbia (critical microhabitat features 

such as platform limbs and moss development are not shown 

on forestry maps or other GIS databases). Some of the 

parameters shown in table 37 are not available in some regions 

in British Columbia; consequently province-wide mapping 

was done using a simpler algorithm based largely on stand 

age, tree height, and distance from the sea (see table 37). 

Mapping of the British Columbia-wide habitat using variations 

of these algorithms is nearing completion but no maps or data 

are available yet (T. Chatwin and M. Mather, British Columbia 

Ministry of Environment). 

The general CMMRT algorithms and regional variations 

thereof have been tested using interpretation of aerial 

photography to assess tree and canopy features, and low-level 

helicopter surveys to assess availability of potential nesting 

platforms, mossy mats, large trees, canopy openings and other 

features deemed necessary for murrelets to nest (Bertram and 

others, 2003). Following field trials, provincial standards were 

introduced for both interpretation of aerial photography and 

low-level helicopter assessments of murrelet habitat (Burger, 

Scenario

I II III IV V VI

Area (thousands of ha)

0

500

1000

1500

2000

2500

Figure 33. Area of low nesting potential habitat (black) and high nesting potential habitat 

(gray) for six habitat modeling scenarios in Prince William Sound (DeVelice, U.S. Forest 

Service, unpub. data, 2006).

116 Status Review of the Marbled Murrelet in Alaska and British Columbia
2004). Waterhouse and others (2004) used a sample of 274 

nest sites from several parts of British Columbia to confirm 

the applicability of interpretation of aerial photography for 

classifying likely murrelet nesting habitat. 

Waterhouse and others (2002) used forest attributes 

available from interpretation of aerial photography to analyze 

45 nest sites found by radio-telemetry on the Sunshine Coast, 

southern mainland of British Columbia. Five attributes (tree 

height, basal area of trees, stand age, crown closure, and 

vertical complexity of the forest canopy) best predicted which 

forest polygons were more likely to be used for nest sites and 

also which nest sites were more likely to be successful. 

Several studies have used observers surveying from 

helicopters flying at low altitudes to gather data for testing 

habitat algorithms and to identify polygons where the canopies 

contain platforms and other essential elements for murrelet 

nesting (e.g., Leigh-Spencer and others, 2002; Hobbs, 2003; 

Burger and others, 2005; Donald, 2005). In British Columbia, 

many forest companies are now using a combination of forest 

cover GIS mapping (sometimes also using interpretation of 

aerial photography) and low-level helicopter assessments, to 

map and rank forest polygons on their potential as nest habitat 

(e.g., Deal and Harper, 2004). 

The area of suitable nesting habitat currently found in 

British Columbia is not accurately known. Estimates of habitat 

areas vary greatly depending on which algorithm is used and 

how reliable the mapping and GIS data are. The first estimate, 

based on Baseline Thematic Mapping (a coarse-scale GIS 

mapping used for forestry in British Columbia) by Marven 

Eng (British Columbia Ministry of Forests, unpub. data, 2006) 

suggested that there were 3.9 million hectares of habitat in 

2000 (table 38). This is almost certainly an overestimate, made 

before detailed algorithms of habitat had been developed in 

Habitat 

available Area (ha) Percent of original

Percent of 

1973 amount

Original 7,670,923 100 -

1973 5,163,830 67 100

2000 3,933,715 51 76

2030 3,161,372 41 61

Table 38. Estimates of areas of likely nesting habitat for Marbled 

Murrelets in British Columbia, 2000.

[Estimates from M. Eng, British Columbia Ministry of Forests]

Feature Most likely Moderately likely Least likely

Distance from saltwater (km): all regions 0.5–30 0–0.5 and 30–50 >50

Elevation (m)

Central & Northern Mainland Coast 0–600 600–900 >900

Haida Gwaii (Queen Charlotte Islands) 0–500 500–800 >800

All other regions 0–900 900–1500 >1500

Stand age class: all regions 9 (>250 yr) 8 (140–250 yr) <8 (<140 yr)

Site index productivity classes: all regions1 Class I and II Class III Class IV

(site index 20+) (site index 15-19) (site index <15)

Tree height class: all regions2 4–7 (>28.5 m) 3 (19.5–28.4 m) <3 (<19.5 m)

Vertical canopy complexity: all regions3 MU NU and U VU

(VNU)

1

Productivity classes as defined in Green and Klinka (1994, p. 197); approximate 50-year site index values also 

given—application of these indices might vary with different tree species and across regions.

2

Nests have been found in polygons ranked height class 1 or 2 but the nests were in larger trees than the polygon 

average.

3

Vertical complexity ranked from least to highest (see Waterhouse and others, 2002). VU = very uniform (<11 percent 

height difference leading trees and average canopy, no evidence of canopy gaps or recent disturbance). U = uniform (11–20 

percent height difference, few canopy gaps visible, little or no evidence of disturbance. MU = moderately uniform (21–30 

percent height difference, some canopy gaps visible, evidence of past disturbance, stocking may be patchy or irrigular. 

NU = non-uniform (31–40 percent height difference, canopy gaps often visible due to past disturbance, stocking typically 

patchy or irregular). VNU = very non-uniform (>40 percent difference, very irregular canopy, stocking very patchy or 

irregular)—has not been tested.

Table 37. Definition of polygon features that provide suitable nesting habitat for Marbled Murrelet in 

British Columbia, as recommended by the Canadian Marbled Murrelet Recovery Team. 

[From Bertram and others, 2003; see also Burger, 2004. The features are grouped by the likelihood that polygons with 

these features will contain a large proportion of suitable nesting habitat. Additional features are described in the text, p. 

116-117. No feature should be used in isolation but in combination with other features in developing algorithms. Symbols: 

>, greater than; <, less than]

Nesting Habitat: Characteristics, Threats, and Trends 117
British Columbia (Burger, 2002). A province-wide mapping 

program that applies an algorithm proposed by the CMMRT 

(Bertram and others, 2003) is nearing completion (T. Chatwin 

and M. Mather, British Columbia Ministry of Environment). 

Preliminary results from such analyses indicate areas of 

habitat ranging from 1.5 to 2 million hectares of likely suitable 

habitat in British Columbia. This is approximately distributed 

in the six Marbled Murrelet Conservation Regions (Bertram 

and others, 2003; see also fig. 7) as follows: Southeast 

Vancouver Island: 4 percent; West and North Vancouver 

Island: 25 percent; Southern Mainland Coast: 10 percent; 

Central Mainland Coast: 28 percent; Northern Mainland 

Coast: 19 percent; Haida Gwaii (Queen Charlotte Islands): 

14 percent.

Threats to Nesting Habitats

The principal threats to Marbled Murrelets in their use 

of the terrestrial environment for nesting are related to losses 

or changes in nesting habitat. When using inland habitats for 

nesting, adult murrelets also are exposed to increased risk of 

predation. Nests also can be lost to terrestrial predators. Many 

of the threats to murrelets in the terrestrial environment are 

anthropogenic. Here we consider the main threats to Marbled 

Murrelets related to nesting, focusing on: 

1. Direct loss of suitable nesting habitat from timber harvest; 

2. Fragmentation and edge effects; 

3. Increased predation risk;

4. Effects of human disturbances at nest sites on adults and 

chicks; and 

5. Changes in nesting habitat from natural forest processes 

such as wildfire, insect/disease, and windthrow. 

These factors are discussed in the following sections as 

they pertain to the recent past, current, and projected future 

nesting habitat conditions for the Marbled Murrelet in Alaska 

and British Columbia.

Losses of Suitable Nesting Habitat from Timber 

Harvest

Timber harvest has occurred at some level throughout the 

entire old-growth forest nesting range of the Marbled Murrelet 

in Alaska and British Columbia. Industrial-scale logging has 

occurred primarily in SEAK and British Columbia. Timber 

harvest from south-central Alaska makes up only 1–3 percent 

of the total harvest for Alaska (U.S. Forest Service, 2002b). 

Logging levels also have varied through time. In this section, 

we review available information about losses of old-growth 

forest suitable (or known to be used) for murrelet nesting in 

Alaska and British Columbia.

Southeast Alaska

Industrial-scale logging began in SEAK in the 1950s. 

The exact number of hectares logged is not known, but the 

available estimates range from 267,400 to 364,500 ha. Albert 

and Schoen (2006) estimate that about 318,000 ha of forested 

land have been harvested, with 188,800 ha on Federal land 

and 129,500 ha on private or other lands. Their analysis also 

found that 12 percent of old-growth forests, and 28 percent 

of large-tree forest types have been harvested since industrial 

logging began in 1954. Barbour and others (2005) determined 

that by 2001, 267,400 ha in SEAK had been harvested with 

175,400 ha on National Forest land; 79,600 ha on native 

corporation lands; and 12,400 ha on State and other lands. Of 

this, about 162,000 ha of high-volume old growth forest has 

been clearcut (Szaro and others, 2005). DeGange’s (1996) 

review found that 184,856 ha of Tongass National Forest 

lands were cut by 1995, and an additional 303,750 ha had 

been conveyed to the State of Alaska or to Alaska Native 

corporations. Iverson and others (1996) suggest that perhaps 

60 percent of those conveyed lands were harvested by 1995, 

bringing the total harvested forest estimate to 364,500 ha 

(DeGange, 1996). 

Historically, timber in the Tongass National Forest was 

not harvested equally across all volumes of productive forest. 

Early harvest practices were more focused on logging the very 

large trees, and less restricted by regulations that were enacted 

later, such as the Tongass Land Management Plan (TLMP) 

and Tongass Timber Reform Act (TTRA; see section, ‘General 

Forest Management Practices’; Albert and Schoen, 2006). 

The pattern of harvesting the most productive and structurally 

most complex forest was consistent through 1994 (Iverson 

and others, 1996). Areas logged after 1986 were 29 percent 

large-tree, 65 percent medium-tree, and 6 percent smalltree productive old growth types. Furthermore, large-tree 

forests were logged at a rate that exceeded their proportional 

abundance by 2.89 times (table 39). Logging also focused 

disproportionately on the most productive landforms, such as 

low-elevation karst and riparian forests (Albert and Schoen, 

2006). These are among the most productive terrestrial 

habitats of SEAK and are likely to contain the forest types 

most preferred by the Marbled Murrelet. 

In recent years, demand and harvest of timber in the 

Tongass has decreased significantly (Hanley and others, 2005). 

From 1990 to 2004, timber harvest decreased by 67 percent 

primarily due to changes in the International market (Brackley 

and others, 2006). The two pulp mills awarded long-term 

contracts in the 1950s have closed, and harvests on Native 

lands decreased dramatically in the early 1990s because much 

of the best timber has already been cut (see section, “Effects 

of Forest Management Practices on Nesting Habitat”; Knapp, 

1992).

118 Status Review of the Marbled Murrelet in Alaska and British Columbia
At the regional-scale, harvests within eight regions 

(E. Baranof, W. Baranof, Etolin/Zarembo, Kupreanof/Mitkof, 

Dall Island Complex, Revilla/Cleveland Peninsula, North 

Prince of Wales, and E. Chichagof) have removed 35–70 

percent of the original large-tree forests (table 40). Four of 

those regions (Etolin/Zarembo, Kupreanof/Mitkof, Revilla/

Cleveland Peninsula, and North Prince of Wales) have 

30 percent or more of the large-tree old-growth stands in the 

timber base.

South-Central Alaska 

The total amount of land area harvested in south-central 

Alaska is not known, however, van Hees (2005) estimated 

that 2062.9 MMBF (scaled post harvest) were harvested from 

1988 to 2001 (table 41). About 97 percent of the harvest 

occurred on private land, 2 percent on State land, and 1 

percent on National Forest land. For the Chugach National 

Forest section of Southcentral, less than 1 percent of the 

forested land has been harvested in the last 30 years (U.S. 

Forest Service, 2002b). The amount of forest harvested on 

6,642 ha of private lands within the Chugach National Forest 

boundary is unknown but expected to be minimal. Although 

the total amount of forest harvested on 168,500 ha of Native 

Corporations’ land within the Chugach boundary is unknown, 

forest managers speculate that several thousand acres have 

been harvested in the last 15 years. Most native harvests have 

occurred in eastern Prince William Sound, Montague Island, 

east of Cordova and the Kenai Peninsula. The State owns 

about 154,400 ha of land within the Chugach boundary and 

less than 404 ha have been harvested (U.S. Forest Service, 

2002b). Timber harvest levels in south-central Alaska have 

declined in recent years (table 41).

The amount of mature and old-growth forest decreased 

by 3,110 ha (17 percent) over a 25-year period between 1974 

and 1999 on Chugach National Forest lands portion of the 

Kenai Peninsula (table 42; U.S. Forest Service, 2002b). From 

1980 to 1999, 35.4 MMBF were harvested from the Chugach 

National Forest at an average annual rate of 1.8 MMBF per 

year. The rate of loss of old-growth and mature forest cover 

classes on the Kenai Peninsula averaged 0.72 percent per year. 

The rate of loss on other portions of the forest is unknown, but 

likely less than this (DeLapp and others, 2000). 

Kodiak Archipelago

The land cover/vegetation classification of the Kodiak 

Archipelago is the result of the digital image analysis of a 

three date series of Landsat ETM + scenes acquired between 

September 1999 and September 2000 (M.D. Fleming and P. 

Spencer, U.S. Geological Survey, unpub data, 1999–2000). 

There are 107,129 ha of old growth forest within the Kodiak 

Archipelago, with 92,867 ha (87 percent) located on Shugak 

and Afognak Island (M.D. Fleming and P. Spencer, U.S. 

Geological Survey, unpub data, 1999–2000). 

Afognak land is largely private, with the exception of 

the Kodiak National Wildlife Refuge and the Afognak Island 

State Park (fig. 34). Most of the logging has been done 

on private land since the 1980s. The vegetation survey of 

1999–2000 (M.D. Fleming and P. Spencer,U.S. Geological 

Survey, unpub data, 1999–2000) allows us to quantify both 

the area of existing old growth forest and the area of logged 

land on Afognak and Shuyak islands (fig. 35, table 43). 

Old growth forest is described as Dense Sitka Spruce 

Forest—areas of dense stands of 60–100 percent crown 

closure. However, it generally is not known how suitable 

the old-growth on Afognak Island is for Marbled Murrelet 

nesting. Four tree nests of Marbled Murrelets are known from 

the Kodiak Archipelago (table 26) and Kuletz and others 

(1995a) found the highest numbers of detections on Afognak 

Island compared to sites in Prince William Sound and in the 

Kenai Fjords. However, Three categories of vegetation fall 

Forest types

Forest types logged Availability of forest types

Index of 

selectivity acres percent 

use

acres percent

available

Large-tree 70,839 29.3 588,871 10.1 2.89

Medium-tree 156,572 64.6 4,334,410 74.6 0.87

Small-tree 14,810 6.1 883,874 15.2 0.40

Total 242,221 100 5,807,155 100

Table 39. Rate of logging for forest types potentially suitable for Marbled Murrelets 

on the Tongass National Forest in Southeast Alaska.

[Figures are based on logging since 1986 to 2000 for which data on previous forest structure was 

available (n = 242,221 acres; Albert and Schoen, 2006). Index of selectivity = percent use / percent 

availability]

Nesting Habitat: Characteristics, Threats, and Trends 119
under ‘Logged land’: (1) Sitka Spruce Regeneration—areas 

that have been logged within the past 15–30 years and are 

re-vegetating with spruce saplings; (2) Salmonberry-Devil’s 

Club-Elderberry—areas exclusive to recently logged stands 

which were dense Sitka spruce, and (3) Sand and Gravel 

Roads. As of 1999–2000, there were 92,867 ha of existing old 

growth forest, and 17,348 ha of logged land (table 43; M.D. 

Fleming and P. Spencer, U.S. Geological Survey, unpub data, 

1999–2000).

British Columbia 

There have been three attempts to quantify the loss 

of likely murrelet nesting habitat in British Columbia. The 

first, in 2000 by M. Eng (British Columbia Ministry of 

Forests) involved fairly broad assumptions and used relatively 

crude estimates of likely habitat applied to coarse-scale 

biogeoclimatic mapping (see above). This analysis suggested 

that throughout coastal British Columbia, 33 percent of 

nesting habitat was removed by 1973 and 49 percent by 2000 

(table 38). This analysis was undertaken during the review of 

the murrelet’s Canadian status by COSEWIC (Hull, 1999), 

and was followed by confirmation of the species’ Threatened 

status in Canada.

The second attempt by Demarchi and Button (2001a, 

2001b) was reviewed in Burger (2002b). Habitat ratings were 

based on the standard six-class system for wildlife in British 

Columbia (Resource Inventory Committee [RIC], 1999), 

and were developed by Demarchi (2001) in collaboration 

with government wildlife biologists familiar with murrelets. 

These were then applied to habitat polygons derived from 

1:250,000 Broad Ecosystem Inventory mapping. This scale 

Province

Large-tree 

forests

(acres)

Productive old growth

(POG) Timber harvest Percent of 

original

POG

harvested

Percent of 

original

large-tree forest

harvested

Index of

selectivity

(acres) (percent) (acres) (percent)

N. Prince of Wales 130,649 632,303 11.33 295,782 37.8 31.9 39.8 2.59

Dall IslandComplex 9,654 108,864 1.95 26,885 3.4 19.8 44.9 1.61

Yakutat Forelands 27,576 82,841 1.48 18,290 2.3 18.1 16.3 1.47

Kupreanof/ Mitkof Islands 21,302 357,721 6.41 67,619 8.6 15.9 48.1 1.29

Etolin/ Zarembo Island 12,128 230,651 4.13 41,300 5.3 15.2 49.9 1.23

E. Chichagof Island 37,775 438,249 7.85 71,483 9.1 14.0 35.6 1.14

Outside Islands 13,573 118,490 2.12 18,404 2.4 13.4 28.4 1.09

E. Baranof Island 2,016 91,309 1.64 13,797 1.8 13.1 66.7 1.07

Chilkat River Complex 20,984 138,538 2.48 19,940 2.6 12.6 21.8 1.02

Revilla Is./ Cleveland Pen. 32,045 580,282 10.40 72,838 9.3 11.2 39.9 0.91

South Prince of Wales 43,490 168,570 3.02 17,881 2.3 9.6 10.7 0.78

Kuiu Island 36,331 290,855 5.21 29,670 3.8 9.3 19.3 0.75

W. Baranof Island 4,795 236,137 4.23 19,445 2.5 7.6 54.3 0.62

Taku River/ Mainland 23,914 344,340 6.17 21,540 2.8 5.9 20.8 0.48

Stikine River/ Mainland 21,207 334,943 6.00 15,031 1.9 4.3 17.2 0.35

Admiralty Island 99,937 606,438 10.87 27,103 3.5 4.3 7.4 0.35

Lynn Canal/ Mainland 16,748 212,334 3.80 6,282 0.8 2.9 9.9 0.23

North Misty Fjords 16,449 217,164 3.89 0 0.0 0.0 0.0 0.00

South Misty Fjords 14,171 316,370 5.67 0 0.0 0.0 0.0 0.00

W. Chichagof Island 2,023 74,397 1.33 0 0.0 0.0 0.0 0.00

All provinces 586,766 5,580,795 100.00 783,288 100.0 12.3 28.1

Table 40. Distribution of productive old-growth forest types and percent of timber harvest within 20 biogeographic provinces in 

Southeast Alaska.

[Albert and Schoen, 2006. Glacier Bay and Fairweather Icefield provinces are not included. Percent of original large-tree forest harvested was estimated by 

extrapolating the rate of logging of large-tree forests after 1986 from areas with known forest structure (29.3 percent) to all areas logged. Index of selectivity 

equals the percentage of timber harvested divided by the percentage of original distribution of productive forests among provinces]

120 Status Review of the Marbled Murrelet in Alaska and British Columbia
Figure 34. Land use of Afognak Island.

Year

Estimated timber harvest volume (million board feet)

National 

Forest State Private All owners

1988 1.0 2.1 85.6 88.7

1989 1.5 2.1 120.0 123.6

1990 1.5 1.0 105.1 107.6

1991 1.5 2.5 134.5 138.5

1992 0.5 1.0 123.5 125.0

1993 1.7 0.0 127.2 128.9

1994 6.5 0.0 186.0 192.5

1995 1.9 2.6 230.1 234.6

1996 3.3 8.1 207.6 219.0

1997 2.2 8.6 237.1 247.9

1998 1.5 5.0 172.2 178.7

1999 0.4 5.4 139.9 145.7

2000 0.3 1.8 56.3 58.4

2001 0.4 2.1 71.3 73.8

Total 24.2 42.3 1,996.4 2,062.9

Table 41. Estimated timber harvest volume (million board feet, 

scaled post harvest) by year and owner group, south-central 

Alaska, 1988 to 2001.

[Adapted from van Hees, 2005. Source: U.S. Department of Agriculture, 

Forest Service, Alaska Region. Data on file with Ecosystems Planning, U.S. 

Department of Agriculture, Forest Service, P.O. Box 21628, Juneau, Alaska 

99802-1628]

allows only a coarse analysis of habitat availability. Two 

maps were produced: the first showed habitat capability

(see Demarchi and Button, 2001a), indicating the likely 

pre-industrial distribution of suitable inland habitat in the 

past, based on biogeoclimatic conditions; the second map 

showed habitat suitability indicating the likely distribution 

and ranking of inland nesting habitat in 2001. Comparisons 

between the capability mapping (predicted historical) and 

suitability mapping (present status) showed considerable 

changes in many areas, primarily due to industrial logging, 

urbanization and agriculture (Burger, 2002, fig. 4.10). Taking 

into consideration the top three habitat rankings (those most 

likely to be used by murrelets; Burger, 2002), this analysis 

indicated an overall loss of habitat by 34.6 percent, with 

particularly high habitat reduction on Vancouver Island, 

the southern Mainland, and Haida Gwaii (Queen Charlotte 

Islands) (table 44). Demarchi (2001) stressed that comparisons 

of habitat suitability and capability provide a meaningful 

expression of the loss of habitat potential but do not provide a 

measure of absolute habitat loss (i.e., square kilometer lost). 

The relative changes suggested by the Demarchi and 

Button (2001a, 2001b) analysis match the losses of old seral 

forests shown in a series of satellite images collated by the 

Nesting Habitat: Characteristics, Threats, and Trends 121
Figure 35. Areas of logged and old growth forest on Afognak and Shuyak Islands, Kodiak Archipelago as of 2000 

(M.D. Fleming and P. Spencer, U.S. Geological Survey, unpub. data, 2000).

Structure class Acreage in

1974

 Percent forest

acreage in

1974

Acreage in

1999

 Percent forest

acreage in

1999

Acreage

change

Percent

change

None 42,233 19.2 39,676 18.0 -2,557 -6

Seed/sapling 14,494 6.6 18,795 8.5 (+) 4,301 (+) 29.7

Pole 111,010 50.5 103,311 47.0 -7,701 -6.9

Young saw 9,254 4.2 8,334 3.8 -920 -9.9

Old saw 42,997 19.5 35,298 16.0 -7,699 -17.9

Standing dead 0 0 14,574 16.6 (+) 14,574

Table 42. Changes in forest size class distribution of the Chugach National Forest portion of the Kenai Peninsula from 

1974–99 (National forest lands only).

[Source: Chugach National Forest GIS corporate database and Kenai Forest Successional Model (DeLapp and others, 2000)]

122 Status Review of the Marbled Murrelet in Alaska and British Columbia
The third attempt to analyze habitat loss was by Holt 

(2004) for Haida Gwaii (Queen Charlotte Islands), using a 

refined version of a GIS habitat algorithm originally developed 

for this archipelago by McLennan and others (2000). This 

analysis indicated a 42 percent decrease in likely nesting 

habitat due to industrial logging (fig. 38). This estimate of loss 

is considerably higher than the 15 percent decrease suggested 

for this region by Demarchi and Button (see table 44). The 

discrepancy is in part due to the coarse-scale nature of the 

Demarchi and Button (2001a, 2001b) analysis. The Holt 

(2004) estimate, based on a local habitat algorithm and more 

detailed GIS mapping, is likely closer to reality. 

A more detailed analysis of currently available and past 

decreases of nesting habitat throughout British Columbia 

by the British Columbia Ministry of Environment is nearing 

completion (December 2006), but the results are not yet 

available. 

In summary, several independent analyses show 

significant reductions in nesting habitat for Marbled Murrelet 

in British Columbia. It is likely that 33–49 percent of habitat 

area has been lost due to industrial logging. The uncertainty 

in estimating habitat loss arises primarily from problems in 

reliably predicting habitat suitability from GIS databases (i.e., 

satellite imagery, interpretation of aerial photography, or forest 

cover mapping; see Tripp, 2001; Burger, 2002). Losses have 

been disproportionately high in regions known to support a 

high proportion of the British Columbia nesting population 

(i.e., Vancouver Island, Haida [Queen Charlotte Islands] 

Gwaii I). Radar studies in British Columbia have consistently 

shown significant correlations between the areas of available 

habitat and numbers of murrelets (Burger, 2001a; Burger and 

others, 2005), suggesting that murrelet populations in British 

Columbia are likely to have declined by a similar proportion to 

the habitat reductions. 

Fragmentation and Edge Effects

Fragmentation of forested habitat occurs when 

contiguous areas of forest are reduced to smaller isolated 

fragments through logging or other forms of habitat 

modification. The ecological consequences of fragmentation 

include effects on population viability and size, local or 

regional extinctions, displacement, fewer nesting attempts, 

failure to breed, reduced number of nests, lower nest success, 

increased predation, crowding in remaining patches and 

overall reduction of adult survival (Andrén, 1995; Raphael 

and others, 2002b; McShane and others, 2004). The effects 

of distance to the edge habitats can vary with the structure 

of the adjacent forested habitat and with distance to human 

activity (Raphael and others, 2002b), however, higher nest 

success has been found farther from the forest edge in some 

studies (Nelson and Hamer, 1995; Manly and Nelson, 1999). 

In this section, we discuss relevant information on the effects 

of fragmentation and edge habitats based on recent reviews 

(Burger, 2002; McShane and others, 2004).

Vegetation category Hectares

Old growth 

forest Dense Sitka Spruce forest 92,867

Logged land Sitka Spruce regeneration 3,149

Logged land Salmonberry-Devil’s Club-Elderberry 10,034

Logged land Sand and gravel roads 4,165

Logged land Total logged 17,348

Table 43. Area of old growth forest and logged land on Shuyak 

and Afognak Islands as of 1999–2000.

[From M.D. Fleming and P. Spencer, U.S. Geological Survey, unpub. data, 

2000]

Forest district

Percentage of area in classes 1-3

Capability Suitability Percent 

change

Port Alberni1 64 34 46.9

Campbell River1 61 36 41

Haida Gwaii (Queen 

Charlotte Islands)

53 45 15.1

Duncan1 53 12 77.4

Port McNeil1 46 30 34.8

Mid-Coast 29 26 10.3

Sunshine Coast 27 8 70.4

North Coast 26 24 7.7

Squamish 13 7 46.2

Chilliwack 13 6 53.8

Kalum 10 8 20

Cassiar 3 0 100

Chilcotin 3 0 100

Whole BC Coast 26 17 34.6

1

 Forest Districts on Vancouver Island.

Table 44. Likely changes in the availability of moderate to very 

high quality nesting habitat (habitat classes 1-3 combined; see 

Burger, 2002) for Marbled Murrelets in each forest district, and for 

the entire British Columbia coast. 

[Data from Demarchi and Button, 2001a, 2001b. Capability represents the 

ability of the land base to produce habitat in which murrelets could nest, and 

suitability represents the current availability of such habitat. In this table the 

combined percent area within the top three habitat classes is shown, along 

with the percent change from capability to suitability. Forest districts are 

ranged from highest to lowest percent capability]

Sierra Club of Canada for coastal British Columbia (fig. 36) 

and Vancouver Island (fig. 37). A high proportion of the “old 

rainforest” mapped from these satellite images would have 

been suitable nesting habitat for Marbled Murrelets, because 

the pre-1999 logging was concentrated in low-elevation, 

accessible forests with the largest trees. Recent GIS analysis 

has confirmed that the Sierra Club of Canada’s selection of 

“old rainforest” was a reasonably good measure of likely 

habitat on southern Vancouver Island (Dr. R. Page, University 

of Victoria, unpub. data, 2006).

Nesting Habitat: Characteristics, Threats, and Trends 123
Most of the available information on the effects of 

habitat fragmentation and edge on Marbled Murrelets has 

come from studies conducted in WOC, and British Columbia 

(McShane and others, 2004). Therefore, some caution should 

be taken when applying the results of these studies to tree 

nesting murrelets in Alaska. Although forest habitat in SEAK 

may be more similar to British Columbia habitats due to 

the contiguous nature of the forest in these areas, the forest 

landscape is very different in south-central Alaska. Here, it has 

been estimated that only 10 percent of all south-central Alaska 

timberland were capable of producing large tree stands (van 

Hees, 2005). In addition, the stands in south-central containing 

the greatest tree volume generally are found near tidewater 

along shorelines, at the lowest elevations, or often occur as 

long narrow stringers between extensive open wetlands or 

non-forest habitat types. Therefore, the forest habitat in southcentral may be naturally fragmented more often. 

The effects on murrelets of fragmentation of forests and 

the creation of artificial forest edges (e.g. at clearcuts and 

roads) were reviewed (Burger, 2002). Important points are as 

follows:

•	 Many nests were near natural and man-made forest

edges. It is not clear whether murrelets consistently 

prefer to nest near edges in all habitats, or whether they 

are attracted to edge habitat by ease of access. 

Figure 36. Satellite imagery showing loss of old seral rainforest in coastal British 

Columbia by 1999 (Sierra Club of Canada).

Figure 37. Satellite imagery showing loss 

of old seral rainforest on Vancouver Island 

(Sierra Club of Canada).

124 Status Review of the Marbled Murrelet in Alaska and British Columbia
•	 Clearcut logging changes the microclimate near abrupt

forest edges. This may affect nest microhabitats 

(e.g., moss cover on branches), and is currently being 

studied in British Columbia (D. Lank, Simon Fraser 

University, oral commun., 2006). 

•	 Edges affect predation risk. Fragmentation and creation

of abrupt forest edges is likely to increase predation 

risk from corvids, especially Steller’s Jay. Several 

studies showed that this jay is most often found 

close to forest edges bordering clearcuts, and is more 

abundant in fragmented forest than in contiguous 

forest. The effects of forest fragmentation on other 

predators, such as squirrels and raptors, are less 

obvious or not significant. Murrelets sympatric with 

Northern Goshawks might suffer greater predation 

if both species are forced to share remaining patches 

of old-growth in heavily logged areas. Proximity 

to human activities, and the age and structure of 

forests bordering old-growth also affect abundance of 

predators. 

•	 Nest success relative to forest edges shows inconsistent

trends. In a sample of murrelet nests from across the 

Pacific Northwest, nests within 50 m of a forest edge 

had lower success than those greater than 50 m from an 

edge (38 and 55 percent, respectively, n = 29 in each 

sample), although this was not statistically significant. 

Successful nests were significantly farther from 

edges (mean 141 m) than failed nests (mean 56 m). In 

contrast, analysis of 98 nest sites in Desolation Sound 

showed that sites adjacent to natural edges appeared 

to have higher success than those in the forest interior, 

and there were no significant differences between nest 

sites adjacent to artificial versus natural edges, and 

artificial edges versus interior forest. The differences 

among the studies with regard to edge effects are 

likely due to variations in predation pressure, edge 

type, and local habitat availability (Lank and others, 

2003). Many of the Desolation Sound nests were in 

small, high elevation forest patches where there were 

few predators, whereas many of the other studies 

Figure 38. Estimated areas of suitable nesting habitat for Marbled Murrelet on Haida Gwaii (Queen Charlotte 

Islands), showing the likely changes between 1800 and 2000 (from Holt, 2004). Overall, this analysis showed a 42 

percent decrease in suitable habitat by 2000.

Nesting Habitat: Characteristics, Threats, and Trends 125

AK20-0056_fig38

Marbled Murrelet

Habitat Suitability Model

1800

Class 1 (Highly Suitable)

Class 2 (Suitable)

Class 3 (Moderately Suitable)

Class 4/5 (Unsuitable)

Wildlife Habitat Area

October 25, 2004 Map 20a

6-041

6-046

Habitat Suitability Indices (HSI) are derived from forest age,

forest height, crown closure, and elevation from sea level.

Habitat Suitability Index (HSI) Classes 1-4 are based on the

following ranges:

Class1: 54 - 60

Class2: 51 - 53

Class3: 46 - 50

Class4/5: 0 - 45

Marbled Murrelet

Habitat Suitability Model

2000

Class 1 (Highly Suitable)

Class 2 (Suitable)

Class 3 (Moderately Suitable)

Class 4/5 (Unsuitable)

Wildlife Habitat Area

October 25, 2004 Map 20b

6-041

6-046

Habitat Suitability Indices (HSI) are derived from forest age,

forest height, crown closure, and elevation from sea level.

Habitat Suitability Index (HSI) Classes 1 - 4 are based on the

following ranges:

Class1: 54 - 60

Class2: 51 - 53

Class3: 46 - 50

Class4/5: 0 - 45
were in low elevation sites with high predation risk. In 

addition, none of the Desolation Sound sites involved 

forest edges near human settlements or other sites 

of human activity likely to attract corvid predators, 

which are known to affect predation risk for murrelets 

(Luginbuhl and others, 2001; Raphael and others, 

2002b).

•	 Simple geometric models of the possible effects of

edges, relative to forest patch area, suggest that effects 

restricted to 50 m of artificial edges would affect a 

progressively larger portion of the forest as patch areas 

declined below 200 ha. Likely effects on breeding 

success would increase most rapidly as patch areas 

declined below about 50 ha. The shape of the forest 

patch also affects the proportion of edge habitat, and 

the proportion of the patch bounded by natural edges 

would modify edge effects. 

•	 The type of edge (natural versus man-made) and the

habitat bordering an old-growth patch (e.g., recent 

clearcut or maturing forest) appear to affect nesting 

success and predation risk, and need to be considered 

in planning protected habitats for murrelets. Natural 

edges (e.g., bordering avalanche chutes or bogs) seem 

to produce fewer negative effects than hard man-made 

edges bordering recent clearcuts and roads.

Predation Effects

The life history and behavior of the Marbled Murrelet has 

been shaped by predation pressure. Despite secretive behaviors 

and cryptic plumage, the Marbled Murrelet is still highly 

susceptible to predation, especially during nesting. In this 

section, we present the potential changes in predation pressure 

based on an analysis of Christmas Bird Count (CBC) data and 

we briefly discuss what is known about predation on murrelets 

in Alaska. 

To explore potential changes in recent predation pressure 

on murrelets, we evaluated trends in abundance of seven 

confirmed or suspected murrelet predators in coastal (<25 

km from shoreline) regions of Alaska and British Columbia. 

Using Christmas Bird Count (CBritish Columbia) data, we 

calculated the normalized deviation in abundance for each 

species from 1970 to 2006 (fig. 39) after adjusting for count 

effort (Sauer and others, 1996). 

Over the 36-year period in Southeast Alaska, there was 

a marked increase in abundance of Bald Eagles (Haliaeetus 

leucocephalus) during the late 1980s (ca. 3-fold increase) but 

numbers apparently decreased again during the late 1990s 

(fig. 39). Periodic Bald Eagle surveys conducted during 

summer by the FWS between 1967 and 2002 revealed a 

similar marked increase during the late 1980s, but much 

less of a decline in the 1990s (Jacobson and Hodges, 1999; 

P. Schempf, U.S. Fish and Wildlife Service, oral commun., 

2006). Eagle populations in Prince William Sound during 

summer also increased by about 60 percent between 1982 and 

1995, but declined about one-third by 2005 (P. Schempf, U.S. 

Fish and Wildlife Service, oral commun., 2006). In SEAK, 

numbers of Steller’s Jays observed on CBritish Columbias 

about tripled up until about the mid-1990s, but counts returned 

to average after that time. Sharp-shinned Hawks (Accipiter 

striatus) and Common Raven (Corvus corax) counts increased 

steadily and significantly during the 36 years (fig. 39), with 

numbers about doubling over that time-span. 

In British Columbia, four of seven predators increased 

significantly in abundance on CBritish Columbias (fig. 39), 

and some of these changes were quite large: Bald Eagles 

increased about 8-fold, Peregrine Falcons (Falco peregrine)

tripled, and populations of Steller’s Jays and Common 

Ravens about doubled. Northwestern Crow (Corvus caurinus) 

populations changed little, while Northern Goshawks 

(Accipiter gentilis) exhibited a significant decrease to 

about one-half of historic count numbers. These striking 

changes in British Columbia may be a direct result of forest 

fragmentation and urban development in the Georgia Basin 

during the past 30 years. 

Studies have clearly shown that an increase in abundance 

of native predators can cause declines in bird populations 

(Cote and Sutherland, 1997, Parrish and others, 2001) but it 

is difficult to quantify those impacts. Experiments in which 

changes in both vertebrate predator and prey populations are 

manipulated and monitored in temperate forest systems are 

rare. Once such study (Marcstrom and others, 1989) showed 

that an approximate doubling or tripling of the population 

of predators— i.e., similar to that noted in the CBritish 

Columbia data— caused a rate of decline in prey as great as 

that observed for Marbled Murrelets in Alaska and British 

Columbia (see section, “Population Status and Trends”). 

Predation pressure can have multiple indirect effects on prey 

species including alteration of foraging behavior (Sinclair 

and others, 1998) and timing of breeding (Lima, 1998). 

An increase in predators can exacerbate existing effects of 

habitat degradation, fragmentation, and destruction (Cote 

and Sutherland, 1997). Predation pressure can directly slow 

or prevent the recovery of a population (Sinclair and others, 

1998) and a stable but reduced population increases the risk 

of extinction through random events (Cote and Sutherland, 

1997).

Other evidence suggests predation may be a factor 

in adult survival. Marbled Murrelets were found to be an 

important prey item for Northern Goshawks in SEAK (Lewis 

and others, 2006). Eleven Marbled Murrelets were delivered 

to six different goshawk nests, based on video recordings at 

nests, and a total of 31 Marbled Murrelets were delivered to 21 

different goshawk nests, based on prey remains and deliveries 

combined.

126 Status Review of the Marbled Murrelet in Alaska and British Columbia
In an ongoing study in SEAK, 32 Marbled Murrelets 

were radio-tagged over 3 nights between June 28–29 to 

June 30–July 1 (Newman and others, 2006). One bird 

(3 percent) was repeatedly detected on land on Admiralty 

Island soon after marking and was presumed to have been 

eaten by a Bald Eagle (Haliaeetus leucocephalus)—a species 

which nested in relatively high densities on the island. 

Similarly, of 15 Kittlitz’s Murrelets radio-tagged in Icy Bay 

during 2006, 2 were killed by Peregrine Falcons, and 2 were 

killed by Bald Eagles (M. Kissling, U.S. Fish and Wildlife 

Service, oral commun., 2005). 

A naturalist aboard a 720-feet long cruse ship in Glacier 

Bay National Park, Bruce Whittington (Victoria Natural 

History Association, oral commun., 2005) observed a 

peregrine falcon prey upon at least four seabirds in a few short 

hours in a single day. These birds appeared to be Kittlitz’s 

Murrelets. He observed the falcon use the various masts 

and other boat structures as perches and, as the cruise boat 

approached adult murrelets on the water, the boat would flush 

these birds from the surface of the water. The falcon was then 

observed to take off and stoop on the fleeing seabirds, catching 

them within seconds and returning to the ship to consume 

them. He also reported talking with other shipboard naturalists 

and Alaska marine pilots and learned that several had seen 

Peregrines landing on ships, and some had seen the falcons 

taking seabirds near the vessels. 

Figure 39. Trends in numbers of murrelet predators observed on Christmas Bird Counts in southern coastal British 

Columbia (Campbell River, Comox, Deep Bay, Duncan, Ladner, Nanaimo, Pender Islands, Squamish, Sunshine Coast, 

Vancouver, Victoria, White Rock) and in Southeast Alaska (Craig, Glacier Bay, Haines, Juneau, Sitka). Plotted are 

normalized annual deviations from long-term average (1970–2006) of the total number of birds seen per party-hour of 

effort.

aibmuloC hsitirB nrehtuoS aksalA tsaehtuoS

Normalized Deviation

Normalized Deviation

Year

Bald Eagles

r 2 = 0.52, p<0.0001

Common Ravens

r 2 = 0.14, p<0.02

Northern Goshawks

r 2 = 0.28, p<0.01

Crow spp.

r 2 = 0.10, ns

Peregrine Falcons

r 2

 = 0.61, p<0.0001

Sharp-shinned Hawks

r 2

 = 0.04, ns

Steller's Jays

r 2 = 0.23, p<0.01

Bald Eagles

r 2

 = 0.02, ns

Common Ravens

r 2 = 0.23, p<0.01

Northern Goshawks

r 2 = 0.03, ns

Crow spp.

r 2 = 0.00, ns

Peregrine Falcons

r 2 = 0.0, ns

Sharp-shinned Hawks

r 2 = 0.17, p<0.02

Steller's Jays

r 2 = 0.04, ns

 1970 1977 1983 1989 1995 2001

Year

 1970 1977 1983 1989 1995 2001

Nesting Habitat: Characteristics, Threats, and Trends 127
Effects of Natural Forest Processes 

Disturbances such as disease, insect infestations, and 

windstorms are natural processes within the old-growth forests 

used by Marbled Murrelets for nesting in Alaska and British 

Columbia. These disturbances have the potential to affect the 

amount and quality of inland habitat for the Marbled Murrelet, 

particularly at the local and watershed scales. Fire and insect 

damage are uncommon throughout much of the coastal areas 

of British Columbia (Burger, 2002). Likewise, the wet climate 

in SEAK causes the threat of wildfires in coastal forests to be 

low (Snyder, 2006). A detailed review of disturbance to forest 

resources is beyond the scope of this report. However, in this 

section, we briefly review what is known about natural forest 

processes that may affect Marbled Murrelet nesting habitat. 

Long-lived trees become infested with heart-rot fungi, 

hemlock dwarf mistletoe, and root rot fungi as they age. Heart 

rot fungi affects nearly one-third the volume of trees in oldgrowth hemlock-spruce forests, causing them to be undesirable 

for commercial timber use. Small-scale disturbances such as 

heart rot fungi such as this may help to maintain the stability 

of old-growth stands when large old trees collapse and create 

a canopy opening that allows suppressed trees to grow. Decay 

fungi are essential for the productive stands in Southeast 

Alaska where wildfires are rare because they decompose 

branches, roots, and dead trees (Snyder, 2006).

Between 1987 and 2003, Spruce Beetle infestation 

affected 429,000 ha on the Kenai Peninsula (U.S. Forest 

Service, 2004; Boucher and Mead, 2006), and 240,000 ha 

in the Copper River Basin (Werner and others, 2006). On 

the Gulf Coast, mixed forests of mountain hemlock and 

Sitka spruce suffered the lowest regional mortality of spruce 

(22 percent reduction in Sitka spruce basal area) during 

the outbreak. Sitka spruce are poor hosts for supporting 

spruce beetle reproduction (Holsten and Werner, 1990) 

which likely influenced the low levels of spruce mortality 

during the outbreak and related vegetation change in this 

region. Although much of the spruce bark beetle infestations 

affected the boreal forest of the Kenai lowlands and regions 

farther inland, infestations also occurred in coastal areas near 

Kachemak Bay (Werner and others, 2006). Dawn watches 

and opportunistic observations (K. Kuletz, U.S. Fish and 

Wildlife Service, oral commun., 1997) indicated that Marbled 

Murrelets had nested in areas where trees later succumbed to 

beetle infestations. It is likely murrelet nesting habitat around 

Kachemak Bay was lost to beetle kill (Kuletz and others, 

1997). 

In SEAK, wind is an important natural disturbance 

agent that develops old-growth forest structure (Harris, 

1989; Nowacki and Kramer, 1998). The topology in SEAK, 

including extensive icefields, steep mountains and narrow 

channels, makes the region particularly susceptible to 

frequent maritime windstorms. Productive western hemlock 

and western hemlock – Sitka spruce forests are predisposed 

to blowdown because of their top-heavy nature (large and 

tall canopies) and shallow rooting (Harris, 1989). When the 

trees fall, uprooting and soil churning causes nutrient cycling 

and increased soil permeability (Snyder, 2006). Although 

windstorms can have a positive effect on unfragmented habitat 

by creating openings in the forest canopy, catastrophic storms 

can cause single-generation stands with uniform canopies to 

form. Large-scale wind disturbance (affecting 70–400 ha) 

has been documented on Chichagof, Kuiu, and Prince of 

Wales Islands (Nowacki and Kramer, 1998). In contrast, 

Hennon and McClellan (2003) found that frequent, smallscale disturbance helps to shape the forest structure in SEAK, 

with decay fungi and heart rot contributing the bole wounds 

and canopy breakage contributing to tree mortality. In some 

areas, wind disturbance and forest management practices have 

additive effects on old-growth loss because clearcuts are more 

prevalent in wind protected areas (Kramer and others, 2001). 

The recent die off of Alaska yellow-cedar will likely 

impact future forest composition in Southeast Alaska and 

British Columbia forests. Alaska yellow-cedar trees have 

declined throughout a 200,000 ha band throughout SEAK to 

at least 150 km south of the Alaska-British Columbia border, 

and most concentrations of dead trees were found between 

300–400 m elevation (Hennon and others, 2005). In SEAK, at 

least 202,500 ha of yellow cedar decline have been mapped to 

date (Snyder, 2006). Active tree mortality occurred in many 

southeast locations in 2005, indicating an intensification of 

the problem on previously impacted lands. Although still not 

completely understood, the cause appears to be related to 

spring freezing injury in open canopy forests characterized by 

reduced snowpack, and is currently hypothesized to be a result 

of climate change (Hennon and Shaw, 1994; Snyder, 2006). 

General Land Management Practices

The USDA Forest Service manages the majority of oldgrowth forests in southeast and south-central Alaska, therefore 

it is important to also consider the relevant land-management 

practices in these regions. In this section, we will discuss the 

historical and current land-management issues as it relates to 

timber harvest and Marbled Murrelet nesting habitat. We then 

discuss habitat reserves in the context of land management 

practices. Finally, we consider how nesting habitat for Marbled 

Murrelets in Alaska and British Columbia could change in the 

near future.

Industrial-scale logging in the Tongass began in the 

1950s when two pulp mills were awarded long-term contracts. 

Although logging began in the late 1800s in the Chugach, 

most of the harvest occurred in Prince William Sound and 

Afognak Island during the late 1960s and 1970s (U.S. Forest 

Service, 2002b). In 1971, the Alaska Native Claims Settlement 

Act (ANCSA) transferred about 223,000 ha from the Tongass 

128 Status Review of the Marbled Murrelet in Alaska and British Columbia
and 168,500 ha from the Chugach to Alaska Natives. Logging 

began shortly after the acquisition and although harvest data 

are limited on Native lands, Knapp (1992) estimated that 

3 billion board feet of timber were harvested on native lands 

in southeast from 1979 to 1989. Today, most timberland on 

native lands in SEAK has already been harvested (Nie, 2006).

Later, several acts of legislation were put into place 

to govern the way National forests were managed. The 

National Forest Management Act of 1976 (NFMA; 16 U.S.C. 

1604) required the USFS to develop management plans that 

provide for the diversity of plant and animal communities 

within National forests. This requirement was interpreted as 

“maintaining habitat to support viable and well-distributed 

populations of existing native and desired nonnative species 

in the planning area,” where viable referred to “the likelihood 

that habitat conditions will support persistent and well 

distributed fish and wildlife populations over time” and well 

distributed referred to the natural distribution and dispersal 

capabilities of individual species over their current and recent 

distribution in SEAK (Julin, 1997). 

The Alaska National Interest Lands Conservation Act 

(ANILCA) of 1980 set aside 2.2 million ha of the Tongass and 

638,000 ha of the Chugach (of 22.6 million ha in Alaska) as 

Federally designated wilderness. In addition, ANILCA set a 

priority for subsistence use, and it created a timber utilization 

plan that was interpreted for the Tongass as a provision to 

supply at least 450 MMBF of timber per year regardless of 

cost or market demand (Nie, 2006). Later, the TTRA of 1990 

was put in place to correct the timber supply mandate in 

ANILCA with new language that required the USFS to meet 

market demand for timber. 

The most recent versions of LMPs were adopted in 

2002 and 1997 for the Chugach and Tongass National 

Forests, respectively. The plans set forest-wide goals and 

objectives, and management prescriptions, as well as landuse designations provided a framework for reserves, natural 

setting, and development areas. For the Tongass, roughly 

2.4 million ha were classified as wilderness and national 

monument, 3 million ha were set aside as natural setting, 

and 1.5 million ha were slated for moderate to intensive 

development such as timber and mineral production (Nie, 

2006). 

Allowable sale quantities (ASQ) also were set by the 

LMPs. For the Chugach, the ASQ was set at 6.3 MMBF for 

the first 5 years, and 10.6 MMBF for the next 10 years. The 

TLMP set the ASQ at 267 MMBF. However, the Tongass ASQ 

was based on an inaccurate interpretation of market demand 

and in August 2005 the 9th Circuit Court of Appeals ruled the 

plan arbitrary and capricious because it failed to consider the 

impacts of logging high-volume old growth forests. A revised 

version of the TLMP is expected in 2007.

Habitat Reserves

In SEAK, an estimated 57 percent of the Tongass is 

protected under the TLMP (Szaro and others, 2005). Although 

the TLMP is currently in a state of flux, as of June 2006, the 

draft proposed forest plan amendment proposal sets aside 

456,948 ha within the old-growth reserve LUD. Another 

1.06 million ha are designated under the wilderness LUD. 

Additionally, 1.25 million ha of land, including most of 

Admiralty Island and Misty Fjords, are within the Wilderness 

National Monument LUD where timber harvest is prohibited. 

About 43 percent of large-tree old growth forests in SEAK are 

protected under watershed-scale reserves (table 31). However, 

some areas of southern SEAK have a lower proportion of the 

large-tree forests protected under watershed-scale reserves. 

For example, North Prince of Wales, Kupreanof/ Mitkof, and 

Etolin/ Zarembo Islands have 13.5, 15.1 and 23.6 percent, 

respectively, designated within watershed-scale reserves 

(Albert and Schoen, 2006).

In south-central Alaska, about 32 percent of the forest 

land (525,200 ha) was withdrawn from timber use through 

statute or administrative regulation (van Hees, 2005; USFS, 

2002). Reserved lands include national parks, national forest 

wilderness study areas, and national wildlife refuges. In 

addition to lands officially designated as reserved, most of 

the forest land on the Chugach National Forest (75 percent) 

is not considered suitable for timber harvest under the 

revised Chugach LMP (Oja and others, 1999) because it is 

currently managed for other uses such as research natural 

areas, recreation areas, beach fringe, riparian areas, scenic 

viewsheds, and wild and scenic recreational rivers. Campbell 

and others (2005) estimate that 68 percent of this forest land 

in the south-central area is reserved from harvest; primarily 

on the Kenai National Wildlife Refuge, national parks, and 

the Chugach National Forest. The Chugach LMP manages 

as much as 75 percent of the forest for activities other than 

timber harvest with a focus on research, recreation, and 

wild and scenic rivers. Additionally, land acquisitions in the 

aftermath of the Exxon Valdez oil spill for injured species 

habitat restoration secured 331,362 acres of forested habitat 

in the Kodiak, Kenai Peninsula, and Prince William Sound 

areas (described if further detail in the section, “Ongoing 

Conservation Efforts”). 

In British Columbia, as of November 2006, about 

590,000 ha of likely nesting habitat is contained within 

protected areas (estimated areas vary considerably according 

to which habitat algorithm is used, and the varying reliability 

of GIS source data and final estimates are not available; 

T. Chatwin and M. Mather, British Columbia Ministry 

Environment, oral commun., 2006). This represents between 

25 and 30 percent of the estimated total habitat area within 

British Columbia. Most of the protected areas (about 456,000 

ha) fall within large provincial and national parks (e.g., 

Carmanah-Walbran and Strathcona provincial parks, and 

Pacific Rim and Gwaii Haanas national park reserves) and 

Nesting Habitat: Characteristics, Threats, and Trends 129
areas proposed for protection under the 2006 North Coast 

and Central Coast land-use decisions (e.g., Kwinamass River, 

Upper Ecstall, Khutzemateen, and Kitlope watersheds on 

the North Coast, and Spirit Bear, Koeye, and the Ahnuhati 

drainage complexes on the Central Coast). 

A further 115,000 ha (approximately) of likely habitat 

is maintained in OGMAs, riparian reserves, and other 

designations restricting forest development. Finally, about 

18,400 ha are maintained within the 124 Marbled Murrelet 

WHAs.

The current total area of protected habitat constitutes 

less than one-half of the 70 percent of 2002 habitat areas 

recommended for long-term maintenance by the CMMRT 

(Bertram and others, 2003). It is unclear whether the IWMS 

and other land-use planning exercises currently underway are 

sufficient to produce the outcomes called for in the CMMRT 

recovery strategy.

Nesting Habitat Projections

Loss of habitat from timber harvest will continue 

throughout the forested regions of Alaska and British 

Columbia. It is likely that in young stands, suitable nesting 

habitat will not develop for 150 or more years (Albert and 

Schoen, 2006; U.S. Forest Service, 2002b). For regenerated 

habitat, a delay in the development and structural complexity 

required for nesting is expected because development of 

suitable nesting habitat is dependent on trees attaining a 

size that supports nest platforms. Furthermore, the use of 

new habitat may lag for a considerable period because high 

philopatry leads to low rates of immigration. (McShane and 

others, 2004). In this section, we will discuss the potential for 

timber harvest projections using past rates of harvest. These 

rates should be viewed with caution as they are dependent 

on continued demand for timber and ever changing land 

management practices.

Southeast Alaska

Annual harvest rates for Tongass old-growth forests were 

classified by type of old-growth forest. Large tree productive 

old growth (POG) had a 0.85 percent, medium tree POG 

a 0.25 percent, and small tree POG a 0.17 percent average 

annual rate of decline (Albert and Schoen, 2006). Using 

these past average rates of decline, over the next 50 years, 

large-tree POG stands, considered to be the most suitable for 

Marbled Murrelets, could possibly show an additional 42.5 

percent decline with a loss of 92,003 ha from timber harvest 

activity. Over the next 50 years, medium and small-tree POG 

stands, could potentially decline by 12.5 percent (186,277 ha) 

and 8.5 percent (26,605 ha), respectively. These projections 

depend, of course, on demand for Tongass timber, which, 

as discussed above, has declined considerably since the late 

1990s.

Over the next 50 years, it is unlikely that any significant 

new old-growth forests will develop in southeast. Forest lands 

in Tongass National Forest are currently on a 100-year timber 

rotation, which does not allow enough time for suitable nest 

tree characteristics to develop (DeGange, 1996). Forests on 

private lands in Southeast Alaska are being clearcut resulting 

in increased forest fragmentation and general loss of suitable 

nesting habitat for Marbled Murrelets.

The location of current Timber Management and Oldgrowth Reserve LUDs relative to one another in southern 

SEAK make nesting habitat in this area particularly 

susceptible to habitat fragmentation. Although old-growth 

reserves have been designated, the placement of both LUDs 

creates a patchwork of forested habitat, especially on Prince 

of Wales Island, where 40 percent of the large-tree old growth 

has already been harvested (table 40). This may be especially 

important for Marbled Murrelets given the area of high marine 

density near the northern end of the island (fig. 32; fig. 40). 

South-Central Alaska

Although the land area statistics were not available, as 

of 2003, 18,933 MMBF of coniferous sawtimber (mature 

and old-growth trees) in south-central Alaska were available 

for future logging (van Hees, 2005). From 1988 to 2001, the 

rate of decline in mature and old-growth conifer forest stands 

averaged 0.8 percent annually. This 0.8 percent annual rate of 

decline represented a particularly volatile period of logging, 

where harvest rates greatly increased from 1993 to 1998 for 

all landowners. Harvest rates on private lands ranged from 

56 to just under 230 million board feet from 1988 to 2001 

(table 41). This large annual range in harvest rates makes 

it very difficult to predict future trends. However, if current 

average annual harvest rates were to continue, this would 

mean a 40 percent decline of mature and old-growth conifer 

forests, through removal of 7,573 million board feet in the next 

50 years. Although this is a dramatic rate of decline for mature 

and old-growth coniferous forests in south-central Alaska, it 

is uncertain whether past harvest rates would likely continue 

over the next 50 years. 

British Columbia

Logging and to a far lesser extent road-building, 

urbanization and agriculture will continue to erode nesting 

habitat in British Columbia. In contrast to the protection 

murrelets have had in the WOC area under the ESA, evidence 

of stand occupancy by murrelets does not prevent forest 

companies from logging old forests in British Columbia, either 

on private land or on public leased lands. The projected loss 

of habitat is not known. The rough estimates made in 2000 

by M. Eng (British Columbia Ministry of Forests) included 

a projected 10 percent loss of original habitat between 2000 

and 2030 (table 38), but this is not considered reliable. A 

project is underway to reliably estimate future losses in some 

130 Status Review of the Marbled Murrelet in Alaska and British Columbia
Figure 40. Timber management and old-growth reserve land use designations (LUD) in southern 

Southeast Alaska relative to density of murrelets at sea. Darker shades of grey represent higher marine 

density (relative scale).

Nesting Habitat: Characteristics, Threats, and Trends 131
forest districts in British Columbia (Malcolm Gray, Integrated 

Land Management Bureau, British Columbia Ministry 

of Agriculture and Lands). The management guidelines 

published by the Canadian Marbled Murrelet Recovery Team 

(Bertram and others, 2003) recommend habitat loss no greater 

than 30 percent of the 2002 area by 2032 (approximately three 

murrelet generations) in order to down-list the murrelet from 

Threatened to Special Concern in Canada. 

Loss of murrelet nesting habitat in the Sunshine 

Coast Forest District, southern mainland British Columbia 

was analyzed by Tomlins and Gray (2006). They used a 

combination of satellite imagery, land-use mapping (Baseline 

Thematic Mapping), forest inventory mapping (Vegetation 

Resources Inventory), and topographic data to identify 

murrelet habitat as defined by CMMRT (Bertram and others, 

2003). Their report does not indicate the area of habitat lost 

prior to 1985, but does show that in that year 57.5 percent 

of the 764,954 ha of forest was classified as younger than 

140 years (i.e., too young to be habitat), at which time likely 

murrelet habitat comprised 13.7 percent of the total forested 

area. Much of the forest lost to logging, and to a lesser extent 

fires and urbanization, prior to 1985 would have been in lowelevation forests with large trees (preferred by both murrelets 

and the timber industry), so the loss of murrelet habitat prior 

to 1985 would have been in the order of 50 percent. An earlier 

analysis using different habitat criteria suggested a 70 percent 

decline in murrelet habitat in this forest district (Demarchi 

and Button, 2001a, 2002b; Burger, 2002). Tomlins and Gray 

(2006) found that by 2005 murrelet habitat had declined by 

a further 12.0 percent of the 1985 area, and in 2005 likely 

murrelet habitat made up 12.1 percent of the total forested 

area (Tomlins and Gray, 2006). The annual rate of habitat loss 

had slowed considerably after 1993 (average <1 percent per 

year), as re-growth of forests into the 140+ age class partially 

balanced the loss of old growth.

Ongoing Conservation Efforts

In this section, we review ongoing efforts within Alaska 

and British Columbia that relate to conservation of the 

Marbled Murrelet. The Marbled Murrelet is not listed as 

Threatened or Endangered in Alaska under the ESA, thus there 

have been no federal efforts or directives aimed specifically 

at conservation of this species in Alaska. Region 7 (Alaska) 

of the USFWS considers Marbled Murrelets a species of 

management concern because of declining populations (U.S. 

Fish and Wildlife Service, 2002), but this designation does 

not confer legal status with respect to funding of studies or 

requirements related to resource extraction or development. 

Conservation efforts in Alaska, therefore, are largely indirect 

and tangential to larger programs with other conservation 

or management goals, such as management of State lands, 

management of National forests, oil spill prevention and 

response, and fisheries management. The only specific 

Marbled Murrelet conservation action we are aware of was 

the purchase of forested lands within the area affected by 

the EVOS to protect nesting habitat of the Marbled Murrelet 

(discussed in further detail below). In contrast, there are 

currently a variety of conservation efforts underway in British 

Columbia. Because the species is listed under both Federal and 

provincial statutes, there are imminent deadlines for recovery 

actions that are driving the current level of conservation effort. 

Although the level of conservation effort in British Columbia 

is currently greater than in Alaska, the British Columbia 

provincial government has been criticized for what many 

consider a slow response. Below, we describe the general 

protections being afforded in Alaska, and the more specific 

protections currently being implemented in British Columbia.

Alaska

State of Alaska Efforts

The Marbled Murrelet is currently a ‘featured species’ 

in the Non-Game Conservation Strategy of the Alaska 

Department of Fish and Game (2006), which has guided 

funding of several studies through the Federally funded State 

Wildlife Grant program. Studies funded by this program have 

included:

1. Decadal trends and current population estimates for 

Marbled and Kittlitz’s Murrelets in Kachemak Bay, 

Alaska, 2004–06;

2. Marbled Murrelet activity patterns in Port Snettisham, 

SEAK, 2004–06; and

3. Marbled Murrelet nesting habitat, activity patterns, and 

health in Port Snettisham, SEAK, 2005–07, using radiotelemetry. 

These studies represent a recent renewal of study effort 

on the species in Alaska, after the pulse of EVOSTC-funded 

studies of Marbled Murrelets tapered off.

Efforts in the Tongass and Chugach National 

Forests 

An interagency conservation assessment for Marbled 

Murrelets in SEAK (DeGange, 1996) concluded that a 

conservation strategy for murrelets in the Tongass National 

Forest should consider a reserve-based approach. DeGange 

(1996) recommended that old growth forests within 31 mi of 

the ocean and at lower elevations be targeted for preservation 

efforts. During the 1990s, the USFS conducted inland ‘dawn 

132 Status Review of the Marbled Murrelet in Alaska and British Columbia
watches’ to assess murrelet breeding activity in selected 

timber parcels of the Tongass National Forest (Brown and 

others, 1999). The USFS also conducted at-sea surveys in 

selected areas (see appendix M). To date, these data have 

not been analyzed, and have not been systematically used to 

manage selection of timber sales.

Farther north, the Chugach National Forest (U.S. Forest 

Service, 2002a) considered Marbled Murrelets a ‘management 

indicator species’ and a ‘species of interest’ in their Forest 

Plan revision process. The Chugach National Forest listed 

the Marbled Murrelet as an indicator species for late forest 

succession stands in the Kenai Peninsula and Prince William 

Sound, and for sheltered inshore waters in Prince William 

Sound and Copper River Delta (U.S. Forest Service, 2002a, 

tables 3–50 therein). Established standards and guidelines in 

the Chugach may provide some level of protection from forest 

management activities.

Oil Spill Prevention and Response

Oil spill prevention and response is organized around 

a Unified Command structure which includes the State and 

Federal on-scene coordinators (Berg, 2003). In the event of 

a spill, an inter-agency spill response team is mobilized to 

assess and mitigate the spill effects, including representatives 

from the USFWS as the trust agency for migratory birds. The 

USFWS may deploy damage assessment teams to monitor bird 

mortality and risk, and recommend ways to minimize impacts. 

Details on the organization and implementation of spill 

response relative to seabirds are available in Berg (2003). In 

Alaska, most spills have not been monitored for bird mortality 

beyond the immediate spill zone. Two citizen’s groups active 

in monitoring oil spill prevention and response in areas 

with high murrelet populations are the Cook Inlet Citizens 

Advisory Group and the Prince William Sound Citizens 

Advisory Council.

Fisheries and Marine Habitat Conservation

There are no Federal or State directives to conserve 

Marbled Murrelets or their foraging habitats at-sea in Alaska. 

However, restriction of some fishing activities in designated 

areas may benefit conservation of murrelets indirectly. 

Presidential Executive Order 13158 (May 2000) directed 

Federal agencies to work with States and other entities to 

develop a National system of Marine Protected Areas (MPAs). 

A National MPA program was reaffirmed by President Bush 

in 2001. A similar program has been mandated from the 

Canadian Federal government for British Columbia under the 

1997 Oceans Act. In November 2001, an ADFG Task Force 

was appointed to develop a strategy for developing a MPA 

program for the State. The Task Force prepared a report to 

provide background on MPAs, outline the strategy, and guide 

public input (Woodby and others, 2002). The report focuses 

on fisheries, but recognizes protection of other marine life, 

including seabirds. The task force was disbanded in 2003, and 

there is no further record of actions by the State on MPAs.

Woodby and others (2002) noted that, “Nationally, 17 

pieces of federal legislation provide a basis for establishing 

and managing MPAs; these include: the Magnuson-Stevens 

Fishery Conservation and Management Act, ESA, Migratory 

Bird Conservation Act, Fish and Wildlife Act (1956), and the 

Alaska National Interest Lands Conservation Act.” Alaska 

currently has semi- or protected areas that are considered 

MPAs under the State’s definition, which differs from the 

national definition in that it may include fishing with some 

temporal or gear closures, or single-species closures. These 

protective measures were established primarily to reduce 

bycatch of non-target species and to protect fish habitats 

(Woodby and others, 2002). Areas with limited or no fishing 

include large offshore areas closed to trawling in the eastern 

Bering Sea shelf, in eastern Gulf of Alaska, and in state waters 

from Kodiak westward to Bristol Bay (Witherell and others, 

2000). 

In waters 3–200 mi offshore (the Exclusive Economic 

Zone), NOAA-Fisheries has jurisdiction. Waters managed 

by the State extend from shore to 3 nmi offshore. Woodby 

and others (2002) listed more than 200 individual MPAs in 

18 categories in State and Federal waters in Alaska. These 

included “State critical habitat areas, State game refuges, State 

and Federal fisheries management zones, wildlife sanctuaries 

and refuges, and Alaska Coastal Zone Management Plan 

areas.” Examples of protected areas include no-transit zones 

around Steller’s sea lion (Eumetopias jubatus) rookeries 

(primarily in the Aleutian Islands and a few areas in the 

Kodiak Archipelago) and the Walrus Island State Game 

Sanctuary (in Bristol Bay), and no-trawl zones in the Aleutian 

Islands Habitat Conservation Area (71 FR 36694; June 28, 

2006). However, many other “MPA’s” listed in the report (e.g., 

the Kachemak Bay National Estuarine Research Reserve) do 

not carry any restrictions. 

Exxon Valdez Oil Spill Trustee Council

The EVOSTC was established with oil spill settlement 

funds, and between 1990 and 1999, the Trustees funded 

nearly annual studies on either nesting habitat or foraging 

requirements of Marbled Murrelets. The EVOSTC funded 11 

years of boat-based surveys of Prince William Sound through 

2007 (9 July surveys, 1989–2005), which provided data on 

population trends in the Sound. Through 2006, the EVOSTC 

has funded nearly $3.9 million in research studies pertaining 

or relevant to Marbled Murrelets.

Ongoing Conservation Efforts 133
The EVOSTC also purchased lands within the spill area 

for habitat protection with the explicit purpose of promoting 

the restoration of injured species, including Marbled 

Murrelets. Most lands were purchased for their ability to 

promote the restoration of one or more injured species. Since 

1993, the EVOSTC expended $375 million and purchased 

643,835 acres in both a large parcel (>1,000 acres) and small 

parcel program. Most large parcels acquired by the EVOSTC 

were purchased from Alaska Native Corporations. Many of 

these were large blocks of land including substantial timber 

holdings. Large parcels purchased with high value as Marbled 

Murrelet nesting habitat included:

•	 23,800 acres in Kachemak Bay State Park;

•	 32,537 acres in Kenai Fjords National Park and

adjacent islands within the Alaska Maritime National 

Wildlife Refuge;

•	 26,665 acres on Shuyak Island, at the northern tip of

the Kodiak archipelago;

•	 41,549 acres of mature spruce forest in the Kodiak

archipelago (now Afognak Island State Park); and

•	 206,811 acres of land, and conservation and timber

easements in Prince William Sound, including parcels 

on Bligh Island, Two Moon Bay, Eshamy Bay, Jackpot 

Bay, Port Gravina, Sheep Bay, and Windy Bay.

Although these acreages are small relative to the overall 

size of the region, because the lands included forest that could 

have been and perhaps were likely to have been logged, the 

transfer of the lands to public, protected status, is important to 

conservation of the Marbled Murrelets in the spill region.

Non-Governmental Entities

In 2001, partly in response to increased vessel traffic 

in Prince William Sound, the National Wildlife Federation 

sponsored a workshop on Biological Hot Spots in Prince 

William Sound. Collaborators included the USFWS, National 

Audubon Society, and the University of Alaska Marine 

Advisory Program. Specific areas of importance to Marbled 

Murrelets and their prey, as well as to other marine wildlife 

and habitats were identified in the workshop report (Adams 

and others, 2002).

British Columbia

As noted above, because the Marbled Murrelet is 

considered a threatened species in Canada and British 

Columbia, there is currently a concerted effort ongoing in 

British Columbia to plan for the species’ recovery. Here, we 

provide a detailed review of these efforts. 

Recovery Planning

The updated Canadian Marbled Murrelet Recovery 

Strategy has been drafted but is under review and should be 

released about June 2007. This document draws heavily on 

a Conservation Assessment undertaken by the CMMRT, the 

Federal government (Environment Canada), and the provincial 

government (British Columbia Ministries of Environment 

and Forestry), with the collaboration of universities, the 

forest industry, First Nations, and NGOs. The assessment 

produced three products: a biological review (Burger, 2002), 

management guidelines (Bertram and others, 2003), and risk 

modelling (Steventon and others, 2003). The final Recovery 

Strategy is expected to draw heavily from the management 

guidelines (Bertram and others, 2003). This document 

established two major goals for the recovery of Marbled 

Murrelets in Canada:

1. To down-list the species from Threatened to Special 

Concern. This would be possible by limiting the decline 

of the British Columbia population and its nesting habitat 

to less than 30 percent over three generations (30 years), 

during 2002 to 2032. The CMMRT recognized that the 

population in 2002 was likely reduced from historical 

levels, but believed that dealing with future declines was 

more realistic than trying to estimate and manage for past 

declines across the entire province; and

2. To ensure that the species would have a low risk of 

reduced viability after 2032. This might be achieved 

by maintaining sufficient suitable nesting habitat and 

reducing other threats at-sea and on land. This goal would 

allow the species to be considered for down-listing to 

Special Concern and eventually de-listed. 

Marbled Murrelet recovery actions are aimed at ensuring 

that there will be less than a 30-percent loss in population and 

nesting habitat between 2002–32, and that human-induced 

population decline will cease after 2032. The guidelines 

(Bertram and others, 2003) further established seven principles 

for formulating the Canadian Recovery Strategy: 

1. The initial goal of the Recovery Strategy will be to downlist the species from Threatened to Special Concern, using 

COSEWIC criteria for declining species. To down-list the 

species the immediate goal of the Recovery Strategy is to 

ensure that the population and suitable nesting habitat will 

not decline by more than 30 percent between 2002 and 

2032; 

2. The long-term goal of the Recovery Strategy will be to 

maintain the provincial population at a level which is 

sufficient to de-list the species using COSEWIC criteria. 

A key objective is to provide sufficient Marbled Murrelet 

nesting habitat at the end of this 30-year period, which 

134 Status Review of the Marbled Murrelet in Alaska and British Columbia
if maintained in the long term, will likely allow the 

provincial population to stabilize, within the accepted 

range of population fluctuations. If this habitat target is 

achieved, the habitat is maintained, and the population 

stabilized, the species may be de-listed; 

3. The present range of Marbled Murrelets in British 

Columbia should be maintained. A basic principle in 

wildlife management for the responsible Canadian 

provincial and Federal agencies is to maintain the 

geographic range of a species. The historical breeding 

range of Marbled Murrelets appeared to cover most 

of the coast of British Columbia, although abundance 

varied widely across this range. Murrelets are still found 

through most of this range and management objectives 

should include efforts to maintain this distribution. The 

extirpation of a local population should be considered a 

serious loss. If possible, efforts should be made to restore 

the Marbled Murrelet to parts of its historical range 

from which most of the nesting habitat has disappeared 

(e.g., parts of eastern Vancouver Island and the southern 

mainland). Management should ensure sufficient habitat 

to maintain a viable population of Marbled Murrelets in 

each conservation region, distributed widely across the 

region in those areas capable of supporting the species. 

Maintaining a widespread range of the British Columbia 

population also is likely to reduce any negative effects that 

may result from global climate change; 

4. Marbled Murrelets should remain a relatively abundant 

bird in British Columbia. The Marbled Murrelet was 

listed as Threatened by COSEWIC because of perceived 

declines in the population. Numerical abundance does not 

guarantee long-term survival of a species that is facing 

serious declines (Caughley, 1994; Pulliam and Dunning, 

1994). The intention of the Recovery Strategy and 

management recommendations is to maintain the species 

as one of the widespread and numerically common 

seabird species in British Columbia; 

5. Conservation goals should be aimed at acceptable, not 

minimal standards. The goal of the Recovery Strategy, 

management recommendations, and operational tactics is 

to prevent unacceptable population decline (>30 percent 

over the next 30 years), and to maintain the geographic 

range of the species in British Columbia. This will require 

maintenance of populations and habitat that are more than 

the minimum needed to prevent extirpation. This also is 

an application of the precautionary principle (Kriebel and 

others, 2001), which is particularly relevant to situations 

where the population size, population trends, habitat use, 

and population dynamics are poorly known, as in many 

areas of the murrelet’s range in British Columbia; 

6. Marbled Murrelets should be managed according to 

coast-wide and regional targets and habitat criteria. 

The Recovery Team identified six conservation regions 

(See fig. 7, section, “Population Status and Trends for 

British Columbia”), which approximately match both 

the variation in Marbled Murrelet habitat use and the 

British Columbia forest districts. Where possible, the 

team recommended province-wide standards and habitat 

criteria, but regionally specific habitat criteria should be 

applied where applicable; and 

7. Uncertainties should be addressed by applying an 

adaptive management approach. The CMMRT lacked 

reliable knowledge of many aspects of Marbled Murrelet 

biology and responses to land use. This prevented them 

from confidently prescribing nesting habitat targets and 

characteristics that would sustain the species in British 

Columbia, and it made projections of future populations 

uncertain. Because logging and other human impacts on 

habitats would continue, however, the team could not wait 

until better information became available through research 

and inventories. Adaptive management will therefore 

be an important tool for improving habitat management 

as the recovery strategy and government conservation 

policies are implemented. To take full advantage of the 

adaptive management process, it must be implemented in 

a structured, systematic way with attention to scientific 

principles of project design and analysis (Holling, 1978; 

Walters, 1986; Walters and Holling, 1990; Nyberg, 1998). 

Adaptive management should be applied with caution, 

taking care not to preclude future opportunities for 

maintaining suitable habitat for murrelets.

The guidelines (Bertram and others, 2003) identify 

operational objectives to meet the strategic plan. The primary 

management goals are to identify and maintain sufficient 

nesting habitat to maintain the target populations in each 

region. Ideally the sequence of management steps include: 

identifying suitable nesting habitat in each region; mapping 

and estimating the areas of suitable habitat; tracking past and 

projected changes in the area and quality of nesting habitat; 

and monitoring selected populations using radar. General 

guidelines are provided for these steps, with the details to be 

spelled-out in more detail by Recovery Action Plans.

Under the Canadian SARA, the Recovery Strategy 

sets out the overall strategy for recovering a listed species, 

but one or more Recovery Action Plans lay out the details, 

responsibilities, and timetable for recovery actions. Three 

Action Plans are envisaged to support the Marbled Murrelet 

Recovery Strategy:

•	 Population Status and Trend Monitoring (by November

2006 an implementation group was being assembled 

but the plan is not drafted);

Ongoing Conservation Efforts 135
•	 Nesting Habitat Retention (an implementation group

has met regularly since September 2004; the draft 

action plan was completed May 2006 and is currently 

in review by the Canadian and British Columbia 

governments); and

•	 Marine and Mortality Issues (by November 2006 an

implementation group was being assembled but the 

plan is not drafted).

The Nesting Habitat Retention Action Plan was perceived 

as the most urgent. It will establish regional objectives for 

habitat retention in old forest, identify who will be responsible 

for selecting and maintaining habitat, and establish a timetable 

for these activities. This action plan also will identify and map 

the current distribution of likely suitable habitat using a range 

of algorithms applied to forest cover, satellite imagery and 

other Geographic Information Systems (GIS) data layers. 

Under SARA, the recovery process also requires a socioeconomic assessment of the costs and benefits of the recovery 

actions. A Federal-provincial working group is currently 

analyzing socio-economic data related to Marbled Murrelet 

recovery, but information on its deliberations is not available 

yet.

Provincial Recovery Actions

Although protection of the birds and their active nest sites 

is a federal responsibility, the great majority (about 80 percent) 

of the forest nesting habitat in British Columbia falls under 

provincial jurisdiction. The Marbled Murrelet is a Redlisted Species in British Columbia and also is an Identified 

Species under the British Columbia FRPA. Measures for 

protecting murrelets and other identified species are provided 

in the Identified Wildlife Management Strategy (2004). The 

province and Federal government are engaged in bilateral 

talks designed to ensure that IWMS and other provincial 

management approaches are consistent with SARA provisions. 

The IWMS measures are meant to be the fine-filter approach 

to maintaining areas of nesting habitat, with strategic decisions 

covering larger tracts of land being made by other means 

(see below). In practice, the IWMS measures usually apply 

to forest lands designated for timber extraction. Identified 

species are managed through the establishment of WHAs and 

other management practices specified in strategic or landscape 

level plans. The application of the IWMS is greatly hampered 

by the limit placed by the British Columbia government on 

timber impacts: only 1 percent of mature forest, by area, of 

each forest district is allocated from the timber harvesting 

land base to cover all species of Identified Wildlife combined 

(currently 85 species). Areas of suitable nesting habitats 

outside the timber harvesting land base (sometimes known 

as the noncontributing land base) can be used for murrelet 

WHAs, but these tend to be in high elevation or steep areas 

where forestry operations are difficult. They often do not offer 

suitable habitat for nesting murrelets, but fortunately, in some 

cases, they do. 

The IWMS measures for Marbled Murrelets, based on 

the 2001–03 Conservation Assessment (see above), came 

into effect in 2004 (Identified Wildlife Management Strategy, 

2004). Key goals are to identify appropriate nesting habitat 

and provide guidance on the size, location, and management 

of WHAs. Using parameters commonly used for landscapelevel forestry mapping (e.g., stand age, tree height, canopy 

closure, distance from the sea) habitats can be classified as 

Most, Moderately, or Least likely to provide suitable nesting 

habitat to murrelets (details in Identified Wildlife Management 

Strategy, 2004). The measures recommend establishing WHAs 

in the “Most Likely” habitats. Habitat rated as “Moderately 

Likely” may be considered for WHAs, but require 

confirmation as suitable habitat using approved methods of 

ground or helicopter surveys. Areas rated as “Least Likely” 

should only be considered if there is evidence of nesting 

(nests, eggshells, or occupied detections), or strong evidence 

that the particular site provides the necessary attributes and 

is within commuting distance of foraging areas at sea. Other 

details are provided to help identify suitable habitat and the 

appropriate patch sizes (Identified Wildlife Management 

Strategy, 2004). 

Marbled Murrelet nesting habitat also may be included 

in forests protected as old growth management areas, riparian 

habitat protected for stream and river integrity, and ungulate 

winter ranges. Small but strategically important areas of 

nesting habitat are currently maintained within the water 

catchment drainages of the cities of Vancouver and Victoria. 

Much larger areas of habitat have been protected in 

provincial parks under the 1996 British Columbia Parks Act 

and the 2000 Protected Areas of British Columbia Act. These 

include extensive tracts in Carmanah-Walbran Provincial and 

Strathcona parks, and some watersheds around Clayoquot 

Sound. Other processes currently in progress which should 

protect some large areas of nesting habitat are the regional 

LRMPs and Land Use Plans (LUPs) directed by the Ministry 

of Agriculture and Lands. The LRMPs for the North Coast and 

Central Coast have been concluded, and proposals announced 

in February 2006 include large areas of protected areas and 

no-timber-harvesting zones that are anticipated to considerably 

increase the areas of suitable nesting habitat protected in 

those regions. The Haida Gwaii LUP is not complete and it is 

not possible to anticipate the level of protection of Marbled 

Murrelet nesting habitat. The Vancouver Island LUP includes 

provisions that extend old growth retention targets in the 

timber harvesting land base in specific areas to meet Marbled 

Murrelet needs.

Criticism has been directed at the British Columbia 

provincial government stating concern for the progress in 

implementing conservation measures for murrelet nesting 

habitat. Dechesne-Mansiere (2004) pointed out that since the 

Marbled Murrelet was listed as Threatened in 1990, about 

400,000 ha of possible habitat had been logged (this represents 

habitat likely to be used by about 24,000 murrelets, taking 

the mean density from radar surveys in British Columbia; 

136 Status Review of the Marbled Murrelet in Alaska and British Columbia
0.06 bird per ha; Burger and others, 2004a). The pace of 

implementing the IWMS guidelines has been criticized by the 

British Columbia Forest Practices Board (FPB), an armslength board that reviews the application of forest policies 

in British Columbia. As of November 2006, about 18,000 

ha (about 2 percent of the nesting habitat available in 2002) 

had been protected as WHAs under the IWMS process. In 

2003–05, the FPB released five reports on Marbled Murrelets3, 

which criticized the lack of direction and action in protecting 

Marbled Murrelet nesting habitat (e.g., Forest Practices Board, 

2004, 2005). In particular, in March 2005, the Board issued a 

strongly worded condemnation of the provincial government, 

stating that “there is a systemic failure in government policy 

to protect threatened species such as Marbled Murrelets on 

crown forest lands” (Forest Practices Board, 2005).

Other Efforts to Maintain Habitat in British 

Columbia

Several forest certification programs are applicable in 

coastal British Columbia that provide opportunities for forest 

companies to establish protected habitat for murrelets. These 

include:

•	 Canadian Standards Association (CSA) Z809;

•	 International Organization for Standardization (ISO)

14001;

•	 Forest Stewardship Council (FSC);

•	 Programme for Endorsement of Certification Schemes

(PEFC); and

•	 Sustainable Forest Initiative (SFI).

Forest certification programs require forest companies 

to demonstrate their ability to meet environmental standards. 

Stewardship and certification plans can apply to both private 

and public (leased) forest lands. The most rigorous effort 

to date to meet certification standards and follow Burger’s 

(2004) measures for Marbled Murrelets was by Canadian 

Forest Products, Ltd. (Canfor) for the Nimpkish Valley (Tree 

Farm Licence [TFL] 37) on Vancouver Island (Deal and 

Harper, 2004). Canfor used a combination of radar surveys, 

audio-visual surveys, low-level helicopter assessments, 

vegetation sampling, and GIS analysis to identify and map 

likely nesting habitat within their leased lands. They proposed 

the conservation of a total of 21,566 ha of potential nesting 

habitat, which included 50 percent of the area in the top four 

habitat quality ranks (Deal and Harper, 2004). No other forest 

company seems to have matched the efforts made by Canfor

3

Available at http://www.fpb.gov.bc.ca/.

in identifying and meeting the needs of Marbled Murrelets 

in coastal British Columbia. Certainly no other company has 

made their intentions known so publicly and with so much 

scientific evidence. Canfor was recently purchased by Western 

Forest Products and it is not clear whether the Deal and Harper 

(2004) proposals for TFL 37 will be fully implemented by the 

new lessees. 

Discussion

In this section, we first discuss factors relevant to the 

consideration of Distinct Population Segments (DPSs) (sensu

ESA) of the Marbled Murrelet. The USFWS specifically asked 

us to include descriptions of populations that may qualify as 

DPSs. Although we do not make any recommendations in that 

regard, we did uncover information that might be relevant to 

the definition of DPSs for the Marbled Murrelet. The main 

purpose of this document is to assess the status of the Marbled 

Murrelet in Alaska and British Columbia. In the second half of 

this discussion, we return to the topic of population trends and 

explore some possible explanations for recent and widespread 

declines observed in Alaska and British Columbia. 

Factors Relevant to Definition of Distinct 

Population Segments 

This status review was prepared for the U.S. Fish and 

Wildlife Service to provide updated information on the 

Marbled Murrelet within the context of the species’ listing 

under the Endangered Species Act. For vertebrate species, 

the USFWS must consider for listing any Distinct Population 

Segment, if information is sufficient to indicate such action 

may be warranted (FR 61, No. 26, February 7, 1996). The 

USFWS uses two elements to assess whether a population 

under consideration for listing may be recognized as a DPS: 

(1) the population segment’s discreteness from the remainder 

of the species to which it belongs; and (2) the biological 

significance of the population segment to the species. A 

population segment may be considered discrete if: (1) it is 

markedly separated from other populations of the same taxon 

due to physical, physiological, ecological or behavioral factors 

(e.g., quantitative measures of genetic or morphological 

discontinuity may provide evidence of this separation); or, 

(2) it is delimited by International boundaries within which 

significant differences in control, exploitation, management 

of habitat, conservation status, or regulatory mechanisms 

exist. If the USFWS determines that a population is discrete, 

Discussion 137
its biological and ecological significance must then be 

considered. Here, we briefly discuss the factors that may be 

relevant to definition of Discrete Population Segments for the 

Marbled Murrelet, based on our review of current knowledge 

for Alaska and British Columbia as compiled in this report.

Population Genetics

Several previous studies of Marbled Murrelet genetics 

(Pitocchelli and others, 1995; Congdon and others, 2000; 

Friesen and Piatt, 2003; Friesen and others, 1997, 2005), and 

the new findings presented in this report have found structure 

within Marbled Murrelet populations across their range. Using 

a variety of analytical techniques, Marbled Murrelets in the 

central and western Aleutian Islands and in central California 

have been found to be differentiated from each other and 

from Marbled Murrelets in the middle portion of their range, 

i.e., from northern California to the eastern Aleutian Islands. 

Marbled Murrelets between northern California and the 

eastern Aleutians, including those in Oregon, Washington, 

and British Columbia, do not appear to be genetically 

differentiated. Gene flow among these three regions 

occurs but is extremely low. These results are superficially 

incongruous with those of Peery and others (2006) who 

suggest that Marbled Murrelets in central California are a 

sink population that is augmented by individuals immigrating 

from populations to the north. However, the genetic identity 

of the central California population could be maintained if 

interbreeding is limited, if immigrants are selected against, 

or if migration into central California is a recent response to 

anthropogenic disturbance.

Distribution

The at-sea distribution of Marbled Murrelets during the 

breeding season approximates its onshore nesting distribution 

at the “landscape” scale. The nesting distribution of the 

Marbled Murrelet is considered to be relatively continuous 

from the western Aleutian Islands to northern California 

although many small to large habitat discontinuities exist 

throughout the species range as a result of island passes 

(e.g., in the Aleutian Islands), and other large water bodies, 

and breaks in nesting habitat in old-growth forests from 

logging and natural factors. From a DPS perspective, the one 

notable gap in its breeding distribution that we are aware of 

is the 450 km of coastline in California, between Humboldt 

County (northern California) and San Mateo County (central 

California) (Nelson 1997, McShane and others 2004). 

However, within this gap, small numbers of Marbled Murrelets 

have recently been found breeding in small patches of forested 

habitat in Mendocino County (McShane and others, 2004). 

This gap in nesting distribution separates the genetically 

differentiated murrelet population in central California 

from the middle population that is distributed from northern 

California to the eastern Aleutians. On the western end of the 

species range, sample collections from the Aleutians used 

in the genetic analysis were made at only three sites – Attu, 

Adak, and Unalaska (fig. 4), thus the geographic demarcation 

between Marbled Murrelets in the central and western 

Aleutian Islands with those from the middle population is 

imprecise.

Morphological, Behavioral, and Ecological 

Factors

Marbled Murrelets also are unique among the alcids 

in that breeding birds nest both on the ground and in trees. 

Where suitable trees and forests exist, Marbled Murrelets nest 

primarily in trees, but a small percentage also may breed on 

the ground. In western Alaska, where suitable trees and forests 

are lacking, Marbled Murrelets must nest on the ground. 

What controls nest site selection and preference is unknown. 

Nest site selection could simply reflect availability, it could 

be learned (i.e., birds nest in habitat similar to where they 

hatched) or it could be controlled by a functional gene.

Little morphological or genetic variation has been noted 

between presumed tree- and ground-nesting populations of 

Marbled Murrelets (Pitocchelli and others, 1995; Friesen 

and others, this report). Of 23 measurements of external 

and skeletal components, five differed significantly between 

presumed tree- and ground-nesting Marbled Murrelets. 

Adaptations for arboreal life in terrestrial birds often includes 

divergence in leg morphology, but of those characters 

measured, only the length of the tarsometatarsus differed 

significantly between ground- and tree-nesting murrelets 

(Pitocchelli and others,1995). Perhaps more morphological 

differences have not been observed between ground and 

tree-nesting murrelets because of over-riding adaptation to 

the marine environment where birds spend most of their time. 

If behavioral differences were important, the most important 

point of demarcation would likely be Kodiak Island and the 

Alaska Peninsula where the western boundary of the Gulf of 

Alaska is found and where Marbled Murrelets must therefore 

nest on the ground.

International Boundary

The USFWS is required to conduct a 5-year review of 

all species listed under the ESA to assess the best available 

information on how the species has fared since its original 

listing or previous review, and consider whether it is listed 

appropriately. The USFWS completed a 5-year review of 

the listed population of Marbled Murrelet in WOC in 2004 

(U.S. Fish and Wildlife Service, 2004), and concluded that 

the WOC population does not satisfy the discreteness criteria 

for designation as a DPS under the USFWS’s 1996 DPS 

Policy. Specifically, the USFWS concluded that there was no 

marked separation of physical, physiological, ecological or 

138 Status Review of the Marbled Murrelet in Alaska and British Columbia
behavioral differences of murrelets at the border with Canada, 

and that there were no differences in control of exploitation, 

management of habitat, conservation status, or regulatory 

mechanisms across the International border that are significant 

in light of the ESA.

In 2004, when the USFWS decided that the WOC 

population of Marble Murrelet did not satisfy the criteria 

for designation as a DPS, Canada’s Species at Risk Act 

(SARA) had only recently passed. Like the ESA, SARA 

may effectively control the illegal exploitation of Marbled 

Murrelets from various forms of direct take. From the 

perspective of conservation of nesting habitat, it is difficult to 

make direct comparisons of the benefits to Marbled Murrelets 

between the two laws. The details of how SARA will be 

applied to Marbled Murrelets have not yet been finalized. 

The Canadian Marbled Murrelet Recovery Team drafted 

a Recovery Strategy, but this strategy is still under review 

by Federal and Provincial governments. At this time, only 

one of three Recovery Action Plans has been submitted for 

government review. The Recovery Strategy and its associated 

Recovery Action Plans will not likely be in place before 2008. 

Unavailable at the time the USFWS completed its 5-year 

review of the Marbled Murrelet in WOC was a report by the 

Forest Practices Board (FPB) in British Columbia that was 

critical of the province’s implementation of the existing forest 

practices regime for conservation of forest nesting habitat 

of this species (Forest Practices Board 2004). The Forest 

Practices Board is an independent, public watchdog that 

conducts audits and investigations on how well industry and 

the government are meeting the intent of British Columbia’s 

forest practices legislation. The FPB concluded that 

conservation of Marbled Murrelet habitat under the Forest and 

Range Practices Act is limited and very slow. The FPB was 

particularly concerned that while the process of developing a 

conservation strategy for Marbled Murrelets is still ongoing, 

logging projects continue to be approved, thereby eliminating 

future options for murrelet habitat conservation, especially 

on the southern British Columbia coast where conservation is 

most needed. The FPB also was critical of British Columbia’s 

implementation of the Identified Wildlife Management 

Strategy under the FRPA. Under this strategy, British 

Columbia arbitrarily restricted protection of forest habitat for 

all IWMS species to less than 1 percent of the mature timber 

land base (in which most murrelet nesting habitat occurs). 

In the FPB’s view, this prevents conservation of the most 

important murrelet nesting habitat and deflects conservation to 

less suitable habitat. 

In summary, information on population genetics and 

distribution may be the most important factors to consider 

if the USFWS decides to re-examine the issue of DPSs for 

the Marbled Murrelets. In contrast, existing information on 

morphology, behavior and ecology appears less instructive 

although the tree line on Kodiak Island and the Alaska 

Peninsula provides an approximate boundary between 

primarily tree-nesting murrelets and ground-nesting murrelets. 

The USFWS also may wish to examine new information 

on forest habitat management in British Columbia and in 

particular the efficacy of existing laws and regulations in 

promoting the conservation of Marbled Murrelet nesting 

habitat there.

Population Status and Trends in Alaska and 

British Columbia

As reported earlier, populations of Marbled Murrelets 

in Alaska may have declined by approximately 70 percent 

during the past few decades. Our analyses found that Marbled 

Murrelet populations had declined at 5 of 8 trend sites in 

Alaska at rates of -5.4 to -12.7 percent per year. We also 

found statistically significant declining population trends for 

Marbled Murrelets at all 8 trend sites in British Columbia with 

rates ranging from -5.8 to -31 percent per year. 

The apparent change in population size and rates of 

decline reported here for murrelets are extraordinary and we 

therefore put them to the “straight-face test” by asking and 

answering four questions: (1) Are declines of this magnitude 

even possible?, (2) Is it possible that survey methods or 

statistics have led us to erroneous measures of trend?, (3) 

Are there precedents for changes of this magnitude in other 

wildlife populations?, and, (4) Is there a plausible explanation 

for these findings? The answer to the first three questions is 

“yes”, and the last is “yes, but not a single explanation.” We 

examine each of these questions below.

Are Declines of This Magnitude Even Possible? 

Yes. Even under natural conditions where environmental 

conditions vary in “normal” fashion (i.e., without recurring 

extraordinary events such as El Niño), members of the 

seabird family Alcidae may exhibit a wide range of trends 

in population size, both increasing and decreasing (Hudson, 

1985). Trends of more than about ±10 percent are uncommon, 

however, and may result from the addition of unnatural 

mortality factors. For a variety of seabirds in Alaska (petrels, 

gulls, auklets, murres, puffins, etc) where significant trends 

could be measured at colonies located around the State during 

the past 30 years (40 of 92 possible species-colony sites, 

Dragoo and others, 2006), 19 were increasing at an average 

rate of 7.3 percent per year (± 6.7 s.d., range 0.9–29 percent) 

while 21 were decreasing at an average rate of 6.8 percent 

per year (± 4.9 s.d., range 1.7–21 percent). The remainder 

of species-colony sites (52) had either stable populations or 

counts were insufficient to measure trend. Thus, the observed 

rates of decline for Marbled Murrelets are not out of line with 

the range observed in other seabirds in Alaska. The difference, 

of course, is that murrelets are declining throughout their 

range and not just at a few sites here and there. 

Discussion 139
When we used a reasonable suite of population parameter 

values to model population dynamics for Marbled Murrelets 

in Alaska (see section, “Demographics and Population 

Dynamics”), and introduced random variability in the 

parameters, we found that it was possible to observe trends of 

more than ±20–30 percent per year over 20- or 30-year periods 

of study. However, the chances of observing this magnitude 

of change “naturally” are low. Indeed, such rates are rarely 

observed in field studies of alcids unless anthropogenic factors 

strongly influence survival or productivity (e.g., sustained 

adult mortality from net bycatch, collapse of a prey stock 

from overfishing, or recovery of a population after removal 

of an introduced predator). All trends we observed were less 

than ±15 percent where we had reasonably long time series. 

Therefore, we conclude that the trends observed in Alaska 

and British Columbia are possible from random variability 

alone, but more likely influenced to some degree by unnatural 

(anthropogenic) factors. 

Is It Possible That the Methods or Statistics Have Led Us to 

Erroneous Measures of Trend?

Yes. Data were obtained from a variety of surveys 

and investigators and it is important to recognize that few 

of these surveys were initiated to monitor populations of 

Marbled Murrelets specifically, and none were designed 

with both statistics and murrelet biology in mind. Indeed, the 

use of at-sea surveys to monitor populations has never been 

validated. Most population monitoring for seabirds takes 

place at colonies— where birds return each year to breed 

and may therefore be censused with relative ease. At Alaskawide spatial scales, at-sea counts are correlated with colony 

counts for several seabird species (Piatt and Ford, 1993). At 

the scale of bays, fjords and sounds, however, we have little 

independent corroboration of at-sea census data. In Prince 

William Sound, marine bird surveys that we used here to 

assess murrelet trends also showed that populations of blacklegged kittiwakes (Rissa tridactyla) were highly variable and 

declining through the 1990s (Irons and others, 2000) although 

numbers have recently returned to 1989 levels (McKnight, 

2005). In contrast, counts of kittiwakes at breeding colonies 

within Prince William Sound reveal much smaller year-to-year 

variation, local upward and downward trends, but no longterm trend for the sound as a whole (Suryan and Irons, 2001). 

Irons and others (2000) attribute the lack of concordance 

between at-sea and colony trends to the volatility in movement 

of foraging kittiwakes as food supplies apparently diminished 

in the mid-1990s (Suryan and Irons, 2001). Variability also 

may arise from differences among years in the abundance of 

non-breeding birds and flux of birds from the Gulf of Alaska. 

In any case, it is important to acknowledge that while 

we have a relatively good grasp on sources of variation 

in attendance by seabirds at their breeding colonies, our 

understanding of how and why seabird populations at sea 

fluctuate over time is minimal. In the case of Marbled 

Murrelets, we have evidence for persistent foraging of nesting 

birds in proximity to nesting areas, but also for long-range 

(100+ km) excursions of breeding birds to distant foraging 

areas. Additionally, we believe that there is a large and 

highly mobile pool of subadult birds, non-breeding birds, 

failed breeders and successful post-breeding birds that are 

not constrained geographically by having to return to nests, 

and therefore may move widely around any area that is being 

surveyed (Kuletz, 2005). Indeed, our demographic modeling 

suggests that about 25 percent of all birds in the population 

at any one time may be subadults. Seasonal changes in 

distribution and abundance could affect trend analyses, but 

with such limited numbers of surveys in Alaska, we have little 

way to evaluate the magnitude of this error at the appropriate 

spatial scales (but see Speckman and others, 2000). However, 

the trend analysis of data from British Columbia was based 

on averages of multiple counts made within each survey year, 

and temporal variability was therefore accounted for in that 

analysis. 

As far as survey “design” is concerned, historical 

surveys included transects that were selected randomly, 

systematically, for their logistic convenience, because they 

were “representative,” or simply in haphazard fashion. 

Only surveys currently employed in California, Oregon, 

and Washington were designed specifically for monitoring 

murrelet populations (Huff and others, 2006). Thousands of 

kilometers of transects using these methods were conducted 

by the U.S. Forest Service in Southeast Alaska during the 

early 1990s (see appendix M), but none were repeated and so 

we could not examine trends using those data. 

Given these issues, how much credence should be 

placed in the population trend information presented in this 

assessment? We used appropriate statistical analyses, and we 

have indicated where we think methodological issues might 

cause error, but we cannot evaluate the underlying assumption 

that at-sea survey data provide an accurate estimate of 

populations and trends. More work is needed to validate 

at-sea survey methods, and we need to develop wholly new 

approaches to censusing murrelets in Alaska (e.g., using radar 

on watersheds) that might be used to corroborate (or replace) 

water-based surveys. In the meantime, we acknowledge that 

the estimates of population size and rates of decline could be 

exaggerated or simply incorrect. In the end, however, we are 

struck by the consistency of the data in showing a declining 

trend, and apparent rates of decline ranging from -5.4 to -31 

percent per year in the cases showing statistically significant 

change. Although the absolute rates could be inaccurate, the 

weight of statistical evidence leads us to err on the side of 

caution and assume that a biologically meaningful decline 

in the core population of murrelets has occurred during the 

past 15–20 years, at least until new data can be collected to 

improve measures of trend. 

140 Status Review of the Marbled Murrelet in Alaska and British Columbia
In this regard, some of the uncertainty about the decline 

could be cleared up by repeating a region-wide survey of 

Southeast Alaska like the one conducted in 1994 by Agler and 

others (1998). This survey covered the entire region that has 

been and likely remains the center of the species’ abundance. 

Obtaining a new estimate of population size in Southeast 

Alaska would answer the immediate questions about the status 

of the species overall. Continuing surveys of the other trend 

sites, especially Prince William Sound and lower Cook Inlet, 

also would be useful.

Are There Precedents for Changes of This Magnitude in Other 

Marine Wildlife Populations in the Northeastern Pacific Ocean?

Yes. In particular, it appears that populations of 

closely related Kittlitz’s Murrelet also are declining rapidly 

throughout their range (Kuletz and others, 2003; Robards and 

others, 2003), which overlaps almost completely with Marbled 

Murrelet from about Glacier Bay westward. Several species 

of seabirds in Alaska are undergoing similar or larger rates 

of decline at specific colonies (Dragoo and others, 2006), 

although no other species is currently undergoing declines in 

most areas of its range at the same time. Tufted puffins have 

shown consistent increases of 2.5 to 17.9 percent per year at 

eight colonies stretching from Prince William Sound to the 

western Aleutians, and consistent decreasing trends of -1.0 to 

-16.9 percent at nine colonies stretching from Southeast 

Alaska to California (Piatt and Kitaysky, 2002). Pelagic and 

red-faced cormorants have undergone precipitous declines 

of 90–95 percent at rates of as much as 13 percent per year 

during the past 20 years at most colonies in the Gulf of 

Alaska, eastern Aleutians and western Aleutians, but not in the 

central Aleutians (Dragoo and others, 2006). 

There are parallels with changes in marine mammal 

populations as well (reviewed by Springer and others, 

2007). The western stock of Steller’s sea lions declined 

during the past 30 years at all 36 rookeries scattered over 

a 2,000 km range from the northeast Gulf of Alaska to the 

western Aleutians. Decline rates of about 6 percent per year 

at some rookeries in the 1970s increased to a more rapid and 

widespread decline of 16 percent per year through the 1980s 

and early 1990s. Harbor seal populations at the largest rookery 

in Alaska (Tugidak Island) declined at a rate of 19 percent per 

year during the 1970s, leveling off to a persistent decline of 

7 percent per year through the 1980s until recovering partially 

in the mid-1990s. The harbor seal declines were widespread, 

and populations declined rapidly by 63 percent in Prince 

William Sound during only a 10-year period in the 1980s. 

Similar rapid declines were noted at Kodiak (-66 percent) and 

the Pribilof islands (-80 percent). Finally, populations of sea 

otters rebounded after harvest ended in the early 1900s, and 

populations increased dramatically for decades in many areas 

of Alaska at rates of 9–13 percent per year. However, in the 

late 1980s populations of the southwest stock (including the 

Aleutians and Alaska Peninsula) plummeted at rates of 17–25 

percent per year. In contrast, sea otter populations in Prince 

William Sound appear stable, while in Southeast Alaska 

populations increased at nearly 20 percent through the late 

20th century and have subsequently stabilized (Esslinger and 

Bodkin, 2006). 

Is There a Plausible Explanation for These Findings?

Yes, but not a single explanation. There is no one factor 

that can be invoked to explain changes of this magnitude, and 

it is likely that many factors acting in concert could result in 

the observed population declines. This is certainly the case 

for the major population fluctuations observed in Alaska 

for cormorants, tufted puffins, Steller’s sea lions, harbor 

seals and sea otters. Factors influencing these populations 

are complicated, possibly additive and in some instances 

impossible to evaluate for relative importance. This has 

led to vigorous debate and widespread disagreement about 

how these wildlife populations are ecologically regulated in 

Alaska (Springer and others, 2007). In previous sections of 

this document, we have reviewed in detail all factors that may 

possibly impact murrelet populations in Alaska and British 

Columbia. In the following, we briefly review that list again, 

and try to identify the most important factors, if possible. 

Anthropogenic Factors Influencing the Marbled 

Murrelet

We have identified several factors that arise from human 

activities and that have a negative influence on murrelet 

populations. In an approximate order of potential importance 

these include:

•	 Destruction of old-growth nesting habitat.

•	 By-catch of birds in fishing gear.

•	 Oil pollution.

•	 Competition from commercial fisheries.

•	 Vessel disturbance.

•	 Overuse for commercial or scientific purposes.

Evidence suggests that the past removal of large areas 

of old-growth nesting habitat in British Columbia (33–49 

percent) and Alaska (probably <15 percent) has had a direct 

negative impact on populations. Thus, it may be reasonable 

to assume that future harvests would result in proportional 

reductions in nesting habitat and therefore eventually 

population size (Burger and others, 2004a). However, recent 

rates of harvest of suitable nesting habitat in Alaska appear to 

be less than 1 percent per year and this cannot by itself explain 

declines of 5–13 percent in Southeast Alaska and Prince 

William Sound (even if loss of habitat translated immediately 

Discussion 141
into population declines, which seems unlikely for birds that 

may live to 15–25 years of age). The observed population 

trends may reflect some time-lag in population effects on these 

long-lived birds as a result of logging from previous decades, 

especially in British Columbia and southern Southeast Alaska. 

However, such an effect would not explain population declines 

in northern Southeast Alaska and Prince William Sound, 

where losses of nesting habitat to logging are much less 

pronounced. An additional by-product of large scale logging 

is habitat fragmentation, which brings an increased threat of 

disturbance and predation (see below). 

The quantity of data available on the impact of fishing 

bycatch, oil pollution, and competition from commercial 

fisheries are simply inadequate to draw firm conclusions about 

the relative or absolute impact of these factors on murrelet 

population dynamics. It is usually difficult to measure the 

impact of these factors on seabirds, even in well-documented 

cases involving colonial species that are relatively easy to 

census. We have evidence that oil pollution and gill-nets kill 

hundreds to thousands of Marbled Murrelets each year in 

Alaska and British Columbia. Even if populations are in the 

low 100,000s this would amount to increasing adult mortality 

by only a few percent, perhaps to 6–7 percent in local 

populations (Carter and Kuletz, 1995). Therefore, it seems 

unlikely that these factors, by themselves, could account for 

the population declines we have observed. A critical question, 

however, is whether or not mortality from these anthropogenic 

factors are additive to natural mortality or compensated for 

in density-dependent mortality (Piatt and Nettleship, 1987). 

Recent analysis of a long-term dataset on survival of murres in 

the North Atlantic indicates that oil spills have a strong impact 

on over-winter survival of murres and that the effect is additive 

to effects of environmental variation (Votier and others, 2005). 

This could be important to populations under stress. 

Finally, we found little or no evidence that vessel 

disturbance or use of murrelets for scientific purposes has 

any significant impact on populations at the present time. 

Increased levels of disturbance at sea, however, increase 

energy demands and could reduce fitness under adverse 

environmental conditions (Agness, 2005). 

Natural Factors Influencing the Marbled 

Murrelet

We have identified several natural factors that can have a 

negative (or positive) influence on murrelet populations. In an 

approximate order of potential importance these include:

•	 Ocean climate change and marine ecosystem regime

shifts.

•	 Disease or predation.

•	 Natural changes in terrestrial habitat.

Periodic (e.g., El Niño) or cyclical changes in marine 

climate are known to cause profound changes in marine 

systems at local and basin scales. In the Northeastern Pacific 

Ocean, environmental conditions cycle between warm and 

cold phases on a multi-decadal time scale (Francis and others, 

1998). At least two cycles are apparent in this century, with 

strong phase reversals occurring around 1925, 1947, and 

1977 (Mantua and others, 1997). In the most recent event, 

the Aleutian Low Pressure system shifted and intensified 

during the late 1970s leading to stronger westerly winds and 

warmer surface waters in the Gulf of Alaska. This apparently 

strengthened the flow of the Alaska Current, and resulted in 

increased primary and secondary production in the Gulf of 

Alaska. Warm water periods were associated with changes 

in the magnitude and timing of primary and secondary 

production, and marked increases in groundfish recruitment 

and salmon catches in Alaska (Francis and others, 1998). 

Conversely, some populations of marine birds and mammals 

exhibited signs of food stress (Piatt and Anderson, 1996; but 

see Springer, 2007 for a different interpretation). 

The shift in climate regime in the late 1970s triggered 

a complete reorganization of trophic structure in the Gulf 

of Alaska ecosystem (Anderson and Piatt, 1999). Important 

forage taxa such as pandalid shrimp, capelin, and herring 

declined by 95 percent or more in less than 15 years and 

never recovered in much of their range, probably owing 

to recruitment failure and predator forcing. This trophic 

reorganization apparently occurred at the expense of some 

piscivorous marine birds and mammals in the Gulf of 

Alaska. During the initial transition in the early 1980s, as 

stocks of common forage species such as capelin and herring 

collapsed, these fatty fish disappeared from diets of seabirds— 

particularly Marbled Murrelets—and were replaced largely 

by lean juvenile pollock (Piatt and Anderson, 1996). Pollock 

have substantially lower energetic value than more typical 

forage species such as capelin (Van Pelt and others, 1997) and 

are not assimilated as efficiently by growing chicks (Romano 

and others, 2006). Even when consumed at a caloric rate equal 

to capelin, pollock induces nutritional stress (Kitaysky and 

others, 1999) and results in little fat deposition (Romano and 

others, 2006) in seabirds. Thus, the change in predator diets 

may have had a negative effect on productivity, recruitment 

and survival in murrelets. 

There is evidence for another weak North Pacific climate 

regime shift in 1999 (Bond and others, 2003) and evidence 

that climate-related physical changes (e.g., winds, SST) have 

had pervasive biological effects on marine animals (Grebmeier 

and others, 2006; but see Litzow, 2006). If so, the period of 

decline in murrelet numbers that apparently began after the 

1977 regime shift (Agler and others, 1999) could have been 

slowed or halted by a later regime shift in 1999. Trends in 

murrelet numbers counted in Barkley Sound, British Columbia 

and Icy Strait, Alaska, suggest the possibility that declining 

trends stopped after 1999 in these areas. 

142 Status Review of the Marbled Murrelet in Alaska and British Columbia
In any case, changes in marine climate and so-called 

“regime shifts” have clearly had pervasive impacts on marine 

communities in the Northeastern Pacific Ocean. Indeed, this 

is the only factor we have examined that has the potential 

to explain large declines in murrelet numbers over a broad 

area of the Northeastern Pacific Ocean. Not surprisingly, the 

1977 regime shift is often implicated in the rapid and large 

declines observed in Steller’s sea lion, sea otter, and harbor 

seal, although the mechanisms of change are unclear and other 

factors are almost certainly at work (Springer, 2007). 

One of those other factors is predation, and Springer 

and others (2003) argues that predation of marine mammals 

by orca could have been a driving force in reducing these 

populations in Alaska. We know that Marbled Murrelets 

have adapted more than any other member of the Alcidae to 

minimize predation of adults and their young (Nelson, 1997). 

Predation occurs at the nest, in forest habitats and on the sea. 

Although we have little quantitative data with which to assess 

the numerical impact of predation on murrelets, it is prudent 

not to underestimate the importance of this powerful force 

in regulating animal populations (Sinclair and others, 1998, 

Parrish and others, 2001, Springer and others, 2003). It is 

noteworthy that populations of five of seven known murrelet 

predators observed on Christmas Bird Counts have increased 

substantially (by 2–8 fold) in British Columbia or Alaska 

during the past 30 years. Predation is one of only a few factors 

we have identified that has the potential to cause the rates of 

change that we observed in murrelet populations. 

We found little evidence for significant effects of 

disease in murrelets, or for significant changes in terrestrial 

ecosystems (fire, pest infestations, precipitation, forest 

community composition) that could account for the changes 

observed in murrelet populations.

Conclusion

We observed declining trends in populations of murrelets 

at eight trend sites in British Columbia and at five of eight 

trend sites in Alaska. If methods for detecting these trends 

are sound, then populations in Alaska may have declined by 

more than 70 percent during the past 20 years. A model of 

population dynamics and observations of other seabirds in 

Alaska suggest that such trends could result from stochastic 

variability in population parameters, but additional factors 

likely are influencing populations. Declines are possibly 

the result of combined and cumulative effects of human 

activities (logging, gillnet bycatch, oil pollution) and natural 

factors such as ocean regime shifts or predation. Important 

questions remain to be addressed about methods for measuring 

population status and change, adult mortality (major 

sources, density dependence, seasonal concordance), and the 

movements of wintering populations. 

Acknowledgments

This review was prepared for the U.S. Fish and Wildlife 

Service, Region 7, by the U.S. Geological Survey under 

Interagency Agreement # 70181-5-N242, and supported with 

funding from both the USFWS and USGS-Alaska Science 

Center. 

Once underway, it became clear that this project was 

going to need full-time coordination to make sure all the 

pieces came together at the same time. The authors are 

grateful to Karen Oakley (USGS) for stepping in as project 

manager, establishing goals and deadlines, and coordinating 

biologists and support staff in a steadfast fashion. Her 

knowledge of murrelet biology was a real asset in pulling 

together the various sections, identifying gaps, and helping us 

to deal with all the reviews. She did a goodly share of editing 

as well. Karen deserves as much credit as anyone else for 

making this happen. 

This compilation and analysis of the growing body of 

information about Marbled Murrelets in Alaska and British 

Columbia would not have been possible without contributions 

from the many people who have been involved in seabird 

research in this region. Our ability to produce a document 

that is both up-to-date and comprehensive is due in large 

measure to extra efforts of those who provided unpublished 

data and willingly reviewed our drafts. We thank especially 

John Lindell, Michelle Kissling, Jack Hodges, Debbie Groves, 

Dennis Zwiefelhofer, Shawn Stephenson and Joel Reynolds 

of the USFWS for access to unpublished data and assistance 

with analysis of boat survey data collected by the USFWS. 

We thank also Kathy Dale, Geoff LeBaron, and Stan Senner 

of the Audubon Society for assistance in obtaining Christmas 

Bird Count data sets. We also appreciate helpful insights from 

Colin Beier (UAF), Dave Albert (TNC), and Francis Biles 

(USDA Forest Service) on Tongass forest issues. Bill van Hees 

and Jane Reid (USDA Forest Service) provided information 

and data from the FIA program. Dede Bohn improved our 

understanding of Exxon Valdez Oil Spill Trustee Council 

actions relative to the Marbled Murrelet. Gus Van Vliet, Matt 

Kirchoff (ADF&G), G. Vernon Byrd (USFWS), Alan Springer 

(University of Alaska Fairbanks), Lyman Thorsteinson 

(USGS), Nancy Naslund, Harry Carter (Carter Consulting), 

and Alison Agness saw early drafts and provided critical 

comments on various sections of the document. Michael 

Fleming (SAIC) and Page Spencer (National Park Service) 

provided land-cover information for the Kodiak archipelago. 

We thank Rob DeVelice (USFS) for providing his unpublished 

nesting habitat model for the Prince William Sound region. 

We also thank Dave Albert and John Schoen for providing 

HSI and other forest data for Southeast Alaska. Karen Murphy 

(USFWS) provided vessel statistics for Prince William Sound.

Acknowledgments 143
Contributors of unpublished data to the British Columbia 

sections include Alan Burger (University of Victoria), Harry 

Carter (Carter Consulting, Victoria), John Deal (Canfor), 

Bill Harper (Osiris Consulting), Laskeek Bay Conservation 

Society (Greg Martin), David Lindsay (TimberWest), Parks 

Canada (Bob Hansen, Danielle Edwards, Danielle Bellefleur), 

and Anne Stewart (Bamfield Marine Sciences Centre). Others 

who helped with the British Columbia reviews include Doug 

Bertram (Canadian Wildlife Service), Trudy Chatwin (British 

Columbia Ministry of Environment), Alvin Cober (British 

Columbia Ministry of Environment), Anne Harfenist, Andrea 

Lawrence, Monica Mather (British Columbia Ministry of 

Environment), Ken Morgan (Canadian Wildlife Service), Jo 

Smith (University of Washington), and Steve Young (formerly 

Sierra Club of Canada). 

Samples used for the genetic study were obtained 

through the assistance of S. Beissinger, T. Bloxton, E. Burkett, 

V. Byrd, H.Carter, F. Cooke, A. Derocher, R. Golightly, 

T. Hofstra, G. Kaiser, M. Kassera, S. Kitaysky, K. Kuletz, 

R. Lowe, K. Martin, K. Nelson, Z. Peery, J. Piatt, M. Raphael, 

T. van Pelt, J. Pitocchelli, A. Pritchard, L. Roberts, D. 

Roseneau, H. Sakai, S. Speckman, W. Sydeman, J. Williams, 

and the Captain and Crew of the R/V Tiglax. Help with data 

collection and interpretation was provided by C. Crossman, 

G. Gissing, D. Harrison, G. Ibarguchi, R. Kristensen, 

D. Michaud, V. Poland, and L.Veit. K. Warheit and P. 

Palsboll facilitated the development of microsatellite primers. 

Funding was provided by the British Columbia Ministry of 

Forests, California Department of Fish and Game, Canadian 

Wildlife Service, the Exxon Valdez Oil Spill Trustee Council, 

Government Works and Public Services Canada, the Natural 

Sciences and Engineering Research Council of Canada, a 

Premier’s Research Excellence Award, Scotia Pacific Lumber, 

the U.S. National Park Service, the U.S. Fish and Wildlife 

Service, the U.S. Geological Survey, and Washington State 

Fish and Wildlife Service.

Lyman McDonald and Shay Howlin (WEST Inc.) 

worked with us from the beginning to ensure our analyses of 

the pertinent archived datasets were statistically sound. Matt 

Kirchhoff (ADF&G) also helped with statistical evaluation of 

the trend data. 

We thank Michelle St. Peters (USGS), who played 

a significant role in compiling the recent literature which 

jumpstarted the process of completing this review. Liz 

Labunski (USFWS) compiled information for the marine 

habitat section, and Tom Hamer, Erin Colclazier, and Nathalie 

Denis, of Hamer Environmental, provided a summary 

of Marbled Murrelet conservation status and provided 

extensive review material on threats to nesting habitat. Paula 

Winningham (USGS) cheerfully expedited our contracts. Mary 

Whalen (USGS) provided graphical support. Katherine Burke 

(USGS) compiled the document, tracked down literature, copy 

edited, and performed numerous other supporting tasks. Linda 

S. Rogers (USGS) provided superb editing and technical 

assistance in publication of this report. 

We are grateful to Kristine Paulus and Lucy Fowler 

Williams at the University of Pennsylvania Museum for 

help with obtaining photographs and documentation on the 

Murrelet Hat.

Finally, we are indebted to our peer reviewers. The report 

was much improved by the thoughtful and thorough comments 

of John R. Sauer (USGS-Patuxent Wildlife Research Center), 

Martin G. Raphael (U.S. Forest Service-Pacific Northwest), 

David (Dov) Lank (Simon Fraser University), Sandra L. Talbot 

(USGS-Alaska Science Center), Timothy L. King (USGSLeetown Science Center), and Robert H. Day, Adrian E. Gall, 

Alex K. Pritchard and Brian Cooper (all of ABR, Inc.). We 

thank them for their contributions to this assessment.

144 Status Review of the Marbled Murrelet in Alaska and British Columbia
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164 Status Review of the Marbled Murrelet in Alaska and British Columbia
Appendix A. Annotated Bibliography of Historical Information on Diet of the 

Marbled Murrelet in Alaska.

Sangster, M.E., Kurhajec, D.J., and Benz, C.T., 1978, 

Reproductive ecology of seabirds at Hinchinbrook Island 

and a census of seabirds at selected sites in Prince William 

Sound, 1977: Anchorage, Alaska, U.S. Fish and Wildlife 

Service, Ecological Services, Office of Special Studies, 98 p.

Sangster and others (1978) examined the feeding and 

breeding ecology of seabirds around Constantine Harbour, 

Hinchinbrook Island, at the entrance to Prince William 

Sound during the summer of 1977. Nine Marbled 

Murrelets were collected over the season, and prey items 

in the stomachs of eight birds keyed out to lowest possible 

taxon. Sand lance was found in 50 percent of the birds, 

capelin in 25 percent, unidentified fish in 12.5 percent, 

and the Decapod T. inermis in 25 percent of the birds.

Oakley, K.L., and Kuletz, K.J., 1979, Summer distribution and 

abundance of marine birds and mammals in the vicinity of 

Naked Island, Prince William Sound, Alaska, in 1978, and 

aspects of the reproductive ecology of the Pigeon Guillemot: 

Anchorage, Alaska, U.S. Fish and Wildlife Service, 95 p.

During the summer of 1978, Oakley and Kuletz (1979) 

collected 12 Marbled Murrelets from the western half 

of Naked Island and 2 from McPherson Bay in Prince 

William Sound. Seventy-three percent of all food items 

were fish. More than one-half of the fish fragments were 

unidentified. Pollock and sand lance were of similar 

importance and one bird contained capelin (see table A1).

Krasnow, L.D., and Sanger, G.A., 1982, Feeding ecology of 

marine birds in the nearshore waters of Kodiak Island: 

Anchorage, Alaska, U.S. Fish and Wildlife Service, National 

Fishery Research Center, Migratory Bird Section, Final 

Report to the Outer Continental Shelf Environmental 

Assessment Program (OCSEAP), Research Unit 45, 

p. 505-630.

Krasnow and Sanger (1982) collected 18 birds at sea 

in Chiniank Bay near Kodiak Island during the winter 

of 1976–77, and 19 murrelets (16 with food) during 

February 1978. Two additional Kodiak sites were sampled 

in 1978; 34 birds (25 with food) from Izhut Bay between 

April and August, and 26 birds (17 with food) from 

Northern Sitkalidak Strait between May and August.

Diet composition at Chiniak Bay differed between 

1976–77 and 1978 (tables A2, A3). Whereas the Chiniak 

diet of 1976–77 was dominated (by volume) by capelin, 

with euphausiids and Osmeridae also important, the 

Chiniak diet of 1978 was dominated by mysids. Diversity 

was fairly high in both years. There also were clear 

monthly and regional differences in diet of birds collected 

in Izhut Bay and Northern Sitkalidak Strait in 1978 

(Krasnow and Sanger, 1982; Burkett, 1995; table A4). 

For example, birds collected in Izhut Bay in May were 

feeding primarily on capelin, whereas birds in northern 

Sitkalidak Strait in May fed mostly on euphausiids. Izhut 

Bay birds fed largely on sand lance in April, but had no 

sand lance in their diet in May. In general, birds seemed to 

prey more on invertebrates during the winter of 1978 and 

more on fish during the summer months. The Krasnow 

and Sanger (1982) study highlights (a) the ability of 

murrelets to switch prey, and, (b) the importance influence 

of local and seasonal differences in food availability on 

the diet choice of murrelets.

Table A1. Frequency of occurrence of prey 

types in stomachs of murrelets collected near 

Naked Island, Prince William Sound, summer 

1978. 

[From Oakley and Kuletz (1979). N = 14 murrelets]

Prey Percentage of 

occurrence

Fish

 Gadidae

 Theragra chalcogramma 21.4

 Ammodytidae

 Ammodytes hexapterus 35.7

 Osmeridae

 Mallotus villosus 7.1

 Unidentified fish fragments 92.9

Crustacea

 Copepoda

 Calonord sp. 35.7

 Caligorda sp. 7.1

 Decapoda

 Shrimp larvae 14.3

 Nemerea

 Nematoda sp. 42.9

Appendix A 165
Species %No %Vol %FO IRI

Mysidea 11.6 12.2 18.8 447

Acanthomysis spp. 74.8 55.1 81.2 1,548

Neomysis spp. 8.1 15.1 37.5 870

Neomysis rayii 1.4 3 6.2 27

Thysanoessa raschii 0.6 0.1 6.2 4

Gammaridea 0.6 2.5 18.8 58

Decapoda 0.1 1.2 6.2 8

Pandalidae 0.1 0.8 6.2 6

Pandalus goniurus 0.1 0.6 6.2 4

Osteichthyes 0.6 1.9 25 62

Osmeridae 0.8 4.5 6.2 33

Mallotus villosus 0.7 2.6 12.5 41

Theragra chalcogramma 0.4 0.2 6.2 4

Table A3. Indices of relative importance of prey eaten by 

Marbled Murrelets, Chiniak Bay, February 1978. 

[From Krasnow and Sanger, 1982. N = 16 murrelets, 3 empty stomachs; 837 

items, 80 mL items, 76 mL volume]

Izhut Bay Northern Sitkalidak Strait

Month/

Sample 

details

Species % No. % Vol. % FO IRI Month Species % No. % Vol. % FO IRI

April Thysaneossa raschii 37.5 9.4 33.3 1,562

n = 3 Osteichthyes 4.2 3.1 33.3 243

24 items Ammodytes hexapterus 58.3 87.5 66.7 9,725

24 mL vol

May Crustacea 1.4 0.4 33.3 60 May Thysanoessa inermis 96.6 92.5 100 18,910

N = 3 Osteichthyes 2.7 6.8 33.3 316 n = 4 Osteichthyes 0.8 2.5 25 82

74 items Osmeridae 2.7 731 33.3 326 177 items Mallotus villosus 2.6 5 25 190

14 mL vol Mallotus villosus 93.2 85.7 33.3 5,957 12 mL vol

June Osteichthyes 80 50 57.1 7,423 June Osteichthyes 37.5 32.7 57.1 4,008

n = 7 Mallotus villosus 20 50 42.9 3,003 n = 7 Mallotus villosus 43.8 27.3 28.6 2,003

15 items 16 items Trichodon trichodon 6.2 3 14.3 132

14 mL vol 11mL vol Ammodytes hexapterus 12.5 37 28.6 1,416

July Ammodytes hexapterus 100 100 100 200,000 July Osteichthyes 50 33.3 50 4,165

n = 3 n = 4 Ammodytes hexapterus 50 66.7 50 5,835

12 items 6 items

22 mL vol 21 mL vol

August Osteichthyes 15.8 12.8 22.2 635 August Osteichthyes 100 100 100 200,000

n = 9 Mallotus villosus 5.3 7.7 11.1 144 n = 2

19 items Gadidae 5.3 5.1 11.1 115 2 items

39 mL vol Theragra chalcogramma 5.3 10.3 11.1 173 2 mL vol

Ammodytes hexapterus 68.4 64.1 44.4 5,883

Table A4. Prey eaten by Marbled Murrelets in Izhut Bay and northern Sitkalidak Strait in 1978. 

[From Krasnow and Sanger, 1982. N = 42 stomachs]

Species %No %Vol %FO IRI

Nereidae 0.3 0.1 5.6 3

Chaetognatha 0.2 5.6 1

Mysidacea 1.8 0.3 11.11 23

Acanthomysis spp. 0.5 0.3 5.6 4

Neomysis rayii 0.2 0.3 5.6 2

Thysanoessa inermis 36.4 16.2 22.2 1,169

T. spinifera 0.3 0.5 5.6 5

T. spp 2.9 3.7 11.1 74

Osteichthyes 0.3 0.3 5.6 3

Osmeridae 21.4 19.3 38.9 1,584

Mallotus villosus 35.6 59.1 5.6 526

Table A2. Indices of relative importance of prey eaten by 

Marbled Murrelets, Chiniak Bay, December 1976–April 1977. 

[From Krasnow and Sanger, 1982. N = 18 stomachs, 612 items, 76 mL 

volume]

166 Status Review of the Marbled Murrelet in Alaska and British Columbia
Sanger, G.A., 1983, Diets and food web relationships of 

seabirds in the Gulf of Alaska and adjacent marine regions, 

National Oceanic and Atmospheric Administration, Outer 

Continental Shelf Environmental Assessment Program Final 

Report 45, p. 631-771.

Sanger’s (1983) study presents a review and summary 

of murrelet diet data collected throughout the Gulf of 

Alaska in the 1970s (table A5). Birds collected at sea 

came from four primary sources: (1) Kodiak Island, 

1977–78 (Krasnow and Sanger, 1982); (2) Kachemak Bay 

(Sanger and Jones, 1982); (3) Ocean Continental Shelf 

Environmental Assessment Program cruises from 1975 to 

1978 in the Gulf of Alaska and southeastern Bering Sea; 

E Gulf of Alaska Kodiak Lower Cook Inlet NE Gulf of Alaska

Su W Sp Su W Sp F Su F

Sample size = 5 31 11 45 13 6 2 15 1

Prey name

Nereid Polychaete _ tr _ _ _ _ _ _ _

L. sitkana (Periwinkle) _ _ _ 1 _ _ _ _ _

Unid. Gastropod _ _ _ tr _ _ _ _ _

Blue Mussel _ _ _ tr _ _ _ _ _

Cephalopoda _ _ _ tr _ _ _ _ _

Acanthomysis sp _ 3 _ _ _ _ _ _

Neomysis rayii _ 1 _ _ _ _ x _ _

N. spp/unid Mysid _ 2 _ _ 2 _ _ _ _

Gammarid Amphipod _ tr _ _ 1 _ _ _ _

Euphausiids

Thysanoessa inermis _ 2 2 1 1 _ _ 3 _

T. raschii _ tr 1 _ 2 3 _ _ _

T. spinifera _ tr _ _ 1 _ _ 1 _

T. sp/Un. Euphausiid 2 1 _ tr 2 2 _ 1 _

Pandalus borealis _ tr _ _ _ _ _ _ _

Unident.Decapod _ _ _ tr _ _ _ _ _

Arrow Worm (Chaetog.) _ tr _ _ _ _ _ _ _

Fish

Capelin _ 2 3 3 3 3 _ 1 x

Unid Osmeridae 2 2 1 _ tr 2 _ _ _

Walleye Pollock _ tr _ _ tr _ _ _ _

Unid Gadid _ _ _ tr tr _ _ _ _

Pacific Sandfish 2 _ _ 1 _ _ _ 2 _

Pacific Sandlance 2 _ 2 3 2 _ x 3 x

Unid fish 3 1 1 3 2 _ _ 2 _

Table A5. Comparison of the importance of the main prey species of Marbled Murrelets in Alaskan waters in the 1970s, by major 

geographic region and season.

[Prey importance levels based on their IRI values, as follows: 0–9 = trace (tr); 10–99 = 1; 100–999 = 2; 1,000–9,999 = 3, 10,000 and up = 4; x = present. 

Seasons: W = Winter; Sp = Spring; Su = Summer; F = Fall. From Sanger, 1983]

and (4) seabirds that had drowned in gillnets deployed 

from research vessels of National Marine Fisheries 

Service south of the Aleutian Islands and the Alaska 

Peninsula from 1969 to 1971, and from collections made 

by National Marine Fisheries Service in the southeastern 

Bering Sea in 1973–74. In total, fish constituted 

50 percent of the prey numbers and 76 percent of the 

volume of Marbled Murrelet diet whereas crustaceans 

accounted for 49 percent of prey numbers and 23 percent 

of the volumes. Sanger’s synthesis highlights the seasonal 

and spatial diversity of Marbled Murrelet diet. This 

flexibility enables a broad and constant supply of food 

and this may play an important role in the over-wintering 

survival of Marbled Murrelets (Sanger, 1987; Burkett, 

1995).

Appendix A 167
Sanger, G.A., 1987, Winter diets of Common Murres and 

Marbled Murrelets in Kachemak Bay, Alaska: Condor, v. 89, 

no. 2, p. 426-430.

Sanger (1987) collected 21 adult murrelets (18 had 

stomach’s examined) from January to April 1978 in 

Kachemak Bay. Capelin was the most dominant prey 

species (by volume), with sand lance, mysids and 

euphausiids also important (table A6). The consistent 

importance of euphausiids in the diet of murrelets from 

January to April suggests there are high concentrations in 

the deepwater portion of the inner bay (Sanger and Jones, 

1982).

Piatt, J.F., and Anderson, P., 1996, Response of Common Murres 

to the Exxon Valdez oil spill and long-term changes in the 

Gulf of Alaska marine ecosystem, in Rice, S.D., Spies, R.B., 

Wolfe, D.A., and Wright, B.A., eds., Exxon Valdez Oil Spill 

Symposium, Anchorage, Alaska, 1993, American Fisheries 

Society Symposium 18, p. 720-737; and Piatt, J.F., unpub. data 

from 1989 to 1996, Alaska, adult murrelet stomach contents.

J.F. Piatt collected a total of 230 Marbled Murrelets 

from six geographic regions of Alaska between 1989–96 

(table A7). All birds were collected during the summer 

months of June–September, most in July and August. This 

represents the widest geographic sampling of murrelets 

in Alaska. Diets were similar across the range, except 

Southeast Alaska. Diets were dominated by sand lance 

and juvenile pollock. In Southeast Alaska, most birds 

Prey Totals: % Nos.

(n = 654)

%Vol. 

(82 mL) %FO IRI

%

Total

IRI

Length data (mm)

n mean SD Min Max

Crustaceans

Unidentified 0.8 1.2 5.6 11 0.2

Unidentified mysid 34.2 6.7 11.1 456 8.8 20 18 7.4 11 38

Unidentified gammarid amphipod 1.2 1.4 11.1 30 0.6 6 15 2.3 12 18

Euphausiids

Thysanoessa inermis 0.5 1.2 5.6 9 0.2 2 15 21

Thysanoessa rachii 19.4 5.7 16.7 418 8 38 14 2.3 11 21

Thysanoessa spinifera 0.2 0.9 5.6 6 0.1 1 24

Thysanoessa spp. 22.1 4 16.7 435 8.4 24 13 1.6 11 18

Fish

Unidentified 3.6 8.3 22.2 264 5.1

Mallotus villosus 11.1 51.8 50 3,146 60.6 18 63 18.1 28 105

Unidentified osmerid 0.2 0.1 5.6 1 0.1

Theragra chalcogramma 0.2 0.2 5.6 2 0.1

Ammodytes hexapterus 6.4 18.5 16.7 415 8.9 13 45 33.7 29 135

Table A6. Winter diet of Marbled Murrelets in Katchemak Bay, Alaska, between January and April 1978. 

[From Sanger (1987). N = 18 stomachs with food]

collected in Icy Strait were eating Myctophids. This 

represents an unusual diet situation for murrelets on the 

continental shelf, but reveals something about winter diet 

possibilities when murrelets are distributed in oceanic 

waters offshore. Most conspicuous in this sample is a near 

absence of capelin compared to samples collected along 

the Alaska Peninsula and around Kodiak in the 1970s–

1980s (see above) when capelin were a very common 

component of diets during summer (Piatt and Anderson, 

1996).

Speckman, S.G., Piatt, J.F., and Springer, A.M., 2003, 

Deciphering the social structure of Marbled Murrelets from 

behavioral observations at sea: Waterbirds, v. 26, no. 3, 

p. 266-274.

Speckman (1996) studied murrelets at sea in Auke Bay 

for 2 years for her MSc Thesis. She identified prey being 

carried by adults on the water. All fish-holding murrelets 

observed were in complete summer plumage, and all 

birds held a single fish crosswise in their bills. Only 12 

fish-holders were seen during morning boat surveys in 

1992, compared to 38 in 1993. A total of 203 fish-holders 

were observed, including opportunistic sightings as well 

as sightings during surveys. Of these, 81 (40 percent) 

were holding Pacific sand lance, four (2 percent) Pacific 

herring, seven (3 percent) capelin, seven (3 percent) 

were holding unidentified fish, but not sand lance, and 

104 (51 percent) were holding an unidentified fish. No 

demersal or benthic fishes or invertebrates were identified.

168 Status Review of the Marbled Murrelet in Alaska and British Columbia
Day, R.H., and Nigro, D.A., 2000, Feeding ecology of Kittlitz’s 

and Marbled Murrelets in Prince William Sound, Alaska: 

Waterbirds, v. 23, no. 1, p. 1-14.

Day and Nigro (2000) examined the feeding ecology 

of Kittlitz and Marbled Murrelets in Prince William 

Sound during the summers of 1996–98 by determining 

the distribution, abundance and foraging activity of 

murrelets on research cruises in four bays (Blackstone 

Bay; Harriman fjord; College Fjord; Unakwik Inlet). The 

number of Marbled Murrelets carrying fish varied across 

the season, with most birds (79 percent) observed during 

the late summer cruise (July 15–August 15). In total, 

77 Marbled Murrelets were observed holding or eating 

fish: 17 (22.1 percent) were Pacific sand lance; six (7.8 

percent) were Pacific herring, and 54 (70.1 percent) were 

unidentified. Overall mean prey length was 8.7 cm (± 3 

SD, n = 40 fish).

K. Kuletz and E. Labunski, U.S. Fish and Wildlife Service 

(USFWS), unpub. data, 2004–06.

K. Kuletz and co-workers at the USFWS, Anchorage, 

Alaska, conducted at-sea surveys in Kachemak Bay, to 

examine the distribution and abundance of Kittlitz’s and 

Marbled Murrelets. All surveys were conducted from a 

25-ft Boston Whaler between 0700–1800 hrs. Surveys 

were conducted on a pre-determined transect route, and 

the presence and behavior of murrelets observed were 

recorded (fig. A1). Over all 3 years, a total of 10,139 

Marbled Murrelets were observed, with 697 birds 

foraging (either actively diving or holding or eating a fish; 

table A8). A total of 57 birds were observed holding a 

fish, 88 percent were unidentified fish species, but 5 were 

Pacific sand lance and 1 was a herring (table A8).

Central-West 

Aleutians

East 

Aleutians

Alaska 

Peninsula

Cook/ 

Kodiak

Prince 

William 

Sound

Southeast 

Alaska Total

n % n % n % n % n % n % n %

Number examined 19 8 23 10 52 23 58 25 43 19 35 15 230 100

Number empty 0 0 11 5 22 10 2 1 15 7 5 2 55 24

Frequency of Occurrence

Invertebrates1 0 0 2 17 0 0 2 4 0 0 1 3 5 3

Capelin (Mallotus villosus) 0 0 0 0 0 0 10 18 0 0 2 7 12 7

Lanternfishes (Myctophidae) 0 0 0 0 0 0 0 0 0 0 17 57 17 10

Pollock and cod (Gadidae) 7 37 8 67 13 43 6 11 24 86 2 7 60 34

Sand lance (Ammodytes 

hexapterus)

11 58 2 17 9 30 31 55 2 7 7 23 62 35

Other2 1 5 0 0 8 27 7 13 2 7 1 3 19 11

Numbers of Individuals

Invertebrates1 0 0 30 44 0 0 2 1 0 0 1 1 33 4

Capelin (Mallotus villosus) 0 0 0 0 0 0 22 14 0 0 2 1 24 3

Lanternfishes (Myctophidae) 0 0 0 0 0 0 0 0 0 0 174 88 174 23

Pollock and cod (Gadidae) 25 31 35 51 90 70 20 13 122 96 5 3 297 39

Sand lance (Ammodytes 

hexapterus)

54 68 3 4 14 11 92 60 3 2 15 8 181 24

Other2 1 1 0 0 25 19 17 11 2 2 1 1 46 6

Estimated Wet Weight (g)

Invertebrates1 0 0 <1 3 0 0 4 1 0 0 2 <1 7 <1

Capelin (Mallotus villosus) 0 0 0 0 0 0 43 10 0 0 4 <1 47 3

Lanternfishes (Myctophidae) 0 0 0 0 0 0 0 0 0 0 406 87 406 28

Pollock and cod (Gadidae) 31 28 18 64 175 83 15 4 194 87 3 <1 435 30

Sand lance (Ammodytes 

hexapterus)

80 72 9 33 25 12 354 83 30 13 50 11 548 37

Other2 <1 <1 0 0 11 5 9 2 <1 <1 <1 <1 20 1

1

 Includes copepods and squid.

2

 Includes sculpin (Cottidae), flatfish (Pleuronectidae) and unidentified fish. 

Table A7. Diet of Marbled Murrelets in Alaska, 1988–2006.

[From Piatt and Anderson, 1996, and J.F. Piatt, U.S. Geological Survey, unpub. data, 2006). N = 175 stomachs with food. Percent number examined and number 

empty are calculated using the total number of birds examined. Percent frequency of occurrence, number of individuals, and estimated wet weight are calculated 

using the number of birds containing prey items. Abbreviations: g, gram; n, number; <, less than]

Appendix A 169
K. Kuletz and E. Labunski, U.S. Fish and Wildlife Service, unpub. 

data., 2005.

K. Kuletz and co-workers at the USFWS, Anchorage, 

Alaska, conducted evening surveys in Kachemak 

Bay in August 2005 to specifically examine the prey 

species that murrelets were catching for their offspring. 

Murrelets holding fish in nearshore areas during the 

evening hours were presumed to be waiting for darkness 

for meal delivery. The survey was conducted between 

1920–2100 hrs from a 25-ft Boston Whaler. Total transect 

distance was 21.1 km (fig. A2). The survey was an 

opportunistic survey of foraging murrelets and did not 

follow any predefined transect route. Observers scanned 

the water and investigated birds with fish to identify the 

prey down to species. A total of 51 birds were observed 

with 16 holding fish. Eight of the birds had a sand lance 

and 8 had an unidentified fish.

Year Month

Transect 

length 

(km)

No. total 

MAMU

No. 

MAMU 

foraging

No. 

unid. 

fish

No. 

sand 

lance

No. 

herring

2004 August 747 3,777 345 19 3 1

2005 April 35 6 0

2005 June 175 78 2 2

2005 July 228 558 13 3

2005 August 629 2,011 129 12 1

2006 June 166 146 5

2006 July 197 552 16 1

2006 August ca 641 3,011 187 13 2

Table A8. At-sea observations of Marbled Murrelets holding 

fish in Kachemak Bay, Alaska, 2004–06.

[Surveys were conducted during the day and food items are presumed to 

be for self feeding (K. Kuletz, U.S. Fish and Wildlife Service, unpub. data, 

2004–06)]

Figure A1. Transects and location of adults observed carrying fish for presumed self-consumption (Kuletz and 

Labunski, U.S. Fish and Wildlife Service, unpub. data, 2005).

170 Status Review of the Marbled Murrelet in Alaska and British Columbia
Kuletz, K.J., 2005, Foraging behavior and productivity of a 

non-colonial seabird, the Marbled Murrelet (Brachyramphus 

marmoratus), relative to prey and habitat, Dissertation: 

British Columbia, University of Victoria.

Kuletz (2005) examined the prey selection of Marbled 

Murrelets at two study sites (Naked Island and Jackpot 

Bay) in Prince William Sound during the summers (June 

to August) of 1997–99. Prey species and abundance was 

measured by sampling fish schools and aerial surveys. 

Adult prey were identified by (a) boat based and land 

based forage observations, (b) observations of fish held 

in the bill by other species foraging in the same feeding 

flock, and (c) capturing fish below foraging murrelets 

using a dip-net. Chick diet was identified by observing 

fish-holding adults during diet cruises in the morning 

(0330–0800 hrs) or evening (1900–2330 hrs).

Visually identified adult prey associated or eaten by 

adult murrelets in both areas (n= 61) were comprised 

of 41 percent herring, 52 percent sand lance, 5 percent 

capelin, and 2 percent gadids. Eighty-four percent of the 

herring were observed at Jackpot and most of the sand 

lance (94 percent) was at Naked. Fish caught in dip nets 

near foraging birds consisted mostly of 0+ and 1+ sand 

lance and 0+ herring.

Four hundred and eighty-two fish-holding birds at 

Jackpot, and 129 birds at Naked were observed during 

94 diet cruises (n = 611 fish). 64 percent of the fish were 

identified down to species (table A9). Jackpot chicks 

primarily were fed 1+ juvenile herring (77–88 percent in 

a given year), whereas birds at Naked were feeding their 

chicks 67–100 percent sand lance.

Figure A2. Transects and location of adults observed holding fish for chicks during a chick-diet survey in 

Kachemak Bay. (Kuletz and Labunski, U.S. Fish and Wildlife Service, unpub. data, 2005).

Appendix A 171
Newman, S.H., Nelson, A.K., Whitworth, D.L., and Carter, H.R., 

2006, Marbled Murrelet (Brachyraphus marmoratus) activity 

patterns and health in Port Snettisham, aoutheast Alaska, 

2005: New York, Wildlife Trust, Unpublished Report, 70 p.

Newman and colleagues conducted radio-telemetry and 

health assessment studies of Marbled Murrelets in Port 

Snettisham, Southeast Alaska, from June to August 2005. 

Four birds holding fish for their chick were captured 

whilst dip-netting adult murrelets for radio attachment. 

Three of the captured fish were large juvenile or first-year 

subadult capelin, and one was a first-year subadult Pacific 

sand lance.

References Cited

Day, R.H., Oakley, K.L., and Barnard, D.R., 1983, Nest sites 

and eggs of Kittlitz’s and Marbled Murrelets: Condor, v. 85, 

no. 3, p. 265-273.

Burkett, E.B., 1995, Marbled Murrelet food habits and prey 

ecology, in Ralph, C.J., Hunt, G.L. Jr., Raphael, M.G., and 

Piatt, J.F., eds., Ecology and conservation of the Marbled 

Murrelet: Albany, California, U.S. Forest Service, Pacific 

Southwest Research Station, General Technical Report 152, 

p. 223-246.

Year Site Identified

fish samples

Percent of total (by year and site)

Herring Sandlance Capelin Gadid Smelt Salmon Sandfish Stickleback

Fish caught below feeding adults

Schools 

(number of fish)

1998 Naked 15 (745) 66.7 33.3 0.0 0.0 0.0 0.0 0.0 0.0

Jackpot 1 100.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

1999 Naked 17 (208) 17.7 47.1 29.4 0.0 0.0 0.0 0.0 5.8

Jackpot 0 nd

Fish held for chick

Adults with fish

1997 Naked 34 0.0 94.1 0.0 2.9 0.0 0.0 2.9 0.0

Jackpot 43 88.4 9.3 0.0 2.3 0.0 0.0 0.0 0.0

1998 Naked 16 0.0 100.0 0.0 0.0 0.0 0.0 0.0 0.0

Jackpot 197 94.9 3.1 0.0 0.0 2.0 0.0 0.0 0.0

1999 Naked 12 16.7 66.7 16.7 0.0 0.0 0.0 0.0 0.0

Jackpot 70 74.3 11.4 0.0 1.4 8.6 4.3 0.0 0.0

Table A9. Species composition of identified prey used by Marbled Murrelets in Prince William Sound, Alaska, in summer, 1997–99. 

[Samples caught below feeding adults (by dip-net) during mid-day were considered self-feeding samples. Observations of fish held by adults during diet surveys 

(< 0800 hr or > 1800 hr) were considered destined for delivery to chicks. Unidentified prey are not included here. (From Kuletz, 2005)]

172 Status Review of the Marbled Murrelet in Alaska and British Columbia

Krasnow, L.D., and Sanger, G.A., 1982, Feeding ecology 

of marine birds in the nearshore waters of Kodiak Island: 

Anchorage, Alaska, U.S. Fish and Wildlife Service, 

National Fishery Research Center, Migratory Bird Section, 

Final Report to OCSEAP, Research Unit 45, p. 505-630.

Piatt, J.F., and Anderson, P., 1996, Response of Common 

Murres to the Exxon Valdez oil spill and long-term changes 

in the Gulf of Alaska marine ecosystem, in Rice, S.D., 

Spies, R.B., Wolfe, D.A., and Wright, B.A., eds., Exxon 

Valdez Oil Spill Symposium, Anchorage, Alaska, 1993, 

American Fisheries Society Symposium 18, p. 720-737.

Sanger, G.A., 1987, Winter diets of Common Murres and 

Marbled Murrelets in Kachemak Bay, Alaska: Condor, 

v. 89, no. 2, p. 426-430.

Sanger, G.A., and Jones, R.D. Jr., 1982, Winter feeding 

ecology and trophic relationships of marine birds in 

Kachemak Bay, Alaska: Anchorage, Alaska, U.S. Fish 

and Wildlife Service, National Fishery Research Center, 

Migratory Bird Section, Final Report to the Outer 

Continental Shelf Environmental Assessment Program 

(OCSEAP), v. 16, Biological Studies, p. 161-294.

Speckman, S.G., 1996, Marbled Murrelet distribution and 

abundance in relation to the marine environment: Thesis, 

Fairbanks, University of Alaska, 89 p.
Appendix B. Source Code Listing (Javascript) for the Demographic Model LIFE

(Note: Line numbers are for reference only and should not be included in the runtime 

Javascript).

_________________________________________________________________________________________

 1 <script type=”text/javascript”>

 2 

 3 function calcLambda() {

 4 var form = document.form1;

 5 var alpha = form.alpha.value;

 6 var gamma = form.gamma.value;

 7 var delta = form.delta.value;

 8 var b1 = form.b1.value;

 9 var b2 = form.b2.value;

 10 var lambda;

 11 

 12 if (!isNumber(alpha) || !isNumber(gamma) || !isNumber(delta) || !isNumber(b1)

 13 || !isNumber(b2)) {

 14 alert(“One or more input values is non-numeric. Fix and try again.”);

 15 return;

 16 }

 17 

 18 if (alpha < 0 || gamma < 0 || b1 < 0 || b2 < 0 || !isPosInteger(delta)) {

 19 alert(“One or more input values invalid. Edit and try again.”);

 20 return;

 21 }

 22 

 23 if (delta < 2) {

 24 alert(“Age at first breeding must be >= 2.”);

 25 return;

 26 }

 27 

 28 alpha = parseFloat(alpha);

 29 gamma = parseFloat(gamma);

 30 delta = parseFloat(delta);

 31 b1 = parseFloat(b1);

 32 b2 = parseFloat(b2);

 33 

 34 var year1 = b1 * gamma;

 35 var year2 = b2 * gamma;

 36 var constant = alpha * year1 * year2 * (Math.pow(gamma,delta-2));

 37 

 38 var upperBound = 1.2

 39 var lowerBound = 0.8

 40 var midValue = 1.0

 41 var criterion = 0.0001

 42 var diff = 1 - gamma - constant;

 43 

 44 if (Math.abs(diff) < criterion) {

 45 form.lambda.value = “1.0000”;

 46 return;

 47 }

Appendix B 173
 48 if (diff < 0) {

 49 upperBound = 1.2;

 50 lowerBound = 1.0;

 51 if (Math.pow(upperBound,delta)-gamma*(Math.pow(upperBound,delta-1)) -

 52 constant < 0) {

 53 alert(“Population growth exceeds 20% per year. Run terminated.”)

 54 return;

 55 }

 56 } else {

 57 upperBound = 1.0;

 58 lowerBound = 0.8;

 59 if (Math.pow(lowerBound,delta)-gamma*(Math.pow(lowerBound,delta-1)) -

 60 constant > 0) {

 61 alert(“Population decline exceeds -20% per year. Run

 terminated.”)

 62 return;

 63 }

 64 }

 65 

 66 while (Math.abs(diff) >= criterion) {

 67 midValue = (upperBound + lowerBound)/2

 68 diff = Math.pow(midValue,delta) - gamma * Math.pow(midValue,delta-1) -

 69 constant;

 70 if (diff == 0) {

 71 form.lambda.value = formatLambda(midValue);

 72 return;

 73 }

 74 if (diff < 0) {

 75 lowerBound = midValue;

 76 } else {

 77 upperBound = midValue;

 78 }

 79 }

 80 form.lambda.value = formatLambda(midValue);

 81 }

 82 

 83 function isNumber(inputVal) {

 84 var oneDecimal = false;

 85 var oneChar;

 86 var inputStr = inputVal.toString();

 87 for (var i = 0; i < inputStr.length; i++) {

 88 oneChar = inputStr.charAt(i);

 89 if (i == 0 && oneChar == “-”) {

 90 continue;

 91 }

 92 if (oneChar == “.” && !oneDecimal) {

 93 oneDecimal = true;

 94 continue;

 95 }

 96 if (oneChar < “0” || oneChar > “9”) {

 97 return false;

 98 }

 99 }

174 Status Review of the Marbled Murrelet in Alaska and British Columbia
 100 return true;

 101 }

 102 

 103 function isPosInteger(inputVal) {

 104 var inputStr = inputVal.toString();

 105 for (var i=0; i<inputStr.length; i++) {

 106 var oneChar = inputStr.charAt(i);

 107 if (oneChar < “0” || oneChar > “9”) {

 108 return false;

 109 }

 110 }

 111 return true;

 112 }

 113 

 114 function formatLambda(midValue) {

 115 var roundup;

 116 if (midValue == 1.0) return “1.0000”;

 117 lambda = midValue.toString();

 118 roundup = (parseInt(lambda.substr(6,1)) >= 5)? true:false;

 119 if (roundup) lambda = (midValue + 0.0001).toString();

 120 return lambda.substr(0,6);

 121 }

 122 

 123 </script>

_________________________________________________________________________________________

Appendix B 175
This page left intentionally blank.

176 Status Review of the Marbled Murrelet in Alaska and British Columbia
Appendix C. Source Code Listing (Fortran) for the Population Model MATRIX

(Note: Line numbers are for reference only and should not be compiled with source code).

_________________________________________________________________________________________

 1 program matrix

 2 

 3 real(8), allocatable :: Nt(:)

 4 real(8), allocatable :: Nzero(:)

 5 real(8), allocatable :: M(:,:)

 6 real(8), allocatable :: detM(:,:)

 7 real(8), allocatable :: stableAD(:)

 8 real(8), allocatable :: oldAD(:)

 9 real(8), allocatable :: newAD(:)

 10 real(8), allocatable :: oldNt(:)

 11 real(8), allocatable :: newNt(:)

 12 real(8), allocatable :: detNt(:)

 13 real(8), allocatable :: stoNt(:)

 14 real span(0:29)

 15 integer E(1:1000,1:4),sumE,cutoff

 16 real(8) year1,year2,b1,b2,gamma,SDb1,SDb2,SDgamma,SDalpha

 17 integer delta,ubound,years,a,meanE

 18 real(8) y,rvcov,rvsummer,rvwinter,oldNtsum,newNtsum,sum

 19 real(8) oldSum,newSum,lambda

 20 real(8) upperbound,lowerbound,midvalue,diff

 21 real(8) criterion1,criterion2

 22 real(8) ntotal,Ntsum,sumN,Nstart,newN,classize

 23 real(8) detNtsum,stoNtsum

 24 real trends(1:3),alpha,adjAlpha,alpha_z

 25 character*1 cov,fixed,allowGTone,done,detDone,lambdaOne

 26 

 27 open (21,file=’c:\matrix_out\stableAD.txt’,status=’replace’)

 28 open (22,file=’c:\matrix_out\stats.txt’,status=’replace’)

 29 open (23,file=’c:\matrix_out\freqtrends_ind.txt’,status=’replace’)

 30 open (24,file=’c:\matrix_out\freqtrends_cov.txt’,status=’replace’)

 31 open (25,file=’c:\matrix_out\ext_times.txt’,status=’replace’)

 32 open (26,file=’c:\matrix_out\growth_det.txt’,status=’replace’)

 33 open (27,file=’c:\matrix_out\growth_sto_L1.txt’,

 34 + status=’replace’)

 35 open (28,file=’c:\matrix_out\growth_sto_Lcalc.txt’,

 36 + status=’replace’)

 37 

 38 data span/30*0/

 39 write(23,’(3a10)’) ‘trends10’,’trends20’,’trends30’

 40 write(24,’(3a10)’) ‘trends10’,’trends20’,’trends30’

 41 write(25,’(4a20)’) ‘ext_ind_L1’,’ext_cov_L1’,’ext_ind_Lcalc’,

 42 + ‘ext_cov_Lcalc’

 43 write(21,’(a5,2a20)’) ‘class’,’SAD(lambda=1)’,’SAD(lambda=calc)’

 44 

 45 * Note: The following lines can be used for interactive user

 46 * input of parameter values

 47 
 48 * print *, ‘ ‘

 49 * print *, ‘Enter first-year survival (as proportion of adult survival):’

 50 * print *, ‘ ‘

 51 * read (*,*) year1

 52 

 53 * print *, ‘ ‘

 54 * print *, ‘Enter SD of first-year survival (decimal value):’

 55 * print *, ‘ ‘

 56 * read (*,*) SDb1

 57 

 58 * print *, ‘ ‘

 59 * print *, ‘Enter second-year survival (as proportion of adult survival):’

 60 * print *, ‘ ‘

 61 * read (*,*) year2

 62 

 63 * print *, ‘ ‘

 64 * print *, ‘Enter SD of second-year survival (decimal value):’

 65 * print *, ‘ ‘

 66 * read (*,*) SDb2

 67 

 68 * print *, ‘ ‘

 69 * print *, ‘Enter adult survival (as proportion, not %):’

 70 * print *, ‘ ‘

 71 * read (*,*) gamma

 72 

 73 * print *, ‘ ‘

 74 * print *, ‘Enter SD of adult survival (decimal value):’

 75 * print *, ‘ ‘

 76 * read (*,*) SDgamma

 77 

 78 * print *, ‘ ‘

 79 * print *, ‘Enter age at first breeding (integer):’

 80 * print *, ‘ ‘

 81 * read (*,*) delta

 82 

 83 * print *, ‘ ‘

 84 * print *, ‘Enter fecundity (female offspring per adult female):’

 85 * print *, ‘ ‘

 86 * read (*,*) alpha

 87 

 88 * print *, ‘ ‘

 89 * print *, ‘Enter SD fecundity (decimal value):’

 90 * print *, ‘ ‘

 91 * read (*,*) SDalpha

 92 

 93 * print *, ‘ ‘

 94 * print *, ‘Enter starting population size (integer):’

 95 * print *, ‘ ‘

 96 * read (*,*) ntotal

 97 

 98 * print *, ‘ ‘

 99 * print *, ‘Could fecundity ever exceed 1.0 in this species? Enter “y” or “n”:’

 100 * print *, ‘ ‘

 101 * read (*,*) allowGTone

 102 

178 Status Review of the Marbled Murrelet in Alaska and British Columbia
 103 year1 = 0.701

 104 year2 = 0.888

 105 gamma = 0.880

 106 SDb1 = 0.06

 107 SDb2 = 0.06

 108 SDgamma = 0.06

 109 delta = 3

 110 alpha = 0.294953

 111 SDalpha = 0.10

 112 ntotal = 3000

 113 allowGTone = ‘n’

 114 

 115 b1 = year1*gamma

 116 b2 = year2*gamma

 117 

 118 cutoff = 5 ! Sets maximum lifespan (% adults still living)

 119 

 120 i=0

 121 do while ((100*gamma**i).ge.cutoff)

 122 i=i+1

 123 end do

 124 

 125 ubound = i + delta

 126 

 127 allocate (Nt(0:ubound))

 128 allocate (M(0:ubound,0:ubound))

 129 allocate (detM(0:ubound,0:ubound))

 130 allocate (stableAD(0:ubound))

 131 allocate (Nzero(0:ubound))

 132 allocate (oldAD(0:ubound))

 133 allocate (newAD(0:ubound))

 134 allocate (oldNt(0:ubound))

 135 allocate (newNt(0:ubound))

 136 allocate (detNt(0:ubound))

 137 allocate (stoNt(0:ubound))

 138 

 139 do i=0,ubound ! Initialize projection matrix

 140 do j=0,ubound

 141 M(i,j) = 0

 142 end do

 143 end do

 144 

 145 * Construct stable age distribution for lambda=1

 146 

 147 Nzero(delta) = 100

 148 i = delta-1

 149 do while (i.gt.1)

 150 Nzero(i) = Nzero(i+1)/gamma

 151 i=i-1

 152 end do

 153 

 154 Nzero(1) = Nzero(2)/b2

 155 Nzero(0) = Nzero(1)/b1

 156 

Appendix C 179
 157 do i = delta+1,ubound

 158 Nzero(i) = Nzero(i-1)*gamma

 159 end do

 160 

 161 Ntsum = 0

 162 do i = 0,ubound

 163 Ntsum = Ntsum + Nzero(i)

 164 end do

 165 

 166 do i = 0,ubound

 167 classize = Nzero(i)/Ntsum

 168 stableAD(i) = classize ! Save stableAD for lambda=1

 169 Nzero(i) = classize * ntotal

 170 end do

 171 

 172 Nt = Nzero

 173 Ntsum = sumNt()

 174 Nstart = Ntsum

 175 Nextinct = 0.05*Nstart ! Population “extinct” when <5% remains

 176 

 177 * Find adjAlpha - fecundity that results in stationary population

 178 * with given survival values (uses iterative interpolation)

 179 * Also, create a fixed projection matrix and save

 180 * a copy (detM) for later use

 181 

 182 oldNtsum = Ntsum

 183 adjAlpha = alpha

 184 criterion1 = .001

 185 

 186 M(1,0) = b1

 187 M(2,1) = b2

 188 do j = 2,ubound-1

 189 M(j+1,j) = gamma

 190 end do

 191 do j = delta,ubound

 192 M(0,j) = alpha

 193 end do

 194 

 195 detM = M

 196 

 197 Nt = matmul(M,Nt)

 198 newNtsum = sumNt()

 199 diff = newNtsum - oldNtsum

 200 

 201 if (diff.gt.0) then

 202 upperbound = alpha

 203 lowerbound = 0

 204 else if (diff.lt.0) then

 205 if (allowGTone.eq.’y’) then

 206 upperbound = 5

 207 else

 208 upperbound = 1

 209 end if

 210 lowerbound = alpha

 211 end if

 212 

180 Status Review of the Marbled Murrelet in Alaska and British Columbia
 213 do while (abs(diff).ge.criterion1)

 214 Nt = Nzero

 215 adjAlpha = (upperbound + lowerbound)/2

 216 do j = delta,ubound

 217 M(0,j) = adjAlpha

 218 end do

 219 Nt = matmul(M,Nt)

 220 newNtsum = sumNt()

 221 diff = newNtsum - oldNtsum

 222 if (diff.lt.0) then

 223 lowerBound = adjAlpha;

 224 else

 225 upperBound = adjAlpha;

 226 end if

 227 end do

 228 

 229 Nt = Nzero

 230 

 231 call random_seed()

 232 

 233 * Compute trend frequencies for intervals of 10,20,30 years

 234 * Cov = ‘y’ means covarience of winter/summer random variates

 235 * Cov = ‘n’ means winter/summer rates vary independently

 236 * Lambda = 1

 237 

 238 do ifreq = 1,2

 239 if (ifreq.eq.1) then

 240 cov = ‘n’

 241 else

 242 cov = ‘y’

 243 end if

 244 do i=1,50

 245 years = 0

 246 Nt = Nzero

 247 Ntsum = Nstart

 248 do while (Ntsum.ge.Nextinct)

 249 call fillMatrix(adjAlpha)

 250 Nt = matmul(M,Nt)

 251 Ntsum = sumNt()

 252 if (years.le.29) then

 253 span(years) = Ntsum

 254 else

 255 call calcTrends()

 256 end if

 257 years = years + 1

 258 end do

 259 end do

 260 end do

 261 

 262 * Compute a large number of extinction times and

 263 * calculate mean time to extinction when lambda=1

 264 

 265 do iext = 1,2

 266 if (iext.eq.1) then

 267 cov = ‘n’

 268 else

Appendix C 181
 269 cov = ‘y’

 270 end if

 271 do i=1,1000

 272 years = 0

 273 Nt = Nzero

 274 Ntsum = Nstart

 275 do while (Ntsum.ge.Nextinct)

 276 call fillMatrix(adjAlpha)

 277 Nt = matmul(M,Nt)

 278 Ntsum = sumNt()

 279 years = years + 1

 280 end do

 281 E(i,iext) = years

 282 end do

 283 end do

 284 

 285 * Save 4 examples of population trajectories

 286 * for cov=’y’ and cov=’n’ when lambda=1

 287 

 288 cov = ‘n’

 289 do i=1,4

 290 years = 0

 291 write (27,’(a4,i1,i7,i10)’) ‘ind’,i,0,nint(Nstart)

 292 Nt = Nzero

 293 Ntsum = Nstart

 294 do while (Ntsum.ge.Nextinct)

 295 call fillMatrix(adjAlpha)

 296 Nt = matmul(M,Nt)

 297 Ntsum = sumNt()

 298 years = years + 1

 299 write (27,’(a4,i1,i7,i10)’) ‘ind’,i,years,nint(Ntsum)

 300 end do

 301 end do

 302 

 303 cov = ‘y’

 304 do i=1,4

 305 years = 0

 306 write (27,’(a4,i1,i7,i10)’) ‘cov’,i,0,nint(Nstart)

 307 Nt = Nzero

 308 Ntsum = Nstart

 309 do while (Ntsum.ge.Nextinct)

 310 call fillMatrix(adjAlpha)

 311 Nt = matmul(M,Nt)

 312 Ntsum = sumNt()

 313 years = years + 1

 314 write (27,’(a4,i1,i7,i10)’) ‘cov’,i,years,nint(Ntsum)

 315 end do

 316 end do

 317 

 318 * Find stable age distribution and lambda for the input

 319 * parameters as given (no stochasticity)

 320 

 321 oldAD = stableAD

 322 oldNt = Nzero

182 Status Review of the Marbled Murrelet in Alaska and British Columbia
 323 do i=1,1000

 324 newNt = matmul(detM,oldNt)

 325 sum = 0

 326 do k=0,ubound

 327 sum = sum + newNt(k)

 328 end do

 329 do k=0,ubound

 330 newAD(k) = newNt(k)/sum

 331 newNt(k) = newAD(k) * ntotal

 332 end do

 333 oldNt = newNt

 334 end do

 335 do i=0,ubound

 336 write (21,’(i5,2(12x,F8.6))’) i,stableAD(i),newAD(i)

 337 end do

 338 

 339 sum = 0

 340 do i=0,ubound

 341 sum = sum + newNt(i)

 342 end do

 343 oldSum = sum

 344 newNt = matmul(detM,oldNt)

 345 newSum = 0

 346 do k=0,ubound

 347 newSum = newSum + newNt(k)

 348 end do

 349 lambda = 1 + (newSum-oldSum)/oldSum

 350 

 351 * Calculate growth for parameters as given

 352 

 353 criterion2 = 0.000001

 354 lambdaIsOne = ‘n’

 355 if (abs(lambda-1).le.criterion2) lambdaIsOne = ‘y’

 356 Nt = Nzero

 357 Ntsum = Nstart

 358 years = 0

 359 write (26,’(a4,i7,i10)’) ‘det0’,0,nint(Nstart)

 360 if (lambdaIsOne.eq.’y’) then

 361 do i=1,100

 362 write (26,’(a4,i7,i10)’) ‘det0’,i,nint(Ntsum)

 363 end do

 364 else if (lambda.lt.1) then

 365 years = 0

 366 do while (Ntsum.ge.Nextinct)

 367 Nt = matmul(detM,Nt)

 368 Ntsum = sumNt()

 369 years = years + 1

 370 write (26,’(a4,i7,i10)’) ‘det0’,years,nint(Ntsum)

 371 end do

 372 else if (lambda.gt.1) then

 373 years = 0

 374 do while (Ntsum.le.50000000.and.years.lt.1000)

 375 Nt = matmul(detM,Nt)

Appendix C 183
 376 Ntsum = sumNt()

 377 years = years+1

 378 write (26,’(a4,i7,i10)’) ‘det0’,years,nint(Ntsum)

 379 end do

 380 end if

 381 

 382 * Compute a large number of extinction times and calculate

 383 * mean extinction time when lambda = lambda(calc)

 384 

 385 do iext = 3,4

 386 if (iext.eq.3) then

 387 cov = ‘n’

 388 else if (iext.eq.4) then

 389 cov = ‘y’

 390 end if

 391 do i=1,1000

 392 years = 0

 393 Nt = Nzero

 394 Ntsum = Nstart

 395 do while (Ntsum.ge.Nextinct.and.years.lt.5000)

 396 call fillMatrix(alpha)

 397 Nt = matmul(M,Nt)

 398 Ntsum = sumNt()

 399 years = years + 1

 400 end do

 401 E(i,iext) = years

 402 end do

 403 end do

 404 

 405 do kk=1,1000

 406 write (25,’(4i20)’) (E(kk,kn),kn=1,4)

 407 end do

 408 

 409 do iext = 1,4

 410 sumE = 0

 411 do kk = 1,1000

 412 sumE = sumE + E(kk,iext)

 413 end do

 414 meanE = sumE/1000

 415 if (iext.eq.1) then

 416 meanEind_L1 = meanE

 417 else if (iext.eq.2) then

 418 meanEcov_L1 = meanE

 419 else if (iext.eq.3) then

 420 meanEind_Lcalc = meanE

 421 else

 422 meanEcov_Lcalc = meanE

 423 end if

 424 end do

 425 

 426 write (22,’(a19,12x,f8.6)’) ‘Lambda (calculated)’,lambda

 427 write (22,’(a23,8x,i8)’) ‘Mean ext lambda=1 (ind)’,meanEind_L1

 428 write (22,’(a23,8x,i8)’) ‘Mean ext lambda=1 (cov)’,meanEcov_L1

 429 write (22,’(a26,5x,i8)’) ‘Mean ext lambda=calc (ind)’,

 430 + meanEind_Lcalc

 431 write (22,’(a26,5x,i8)’) ‘Mean ext lambda=calc (cov)’,

184 Status Review of the Marbled Murrelet in Alaska and British Columbia
 432 + meanEcov_Lcalc

 433 write (22,’(a20,11x,f8.6)’) ‘Alpha (for lambda=1)’,adjAlpha

 434 

 435 * Save 4 examples of population trajectories

 436 * for cov=’y’ and cov=’n’ when lambda = lambda(calc)

 437 

 438 cov = ‘n’

 439 do i=1,4

 440 years = 0

 441 detDone = ‘n’

 442 write (28,’(a4,i1,i7,2i10)’) ‘ind’,i,0,nint(Nstart),

 443 + nint(Nstart)

 444 detNt = Nzero

 445 stoNt = Nzero

 446 detNtsum = Nstart

 447 stoNtsum = Nstart

 448 do while (stoNtsum.ge.Nextinct.and.stoNtsum.lt.50000000

 449 + .and.years.lt.5000)

 450 call fillMatrix(alpha)

 451 stoNt = matmul(M,stoNt)

 452 stoNtsum = 0

 453 do kj=0,ubound

 454 stoNtsum = stoNtsum + stoNt(kj)

 455 end do

 456 if (detDone.eq.’n’) then

 457 if (lambdaIsOne.eq.’n’) then

 458 detNt = matmul(detM,detNt)

 459 detNtsum = 0

 460 do kj=0,ubound

 461 detNtsum = detNtsum + detNt(kj)

 462 if (detNtsum.gt.50000000) detDone = ‘y’

 463 end do

 464 else

 465 detNtsum = Nstart

 466 end if

 467 else

 468 detNtsum = 0

 469 end if

 470 years = years + 1

 471 write (28,’(a4,i1,i7,2i10)’) ‘ind’,i,years,

 472 + nint(stoNtsum),nint(detNtsum)

 473 end do

 474 end do

 475 

 476 cov = ‘y’

 477 do i=1,4

 478 years = 0

 479 detDone = ‘n’

 480 write (28,’(a4,i1,i7,2i10)’) ‘cov’,i,0,nint(Nstart),

 481 + nint(Nstart)

 482 detNt = Nzero

 483 stoNt = Nzero

 484 detNtsum = Nstart

 485 stoNtsum = Nstart

 486 do while (stoNtsum.ge.Nextinct.and.stoNtsum.lt.50000000

 487 + .and.years.lt.5000)

Appendix C 185
 488 call fillMatrix(alpha)

 489 stoNt = matmul(M,stoNt)

 490 stoNtsum = 0

 491 do kj=0,ubound

 492 stoNtsum = stoNtsum + stoNt(kj)

 493 end do

 494 if (detDone.eq.’n’) then

 495 if (lambdaIsOne.eq.’n’) then

 496 detNt = matmul(detM,detNt)

 497 detNtsum = 0

 498 do kj=0,ubound

 499 detNtsum = detNtsum + detNt(kj)

 500 if (detNtsum.gt.50000000) detDone = ‘y’

 501 end do

 502 else

 503 detNtsum = Nstart

 504 end if

 505 else

 506 detNtsum = 0

 507 end if

 508 years = years + 1

 509 write (28,’(a4,i1,i7,2i10)’) ‘cov’,i,years,

 510 + nint(stoNtsum),nint(detNtsum)

 511 end do

 512 end do

 513 

 514 contains

 515 

 516 function rv()

 517 total = 0

 518 do k = 1,12

 519 call random_number(y)

 520 total = total + y

 521 end do

 522 rv = total-6

 523 end function

 524 

 525 subroutine fillMatrix(alpha_z)

 526 rvcov = rv()

 527 rvwinter = rv()

 528 rvsummer = rv()

 529 do a = delta,ubound

 530 if (cov.eq.’y’) then

 531 M(0,a) = alpha_z + (SDalpha*rvcov)

 532 else

 533 M(0,a) = alpha_z + (SDalpha*rvsummer)

 534 end if

 535 if (M(0,a).lt.0) M(0,a) = 0

 536 if (M(0,a).gt.1.and.allowGTone.eq.’n’) M(0,a) = 1

 537 end do

 538 if (cov.eq.’y’) then

 539 M(1,0) = b1 + (SDb1*rvcov)

 540 M(2,1) = b2 + (SDb2*rvcov)

 541 else

 542 M(1,0) = b1 + (SDb1*rvwinter)

186 Status Review of the Marbled Murrelet in Alaska and British Columbia
 543 M(2,1) = b2 + (SDb2*rvwinter)

 544 end if 

 545 if (M(1,0).lt.0) M(1,0) = 0

 546 if (M(1,0).gt.1) M(1,0) = 1

 547 if (M(2,1).lt.0) M(2,1) = 0

 548 if (M(2,1).gt.1) M(2,1) = 1

 549 do a = 2,ubound-1

 550 if (cov.eq.’y’) then

 551 M(a+1,a) = gamma + (SDgamma*rvcov)

 552 else

 553 M(a+1,a) = gamma + (SDgamma*rvwinter)

 554 end if

 555 if (M(a+1,a).lt.0) M(a+1,a) = 0

 556 if (M(a+1,a).gt.1) M(a+1,a) = 1

 557 end do

 558 end subroutine

 559 

 560 function sumNt()

 561 sum = 0

 562 do k=0,ubound

 563 sum = sum + Nt(k)

 564 end do

 565 sumNt = sum

 566 end function

 567 

 568 subroutine calcTrends()

 569 do nn=0,28

 570 span(nn) = span(nn+1)

 571 end do

 572 span(29) = Ntsum

 573 do lk=1,3

 574 trends(lk) = ((span(10*lk-1) - span(0))/span(0))*100

 575 end do

 576 if (cov.eq.’n’) then

 577 write (23,’(3(f10.1))’) (trends(il),il=1,3)

 578 else

 579 write (24,’(3(f10.1))’) (trends(il),il=1,3)

 580 end if

 581 end subroutine

 582 

 583 end program

_________________________________________________________________________________________

Appendix C 187
188 Status Review of the Marbled Murrelet in Alaska and British Columbia

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Appendix D. Current Population Estimates—British Columbia

by Alan E. Burger1

Burger (2002) summarized at-sea and radar counts 

for British Columbia to estimate the provincial population 

(table D1). Most of the vast coastline of British Columbia 

did not have count data and estimates were based on several 

methods of extrapolating from at-sea or radar counts covering 

portions of each of the six conservation regions established by 

the Canadian Marbled Murrelet Recovery Team (CMMRT) 

(see map of regions: fig. 7). More than 32,500 birds were 

actually counted, and the likely population was estimated 

to be 55,000–78,000 birds (median 66,000 birds; table D1). 

Burger (2002) stressed that there was much uncertainty in 

these estimates, because large areas of the British Columbia 

coast had not been censused, many of the census data were 

out of date and often based on single boat transects, and 

extrapolations from the patchy census data were necessarily 

crude.

There is little new information with which to update 

and improve the crude population estimates made by Burger 

(2002). Nevertheless, I have tried to improve the population 

estimates in two ways: first by updating, where possible, the 

information used by Burger (2002), and second by making a 

new estimate by applying densities derived from radar studies 

to estimates of total habitat area within British Columbia. 

Neither of these approaches is highly satisfactory and an 

accurate estimate of the British Columbia population remains 

elusive.

Updated Regional Population Estimates

The only new data available to improve regional 

population estimates comes from radar studies. The CMMRT 

has recommended the use of radar to monitor population 

trends (Bertram and others, 2003), and radar also is 

widely used in British Columbia for identifying watershed 

populations and relationships with habitat (see for example, 

Burger, 2001, Burger and others, 2004). Radar counts 

cannot be directly compared with at-sea counts from boats. 

Most studies in British Columbia use radar at the mouths of 

watersheds to count birds heading into watersheds. Radar 

counts tend to reveal higher numbers of birds than at-sea 

counts in adjacent areas (Burger, 2001), but because murrelets 

can commute large distances (Whitworth and others, 2000; 

Hull and others, 2001), one cannot reliably link these radar 

counts with counts made at sea in marine foraging areas. 

In some cases, estimates based on incomplete at-sea counts 

(Burger, 2002) can be re-assessed using radar counts made in 

the same areas. Neither method provides a complete, accurate 

measure of local populations and uncertainty remains over all 

regional estimates, and mix of radar and at-sea counts had to 

be used in some regions.

West and North Vancouver Island.—The 2002 

estimates were based on both at-sea and radar counts where 

appropriate (Burger, 2002). There are no new at-sea counts 

to include, but recent radar counts tend to support earlier 

estimated population ranges (table D2). Estimates made in the 

subregions on West and North Vancouver Island are discussed 

here.

Owen Point-Cape Beale (West Coast Trail coast).—The 

2002 estimate was based on repeated at-sea counts made 

in 1994–2001 covering this entire coastline, and there was 

some confidence in the estimate (3,000–3,300 birds; table 

D2). The same transect data indicate declines in numbers in 

this area between 1994 and 2006 (see appendix E). Radar 

surveys covering 11 watersheds leading off this coast in 

2002–05 gave pooled mean counts of 2,126 birds and pooled 

mean of the annual maximum counts of 2,593 birds (table 

D3; A.E. Burger, University of Victoria, unpub. data, 2006). 

The watersheds sampled included a substantial portion of 

the likely nesting areas off this coast, but did not cover some 

large areas of suitable forest, including the Nitinat Triangle, 

Cheewat, lower Walbran, Logan and Cullite drainages. Taking 

these unsurveyed areas into account, the radar counts seem 

1 consistent with the 2002 estimates. University of Victoria, British Columbia

Conservation region

Population 

estimate made 

in 2002 (birds)

Updated estimate 

(birds)

West and North Vancouver 

Island

19,400–24,500 18,700-23,600

East Vancouver Island 700–1,000 1,000-2,000

Southern Mainland Coast 6,000–7,000 6,000–7,000

Central Mainland Coast 10,000–21,000 10,000–21,000

Northern Mainland Coast 10,100–14,600 10,100–14,600

Haida Gwaii (Queen 

Charlotte Islands) 

8,500–9,500 8,500 – 25,000

Total for British Columbia 54,700–77,600 54,300 – 92,600

Table D1. Population estimates for British Columbia as reported 

by Burger (2002) and updated with new information (2006). 

[Birds, not breeding pairs or nests, are the measure of population used here. 

Conservation region: For details on the conservation regions see Bertram 

and others (2003; available at http://www.sfu.ca/biology/wildberg/bertram/

mamurt/links.htm). Population estimate made in 2002: Range indicates the 

pessimistic and optimistic population estimates (Burger, 2002). Note that these 

estimates were often based on data from 10 to 25 years earlier than 2002. 

Updated estimate: See text for details on new population data and updated 

estimates. Note that these estimates remain relatively crude for most of the 

conservation regions.

Appendix D 189
Barkley Sound and Alberni Canal.—The 2002 estimate 

for these areas (3,200–3,900 birds; table D2) was based on 

at-sea counts made in the 1980s and early 1990s (Burger, 

2002). Repeated surveys on four transect routes in Barkley 

Sound all indicate declines since 1979 or 1980 (see appendix 

E). Radar surveys covering 19 watersheds leading off these 

waterways in 2002–05 gave pooled mean counts of 1,949 

birds and pooled mean of the annual maximum counts of 

2,182 birds (table D3; A.E. Burger, University of Victoria, 

unpub. data, 2005). The watersheds sampled covered all major 

drainages containing likely nesting habitat and a substantial 

portion of the total nesting habitat area here. It therefore seems 

unlikely that the 2002 estimate is correct, and a more likely 

population range here is 2,500–3,000 birds.

Clayoquot Sound and Long Beach.—The 2002 estimate 

of 6,000—8,000 birds (table D2) was based on radar counts at 

20 watersheds in 1995–98 covering most of the likely habitat 

(Burger, 2002, appendix 2). Fourteen of these sites were 

resurveyed with radar in 2006, yielding similar total counts to 

1995–98 (A.E. Burger, unpub. data). Consequently, there is no 

evidence to change the 2002 estimate.

NW Vancouver Island (Estevan Point to Cape Sutil).—

At-sea counts were too sparse to derive estimates for this area, 

and Burger (2002) used Manley’s (British Columbia Ministry 

of Environment, unpub. data, 2000) radar counts from 1999 

and 2001 at 18 watersheds totaling 5,930 birds to reach an 

estimate of 6,500–8,000 birds (table D2; see also Burger, 

2002, appendix 2). Radar counts made by W. Harper and J. 

Deal (Canadian Forest Products, Ltd., unpub. data, 2003–04) 

at four of Manley’s coastal sites showed similar numbers 

to 1999–2001. There are no new at-sea counts in this area. 

Population estimates for this area therefore remain the same as 

in 2002 (table D2).

NE Vancouver Island.—Burger (2002) estimated 500–

1,000 murrelets in the sector, based on very incomplete at-sea 

counts made in 1991 (table D2). Radar counts in 2003–04 at 

nine sites in this region, mostly inland, showed a total of 295 

(sum of mean counts) to 383 birds (sum of the total counts; 

W. Harper and J. Deal, Canadian Forest Products, Ltd., unpub. 

data, 2003–04). There are no new at-sea counts. The estimate 

of 500–1,000 murrelets in this area might be optimistic, but in 

the absence of better data should remain (table D2).

The updated total for the West and North Vancouver 

Island region is 18,700–23,600 birds (table D1), which is 

slightly lower overall than the 2002 estimate (table D1).

Section within 

the region

2002 estimates 2006 estimates

Notes on new data

Actual counts Estimated 

range

Actual counts Estimated 

range

Victoria Harbour to 

Port San Juan

– 200–300 – 200–300 No new data

West Coast Trail 

(Owen Point to 

Cape Beale)

2,859 3,000–3,300 Mean: 2,126

Mean of max.: 

2,593

3,000–3,300 Radar counts covered most but 

not all watersheds. Radar 

counts support previous 

estimate.

Barkley Sound + 

Alberni Inlet

3,618 3,200–3,900 Mean: 1949

Mean of max.: 

2,182

2,500–3,000 Radar counts covered all 

major watersheds and most 

nesting habitat. Previous 

estimate reduced.

Clayoquot Sound 

and Long Beach

5,536 6,000–8,000 See text 6,000–8,000 Radar counts show no change.

NW Vancouver 

Island

5,930 6,500–8,000 See text 6,500–8,000 Radar counts at a four sites 

similar to previous.

NE Vancouver 

Island

418 500–1000 383 500–1,000 Radar counts at nine sites. 

Estimates possibly 

optimistic.

Total 18,361 19,400–24,500 - 18,700–23,600

Table D2. Counts and estimated populations of Marbled Murrelets during the breeding season (May through 

July) in the West and North Vancouver Island conservation region, British Columbia. 

[See Burger (2002) for details on 2002 estimates]

190 Status Review of the Marbled Murrelet in Alaska and British Columbia
Marine 

source

Watershed 

code Watershed

Pre-sunrise count of murrelets

Number of 

Mean surveys SD Min. Max. Mean of annual 

maximum

A.—Birds likely to be coming from West Coast Trail coast

CAR Carmanah Valley 114.5 61.0 63 196 196.0 4

CAY Caycuse River 195.7 86.7 124 292 231.5 3

DAR Darling River 91.5 65.1 15 150 75.0 4

GOR Gordon River 148.2 99.4 47 287 244.5 5

KLA_BO Bottard Creek 120.3 50.9 75 180 130.5 4

KLA_GO Gorge Creek 151.8 76.1 67 234 175.0 5

KLA_KR Klanawa River 231.8 97.4 121 317 268.7 4

KLA_WK West Klanawa 46.3 42.2 11 93 52.0 3

NIT Nitinat River 311.9 157.3 96 559 396.3 7

SJN San Juan River 320.3 215.7 87 609 444.5 4

WAL Mid and Upper Walbran Valley 393.5 125.7 233 532 378.7 4

Total West Coast Trail 2,125.6 – 939.0 3,449.0 2,592.6 47

B.—Birds likely to be coming from Barkley Sound or Alberni Inlet

CHI China Creek 215.7 227.5 62 477 292.5 3

EFI Effingham River 21.3 20.0 6 44 25.0 3

EFI_British 

Columbia

Brand Creek 29.7 25.1 6 56 31.0 3

FRB Franklin River 35.3 1.0 34 36 36.0 4

HAN Handy Creek 15.5 9.2 9 22 22.0 2

LUC Lucky Creek 292.8 75.0 191 350 311.3 5

MAC Macktush Creek 1.0 1.2 0 2 1.3 4

MAG Maggie River/Draw Creek 13.3 11.6 3 28 16.7 4

NAH Upper Nahmint River 34.0 12.5 26 55 39.3 5

NUM_CC Carnation Creek 54.3 24.5 37 90 65.0 4

PAC Pachena River 140.7 19.6 120 159 151.0 3

PIP_BP Black Peaks 26.5 27.6 7 46 26.5 2

PIP_SL Skull Lake 32.0 0.0 32 32 32.0 2

RIT Ritherdon Creek 25.3 1.5 24 27 25.5 3

SAR Sarita River 180.8 52.8 144 259 208.0 4

SNO Snow Creek 1.3 1.5 0 3 1.5 3

SPE Spencer Creek 65.8 32.4 40 111 78.0 4

TOQ Toquart River 436.9 129.7 272 636 458.3 7

UC_HEN Henderson Lake (Uchucklesit and 

Useless Inlets)

326.7 130.9 167 549 361.3 6

Total Barkley Sound and Alberni 1,948.6 – 1,180.0 2,982.0 2,182.3 71

Overall total 4,074 – 2,119 6,431 4,775 118

Table D3. Radar counts at 30 watersheds on southwest Vancouver Island in 2002–05, grouped by the likely marine source of the 

incoming murrelets. 

[Mean, SD, minimum and maximum pre-sunrise counts of incoming Marbled Murrelets entering watersheds. The mean of each year’s maximum count also is 

shown. Data from A.E. Burger (University of Victoria, unpub. data, 2002–05)]

Appendix D 191
East Vancouver Island.—The 2002 estimate (700–1,000 

birds; table D1) was based on at-sea counts totaling 437 birds 

but covering a small portion of the region (Burger, 2002). 

There are no new at-sea counts, but radar counts were 

undertaken by D. Lindsay (TimberWest, Ltd.; unpub. data, 

2002–04) at nine sites in this region over 3 years (total of 

95 surveys in 2004–06). The sum of the annual mean count 

at these sites was 435 ± 351 birds (SD), and the sum of the 

maximum count at each site was 1,194 birds. A few of the 

birds likely flew from the west coast of the island, but these 

radar counts indicate that the original estimate for this region 

was low because these sites did not cover all the likely flight 

paths. Until more detailed data are available, a more realistic 

population range is 1,000–2,000 birds.

Southern Mainland Coast.—The 2002 estimate (6,000–

7,000 birds; table D1) was based on a combination of at-sea 

counts, radar counts and population estimates based on markrecapture studies in Desolation Sound (Burger, 2002). There 

are no new data with which to update this estimate. Radar 

surveys were repeated in 2006 at some of the sites sampled 

in 2000–01, but these data are not yet available (D. Bertram, 

Canadian Wildlife Service). The 2002 estimate therefore 

remains unchanged.

Central Mainland Coast.—The 2002 estimate (10,000–

21,000 birds; table D1) was based primarily on models that 

combined murrelet densities from radar counts done in 1998 

with Geographic Information System (GIS) measures of likely 

habitat (Schroeder and others, 1999; see also Burger, 2002). 

Other estimates for parts of this coast indicated fewer birds 

(Burger, 2002). Some of the radar sites were resurveyed in 

2006 but the data are not yet available (D. Bertram, Canadian 

Wildlife Service). In the absence of additional information, the 

crude population estimate from 2002 cannot be changed.

Northern Mainland Coast.—The 2002 estimate 

(10,100–14,600 birds; table D1) was based on extrapolations 

from radar counts at 26 watersheds in 2001 using a Habitat 

Suitability Index model (Steventon and Holmes, 2002; see also 

Burger, 2002). There have been very few at-sea counts in this 

area. Radar surveys at some of the 2001 sites were repeated in 

2005 but these data are not available (D. Bertram, Canadian 

Wildlife Service). In the absence of additional information, the 

crude population estimate from 2002 cannot be changed.

Haida Gwaii (Queen Charlotte Islands).—The 2002 

estimate from this archipelago was 8,500-9,500 birds (table 

D1) based on actual counts of 6,063 birds mostly made 10–25 

years previously and covering only part of the coastline 

(Burger, 2002). There are no new at-sea counts covering 

previously uncounted areas.

Information available since 2002 provides conflicting 

evidence of what current populations might be. On the one 

hand, the analysis by Holt (2004) indicated that habitat areas 

have declined by an estimated 42 percent, mostly throughout 

the past 50 years, so that if murrelet numbers tracked habitat 

area as expected (Burger, 2001) then populations should be 

lower than 10–25 years ago. This is supported by the declines 

in numbers seen in the long-term data from Laskeek Bay in 

this region (see appendix E).

Densities (birds per hectare of apparently suitable 

habitat) made from recent radar counts applied to areas of 

habitat estimated from a management algorithm suggest 

that the population might be considerably higher than the 

2002 estimate. Harfenist and Cober (2006) reported mean 

totals of 2,029 birds (sum of the annual mean of pre-sunrise 

incoming birds) or 2,492 birds (sum of annual maximum 

count of incoming or outgoing birds) from radar counts 

made in 2004–05 at 26 watersheds (table D4). It was difficult 

to determine the catchment areas (areas of inland suitable 

nesting habitat) into which these birds were flying. Using 14 

watersheds with the most likely predicted catchment areas, 

Harfenist and Cober (2006) calculated mean densities of 0.157 

± 0.078 (SD) birds per hectare of nesting habitat derived from 

the algorithm used for land-use planning. When applied to 

the total area of this habitat in Haida Gwaii (Queen Charlotte 

Islands), this density predicted a total population of 41,000 

birds. This figure seems unreasonably high, given the numbers 

of birds counted on the water (Burger, 2002) and in the radar 

counts (table D4). Habitat mapping that is now in progress 

(but incomplete) using interpretation of aerial photographs 

suggests that the planning algorithm did not reliably 

predict habitat areas (Harfenist and Cober, 2006; A. Cober, 

Environment Canada, oral commun., 2006). The radar-based 

density derived from this study was 74 percent higher than that 

derived using a similar method on western Vancouver Island 

(0.090 birds per hectare of nesting habitat; Burger and others, 

2004b) where densities of murrelets on the water were higher 

than off Haida Gwaii (Queen Charlotte Islands) (Burger 1995, 

2002). Applying the west Vancouver Island density to the 

estimated habitat area gives an estimated population of 23,500 

birds.

Applying radar densities in Haida Gwaii (Queen 

Charlotte Islands) seems problematic, due in part to the 

topography. The mountain ranges generally are lower than 

on the British Columbia mainland and Vancouver Island, 

making it less likely that murrelets would be constrained to 

remain in the watersheds in which they were seen entering. 

In addition, the relatively narrow land area means that 

murrelets are likely to fly across the islands entirely. Both of 

these factors would lead to an overestimate of densities and 

hence estimated populations. It seems that the radar density 

method is overestimating the Haida Gwaii (Queen Charlotte 

Islands) population but it does suggest that the population is 

indeed larger than that estimated by Burger (2002). Given 

these uncertainties, it seems the most prudent approach 

is to estimate a wide range in the likely population taking 

into account both past and previous estimates. Until further 

192 Status Review of the Marbled Murrelet in Alaska and British Columbia
scattered data points in some studies (Burger and others, 

2004).

In radar studies, murrelet populations are estimated 

as birds, not nests or pairs because birds are what the radar 

detects. The actual breeding status of birds detected by radar 

is not known, but a portion of the birds flying into the forests 

are known to be non-breeders or failed breeders (Peery and 

others, 2004). Because other measures of Marbled Murrelet 

population size (at-sea counts) also record birds of all ages 

and breeding condition, there is compatibility between radar 

counts and at-sea counts.

Areas of likely suitable habitat can be estimated by 

applying algorithms to forest cover, satellite imagery or other 

measures of forest composition using GIS. In the British 

Columbia-wide radar study (Burger and others, 2004), areas of 

likely suitable habitat were estimated using a simple algorithm 

based on the suggestions of the Canadian Marbled Murrelet 

Recovery Team (Bertram and others, 2003; see table 37); 

likely habitat was selected as forest with stand age class 8+ 

(>140 years), tree height class 4+ (>27.5 m), and distance 

from the sea <30 km. This same algorithm also was used to 

estimate the area and distribution of suitable habitat across 

the murrelet’s range in British Columbia (see below and also 

section, “Population Status and Trends”).

By dividing radar counts by the estimated areas of habitat 

within the “catchment areas” into which murrelets counted 

with radar are flying, one can estimate murrelet densities 

(expressed as birds per hectare of suitable habitat). The two 

largest sources of error in making these density calculations 

arise from estimating the extent of the catchment area and in 

estimating the area of suitable habitat within this area. Errors 

in defining catchment areas are less when the murrelets are 

entering well-defined valleys bounded by high mountains 

(Burger, 2001). Many of the radar studies in British Columbia 

were made in such areas, but murrelets are known to cross 

high mountain ridges and some catchment areas were not 

bounded by high mountains. Murrelets may therefore continue 

flying beyond the estimated catchment area (leading to 

overestimates of density) or may enter the catchment areas 

undetected (leading to underestimates of density). Errors in 

estimating likely habitat within the catchment area depend on 

the accuracy of the GIS data used.

Densities derived from the radar counts can be used in 

two ways: to estimate the areas of suitable forest needed to 

support a given population of murrelets; or conversely to 

estimate the number of birds that a given area of habitat is 

likely to support. Here, I apply the second approach to make 

a crude estimation of the possible population likely to be 

supported by the habitat area in British Columbia predicted 

from a simple algorithm (CMMRT) applied to the provincewide forest cover and biogeographic data.

Burger and others (2004) showed that there was a 

consistent statistically significant difference between densities 

on the British Columbia mainland (0.045 ± 0.039 SD birds 

Radar station

Mean pre-sunrise 

count of incoming 

birds

Mean of the 

annual maximum 

count

Number of 

surveys

Bigsby 98.0 130.0 2

Botany 86.8 130.5 4

Dawson Harbour 65.5 66.0 2

Dawson Inlet 95.0 110.0 3

Fairfax 90.3 123.0 3

Gregory 176.0 220.0 4

Harriet Harbour 42.5 43.0 2

Huston 96.8 127.0 4

Hutton 88.3 92.0 3

Jalun Lake 30.0 30.0 1

Kitgoro 47.0 57.0 1

Klunkwoi 48.0 98.0 3

Lagoon 79.0 79.5 2

Long 133.5 146.5 3

Mather’s Lake 10.0 11.0 1

Mitchell 32.8 40.0 4

Mt. Creek 30.0 48.0 2

Port Chanal 193.8 233.5 3

Security 82.3 154.0 3

Shields 36.0 37.0 1

Slatechuck 64.0 66.0 1

South Carmichael 19.0 20.0 1

South Louise 9.0 11.0 1

Tartu 109.3 127.0 3

Trounce 55.5 65.5 3

Windy Bay 210.8 226.5 4

Sum 2,029 2,492 64

Table D4. Summary of radar counts of Marbled Murrelets from 

26 radar stations on Haida Gwaii (Queen Charlotte Islands) in 2004 

and 2005.

[Data from Harfenist and Cober, 2006. Surveys between May 28 and July 16 

were included, and those with rain or technical problems were excluded]

information can refine the estimate, it should be considered to 

be 8,500–25,000 birds.

Population Estimated by Applying RadarDerived Densities

Several studies have shown a significant positive 

correlation between the numbers of murrelets counted with 

radar as they enter watersheds before dawn and the area of 

likely habitat within those watersheds (Burger, 2001; Raphael 

and others, 2002; Bigger and others, 2006). Five studies in 

British Columbia, covering a 101 watersheds (more than 

2 million hectares) showed this trend; linear regressions 

generally fit this relationship well although there were widely 

Appendix D 193
per ha; data from 62 watersheds in three separate studies) and 

the west coast of Vancouver Island (0.090 ± 0.060 SD birds 

per ha; 36 watersheds in two studies). The reasons for these 

differences are not known but might include more favorable 

foraging conditions or nesting habitat on western Vancouver 

Island. A third reason seems to be differences in topography: 

the mainland coast has many long fjords and inlets. Murrelets 

tend to forage at the seaward ends of these and densities are 

lower in apparently suitable habitat accessible from these 

fjords (distance to open sea was a significant covariate with 

murrelet densities in the British Columbia mainland but not 

on Vancouver Island; Burger and others, 2004). The habitat 

mapping study has not released regional totals for likely 

suitable habitat. I was therefore unable to apply the regional 

densities to regional habitat areas, but used the two different 

regional densities instead as indicators of high (Western 

Vancouver Island density) or low (British Columbia Mainland 

density) estimators. The mean density from both regions in 

British Columbia was 0.061 ± 0.052 SD birds per hectare 

(Burger and others, 2004).

Areas of likely suitable habitat in each of the six 

regions in British Columbia have been estimated by the 

British Columbia Ministry of Environment (M. Mather and 

T. Chatwin, unpub. data, 2006) using GIS and applying the 

simple algorithm given above (age >140 years; tree height 

>27.5 m). The mapping is being done for both 0–30 km 

and 0–50 km distances from the ocean. I considered habitat 

<30 km from the coast to be the most likely to be used; 

this also matches the limits set on catchment areas used to 

derive the densities (Burger and others, 2004). The final 

maps and estimates of habitat area from this study are not yet 

available, but preliminary estimates suggest that the habitat 

areas comparable with the radar density estimates total about 

1.6 million ha in British Columbia.

Estimates using these density and habitat area measures 

indicate that the total British Columbia population is in the 

range of 72,000–175,000 birds, with the extremes in this 

range being due to the application of low (British Columbia 

Mainland) and high (western Vancouver Island) densities 

(table D5). Using the mean density for all 98 radar sites, 

the total population is estimated at 97,600 birds (95 percent 

confidence limits (CL): 81,000–114,000). These estimates 

capture some of the uncertainty in the radar density estimates, 

but because the habitat mapping study is not complete, I was 

not able to incorporate effects of variance in habitat estimates. 

These estimates of the total British Columbia population 

therefore remain crude and unreliable.

Total Population in British Columbia

The total British Columbia population of Marbled 

Murrelets based on the most recent information is estimated 

to be in the range of 54,300–92,600 birds (median 73,000 

rounded to the nearest thousand; table D1). This is slightly 

higher than the previous estimate (55,000–78,000 birds; 

median 66,000 birds; table D1; Burger, 2002). It must be 

emphasized that both the current and the previous estimates 

are crude, based on extrapolations from rather sparse 

information in most regions and with large margins for error. 

It also must be emphasized that the slightly higher population 

estimate produced in 2006 does not indicate that the numbers 

of murrelets in British Columbia have risen since the last 

estimate or since the original estimate made by Rodway (1990; 

45,000–50,000 breeding birds or approximately 53,000–

59,000 birds; see Burger, 2002). Rather the higher numbers 

reflect somewhat improved data and greater geographical 

coverage of surveys. All available evidence points to declining 

populations in British Columbia (see appendix E).

Mean Lower CL Upper CL

A.—Murrelet density (birds/ha)1

Density 1: British Columbia 

Mainland watersheds

0.045 0.035 0.055

Density 2: Western Vancouver 

Island watersheds

0.090 0.070 0.110

Density 3: Mean of both areas 0.061 0.051 0.071

B.—Population estimate based on estimate habitat (birds)

Habitat area = 1,600,000 ha2

Density 1 72,000 56,467 87,533

Density 2 144,000 112,640 175,360

Density 3 97,600 81,127 114,073

1

Densities from radar studies summarized by Burger and others (2004).

2

Based on recent updates of the habitat estimates given by DeschesneMansiere (British Columbia Forest Practices Board, unpub. data, 2004)

Table D5. Estimates of the population of Marbled Murrelets in 

British Columbia made by applying radar-derived densities to the 

estimated total area of likely suitable habitat within 30 kilometers 

of the coast.

[The 95-percent confidence limits (CL) were derived from the variance in the 

density.]

194 Status Review of the Marbled Murrelet in Alaska and British Columbia
Population estimates from the central and northern 

mainland and the Haida Gwaii (Queen Charlotte Islands) 

probably are the least reliable. In the two mainland regions, the 

populations were estimated from a single year of radar counts 

extrapolated using correlates with areas of apparently suitable 

habitat. Radar surveys are underway, which will improve our 

knowledge of these populations and their trends (D. Bertram, 

Canadian Wildlife Service). In all three of these regions, 

the numbers of murrelets per 1,000 ha of suitable habitat 

varied considerably among the sampled watersheds, and the 

interpretation of suitable habitat from the GIS data also has 

considerable scope for error. GIS mapping to improved the 

estimates of areas of suitable habitat across British Columbia 

is nearing completion (T. Chatwin and M. Mather, British 

Columbia Ministry of Environment), which will help improve 

population estimates based on the radar densities.

References Cited

Bertram, D.F., Burger, A.E., Chatwin, T.A., Chutter, M.J., 

Guy, S., Cooke, F., Lank, D.B., Deal, J.A., Hay, D.E., Jones, 

T.L., Lindsay, D.J., Manley, I.A., Reader, B., Steventon, 

J.D., Waterhouse, F.L., and Williams, E., 2003, Canadian 

Marbled Murrelet Recovery Team advisory document on 

conservation and management, Part B in Marbled Murrelet 

conservation assessment 2003: Delta, British Columbia, 

CWS, Working Document 1, 31 p.

Bigger, D., Peery, M.Z., Baldwin, J., Chinnici, S., and 

Courtney, S.P., 2006, Power to detect trends in Marbled 

Murrelet populations using audio-visual and radar surveys: 

Journal of Wildlife Management, v. 70, p. 493-504.

Burger, A.E., 1995, Marine distribution, abundance, and 

habitats of Marbled Murrelets in British Columbia, in

Ralph, C.J., Hunt, G.L. Jr., Raphael, M.G., and Piatt, J.F., 

eds., Ecology and conservation of the Marbled Murrelet: 

Albany, California, U.S. Forest Service, Pacific Southwest 

Research Station, General Technical Report 152, 

p. 295-312.

Burger, A.E., 2001, Using radar to estimate populations and 

assess habitat associations of Marbled Murrelets: Journal of 

Wildlife Management, v. 65, no. 4, p. 696-715.

Burger, A.E., 2002, Conservation assessment of Marbled 

Murrelets in British Columbia. Part A: Review of the 

biology, populations, habitat associations, and conservation: 

Delta, British Columbia, CWS, Pacific and Yukon Region, 

Technical Report 387, 194 p.

Burger, A.E., Chatwin, T.A., Cullen, S.A., Holmes, N.P., 

Manley, I.A., Mather, M.H., Schroeder, B.K., Steventon, 

J.D., Duncan, J.E., Arcese, P., and Selak, E., 2004, 

Application of radar surveys in the management of nesting 

habitat of Marbled Murrelets Brachyramphus marmoratus: 

Marine Ornithology, v. 32, no. 1, p. 1-11.

Harfenist, A., and Cober, A., 2006, Baseline radar inventory 

of Marbled Murrelets on Haida Gwaii/Queen Charlotte 

Islands, 2004-2005: Queen Charlotte City, British 

Columbia, Ministry of Environment.

Holt, R.F., 2004, Environmental conditions report for the 

Haida Gwaii/Queen Charlotte Islands land use plan: 

Victoria, British Columbia, Ministry of Sustainable 

Resource Management.

Hull, C.L., Kaiser, G.W., Lougheed, C., Lougheed, L.W., 

Boyd, W.S., and Cooke, F., 2001, Intraspecific variation in 

commuting distance of Marbled Murrelets (Brachyramphus 

marmoratus): Ecological and energetic consequences of 

nesting further inland: Auk, v. 118, no. 4, p. 1036-1046.

Peery, M.Z., Beissinger, S.R., Newman, S.H., Becker, B.H., 

Burkett, E., and Williams, T.D., 2004, Individual and 

temporal variations in inland flight behavior of Marbled 

Murrelets: Implications for population monitoring: Condor, 

v. 106, p. 344-353.

Schroeder, B.K., Mather, M.H., and Chatwin, T.A., 1999, 

Reconnaissance inventory of Marbled Murrelets on the 

central coast of British Columbia 1998: Nanaimo, British 

Columbia, Ministry of Environment, Lands, and Parks, 

108 p.

Raphael, M.G., Evans Mack, D., and Cooper, B.A., 2002, 

Landscape-scale relationships between abundance of 

Marbled Murrelets and distribution of nesting habitat: 

Condor, v. 104, no. 2, p. 331-342.

Steventon, J.D., and Holmes, N.L., 2002, Radar-based 

inventory of Marbled Murrelets (Brachyramphus 

marmoratus), northern mainland coast of British Columbia: 

Smithers, British Columbia, Ministry of Forests, Prince 

Rupert Forest Region.

Whitworth, D.L., Nelson, S.K., Newman, S.H., van Vliet, 

G.B., and Smith, W.P., 2000, Foraging distances of radiomarked Marbled Murrelets from inland areas in southeast 

Alaska: Condor, v. 102, no. 2, p. 452-456.

Appendix D 195
196 Status Review of the Marbled Murrelet in Alaska and British Columbia

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Appendix E. Population Trends of the Marbled Murrelet Evident from At-Sea 

Surveys in British Columbia

By Alan E. Burger1, Bob Hansen2, E. Anne Stewart3, Danielle Bellefleur2, Danielle Edwards2, Harry R. Carter4, 

Shay Howlin5

, and Anthony J. Gaston6

Abstract

This appendix summarizes multi-year trends in counts 

of Marbled Murrelets made at sea in British Columbia during 

the breeding season (late April–mid-July). Data were available 

from six transect routes, which were repeatedly sampled (but 

not in every year) within the period 1979 to 2006, and two 

routes sampled in 1996–2000. Most of the data cover the 

years 1995–2006. Seven of the transects were off southwest 

Vancouver Island (Clayoquot Sound, Barkley Sound, and 

the West Coast Trail) and one was in Laskeek Bay off Haida 

Gwaii (Queen Charlotte Islands). Methods varied somewhat 

among the studies but generally murrelets were counted on 

both sides of a small vessel running at constant speed along 

a fixed route and densities were estimated either using an 

unlimited distance transect (giving densities as birds per 

kilometer) or within 300 meter-wide strip transects (giving 

densities as birds per square kilometer). All six data sets 

with more than 10 years of data show declines in densities 

of Marbled Murrelets and these trends were statistically 

significant at four sites. Annual rates of change ranged 

between -5.8 and -14.6 percent. The two surveys in Clayoquot 

Sound showed significant or near-significant rates of decline 

(-21.3 and -31.2 percent) in 1996–2000. Four of the data 

sets with adequate sampling from 1999 to 2006 showed no 

significant change in densities through these years, indicating 

that the major declines happened prior to 1999. Other 

published sources on murrelet numbers or relative activity in 

British Columbia also indicate declines over the past century 

and particularly in the past 20 years. The causes of population 

declines are not known but are likely to involve a combination 

of loss of nesting habitat due to logging and changes in ocean 

conditions affecting foraging at sea. Mortality from fisheries 

bycatch also might be a factor in some areas.

Introduction

Marbled Murrelets were listed as Threatened in Canada 

on the basis of perceived reductions of nesting habitat in 

British Columbia in the absence of data on population trends. 

Information on population trends is therefore needed in order 

to assess the species status within British Columbia (Bertram 

and others, 2003), but there are no data covering the entire 

British Columbia range with which to assess population 

changes. For much of the province, population estimates are 

sketchy, based on extrapolations from a few at-sea surveys or 

radar counts which do not provide a long time series (Burger, 

2002). Indications of population trends are therefore possible 

only from a few long-term data sets involving at-sea counts 

in relatively small prescribed areas. In this appendix, we 

collate available data from these studies, analyse trends in the 

sampled populations, and review other evidence for population 

change in British Columbia.

On the basis of the power analysis by Arcese and others 

(2005), radar counts have been identified by the Canadian 

Marbled Murrelet Recovery Team (CMMRT) as the most 

reliable method for monitoring population trends in British 

Columbia (Bertram and others, 2003). Several studies show 

that repeated radar counts at fixed stations have high power to 

detect trends in Marbled Murrelet counts (Arcese and others, 

2005; Bigger and others, 2006; Cooper and others, 2006). 

Bi-annually repeated radar surveys are now being undertaken 

in all six Marbled Murrelet conservation regions in British 

Columbia, but repeated counts have not been done for long 

enough to report on trends, and the results of surveys done 

in 2006 to repeat those done in the late 1990s in Clayoquot 

Sound, and parts of the British Columbia mainland are not yet 

available.

The few at-sea surveys that cover 10 or more years 

provide the most reliable insights into population trends. We 

recognize that the available data have severe limitations in 

their geographical scope (five of the sites are close together in 

Barkley Sound and adjacent West Coast Trail and the sixth is 

in Laskeek Bay off Haida Gwaii (Queen Charlotte Islands); 

fig. E1). We also include a re-analysis of previously published 

data from the Tofino and Flores transects done in Clayoquot 

Sound more than 4 years (Mason and others, 2002), which 

help to explain the long-term trends seen in that area (Kelson 

and others, 1995; Burger, 2002). Although there are gaps 

1

Department of Biology, University of Victoria, Victoria, British Columbia.

2

Parks Canada, Pacific Rim National Park Reserve, Ucluelet, British 

Columbia, V0R 3A0, Canada.

3

Bamfield Marine Sciences Centre, Bamfield, British Columbia, V0R 1B0, 

Canada.

4

Carter Biological Consulting, Victoria, British Columbia, V8S 4S8, 

Canada.

5

Western EcoSystems Technology, Inc., Cheyenne, Wyoming.

6

Canadian Wildlife Service, National Wildlife Research Centre, Hull, 

Quebec, K1A 0H3, Canada.

Appendix E 197
Figure E1. Location of sites where at-sea surveys were undertaken in British Columbia.

and inconsistent survey effort in all data sets, sampling effort 

was sufficient to reveal likely trends. Because all eight data 

sets were derived from fixed transect routes, spatial variation 

within study areas is not an issue when analysing long-term 

temporal variations in these data. Portions of these data sets 

have been used to summarize interannual variations in earlier 

reviews (Burger 1995, 2000, 2002; Bellefleur and others, 

2005), but this appendix is the most complete analysis of these 

data.

In addition to analyzing the data from the at-sea transects, 

we also summarize other evidence for population trends in 

British Columbia, which has been previously published.

198 Status Review of the Marbled Murrelet in Alaska and British Columbia
Methods

At-Sea Surveys.—The eight studies reviewed here were 

all established before provincial standards were in place 

for sampling Marbled Murrelets at sea. Nevertheless, all 

conform to these standards with minor deviations. Within 

each data set there were some inconsistencies in boat type, 

observer skills, sea and weather conditions, and other variables 

which confound boat surveys for seabirds, but we found no 

evidence that these variations were systematic and might 

have caused the trends which emerge from the data. We used 

data representative of the breeding season and all surveys fell 

within the period April 24–July 16, which covers the period 

that numbers of murrelets were highest and most consistent 

off Vancouver Island (Burger, 2000, 2001) and Haida Gwaii 

(Queen Charlotte Islands) (Harfenist and Cober, 2006). We 

examined each data set carefully to ensure that there was no 

bias caused by including or excluding data at either extreme in 

this seasonal range.

Laskeek Bay.—Laskeek Bay on the east side of 

Moresby Island in the Haida Gwaii (Queen Charlotte Islands) 

archipelago has been surveyed by boat annually by the 

Laskeek Bay Conservation Society since 1991 (2005 and 

2006 data not yet available), using a protocol established by 

A.J. Gaston of the Canadian Wildlife Service (Gaston, 1996). 

The 53.8-km route covers both nearshore sheltered waters and 

open water between islands. All murrelets on the water on 

either side of the boat were reported and we therefore report 

densities as birds on the water per kilometer.

Trevor Channel.—In 1980, Carter (1984) undertook 

repeated surveys of murrelets within a 23.7-km2 grid in lower 

Trevor Channel, Barkley Sound, which he had previously 

identified as an area with high densities of murrelets. Alan E. 

Burger and E. Anne Stewart censused murrelets in the same 

area between 1992 and 2000. Initially, they used the same grid 

pattern as Carter but in July 1994 switched to a looping 43-km 

long strip-transect route covering the same area in order to 

facilitate habitat analyses and hydroacoustic sampling of prey 

(see Carter, 1984: fig. 15 for the grid map and Burger, 2000 

for the overlapping transect route). For this analysis, Carter 

(1984) provided the raw data for each survey, which were not 

available in his thesis. To accommodate the change in method, 

we analysed total counts of birds (in and out of transect strips) 

made in each survey and hence report numbers of murrelets 

seen on the water within the entire grid area.

Trevor-Beale-Seabird Rocks.—In 1979, Carter (1984) 

did repeated surveys along a 17.2-km L-shaped line transect 

running down the centre of Trevor Channel past Cape Beale, 

then turning to run parallel with the outer coast to Seabird 

Rocks (see Carter, 1984: fig. 6, sectors 1–4 for the route 

map). Part of this transect crosses the area sampled in the 

Trevor Channel grid area. Alan E. Burger and E. Anne Stewart 

sampled a 19.5-km route (slightly different start and turning 

points to Carter) sporadically between 1987 and 2006. Both 

survey teams recorded birds ahead and to both sides of the 

vessel, but Carter (1984) recorded all birds to 750 m while 

Alan E. Burger and E. Anne Stewart recorded murrelets within 

and beyond a 300-m strip (150 m on either side of the vessel). 

To accommodate these different methods, we analyzed all 

birds reported inside or outside the transect strips and hence 

report densities as birds on the water per kilometer.

Broken Group Islands Inner and Outer (BGI Inner and 

BGI Outer).—These data sets come from two non-overlapping 

routes within Barkley Sound (see Bellefleur and others, 2005, 

for maps), which were sampled by trained Parks Canada staff, 

under the supervision of Bob Hansen. Broken Group Islands 

(BGI) Inner (9.2 km) runs through the center of the BGI and 

BGI Outer (14.6 km) runs from the mouth of Ucluelet Harbour 

across Loudon Channel to end at Turtle Island in the Broken 

Group. Both routes were sampled using a 300-m wide strip 

transect (150 m on either side of the boat) from 1995 to 2006, 

but murrelets outside the transect also were recorded. The BGI 

Inner route was previously sampled as an unlimited distance 

line transect in 1991–93. To cover the longest time period, we 

therefore considered all birds seen on the water (in or out of 

the transect strip) in the BGI Inner data set and hence report 

density as birds on the water per kilometer. For BGI Outer, we 

used birds on the water within the transect and report densities 

as birds per square kilometer.

West Coast Trail.—This transect runs parallel to the 

coastline for 64.6 km (vessel approximatley 200 m offshore) 

between Seabird Rocks and Owen Point (map in Burger, 

2000), covering the nearshore area with the highest known 

density of Marbled Murrelets in British Columbia (Burger 

1995, 2002). Surveys were initially done by Alan E. Burger 

working with Parks Canada staff (1994–96) and subsequently 

by the park staff. Birds were counted in a 300-m-wide strip 

(150 m on either side of the vessel) and we report densities as 

birds per square kilometer.

Tofino and Flores transects. —We re-analyzed the data 

from these two transect routes in Clayoquot Sound recorded 

in 1996–2000 and previously published by Mason and others 

(2002; see this reference for maps and details). Both transects 

covered large areas of exposed inshore waters and sheltered 

channel waters in areas of high murrelet densities previously 

identified from grid surveys (Sealy and Carter, 1984; Kelson 

and others, 1995). The Tofino transect (49.8 km), sampled 

annually in 1996–2000, covered exposed waters off the 

Tofino peninsula and both exposed and sheltered waters 

around Vargas Island. The Flores transect (82.1 km), sampled 

annually in 1997–2000, covered exposed and sheltered waters 

around Flores Island and off the Catface Peninsula.

Appendix E 199
Statistical Analysis.—To analyze trends across years, we 

first calculated the annual mean murrelet response (density 

or count) across the replicate surveys for each transect. In 

order to apply linear regression, we log transformed the 

mean value, and because there were no zero values, we did 

a simple transformation using the natural logarithm, i.e. ln 

(mean) (Zar, 1996, p. 279). area. We plotted graphs showing 

the log transformed data on the y-axis, but to make the scale 

more readily understandable, we show the actual densities or 

numbers of birds and not the log values on these axes. The 

variance of the log-transformed annual means was calculated 

using a first order Taylor Series expansion (Seber, 1982). This 

approximation equates to the variance of the annual mean 

divided by the product of the sample size and the square of the 

annual mean. Linear regression of the logged mean response 

was conducted with year as the independent variable and the 

inverse of the variance as the weight. From the regression, 

we derived the slope of the trend in the log-transformed data 

and the amount of variance explained by the regression line 

(R-squared value). The annual rate of change (percent change) 

was then calculated from the slope using the formula: 1-eslope, 

where e is the base of natural logarithms (2.71828). Moran’s 

I was calculated to estimate the autocorrelation of the model 

residuals (Moran, 1948). The model for Trevor Channel 

included an indicator variable for survey method, given as 0 

for grid surveys (during and before 1994) and 1 for looped 

transect surveys (during and after 1995).

Because there was evidence of changing trends before 

and after 1999 (see section, “Results”), we also calculated 

linear regressions of the log-transformed mean responses for 

four survey areas using data after and including 1999. Again, 

year was the independent variable and the inverse of the 

variance was the weight in the model.

Results

Trends in At-Sea Densities—All survey areas had 

negative trends in murrelet counts or densities across years; six 

areas had significant negative trends (table E1). The parameter 

estimate on survey method for the Trevor Channel model 

was not significantly different from zero (P = 0.507). The 

estimate for the indicator variable was 0.235, which represents 

the difference in the predicted means for the looped transect 

surveys, where the grid surveys are the reference level. 

Moran’s I indicated negative serial autocorrelation for the 

West Coast Trail area model. The error estimate for this model 

may be underestimated resulting in decreased confidence in 

the significance of the trend estimate. There was no serial 

autocorrelation indicated in the residuals of the remaining 

models. 

The Laskeek Bay data show a decline in annual mean 

density over the 14-year period 1991–2004 (fig. E2). This 

trend was statistically significant and indicated an annual rate 

of decline of -14.6 percent (table E1).

Off southwest Vancouver Island, both the Trevor Channel 

and the Trevor-Beale-Seabird Rocks data show declining 

trends in the period 1979–2006 (fig. E3) but sampling over 

the years was inconsistent and only the Trevor Channel survey 

was statistically significant (table E1). Similarly the three 

survey routes covered by Parks Canada (Broken Group Inner 

and Outer within Barkley Sound and the West Coast Trail on 

the outer coast) showed declines in 1990–2006 (fig. E4) and 

these trends were significant for the BGI Inner (annual decline 

of -8.3 percent) and West Coast Trail (annual decline -6.1 

percent; table E1).

At-sea surveys using a grid pattern covering most of 

Clayoquot Sound, west Vancouver Island (fig. E1) were 

done in 1982 (Sealy and Carter, 1984) and repeated using the 

same method in 1992, 1993, and 1996 (Kelson and others, 

1995; Kelson and Mather, 1999). This area supports one of 

the highest concentrations of murrelets in British Columbia 

(Burger, 1995, 2002). The grid survey data show declines in 

populations of between 22 and 40 percent since 1982 (fig. E5), 

attributed to the effects of logging (Kelson and others, 1995). 

Closer examination of these data, however, revealed that the 

only significant change occurred in the exposed inshore zone, 

and there was no evidence of change in the protected channels 

(fig. E5; Burger, 2000). Burger (2000) also suggested that the 

changes in the exposed inshore zone might have been linked 

with exceptionally warm ocean conditions in the 1990s, but 

there are insufficient data to statistically separate the effects of 

temperature and years. 

The Flores and Tofino transects in Clayoquot Sound 

offer a much shorter time span to measure trends (4 and 3 

years, respectively in 1996–2000), but both transects sampled 

both exposed inshore waters and sheltered channel waters. 

A significant decline was evident in the Flores data and the 

Tofino trend was close to significant (fig. E6; table E1). The 

annual rates of decline in these years were -21.3 and –31.2 

percent in the Flores and Tofino transects, respectively (table 

E1).

Trends Since 1999 – There are indications that the 

long-term Pacific Decadal Oscillation (PDO) shifted from a 

warm to a more mixed phase in 1999, and large-scale logging 

practices affecting murrelets changed in the mid-1990s. We 

therefore tested for trends in the data for 1999–2006 in the 

four data sets that adequately covered this period (figs. E2

and E4). There were no significant trends in any of the data 

sets (table E2) and none of these data sets showed evidence of 

autocorrelation. Most of the changes in densities in these areas 

therefore occurred prior to 1999. 

200 Status Review of the Marbled Murrelet in Alaska and British Columbia
Figure E2. Mean plus or minus SE linear densities (birds per kilometer of transect) of Marbled Murrelets 

along a 54-km boat transect in Laskeek Bay, Haida Gwaii (Queen Charlotte Islands). (Data from Laskeek Bay 

Conservation Society). Note that the y-axis has a logarithmic scale but the labels are actual densities and not the 

log values. Sample size (number of days surveyed) is shown for each year.

Laskeek Bay - Marbled Murrelets

19901992

199419961998200020022004

2006

Birds per km .

0.4

1.0

2.7

7.4

20.1

3 5

7

4

4

4

3

4

2

3

4

4

5

4

Table E1. Summary of trends of Marbled Murrelet counts and densities at eight marine transect routes in British Columbia.

[Linear regressions were derived from log transformed annual means using annual variance as the regression weighting. Statistically significant trends (P<0.05) 

are shown in bold. Sites are listed from north to south]

Site or transect 

route Region Range of years

Number 

of years 

sampled

Number 

of surveys

Regression of log transformed data

Slope Rate of change 

percent per year R-squared F df P

Laskeek Bay Haida Gwaii (Queen 

Charlotte Islands) 

1992–2004 14 56 -0.158 -14.6 0.394 7.790 1,12 0.016

Flores transect West Vancouver Island 1997–2000 4 15 -0.240 -21.3 0.977 86.030 1,2 0.011

Tofino transect West Vancouver Island 1996–2000 4 19 -0.375 -31.2 0.892 16.580 1,2 0.055

BGI Inner West Vancouver Island 1991–2006 14 65 -0.087 -8.3 0.720 30.850 1,12 0.000

BGI Outer West Vancouver Island 1995–2006 10 41 -0.062 -6.0 0.173 1.670 1,8 0.232

Trevor Channel West Vancouver Island 1980–2000 10 61 -0.060 -5.8 0.585 4.930 1,7 0.046

Trevor/Beale/SBR West Vancouver Island 1979–2005 6 20 -0.097 -9.3 0.482 3.720 1,4 0.126

West Coast Trail West Vancouver Island 1994–2006 10 32 -0.063 -6.1 0.530 9.020 1,8 0.017

Appendix E 201
Figure E3. Mean (plus or minus SE) counts of Marbled Murrelets made in two overlapping census routes 

(Trevor Channel, upper graph; Trevor Channel-Cape Beale-Seabird Rocks, lower graph) in Barkley Sound, 

southwest Vancouver Island, between late April and mid-July. (Updated from Burger, 2000, 2002; Burger and 

Stewart, University of Victoria, unpub. data). Note that the y-axes have logarithmic scales but the labels are 

actual densities and not the log values. The sample size (number of days surveyed) is shown for each year.

Trevor Channel - Marbled Murrelets

197919801981198219831984198519861987

198819891990

199119921993199419951996199719981999

2000

No. of birds on water .

55

90

148

245

403 10

3

5

8

7

4

6

6

6

6

Trevor-Beale-Seabird Rocks transect - Marbled Murrelets

1978198019821984

198619881990

1992199419961998

2000200220042006

Birds per km .

0.01

0.05

0.37

2.72

20.1

7

2

5

2

2 4

1

202 Status Review of the Marbled Murrelet in Alaska and British Columbia
Broken Group Inner Transect - Marbled Murrelets

19901992

199419961998

2000200220042006

Birds per km .

0.37

1.0

2.7

7.4

20.1

10

8

6

3

2 3

4

5

3

4

4 5

4

5

Broken Group Outer Transect - Marbled Murrelets

1994199519961997

1998

1999200020012002

200320042005

2006

Birds per sq. km .

1.0

2.7

7.4

20.1

54.6

2

3

5

4

2

4 5

5

6 5

West Coast Trail Transect - Marbled Murrelets

1993

199419951996

19971998

1999

20002001

200220032004

20052006

Birds per sq. km .

2.7

7.4

20.1

54.6

2

148.4

3 3 1

3

2 3

5

4 5

2

Figure E4. Trends in densities of Marbled Murrelets in three transects surveyed by Parks Canada 

in Barkley Sound (Broken Group Islands Inner, Broken Group Islands Outer) and the West Coast Trail. 

Annual means (plus or minus SE) shown for counts made between April 24 and July 16. Linear density 

(birds per kilometer) is used for the Broken Group Islands Inner transect to cover a wider range of 

years. The y-axes have log scales but labels are actual densities and not log values. Sample size (n

days surveyed) is shown for each year.

Appendix E 203
522 

0

1000

2000

3000

4000

5000

1982

1983198419851986198719881989

19901991

199219931994

19951996

No. of birds

Clayoquot Sound All areas Channels Exposed inshore

Figure E5. Counts of Marbled Murrelets in a grid-survey census in Clayoquot Sound, broken down by habitat 

type. (Data from Sealy and Carter, 1984; Kelson and others, 1995; Kelson and Mather, 1999). See Burger (2002) for 

further details.

Table E2. Summary of regressions testing for trends in counts of Marbled Murrelets in the years 

1999-2006. 

[Linear regressions were applied to log transformed annual means. None of the tests was significant]

Site or transect route Regression of log transformed data

Slope R-squared F df P

Laskeek Bay 0.156 0.175 0.85 1,4 0.409

BGI Inner -0.014 0.008 0.05 1,6 0.833

BGI Outer -0.010 0.004 0.03 1,6 0.879

West Coast Trail 0.037 0.060 0.38 1,6 0.559

204 Status Review of the Marbled Murrelet in Alaska and British Columbia
523 

Tofino transect, Clayoquot Sound

1995 1996 1997 1998 1999 2000

Birds per sq. km .

20.1

12.2

7.4

4.5

2.7

6

7 7

2

3

Flores transect, Clayoquot Sound

1995 1996 1997 1998 1999 2000

Birds per sq. km .

20.1

12.2

7.4

4.5

2.7

4

8

2 3

Figure E6. Mean (plus or minus SE) counts of Marbled Murrelets made in two census routes (Tofino, upper 

graph; Flores, lower graph) in Clayoquot Sound, southwest Vancouver Island, between May 14 and July 13. 

(Updated from Mason and others, 2002). Note that the y-axis has a logarithmic scale but the labels are actual 

densities and not the log values. The sample size (number of days surveyed) is shown for each year.

Appendix E 205
Discussion

Trends within the transect data.—Overall, we found 

declines in densities or counts of Marbled Murrelets in all six 

data sets covering 1979–2006, and the two data sets covering 

much shorter periods 1996–2000. Despite considerable withinand among-year variations in densities, these trends were 

statistically significant in five data sets (table E1). Statistically 

significant trends emerged from the three data sets with the 

most consistent sampling (Laskeek Bay, BGI Inner, and West 

Coast Trail) and we feel the lack of significant trends in three 

data sets might be due to insufficient sample sizes needed 

to overcome the natural variation in these at-sea data. The 

annual rates of decline in these data covering more than 10 

years ranged from -5.8 to -14.6 percent (6.1–14.6 percent in 

the statistically significant data sets; table E1), and was much 

higher in the Flores and Tofino transects covering 1996–2000 

(table E1). These estimated rates of decline are not precise and 

the addition of another year or two of data would undoubtedly 

change the calculated rate. Nevertheless, these are high rates 

of decline for any population and indicate a potentially serious 

problem for the populations that they represent. In the four 

data sets with adequate sampling in recent years, we found no 

significant trends in densities since 1999 suggesting that the 

major changes occurred prior to this year.

Although some of the survey sites (Trevor Channel, 

Trevor-Beale-Seabird Rocks) were chosen as study areas 

because of high densities of murrelets (Carter, 1984), there is 

no evidence that selection of sites with initial high densities 

produced a biased measure of trend. The high densities in 

the Trevor Channel area were well known to local residents 

for many years prior to Carter’s (1984) study and Harry R. 

Carter’s unpublished data shows consistent high densities in 

both 1979 and 1980. Most of the other transects were long 

enough that they encompassed a wide range of habitats and 

murrelet densities (see Gaston, 1996; Mason and others, 2002; 

Bellefleur and others, 2005), reducing the likelihood that high 

counts in early years were spatial anomalies. Furthermore, 

the large spatial coverage of seven transect routes on the 

west coast of Vancouver Island, all of which show declines, 

reduces the likelihood that the trends observed were due to 

local movements. We cannot, however, rule out larger-scale 

emigration to other parts of the murrelet’s range.

Other evidence of change in British Columbia.—Burger 

(2002) reviewed evidence for population trends of murrelets in 

British Columbia and the main points are briefly summarized 

here. Rodway and others (1992) found no clear trends in 

Christmas Bird Count data from 1957 through 1988. This 

analysis has not been expanded to include more recent data, 

because few count areas overlap with significant wintering 

populations in British Columbia and Christmas Bird Count 

data seem to be poor indicators of widespread population 

trends in this species (Piatt, 1998; Hayward and Iverson, 

1998). 

There is anecdotal evidence that populations of Marbled 

Murrelets in the Strait of Georgia declined significantly in 

the early 1900s. Brooks (1926) commented on the scarcity of 

Marbled Murrelets along the east coast of Vancouver Island 

in 1925–26 compared with numbers observed in 1920 and 

earlier. Pearse (1946) reported a decline in numbers around 

Comox between 1917 and 1944, concomitant with the loss 

of large tracts of the surrounding coniferous forests. In more 

recent times, counts of birds along a 6 km stretch of shoreline 

at Boundary Bay, south of Vancouver, between November 

and August showed a decline from an average of 66 Marbled 

Murrelets in 1980–81 to 2 in 1994–95 and no birds in 1996 

and 1997 (Cooke, 1999). Murrelets appear to have disappeared 

from Burrard Inlet near Vancouver since 1990 (G. Kaiser 

quoted by Hull, 1999). 

Burger (2002) analyzed data from audio-visual surveys 

made from 1991 through 1999 at 11 stations within the forest 

nesting habitat in the Carmanah and Walbran watersheds 

adjacent to the West Coast Trail on southwest Vancouver 

Island. A sub-set of the audio-visual detections which indicate 

site occupancy provided indirect measures of relative murrelet 

abundance. Mean frequencies of occupied detections showed 

a significant negative correlation with sea temperature 

(Burger ,2000), but Burger’s (2002) analysis, using analysis 

of covariance (ANCOVA) with sea temperature as a covariant, 

showed a significant negative trend over the 9 years (fig. E7; 

adjusted r2

 = 0.347, P<0.001). Since 1990, there has been no 

logging in the Carmanah valley, but parts of upper Carmanah 

were logged in the late 1980s and logging continued in the 

upper Walbran close to the observation stations. 

Radar counts made during the breeding season at the 

mouth of the Bedwell-Ursus watershed in Clayoquot Sound 

showed a significant decline in 1995–98, which corresponded 

to declines in annual mean detections in audio-visual surveys 

made in same drainage (Burger, 2000). This could not be 

attributed to logging because there had not been any logging in 

that drainage for 40 years. There was a weak non-significant 

negative correlation with local sea temperatures in both the 

radar and audio-visual detections (Burger, 2000). 

Overall, these published data and reviews show a 

consistent pattern of decline in numbers of Marbled Murrelets 

wherever there are reasonable data to test trends in British 

Columbia.

Causes of change.—There are no obvious explanations 

for the declining trends seen in the at-sea surveys made in 

two widely separate regions in British Columbia, and in the 

other data reviewed here. The two most likely causes are the 

impacts of logging causing reductions in nesting habitat and 

unfavorable conditions in the ocean foraging environment. It is 

most probable that both factors contribute to the declines.

206 Status Review of the Marbled Murrelet in Alaska and British Columbia
There have been significant reductions in areas of 

nesting habitat for Marbled Murrelets in many areas of their 

British Columbia range and in particular on Vancouver 

Island and Haida Gwaii (Queen Charlotte Islands) (details 

given elsewhere in this review). Given that there is a strong 

relationship between area of habitat and numbers of murrelets 

entering watersheds (Burger, 2001; Burger and others, 2004), 

loss of habitat is expected to result in population reductions, 

although these might be delayed by many years in these 

long-lived birds. Reduction in nesting habitat prior to 2000 

was estimated to be 46 percent in the Alberni Forest District, 

adjacent to the Barkley Sound and West Coast Trail at-sea 

surveys and the Clayoquot Sound grid surveys (Burger, 2002, 

using data from Demarchi and Button, 2001a, 2001b) and 42 

percent in Haida Gwaii (Queen Charlotte Islands), adjacent 

to the Laskeek Bay survey area (Holt, 2004). Logging was 

particularly intense in the 1970s through to the mid-1990s in 

both of these regions, but was reduced as the new provincial 

Forest Practices Code came into effect in the late 1990s and 

large tracts of suitable habitat were protected (Gwaii Haanas 

National Park Reserve on Haida Gwaii (Queen Charlotte 

Islands); Carmanah-Walbran Park and large parks adjacent 

to Clayoquot Sound on southwestern Vancouver Island). It is 

possible that the trends seen in the six data sets, i.e., declines 

overall but with less change after 1999, could be explained by 

loss of nesting habitat, which was more intense prior to the 

mid-1990s than afterwards. 

Changes in ocean conditions affecting murrelets are 

another possible explanation. Many seabirds in the Pacific 

Northwest respond to changes associated with varying sea 

temperatures, either generated by periodic El Niño (ENSO) 

events (Hodder and Greybill, 1985; Wilson, 1991; Ainley 

and Boekelheide, 1990), or longer-term PDO cycles (Piatt 

and Anderson, 1996; Anderson and Piatt, 1999). Generally 

warm ocean conditions reflect reduced upwelling in nearshore 

waters resulting in reduced productivity. Other alcids are 

known to be negatively impacted by warm ocean conditions in 

British Columbia (Bertram and others, 2000, 2001; Gjerdrum 

and others, 2003). 

Impacts of such ocean and climatic changes are poorly 

known for Marbled Murrelets and it is uncertain whether 

warm ocean conditions have negative, neutral or positive 

effects. In central California, Peery and others (2004) reported 

fewer murrelets flying inland to breeding sites in warm years, 

which was linked with improved adult survival in those 

years (Peery and others, 2006). Burger (2000) reported weak 

negative effects of the warm 1992–93 El Niño events in British 

Columbia, inconsistent correlations between sea temperatures 

and annual averages of at-sea, audio-visual and radar counts, 

but some indications that warm sea temperatures had negative 

effects on these measures. 

Bellefleur and others (2005) compared the densities of 

murrelets within the BGI Inner, BGI Outer, and West Coast 

Trail transects with mean sea surface temperatures recorded 

in spring at Amphitrite Point in Barkley Sound. They found 

no significant correlations in the BGI Outer and West Coast 

Trail data. There was a weak but significant interaction in the 

BGI Inner data, primarily due to high counts in the El Nino 

year of 2002, but when possible effects of sea temperature 

were statistically controlled, the significant long-term decline 

remained significant (details in Bellefleur and others 2005). 

Note that the temperature effect here was the opposite of what 

is expected with seabirds: numbers were higher in BGI Inner 

some warm years. The prolonged warm conditions in 1993, 524 

0

0.5

1

1.5

2

2.5

3

3.5

1990 1992 1994 1996 1998 2000 Years

Occupied detections 

(log transformed)

Mean occupied detections 

Figure E7. Trends in occupied detections of Marbled Murrelets in Carmanah-Walbran. Each point 

represents the mean frequency of occupied detections from three or more surveys at each station per year. 

The trend line was determined from ANCOVA analysis, with local sea temperatures as a covariate (see 

Burger, 2002).

Appendix E 207
however, coincided with exceedingly low densities in Barkley 

Sound (see figs. E3 and E4; also Burger, 2000). Conversely, 

the densities at Laskeek Bay were the highest recorded in 

1993. Clearly there is no simple relationship between murrelet 

densities and local sea temperatures, and ocean conditions 

directly associated with sea temperatures do not explain the 

long-term trends in these data. Cooper and others (2006) 

examined the effects of oceanic and climatic factors on radar 

counts of murrelets on the Olympic Peninsula, Washington 

in 1996–2004. They found no significant effects of sea 

surface temperature, Northern Oscillation Index (a measure of 

upwelling strength) or the 1998 El Niño, and suggested that 

oceanic effects off northern Washington might have less severe 

impacts on murrelets and other seabirds than in the upwelling 

systems off California.

In 1999, there was evidence of a weak regime shift in 

the broad-scale ocean conditions in the eastern North Pacific 

associated with the PDO (Bond and others, 2003; Curchitser 

and others, 2005). Off British Columbia, ocean temperatures 

tended to be cooler than in the previous 1977–99 period 

(Department of Fisheries and Oceans: satellite and lighthouse 

temperature data at http://www-sci.pac.dfo-mpo.gc.ca/osap/

data/default_e.htm) and breeding success improved for 

some seabirds (Gjerdrum and others, 2004). This large-scale 

shift coincided with the change in density trends reported in 

four of our murrelet data sets, which showed no significant 

declines in 1999–2006 (table E2). Interestingly, this was 

seen in data from both southwestern Vancouver Island and 

Laskeek Bay even though these fall into different oceanic 

zones. Southwest Vancouver Island is within the Coastal 

Upwelling Domain influenced by the California Current and 

wind-driven summer upwelling, whereas Laskeek Bay is in 

the Transition Zone separating the upwelling domain from 

the Coastal Downwelling Domain of Southeast Alaska (Ware 

and McFarlane, 1989). There are hints therefore that the large 

scale changes in ocean conditions experienced across the 

eastern North Pacific might be influencing Marbled Murrelets 

in British Columbia, although we are a long way from 

understanding and explaining these possible links. 

Marbled Murrelets are known to be killed as bycatch in 

gillnet and sports fishing (Carter and Kuletz 1995). Carter and 

Sealy (1984) reported significant mortality caused by gillnet 

fishing in Barkley Sound in the 1980s, but this fishery has 

been greatly curtailed since then (Smith and Morgan 2005). 

In the 1980s and early 1990s, the Barkley Sound salmon 

gillnet fishery had an active fleet of 300 to 400 vessels, each 

fishing 2-3 days per week, and 24 hours a day between late 

June and early August (when murrelet numbers were highest 

in Barkley Sound). This effort decreased greatly after the 

mid-1990s, with a reduction in the number of vessels, daylight 

fishing only and single-day openings in July and August. 

Sports fishing has, however, greatly increased in the Barkley 

Sound and West Coast Trail waters and small boats are known 

to disrupt feeding of Marbled Murrelets there (Hentze 2006, 

Bellefleur and others in prep.). Murrelets might therefore still 

be negatively impacted by human fishing activities in these 

waters but in a different manner. Gillnet fishing has not been 

identified as a problem for Marbled Murrelets off Haida Gwaii 

(Queen Charlotte Islands) (Smith and Morgan, 2005), although 

gillnetting and collisions with fishing vessels were known 

to impact Ancient Murrelets Synthliboramphus antiquus in 

these waters in the 1950s–1970s (Bertram, 1995; Vermeer and 

Sealy, 1984). 

We cannot rule out a role of fisheries bycatch in the 

declining trends of Marbled Murrelets some areas of British 

Columbia given the paucity of data available, but the available 

evidence suggests that these impacts could not explain the 

consistent declining trends seen in many areas of British 

Columbia. A new study is underway to elucidate possible 

impacts of fisheries on this species (D. Bertram and K. 

Charleton, Canadian Wildlife Service). 

Conclusions

It is striking that nearly all of the quantitative or 

anecdotal evidence for population trend of Marbled Murrelets 

in British Columbia consistently indicates a decline. The 

multi-year series of data that we analysed from six transect 

sources in two widely separated regions show quite startling 

rates of declines, which were statistically significant in those 

data sets with the largest and most consistent sampling. We 

are frustrated in trying to interpret and explain these trends by 

the paucity of comparable data from other regions in British 

Columbia and the lack of information of factors that affect the 

distribution and densities of murrelets at sea. Nevertheless we 

believe that our data and the other evidence that we reviewed 

are symptoms of widespread and biologically significant 

adverse conditions experienced by murrelets in this province. 

Loss of nesting habitat caused by logging and unfavorable 

foraging conditions in the ocean remain the two most likely 

explanations for the changes. It is heartening to note that there 

is evidence that declines seem to have leveled off since 1999, 

but until we understand the underlying causes of population 

changes in this species there is no room for complacency.

Acknowledgments

We thank the many volunteers, students at Bamfield 

Marine Sciences Centre and University of Victoria, and 

staff of Parks Canada, Laskeek Bay Conservation Society, 

Canadian Wildlife Service who contributed hundreds of 

hours in collecting these data. At-sea surveys were funded 

by Parks Canada, Canadian Wildlife Service, Laskeek Bay 

Conservation Society, and grants to AEB from NSERC 

Canada, the Nestucca Trust Fund, British Columbia Forest 

Science Program, and Endangered Species Recovery Fund 

(World Wildlife Fund Canada and CWS). 

208 Status Review of the Marbled Murrelet in Alaska and British Columbia
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Ainley, D.G., and Boekelheide, R.J., 1990, Seabirds of the 

Farallon Islands: Ecology, dynamics, and structure of 

an upwelling-system community: California, Stanford 

University Press.

Arcese, P., Bertram, B., Burger, A.E., Cullen, S.A., Deal, J.A., 

Gibbs, J., Fall, A., Harfenist, A., Harper, W.L., Jones, G., 

Lank, D.B., Lindsay, D.J., Manley, I.A., Selak, E., Runyan, 

S., Schroeder, B.K., Staudhamer, C., Steventon, J.D., and 

Sutherland, G.D., 2005, Monitoring designs to detect 

population declines and identify their causes in the Marbled 

Murrelet: Vancouver, University of British Columbia, 

Centre for Applied Conservation Research, Report to 

Ministry of Water, Land, and Air Protection.

Bertram, D.F., Jones, I.L., Cooch, E.C., Knechtel, H.A., and 

Cooke, F., 2000, Survival rates of Cassin’s and Rhinoceros 

auklets at Triangle Island, British Columbia: Condor, v. 102, 

p. 155-162.

Bertram, D.F., Mackas, D.L., and McKinnell, S.M., 2001, 

Seasonal cycle revisited: Interannual variation and 

ecosystem consequences: Progress in Oceanography, v. 49, 

p. 283-307.

Bellefleur, D., Edwards, D., Hansen, B., and Burger, A.E., 

2005, Marine distribution and abundance of Marbled 

Murrelets in Pacific Rim National Park Reserve of Canada, 

1995-2004: Ucluelet, British Columbia, Parks Canada, 

Pacific Rim National Park Reserve.

Bertram, D.F., Burger, A.E., Chatwin, T.A., Chutter, M.J., 

Guy, S., Cooke, F., Lank, D.B., Deal, J.A., Hay, D.E., Jones, 

T.L., Lindsay, D.J., Manley, I.A., Reader, B., Steventon, 

J.D., Waterhouse, F.L., and Williams, E., 2003, Canadian 

Marbled Murrelet Recovery Team advisory document on 

conservation and management, Part B in Marbled Murrelet 

conservation assessment 2003: Delta, British Columbia, 

CWS, Working Document 1, 31 p.

Bigger, D., Peery, M.Z., Baldwin, J., Chinnici, S., and 

Courtney, S.P., 2006, Power to detect trends in Marbled 

Murrelet populations using audio-visual and radar surveys: 

Journal of Wildlife Management, v. 70, p. 493-504.

Brooks, A., 1926, Scarcity of the Marbled Murrelet: Murrelet, 

v. 7, p. 39.

Burger, A.E., 1995, Marine distribution, abundance, and 

habitats of Marbled Murrelets in British Columbia, in

Ralph, C.J., Hunt, G.L. Jr., Raphael, M.G., and Piatt, J.F., 

eds., Ecology and conservation of the Marbled Murrelet: 

Albany, California, U.S. Forest Service, Pacific Southwest 

Research Station, General Technical Report 152, 

p. 295-312.

Burger, A.E., 2000, Bird in hot water: Responses by Marbled 

Murrelets to variable ocean temperatures off southwestern 

Vancouver Island, in Darling, L.M., ed., Biology and 

Management of Species and Habitats at Risk Conference, 

Kamloops, British Columbia, 1999, v. 2, p. 723-732.

Burger, A.E., 2001, Using radar to estimate populations and 

assess habitat associations of Marbled Murrelets: Journal of 

Wildlife Management, v. 65, no. 4, p. 696-715.

Burger, A.E., 2002, Conservation assessment of Marbled 

Murrelets in British Columbia. Part A: Review of the 

biology, populations, habitat associations, and conservation: 

Delta, British Columbia, CWS, Pacific and Yukon Region, 

Technical Report 387, 194 p.

Carter, H.R., 1984, At-sea biology of the Marbled Murrelet 

(Brachyramphus marmoratus) in Barkley Sound, British 

Columbia, Thesis: Winnipeg, University of Manitoba.

Cooke, F., 1999, Population studies of Marbled Murrelets 

(Brachyramphus marmoratus) in British Columbia, in

Nettleship, A.W., and Diamond, D.N., eds., Biology and 

conservation of forest birds [Proceedings], Fredericton, New 

Brunswick, 1999, Special Publication 1, p. 43-51.

Cooper, B.A., Raphael, M.G., and Peery, M.Z., 2006, Trends 

in radar-based counts of Marbled Murrelets on the Olympic 

Peninsula, Washington, 1996-2004: Condor, v. 108, 

p. 936-947.

Gaston, A.J., 1996, Seabird distributions in Laskeek Bay, 

in Gaston, A.J., ed., Laskeek Bay Conservation Society: 

Queen Charlotte City, British Columbia, Annual Scientific 

Report, 1995, p. 2-28.

Kelson, J.D., Manley, I.A., and Carter, H.R., 1995, Decline 

of the Marbled Murrelet in Clayoquot Sound, British 

Columbia: 1982-1993: Northwestern Naturalist, v. 76, no. 1, 

p. 90-98.

Harfenist, A., and Cober, A., 2006, Baseline radar inventory 

of Marbled Murrelets on Haida Gwaii/Queen Charlotte 

Islands, 2004-2005: Queen Charlotte City, British 

Columbia, Ministry of Environment.

Mason, A., Burger, A.E., and Hansen, B., 2002, At-sea surveys 

of Marbled Murrelets in Clayoquot Sound, 1996-2000, in

Burger, A.E. and Chatwin, T.A., eds., Multi-scale studies 

of populations, distribution and habitat associations of 

Marbled Murrelets in Clayoquot Sound, British Columbia: 

Victoria, British Columbia, Ministry of Water, Land and Air 

Protection, p. 15-33.

Appendix E 209
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210 Status Review of the Marbled Murrelet in Alaska and British Columbia
Appendix F. Comparison of Two Large-Scale Surveys for Brachyramphus

Murrelets in Southeast Alaska

By John Piatt1, Gary Drew1, Mayumi Arimistu1, Shay Howlin2, and Lyman McDonald2

1

U.S. Geological Survey.

2

WEST, Inc., Cheyenne, Wyoming.

Southeast Alaska hosts the largest concentration of 

Marbled Murrelets (Brachyramphus marmoratus) found 

anywhere throughout their range from California to the Bering 

Sea (Piatt and Naslund, 1995; Nelson, 1997). A regional-scale 

survey of Southeast Alaska in 1994 suggested that between 

486,000 and 888,000 Brachyramphus murrelets resided in 

Southeast Alaska during summer (Agler and others, 1998). 

This survey has not been repeated, and we do not know the 

size of the present-day murrelet population in Southeast 

Alaska. However, between 1997 and 2001, the U.S. Fish 

and Wildlife Service conducted aerial surveys of the entire 

shoreline of Southeast Alaska, and conducted small boat 

surveys over about 16 percent of the shoreline to provide 

correction factors for numbers of birds observed on aerial 

surveys. We compiled and analyzed the boat-based survey 

data and compared them with the previous area-wide survey 

conducted by Agler and others (1998). These data suggest 

a decline in murrelet populations during the short period 

between surveys. Estimated populations diminished by 

approximately 45 percent during a period of 7 years and at an 

approximate overall rate of -11.5 percent per year. Owing to 

differences in timing and methodology between surveys, these 

estimated changes should be considered tentative and part of 

the overall assessment of populations in Southeast Alaska.

Methods

Agler Survey Methods.—Agler and others (1998) used 

small boats to survey murrelets throughout Southeast Alaska. 

These methods have been widely used and reported in detail 

elsewhere (e.g., Klowieski and Laing, 1994; Agler and 

others, 1998, 1999; Irons and others, 2000). In summary, 631 

randomly selected transects (fig. F1) were surveyed between 

June 9 and July 27, 1994. The study area was divided into 

two strata: (1) coastal (all waters <200 m from shore), and 

(2) offshore (all waters >200 m from shore). Potential transects 

were created by using Geographic Information System (GIS) 

to overlay a grid of 1.9 km (1 nmi) square blocks over the 

entire southeast area, and selecting at random from those that 

had no land closer than 200 m from shore (offshore block) 

and those that did (coastal block). Transects in offshore blocks 

simply cut straight through blocks and averaged 1.7 km in 

length. Coastal transects followed any shoreline falling within 

the block and averaged 3.9 km in length. In all surveys, 

observers surveyed a sampling window 100 m on either side 

and ahead of the boat. All flying birds and birds on the water 

were recorded continuously and binoculars were used to 

aid in identification of species. Because of the difficulty in 

distinguishing Marbled from Kittlitz’s Murrelet, most birds 

were recorded simply as Brachyramphus murrelets.

We obtained the original data from this survey from the 

U.S. Fish and Wildlife Service (Migratory Bird Management, 

Anchorage). Given the importance of this area-wide survey, 

we also located the original field data sheets containing raw 

data and we verified that the computer files were accurate 

with respect to murrelet observations. We found a few minor 

discrepancies, and we adjusted the number of murrelets 

observed on four transects. The total number of murrelets 

observed was adjusted to 5,702 from 5,714 reported in Agler 

and others (1998). No adjustments were necessary for the 631 

transect distances or calculated areas. We used this data set for 

all statistical comparisons with Hodges data (see below).

Hodges Survey Methods.—A complete aerial survey 

of the shoreline and boat sample survey of the shoreline was 

conducted for marine birds in Southeast Alaska during the 

summers of 1997–2001 (Jack Hodges and Debbie Groves, 

U.S. Fish and Wildlife Serfice, Migratory Bird Management, 

Juneau Field Office, unpub. data, 1997–2001). The primary 

aerial survey was conducted using fixed wing aircraft and 

standardized methods for aerial surveys in Alaska (e.g., 

Conant and others, 1988). The plane was flown parallel to all 

shores and birds were counted in a 400-m strip from the beach 

outward. The survey was conducted over a 5-year period 

in which successive blocks of shoreline were sequentially 

flown until the entire study area was completely covered. 

Surveys were conducted during the last week of July or the 

first 2 weeks of August. Aerial surveys are known to have 

measurement bias with respect to identification of species 

and counting of numbers (Briggs and others, 1985). Owing to 

their relatively small size and drab plumage, murrelets are not 

always detected under poor viewing conditions (e.g., glare, 

white-caps) on aerial surveys (Piatt and others, 1991; Varojean 

and Williams, 1995; Nysewander and others, 2005). Therefore, 

counts of murrelets obtained on the Southeast Alaska aerial 

survey were not considered reliable for evaluating murrelet 

distribution or estimating population size of murrelets. The 

aerial survey data are not considered further in this report.

However, subareas of Southeast Alaska shoreline were 

also surveyed by boat in order to obtain visibility correction 

ratios for the aerial survey data. Areas were subjectively 

selected (fig. F2) to be logistically practical and representative 

of all habitat types. Boat surveys were conducted over a 5-year 

period, with similar effort (table F1) in each of 4 of those 

Appendix F 211
Figure F1. Survey of Southeast Alaska conducted by Agler and others (1998) in 1994. The survey 

comprised 631 randomly selected transects in coastal and pelagic waters.

212 Status Review of the Marbled Murrelet in Alaska and British Columbia

Table F1. Details of effort on Agler and Hodges surveys and a comparison of population size estimated from those surveys.

Comparison Survey Sampling area

Transect effort Number 

of birds

Density 

(No./km2

)

Total 

area

Population 

estimate

95 percent 

confidence limit Prob.

A = H

Percent 

change per 

n annum Area 

(km2

) Lower Upper

All SE Alaska Agler, 1994 Coastal, Offshore 631 297 5,702 19.22 35,468 681,741 485,678 877,804

Hodges, 

1997–2001

Coastal 1,704 748 7,795 10.42 35,468 369,708 284,333 500,370 p<0.01 -11.5

Agler, 1994 Coastal 191 150 2,799 18.66 4,690 87,498 65,403 109,593

Hodges, 

1997–2001

Coastal 1,704 748 7,795 10.42 4,690 48,887 37,598 66,165 p<0.10 -11.0
Figure F2. Location of coastal small-boat surveys for marine birds in Southeast Alaska 

conducted by U.S. Fish and Wildlife Service (J. Hodges and others) during four years (1997, 

1998, 1999, 2001). Colored polygons indicate what year surveys were conducted, and the red 

lines indicate the survey tracks.

Appendix F 213

years (1997: 1,015 km; 1998: 743 km; 1999: 705 km; 2001: 

894 km). Effort was distributed over a different geographic 

range of Southeast Alaska in each year (fig. F2). On boat 

surveys, two observers with binoculars rode in stable skiffs 

with outboard motors. Skiffs were driven about 100 m from 

shore and all birds observed between the boat and shore were 

counted. On the offshore side of the boat, birds were surveyed 

out to 300 m. All marine birds flying or on the water within 

the transect zone were identified and counted on boat surveys. 

Laptop computers, housed in protected cases, allowed Global 

Positioning System (GPS) locations to be tagged with each 

observation. Because the purpose of the boat surveys was to 

provide a correction factor for aerial surveys, the vessel was 

slowed or stopped when necessary in order to count flocks or 

identify species. The evasive behavior of birds ahead of the 

boat was carefully monitored and the path of the skiff adjusted 

to help prevent roll up of flocks ahead of the skiff that might 

have resulted in double counting.
The skiffs were driven in a similar fashion as the airplane 

track, that is, distance from shore was optimized to best 

census coastal birds such as harlequin ducks (Histrionicus 

histrionicus), mergansers and gulls. Murrelets can be observed 

as much as 1 km from shore under optimum conditions 

(Speckman and others, 2000). In field trials, observers 

traveling in small skiffs detected 60–80 percent of murrelets 

at distances of as much as 200 m even when the water 

surface was choppy (Mack and others, 2002). However, we 

assume that under average conditions, counts of murrelets 

beyond 100 m from the boat were biased low because some 

individuals were not detected (Ralph and Miller, 1995; 

Strong and others, 1995), but most murrelets as much as 

100 m distance were detected—which is why this distance 

is frequently used as a truncation distance on line transects 

for murrelets (Bentivoglio and others, 2002). Therefore, to 

be conservative in comparisons to the Agler data, and to 

keep these transect tracks comparable to others conducted 

by USFWS, we assume an effective transect width of 200 m 

(100 m either side of boat) for Marbled Murrelets and we use 

this distance in all calculations of density. Correspondingly, 

all density and population estimates from Hodges’ shoreline 

survey probably are biased upwards because the counts 

included individuals detected at greater than 100 m. These 

surveys were never intended to collect population assessment 

data for Marbled Murrelets and observers are not confident 

that they observed all murrelets on boat-based surveys (J. 

Hodges, U.S. Fish and Wildlife Service, oral commun., 2006). 

We compared estimates of murrelet densities with those of 

other seabird species observed on both Agler and Hodges 

surveys to get some idea of the magnitude of errors arising 

from the use of different methods among surveys.

 All of Hodge’s boat surveys were conducted between 

August 1–13 over all years (1997–2001), and this constitutes 

another source of error in the data. Bird numbers observed in 

early August tend to be elevated by ca. 20–40 percent relative 

to counts earlier in the season (DeGange, 1996; Speckman 

and others, 2000; Kuletz, 2005). This corresponds to the 

late chick-rearing and fledging period when foraging adults 

are highly mobile (Whitworth and others, 2000), and large 

numbers of failed breeders and subadults contribute to the 

size of local populations in the surveyed area (Speckman 

and others, 2000). For these reasons, we assume that counts 

of murrelets on the 1997–2001 boat-based shoreline surveys 

would be biased high relative to counts conducted in June and 

July (Speckman and others, 2000), and hence conservative 

when compared to the Agler surveys that were conducted 

during June and July 1994. No adjustments were made for this 

potential source of error.

Data Analysis.–Agler data were collected in 631 

randomly placed transects. Hodges data were collected over 

stretches of continuous shoreline. In order to compare data 

sets at similar spatial scales of analysis, we used the same 

1 nmi (1.9 km) square grid overlay used by USFWS to create 

and select the original Agler transects (see above) and binned 

the Hodges survey track into 1,704 coastal transects with 

an average length of 4.4 km (fig. F2). Agler estimated the 

mean and variance of population size in Southeast Alaska 

using a ratio estimator (Cochran, 1977) applied to the two 

strata; coastal and offshore (Agler and others, 1998). Because 

the Hodges transects were not randomly selected and were 

continuous with potential autocorrelation among adjacent 

transects, we used a bootstrap procedure to estimate the 

variance and confidence intervals on density for each survey 

data set. The population density was estimated from the 

ratio of total birds observed on all transects to the total area 

surveyed on all transects (Cochran, 1977). The total population 

size of Southeast Alaska was estimated by extrapolation from 

the estimate of density to the total area of Southeast Alaska

(table F1). The bootstrap procedure resampled the original 

transects with replacement, assuming the variance in the 

sample was equivalent to the variance of the universe of all 

possible transects in the area of interest (Manly, 1997). The 

ratio estimator of density (total murrelets observed to total 

area surveyed) was calculated for each resampled dataset. 

These steps were repeated 2,000 times. The mean, standard 

deviation, variance, and percentile confidence intervals 

were calculated for the 2,000 bootstrapped ratios. Potential 

mathematical bias was calculated for each survey as the 

difference between the bootstrap mean and the observed ratio 

of totals. Density estimates are reported as the ratio estimator 

of density, because mathematical bias was insignificant, being 

less than 0.6 percent in all comparisons.

Agler conducted surveys in both coastal and offshore 

waters, and Hodges surveyed coastal waters only (figs. F1

and F2). First, we considered whether comparisons of these 

surveys would be biased by the unequal spatial distribution 

of transects among studies. Although offshore densities (19.8 

birds/km2) were slightly higher than coastal densities (18.7 

birds/km2 0.196, p>0.25, df = 395 using Welch’s correction for 

unequal variance; Zar, 1999). We observed a similar tendency 

for murrelet densities to be about 20 percent higher in offshore 

waters of Glacier Bay, but densities did not vary consistently 

among 6 years of study (J. Piatt, U.S.Geological Survey, 

unpub. data, 1991–2003). Therefore, in contrast to the methods 

and results reported by Agler and others (1998), we combined 

transects from the coastal and offshore strata and calculated 

a single ratio estimate of density. The fact that our estimate 

differs by less than 0.8 percent from Agler’s indicates in itself 

how evenly distributed murrelets were in both habitats.

We have observed that murrelets move rapidly between 

offshore and coastal habitats over daily, weekly and monthly 

time scales (Romano and others, 2004), but data collected 

over many weeks (Agler) and years (Hodges) should reflect 

average use of both habitats. There is evidence, however, that 

murrelets in some areas move away from coastal habitats 

and toward offshore habitats in August (Matt Kirchhoff, 

Alaska Department of Fish and Game. oral commun., 2006). 

214 Status Review of the Marbled Murrelet in Alaska and British Columbia
Therefore we also compared Agler’s subset of coastal transects 

with Hodges coastal-only dataset. Differences between studies 

in the density of murrelets were tested using a 2-tailed t-test with 

Welch’s correction for unequal variance (Zar, 1999). Because 

Hodges data were collected over 4 years (1997, 1998, 1999, 

2001), we compared Agler data to the entire 4-year dataset of 

Hodges as a group, and estimate trend by assuming a year midpoint of 1999 for the Hodges data.

Results and Conclusions

These data indicate that a sharp decline in murrelet 

populations occurred during the short period between surveys. 

Comparing the region-wide data of Agler and Hodges (table F1), 

and using all of Agler’s survey data (coastal and offshore 

transects), and conservative estimates for 1997–2001, we found 

a significant decline (t=2.71, corrected df=1,060, p<0.01) in the 

population between 1994 and the 1997–2001 sampling period. 

This comparison indicates that the population diminished by 

approximately 46 percent. If we use 1999 as a mid-point for date 

of the later surveys, the change occurred at an estimated rate 

of about -11.5 percent per year (table F1). If we compare only 

Agler’s coastal transects to those of Hodges, we observe about 

the same decline (44 percent) and about the same rate (-11.0 

percent per year) of decline (t=1.70, corrected df=239, p<0.10).

We have concerns that differences in the purpose, methods, 

and timing of each survey could affect the outcome of the survey 

comparison. One way to cross-check these results is to examine 

other species of seabirds observed on both surveys, and contrast 

changes in their estimated numbers with those of murrelets. 

Results suggest that the density of all other seabirds remained 

similar or increased markedly between the Agler and Hodges 

surveys (table F2). The “increase” in density of some species may 

be due to the conservative assumption of a 200-m transect 

width on Hodge’s survey, or to the inherent variability in 

temporal-spatial abundance of some species that tend to 

aggregate (e.g., kittiwakes, gulls, murres, and puffins), or 

because populations actually increased. Perhaps the best 

species to compare with murrelets is the pigeon guillemot, 

a widely distributed, dispersed and coastal relative of 

the murrelet. Data indicated almost no change in pigeon 

guillemot densities and murrelet densities decreased by 44 

percent. This comparison eliminates some concerns about 

the comparability of methods, but does not resolve the 

issue of timing.

In summary, the weight of evidence supports a 

conclusion that murrelet populations have declined 

markedly in Southeast Alaska. The comparison of 

Agler and Hodges data suffers from at least three major 

sources of potential bias (timing of surveys, effective 

transect width, and location of transects), but on average 

these biases should lead to a conservative comparison. 

Conclusions based on the Agler-Hodges data should 

be considered tentatively, and results should be viewed 

more as a corroboration of trends suggested by better 

and completely independent data sets in Icy Strait (-12.7 

percent per year) and Glacier Bay (-11.7 percent per year) 

(see appendixes G and H for details). The Agler-Hodges 

comparison provides compelling evidence that the changes 

observed in Glacier Bay and Icy Strait were not restricted 

to this area, but were in fact observed widely in Southeast 

Alaska.

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Appendix F 215

Table F2. Comparison of estimated seabird densities on 

shoreline surveys conducted in SE Alaska by Agler (1994) and 

Hodges (1997–2001).

Taxa

Density (birds/km2) Direction of 

change Agler Hodges

Arctic Tern 0.41 0.37 Down

Kittiwake 0.73 12.34 Up

Bonaparte’s Gull 7.17 10.18 Up

Common Loon 0.13 0.18 Up

Common Murre 0.13 2.42 Up

Cormorant (spp) 0.36 3.39 Up

Larus gulls (spp) 3.03 18.03 Up

Mew Gull 5.67 47.40 Up

Murrelet 18.70 10.42 Down

Pacific Loon 0.02 0.07 Up

Pigeon Guillemot 1.79 1.88 Up

Rhinoceros Auklet 0.68 4.15 Up

Red-throated Loon 0.05 0.08 Up

Tufted Puffin 0.05 0.25 Up
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Romano, M.D., Arimitsu, M.L., Piatt, J.F., Agness, A.A., 

and Drew, G.S., 2004, At-sea density and distribution of 

Kittlitz’s Murrelets (Brachyramphus brevirostris) and 

Marbled Murrelets (Brachyramphus marmoratus) in Glacier 

Bay, Alaska, Summer 2003: Anchorage, U.S. Geological 

Survey Alaska Science Center, Annual Report to U.S. 

National Park Service, Glacier Bay National Park and 

Preserve.

Speckman, S.G., Springer, A.M., Piatt, J.F., and Thomas, 

D.L., 2000, Temporal variability in abundance of Marbled 

Murrelets at sea in southeast Alaska: Waterbirds, v. 23, 

no. 3, p. 364-377.

Strong, C.S., Keitt, B.S., McIver, W.R., Palmer, C.J., and 

Gaffney, I., 1995, Distribution and population estimates of 

Marbled Murrelets at sea in Oregon during the summers 

of 1992 and 1993, in Ralph, C.J., Hunt, G.L. Jr., Raphael, 

M.G., and Piatt, J.F., eds., Ecology and conservation of the 

Marbled Murrelet: Albany, California, U.S. Forest Service, 

Pacific Southwest Research Station, General Technical 

Report 152, p. 339-352.

Varoujean, D.H. II, and Williams, W.A., 1995, Abundance 

and distribution of Marbled Murrelets in Oregon and 

Washington based on aerial surveys, in Ralph, C.J., Hunt, 

G.L. Jr., Raphael, M.G., and Piatt, J.F., eds., Ecology and 

conservation of the Marbled Murrelet: Albany, California, 

U.S. Forest Service, Pacific Southwest Research Station, 

General Technical Report 152, p. 327-338.

Whitworth, D.L., Nelson, S.K., Newman, S.H., van Vliet, 

G.B., and Smith, W.P., 2000, Foraging distances of radiomarked Marbled Murrelets from inland areas in southeast 

Alaska: Condor, v. 102, no. 2, p. 452-456.

Zar, J.H., 1996, Biostatistical analysis: Upper Saddle River, 

New Jersey, Prentice Hall, ed. 3.

216 Status Review of the Marbled Murrelet in Alaska and British Columbia
Appendix G. Population Trend of the Marbled Murrelet in Icy Strait, Southeast 

Alaska

By John Piatt1, Gary Drew1, John Lindell2, Lyman McDonald3, Shay Howlin3, and Kirsten Bixler1

1

U.S. Geological Survey.

2

U.S. Fish and Wildlife Service.

3

WEST, Inc., Cheyenne, Wyoming.

Summary

Throughout its range in North America, the largest 

concentration of Marbled Murrelets is found in Southeast 

Alaska (Piatt and Naslund, 1995; Nelson, 1997). The entire 

region was sampled with randomly selected transects in 1994 

in order to estimate the size of marine bird populations (Agler 

and others, 1998). This survey suggested that between 486,000 

and 888,000 Brachyramphus murrelets resided in Southeast 

Alaska during the summer. This survey has not been repeated, 

and we do not know the size of the present-day murrelet 

population in Southeast Alaska. However, we can examine 

trends for Icy Strait, an east-west waterway in northern 

Southeast Alaska (fig. G1) that is an important staging 

and foraging area for thousands of murrelets in the region 

(DeGange, 1996; Whitworth and others, 2000). This large 

strait was surveyed repeatedly between 1993 and 2003 using 

the same survey track and protocols in each year (Robards and 

others, 2003; Lindell, 2005). Here we analyze the data and 

report on the observed trend. The estimated total population 

size of murrelets in Icy Strait shows a statistically significant 

decrease from approximately 37,000–53,000 birds in 1993 

to approximately 16,000–17,000 birds in 2002–03. Linear 

modeling also suggests a decline since 1993 of 11.4 percent 

per year. These approaches support the projection of an 

80 percent decline in total numbers between 1993 and 2006.

Methods

Beginning in 1993, the U.S. Fish and Wildlife Service 

initiated a systematic survey of Icy Strait (Lindell, 2005). 

This survey was comprised of a grid of 12 north-south legs 

separated by 2.5 nmi and set perpendicular to Icy Strait, 

running from the head of Chatham Strait in the east to the 

mouth of Glacier Bay in the west (fig. G2). The cross-strait 

Figure G1. Location of Icy Strait study area in the northern half of Southeast Alaska. Area outlined in red is 

where surveys were conducted.

Appendix G 217
Figure G2. Selection of Icy Strait surveys to illustrate the 

change in murrelet population abundance and distribution over 

time.

transects were joined by 13 east-west legs that ran parallel 

to the coast on both sides of the Icy Strait. The total distance 

surveyed comprised 240 km or about 70 km2 within an area of 

about 1,000 km2. This grid was surveyed repeatedly within and 

between the years of 1993 to 1999 by Lindell (2005) and then 

once a year between 1999 and 2003 by the U.S. Geological 

Survey (Robards and others, 2003).

Lindell’s Survey Methods—The end of each Icy Strait 

segment was fixed with latitude and longitude waypoints, and 

these were used by Lindell (2005) as start and stop positions 

for each segment of the Icy Strait survey. All surveys were 

completed using the U.S. Fish and Wildlife Service motor 

vessel Curlew, a 65-foot ship. When he established near-shore 

segments, Lindell placed transects as near as possible to the 

adjacent shore without compromising survey vessel safety. 

These along-shore segments were straight-line transects and 

did not often venture within 200 m of shore. In this respect, 

they differ from small-boat protocols used by other researchers 

(Agler and others, 1998) where vessels closely followed 

shorelines at 100 m distance offshore, and where offshore (≥ 

200 m) areas were segregated as different strata for statistical 

analysis.

Lindell (2005) conducted 15 complete surveys of Icy 

Strait during the summers of 1993–99. In some years, he 

replicated surveys in June, July, and August. However, 

surveys conducted by U.S. Geological Survey (USGS) in 

1999–2003 were only conducted in June, raising concerns 

about comparability with some of Lindell’s surveys. Bird 

numbers observed in early August also tend to be elevated and 

more variable (DeGange, 1996). This corresponds to the late 

chick-rearing period when foraging adults are highly mobile 

(Whitworth and others, 2000), and large numbers of failed 

breeders and subadults also contribute to volatility in size of 

local populations (Speckman and others, 2000). For all these 

reasons, then, we excluded all of Lindell’s surveys that were 

conducted in the month of August, leaving seven surveys 

that were conducted between June 14 and July 16, in 1993, 

1995, 1998, and 1999. Out of concern that the August survey 

might still provide some useful trend information, or at least a 

different perspective, we analyzed those data separately.

USGS Survey Methods.—Beginning in 1999, surveys 

were conducted by USGS in Icy Strait, using the same 

protocols as Lindell (Gould and Forsell, 1989). Again, all 

flying birds were counted continuously (e.g., Agler and 

others, 1998) rather than on periodic scans. In 1999, surveys 

were conducted using a 300-m strip transect, counting birds 

on 150 m either side of the R/V Pandalus, (22-m length, 5-m 

viewing height). In 2000–03, observations were made from 

several vessels including the R/V Alaskan Gyre (17 m, 5-m 

viewing height, 300–m transect width) and the smaller vessels 

Lutris II, (8 m, 2-m viewing height) and David Grey (10 m, 

2.5-m viewing height) from which we reduced the strip width 

218 Status Review of the Marbled Murrelet in Alaska and British Columbia
from 300 to 200 m. Although the total linear distance surveyed 

(240 km) did not change among years, the total area surveyed 

changed from about 72 km2 during 1993–99 to about 52 km2

during 2000–03 because of the difference in vessel type and 

strip widths.

Most other USGS methods were similar to those used 

by Lindell and described above. Birds were identified to 

species whenever possible, and again, only 19 Kittlitz’s were 

observed out of 2,188 birds identified, so we are essentially 

analyzing trends for Marbled Murrelets in this report. We 

used exactly the same waypoints and segments as Lindell. 

All surveys were conducted between June 11 and June 23, so 

seasonal variability is not a significant issue. Surveys were 

not conducted when seas exceeded 1 m. Bird and mammal 

sightings were recorded by entering them directly into a 

real-time computer data-entry system (Glenn Ford, R.G. Ford 

Consulting Inc.) that plots sighting positions continuously 

using Global Positioning System (GPS) coordinates. 

GPS locations were obtained from a Rockwell Precision 

Lightweight Global-Positioning Receiver (PLGR). PLGR 

units have a worst-case horizontal position accuracy of ±10 m 

at speeds less than 36 kph.

Data Analysis.—Data were collected using protocols 

established for 10 minute transects. This is a robust scale for 

collection of marine bird data, and widely used for pelagic 

observation programs in the Pacific and Atlantic oceans 

(Gould and Forsell, 1989; Huettmann and Diamond, 2006). 

Serial correlation of birds along continuously recorded survey 

lines can be a problem in data analysis (Schneider, 1990), 

but binning of data into 10-15 min or 3-5 km transect lengths 

reduces substantially or eliminates autocorrelation effects 

for most species (Fauchald and others, 2000; Yen and others, 

2004; Huettmann and Diamond, 2006) perhaps because it 

matches the typical scale of aggregation of seabirds and 

their prey (Schneider and Piatt, 1986; Piatt, 1990; Fauchald 

and others, 2000), including Marbled Murrelets (Burger and 

others, 2004). Autocorrelation of adjacent 10- min survey 

periods and 20-min survey periods were investigated using 

Moran’s I statistic (Moran, 1948). We calculated Moran’s I 

for each survey and day. Autocorrelation was indicated for 

adjacent 20-min survey lengths for only 2 of 27 survey days. 

We proceeded with statistical analysis to estimate variances of 

density estimates using a bootstrapping procedure (described 

below) on 20-min survey periods.

Population density of murrelets on each survey was 

calculated as the ratio (number per square kilometer) of total 

murrelets observed to total area surveyed (Cochran, 1977, 

table 1). The total population size of Icy Strait was estimated 

by extrapolation from the ratio estimator of density to the 

total Icy Strait study area (1,063 km2

). A bootstrap procedure 

(Manly, 1997) was used to estimate the variance of the density 

estimate for every survey. The bootstrap procedure resampled 

the original data with replacement, assuming the variance 

in the sample was equivalent to the variance of the universe 

of all possible sample units in the study area (Manly, 1997). 

The bootstrap procedure was conducted separately for each 

survey. For each replication of the bootstrap procedure, 20-

min survey periods were resampled with replacement until the 

resampled sample size was equal to the original sample size. 

The ratio estimator of density (total murrelets observed to 

total area surveyed) was calculated for each resampled dataset. 

These steps were repeated 2,000 times. The mean, standard 

deviation, variance, and percentile confidence intervals were 

calculated for the 2,000 bootstrapped ratios. We also computed 

the bootstrapped variance of log-transformed estimates of 

density. Potential mathematical bias was estimated for each 

survey as the difference between the bootstrap mean and the 

observed ratio of totals. Density estimates are reported as the 

ratio estimator of density, because mathematical bias was 

insignificant, being less than 1 percent in all comparisons.

Trend was estimated by weighted linear regression of 

natural log of murrelet densities on time where the weights 

were the inverse of the estimated variance of log-transformed 

density (Sokal and Rohlf, 1981). Potential autocorrelation in 

the time series was investigated by computing Moran’s I on 

the residuals in the weighted regression analysis.

Results and Conclusions

There was a large change in estimated total numbers of 

murrelets in Icy Strait between 1993 and 2003, declining from 

a high of more than 50,000 birds in 1993 to about 16,000 birds 

in recent years (table G2). The areal extent of distribution 

contracted as well, with birds retaining high densities near the 

entrance to Glacier Bay but diminishing in areas to the east 

(fig. G3). This represents a significant change in abundance 

over time, as indicated by the lack of overlap in 95-percent 

confidence limits surrounding population estimates during 

the early versus late years of sampling (table G2, fig. G3). 

Weighted linear regression of log-transformed densities 

indicates a significant decline over the time period of 1993 

through 2003 (F=8.52, df=1,10, p=0.015, r2 =0.46), at a rate 

of -12.7 percent per year (fig. G3). All 95-percent confidence 

intervals on Moran’s I contained zero indicating no significant 

serial autocorrelation among the residuals over time. Separate 

regression of Lindell’s August data (1993–98 only) provided 

corroboration of the magnitude of the trend (-8.5 percent per 

year) although the amount of explained variation was low and 

insignificant (r2

 = 0.14, F=1.02, df=1,6, p=0.35). Because of 

the shorter time span, higher variability among counts, lack of 

significance, and less certainty about the source of variability 

during this part of the season, we place no confidence in these 

results from August, nor use them for further analyses.

Appendix G 219
Figure G3. Population trend for Marbled Murrelets in Icy Strait, 1993–2003. Note log scale for population 

size. Each point represents a different survey of Icy Strait. Weighted linear regression indicates a decline of 

-12.7 percent per year (p=0.015).

220 Status Review of the Marbled Murrelet in Alaska and British Columbia

Table G1. Survey effort, area surveyed (km2), and total number 

of murrelets observed on Icy Strait surveys.

Date No. of 

transects

Area 

surveyed

Percent 

total area

No. murrelets 

counted

06/21/1993 71 71.1 6.7 3,555

07/15/1993 71 72.5 6.8 2,510

07/09/1995 69 71.6 6.7 2,631

07/11/1995 74 71.6 6.7 2,038

06/22/1998 77 74.8 7.0 1,221

06/24/1998 84 71.6 6.7 803

06/11/1999 88 73.0 6.9 336

06/14/1999 77 71.6 6.7 944

06/21/2000 79 46.4 4.4 638

06/21/2001 79 48.3 4.5 1,073

06/13/2002 90 57.6 5.4 899

06/11/2003 82 55.0 5.2 822

Table G2. Estimated density (birds/km2) and total number of 

Marbled Murrelets occupying Icy Strait during summer with 95-

percent confidence limits on the total.

Date Density Population 

estimate

95-percent 

confidence limits

Lower Upper

06/21/1993 50.0 53,171 36,107 72,817

07/15/1993 34.6 36,815 23,957 50,792

07/09/1995 36.7 39,042 21,216 60,719

07/11/1995 28.5 30,243 15,753 49,052

06/22/1998 16.3 17,340 8,407 26,990

06/24/1998 11.2 11,916 5,429 22,470

06/11/1999 4.6 4,892 3,045 7,084

06/14/1999 13.2 14,009 6,309 23,608

06/21/2000 13.7 14,615 7,850 22,497

06/21/2001 22.2 23,594 13,980 35,306

06/13/2002 15.6 16,589 7,939 26,617

06/11/2003 14.9 15,880 8,966 23,654
The relationship of log-transformed density and time may 

not be strictly linear over the period from 1993 through 2003. 

Estimated population declines exhibited in this data set may 

have occurred mostly between 1993 and 1999, as indicated 

by a conjectured stronger negative trend in log-transformed 

counts during this period, followed by a period of little change 

during 2000 through 2003 when the trend is relatively flat. The 

estimated decrease per annum during 1993 through 1999 is -

25.9 percent per year (r2 =0.84, F=30.47, df=1,6, p=0.002) and 

the slope during 2000 through 2003 is not statistically different 

from zero, although this conjectured break in the data was not 

defined a-priori and the results must be viewed as tentative.

 There is evidence for a weak North Pacific climate 

regime shift in 1999 (Bond and others, 2003; Curchitser and 

others, 2005; Overland and Wang, 2005) and evidence that 

climate-related physical changes (e.g., winds, SST) have had 

pervasive biological effects on marine animals (Springer, 

2004; Grebmeier and others, 2006; but see Litzow, 2006). 

Under this scenario, the long period of decline in murrelet 

numbers that began after the 1976 regime shift (Agler and 

others, 1999) could have been slowed or halted by a later 

regime shift in 1999. In the absence of a longer time series 

of data, or any data after 2003, or any clear understanding 

of the mechanism by which regime shifts influence seabirds 

(Springer, 2004), the conservative conclusion based on the 

best available information should be that (1) murrelet numbers 

in Icy Strait have declined at a very high rate since 1993, and 

(2) we have insufficient data to establish whether or not the 

decline is continuing.

References Cited

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1999, Declines in marine bird populations in Prince William 

Sound, Alaska coincident with a climatic regime shift: 

Waterbirds, v. 22, no. 1, p. 98-103.

Agler, B.A., Kendall, S.J., Seiser, P.E., and Irons, D.B., 1998, 

Abundance and distribution of Marbled and Kittlitz’s 

murrelets in south central and southeast Alaska: Condor, 

v. 100, no. 2, p. 254-265.

Bond, N.A., Overland, J.E., Spillane, M., and Stabeno, P., 

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continental shelf off southwest Vancouver Island: Marine 

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Cochran, W.G., 1977, Sampling techniques: New York, John 

Wiley and Sons, 428 p.

Curchitser, E., Haidvogel, D.B., Hermann, A.J., Dobbins, E.L., 

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of the North Pacific Ocean: Assessment and analysis of 

simulated basin-scale variability (1996-2003): Journal of 

Geophysical Research, v. 110, p. 11021-11042.

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Marbled Murrelet in southeast Alaska: Portland, Oregon, 

U.S. Forest Service, Pacific Northwest Research Station, 

General Technical Report 388, 72 p.

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distribution of seabirds and prey: Ecology, v. 81, p. 772-783.

Gould, P.J., and Forsell, D.J., 1989, Techniques for shipboard 

surveys of marine birds: Washington, D.C., U.S. Fish and 

Wildlife Service Technical Report 25, 22 p.

Fauchald, P., Erikstad, K.E., and Skarsfjord, H., 2000, Scaledependent predator-prey interactions: Hierarchical spatial 

distribution of seabirds and prey: Ecology, v. 81, p. 772-783

Grebmeier, J.M., Overland, J.E., Moore, S.E., Farley, 

E.V., Carmack, E.C., Cooper, L.W., Frey, K.E., Helle, 

J.H., McLaughlin, F.A., and McNutt, S.L., 2006, Major 

ecosystem shift in the northern Bering Sea: Science, v. 311, 

p. 1461-1464.

Huettmann, F., and Diamond, A.W., 2006, Large-scale effects 

on the spatial distribution of seabirds in the Northwest 

Atlantic: Landscape Ecology, v. 21, p. 1089-1108.

Lindell, J.R., 2005, Results of at-sea Brachyramphus murrelet 

surveys in Icy Strait and other selected areas of southeast 

Alaska, 1993-1999: Juneau, Alaska, U.S. Fish and Wildlife 

Service, Unpublished Report, 17 p.

Litzow, M.A., 2006, Climate regime shifts and community 

reorganization in the Gulf of Alaska: How do recent shifts 

compare with 1976/1977?: Journal of Marine Sciences, 

v. 63, p. 1386-1396.

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marmoratus), in Poole, A., and Gill, F., eds., Birds of North 

America: Philadelphia, Pennsylvania, Academy of Natural 

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Appendix G 221
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eds., Ecology and conservation of the Marbled Murrelet: 

Albany, California, U.S. Forest Service, Pacific Southwest 

Research Station, General Technical Report 152, 

p. 285-294. 

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A., Bodkin, J.L., Hooge, P., and Speckman, S.G., 2003, 

Ecology of selected marine communities in Glacier Bay: 

Zooplankton, forage fish, seabirds and marine mammals: 

Anchorage, USGS Alaska Science Center, Final Report to 

USNPS, GBNPP, 156 p. 

Schneider, D.C., 1990, Spatial autocorrelation in marine birds: 

Polar Biology, v. 8, p. 89-97.

Schneider, D., and Piatt, J.F., 1986, Scale-dependant 

aggregation and correlation of seabirds with fish in a coastal 

environment: Marine Ecology Progress Series, v. 32, 

p. 237-246.

Speckman, S.G., Springer, A.M., Piatt, J.F., and Thomas, 

D.L., 2000, Temporal variability in abundance of Marbled 

Murrelets at sea in southeast Alaska: Waterbirds, v. 23, 

no. 3, p. 364-377.

Springer, A.M., 2004, Changing relationships between 

climate and biological indices in the eastern Bering Sea, 

in Macklin, S.A. and Hunt, G.L. Jr., eds., Southeast 

Bering Sea ecosystem: Implications for marine resource 

management: Silver Springs, Maryland, National Oceanic 

and Atmospheric Administration Coastal Ocean Program 

Decision Analysis Series 24 Final Report, p. 112-125.

Whitworth, D.L., Nelson, S.K., Newman, S.H., van Vliet, 

G.B., and Smith, W.P., 2000, Foraging distances of radiomarked Marbled Murrelets from inland areas in southeast 

Alaska: Condor, v. 102, no. 2, p. 452-456.

Yen, O.P.W., Sydeman, W.J., and Hyrenbach, K.D., 2004, 

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Systems, v. 50, p. 79-99.

222 Status Review of the Marbled Murrelet in Alaska and British Columbia
Appendix H. Population Trend of Brachyramphus Murrelets in Glacier Bay, 

Alaska

By John Piatt1, Gary Drew1, John Lindell2, Shay Howlin3, and Lyman McDonald3

1

U.S. Geological Survey.

2

U.S. Fish and Wildlife Service.

3

WEST, Inc., Cheyenne, Wyoming.

Methods

Outside of a few partial or localized surveys of Glacier 

Bay (e.g., Conant, 1991; Duncan and Climo, 1991; Agler and 

others, 1998; Eckert, 2005), this region has been the object 

of extensive, bay-wide surveys for marine birds on eight 

occasions between 1991 and 2003 (Piatt and others, 1991; 

Robards and others, 2003; Lindell, 2005; Drew and others 

(U.S. Geological Survey, unpub. data, 2006). Methods for all 

surveys were similar, but in the following, we review them 

individually. 

Figure H1. Location of Glacier Bay in the northern end of Southeast Alaska. Area 

outlined in red is where surveys were conducted.

Recent concerns over the 

population status of Marbled Murrelets 

(Brachyramphus marmoratus) and 

Kittlitz’s Murrelets (B. brevirostris) led 

us to examine murrelet population trends 

in Glacier Bay, Alaska. Glacier Bay is 

located in the northern end of Southeast 

Alaska, a region that hosts the largest 

concentration of Marbled Murrelets 

found anywhere throughout their range 

from California to the Bering Sea (Piatt 

and Naslund, 1995; Nelson, 1997). 

A regional-scale survey of Southeast 

Alaska in 1993 suggested that between 

486,000 and 888,000 Brachyramphus

murrelets resided in Southeast Alaska 

during summer (Agler and others, 1998). 

This survey has not been repeated, 

and we do not know the size of the 

present-day murrelet population in 

Southeast Alaska. However, we can 

examine trends for Glacier Bay, a large, 

protected body of water at the northern 

end of Southeast Alaska (fig. H1) and 

an important breeding and foraging area 

for thousands of murrelets in the region 

(DeGange, 1996; Whitworth and others, 

2000). Glacier Bay was surveyed for 

marine birds in 1991 (Piatt and others 

1991), 1993 (Lindell, 2005) and in 

1999–2003 (Robards and others, 2003). 

Here we analyze these data and report 

on the observed trend. The estimated 

total population size of Brachyramphus

murrelets in Glacier Bay shows a 

statistically significant decrease from 

approximately 75,000 birds in 1991 to 

approximately 16,000 birds in 2003. In 

contrast, no other bird species in Glacier 

Bay appear to have declined during this 

period. Linear modeling of log-transformed density estimates 

suggests a decline since 1991 of 11.7 percent per year. These 

approaches support the projection of approximately an 

85 percent decline in total numbers between 1991 and 2006. 

Appendix H 223
U.S. Fish and Wildlife Service 1991 Methods.—In 1991, 

biologists with the U.S. Fish and Wildlife Service, Glacier 

Bay National Park and University of Alaska, Fairbanks, 

conducted a systematic survey of Glacier Bay Alaska (Piatt 

and others, 1991). The purpose of these surveys was to 

conduct a preliminary reconnaissance for both Marbled 

and Kittlitz’s Murrelets in Glacier Bay, as well as to collect 

baseline data on other marine bird and mammal species in 

the park. Using small, open skiffs, observers set out to survey 

the entire coastline and opportunistically sampled 15 offshore 

segments as well (fig. H2). Transect lengths ranged from 0.88 

to 11.98 km with a total length of 723.36 km (table H1) and a 

surveyed area of 144.76 km2 (about 10 percent of which was 

offshore). 

Observers used standard sampling protocols developed 

for small-boat surveys of Prince William Sound shoreline 

following the Exxon Valdez oil spill (Klowsiewski and Laing, 

1994). All flying birds were counted continuously (e.g., Agler 

and others, 1998) rather than on periodic scans (Gould and 

Forsell, 1989). Observers viewed birds from about 2 m above 

the water surface and two observers were on duty during all 

surveys. Observers surveyed continuously along transects and 

binoculars were used to aid in identification of species. All 

swimming birds and mammals within 100 m on either side or 

200 m forward of the boat were identified to species. For more 

details on methods, see Klosiewski and Laing, 1994; Agler 

and others, 1998, 1999; Robards and others, 2003). 

Lindell’s Survey Methods.— In 1993, the U.S. Fish and 

Wildlife Service conducted systematic surveys of Glacier 

Bay, Alaska (Lindell, 2005). The survey consisted of 38 strip 

transects laid out in a zig-zag fashion to broadly cover the 

full length of Glacier Bay (fig. H3). Transect lengths ranged 

from 1.4 to 14.35 km with a total length of 278.6 km and a 

surveyed area of 83.6 km2 (table H1). Surveys were conducted 

using the U.S. Fish and Wildlife Service motor vessel Curlew, 

a 65-foot ship. The survey was conducted once in June 1993 

and replicated later in mid-August 1993. However, surveys for 

murrelets in late July and August may detect higher densities 

and greater variability within and between years (DeGange, 

1996; Speckman and others, 2000). This corresponds to the 

late chick-rearing period when foraging adults are highly 

mobile (Speckman and others, 2000; Whitworth and others, 

Figure H2. Route of surveys in Glacier Bay conducted in 1991 by U.S. Fish and Wildlife 

Service and National Park Service. (Piatt and others 1991).

2000), and large numbers of failed 

breeders and subadults also contribute 

to the size and volatility of local 

populations (Speckman and others, 

2000). For these reasons, the best 

time period for monitoring population 

change in murrelets is during June 

and early July when adults are still 

tied to nesting areas and attendance 

at sea is most stable (Speckman and 

others, 2000). Because of this, and 

because all other survey data were 

collected in June or early July, we 

excluded Lindell’s survey data from 

August (even though murrelet densities 

[31.0 birds per square kilometer] were 

similar to those observed in June). 

Lindell (2005) used shipboard 

survey methods described by Gould 

and Forsell (1989), with the exception 

that all flying birds were counted 

continuously (per Klosiewski and 

Laing, 1994) rather than on periodic 

scans. All surveys were completed 

using the M/V Curlew at a cruising 

speed of about 10 nmi/h (knots) 

(18.5 km/h). Observers were stationed 

approximately 5 meters above the 

water surface atop the ship’s wheel 

house. 

224 Status Review of the Marbled Murrelet in Alaska and British Columbia
Figure H3. Route of surveys in Glacier Bay conducted in 1993 by U.S. Fish and Wildlife 

Service.

Appendix H 225

Table H1. Survey effort, distance and area surveyed, and total 

number of Brachyramphus murrelets observed on Glacier Bay 

surveys.

[Abbreviations: km2, square kilometer]

Year Month Number. of 

transects

Amount surveyed Percent 

total area

Number of 

murrelets 

km km counted 2

1991 June-July 173 723.6 144.7 11.2 8,474

1993 June 37 278.6 83.6 6.5 3,017

1999 June 110 1,138.9 316.4 24.5 5,972

2000 June 109 1,169.1 270.1 21.0 3,879

2001 June 105 1,175.7 276.0 21.4 4,545

2002 June 109 1,218.5 258.5 20.1 3,302

2003 June 109 1,164.8 263.5 20.4 3,300
At least two observers were on duty during all surveys. A 

third observer was added when large numbers of birds were 

encountered. They identified and recorded all birds and 

mammals encountered within 150 m either side and ahead of 

the survey vessel. Observers estimated this distance using sight 

boards installed on the vessel and by calibrating against duck 

decoys or similarly sized buoys placed at a known distance 

from the vessel. Observers sampled continuously along 

transects, and binoculars were used to aid in identification 

of species. Surveys typically were conducted when wave 

heights were less than 0.6 m (2 ft), with few, if any, white 

caps. Surveys were conducted during all phases of the tide and 

throughout daylight hours, which would tend to reduce the 

variability associated with those factors (Speckman and others, 

2000). Observers recorded the time of each Brachyramphus 

murrelet observation by hour and minute. Positions for each 

minute were calculated from time between waypoints obtained 

from the Differential Global Positioning System. 

USGS Survey Methods.—Beginning in 1999, U.S. 

Geological Survey (USGS) biologists collected data along 

the entire coastline of Glacier Bay and on offshore transects 

that were perpendicular to the coastline and spaced at 2.5 nmi 

intervals (fig. H4). Methodologies were those recommended 

in Gould and Forsell (1989) for ship-based surveys except 

that all flying birds were counted continuously in order to be 

comparable with previous surveys of Glacier Bay (Piatt and 

others, 1991; Lindell, 2005). Transect lengths varied from 

1.2 to 12.7 km with a total length of more than 1,100 km and 

a surveyed area of more than 250 km2 each year (table H1), 

about 35 percent of which was offshore habitat. 

During the years of study (1999–2003), several vessels 

were used to collect survey data. Observers on the 

R/V Pandalus (22 m length, 5-m viewing height, 300-m 

transect width) and Alaskan Gyre R/V Alaskan Gyre (17 m, 

5-m viewing height, 300-m transect width) counted and 

identified birds and mammals within 150 m on either side 

Figure H4. Route of surveys in Glacier Bay established in 1999 by the U.S. Geological 

Survey and conducted annually in 1999–2003. (Robards and others, 2003; U.S. Geological 

Survey, unpub. data, 1999–2003).

or 150 m forward of the boat. Several 

smaller vessels also were used in these 

surveys. Due to the lower viewing 

angles from these boats, we limited the 

transect window to 100 m on either side 

and 100 m forward of the boats Lutris 

II, (8 m, 2-m viewing height), David 

Grey (10 m, 2.5-m viewing height), 

Capelin (8 m, 2.5-m viewing height), 

and Sigma-t (9.5 m, 2-m viewing 

height). Observers actively scanned 

ahead of and alongside the survey 

vessel, and species identifications 

were confirmed using 7–10 power 

binoculars. Standard guides were used 

for identifications. 

All surveys were conducted 

between June 11 and June 23, so 

seasonal variability is not an issue. 

Surveys were not conducted when 

seas exceeded 1 m. Bird and mammal 

sightings were recorded by entering 

them directly into a real-time 

computer data-entry system (DLOG; 

Glenn Ford, ECI) that plots sighting 

positions continuously using Global 

Positioning System (GPS) coordinates. 

GPS locations were obtained from 

a Rockwell Precision Lightweight 

Global-Positioning Receiver (PLGR). 

PLGR units have a worst-case 

horizontal position accuracy of ± 10 m 

at speeds less than 36 kph. 

226 Status Review of the Marbled Murrelet in Alaska and British Columbia
Data Analysis.—Murrelets were identified to species 

when possible, but a significant proportion were recorded 

as unidentified on all surveys. Identification of murrelets in 

the field can be difficult, even for experienced observers. 

Lighting conditions, distance, visibility, sea conditions, 

plumage variation, and willingness of observers to persist in 

efforts to verify identification, also contribute to variability in 

categorizing birds to species. For the seven surveys compiled 

here, the fraction of birds on survey that were categorized as 

unidentified Brachyramphus ranged from 22 to 58 percent of 

all birds observed. For those birds that were identified, the 

fraction that were Kittlitz’s murrelet ranged from 7.2 to 25 

percent, and averaged 15 percent. Ideally, we could prorate 

the unidentified Brachyramphus birds into species, but this 

would add uncertainty to our conclusions about trends for 

Marbled Murrelets. Therefore, for purposes of analyses 

here, all Marbled, Kittlitz’s and Unidentified Murrelets were 

combined as Brachyramphus murrelets. On average, only 

about 15 percent of these are Kittlitz’s Murrelets, and so the 

overall trends are still mostly attributable to those of Marbled 

Murrelets. 

Data were collected and organized at spatial scales 

ranging between about 1–14 km in length and transects 

averaged about 4–10 km in length on all surveys. This is a 

robust scale for analysis of marine bird data. Serial correlation 

of birds along continuously recorded survey lines can be a 

problem in data analysis (Schneider, 1990), but binning of 

data into 1–10 km transect lengths reduces or eliminates 

autocorrelation effects for many species (Fauchald and others, 

2000; Yen and others, 2004; Huettmann and Diamond, 2006) 

perhaps because it matches the typical scale of aggregation of 

seabirds and their prey (Schneider and Piatt, 1986; Piatt, 1990; 

Fauchald and others, 2000; Burger and others, 2004). 

The design of surveys varied considerably among years. 

The 1991 survey was designed to sample shoreline habitat, 

and only about 10 percent of transects sampled offshore 

habitat haphazardly. In contrast, the survey conducted in 1993 

sampled mostly offshore waters, and ventured near shore only 

near the end of pelagic transects or when surveying long, 

narrow arms of Glacier Bay. Finally, the 1999–2003 surveys 

sampled both shoreline and offshore habitats extensively, 

with about 35 percent of effort directed to offshore habitat. It 

is important to consider whether comparisons among studies 

are likely to be biased by this unequal distribution of effort 

among habitats. Preliminary analyses of habitat use by marine 

birds in Glacier Bay (G. Drew, U.S. Geological Survey, unpub. 

data, 2006) suggests that while some species exhibit markedly 

higher densities in shallow (0–60 m) waters (e.g., Common 

Mergansers Mergus merganser, Harlequin Duck Histrionicus 

histrionicus) or deeper (>60 m) offshore waters (e.g., Blacklegged Kittiwake Rissa tridactyla), neither Marbled nor 

Kittlitz’s Murrelet exhibited any persistent differences in their 

at-sea densities among habitats and years. Furthermore, birds 

move rapidly between offshore and coastal habitats over daily, 

weekly and monthly time scales (Romano and others, 2004). 

A simple comparison (using t-test) of shoreline and pelagic 

transect densities suggests some difference in distribution, 

with higher densities offshore in 3 of 6 years analyzed 

(1991, 1999–2000). A similar analysis of Agler and others 

(1998) survey data for all of Southeast Alaska revealed no 

difference in murrelet densities between shoreline and offshore 

transects. On average among these surveys, offshore densities 

were about 20 percent higher than coastal densities, but this 

difference was not apparent in all years, nor significant (t = 

2.20, p=0.51, df = 11 using Welch’s correction for unequal 

variance; Zar, 1996). Therefore, we proceeded with the 

comparison of murrelet densities among studies and years.

A bootstrap procedure was used to estimate the mean 

density (number per square kilometer) and variance for every 

survey. The population was estimated from the ratio of total 

birds observed on all transects to the total area surveyed 

on all transects (Cochran, 1977). The total population size 

of Glacier Bay was estimated by extrapolation from the 

bootstrap estimate of density to the total area of Glacier Bay 

(1288.7 km2 ). The bootstrap procedure resampled the original 

data with replacement, assuming the variance in the sample 

was equivalent to the variance of the population (Manly, 

1997). The bootstrap procedure was conducted separately for 

each survey. For each replication of the bootstrap procedure, 

transects were resampled with replacement. The resampled 

sample size was the original sample size. The ratio estimator 

of density (total murrelets observed to total area surveyed) 

was calculated for each resampled dataset. These steps were 

repeated 2,000 times. The mean, standard deviation, variance, 

and percentile confidence intervals were calculated for the 

2,000 bootstrap ratios. We also computed the bootstrapped 

estimate of the variance of the log-transformed estimate of 

density.

Potential mathematical bias was calculated for each 

survey as the difference between the bootstrap mean and the 

observed ratio of totals. Density estimates are reported as the 

ratio estimator of density, because mathematical bias was 

insignificant, being less than 0.4 percent in all comparisons. 

Trend was estimated by weighted linear regression of natural 

log of murrelet densities on time where the weights were the 

inverse of the estimated variance of log-transformed density 

(Sokal and Rohlf, 1981). Potential autocorrelation in the 

time series was investigated by computing Moran’s I on the 

residuals in the weighted regression analysis.

Appendix H 227
Results and Conclusions

There was a large change in total numbers of 

Brachyramphus murrelets observed in Glacier Bay between 

1991 and 2003, declining from an estimated high of more than 

75,000 birds in 1991 to about 16,000 birds in 2003 (table H2). 

This represents a significant change in abundance over time, 

as indicated by the lack of overlap in 95-percent confidence 

Murrelet Population Trend in Glacier Bay

9

10

11

1990 1993 1996 1999 2002

Year

Total no. birds

8,100

22,000

60,000

Figure H5. Population trend for Brachyramphus murrelets in Glacier Bay, 1991–2003. Note log 

scale for population size. Weighted linear regression indicates a decline of -11.8 percent per 

annum (p<0.0001, r2

 =0.96). 

limits surrounding population estimates during the early versus 

late years of sampling (table H2, fig. H5). Weighted linear 

regression of log-transformed densities indicates a significant 

decline over time (F=128.5, df=1,6; p<0.0001, r2=0.96), 

at a rate of -11.8 percent per year (fig. H5). All 95-percent 

confidence intervals on Moran’s I contained zero indicating 

no significant serial autocorrelation among the residuals over 

time. 

228 Status Review of the Marbled Murrelet in Alaska and British Columbia

Table H2. Estimated density (birds/km2) and total number of 

Brachyramphus murrelets occupying Glacier Bay during summer 

with 95-percent confidence limits on the total.

Date Density Population 

estimate

95-percent confidence limits

Lower Upper

1991 58.6 75,486 59,721 92,627

1993 36.1 46,552 31,275 63,928

1999 18.9 24,397 20,034 29,509

2000 14.4 18,550 15,120 22,254

2001 16.5 21,294 17,231 25,612

2002 12.8 16,485 13,221 20,380

2003 12.5 16,178 12,851 20,070

References Cited

Agler, B.A., Kendall, S.J., Irons, D.B., and Klosiewski, S.P., 

1999, Declines in marine bird populations in Prince William 

Sound, Alaska coincident with a climatic regime shift: 

Waterbirds, v. 22, no. 1, p. 98-103.

Agler, B.A., Kendall, S.J., Seiser, P.E., and Irons, D.B., 1998, 

Abundance and distribution of Marbled and Kittlitz’s 

murrelets in south central and southeast Alaska: Condor, 

v. 100, no. 2, p. 254-265.

Burger, A.E., Hitchcock, C.L., and Davoren, G.K., 2004, 

Spatial aggregations of seabirds and their prey on the 

continental shelf off southwest Vancouver Island: Marine 

Ecology Progress Series, v. 283, p. 279-292.
Conant, B., 1991, Marbled Murrelet population estimates 

for southeast Alaska: Anchorage, Alaska, U.S. Fish and 

Wildlife Service.

DeGange, A.R., 1996, Conservation assessment for the 

Marbled Murrelet in southeast Alaska: Portland, Oregon, 

U.S. Forest Service, Pacific Northwest Research Station, 

General Technical Report 388, 72 p.

Duncan, T., and Climo, L., 1991, Beardslee Island bird and 

mammal survey: Gustavus, Alaska, Glacier Bay National 

Park and Preserve, 14 p.

Eckert, G., 2005, Southeast Alaska synthesis of marine 

biology and oceanography: Juneau, University of Alaska 

Southeast, Report to the North Pacific Research Board.

Fauchald, P., Erikstad, K.E., and Skarsfjord, H., 2000, Scaledependent predator-prey interactions: Hierarchical spatial 

distribution of seabirds and prey: Ecology, v. 81, p. 772-783.

Gould, P.J., and Forsell, D.J., 1989, Techniques for shipboard 

surveys of marine birds: Washington, D.C., U.S. Fish and 

Wildlife Service Technical Report 25, 22 p.

Huettmann, F., and Diamond, A.W., 2006, Large-scale effects 

on the spatial distribution of seabirds in the Northwest 

Atlantic: Landscape Ecology, v. 21, p. 1089-1108.

Klosiewski, S.P., and Laing, K.K., 1994, Marine bird 

populations of Prince William Sound, Alaska, before and 

after the Exxon Valdez oil spill: Anchorage, Alaska, Exxon 

Valdez Oil Spill Trustee Council, State / Federal Natural 

Resource Damage Assessment Final Report, Bird Study 2, 

88 p.

Lindell, J.R., 2005, Results of at-sea Brachyramphus murrelet 

surveys in Icy Strait and other selected areas of southeast 

Alaska, 1993-1999: Juneau, Alaska, U.S. Fish and Wildlife 

Service, Unpublished Report, 17 p.

Nelson, S.K., 1997, Marbled Murrelet (Brachyramphus 

marmoratus), in Poole, A., and Gill, F., eds., Birds of North 

America: Philadelphia, Pennsylvania, Academy of Natural 

Sciences and American Ornithologists’ Union, p. 276.

Piatt, J.F., Conant, B., and Iverson, C.G., 1991, Comparison 

of aerial and boat-based surveys for Marbled Murrelets in 

southeast Alaska, July 23-28, 1991: Anchorage, Alaska, 

U.S. Fish and Wildlife Service, 14 p.

Piatt, J.F., 1990, Aggregative response of Common Murres 

and Atlantic Puffins to their prey: Studies in Avian Biology, 

v. 14, p. 36-51. 

Appendix H 229

Piatt, J.F., and Naslund, N.L., 1995, Abundance, distribution, 

and population status of Marbled Murrelets in Alaska, in

Ralph, C.J., Hunt, G.L. Jr., Raphael, M.G., and Piatt, J.F., 

eds., Ecology and conservation of the Marbled Murrelet: 

Albany, California, U.S. Forest Service, Pacific Southwest 

Research Station, General Technical Report 152, 

p. 285-294. 

Romano, M.D., Arimitsu, M.L., Piatt, J.F., Agness, A.A., 

and Drew, G.S., 2004, At-sea density and distribution of 

Kittlitz’s Murrelets (Brachyramphus brevirostris) and 

Marbled Murrelets (Brachyramphus marmoratus) in Glacier 

Bay, Alaska, Summer 2003: Anchorage, U.S. Geological 

Survey Alaska Science Center, Annual Report to U.S. 

National Park Service, Glacier Bay National Park and 

Preserve.

Sokal, R.R., and Rohlf, F.J., 1981, Biometry: New York, W.H. 

Freeman.

Robards, M., Drew, G.S., Piatt, J.F., Anson, J.M., Abookire, 

A., Bodkin, J.L., Hooge, P., and Speckman, S.G., 2003, 

Ecology of selected marine communities in Glacier Bay: 

Zooplankton, forage fish, seabirds and marine mammals: 

Anchorage, USGS Alaska Science Center, Final Report to 

USNPS, GBNPP, 156 p. 

Schneider, D.C., 1990, Spatial autocorrelation in marine birds: 

Polar Biology, v. 8, p. 89-97.

Schneider, D., and Piatt, J.F., 1986, Scale-dependant 

aggregation and correlation of seabirds with fish in a coastal 

environment: Marine Ecology Progress Series, v. 32, 

p. 237-246.

Speckman, S.G., Springer, A.M., Piatt, J.F., and Thomas, 

D.L., 2000, Temporal variability in abundance of Marbled 

Murrelets at sea in southeast Alaska: Waterbirds, v. 23, 

no. 3, p. 364-377.

Whitworth, D.L., Nelson, S.K., Newman, S.H., van Vliet, 

G.B., and Smith, W.P., 2000, Foraging distances of radiomarked Marbled Murrelets from inland areas in southeast 

Alaska: Condor, v. 102, no. 2, p. 452-456.

Yen, O.P.W., Sydeman, W.J., and Hyrenbach, K.D., 2004, 

Marine bird and cetacean associations with bathymetric 

habitats and shallow-water topographies: Implications 

for trophic transfer and conservation: Journal of Marine 

Systems, v. 50, p. 79-99.

Zar, J.H., 1996, Biostatistical analysis: Upper Saddle River, 

New Jersey, Prentice Hall, ed. 3.
230 Status Review of the Marbled Murrelet in Alaska and British Columbia

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Appendix I. Change in Abundance of Brachyramphus Murrelets Along the Outer 

Gulf of Alaska Coast, Adjacent to Malaspina Glacier

Summary by J. Piatt of information provided by Michelle Kissling1

1

3000 Vintage Blvd., Suite 240, Juneau, Alaska 99801-7100.

Summary

The U.S. Fish and Wildlife Service (USFWS) has been 

surveying areas of Southeast Alaska for Marbled and Kittlitz’s 

Murrelets since 2002. Some results have reported elsewhere 

(e.g., Kissling, 2006). This is a synopsis of a USFWS survey 

of an area along the Malaspina Forelands that was previously 

surveyed in 1992 (Kozie, 1993). This is the only data from the 

outer coast of the Gulf of Alaska that can be used to assess 

changes in murrelet populations in this region. Results of other 

population surveys in the region are tabulated here (table I1), 

but for details on those contact Michelle Kissling.

Methods

Kissling conducted broad-scale surveys to describe 

distribution and abundance of Brachyramphus murrelets in 

Southeast Alaska. The Icy Bay and Malaspina study areas 

were surveyed in 2002, and the Outer Coast study area was 

surveyed in 2003 and 2004 (fig. I1). Only the Malaspina 

survey is discussed here.

The following protocols were adopted by both Kissling 

(this report) and Kozie (1993). Shoreline transects ran parallel 

to shore and covered waters less than 200 m offshore. Along 

the Malaspina Forelands, boats maintained a distance of 

approximately 1 km from shore, roughly following the 10 

fathom contour. Surveys were conducted from July 25–26, 

1992 by Kozie and July 7–14, 2002 by Kissling using strip 

transect survey methods (Gould and Forsell, 1989) and 

all flying birds were counted continuously. Two observers 

recorded all birds 100 m either side of and ahead of the vessel. 

In 1992, observations were recorded on data sheets and in 

2002 using a Global Positioning System (GPS)-integrated 

voice recording system (Program SURVEY, J. Hodges, U.S. 

Fish and Wildlife Service, Juneau). Information recorded 

included number of birds, behavior (on water, flying, foraging) 

and various environmental parameters (e.g., sea and ice 

conditions, wind speed, etc.).

The identification of murrelets in the field is often 

difficult. In 1992, 27–31 percent of murrelets were not 

identified, and Marbled Murrelets comprised 33–48 percent of 

those identified on replicate transects. In 2002, about 

5–11 percent of birds were not identified to species on 

replicate transects, and about 81-93 percent of identified birds 

were Marbled Murrelets. With such high variability among 

transects and observers in the fraction of birds identified to 

species, and in the ratio of Marbled to Kittlitz’s, the data have 

been lumped simply into Brachyramphus species.

Appendix I 231

Table I1. Marbled Murrelet population estimates by area. 

[Data from M. Kissling, U.S. Fish and Wildlife Service, unpub. data, 2005]

Area

Populaton (N)

Estimate Percent CV

95-percent 

confidence 

interval

Icy Bay 199 51.39 0 399

Malaspina Forelands 5,367 38.1 1,359 9,375

Exposed North 2,720 21.57 1,570 3,870

Mouth of Lituya Bay 1,390 22.48 778 2,002

Lituya Bay 145 27.19 68 222

Exposed South 5,902 15.95 4,057 7,747

Icy Point 1,000 9.09 821 1,178

Outer Coast Bays 62 21.55 36 88
232 Status Review of the Marbled Murrelet in Alaska and British Columbia

Results

The Malaspina survey basically consisted of running 

127 km in 1-day from a point mid-way along the north 

coast of Yakutat Bay, around the Malaspina Forelands, and 

into Icy Bay (fig. I1). The survey was replicated on the 

second day by returning on the same track from Icy Bay to 

Yakutat Bay The total area surveyed was 25.4 km2 on each 

trip, except on the first replicate in 2002 when a recorder 

malfunction resulted in loss of data from one side of the 

vessel (reducing transect width to 100 m). The transect 

still yielded data on murrelet densities, but only over a 

100-m strip-width.

The number of Marbled Murrelets may have 

increased by 22 percent between 1992 and 2002 if we 

include and prorate unidentified Brachyramphus murrelets 

in the counts. However, as noted in the section, “Methods” 

above, uncertainties about identification of species suggest 

Table I2. Counts of Brachyramphus murrelets on the Malaspina 

transect in 1992 and 2002.

Year

Survey Number of 

birds

Density number 

per square 

kilometer Replicate Area, square 

kilometers

1992 1 25.4 1,029 40.5

1992 2 25.4 1,070 42.1

2002 1 12.7 286 22.5

2002 2 25.4 631 24.8

Figure I1. Study areas and 12 sampling strata delineated for estimation of 

Brachyramphus murrelet densities and populations in July 2002–04. Icy Bay 

and Malaspina Forelands study areas were surveyed in 2002, and the Outer 

Coast study area was surveyed in 2003 and 2004.

N

Icy Bay

Outer Coast

Mainland

Fjords

0 50 100 150 200 Kilometers

Sampling Strata 

Icy Bay

Malaspina Forelands

Exposed North

Mouth of Lituya Bay

Lituya Bay

Exposed South

Icy Point

Outer Coast Bays

Cross Sound

Wilderness Bays

Thomas Bay

LeConte Bay

the conservative approach is to consider trends 

in all Brachyramphus combined (Marbled + 

Kittlitz’s + Unidentified).

The average density of Brachyramphus

murrelets declined by about one-half from 1992 

to 2002 (table I2). Regression of the natural log 

of bird density versus date suggests (r2

=0.97, 

F=111.4, df=1,2, p<0.009) a rate of change equal 

to -5.4 percent per year.

References Cited

Gould, P.J., and Forsell, D.J., 1989, Techniques 

for shipboard surveys of marine birds: 

Washington, D.C., U.S. Fish and Wildlife 

Service Technical Report 25, 22 p.

Kissling, M., Kuletz, K.J., and Brockmann, S., 

2006, Distribution and abundance of Kittlitz’s 

Murrelets along the outer coast of Glacier 

Bay National Park and Preserve, in Piatt, J.F., 

and Gende, S.M., eds., Glacier Bay Science 

Symposium 4, 2004, p. 116-120.

Kozie, K., 1993, Coastal wildlife survey - 

Seabirds and marine mammals along the 

Malaspina Forelands 1992: Glenallen, Alaska, 

Wrangell-St. Elias National Park and Preserve, 

Research and Resource Management Report 

92-07.
Appendix J. Population Trend of Kittlitz’s and Marbled Murrelets in Prince 

William Sound

By Kathy Kuletz1, Bryan Manly1, Chris Nations1, and David Irons1

[This analysis appears as an appendix in: Kuletz, K.J. 2005, Foraging behavior and productivity of a non-colonial seabird, the Marbled Murrelet 

(Brachyramphus marmoratus), relative to prey and habitat, Ph.D. Dissertation, University of Victoria, British Columbia.]

1

U.S. Fish and Wildlife Service.

Abstract

Monitoring population trends of rare species can be 

difficult if the species are not distinguished in the field from 

closely related, abundant species. We faced this problem in 

Prince William Sound, Alaska for two seabirds, the Marbled 

Murrelet (Brachyramphus marmoratus) and the Kittlitz’s 

Murrelet (B. brevirostris), both of which are surveyed at sea 

because they are non-colonial. As a group, Brachyramphus

murrelets showed declines, but Marbled Murrelets (2004 

population = 35,657 ± 7,809 birds; 95 percent CI greatly 

outnumbered Kittlitz’s (2004 population = 778 ± 516), and 

murrelets were not always identified to species in the field. 

Using data from nine summer surveys (1972 and 1989–2004), 

we developed models that incorporated unidentified murrelets 

and predicted trends for each species. Model predictions 

reasonably fit field survey estimates, and substantiated 

observed trends of identified birds. Based on July (midbreeding season) surveys, the Marbled Murrelet population 

declined at a rate of about 5 percent per year, a total of 85 

percent since 1972, or 63 percent since 1989; predicted 

quasi-extirpation (<100 birds) is in year 2120. Kittlitz’s have 

declined 17.7 percent per annum since 1972 (a total of 99 

percent), or by 30.8 percent per year since 1989 (a total of 88 

percent); predicted quasi-extirpation is year 2006, although 

the 2004 field estimate was about 700 birds. The decline in 

July estimates in both species is of concern, but the Kittlitz’s 

is at greater risk because of its low numbers and faster rate 

of decline. For Kittlitz’s, the decline may be exacerbated 

by dependence on foraging habitat that is undergoing rapid 

change due to glacial recession. For both species, the ability 

to identify species-specific trends will be important in forming 

policy decisions and conservation efforts.

Introduction

Identifying and interpreting trends in populations is a 

critical aspect of conservation and management, and the task 

is complicated by uncertainties in survey data (Harwood 

and Stokes, 2003). For rare species, detection of statistically 

significant trends is difficult, due to large errors in population 

estimates, often exacerbated by an insufficient number of 

years of data (Taylor and Gerrodette, 1993). Inaction due 

to inconclusive or compromised results hampers status 

designations and thus management and conservation by 

affecting legal and policy making decisions (Reed and 

Blaustein, 1997; Ralls and Taylor, 2000; Harwood and 

Stokes, 2003). For closely related species that are difficult 

to distinguish, another source of uncertainty is species 

identification (Hey and others, 2003). Incomplete speciesspecific data can result in trends of rare species being 

masked by trends in the more abundant species (Ludwig and 

others, 1993; Roberts and Hawkins, 1999; Dulvy and others, 

2000). We faced these problems in attempts to determine 

the population status of two seabirds, the rare Kittlitz’s 

Murrelet (Brachyramphus brevirostris) and the relatively 

abundant Marbled Murrelet (B. marmoratus). These closely 

related and phenotypically similar murrelets are sympatric in 

Prince William Sound, Alaska, with the Kittlitz’s Murrelet 

found almost exclusively in fjords with tidewater glaciers 

(Kendall and Agler, 1998; Day and others, 2003; Kuletz 

and others, 2003), and the Marbled Murrelet occurring 

throughout coastal areas and outnumbering other seabird 

species in summer (Agler and others, 1998). The combined 

population of Brachyramphus murrelets was declining in 

Prince William Sound at least since 1989, and probably since 

1972 (Lance and others, 2001). However, inconsistencies in 

species identification reduced confidence in interpretation of 

possible trends. The goal of this study was to substantiate and 

distinguish the trends of the two murrelet species.

Brachyramphus murrelets are small, diving, fish-eating 

seabirds (family Alcidae) found only in the North Pacific. 

Most of the world population of Kittlitz’s Murrelets breed 

along Alaska’s coastlines, but some occur off eastern Russia 

(Day and others, 1999). In 2004, Kittlitz’s Murrelet became a 

candidate for listing under the Endangered Species Act (U.S. 

Fish and Wildlife Service, 2004). Concerns about possible 

declines in the Kittlitz’s Murrelet spurred us to examine the 

best available data on their population trends, to insure that 

timely management actions could be implemented for this 

uniquely Alaskan species. Marbled Murrelets breed from the 

Aleutian Archipelago in Alaska to central California (Nelson, 

1997) and are listed as threatened from British Columbia 

(Burger, 2002 to California (McShane and others, 2004). Most 

of the world population of Marbled Murrelets breed in Alaska 

(McShane and others, 2004), and Prince William Sound has a 

Appendix J 233
relatively large population (Agler and others, 1998). Recently 

the U.S. Fish and Wildlife Service (USFWS) has proposed 

to eliminate the ‘Distinct Population Segment’ status of 

Marbled Murrelets in California, Oregon, and Washington 

(News Release, USFWS Pacific Regional Office, Portland, 

OR., September 1, 2004), which by inclusion with the Alaska 

population could lead to delisting. Thus, knowing the current 

status and trends of Marbled Murrelets in Alaska is important 

for determining the future legal status of this species. Because 

Prince William Sound is one of the few regions in Alaska with 

long-term data, it provides a valuable record of trends in the 

northern portion of the Marbled Murrelet’s range.

To evaluate the status of both murrelet species and assist 

future management decisions, we used at-sea survey data for 

Prince William Sound, which has data for the longest time 

span (9 years within the period, 1972–2004) for any region in 

Alaska. This level of coverage was unique for marine birds at 

sea in Alaska, but trends analysis was complicated by wide 

confidence intervals in the estimates for Kittlitz’s Murrelets, 

variable proportions of unidentified murrelets among years, 

and unusual spikes in the estimates in 2 years. To address these 

issues, we used the Prince William Sound population estimates 

in a modeling technique that incorporated unidentified birds, 

to estimate the size and trend of populations of each species.

Methods

Study Site— Our study site was Prince William Sound, 

a ca. 10,000 km2 protected body of water in the northern Gulf 

of Alaska (Gulf of Alaska). Most of the shoreline is highly 

convoluted and includes deep fjords, shallow bays, deltas, 

large and small islands. There are several large icefields 

with more than 20 tidewater glaciers entering coastal waters 

(Molnia, 2001). The high freshwater input from rain and 

snow or glacial melt influences the strong cyclonic circulation 

that generally runs east to west (Niebauer and others, 1994). 

Surface waters from the Gulf of Alaska pulse into Prince 

William Sound primarily during winter months, via the Alaska 

Coastal Current, and in summer Prince William Sound waters 

become warmer and stratified (Niebauer and others, 1994).

Data Collection.— Between 1989 and 2004, surveys 

were conducted in 8 years (1989–91; 1993; 1996; 1998; 2000; 

2004) during July, which is mid-breeding season (chickrearing) for Brachyramphus murrelets in Prince William 

Sound (Kuletz and Kendall, 1998; Day and others, 1999). 

The USFWS surveys were designed for collecting data on 

all marine birds and mammals using randomly selected strip 

transects, (n = 325–350 per year, including 187–212 shoreline 

and 138 offshore) of varying length and 200 m wide, including 

shoreline, coastal pelagic, and pelagic. Crews on three 7.7 m 

fiberglass boats operated daily and simultaneously to complete 

the survey over a 3-week period. The USFWS conducted 

similar surveys, with different transects and slightly different 

design, in July 1972 (reanalyzed in Klosiewski and Laing, 

1994). The 1972 survey used vessels and transect widths 

similar to the later surveys, but the randomly selected transects 

of the 1972 survey used a different grid system and included a 

‘bay’ stratum along with shoreline and pelagic strata.

For surveys since 1989, 187 shoreline transects were 

randomly selected in 1989, with an additional 25 transects 

randomly selected in 1990. Shoreline transects were defined 

by geographical features, and ranged from 1 to 30 km and 

averaged 5.6 km in length (fig. J1; details in Agler and others, 

1998; Irons and others, 2000; Lance and others, 2001); these 

were surveyed by piloting the boat parallel to and 100 m 

from shore. For offshore areas, a grid with 5-minute latitudelongitude blocks was overlaid on a nautical chart, and 69 

blocks were randomly selected. Blocks that intersected the 

shoreline were categorized as ‘coastal-pelagic’ (n = 44), and 

those that did not touch land were ‘pelagic’ (n = 25). Within 

each block, two parallel lines running north-south were 

surveyed, for a total of 138 pelagic transects. For each block, 

bird density (birds/km2

) was averaged from the two lines, and 

this density was assumed to apply to the entire block, with the 

block density used to extrapolate to total area within its strata. 

Except for the lower number of shoreline transects in 1989, 

the same transects in all strata were surveyed every year. The 

surveyed area amounted to 4.6 percent of the surface area of 

Prince William Sound waters (Agler and others, 1998).

All birds and marine mammals were recorded 

continuously within 100 m either side of and 100 m ahead of 

the boat, with two observers and a driver. Observers identified 

all birds to the highest possible taxon, using 10× binoculars 

for species identification where necessary. Because the two 

murrelet species were difficult to distinguish at sea, a portion 

of them were recorded as ‘unidentified Brachyramphus’. More 

problematic, among years there was unequal emphasis on 

distinguishing between these two species, and the proportion 

of unidentified murrelets ranged from 2 to 89 percent.

Data Analysis.—The study design used for these 

surveys was well-suited to abundant and widely dispersed 

species such as Marbled Murrelets, but not for the rare and 

patchily-distributed Kittlitz’s Murrelet. For the latter species, 

population estimates had wide confidence intervals. Analysis 

of long-term trends also was complicated by the fact that 

the population estimates in 1972 and 1993 for both murrelet 

species were considerably higher than in other years. In 

summary, the analysis of trend data was complicated by large 

error in the estimates for the Kittlitz’s Murrelet, variable 

proportions of unidentified murrelets, and large population 

estimates in 1972 and 1993. Consequently, we analyzed 

three subsets of the data from Prince William Sound in July 

(table J1): (1) including all years; (2) excluding 1972; and, 

(3) excluding both 1972 and 1993.

The original population estimates (hereafter, ‘field 

estimates’) and variances were calculated using a ratio 

estimator (Cochran, 1977) on the densities for each stratum 

(shoreline, coastal-pelagic, and pelagic; see Stephensen and 

234 Status Review of the Marbled Murrelet in Alaska and British Columbia
Figure J1. Prince William Sound, Alaska, showing locations of the shoreline transects (in heavy green) and blocks 

used for pelagic transects for marine surveys from 1989–2004. Two parallel transects running north-south were 

averaged for every pelagic block to obtain bird density.

others, 2001 for details). The total field estimates 

were derived from the summed estimates and 

variances of each stratum. Data used for the 

analyses reported here were field estimates of 

population size and their standard errors (table 

J1). Standard errors (SE) were obtained from the 

95-percent confidence intervals (CI) originally 

calculated from the survey data, using SE = 

CI/1.96. The rate of change for population 

estimates of identified birds was calculated with 

linear regression analyses of log-transformed 

values. We then compared rates of change 

over time between the two species with a 

homogeneity of slopes test (Freud and Littell, 

1981) using linear models.

Using the field estimates and variances 

for Marbled, Kittlitz’s, and unidentified 

Brachyramphus murrelets, we developed 

a population model that accounts for the 

unidentified birds, and provides ‘model 

Appendix J 235

Table J1. Original field population estimates and standard errors (SE) for 

Brachyramphus murrelets in July in Prince William Sound. 

Year

Kittlitz’s Murrelets Marbled Murrelets Unidentified birds

Estimate SE Estimate SE Estimate SE

1972 63,229 40,879 236,633 26,391 4,570 4,018

1989 6,436 1,608 59,284 6,033 41,634 4,194

1990 5,231 4,315 39,486 5,095 36,624 4,036

1991 1,184 572 42,477 4,669 62,816 7,149

1993 2,710 685 14,177 2,295 142,546 21,365

1996 1,280 696 63,455 8,185 17,429 3,056

1998 279 98 49,879 4,818 3,036 1,089

2000 1,033 683 52,377 7,383 1,077 519

2004 778 516 35,658 7,809 840 370
predictions’ of population sizes. The model assumes that the 

probability of being identified is the same for both species 

but may differ from year to year. Identifications are assumed 

implicitly to be correct—e.g., a bird identified as a Kittlitz’s 

Murrelet is not a Marbled Murrelet. The model also assumes 

that Kittlitz’s and Marbled Murrelets have independent but 

constant trends over time. Let NK,0 and NM,0 represent the 

unknown numbers of Kittlitz’s and Marbled, respectively, 

in the starting year, t

0

. The symbols Kt, Mt, and Ut are the 

field estimates of Kittlitz’s, Marbled, and unidentified birds, 

respectively, in year t. Let θK and θK represent the annual 

population growth rate for Kittlitz’s and Marbled, respectively, 

let γt be the probability that a bird will be identified in year 

t, and let EKt, EMt, and EUt represent error terms (including 

discrepancies between predictions of the fitted model and

the observations, but also assuming measurement error in the 

field). The model is then

K N E

M N E

U N N

t K K

t t

t K

t M K

t t

M

t K K

t t

M

t

t t

= +

= +

= +

−

−

−

,

,

, (

0

0

0

0

0

0

θ γ

θ γ

θ

and

, )( ) 0 0 θ γ 1 K

t t

t t EU

− − +

 , (1)

Note that model predictions for Kt, Mt, and Ut are 

predicted numbers seen in surveys, not predicted population 

sizes. To make the distinction clear, we henceforth refer to 

Kt, Mt, and Ut, whether from field observations or model 

predictions, using the term survey size. We estimated the 

unknown parameters (NK, NM, θK, θK, γt) in the model above 

through a weighted least-squares nonlinear regression. Least 

squares chose the parameter values that minimized the 

criterion Q,

( )2

, ,

,

ˆ it it

i t

i t

Y Y

Q V

− = ∑ ∑ , (2)

where

Yi,twas the observed survey size for the i

th group of birds 

at time (i.e., either Kt

, Mt, or Ut), 

,

ˆYi t was the corresponding predicted value, and

Vi,twas the corresponding variance (the standard error 

squared from table J2.

For the nonlinear minimization, we used “reasonable” initial 

guesses based on available information. Initial values for NK

and NM were taken from field estimates in year t

0

 (table J2). 

In all analyses, initial values were θK = θM = 1, representing 

stable populations, and γt = (Kt + Mt)/(Kt + Mt + Ut), the 

observed proportions of identified birds.

We obtained variance for our estimators by simulation. 

We assumed that field observations for all three groups 

of birds (Kittlitz’s, Marbled, and unidentified) were log 

normally distributed with means and variances determined 

by the field estimates (table J2). Random survey sizes were 

generated 5,000 times, based on this assumption in place of 

the field estimates, and parameters were re-estimated from 

the simulated data sets using nonlinear regression. Empirical 

variances were then estimated from the simulated parameter 

estimates using

( ) ( )2

1 ˆ ˆ

ˆ

1

n

i i

V n

∑ = φ −φ

φ = −

 , (3)

where

ni,twas the number of successful optimizations,

ˆ

φi was the i

th parameter estimate, and

ˆ

φ was the mean of the n estimates.

While each simulation entailed 5,000 iterations, the nonlinear 

optimization routine failed to converge occasionally (generally 

<5 percent of the time).

Projections of population size (rather than survey size) 

were generated using a simple exponential growth model 

implied by Eq. 1. Projected numbers of Kittlitz’s Murrelet, 

NK,t, and Marbled Murrelet, NM,t were calculated as

0

0

, ,0

, ,0

ˆ ˆ

and

ˆ ˆ

t t

Kt K K

t t

Mt M M

N N

N N

−

−

= θ

= θ

 , (4)

where all parameter estimates on the right hand side of the 

equations were obtained from the fitted nonlinear regression. 

We also modeled the predicted population size to quasiextinction (<100 birds) for total Brachyramphus murrelets. All 

analyses were conducted in Matlab 6.5.

236 Status Review of the Marbled Murrelet in Alaska and British Columbia
Results

Population Estimates and Trends

Surveys.—Between 1972 and 2004 the field survey 

population estimates for identified birds (table J2) showed a 

decline of 19.9 percent per year for Kittlitz’s murrelet and 

2.3 percent for Marbled Murrelets. The slope for Kittlitz’s 

population estimates was significant (P = 0.04) while that 

for Marbled Murrelets was not (P = 0.69), with the latter 

influenced by large numbers of unidentified birds in some 

years (table J2). The decline of all Brachyramphus murrelets, 

however, was highly significant (r2

 =0.85, F=40.7, p<0.001) 

with long-term rate of -6.3 percent per year (and slightly 

higher rate of -6.9 percent per year when the 1972 data 

are excluded). The rate of decline between species was 

significantly different (Homogeneity of slopes test; 

F1,8 = 6.2, P = 0.03). In July, Kittlitz’s Murrelets were 

primarily found in the upper fjords, and in 2004, their 

distribution was much more restricted than in 1989, with 

most birds found in the northwest area of Prince William 

Sound (fig. J2A). Marbled Murrelets were found throughout 

nearshore areas in all years (fig. J2B). Although the trend for 

Brachyramphus murrelets largely reflects that of Marbled 

Murrelet, owing to their much greater abundance, we 

developed models to assign unidentified birds to species and 

develop better assessments of trends for Kittlitz’s.

Model estimates.—The parameter estimates show that 

both Marbled and Kittlitz’s Murrelets are declining (θ <1.0; 

table J2). The estimated rate of decline is greater for Kittlitz’s 

than for Marbled Murrelets, and θM is larger than θK in all 

scenarios (with 1972 or 1993, or without) even considering 

the estimated variances in those parameters (table J1). Using 

all July data from Prince William Sound (table J2), the 

estimate of θK is 0.8226 (a decline of 17.74 percent per year). 

Excluding data from 1972 or both 1972 and 1993 results in 

even lower estimates of θK, 0.6908 and 0.6825, respectively 

(declines of 30.82 and 31.75 percent per year). The estimates 

of θM and γt

 (for those years in common) are strikingly similar 

in all three cases (θM is approximately 0.94 in each case). 

The model estimates indicate a rate of decline of about 5 

percent per annum, with a total 85 percent decline since 1972 

Table J2. Model parameter estimates from July survey data. 

Parameter

All years1 Exclude 19722 Exclude 1972

and 19933

Mean SE Mean SE Mean SE

NK,0

70,119 21,403 9,402 2,294 9,008 2,428

NM,0

232,710 9,447 94,981 4,716 93,517 4,779

θK

0.8226 0.0098 0.6908 0.0351 0.6825 0.0561

θM

0.9487 0.0024 0.9468 0.0074 0.9467 0.0078

γ

1972

0.9853 0.0129 – – – –

γ

1989

0.5944 0.0361 0.6105 0.0334 0.6091 0.0340

γ

1990

0.5415 0.0344 0.5568 0.0345 0.5546 0.0343

γ

1991

0.4331 0.0443 0.4171 0.0451 0.4212 0.0462

γ

1993

0.1776 0.0303 0.1834 0.0310 – –

γ

1996

0.7673 0.0424 0.7650 0.0443 0.7641 0.0437

γ

1998

0.9425 0.0176 0.9430 0.0185 0.9438 0.0178

γ

2000

0.9798 0.0098 0.9795 0.0098 0.9792 0.0099

γ

2004

0.9803 0.0086 0.9797 0.0089 0.9793 0.0089

1

Optimization successful in 4,790 of 5,000 iterations (95.8 percent).

2

Optimization successful in 5,000 of 5,000 iterations (100 percent).

3

Optimization successful in 4,967 of 5,000 iterations (99.3 percent).

Appendix J 237
or 63 percent decline since 1989. The parameter estimates 

for both Kittlitz’s (NK,0) and Marbled Murrelets (NM,0) differ 

substantially, depending on the starting year (note that 1972 

had much higher field estimates than 1989; table J2).

Comparison of model and field estimates.—In most 

cases, the models appear to fit the field estimates reasonably 

well, although Kittlitz’s tended to show more divergence 

between model and field estimates than did Marbled or 

unidentified murrelets (figs. J3, J4). Model predictions show 

a pronounced decline in numbers of Kittlitz’s Murrelets 

irrespective of whether data from 1972 are included 

(fig. J3A) or not (fig. J4A). Pattern in predicted numbers of 

Marbled Murrelets is less clear particularly when data from 

1972 are excluded (figs. J3B, J4B). The sharp decline in 

unidentified murrelets after 1993 (figs. J3C, J4C) reflects 

both greater success in species identification and decline in 

total Brachyramphus murrelets (fig. J5). Model predictions of 

survey sizes for Kittlitz’s change when data from problematic 

years (either 1972 alone, or both 1972 and 1993) are excluded 

(figs. J3A, J4A). Omitting the problematic years, in both 

scenarios, led to smaller residuals (differences between field 

estimates and model predictions) in 1989 and 1990, but 

larger residuals in 2000 and 2004. However, whether only 

1972 or both 1972 and 1993 (figure not shown) are excluded 

makes little difference in predicted survey size for the years 

in common. In contrast to the situation with Kittlitz’s, results 

for Marbled Murrelets and unidentified birds (most of which 

would have been Marbled Murrelets) are little affected by 

exclusion of the 1972 data.

Projected trends.—Parameter estimates from the fitted 

model were used to project population sizes (table J3) and 

trends of Kittlitz’s and Marbled Murrelets (fig. J6). Assuming 

Kittlitz’s had an initial (1972) population of NK,0 = 70,119 

(table J2, including all years), the model estimate of θK leads 

to a predicted population of 294 in 2000, and less than 100 

(treated as a quasi-extinction threshold) by 2006. Starting with 

the 1989 model estimate of 9,008 and θK = 0.6825 (table J2, 

excluding 1972 and 1993) yields a predicted population of 

only 149 in 2000. Within one year, i.e., by 2001, the predicted 

population is less than 100, thus, the latter set of estimates 

leads to a much more rapid decline (fig. J6).

The projections for Marbled Murrelets are very similar 

whether or not model estimates include 1972 and 1993 July 

data. Using data from all years, where the initial population is 

232,710 and θM = 0.9487 (table J2), the projected population 

in 2000 is 53,105. Because of the modest reduction and larger 

initial population, the predicted population does not decline 

below 100 until the year 2120.

238 Status Review of the Marbled Murrelet in Alaska and British Columbia

Table J3. Population projections for murrelets in Prince William Sound in 

July, with estimates based on data from all years (table 1), excluding 1972, 

and excluding 1972 and 1993. The projections incorporated unidentified 

Brachyramphus murrelets (see section, “Methods”).

Year

Kittlitz’s Murrelets Marbled Murrelets

All years Omit 

1972

Omit 1972 

and 1993 All years Omit 1973

Omit 1972 

and 1993

1972 63,209 236,598

1989 2,425 9,269 8,843 95,510 95,210 93,669

1990 2,002 6,420 6,100 90,547 90,112 88,667

1991 1,653 4,446 4,209 85,842 85,288 83,932

1993 1,126 2,133 2,003 77,153 76,400 75,207

1996 633 709 658 65,740 64,774 63,791

1998 432 340 313 59,086 58,024 57,159

2000 294 163 149 53,105 51,977 51,218

2004 137 38 34 42,898 41,709 41,123
Figure J2A. Distribution of Kittlitz’s Murrelets in Prince William 

Sound, Alaska, in July 1989 (top) and 2004 (bottom).

Figure J2B. Distribution of Marbled Murrelets in Prince 

William Sound, Alaska, in July 1989 (top) and 2004 (bottom).

Appendix J 239
(a)

(b) 

(c)

101

102

103

104

105

Kittlitz's Murrelets

104

105

106

Marbled Murrelets

1970 1975 1980 1985 1990 1995 2000 2005

102

103

104

105

106

Unidentified Murrelets

YEAR

Figure J3. Estimated and predicted July population size of murrelets, including all years.

240 Status Review of the Marbled Murrelet in Alaska and British Columbia
(a)

(b) 

(c)

101

102

103

104

105

Kittlitz's Murrelets

104

105

106

Marbled Murrelets

1985 1990 1995 2000 2005

102

103

104

105

106

Unidentifed Murrelets

YEAR

Figure J4. Estimated and predicted July population size of murrelets, excluding 1972.

Appendix J 241
1970 1975 1980 1985 1990 1995 2000 2005

104

105

106

YEAR

TOTAL PREDICTED NUMBER

1970 1975 1980 1985 1990 1995 2000 2005

101

102

103

104

105

106

POPULATION SIZE

YEAR

MAMU

KIMU

Figure J5. Total predicted population size of murrelets for July survey, including all years.

Figure J6. Population projections (eq. 4) based on model estimates of initial murrelet 

numbers and growth rates.

242 Status Review of the Marbled Murrelet in Alaska and British Columbia
Discussion

Both the original population field estimates and the 

model estimates indicate declining populations of total 

Brachyramphus murrelets in Prince William Sound, and 

a more drastic decline in the Kittlitz’s Murrelet than the 

Marbled Murrelet. Of course, any prediction of extirpation or 

quasi-extinction must be qualified by the possibly unrealistic 

assumption of a constant rate of change in population size, 

and by the uncertainty in the model estimates of population 

growth rate. This is evident in the model estimates for 

Kittlitz’s, which predicted less than 100 birds by 2001 (based 

on estimated growth rate from data since 1989) or by 2006 

(using estimated growth rate from data since 1972), whereas 

the actual field estimates were about 1,000 birds in 2000 and 

about 700 birds in 2004 (table J1). Nonetheless, the rate of 

decline for field estimates of identified birds indicates that the 

general conclusions of the model are consistent with trends 

observed for identified birds. The model estimates were much 

closer to field estimates for Marbled Murrelets (e.g., the model 

predicted about 53,000 birds in 2000, and the field estimate 

for that year was about 52,000), which at the current rate of 

decline indicate extirpation of Marbled Murrelets in about 

100 years. The inclusion of the 1972 data did not affect the 

predicted trends of Marbled Murrelets, and actually reduced 

the estimated decline of Kittlitz’s Murrelets when included. 

Although the 1972 field estimates were obtained with a 

different set of transects, we included them because they were 

a valid sampling method. They suggest that declines in both 

species began at least between 1972 and 1989, although for 

Kittlitz’s, the rate of decline may have accelerated in the last 

15 years.

The decline of two closely related species suggests a 

regional and long-term alteration in their environment may be 

responsible. For Marbled Murrelets, loss of old-growth forests 

where they nest has been implicated in murrelet declines 

farther south (Burger, 2002; McShane and others 2004). In 

Prince William Sound, roughly 10,000 acres of forest have 

been harvested since the 1940s, which is approximately 

5 percent of the total forested acreage today, or between 5–10 

percent of ‘harvestable’ timber (of commercial quality in 

harvestable areas) (U.S. Forest Service, Chugach National 

Forest, unpub. data, 2005). Thus, although timber harvests 

could have impacted Marbled Murrelets in Prince William 

Sound, the loss of potential nesting habitat there has been low, 

relative to the 80 percent loss of nesting habitat from British 

Columbia to California (Burger, 2002; McShane and others, 

2004). Kittlitz’s Murrelets nest in remote alpine areas (Day 

and others, 1999) with little human impact, and alteration of 

nesting habitat is not documented. The Prince William Sound 

declines in Brachyramphus murrelets likely are primarily 

related to changes in the marine environment, either in their 

breeding or wintering grounds.

Both murrelet species face similar documented threats at 

sea. First, they are susceptible to mortality in gillnet fisheries 

(Carter and others, 1995; Day and others, 1999), and a 

1990–91 study in Prince William Sound estimated that 

between 450 and 1,470 murrelets were killed in drift gillnets 

per year (extracted from data in Wynne and others, 1991, 

1992). The proportion of Kittlitz’s killed in nets was higher 

than for Marbled Murrelets, relative to their abundance in 

Prince William Sound, suggesting greater susceptibility to 

or overlap with Prince William Sound gillnet fisheries (Day 

and others, 1999). Second, oil spills were and continue to be 

a threat in Prince William Sound. In 1989, the largest spill 

in North America, the Exxon Valdez oil spill, caused direct 

mortality of an estimated minimum of 8,400 Brachyramphus

murrelets (Kuletz, 1996). Although most were likely Marbled 

Murrelets (Carter and Kuletz, 1995), Kittlitz’s lost a greater 

proportion of its population in the spill zone (Day and 

others, 1999). Small spills occur from tour and fishing vessel 

accidents (Kuletz, 2001; U.S. Fish and Wildlife Service, 

2004), primarily during the summer, when murrelets occupy 

inshore waters. Third, since the 1980s tourism has increased 

in Prince William Sound (Murphy and others, 2004), and 

related vessel traffic is heaviest in the fjords with tidewater 

glaciers, where Kittlitz’s forage (Day and others, 2003, Kuletz 

and others, 2003). Finally, in the Gulf of Alaska, prey species 

composition and abundance has changed since the 1970s 

(Piatt and Anderson, 1996; Anderson and Piatt, 1999), and in 

Prince William Sound these changes appear to correspond to 

population declines in piscivorous birds in particular (Agler 

and others, 1999). All these factors could have impacted the 

survival or productivity of murrelets in Prince William Sound. 

In addition, two large scale anthropogenic factors of unknown 

impact include fishery impacts to the ecosystem (Pearson and 

others, 1999) and possible long-term damage from the Exxon 

Valdez Oil Spill (Peterson and others, 2003).

Differences Between Species

Population declines of the magnitude we show for 

murrelets in Prince William Sound would be a concern for 

any long-lived species. Brachyramphus murrelets exhibit 

life-history traits that make them sensitive to loss of adults 

and adversity (Stearns, 1992; Croxall and Rothery, 1995). As 

with many seabirds, they are long-lived, with an estimated 

lifespan of 10–11 years (Burger, 2002; McShane and others, 

2004). They have delayed breeding, with age at first breeding 

estimated to be 2–3 years (Burger, 2002; Cam and others, 

2003) and low fecundity (1 egg/year). The declines were 

not equal for these two species, however, and the proportion 

of Kittlitz’s Murrelet in the field counts of Brachyramphus

murrelets went from 21 percent in 1972 to less than 2 

percent since 1996. The faster trajectory of Kittlitz’s toward 

extirpation suggests greater sensitivity to the same, or 

Appendix J 243
additional, environmental pressures. The different rates of 

decline for these two species could be a result of different 

dietary and habitat needs, and warrant further investigation.

Changes in food availability have often been linked to 

changes in seabird populations (review in Croxall and Rothery, 

1995). Both murrelet species are generalist feeders, consuming 

small, planktivorous fish in addition to invertebrates, but 

Kittlitz’s Murrelets appear to take a larger portion of macrozooplankton (Nelson, 1997; Day and others, 1999). There 

is evidence that warming trends in northern waters affects 

birds that feed on macro-zooplankton more than primarily 

piscivorous birds, because these plankton often require cooler 

water (Kitaysky and Golubova, 2000; Crick, 2004). Since the 

1970s, Prince William Sound sea surface temperatures (SST) 

generally have increased (National Center for Atmospheric 

Research, data from http://www.ncar.ucar.edu).

Kittlitz’s Murrelets also are more specialized than 

Marbled Murrelets in their selection of foraging habitat 

(Day and others, 2003). In Prince William Sound, Kittlitz’s 

are closely associated with glacially influenced, turbid 

waters in the upper fjords (Day and others, 2003, Kuletz 

and others, 2003), as was evident in our surveys (fig. J2). 

Kittlitz’s also may be impacted by changes in these habitats 

arising from glacial recession, as suggested by their present 

day concentration in the few remaining fjords with stable 

or advancing glaciers (Kuletz and others, 2003). Across all 

taxa, species with more northerly distribution, and those more 

specialized, are experiencing greater declines in response to 

climate changes (Root and others, 2003, Julliard and others, 

2004). Our results are consistent with this scenario, since 

Kittlitz’s are both more northerly in distribution and more 

specialized in foraging habitat than Marbled Murrelets.

The causes of declines in Marbled Murrelets in Prince 

William Sound could include several factors already 

mentioned (timber harvest, oil spills, gillnet mortality) or 

extended periods of low recruitment to the population due to 

reproductive failure. However, unlike populations in California 

(Peery and others, 2004), there was no evidence of the latter. 

In Prince William Sound, juvenile Marbled Murrelet densities 

have been relatively high compared to populations farther 

south (Kuletz and Kendall, 1998), and although juvenile 

densities declined from 1995 to 1999, the juvenile:adult ratios 

did not decline significantly (Chapter 4). This suggests that 

loss or emigration of adults is the main factor in the decline of 

the Prince William Sound population.

Notably, in Prince William Sound, the decline in the 

murrelet population parallels the 88 percent decline in stocks 

of Pacific herring (Clupea pallasi) between 1989 and 2000 

(Thomas and Thorne, 2003). The Prince William Sound 

herring crash could have been a consequence of the 1989 oil 

spill, disease, over-harvest in the early 1990s, environmental 

conditions, or a combination of those factors (Pearson and 

others, 1999; Brown and others, 1996; Petersen and others, 

2003; Thomas and Thorne, 2003), but the net effect on 

murrelets was drastic reduction of an important prey base. 

Juvenile herring are a key prey for Marbled Murrelets in 

Prince William Sound, both for adults (which eat age classes 

0 and 1+ herring; Ostrand and others, 2004; Chapter 2) and as 

chick food (which require age class 1+; Chapter 2). Although 

‘forage fish’ are protected from commercial fisheries in 

Alaska (Witherell and others, 2000), abundance of juveniles 

of commercial species, such as herring, could be indirectly 

impacted (Pikitch and others, 2004).

The trends in Brachyramphus murrelets was complicated 

by the unusual spike in their numbers in 1993. Although 

our surveys covered a large geographic area, the extent of 

movement between Prince William Sound and the Gulf 

of Alaska by murrelets is unknown, and it is possible that 

large-scale movements result in fluctuations in the size of the 

population within Prince William Sound. The unusually high 

numbers of murrelets present in July 1993 coincided with 

a year of anomalously warm waters in the Gulf of Alaska 

that year, while Prince William Sound remained relatively 

cool (Piatt and Van Pelt, 1997, Pearson and others, 1999). 

Marbled Murrelets appear to alter their distribution at sea and 

their inland breeding activity in response to oceanographic 

conditions (Becker and Beissinger, 2003; Burger, 2000). In 

California, Marbled Murrelets foraged farther from nesting 

areas in a year with warmer SST, and they selected areas with 

cooler SST in a year when prey abundance was low (Becker 

and Beissinger, 2003). Together with our results, these studies 

highlight the necessity of maintaining long-term monitoring 

programs. Managers must also acknowledge the potential for 

large-scale movements when tracking murrelet population 

trends.

Management Implications

Marbled Murrelets.—The size of the Alaska population 

of Marbled Murrelets relative to populations farther south 

(McShane and others, 2004) might lead to the conclusion that 

the meta-population is healthy. However, the published Alaska 

population estimates were based on surveys conducted from 

1993 to 1996 (Agler and others, 1998), and given the rapid 

changes evident in Prince William Sound, those estimates 

may not represent current populations in Alaska. In addition 

to Prince William Sound, recent declines in Brachyramphus

murrelets have been documented at Glacier Bay in Southeast 

Alaska (Robards and others, 2003), the Malaspina Forelands 

near Yakutat (Kissling and others, U.S. Fish and Wildlife 

Service, unpub. data, 2002–04), and Kachemak Bay in Cook 

Inlet (Speckman and others, 2005). An exception was the 

Kenai Fjords, where a relatively small population (about 9,500 

birds) of Marbled Murrelets declined between 1976 and 1986 

and then increased between 1986 and 2003 (Van Pelt and Piatt, 

2003). Because four of five Alaska sites with trend data show 

244 Status Review of the Marbled Murrelet in Alaska and British Columbia
evidence of declines, we suggest that the status of Marbled 

Murrelet populations warrant closer examination. In particular, 

current data are lacking for Southeast Alaska, which was 

last surveyed entirely in 1994 (Agler and others, 1998) and 

may support more than 70 percent of the world population of 

Marbled Murrelets (McShane and others, 2004).

Kittlitz’s Murrelet.—The rate of decline we found for the 

Prince William Sound population of Kittlitz’s Murrelet is rare 

for any long-lived species, and to our knowledge has not been 

documented in another seabird species, with the exception 

of intense hunting or bycatch mortality of some albatrosses. 

Because Kittlitz’s were a small portion of Brachyramphus

murrelets, their population trend could have been increasing 

or decreasing without necessarily affecting the trend for the 

genus. Similar situations have been found in fisheries, where 

the aggregate (lumped species) trend was stable, but some 

species within the group declined or went extinct before 

managers could act (Ludwig and others, 1993; Dulvy and 

others, 2000, 2003; Harwood and Stokes, 2003). The problem 

of masked trends and crypto-extinctions, while documented 

and discussed for invertebrates and fishes, has not been widely 

recognized for marine birds. Yet, marine birds, especially 

if they are not conspicuous when nesting, have many of the 

same attributes that contribute to crypto-extinctions in fish; 

they are widely dispersed in uninhabited areas most of the 

year, difficult to encounter and enumerate, and may change 

distribution in response to a dynamic and structurally complex 

habitat (Croxall and Rothery, 1995).

Monitoring.—While multi-species monitoring programs 

such as the one in Prince William Sound are not always ideal, 

when protocols are consistent and continue over long time 

frames, they can be useful even for rare, patchily distributed 

species such as the Kittlitz’s Murrelet. The model presented 

here demonstrates a way to make optimum use of population 

estimates for rare species that coexist with abundant ones, or 

when species identification is a source of error. The problem 

of variable proportions of unidentified Brachyramphus

murrelets occurs in other regions of Alaska, and this model 

could be used to re-examine murrelet trends wherever these 

two species co-exist. Similar modeling could benefit trends 

analysis for other species groups as well. For example, 

during marine surveys in Alaska, cormorants (4 spp), murres 

(2 spp), mergansers (3 spp), and loons (5 spp) were not always 

identified to species (North Pacific Pelagic Seabird Database, 

USFWS, Anchorage, Alaska).

Compared to many species listed under the Endangered 

Species Act, Marbled, and even Kittlitz’s Murrelets, still 

have relatively high numbers of individuals. Nonetheless, 

as population size is reduced, fluctuations in population 

size increase the probability of extinction, particularly for 

vertebrate populations numbering in the low thousands 

(Reed and Hobbs, 2004). Furthermore, rapid population 

decline is recognized as a cause for listing species and 

triggering recovery actions regardless of population size 

(World Conservation Union, 2001; U.S. Fish and Wildlife 

Service, 2004). The trends observed in Prince William 

Sound for Marbled and Kittlitz’s Murrelets over the last 30 

years, and especially in the past decade, suggest that both 

Brachyramphus species should be conservation priorities.

Acknowledgments

The field surveys were conducted by dozens of people 

over the years, and we can not thank them all by name, but 

special recognition goes to project and field crew leaders 

Beverly Agler, Steve Kendall, Steve Klosiewski, Karen Laing, 

Brian Lance, and Kelsy Sullivan. The 1972 surveys were 

conducted in part by Pete Isleib and Mimi Hogan. The U.S. 

Forest Service, Chugach National Forest, gave us permission 

to camp on Forest lands. Ally McKnight and Elizabeth 

Labunski provided some of the figures. Drafts were greatly 

improved by review and comments from Alan Burger and 

Tom Reimchen. This research was supported by, but does not 

necessarily reflect the views of, the Exxon Valdez Oil Spill 

Trustee Council.

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248 Status Review of the Marbled Murrelet in Alaska and British Columbia
Appendix K. Population Changes of Marbled Murrelet at Adak Island, Alaska

By John Piatt1, Marc Romano1, James Bodkin1, Kathy Kuletz2, and Jeff Williams2

1

U.S. Geological Survey

2

U.S. Fish and Wildlife Service

Most populations of Marbled Murrelet and Kittlitz’s 

Murrelet (B. brevirostris) outside the Southcentral and 

Southeast Alaska core area have not previously been surveyed. 

The Alaskan distribution of both murrelet species extends 

along the Alaska Peninsula and Aleutian Islands (Day and 

others, 1999; Nelson, 1997). Murrelets are known to occur 

on larger islands of the Aleutians including Unalaska Island, 

Atka Island, Adak Island and Attu Island (Gibson and Byrd, 

in press). Breeding has been confirmed at Atka Island (Day 

and others, 1983) and birds in breeding condition have been 

collected at Adak Island (Byrd and others, 1974). Due to an 

increased concern for murrelets (e.g., Kittlitz’s Murrelet is a 

candidate species for listing under the Endangered Species 

Act), we systematically surveyed murrelets at Attu, Agattu, 

Alaid-Nizki, Shemya, Atka and Unalaska islands in recent 

years to determine population size and lay the foundation for 

assessing population trends in the future (Piatt and others, 

2005; Romano and others, 2005a, 2005b). We surveyed Adak 

Island in 2006 for murrelets, and here we compare results 

of our survey with one conducted in 1995 (Meehan, 1996). 

This constitutes the only dataset in the Aleutian Islands, (and 

indeed west of Cook Inlet) for which historical data allow for 

a measure of population change. 

Survey Methods

Adak is the only Aleutian Island for which there exists 

quantitative, replicated survey data on murrelets. Both 

species are reasonably common at Adak, where they nest 

on the ground and feed in nearshore waters. As part of the 

Department of Defense Legacy Resource Management 

Program, the U.S. Fish and Wildlife Service (USFWS) 

conducted a study of distribution, relative abundance, seasonal 

trends and breeding chronology of Marbled and Kittlitz’s 

murrelets at Adak, Alaska, from 1993 to 1995 (Meehan, 

1996). In addition to land-based observations of murrelets 

flying inland to nest sites, biologists conducted a series 

of shoreline transects (fig. K1) using the same protocols 

developed elsewhere for small-boat surveys (Klosiewski 

and Laing, 1994). Strip transects were conducted from a 25’ 

Boston Whaler or inflatable skiff using a 200-m transect 

width. All birds on the water and flying were counted, and 

identified to species when possible. Surveys covered more 

than half the coast, from the Northeast to Southwest corners of 

Adak (fig. K1). Shagak Bay on the west coast was surveyed in 

an inflatable using a series of parallel transects spaced 200 m 

apart. Incomplete sets of shoreline surveys were conducted in 

1993, and at Shagak in 1993–95, but only in June 1995, was a 

complete set of transects surveyed in all areas. 

We used these data for comparison with a repeated 

survey of this coast in June 2006, which we conducted in 

the nearshore and offshore waters of Adak Island during 

June 13–17, 2006 (fig. K1). We not only wanted to replicate 

the shoreline surveys conducted earlier by Meehan (1996), 

but we wanted to substantially increase survey effort so 

that we could obtain an estimate of population size for the 

entire island, and add to the foundation for future studies 

of population trend. Surveys were conducted, with some 

modification, according to strip survey protocols established 

by the U.S. Fish and Wildlife Service for surveying marine 

birds (Gould and Forsell, 1989, using modifications in Agler 

and others, 1998). Surveys were made from the 40-m 

M/V Tiglax, and a 4.5 m Achilles inflatable skiff. Surveyors 

from the skiff identified swimming birds (and mammals), and 

flying birds, within 100 m of either side or 100 m forward of 

the vessel, resulting in a 200-m wide survey strip. Only the 

skiff was used for coastal transects. The survey strip width 

was increased to 300 m wide aboard the Tiglax with surveyors 

identifying birds (and mammals) within 150 m on either 

side and 150 m forward of the vessel. Only offshore surveys 

were conducted from the ship. The greater height above the 

water surface from the observation area of the Tiglax allowed 

for a greater viewing distance. For surveyors aboard either 

vessel, only birds and mammals sighted forward of mid-ship 

were counted. Ground speed of the vessels while conducting 

surveys was held between 7–12 knots. 

Sightings were recorded by entering them directly into a 

real-time computer data-entry system (DLogCE; Glenn Ford, 

ECI) that logs sightings continuously along with their Global 

Positioning System (GPS) coordinates. A waterproof, shockproof, hand-held computer (TDS Recon) was used for data 

entry. GPS locations were obtained from a Garmin GPS unit. 

All flying birds that crossed within transect were counted, 

regardless of their elevation. Observers actively scanned ahead 

of and alongside the survey vessel, and species identifications 

were confirmed with 8–10 power binoculars. Standard 

guides were used for identification of birds and mammals. 

Weather conditions and sea state were constantly monitored. 

If observation conditions became unsuitable for sighting 

and identifying birds and mammals at the extreme range of 

the survey window then the survey was discontinued until 

conditions improved. Surveys were not conducted if wave 

height exceeded 0.5 m in height.

Appendix K 249
Data Analysis

Because we were also conducting shoreline surveys for 

sea otters (Enhydra lutris) for comparison with historical 

surveys (Jim Estes and Jim Bodkin, U.S. Geological Survey, 

unpub. data, 2006), we gathered data into transects developed 

for that study (fig. K1). However, for comparison with 

murrelet surveys of 1995, we are using only that part of 

sea otter survey transects that overlap completely with the 

1995 surveys. Owing to a computer error, data from several 

shoreline transects on the Northeast side of Adak were lost 

from the 2006 dataset. We also surveyed the entire coast in 

2006, as well as offshore, to obtain a total population estimate. 

Population density of murrelets in 2006 was calculated as 

the ratio (number per square kilometer) of total murrelets 

observed to total area surveyed (Cochran, 1977) of coastal 

(0–500 m) and offshore (500–3,000 m) strata. The total 

population size of was estimated by extrapolation from the 

ratio estimator of density to the total area of each stratum, and 

combining results of both strata.

Because of uncertainty about identification of murrelets 

to species in 1995, we simply lumped all Brachyramphus

species for this analysis of trend. The whole island survey in 

2006 indicated that 83 percent of all Brachyramphus identified 

were Marbled Murrelets. We estimated the density of birds on 

transects and variances using the ratio of total count to area 

surveyed (Cochran, 1977). We added the numbers of murrelets 

observed on all transects surveyed and divided by the sum 

of the areas of all transects surveyed. We then calculated the 

95-percent confidence intervals for these estimates from the 

estimated variance of the ratio of total count to area surveyed 

(Cochran, 1977). Shoreline transects in both 1995 and 2006 

were larger than 3 km in length, a scale below which spatial 

autocorrelation among adjacent segments may be significant 

for a variety of seabirds (Yen and others, 2004; Huettman and 

Diamond, 2006). Thus, we assumed that counts of adjacent 

transects were independent. Density estimates were compared 

among years using a t-test, with Welch’s approximate t

accounting for differences in variance among samples (Zar 

1999, p. 129) and assuming that counts among the transects 

are independent.

Results and Conclusions

On those surveys which could be compared among 

years, we estimated a density in 1995 of 11.5 birds per square 

kilometer (± 8.08 SE, n=26) and in 2006 of 3.97 birds/km2 (± 

1.52 SE,n=14). Despite the large difference in density among 

years, it was not statistically significant (t = 1.04, p>0.05, df 

= 36.8 using Welch’s correction for unequal variance). This 

lack of power to detect statistical significance in a change of 

this magnitude is due in part to the small number of transects 

and in part to the patchiness of murrelet distribution around 

Adak. The problem should be rectified in future years by the 

Figure K1. Seabird surveys conducted around Adak Island in 

1993 and 2006. Top map shows coastal transects completed in 

1995, and red lines indicate which of these were compared to 2006 

data. Middle map shows all transects conducted in 2006, including 

coastal (red) and offshore (blue) transects. Bottom map shows 

coastal transects from 2006 used for comparison with 1995 data.

250 Status Review of the Marbled Murrelet in Alaska and British Columbia
large increase in sample size in 2006 (increased coverage 

with smaller transects of 2–6 km length). Considered simply 

as a complete census of the same stretch of shoreline, 

murrelet numbers declined by about 60 percent between 

1995 (389 birds) and 2006 (167). Noting that two points 

are obviously minimal for assessing a trend, it represents an 

average decrease of 7.4 percent per annum. A change of this 

magnitude, with appropriate statistical rigor, would be of great 

biological significance.

This represents the only data on change for murrelets 

in the Aleutians. This is an important sub-population to 

monitor because genetic studies suggest that populations in 

the Aleutians are different enough from populations elsewhere 

in Alaska and British Columbia to warrant status as a distinct 

management unit (Friesen and others, 2005). From water 

and land-based surveys conducted in 1995, Meehan (1996) 

estimated that about 800–1,000 murrelets (predominantly 

Marbled) resided at Adak during summer. This was certainly 

an underestimate since he did not survey the entire shoreline 

of Adak, or sample much of the offshore. Our survey in 2006 

suggests a population of 1,674 birds (95-percent confidence 

limits: 1,015–2,333) within a 3-km zone around the coast of 

the entire island. 

References Cited

Agler, B.A., Kendall, S.J., Seiser, P.E., and Irons, D.B., 1998, 

Abundance and distribution of Marbled and Kittlitz’s 

murrelets in south central and southeast Alaska: Condor, 

v. 100, no. 2, p. 254-265.

Byrd, G.V., Gibson, D.D., and Johnson, D.L., 1974, Birds of 

Adak Island, Alaska: Condor, v. 76, no. 3, p. 288-300.

Cochran, W.G., 1977, Sampling techniques: New York, John 

Wiley and Sons, 428 p.

Day, R.H., Oakley, K.L., and Barnard, D.R., 1983, Nest sites 

and eggs of Kittlitz’s and Marbled Murrelets: Condor, v. 85, 

no. 3, p. 265-273.

Day, R.H., Kuletz, K.J., and Nigro, D.A., 1999, Kittlitz’s 

Murrelet (Brachyramphus brevirostris), in Poole, A., and 

Gill, F., eds., Birds of North America: Washington, D.C., 

Academy of Natural Science and American Ornithologists’ 

Union, p. 28.

Friesen, V.L., Birt, T.P., Piatt, J.F., Golightly, R.T., Newman, 

S.H., Hébert, P.N., Congdon, B.C., and Gissing, G., 2005, 

Population genetic structure and conservation of Marbled 

Murrelets (Brachyramphus marmoratus): Conservation 

Genetics, v. 6, no. 4, p. 607-614.

Gibson, D.D., and Byrd, G.V., in Press, Birds of the Aleutian 

Islands, Alaska: Ornithological Monographs.Gould, P.J., 

and Forsell, D.J., 1989, Techniques for shipboard surveys 

of marine birds: Washington, D.C., U.S. Fish and Wildlife 

Service Technical Report 25, 22 p.

Huettmann, F., and Diamond, A.W., 2006, Large-scale effects 

on the spatial distribution of seabirds in the Northwest 

Atlantic: Landscape Ecology, v. 21, p. 1089-1108.

Klosiewski, S.P., and Laing, K.K., 1994, Marine bird 

populations of Prince William Sound, Alaska, before and 

after the Exxon Valdez oil spill: Anchorage, Alaska, Exxon 

Valdez Oil Spill Trustee Council, State / Federal Natural 

Resource Damage Assessment Final Report, Bird Study 2, 

88 p.

Meehan, J.P., 1996, Status of Marbled and Kittlitz’s murrelets 

at the Adak Naval Reservation, Alaska: Adak, Alaska, U.S. 

Fish and Wildlife Service, AMNWRR 08, Department of 

Defense Legacy Projects 400 and 1658, 48 p.

Nelson, S.K., 1997, Marbled Murrelet (Brachyramphus 

marmoratus), in Poole, A., and Gill, F., eds., Birds of North 

America: Philadelphia, Pennsylvania, Academy of Natural 

Sciences and American Ornithologists’ Union, p. 276.

Piatt, J.F., Romano, M.D., Gill, V., and DeGange, A.R., 

2005, Density and abundance of Kittlitz’s Murrelets 

(Brachyramphus brevirostris) in the Near Islands, Aleutian 

Islands, Alaska, July 2003: Anchorage, USGS Alaska 

Science Center, Final Report to USFWS, 24 p.

Romano, M.D., Piatt, J.F., and DeGange, A.R., 2005a, At-sea 

density and abundance of Kittlitz’s and Marbled murrelets 

around Unalaska Island, Alaska, June 2005: Anchorage, 

USGS Alaska Science Center, Final Report to the U.S. Fish 

and Wildlife Service, 29 p.

Romano, M.D., Piatt, J.F., Williams, J., and DeGange, A.R., 

2005b, At-sea density and abundance of Kittlitz’s Murrelets 

(Brachyramphus brevirostris) and Marbled Murrelets 

(Brachyramphus marmoratus) at Atka Island, Alaska, June 

2004: Anchorage, USGS Alaska Science Center, Final 

Report to the U.S. Fish and Wildlife Service, 26 p.

Yen, O.P.W., Sydeman, W.J., and Hyrenbach, K.D., 2004, 

Marine bird and cetacean associations with bathymetric 

habitats and shallow-water topographies: Implications 

for trophic transfer and conservation: Journal of Marine 

Systems, v. 50, p. 79-99.

Zar, J.H., 1996, Biostatistical analysis: Upper Saddle River, 

New Jersey, Prentice Hall, ed. 3.

Appendix K 251
252 Status Review of the Marbled Murrelet in Alaska and British Columbia

This page left intentionally blank.
Appendix L. Probability of Assignment of Individual Marbled Murrelets to Each 

of Four Genetic Populations

[See figure 4 for population codes]

Specimen Sampling 

site

Probability of assignment to 

genetic population

1 2 3 4

3695 Near 1.000 0.000 0.000 0.000

3696 Near 1.000 0.000 0.000 0.000

3697 Near 0.998 0.001 0.000 0.000

3698 Near 0.531 0.186 0.275 0.008

3705 Near 0.999 0.001 0.000 0.000

95-183 Near 1.000 0.000 0.000 0.000

95-184 Near 0.998 0.001 0.000 0.001

95-185 Near 1.000 0.000 0.000 0.000

95-186 Near 1.000 0.000 0.000 0.000

Attu3 Near 1.000 0.000 0.000 0.000

Attu4 Near 0.999 0.001 0.000 0.000

96-168 Andr 1.000 0.000 0.000 0.000

96-169 Andr 1.000 0.000 0.000 0.000

96-170 Andr 1.000 0.000 0.000 0.000

96-171 Andr 1.000 0.000 0.000 0.000

96-172 Andr 1.000 0.000 0.000 0.000

UAMX660 Andr 1.000 0.000 0.000 0.000

UAMX662 Andr 0.997 0.001 0.001 0.000

UAMX663 Andr 0.946 0.023 0.031 0.000

UAMX673 Andr 0.997 0.000 0.000 0.002

UAMX701 Andr 1.000 0.000 0.000 0.000

UAMX710 Andr 0.898 0.034 0.007 0.061

UAMX712 Andr 1.000 0.000 0.000 0.000

UAMX688 Unal 0.213 0.533 0.254 0.000

1679 Unal 0.645 0.156 0.116 0.083

1680 Unal 0.072 0.239 0.689 0.000

1681 Unal 0.032 0.373 0.594 0.001

1682 Unal 0.338 0.210 0.157 0.294

1704 Unal 0.716 0.093 0.190 0.001

1705 Unal 0.030 0.815 0.154 0.002

1706 Unal 0.889 0.051 0.060 0.000

1707 Unal 0.021 0.676 0.300 0.002

1708 Unal 0.982 0.008 0.009 0.001

1710 Unal 0.008 0.351 0.625 0.016

9304a Unal 0.751 0.102 0.147 0.000

9304b Unal 0.109 0.778 0.113 0.000

1645 Shum 0.001 0.643 0.346 0.010

1646 Shum 0.003 0.936 0.060 0.000

1647 Shum 0.002 0.424 0.573 0.001

1662 Shum 0.001 0.142 0.855 0.001

2360 Shum 0.001 0.979 0.020 0.000

2361 Shum 0.000 0.268 0.732 0.000

2362 Shum 0.001 0.710 0.271 0.018

2431 Shum 0.357 0.070 0.571 0.002

2466 Shum 0.000 0.154 0.846 0.000

2623 Shum 0.060 0.229 0.709 0.002

2663 Shum 0.001 0.886 0.113 0.000

2664 Shum 0.000 0.110 0.849 0.041

Specimen Sampling 

site

Probability of assignment to 

genetic population

1 2 3 4

95-108 Shum 0.000 0.979 0.021 0.000

95-109 Shum 0.035 0.570 0.300 0.095

95-110 Shum 0.005 0.321 0.673 0.000

95-111 Shum 0.002 0.896 0.102 0.000

95-112 Shum 0.000 0.553 0.447 0.000

95-113 Shum 0.000 0.369 0.629 0.001

3870 Shum 0.000 0.163 0.836 0.000

3871 Shum 0.000 0.923 0.077 0.000

3872 Shum 0.002 0.213 0.778 0.007

3873 Shum 0.000 0.479 0.486 0.035

3874 Shum 0.004 0.699 0.297 0.000

3875 Shum 0.005 0.343 0.652 0.000

3876 Shum 0.000 0.036 0.964 0.000

3877 Shum 0.001 0.577 0.252 0.170

3878 Shum 0.315 0.482 0.198 0.005

3879 Shum 0.000 0.072 0.928 0.000

5mamu Cook 0.000 0.854 0.145 0.000

6mamu Cook 0.000 0.062 0.183 0.755

8504 Cook 0.000 0.114 0.867 0.018

96-87 Cook 0.000 0.976 0.023 0.001

96-88 Cook 0.478 0.384 0.137 0.000

96-90 Cook 0.000 0.035 0.002 0.963

96-91 Cook 0.000 0.035 0.002 0.963

96-92 Cook 0.000 0.476 0.522 0.002

96-93 Cook 0.033 0.562 0.392 0.013

96-94 Cook 0.004 0.705 0.208 0.083

96-95 Cook 0.004 0.781 0.213 0.002

96-96 Cook 0.000 0.164 0.834 0.001

96-97 Cook 0.000 0.260 0.739 0.001

96-98 Cook 0.000 0.144 0.828 0.028

96-99 Cook 0.086 0.615 0.298 0.001

3100 Cook 0.000 0.222 0.756 0.022

3101 Cook 0.490 0.137 0.373 0.000

3102 Cook 0.000 0.014 0.019 0.966

3103 Cook 0.000 0.860 0.140 0.000

3104 Cook 0.000 0.376 0.623 0.001

96-46 Cook 0.000 0.221 0.774 0.005

96-47 Cook 0.936 0.049 0.015 0.000

96-48 Cook 0.005 0.410 0.585 0.000

96-49 Cook 0.000 0.660 0.340 0.000

96-50 Cook 0.000 0.397 0.602 0.000

96-51 Cook 0.018 0.840 0.133 0.009

96-52 Cook 0.000 0.062 0.937 0.000

96-53 Cook 0.007 0.854 0.139 0.000

96-54 Cook 0.000 0.552 0.444 0.004

96-55 Cook 0.004 0.622 0.374 0.001

96-56 Cook 0.001 0.051 0.948 0.000

3311 PWS 0.000 0.169 0.018 0.813

Appendix L 253
Specimen Sampling 

site

Probability of assignment to 

genetic population

1 2 3 4

3312 PWS 0.004 0.355 0.638 0.002

3313 PWS 0.000 0.067 0.933 0.000

3314 PWS 0.001 0.729 0.192 0.078

3315 PWS 0.011 0.734 0.092 0.163

3316 PWS 0.003 0.157 0.838 0.002

3317 PWS 0.000 0.400 0.600 0.000

3318 PWS 0.000 0.466 0.389 0.145

3321 PWS 0.064 0.781 0.155 0.000

3322 PWS 0.000 0.485 0.515 0.000

96-176 Alex 0.000 0.102 0.782 0.116

1mamu Alex 0.001 0.497 0.485 0.016

BmYa99-1 Alex 0.295 0.240 0.255 0.210

96-175 Alex 0.000 0.143 0.855 0.001

96-177 Alex 0.000 0.055 0.945 0.000

94-001 Alex 0.000 0.232 0.062 0.706

94-002 Alex 0.000 0.522 0.478 0.000

94-003 Alex 0.000 0.010 0.990 0.000

94-004 Alex 0.000 0.544 0.456 0.000

94-005 Alex 0.000 0.061 0.939 0.000

94-006 Alex 0.016 0.429 0.388 0.168

94-007 Alex 0.002 0.554 0.416 0.028

94-008 Alex 0.005 0.522 0.465 0.008

94-009 Alex 0.000 0.625 0.363 0.011

94-010 Alex 0.000 0.177 0.823 0.000

94-011 Alex 0.001 0.053 0.945 0.000

94-012 Alex 0.000 0.012 0.988 0.000

94-013 Alex 0.002 0.745 0.251 0.002

94-015 Alex 0.001 0.309 0.652 0.037

94-016 Alex 0.983 0.015 0.002 0.000

94-017 Alex 0.000 0.326 0.674 0.000

94-018 Alex 0.000 0.928 0.072 0.000

94-019 Alex 0.001 0.326 0.669 0.004

94-020 Alex 0.000 0.298 0.698 0.004

94-021 Alex 0.000 0.074 0.926 0.000

203 BC 0.004 0.360 0.636 0.000

204 BC 0.000 0.142 0.858 0.000

205 BC 0.009 0.756 0.233 0.001

207 BC 0.974 0.016 0.010 0.000

210 BC 0.002 0.766 0.148 0.084

212 BC 0.012 0.736 0.251 0.001

217 BC 0.005 0.307 0.688 0.000

218 BC 0.070 0.839 0.090 0.001

219 BC 0.000 0.932 0.068 0.000

220 BC 0.000 0.822 0.178 0.000

221 BC 0.000 0.252 0.748 0.000

235 BC 0.000 0.912 0.088 0.000

241 BC 0.000 0.497 0.503 0.000

Specimen Sampling 

site

Probability of assignment to 

genetic population

1 2 3 4

244 BC 0.000 0.615 0.326 0.059

246 BC 0.018 0.488 0.494 0.000

253 BC 0.000 0.110 0.890 0.000

254 BC 0.000 0.269 0.731 0.000

256 BC 0.000 0.835 0.160 0.004

258 BC 0.000 0.283 0.714 0.002

261 BC 0.003 0.211 0.786 0.000

278 BC 0.000 0.805 0.195 0.001

282 BC 0.000 0.773 0.218 0.009

283 BC 0.000 0.641 0.359 0.000

284 BC 0.000 0.892 0.087 0.020

285 BC 0.000 0.580 0.419 0.001

290 BC 0.011 0.602 0.271 0.116

291 BC 0.000 0.093 0.903 0.004

292 BC 0.000 0.827 0.173 0.000

293 BC 0.579 0.311 0.105 0.006

296 BC 0.000 0.305 0.690 0.005

Wa03-01 WA 0.000 0.693 0.260 0.047

Wa03-02 WA 0.000 0.564 0.161 0.274

Wa03-03 WA 0.003 0.288 0.709 0.000

Wa03-04 WA 0.000 0.259 0.052 0.689

Wa04-01 WA 0.000 0.079 0.041 0.879

Wa04-02 WA 0.000 0.503 0.490 0.007

Wa04-03 WA 0.002 0.841 0.157 0.000

Wa04-04 WA 0.000 0.286 0.714 0.000

Wa04-05 WA 0.000 0.657 0.341 0.002

Wa04-06 WA 0.000 0.346 0.021 0.633

Wa04-07 WA 0.015 0.553 0.431 0.000

Wa04-08 WA 0.000 0.856 0.144 0.000

Wa04-10 WA 0.000 0.358 0.282 0.360

Wa04-11 WA 0.000 0.112 0.887 0.000

Wa04-12 WA 0.010 0.851 0.138 0.000

Wa04-13 WA 0.005 0.721 0.201 0.074

Wa04-14 WA 0.000 0.504 0.468 0.028

Wa04-15 WA 0.001 0.543 0.428 0.028

Wa04-16 WA 0.004 0.117 0.871 0.008

Wa04-17 WA 0.599 0.260 0.053 0.088

Wa04-18 WA 0.000 0.747 0.252 0.000

Wa04-19 WA 0.000 0.630 0.335 0.036

Wa04-20 WA 0.000 0.371 0.629 0.000

Wa04-21 WA 0.000 0.100 0.900 0.000

Wa04-22 WA 0.000 0.243 0.756 0.001

Wa04-23 WA 0.000 0.200 0.799 0.002

Wa04-24 WA 0.000 0.234 0.766 0.000

Wa04-25 WA 0.000 0.436 0.563 0.001

Wa04-26 WA 0.000 0.442 0.556 0.002

Wa04-27 WA 0.001 0.476 0.461 0.062

254 Status Review of the Marbled Murrelet in Alaska and British Columbia
Specimen Sampling 

site

Probability of assignment to 

genetic population

1 2 3 4

Wa04-28 WA 0.001 0.868 0.131 0.000

Wa04-29 WA 0.013 0.738 0.247 0.001

Wa04-30 WA 0.000 0.583 0.417 0.000

2mamu OR 0.107 0.170 0.706 0.017

3mamu OR 0.026 0.231 0.729 0.015

4mamu OR 0.696 0.063 0.156 0.085

OR05-1 OR 0.000 0.085 0.914 0.001

OR05-2 OR 0.147 0.770 0.083 0.000

OR05-3 OR 0.008 0.379 0.612 0.001

OR05-4 OR 0.000 0.246 0.752 0.002

OR05-5 OR 0.000 0.065 0.935 0.000

OR05-6 OR 0.012 0.866 0.121 0.000

OR05-7 OR 0.000 0.167 0.828 0.004

Or-99-16 OR 0.000 0.138 0.743 0.119

Or-99-17 OR 0.100 0.645 0.228 0.027

Or-99-18 OR 0.000 0.237 0.762 0.000

Or-99-21 OR 0.921 0.069 0.010 0.001

Or-99-23 OR 0.075 0.763 0.159 0.003

Or-99-24 OR 0.000 0.830 0.163 0.007

Or-99-25 OR 0.000 0.463 0.535 0.002

Or-99-26 OR 0.002 0.250 0.396 0.352

Ca01-01 NCA 0.000 0.226 0.766 0.008

Ca01-02 NCA 0.000 0.348 0.648 0.005

Ca01-03 NCA 0.002 0.746 0.166 0.086

Ca01-04 NCA 0.003 0.041 0.055 0.901

Ca01-06 NCA 0.000 0.609 0.364 0.026

Ca01-07 NCA 0.005 0.588 0.344 0.062

Ca01-10 NCA 0.003 0.061 0.112 0.824

Ca01-11 NCA 0.000 0.540 0.460 0.000

Ca01-12 NCA 0.000 0.103 0.897 0.000

Ca01-13 NCA 0.002 0.772 0.208 0.018

Ca01-14 NCA 0.000 0.399 0.571 0.030

Ca01-15 NCA 0.000 0.011 0.037 0.952

Ca01-16 NCA 0.000 0.002 0.002 0.996

Ca01-17 NCA 0.000 0.162 0.821 0.017

Ca01-18 NCA 0.000 0.227 0.773 0.000

Ca01-19 NCA 0.000 0.155 0.845 0.000

Ca02-01 NCA 0.000 0.265 0.734 0.001

Ca02-04 NCA 0.000 0.106 0.240 0.654

Ca02-05 NCA 0.000 0.350 0.152 0.498

Ca02-06 NCA 0.001 0.113 0.886 0.000

Ca02-07 NCA 0.000 0.173 0.827 0.000

Ca02-08 NCA 0.000 0.455 0.544 0.000

Ca02-09 NCA 0.000 0.413 0.587 0.000

Ca02-10 NCA 0.000 0.587 0.404 0.009

Ca02-11 NCA 0.000 0.244 0.732 0.024

Ca02-12 NCA 0.001 0.798 0.193 0.008

Specimen Sampling 

site

Probability of assignment to 

genetic population

1 2 3 4

Ca02-13 NCA 0.000 0.084 0.906 0.010

Ca02-14 NCA 0.000 0.294 0.541 0.165

Ca02-15 NCA 0.000 0.164 0.685 0.151

Ca02-17 NCA 0.000 0.068 0.919 0.013

Ca02-18 NCA 0.000 0.483 0.213 0.304

Ca02-19 NCA 0.001 0.084 0.908 0.008

Ca02-20 NCA 0.000 0.908 0.092 0.000

Ca02-21 NCA 0.022 0.461 0.430 0.088

Ca02-22 NCA 0.000 0.001 0.001 0.998

Ca02-23 NCA 0.002 0.444 0.553 0.000

BmCa97-1 CCA 0.000 0.087 0.006 0.906

BmCa97-2 CCA 0.000 0.019 0.005 0.975

BmCa97-3 CCA 0.000 0.000 0.000 1.000

BmCa97-4 CCA 0.000 0.004 0.025 0.971

BmCa97-5 CCA 0.051 0.267 0.025 0.657

BmCa97-6 CCA 0.000 0.000 0.000 1.000

BmCa97-7 CCA 0.000 0.001 0.000 0.999

BmCa97-8 CCA 0.000 0.001 0.000 0.999

BmCa97-9 CCA 0.000 0.006 0.009 0.984

BmCa97-10 CCA 0.005 0.008 0.003 0.985

BmCa97-11 CCA 0.000 0.000 0.000 1.000

BmCa97-12 CCA 0.000 0.000 0.000 1.000

BmCa97-13 CCA 0.001 0.000 0.000 0.998

BmCa97-14 CCA 0.001 0.002 0.000 0.997

BmCa97-15 CCA 0.000 0.000 0.000 1.000

BmCa97-16 CCA 0.001 0.007 0.003 0.989

BmCa97-17 CCA 0.000 0.000 0.000 1.000

BmCa97-18 CCA 0.000 0.000 0.000 1.000

BmCa97-19 CCA 0.000 0.000 0.000 1.000

BmCa97-20 CCA 0.000 0.000 0.000 1.000

BmCa97-21 CCA 0.000 0.000 0.001 0.999

BmCa97-22 CCA 0.001 0.015 0.004 0.980

BmCa97-23 CCA 0.000 0.000 0.000 1.000

BmCa97-24 CCA 0.000 0.004 0.002 0.994

BmCa97-25 CCA 0.000 0.000 0.000 1.000

BmCa97-26 CCA 0.000 0.000 0.000 1.000

BmCa99-1 CCA 0.000 0.001 0.000 0.999

BmCa99-2 CCA 0.000 0.000 0.000 1.000

BmCa99-3 CCA 0.018 0.946 0.035 0.000

BmCa99-4 CCA 0.000 0.063 0.002 0.936

BmCa99-5 CCA 0.000 0.000 0.000 1.000

BmCa99-6 CCA 0.014 0.123 0.709 0.154

BmCa99-7 CCA 0.000 0.000 0.000 1.000

BmCa99-8 CCA 0.000 0.001 0.001 0.998

BmCa99-9 CCA 0.000 0.001 0.000 0.999

BmCa99-10 CCA 0.000 0.002 0.002 0.997

Appendix L 255
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256 Status Review of the Marbled Murrelet in Alaska and British Columbia
Appendix M. U.S. Forest Service Nearshore Surveys, 1991 to 1995: Summary and 

Recommendations

By Kirsten Bixler and John Piatt

In the first half of the 1990s, the United States Forest 

Service surveyed nearshore waters in Southeast Alaska in 

Craig, Thorne Bay, Hoonah, Juneau, Admiralty, KetchikanMisty Fjords, Petersburg, Sitka, Wrangell and Yakutat Ranger 

Districts for Marbled Murrelets, as well as other marine birds 

and mammals. These surveys more or less followed one 

protocol, Methods for Surveys in Southeast Alaska of Seabirds 

and Mammals in Nearshore Waters: A Guide, by C.J. Ralph 

and S.L. Miller, 1991. Most of the data were archived in 1991, 

1992, and to a lesser extent in 1993 and 1995, at the Redwood 

Sciences Forest Service Laboratory in Arcata, California. 

Except for survey routes, the data were digitized when 

archived. We retrieved a copy of these records in May 2006 

and edited a subset in October 2006 (table M1).

The Forest Service surveys combine attributes of both 

strip transects and line transects. The focus of observation was 

within 100 meters of either side of the vessel forming a 200-m 

wide strip. This approach adheres to a standard strip transect 

survey although sightings outside of the strip were recorded as 

well. And as in line transect surveys, observers recorded the 

distance of the animal from the vessel. Observers completed 

two survey types, extensive and intensive. Extensive surveys, 

composed of variable length transects, were split into 2-

kilometer segments parallel to the shoreline and at 100 m and 

500 m from shore. Additionally, every two segments (4 km) a 

segment extended 3,000 m perpendicular to the shore or to the 

center of the waterway. Intensive surveys, were composed of 

segments parallel to shore at 100 m, 500 m, 1,000 m, 1,500 m 

and 2,000 m from the shoreline. In both survey types, all 

flying Brachyramphus murrelets were recorded. Other species 

were recorded if within the 200-m strip or if foraging in flight. 

Birds following the vessel were recorded once per segment. 

Data collected included observer initials, number of observers, 

date, forest service district, vessel length, vessel type, swell 

direction, swell time, visibility, wind direction, cloud cover, 

precipitation, water temperature, tide, ice cover, swell height, 

water depth, water boundary (obvious boundaries between 

water masses), transect start time, bird/mammal species, 

number of animals seen, direction of observation, behavior of 

animals, plumage if applicable, distance from vessel, notes 

and a map of the survey route.

Complete extensive survey data (observational data 

as well as a map of the survey route), was retrieved for 

1,132 segments (2,264 km) parallel to shore and 123 

segments perpendicular to shore. The intensive survey 

data obtained was complete for 42 segments (84 km). 

For use in Marbled Murrelet population estimation and 

trend analysis, we edited all complete intensive segments 

as well as 562 segments (1,124 km) parallel to shore and 

7 segments (39 km) perpendicular to shore of extensive 

transects. Edits included a check for typographical errors, 

data formatting, standardization of units and codes, entering 

missing data, deletion of observations off transect as well 

as observations without a number or distance of animals, 

removal of perpendicular segments with unknown segment 

length, elimination of extraneous data, and location (latitude/

longitude) of starting position of each segment.

These nearshore surveys, in their entirety, would 

significantly expand the data available for estimation of 

population size, trends and distribution of Marbled Murrelets 

in Southeast Alaska as well as provide a similar, extremely 

valuable dataset on other populations of marine birds and 

mammals, such as the Kittlitz’s murrelet, Steller’s sea lion and 

harbor seal. To maximize usefulness and accessibility, all data 

must first be archived in one location, all observational data 

must be entered and edited in a database and each survey route 

digitized within a mapping program such as ArcGIS. Further, 

the data must be made available to interested parties.

We recommend that the following be completed:

1. Digitize maps of surveys for which observational data is 

entered and edited, 611 transects (1,247 km).

2. Fully digitize and edit remaining extensive surveys for 

which both observational data and survey route have been 

acquired, 570 segments (1,140 km) parallel to shore and 

116 segments perpendicular to shore.

3. Through travel to individual ranger districts, retrieve a 

copy of data not archived at the Redwood Sciences Forest 

Service Laboratory. We estimate that the amount of new 

data (i.e. not in our possession) currently languishing 

in warehouses in Southeast Alaska is at a minimum the 

amount of surveys for which we have incomplete data, 

170 segments (340 km). However, it is far more likely 

to be closer to our estimate of the maximum amount of 

new data, which is double the number of segments that 

we now possess, about 2,500 segments (5,000 km). At 

the same time, a copy of all land-based Marbled Murrelet 

survey data can be retrieved.

4. Digitize and edit this new data.

Appendix M 257
258 Status Review of the Marbled Murrelet in Alaska and British Columbia

Table M1. Forest service nearshore survey data from Southeast Alaska for which both observational data and survey route are inhand.

Location Years surveyed

Transect 

type Ranger District

No. parallel 

segments in 

transect

No. perpendicular 

segments in transect

Length (km) 

of parallel 

transect

Bucareli Bay 1991 Extensive Craig 60 50 120

Idaho Inlet 1991 Extensive Hoonah 30 9 60

Lemesurier Island 1991 Extensive Hoonah 20 5 40

Liskianski Inlet East 1991 Extensive Hoonah 22 6 44

Liskianski Strait 1991 Extensive Hoonah 20 4 40

Liskianski Inlet West 1991 Extensive Hoonah 17 6 34

NE Chichagof Isand 1991, 1992 Extensive Hoonah 115 7 230

Neka Bay 1991 Intensive Hoonah 42 0 84

Pleasant Island 1991 Extensive Hoonah 14 4 28

Point Adolphus 1991, 1992 Extensive Hoonah 42 6 84

Tracy Arm 1992 Extensive Juneau 56 0 112

Bakewell 1991 Extensive Ketchikan - Misty Fjords 13 1 26

Channel Island 1991 Extensive Ketchikan - Misty Fjords 5 0 10

East Behm 1991 Extensive Ketchikan - Misty Fjords 13 3 26

Klahini 1991 Extensive Ketchikan - Misty Fjords 4 2 8

Smeaton Bay 1991, 1992 Extensive Ketchikan - Misty Fjords 20 2 40

Walker Cove to Rudyard Bay 1991 Extensive Ketchikan - Misty Fjords 48 2 96

Winstanley Island 1991, 1992 Extensive Ketchikan - Misty Fjords 7 2 14

Rudyerd Bay 1992 Extensive Ketchikan - Misty Fjords 24 1 48

West Duncan Canal 1992 Extensive Petersburg 19 0 38

Frederick Sound 1992 Extensive Petersburg 76 0 152

Wrangell Narrows 1992 Extensive Petersburg 7 0 14

Sumner Strait 1992 Extensive Petersburg 14 0 28

Duncan Canal 1992 Extensive Petersburg 18 0 36

Kruzof Island, Brents Beach 1992 Extensive Sitka 8 0 16

Chatham Cannery 1992 Extensive Sitka 12 0 24

Corner Bay, Chichagof Island 1992 Extensive Sitka 7 0 14

Krestof Sound, Krestof Island 1992 Extensive Sitka 10 0 20

Katlain Bay 1993 Extensive Sitka 7 0 14

Lisianki Pt, Nakwasina Pass. 1993 Extensive Sitka 15 0 30

St. John Baptist Bay 1993 Extensive Sitka 13 0 26

Shulze Cove and Baby Bear Bay 1993 Extensive Sitka 8 0 16

Yellow Point to Rodman Bay 1993 Extensive Sitka 15 0 30

Rodman Bay 1993 Extensive Sitka 7 0 14

Anita Bay 1991 Extensive Wrangell 12 0 24

Kadin Island 1991 Extensive Wrangell 2 0 4

North Etolin 1991 Extensive Wrangell 7 2 14

Rynda and Greys Island 1991, 1992 Extensive Wrangell 15 0 30

Rynda Island 1991 Extensive Wrangell 6 0 12

Vank and Sokalof Island 1991 Extensive Wrangell 7 3 14

Bradfield Canal 1992 Extensive Wrangell 14 0 28

Kadin Island 1992 Extensive Wrangell 3 0 6

Logan Bluffs 1991 Extensive Yakutat 9 0 18

Olgan Cape to Dangerous River 1991 Extensive Yakutat 30 5 60

Redfield 1991 Extensive Yakutat 22 0 44

Yakutat Bay 1991 Intensive Yakutat 19 0 38

Knight Island, Krutoi Island 1992 Extensive Yakutat 31 0 62

Southwest Admiraly 1992 Extensive Yakutat/Admiralty 14 0 28

Pt. Gardener to Whitewater Bay 1992 Extensive Yakutat/Admiralty 13 0 26

Chaik Bay 1992 Extensive Yakutat/Admiralty 22 0 44

Hood Bay 1992 Extensive Yakutat/Admiralty 46 0 92

Northwest Admiralty 1992 Extensive Yakutat/Admiralty 44 0 88
For more information concerning the research in this report, contact the 

Director, Alaska Science Center

U.S. Geological Survey, 4230 University Dr., Suite 201 

Anchorage, AK 99508-4650

http://alaska.usgs.gov
Piatt and others

OFR 2006–1387

Printed on recycled paper

Status Review of the Marbled Murrelet (Brachyramphus marmoratus)

in Alaska and British Columbia