Alaska 

Fisheries Science 

Center 

National Marine 

Fisheries Service 

U.S DEPARTMENT OF COMMERCE 

AFSC PROCESSED REPORT 2006-02


Disturbance of Harbor Seals by 

Cruise Ships in Disenchantment Bay, 

Alaska: An Investigation at Three 

Spatial and Temporal Scales 

February 2006 

This report does not constitute a publication and is for information only. 

All data herein are to be considered provisional. 

Disturbance of Harbor Seals by Cruise Ships in 


Disenchantment Bay, Alaska: An Investigation at 


Three Spatial and Temporal Scales 

Final Report with Results on: 

1) Behavioral response of seals to approaching vessels (fine scale); 

2) Variation in local seal abundance and distribution in relation to 

environmental factors including vessel traffic (medium scale); and 

3) Comparing variation in seal abundance between nearby bays with 

and without cruise ship traffic (large scale) 

by


John K. Jansen, John L. Bengtson, Peter L. Boveng, 


Shawn P. Dahle, and Jay Ver Hoef


National Marine Mammal Laboratory


Alaska Fisheries Science Center


7600 Sand Point Way NE


Seattle, WA 98115 


February 2006 
The mention of trade names, commercial products, or vendors in this report does not 

constitute endorsement or recommendation for use by the United States Government 

ii 
Executive Summary 

Cruise tourism in Alaska has been growing rapidly since the early 1970s. Over 

the last decade there has been increasing concern about possible impacts on sensitive 

coastal ecosystems. Attention has focused most recently on the possible effects of tour 

vessels, particularly cruise ships, on subsistence resources that have been critically 

important to Alaska Natives for many generations. Harbor seals that haul out yearround on floating ice near tidewater glaciers are one such resource of concern because 

their habitat is a popular destination for tourism. This study examined the potential 

effects of cruise ships on the behavior, abundance, and distribution of harbor seals in 

Disenchantment Bay, Alaska, from early May 2002, at the onset of seal pupping, to midAugust 2002, during the molting season. 

Analyses presented here of the behavioral observations – conducted from cruise 

ships – indicate that the likelihood of harbor seals vacating ice floes rose steeply when 

ships approached to less than 500 m; seals approached by a ship at 100 m were 25 

times more likely to enter the water than seals approached at 500 m. Seals were also 

four times more prone to enter the water when ships approached them directly rather 

than passing abeam. The proportion of seals that entered the water when ships passed 

within 200 m was nearly 75% compared to less than 10% entering the water at 

distances where seals showed no apparent overt response to vessels (i.e., > 600 m). 

Analysis of aerial strip-transect sampling (by video playback) showed 

pronounced shifts in seal abundance, with a decline of 75% in mid-May during early 

pup-rearing. Abundance rebounded to peak levels in late June, as cruise ship traffic 

reached maximum levels. Sightings of mother-pup pairs also peaked in late June. Seal 

abundance then stabilized at near-peak levels from late June until the end of the study 

in early August. The decline in seal abundance in mid-May was already underway at 

the first cruise ship entry. Seal abundance then steadily increased in concert with 

increasing ship traffic, suggesting that changes in overall abundance were influenced by 

factors other than ship presence, such as constraints related to pupping and breeding, 

or other environmental variables. 

Space-time statistical models of the effect of environmental and cruise ship 

covariates on seal abundance and distribution were conducted in two stages: one 

model to assess effects on the distribution of seals (i.e., absence-presence in a grid); 

the other to assess effects on seal abundance in grid cells where seals occurred. The 

two models showed that ice cover was a dominant factor with seals tending to occur at 

the highest frequency and in higher numbers in intermediate ice cover (i.e., 50-70% 

coverage by area). Mother-pup pairs showed similar patterns with regard to the type of 

ice cover. Other natural variables, such as precipitation, wind speed, and the area of 

ice habitat available to seals, did not have a measurable effect on the abundance or 

distribution of the pooled seals or mother-pup pairs. 

iii 
Measures of ship traffic, including time spent at closest approach and number of 

ship visits occurring on the 3 days prior to a survey, did not have a statistically 

measurable effect on the abundance of all seals or mother-pup pairs. A negative 

relationship between ships’ closest approach distance and both seal abundance and 

distribution (i.e., more seals at shorter distances) is likely the result of close spatial 

overlap between ships and seals in conjunction with no obvious avoidance by seals of 

areas used by ships. However, increased time that ships spent at their closest approach 

coincided with tighter distributions of harbor seals with no detectable change in 

abundance. This suggests that seals aggregated more closely with increasing ship 

presence. Such findings are consistent with other studies of marine mammals that 

show denser aggregations during periods of disturbance. Coupled with no apparent 

negative effect of ship distance on seal abundance (e.g., no short-term avoidance of 

areas used by ships), these findings suggest the seals’ aggregation response is 

independent of proximity to ship areas and thus appears to occur at distances greater 

than the 500 m threshold suggested by the shipboard observations. 

The seasonal comparison of seal abundance between Disenchantment Bay and 

nearby Icy Bay, where cruise ships are reportedly rare, showed some pronounced 

differences. The maximum total count at Icy Bay was reached in August (5435) during 

molting, with numbers having steadily increased from lower counts in May (1011) and 

June (2543) during early to mid-pupping. In contrast, the peak count at Disenchantment 

Bay (2149) occurred in June at mid-pupping with numbers falling slightly through July 

(1786) and August (1778). The different seasonal patterns suggest that comparable 

numbers of seals use the two sites during pupping but that only a third to half the 

number of seals use Disenchantment Bay during the molting period. Information about 

the actual movement of seals, possibly between the two sites, in relation to natural and 

anthropogenic factors would aid in interpreting these patterns. 

iv 
Contents 

Executive Summary ..................................................................................................... iii

1.0 Introduction......................................................................................................... 1

2.0 Study Area........................................................................................................... 4

2.1 Overview of Past and Present........................................................................ 4

2.2 Defined Area for This Study........................................................................... 6

2.3 Environmental Conditions – In General and During the Study................... 7

2.3.1 Meteorology ............................................................................................... 7 

2.3.2 Ice Conditions ............................................................................................ 9 

2.3.3 Cruise Ships .............................................................................................. 9 

2.3.4 Other Potential Anthropogenic Disturbance............................................. 13 

3.0 Three Spatio-Temporal Scales for Studying Harbor Seals ........................... 15

 3.1 Fine Scale: Observations of Individual Seal Behavior in Relation to 

Vessel Approach Distance ......................................................................................... 15

3.1.1 Methods................................................................................................... 15 

3.1.1.1 Analyses of Shipboard Observations................................................ 16 

3.1.1.2 Statistical Modeling of Behavioral Responses................................... 15 

3.1.2 Results..................................................................................................... 17 

3.1.3 Discussion ............................................................................................... 20 

v 
3.2 Medium Scale: Weekly Aerial Surveys of Seal Distribution and Relative 

Abundance in Disenchantment Bay........................................................................ 23

3.2.1 Methods................................................................................................... 23 

3.2.1.1 GIS Analysis ..................................................................................... 25 

3.2.1.2 Statistical Analyses........................................................................... 26 

3.2.1.2.1 Time Series of Relative Abundance .............................................. 26 

3.2.1.2.2 Space-Time Modeling of Covariate Effects on Seal Counts .......... 26 

3.2.2 Results..................................................................................................... 27 

3.2.2.1 Potential Biases in Seal Abundance................................................. 27 

3.2.2.2 Visual Sampling of Harbor Seals ...................................................... 28 

3.2.2.3 Video Sampling of Harbor Seals....................................................... 28 

3.2.2.3.1 Time Series of Total Abundance ................................................... 29 

3.2.2.3.2 General Patterns in Seal Distribution............................................. 29 

3.2.2.3.3 Seal Abundance in Relation to Ice Cover ...................................... 30 

3.2.2.3.4 Space-Time Model of Seal Counts................................................ 37 

3.2.3 Discussion ............................................................................................... 40 

3.2.3.1 Seasonal Patterns in Daily Abundance............................................. 40 

3.2.3.2 Cell-based Seal Counts in Relation to Environmental Covariates .... 42 

3.3 Large Scale: Monthly Aerial Photographs of Regional Seal Distribution 

and Total Abundance at Disenchantment and Icy Bays........................................ 45

3.3.1 Methods................................................................................................... 45 

3.3.2 Results ..................................................................................................... 45 

3.3.2.1 Potential Sources of Error in High-Altitude Photogrammetry ............ 45 

3.3.2.2 Seal Counts from Photogrammetry .................................................. 46 

3.3.3 Discussion ............................................................................................... 47 

4.0 Conclusions...................................................................................................... 49

5.0 Acknowledgments............................................................................................ 51

6.0 Citations ............................................................................................................ 52 

Appendices.................................................................................................................. 61

vi 
List of Appendices 

Appendix 1. Details of the Space-Time Model ...................................................... 63

A1.1 Zero-Inflated Poisson Regression Model ................................................... 63 

A1.1.1 Spatial Effects........................................................................................... 63 

A1.2 Spatial Conditional Autoregressive Model ................................................. 63 

A1.2.1 Time Effects.............................................................................................. 63 

A1.3 Temporal AR1 Model ................................................................................... 64 

A1.3.1 Prior Distributions .................................................................................... 64 

A1.3.2 Standardized Selection Coefficients ........................................................ 64 

A1.4 Computation.................................................................................................. 65 

A1.5 Results........................................................................................................... 65 

Appendix 2. Data Collection on Harbor Seals in 2004.......................................... 69

A2.1 Fine-Scale Study........................................................................................... 69

A2.2 Medium-Scale Study..................................................................................... 71

A2.3 Large-Scale Study......................................................................................... 73

Appendix 3. Harbor Seal Behavioral Observation Guidelines ............................... 75

vii 
List of Figures 

Figure 1. Map of the Yakutat Bay area showing the two tidewater glaciers, Turner and 

Hubbard ................................................................................................................... 5 

Figure 2. Map of Icy Bay area showing the three tidewater glaciers, Guyot, Yahtse, and 

Tyndall ..................................................................................................................... 7 

Figure 3. Indices of rainfall and wind speed for Disenchantment Bay, May to early 

August 2002............................................................................................................. 8 

Figure 4. Area of Disenchantment Bay (km2

) represented by different ice cover zones, 

scattered (1-3 tenths), intermediate (4-6 tenths), and dense (7-10 tenths), and all 

types combined (i.e., ice-covered area [ICA]) from 3 May to 4 August 2002 ......... 10 

Figure 5. Distribution of cruise ship visits to Disenchantment Bay, with and without 

observers, and aerial surveys, 28 April to 3 August 2002 ...................................... 11 

Figure 6. Haulout behavior of harbor seals (top panel) in relation to the timing (bottom) 

and frequency (top) of cruise ship visits to Disenchantment Bay ........................... 12 

Figure 7. Patterns of ship movement and residence time in Disenchantment Bay in 

2002 ....................................................................................................................... 14 

Figure 8. Relative risk, expressed as the logarithm of the hazard, of a harbor seal 

entering the water (abandoning its ice haul-out platform) in response to varying 

distances of approach by cruise vessels in Disenchantment Bay, Alaska ............. 18 

Figure 9. Relative risk, expressed as the logarithm of the hazard, of a harbor seal 

entering the water (abandoning its glacial ice haul-out platform) in response to 

varying bearing angles during approach by cruise vessels in Disenchantment Bay, 

Alaska. ................................................................................................................... 19 

Figure 10. Estimates of the proportions of harbor seals entering the water in response 

to varying approach distances (in 100 m bins) by cruise ships in Disenchantment 

Bay, Alaska ............................................................................................................ 20 

Figure 11. Map of Disenchantment Bay study area ..................................................... 24 

Figure 12. Vertical angle measurements of perpendicular distance of the two sighting 

bins from the survey aircraft................................................................................... 25 

Figure 13. Relative abundance of all seals and mother-pup pairs in relation to date. . 29 

Figure 14. Spatial distribution of harbor seals, ice cover zones, and maximum 

penetration of cruise ships on the day of surveys () and the previous day () for 

3, 6, and 7 May 2002 ............................................................................................. 31 

Figure 15. Spatial distribution of harbor seals, ice cover zones, and maximum 

penetration of cruise ships on the day of surveys () and the previous day () for 

12, 13, and 16 May 2002 ....................................................................................... 32 

Figure 16. Spatial distribution of harbor seals, ice cover zones, and maximum 

penetration of cruise ships on the day of surveys ( and the previous day () for 

23, 25, and 27 May 2002 ....................................................................................... 33 

Figure 17. Spatial distribution of harbor seals, ice cover zones, and maximum 

penetration of cruise ships on the day of surveys () and the previous day () for 

31 May, 6 and 16 June 2002.................................................................................. 34 

Figure 18. Spatial distribution of harbor seals, ice cover zones, and maximum 

penetration of cruise ships on the day of surveys () and the previous day () for 

20 and 23 June, and 8 July 2002 ........................................................................... 35 

viii 
Figure 19. Spatial distribution of harbor seals, ice cover zones, and maximum 

penetration of cruise ships on the day of surveys () and the previous day () for 

18 and 28 July, and 4 August 2002........................................................................ 36 

Figure 20. Relative abundance of harbor seals within the three ice zones: scattered, 

intermediate, and dense (see legend), from 3 May to 4 August 2002 in 

Disenchantment Bay .............................................................................................. 37 

Figure 21. Standardized selection coefficient for ice cover class for the Bernoulli part of 

the ZIP model (i.e., for the cell-based spatial distribution of seals) ........................ 38 

Figure 22. Standardized selection coefficient for ice cover class for the Poisson part of 

the ZIP model (i.e., for the cell-based abundance of seals) ................................... 39 

Figure 23. Distribution of cruise ship visits to Disenchantment Bay, with and without 

observers, and aerial surveys flown at both Disenchantment and Icy bays, 3 May to 

20 July 2004........................................................................................................... 66 

Figure 24. An example of an aerial photograph with seal groups present................... 67

Figure 25. Map of the Icy Bay study area showing the aerial transect grid for the 

medium scale photogrammetric surveys................................................................ 68 

ix 
List of Tables 

Table 1. Summary of harbor seal counts (uncorrected) from the high-altitude 

photogrammetry in 2002 ........................................................................................ 47

Table 2. Bernoulli regression estimates for the zero-inflated, space-time Poisson model 

to examine the cell-based absence/presence (i.e., spatial distribution) of pooled 

seals....................................................................................................................... 65

Table 3. Poisson regression estimates for the zero-inflated, space-time Poisson model 

to examine the cell-based abundance of pooled seals........................................... 66

Table 4. Bernoulli regression estimates for the zero-inflated, space-time Poisson model 

to examine the cell-based absence/presence (i.e., spatial distribution) of motherpup pairs ................................................................................................................ 66

Table 5. Poisson regression estimates for the zero-inflated, space-time Poisson model 

to examine the cell-based abundance of mother-pup pairs.................................... 67

x 
1.0 Introduction 

1.0 Introduction 

Alaska is a major destination in 

cruise tourism, with the third highest share 

(8%) of the total world capacity ranking 

only behind the Caribbean (41%) and the 

Mediterranean (13%; CLIA 2005). The 

cruise ship capacity allotted to Alaska has 

nearly quadrupled since 1987, surpassing the 

Bahamas (6%), and current annual growth is 

8% compared to a slight decline averaged 

across the industry (CLIA 2005). The 

North American fleet in 2004 comprised 192 

ships, an 18% increase from 163 ships in 

2000; an additional 17 are projected by 2008 

(ICCL 2005). At least half of the summer 

visitors to Alaska, which is approaching a 

million annually (ADEC 2004), embark on a 

cruise (ADCED 2004). These statistics, 

combined with a growing interest globally in 

nature-based and cultural tourism, ecotourism, and adventure travel (Reynolds and 

Braithwaite 2001; WTO 2001), point to 

Alaska’s growing popularity among cruise 

tourists. This growth has prompted concern 

about the potential environmental impacts of 

cruise tourism in Alaska and whether it is 

environmentally sustainable. In particular, 

marine living resources and the local people 

who rely on them may be sensitive to the 

changes brought about by the presence of 

cruise ships. Marine mammals are some of 

the most conspicuous examples of 

potentially vulnerable species because they 

historically congregate in coastal habitats, 

such as tidewater glacial fjords, that are now 

popular destinations for cruise tourists. 

Harbor seals (Phoca vitulina 

richardii) in Alaska inhabit coastal and 

estuarine waters from Southeast, Alaska 

through the Gulf of Alaska to Cape 

Newenham in the Bering Sea. They haul 

out to rest, rear pups, and molt on rocky 

coastlines and outcrops, sandy beaches, and 

floating ice. Following population declines 

in the Gulf of Alaska (Pitcher 1990; 

Mathews and Kelly 1996; Frost et al. 1999; 

Jemison and Pendleton 2001; Small et al. 

2001) and most recently in Glacier Bay 

National Park (Mathews and Pendleton 

2006), it has become increasingly important 

to understand the factors that affect seal 

survival and recruitment. Ice emanating 

from tidewater glaciers serve as important 

pupping grounds for harbor seals from midMay to early July, and as molting platforms 

during August (Streveler 1979; Hoover 

1983). Whereas the largest terrestrial haulout sites rarely exceed several hundreds of 

animals, many glacial sites have ice fields 

that are used by thousands of seals (Withrow 

and Loughlin 1997; Withrow et al. 1998; 

1999a; 1999b; 2001). 

These seal aggregations have 

nutritional and cultural importance for 

Alaska Natives, such as those living in the 

Yakutat area, who have utilized sealing 

camps in Yakutat and Disenchantment Bays 

(Fig. 1) for many generations. Harbor seals 

were likely an important resource dating 

back to the earliest known settlements of the 

Yakutat Forelands – 1,100 years ago (Davis 

1996). Despite the importance of these 

seals, little is known of their trends in 

abundance or why the animals concentrate 

in ice fields in such large numbers. Glacial 

ice may function uniquely as both a refuge 

from land and marine predators and a 

reliable platform for resting and rearing 

young. 

Tour vessels were first reported in 

Disenchantment Bay (60°N 139°32'W) in 

1883, though the number of visits probably 

remained low during most of the 20th 

century (USFS 2001). More than a century 

later, in 1989, still fewer than 15 visits 

occurred per year (Kozie et al. 1996). About 

a decade later, in 2001, visits had increased 

10-fold to 157; ship visits continue to 

increase to the current level of 170 in 2005 

(NWCA; 2001-2005). This amounts to near 

daily visits from mid-May to September. 

1
Cruise ships typically venture at least as far 

north as Egg (Haenke) Island, ice and 

visibility conditions permitting, to afford 

passengers a close view of Hubbard Glacier 

(Fig. 1). As many as five ships, which can 

be nearly 1,000 feet (305 m) long and 100 

feet (30 m) wide, visit the bay on peak 

traffic days. Disenchantment Bay may 

experience further increases in ship traffic 

due to several factors: 1) expected increases 

in the cruise ship fleet; 2) an annual quota 

for cruise ship visits to nearby Glacier Bay 

(of 231 visits) with a daily quota of two 

ships; and 3) the rapid retreat of other 

tidewater glaciers (e.g., South Sawyer 

Glacier, Tracy Arm; D. Withrow, Alaska 

Fisheries Science Center, National Marine 

Mammal Laboratory (AFSC/NMML), pers. 

comm.), which, if the glaciers ground and 

stop calving ice into the water, may cause 

ships to divert elsewhere. 

Alaska Natives from the Yakutat 

Tlingit Tribe are concerned that the presence 

of cruise ships in Disenchantment Bay – 

which peak in numbers during pup rearing 

and persist through molting season – are 

having adverse impacts on the distribution 

and abundance of harbor seals. Many 

among the Tlingit Tribe consider cruise 

ships a source of disturbance that may be 

disrupting the seals’ normal behavior during 

the pup-rearing season, thus leading to 

reduced survival of offspring and a 

population decline. Evidence of a 

population decline comes from Yakutat seal 

hunters who believe that the availability of 

seals has declined over the past 10-15 years, 

as reflected by hunting trips that have 

progressively been less successful and have 

required more time (Yakutat Tlingit Tribe, 

pers. comm.). Hypothesized declines in seal 

numbers are consistent with trends in 

subsistence harvests by Yakutat hunters. 

Seal takes per capita in 2001 were only 38% 

of the 1993 levels, a steep decline (65%) 

from a peak in 1996 (Wolfe and Mishler 

1.0 Introduction 

1993; 1996; Wolfe 2001). Though there has 

also been a downward trend in harbor seal 

harvests for the entire Southeast Alaska 

region, the decline of Yakutat sealing was 

more than twice the regional average. Part 

of this trend could be attributed to decreases 

in hunting effort, but the number of 

households that use seal has remained 

consistently high, though falling slightly 

from 93% in 1993 to 85% in 2001 (Wolfe 

and Mishler 1996; 2001). Still, Yakutat 

reports one of the highest annual takes in 

Alaska (range: 138 [in 2002] to 764 [in 

1996]; Wolfe et al. 2003). It is clear that 

harbor seals are a valued resource for the 

Tlingit Tribe, one that they perceive has 

become less available over the period that 

cruise ship traffic has risen steeply. 

The historical traditions of the 

Tlingit Tribe – as reported by de Laguna 

(1972) – suggest that harbor seals were 

typically left undisturbed until pup rearing 

was underway and post partum females (and 

their young) were less prone to leave the 

area. However, contemporary estimates of 

subsistence hunting suggest that most seals 

are taken from March to May (Wolfe and 

Mishler 1993; 1994; 1995; 1996; 1997; 

1998; Wolfe and Hutchinson-Scarbrough 

1999; Wolfe 2000; Wolfe et al. 2002; 2003; 

2004), prior to and in the early stages of pup 

rearing. Seal takes consist largely of 

juveniles and adults though pups are 

sometimes targeted (Yakutat Tlingit Tribe, 

pers. comm.). 

There are no published findings on 

how seals on glacial ice respond when they 

are approached by vessels, though studies 

have been undertaken. In Muir Inlet, 

Glacier Bay, more harbor seals entered the 

water in response to smaller boats, such as 

kayaks, than to cruise ships, though the 

latter disturbed seals at greater distances 

(Calambokidis et al. 1985, unpub. ms.). In 

McBride Fjord, Glacier Bay, researchers 

found that seals entered the water more 

2
often and in larger numbers in response to 

kayaks than larger skiffs (Lewis and 

Mathews 2000). In Johns Hopkins Inlet, 

Glacier Bay, Mathews (1994) reported that 

harbor seals vacated ice floes at greater 

distances to cruise ships than boats about 

one-quarter the size. Similar results on 

harbor seals at terrestrial haul-out sites 

support the hypothesis that vessel type may 

be as important as approach distance in 

determining the outcome of seal-vessel 

interactions (Suryan and Harvey 1999; Lelli 

and Harris 2001). The sensitivity of animals 

to such factors may also differ depending on 

experience and their breeding or molting 

status. Suryan and Harvey (1999) found 

increasing levels of tolerance among harbor 

seals to repeated disturbance by small boats, 

and increasing vigilance and disturbance 

with number of pups present across three 

sites. That pregnant and post partum 

females appear more sensitive to disruptions 

(Newby 1973; Lawson and Renouf 1985) is 

likely one reason they tend to haul out at the 

edges of mixed groups or at separate nursery 

sites altogether (Jeffries 1982; Allen et al. 

1988; Thompson 1989). In Disenchantment 

Bay, potential sources of human disturbance 

to harbor seals are mainly the visitation of 

cruise ships, which occurs from mid-May to 

September, and subsistence hunting, which 

occurs mostly from March to August (Wolfe 

2001). Charter or private boats reportedly 

traverse the eastern coastline relatively 

infrequently to view the Hubbard Glacier, 

fish, hunt, or visit Egg (Haenke) Island. 

The focus of this study was to assess 

the potential disturbance of harbor seals in 

Disenchantment Bay by cruise ships that 

move through and near areas of floating ice 

where seals are present. The two working 

hypotheses were: 1) individual seals that are 

hauled out on floating ice respond 

behaviorally to approaching vessels (i.e., by 

becoming agitated or entering the water); 

and 2) the population of seals in 

1.0 Introduction 

Disenchantment Bay responds to vessels 

through shifts in spatial distribution and/or 

by leaving the haul-out area. Of particular 

importance was evaluating the potential 

disturbance of nursing females and pups, as 

they have been shown to be particularly 

sensitive to disturbance at terrestrial sites 

(Newby 1973; Lawson and Renouf 1985; 

Suryan and Harvey 1999). To test these 

hypotheses, the potential response of harbor 

seals to vessel traffic was assessed at three 

spatial and temporal scales: 1) fine scale – 

daily observations of individual seal 

behavior in relation to vessel approach 

distance and angle, 2) medium scale – 

weekly aerial surveys of seal distribution 

and relative abundance in Disenchantment 

Bay, and 3) large scale – monthly aerial 

photographs of regional seal distribution and 

total abundance at glacial haul outs of the 

greater Yakutat area (i.e., in areas with and 

without [Icy Bay] cruise ships). 

This report supersedes and updates 

the preliminary report issued in February 

2003. New results have been integrated 

with summaries of previous findings, most 

of which appear here unchanged. For better 

clarity and organization, starting after a 

discussion of the study area, the report has 

been split into three sections to better reflect 

each of the studies conducted at different 

spatial and temporal scales. The objective 

of the first draft report was to summarize the 

field activities in 2002 and the preliminary 

findings for the seal behavior observations 

that were conducted from cruise ships. 

Since that report, we have continued to 

process, extract, and analyze statistically the 

distribution and abundance data from the 

aerial imagery. In this final report, we add 

the latest findings from both the mediumscale aerial surveys flown over 

Disenchantment Bay at roughly weekly 

intervals, and the large-scale 

photogrammetry conducted at monthly 

intervals. Future findings from additional 

3
studies conducted in 2004 and 2005 will be 

submitted directly to peer-review for 

publication. These complementary studies 

and the ongoing analyses are summarized in 

Appendix 2 of this report. 

An overarching goal of this study is 

to produce reliable information on the 

behavior, distribution, and abundance of 

harbor seals in areas frequented by tour 

vessels to assist tribal representatives and 

the cruise ship industry in their mutual 

desire to maintain healthy populations of 

harbor seals in the ecosystems represented 

by tidewater glacial fjords. 

2.0 Study Area 

2.1 Overview of Past and Present 

Disenchantment Bay (Tlingit: 

Ateix’) is characterized by two tidewater 

glaciers, Turner (Sít’ kusa) and Hubbard 

(Sít’ tłen), of which the latter is the largest 

of only eight Alaska tidewater glaciers that 

are currently advancing (out of an estimated 

36 total in 2005; JKJ and D. Withrow, 

AFSC/NMML, unpublished data; Long 

1992; Trabant et al. 2002; Fig. 1). In 

addition to its massive size (123 km long 

with an 11 km calving face), Hubbard 

Glacier has attracted steadfast interest for 

other reasons: 1) for several decades, it has 

threatened to permanently block the 

entrance to Russell Fjord putting at risk a 

local fishery and the Yakutat Airport 

(Lorenz 1994); 2) it has a two-century 

written and pictorial record dating back to 

the earliest European visitors (Barclay et al. 

2001); and 3) its geological history is 

dynamic, distinctly cyclical, and seemingly 

runs contrary to global climate changes 

(Trabant et al. 2002). Historical accounts 

coupled with scientific research since 1890 

(Russell 1891) provide evidence of three 

major expansions (and retreats) of Hubbard 

Glacier in the last 8,000 years. At the time 

of the earliest recorded accounts (Malaspina 

2.0 Study Area 

in 1791), Hubbard Glacier was at or nearing 

its minimum extent. It is currently readvancing toward the mouth of Yakutat 

Bay, a distance of 60 km, where it last 

stopped ca. 1,000 years ago (Barclay et al. 

2001). At that time, when Hubbard Glacier 

was calving ice into the open ocean, the 

earliest known settlements of the Yakutat 

Forelands area were already established 

(Davis 1996). The role of harbor seals in the 

local culture and ecosystem at that time is 

unknown, but it is clear that a nearby 

protected embayment with floating ice (i.e., 

Yakutat Bay) would have been much 

smaller or may not have existed. Malaspina 

Glacier, which would have been located 

near the far western flank of the calving face 

of Hubbard, may have been retracted 

enough to provide larger ice-filled 

embayments (D. Barclay, pers. comm.). 

The marine environment of 

Disenchantment Bay comprises some 70 

km2, reaches depths of 260 m (850 ft), and 

is bounded by both steeply sloping 

shorelines and a complex system of 

submarine moraines which extend south into 

Yakutat Bay (Fig. 1). At the surface, the 

bay is dominated by floating ice emanating 

southward from the two tidewater glaciers. 

Ice coverage is non-uniform and varies 

widely – from solidly packed areas with no 

open water visible, as often occurs in the 

northern area in front of and between the 

glaciers, to single floes surrounded by 

expanses of water. At present, 

Disenchantment Bay is still connected to 

Russell Fjord by a narrow channel (Fig. 1), 

so both strong tidal currents and the wind 

cause the ice field on which seals haul out to 

shift rapidly and disperse in the bay. 

Glaciologists expect that the advancing 

Hubbard Glacier will permanently block this 

channel in the near future, as has already 

occurred for short periods in 1986 and 

during this study in 2002. In 2002, tidal 

exchange with Russell Fjord was restricted 

4
2.0 Study Area 

R

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s

e l l 

F j o

r d 

H u b b a r d 

T u r 

G l a c i e r n e r G l a c i e r

D i s e n c h a n t m e n t 

B a y

Tongass National Forest

Wrangell St. Elias National Park 

Tongass National

Forest 

Wrangell St. Elias 

National Park 

Y a k u t a t B a y 

Canada

U.S. 

Pt. LaTouche 

Bathymetry (m) 

0 

260 

­

0 2.5 5 10 

km 

Egg I. 

Figure 1. Map of the Yakutat Bay area showing the two tidewater glaciers, Turner and Hubbard. 

Bathymetry data was acquired from the C-CAP database (NOAA Coastal Services Center 1997) 

and is shown in gradations of blue, from light (shallow) to dark (deep; see legend). The study 

area was north of Point LaTouche. The extent of glaciated terrain (light blue) was derived from a 

1993 satellite photo. The location of the terminus of Hubbard Glacier was mapped in early June 

2002 as part of this study (D. Seagars, USFWS). 

from June to mid-August after Hubbard 

Glacier surged and blocked off the inlet to 

the fjord. This effectively created Russell 

Lake which persisted until the moraine dam 

was breached by rising water on 14 August 

2002. Despite this anomaly, the densest 

concentration of seals was found – prior to 

and during the formation of the ice dam, and 

right after it breached – in the northwest area 

of the bay (NMML, unpublished data; Fig. 

1). Aerial sampling conducted in 2004 and 

2005 will be compared with 2002 to assess 

whether ice conditions during the Russell 

Fjord blockage were typical or not. 

Whereas the general distribution of 

harbor seals in Disenchantment Bay is fairly 

well known, the numbers of seals using the 

area is less clear. On ice between the two 

glaciers is historically where Native hunters 

have observed the densest aggregations of 

seals, and also where seals were 

concentrated during surveys by the National 

Marine Mammal Laboratory (NMML) in 

1993, 1997, and 2001. The earliest 

historical records from Disenchantment Bay 

point to a larger population of seals in the 

past. In mid-June 1899, Grinnell (1995) 

estimated that among three sealing camps 

about 1,000 seals had been hunted to allow 

the Tlingit Tribe to secure their annual 

supply of oil. In mid-July 1886, Schwatka 

reported that as many as 1,500 seals had 

been taken (Schwatka 1891 in de Laguna 

1972). These figures represent about four to 

five times the contemporary subsistence take 

(Wolfe et al. 2002) and roughly half of the 

5
most recent minimum population estimate 

(this study). Though we cannot know the 

accuracy of these historical estimates, 

suspected shifts in the environment may 

lend further support to larger seal 

populations in earlier times. Traditional 

knowledge of the Tlingit Tribe suggests that 

calving rates of Hubbard and/or Turner 

Glaciers were declining near the end of the 

19th century, thus affecting both the location 

of optimal hunting grounds and patterns of 

use of established sealing camps (de Laguna 

1972). Under a decline in ice coverage, the 

ice habitat would have been reduced and 

may have supported a smaller seal 

population. Such declines in calving rates 

and ice coverage are consistent with a 

reversal of the Hubbard Glacier from retreat 

(more calving) to advance (less calving) 

though there is debate among glaciologists 

about whether the reversal could have 

occurred as late as the latter half of the 19th 

century (Barclay et al. 2001; Trabant et al. 

2002). 

Despite more sophisticated 

techniques of enumerating seals (e.g., aerial 

surveys using photography), contemporary 

estimates of the number of seals hauled out 

on floating ice are still prone to biases due to 

the difficulty of counting animals over large 

areas of scattered, moving ice with no 

topographical reference. Moreover, the 

seals that are visible on the ice during an 

overflight represent only a fraction of the 

total population since many remain in the 

water. So, even the most accurate counts 

must be corrected upward by some factor 

that integrates the varying propensities of 

seals to haul out under varying 

environmental conditions. In 

Disenchantment Bay, Kozie et al. (1996) 

derived uncorrected estimates for the 

pupping period (mid-May) of about 750 

harbor seals. During the August molt, 

estimates range from 467 (Kozie et al. 1996) 

to 1009 seals (Withrow et al. 1997). 

2.0 Study Area 

Estimates using more accurate techniques 

for counting (e.g., 100% coverage via highaltitude, high-resolution photographs) 

yielded an uncorrected August count of 

1,778 seals (AFSC/NMML, this study). 

Still, it is unknown to what extent the seals 

in Disenchantment Bay use other areas in 

the greater Yakutat Bay area or mix with 

other significant nearby populations (e.g., 

Icy and Dry Bays). Nine radio-tagged 

harbor seals in Southeast Alaska (South 

Sawyer Glacier, Tracy Arm) migrated 

considerable distances between haul-out 

bouts on the ice. The seals spent more than 

half of their time in areas outside the fjord 

(100 km by water), especially by the onset 

of pupping at which time all tagged seals 

were outside the fjord; the two-thirds that 

returned stayed for only brief visits (Jansen 

et al. 2001). 

2.2 Defined Area for this Study 

The study area was geographically 

defined as the region north of Point 

LaTouche, which essentially marks the 

boundary between Yakutat and 

Disenchantment Bays (Fig. 1). Though 

some ice floes were scattered to the south of 

this boundary, the densest patches were 

nearly always north of this boundary, 

especially in the upper reaches of the bay 

where the vast majority of harbor seals were 

located. Elevated concentrations of ice and 

seals were sometimes observed in Yakutat 

Bay, and thus shipboard observations 

sometimes occurred there. The mediumscale aerial surveys were confined to 

Disenchantment Bay during May, but as ice 

increased through the season and extended 

into Yakutat Bay, observers began flying a 

single transect south of Point LaTouche in 

areas of dispersed ice. The large-scale aerial 

photography in Disenchantment Bay was 

confined to the area north of Point 

LaTouche. In Icy Bay, the surveys were 

conducted north of Kichyatt Point (Fig. 2). 

6
2.0 Study Area 

G u y o t 

G l a c i e r 

Y a h t s e

G l a c i e r 

Tyndall

Glacier 

Wrangell St. Elias 

I

National Park 

c y B a y 

T a a n F j o r d 

Kageet Pt 

Kichyatt Pt 

Wrangell St. Elias 

National Park 

­

0 2.5 5 10 

km 

Figure 2. Map of Icy Bay area showing the three tidewater glaciers, Guyot, Yahtse, and Tyndall. 

The study area was north of Kichyatt Point. The extent of glaciated terrain (stippled) was

derived from a 1993 satellite photo (NOAA Coastal Service Center 1997). 

2.3 Environmental Conditions – in 

General and During the Study 

2.3.1 Meteorology 

The climate of the Yakutat Forelands 

is distinctly maritime. The surrounding 

4,000+ m (13,000+ ft) peaks, in conjunction 

with exposure to moisture-laden air from the 

Gulf of Alaska (GOA), contribute to one of 

the highest average rainfalls in Alaska (330 

cm; NOAA-NCDC 2002). The nearby 

glaciers exert a pronounced influence on the 

climate particularly when low pressure 

systems in the GOA cause steep pressure 

gradients which draw cold air down the 

glaciers causing localized cloudless 

conditions. Cloudless or partly cloudy skies 

immediately downwind of Hubbard and 

Turner Glaciers are often in sharp contrast to 

dense clouds and stormy conditions just 

outside Disenchantment Bay (JKJ and SPD, 

pers. obs.). Overall, clouds and fog are 

common around the Yakutat area throughout 

the year with mean sky cover averaging 

greater than 80% (NOAA-NCDC 2002). 

During the study, weather conditions 

in Disenchantment Bay were monitored 

using a HOBO weather station (Onset 

Computers, Bourne, MA, USA) installed on 

Egg (Haenke) Island (Fig. 1). From 1 May 

to 2 August 2002, data on air temperature, 

barometric pressure, relative humidity, and 

wind speed were collected at 1-minute 

intervals which were then averaged into 30-

minute observations. Sampling was 

interrupted from 26 June to 12 July due to a 

circuit defect in the weather station causing 

a power drain; no data on precipitation were 

7
2.0 Study Area 

25 

20 

1.6 

1.4 

1.2 

15

1.0 

0.8 10 

0.6 

5 

0.4 

* 0 0.2 

* * * *

*

*

0.0 * *** * ** * * * * 

May Jun Jul Aug 

Date 

Cumulative rainfall (0700 - 1300 h) 

Maximum gust (0700 - 1300 h) 

Wind S

peed (kn

ots) 

Rainf

all (in) 

Figure 3. Indices of rainfall and wind speed for Disenchantment Bay, May to early August 2002. 

Indices were calculated for the 6-hour period preceding aerial surveys, which occurred on days 

marked with an asterisk. Wind speed was measured in Disenchantment Bay; rainfall was measured 

at the Yakutat Airport (NOAA-NCDC 2002). An instrument malfunction caused the data gap in 

wind speed. 

collected due to a sensor malfunction. We 

used precipitation data collected by 

NOAA’s National Weather Service in 

Yakutat (NOAA-NCDC 2002) as a proxy 

for rainfall in Disenchantment Bay (Fig. 3). 

Of primary interest were measures of 

rainfall and wind speed (Fig. 3) because 

increased levels are known to reduce the 

propensity of seals to haul out (Hoover 

1983; Boveng et al. 2003). 

Overall conditions during the study 

were unusually dry: for May, June, and 

July, departures from the 50-year average 

rainfall (22.8, 15.9, 20.6 cm, respectively) 

were -14.7, -2.2, -5.8 cm, respectively. 

Rainfall for May (8.1 cm) approached the 

record low (6.9 cm; 1951-2001; NOAANCDC 2002). Daily temperatures in the bay 

in early May were typical, fluctuating 

between the low 30s at night and low 40s 

(°F) by day. From 16 to 21 May, peak daily 

temperatures in the bay were above normal 

reaching 65°F on 20 May; the monthly 

maximum at the Yakutat Airport was 

reached the same day (76°F; near the 78°F 

record in 1963). June was characterized by 

daily temperatures ranging from the high 

30s to the high 40s (°F) frequently peaking 

above 50°F after 12 June. Daily 

temperatures in July were generally from 

40°F to 50°F with peak temperatures 

approaching 60°F from 31 July to 2 August 

(the last day of observations). Maximum 

daily wind gusts, measured in 

Disenchantment Bay, ranged from about 3 

to 16 knots during the study (Fig. 3). 

Because of minimum visibility 

requirements for flights, our surveys were 

conducted under better than average 

conditions (e.g., several flights had to be 

rescheduled due to rain, poor visibility, 

and/or high winds). This served to largely 

8
control for weather effects in the analysis. 

Data on hourly precipitation (NOAA-NCDC 

2002) and wind speed (this study) were 

summed for the 6, 12, and 24 hours 

preceding each aerial survey to be used as a 

covariate in the statistical modeling of seal 

distribution and abundance (Fig. 3). 

2.3.2 Ice Conditions 

Ice floating in Disenchantment Bay 

emanated from both Hubbard and Turner 

Glaciers though the vast majority was 

derived from the former. Turner, with only 

a third of the calving face (3-4 km) of 

Hubbard, is retreating and becoming 

grounded along its north and south flanks 

(Fig. 1). Its contribution of calved ice to the 

ice field is also likely diminishing. Though 

calved ice can be large, exceeding 15 m 

across and > 5 m above water (termed 

icebergs), most ice in Disenchantment Bay 

is considerably smaller (termed bergy bits [< 

15 m across], growlers [< 5 m], and brash 

[< 2 m]). Dispersing south from the glaciers 

on wind and tidal currents, most icebergs 

melt in a few days; bergy bits, growlers, and 

brash usually melt in less than a day (Long 

1992). Ice in the bay thus indicates active, 

daily calving, primarily by Hubbard Glacier. 

For this study, ice cover was defined 

as the percent of area that was occupied by 

ice that was greater than or equal to 2 m at 

its longest axis (i.e., growlers or larger). 

Hoover (1983) found that seals in Aialik 

Bay hauled out in peak numbers on ice that 

was 1-3 m across; parturient females 

preferred ice that was > 5 m. Further, we 

categorized ice cover into three types (or 

zones): scattered ice (1-3 tenths ice cover), 

intermediate ice (4-6 tenths), and dense ice 

(7-10 tenths). See section 3.2.1 for details. 

Ice coverage in Disenchantment Bay 

varied dramatically during the study. In 

May, the ice-covered area (ICA) for 

scattered ice or greater varied between 28 

and 56 km2 (ca. 65% of the total 70 km2 

2.0 Study Area 

area; Fig. 4). During June, ICA peaked at 

approximately 64 km2

 (~ 90%) and then 

declined through July to a minimum of 

about 5 km2

 (~ 7%) on the last survey on 4 

August 2002. In general, ICA was 

dominated by scattered ice, representing 25-

45 km2

 (~ 70-80% in proportion); 

intermediate ice rarely exceeded 15 km2 (20-

30%) and dense ice was typically less than 3 

km2 (<1%). Patterns in the total ICA were 

driven largely by variation in the area 

covered by scattered ice. It is unclear 

whether the blockage of Russell Fjord, and 

the preclusion of tidal currents through the 

channel near Gilbert Point, significantly 

affected ice cover. If ice cover had 

remained high after the moraine dam had 

formed in mid-June it would point to 

reduced tidal circulation, an increased 

residence time of ice in the upper bay, and 

ultimately greater ice cover. But the steady 

decline of ICA despite near zero tidal 

exchange with Russell Fjord (from late June 

to the end of the study) suggests that largerscale factors were driving ice coverage in 

the bay. An annual pulse in the calving rate 

of the two glaciers, during peak spring runoff (May-June), likely produced the 

observed seasonal pattern in ice cover. 

2.3.3 Cruise Ships 

In 2002, 168 cruise ship visits to 

Disenchantment Bay were scheduled from 

14 May to 24 September (NWCA 2002). Of 

those, 105 visits occurred during the study 

and 56 complete navigation tracks were 

recorded using portable global positioning 

systems (GPS). For this study, the last ship 

was tracked on 1 August. Due to the typical 

7-day duration of cruises – which embark 

passengers on weekends from ports 2-3 days 

travel from the study area – cruise ships 

tended to arrive midweek (e.g., 81% on 

Tuesday, Wednesday, or Thursday; Fig. 5). 

Visits were less frequent late-week (18% on 

Friday or Saturday) and only one visit (1%) 

9
2.0 Study Area 

Area of ice c

o

v

er (

s

q k

m) 70 

60 

50 

40 

30 

20 

10 

0 

scattered 

intermediate 

dense 

total 

Total area of Disenchantment Bay: 70 sq km 

May Jun Jul Aug 

Date 

Figure 4. Estimated area of Disenchantment Bay (sq km) represented by different ice cover types, 

scattered (1-3 tenths), intermediate (4-6 tenths), and dense (7-10 tenths), and all types combined (i.e., 

ice-covered area [ICA]) from 3 May to 4 August 2002. Estimates of ice cover were averaged within 

grid cells (when n > 1) and the areas of cells with each type of ice cover were summed (see Section 

3.2.1), and then scaled upward (proportionately) based on the percent of the study area that was 

sampled on a given day. 

occurred early-week (Sunday or Monday). 

About half of the visits (46%) were without 

other cruise ships present; 42% overlapped 

with one other vessel (for an average of 1 

hour) and the remaining overlapped with 

two (11%) or three (1%) other vessels. As 

ships approached Point LaTouche from the 

south, they typically reduced speed from ca. 

12 to 6 knots, or lower if ice was in the 

immediate area. Vessel speed north of Point 

LaTouche ranged from less than 1 to 6 knots 

depending on visibility and ice which varied 

considerably across the bay. Thicker bands 

of ice would cause ships to temporarily slow 

to less than 2 knots. 

The durations of visits varied widely 

and were dependent partly on ice conditions 

and visibility (Fig. 6). It was apparent that 

vessels had varying criteria for the type 

and/or size of ice they would negotiate to 

afford passengers better views of the two 

glaciers. Vessel captains and pilots were 

less inclined to penetrate Disenchantment 

Bay when larger ice spanned the mouth of 

the bay, usually resulting in shorter visits. 

Hampered visibility also reduced visit 

durations especially if Hubbard Glacier was 

obscured (Fig. 6; see visits in early July 

during persistent fog). Under such 

conditions, ships would rarely venture north 

of Point LaTouche. Based on GPS tracks 

collected on cruise ships from 14 May to 1 

August 2002 (N=56), the average period that 

vessels were north of Point LaTouche (i.e., 

10
2.0 Study Area 

SU M T W TH F S SU M T W TH F S 

12-25 May 

0 

1 

2 

3 

4 

26 May - 8 June 

0 

1 

2 

3 

4 

9-22 June 

0 

1 

2 

3 

4 

23 June - 6 July 

0 

1 

2 

3 

4 

7-20 July 

0 

1 

2 

3 

4 

21 July - 3 Aug 

0 

1 

2 

3 

4 

28 April - 11 May 

Number of Ships 0 

1 

2 

3 

4 

5 

Ships w/o Observers 

Ships with Observers 

Visual/Video Survey 

Photo Surveys 

Day of Week

Figure 5. Distribution of cruise ship visits to Disenchantment Bay, with and without observers, 

and aerial surveys, 28 April to 3 August 2002. Surveys were also flown on 4 August (visual/video) 

and 14-15 August (photogrammetry). The photogrammetry surveys of Icy Bay were flown on the 

same day as Disenchantment Bay except for those flown on 4 May and 15 August. 

11
2.0 Study Area 

Cruise Ship Visits 

0 

10 

20 

30 

40 

50 

60 

70 

80 

Cruise Ship Frequency

(15 min intervals) 

0 

10 

20 

30 

40 

Abundance Rank (Aialik Bay) 

2 

4 

6 

8 

10 

% Hauled Out (Tracy Arm) 

0 

10 

20 

30 

40 

50 

6 0 D isenc h a n tm ent B ay 

A ia lik Ba y 

T ra c y A rm 

1 4 M a y 

1 Ju n e 

1 J u ly 

1 A ugus t 

6 :00 8 :0 0 10:00 12:00 1 4 :00 1 6 :00 18:00 

T im e of d a y (h ) 

Figure 6. Haulout behavior of harbor seals (top panel) in relation to the timing (bottom) and frequency (top) of 

cruise ship visits to Disenchantment Bay. Haulout behavior was measured at South Sawyer Glacier, Tracy Arm 

(proportion of seals hauled out by time of day [ADT]; Jansen et al. 2001) and Aialik Glacier (abundance rank by 

time of day; Hoover 1983). The horizontal bars indicate the timing and duration of cruise ship visits (N=86) for 

which data was collected directly (by GPS) or indirectly (by remote observation). For ships that stopped south 

of the study area, tick marks show the times that ships turned around (N=9). The timeline on the right axis, 

bottom panel, shows the temporal progression of visits from the first ship on 14 May to early August. 

inside the study area) was 2.17 hours (range: we assumed that harbor seals in this study 

0.25 - 3.98 hours). On average, ships exhibited similar behavior. We thus 

arrived at 1141 h (range: 0721-1541 h) and expected that the majority of harbor seals in 

departed at 1353 h (range: 0904-1721 h). Disenchantment Bay hauled out during 

An examination of the frequency of periods that coincided closely with cruise 

cruise ship visits by time of day revealed a ship visits. Direct studies of individual seals 

distinct diel pattern of visitation with a peak in Disenchantment Bay are needed to 

in the early afternoon (Fig. 6). At other confirm the extent of temporal overlap 

tidewater glaciers, harbor seals haul out in between hauled-out seals and ships. 

peak numbers also in the early afternoon, Tracking by GPS showed that cruise 

typically between 1200 and 1600 h (Aialik ships entered Disenchantment Bay while 

Bay: Hoover 1983; Tracy Arm: Jansen et al. favoring the eastern shoreline (by Point 

2001; Fig. 6). Given this consistent pattern, LaTouche; Fig. 7). In the early season (i.e., 

12
May and June), ships would sometimes use 

the area south of Egg (Haenke) Island, 

where open water often persisted, in order to 

maintain higher speed. Later in the season, 

as ice coverage diminished, cruise ships 

took more direct routes northward traveling 

directly up the middle of the bay, past the 

west side of Egg (Haenke) Island, to 

approach Hubbard Glacier to within 2 km (< 

1 nautical mile [nm]; Fig. 7). Regardless of 

whether ships stopped because of 

impenetrable ice or to maintain a safe 

distance from Hubbard Glacier, they would 

usually rotate at their northernmost point 

using side thrusters to enhance viewing for 

passengers. Most ships exited using the 

same route, though after a close approach of 

Hubbard a few ships (for which we do not 

have tracking data) would depart between 

Egg (Haenke) Island and the mainland. 

North of Point LaTouche, ships 

would regularly use a public address (PA) 

system, audible on most outer decks, to 

communicate programs to the passengers on 

the culture and natural history of the region. 

Most often ships would begin broadcasting 

prior to and at their deepest penetration in 

the bay (e.g., while rotating at their turnaround point). During land-based studies in 

2004, voices on ships’ PA systems were 

discernable and understandable at distances 

of at least 1.4 km (0.75 nm). Though 

beyond the scope of this study, we expect 

that such sounds are audible to seals at much 

greater distances and could be a source of 

disturbance. 

2.3.4 Other Potential Anthropogenic 

Disturbance 

Occasionally other watercraft (e.g., 

skiffs and day charters) were observed in the 

vicinity of Egg (Haenke) Island and in open 

areas to the south. Because these sightings 

were infrequent, usually involved a single 

boat, and rarely occurred in areas of thicker 

ice, we deemed the potential for disturbance 

2.0 Study Area 

– as a result of the mere presence or sound 

emitted by these smaller boats – to be very 

low. 

Subsistence hunting of seals, which 

is undertaken from small boats, could affect 

the distribution and abundance of seals. We 

do not expect that the direct effects of 

removing seals from the population would 

affect measurably the survey results on a 

given day (i.e., on short time scales). 

However, when hunting does occur, some 

level of incidental disturbance is expected, 

particularly as the report from a rifle might 

elicit a response causing seals to enter the 

water. We could only monitor the presence 

of smaller boats in Disenchantment Bay in 

the course of our aerial surveys or when 

observers were aboard cruise ships. This 

effort, though near daily, represents a small 

fraction of the time available to visit the bay. 

Moreover, it was impractical to track the 

movement of observed boats or attempt to 

surmise the purpose of such visits whether it 

be hunting or sightseeing. Short- and longterm effects of subsistence hunting on seal 

behavior or abundance are currently beyond 

the scope of this study. 

Aircraft, including the plane flying 

surveys for this study, might also cause 

disturbance. Few studies have systematically 

examined the effects of fixed-wing aircraft 

on harbor seals. In Muir Inlet, Glacier Bay, 

Streveler (1979) showed that seals did not 

enter the water in response to flights at or 

above 250 feet (N = 32 flights); less overt 

reactions were not studied. In our study, the 

incidence of aircraft other than our survey 

plane was low and such aircraft were usually 

operating at altitudes higher than 1,000 feet; 

however, on one occasion a plane was seen 

operating at less than 500 feet. In addition, 

the analysis of video directly below our 

survey plane did not reveal any overt 

reactions by seals though the observation 

window was short and reactions could have 

occurred in advance of or following an 

13
2.0 Study Area 

May June July 

Figure 7. Patterns of ship movement and residence time in Disenchantment Bay in 2002 (N = 56 cruise ships [of 105 total during study]). Shading of 

cells represent the cumulative time that visiting ships spent within that cell for each month, May, June, and July (including early August). Four 

distinct shades, from light to black, reflect increasing residence: < 5 min, 5-10 min; 10-20 min; > 20 min, respectively. 

14
overflight. Based on previous findings, 

albeit limited, and our own general 

observations in Disenchantment Bay, we 

conclude that it is unlikely that our aerial 

surveys elicited a significant response from 

seals, particularly one that would bias the 

results presented here. 

3.0 Three Spatio-Temporal 

Scales for Studying Harbor 

Seals 

3.1 Fine Scale: Observations of 

Individual Seal Behavior in Relation 

to Vessel Approach Distance 

3.1.1 Methods 

Shipboard observations were 

conducted from 14 May 2002, when the first 

cruise ship entered Disenchantment Bay, to 

1 August 2002 (Fig. 5), by which time we 

expected pups to have weaned. To ensure 

full coverage of vessels in the early season, 

arrangements were made to transport 

observers to all ships in May including those 

that did not embark pilots or cultural 

interpreters from Yakutat. From June to 

August, when there were more ships than 

observers on a particular day, higher priority 

was given to earlier ships provided the 

tender boat was scheduled. Portable GPS 

receivers were used to continually log the 

positions of ships during the observers’ 

visits. Observers were typically onboard for 

5-6 hours, which included at least 2 hours of 

transit to and from the ice field. 

Observations were made of seals 

hauled out on ice during the entire period a 

ship was within viewing range of animals, 

which was typically out to a maximum of 

800-1,000 m, depending on visibility. There 

were four possible observation posts 

onboard, each being described as some 

combination of port or starboard, and bow or 

stern. As many as three posts were occupied 

on a single cruise depending on the number 

of observers present. Observers noted 

whether ships were inbound toward 

Hubbard Glacier, rotating in place, or 

outbound toward Yakutat Bay. Efforts were 

made to first locate seal groups at varying 

distances and bearings from the ship to 

provide a behavioral contrast between near 

and distant animals. A seal group was 

defined as one or more animals hauled out 

on a single ice floe. 

Behavioral observations were 

recorded during 15-second intervals on data 

forms or by using a hands-free digital voice 

recorder. The time that a digital voice 

recorder was started was noted and recorders 

ran continuously during observations. 

Digital voice files were later downloaded, 

played back via sound editing software that 

allowed observers to assign times to their 

observations, and transcribed into a 

database. For each 15-second sample, 

observers recorded the distance and bearing 

(relative to the ship in 15° increments) to the 

group, total number of animals in a group, 

and the number of animals that exhibited a 

particular behavioral state (i.e., level of 

excitement) during the interval. The 

behavioral state of seals was recorded as: 1) 

resting - seal was motionless with head 

down, 2) alert - seal was stationary but had 

head up, 3) active - seal moved across the 

ice floe or interacted with neighbors, or 4) 

entered water - seal departed ice floe during 

observation period. Only the highest level 

of excitement was recorded for each seal 

(e.g., “enter water” was the highest 

excitement, “resting” was the lowest). 

Distances between ships and seals were 

estimated using laser rangefinder binoculars 

(Leica VectorTM, Ashbury International 

Group, Inc., Sterling, VA) or an 

inclinometer. Data on mothers and pups 

were recorded separately from other animals 

and independent of each other. Once chosen 

for observation, a seal group was observed 

continuously until the seals either passed 

15
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

abeam of the ship (for groups observed from 

the bow), entered the water, or passed out of 

observation range astern (for groups 

observed from the stern). 

For each group observed, additional 

data were collected on covariates such as ice 

coverage (estimated in tenths within a 50 m 

radius of the seal group), ice floe size 

(longest axis), and other potential sources of 

disturbance to the seals. Weather conditions 

were noted at the beginning of observations 

and whenever significant changes occurred 

thereafter. Appendix 3 shows the sampling 

guidelines observers followed. As a 

separate protocol, observers were sometimes 

stationed amidships to estimate distances to 

and size of seal groups abeam of the ship. 

These data will be used to calculate seal 

densities as a function of distance from the 

ship. 

In total, observers recorded data on 

76 of the 105 cruises (73%) that were 

scheduled to visit Disenchantment Bay 

during the study (Fig. 5). Complete 

navigational tracks were acquired from GPS 

units on most of these cruises. A total of 

772 seal groups were observed comprising 

6,008 15-second observations and a total 

effort of about 207 observer-hours. 

Observations were taken amidships on 52 

cruises and distances were estimated to a 

total of 1,796 seal groups. 

3.1.1.1 Analyses of Shipboard 

Observations 

The analyses presented in this report 

were based only on data collected during 15-

second observation periods while the ships 

were moving (as opposed to stopped or 

rotating in place). The data were further 

focused by considering only the forwardlooking (bow) observer positions and by 

eliminating a few observations for which 

distance or bearing was not recorded. These 

criteria produced a data set from 584 seals 

observed in 307 groups. 

Of the four behavioral responses 

recorded, entering the water was likely to 

have a stronger relationship to any potential 

longer-term impacts on the seals’ vital rates 

than the other responses (resting, alert, or 

active). Also, analysis of the water entry 

response was simpler because it involved 

just one transition, from on ice to in the 

water, whereas the other responses could 

include reverse transitions and transitions 

between multiple behavioral states (e.g., a 

sequence recorded as resting, alert, resting, 

active, alert, on consecutive 15-second 

observation intervals). Therefore, we have 

focused on “entering the water” as the 

response variable. This choice allowed 

assignment of unique identifiers to all seals 

in the data set, even though the data had 

been recorded simply as counts of the 

numbers of seals within each group 

displaying the four behavioral responses. 

The seals were given individual identifiers 

by numbering the individuals within a 

group; the first to enter the water was 

numbered “1", the second numbered “2", 

and so on. Remaining seals that did not 

enter the water while under observation 

could be numbered arbitrarily because they 

all had identical behavior records (when 

considering only the water entry response). 

Representing the data in this way, there were 

5,344 records (15-second observations) from 

the 584 seals. Each record included the seal 

and group identifiers, the start and stop 

times of the 15-second interval, the response 

(0 if the seal stayed on the ice, 1 if the seal 

entered the water), and the explanatory 

variables (“covariates”): distance from the 

ship to the seal, bearing from the ship to the 

seal, seal group size, and type of seal 

(mother, pup, or other). 

3.1.1.2 Statistical Modeling of 

Behavioral Responses 

The data we described above are 

“time to event” data with censoring. The 

16
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

censoring occurred whenever a seal was lost 

to observation before entering the water, 

which occurred, for example, when the seal 

passed abeam of the ship or when the 

shipped stopped its forward progress while a 

seal was being observed. For censored time 

to event data, the Cox proportional hazards 

model is a natural and widely used 

technique for estimating the effects of 

covariates on a response variable (Therneau 

and Grambsch 2000). In such analyses, the 

response is often death of the subject under 

observation, which is why this type of 

analysis is commonly called “survival 

analysis”, but the technique is equally 

applicable to other types of binary censored 

outcomes, such as a seal entering the water. 

Although the basic Cox model assumes 

linear relationships and time-constant 

covariates, we used semi-parametric 

extensions of the Cox model that allowed 

the data to suggest the functional form of the 

covariate effects and that allowed for timedependent covariates such as distance from 

the seal to the approaching vessel (Therneau 

and Grambsch 2000). We used S-Plus® 

version 6.1 for Windows (Insightful Corp., 

Seattle, WA) for all Cox regression 

modeling. 

The Cox model is ideal for 

expressing covariate effects in terms of 

relative risk. For example, a subject with a 

value of 10 units for covariate A might be 

found to have twice the risk of the response 

outcome as a subject with 15 units of A. 

However, the absolute risk (e.g., What is the 

risk that a subject with 10 units of A will 

experience the outcome?), is not a product 

of the Cox model. For this initial analysis, 

we computed simple proportions of seals 

under observation entering the water for 

each of several distance bins as an 

approximate measure of the absolute risk. 

We are currently examining other 

statistical frameworks, such as a repeated 

measures analysis on ordered categories 

(McCullagh and Nelder 1994), which have 

recently been used to test for disturbance 

effects on wildlife using a sequence of 

ordered responses from least to most 

disturbed (Lawler et al. 2005). For our 

study, such a framework would allow for 

testing simultaneously relationships between 

the frequency of harbor seal behaviors, from 

“head up” to “entering the water”, and the 

vessel and environmental variables collected 

during cruise ship approaches. 

3.1.2 Results 

A Cox regression indicated that 

neither group size nor seal type was 

significantly related to the risk of seals 

entering the water (P > 0.3). Distance and 

bearing from the vessel, however, were 

highly significant explanatory variables for 

that risk. Figure 8 shows the functional 

form of the relationship with varying 

approach distance, obtained using a 

penalized smoothing spline (Therneau and 

Grambsch 2000). The Cox regression 

results are in terms of relative risk; to 

interpret Figure 8, it is easiest to compare 

two points. For example, at a distance of 

about 500 m, the effect curve begins to rise 

steeply. Because the vertical axis is on a 

natural-log scale, this point corresponds to a 

risk of e0.5 = 1.6. Comparing this to the 

scenario at very small distances, say less 

than 100 m, where the curve has a value of 

about 3.7, indicates that a seal approached at 

less than 100 m is about e3.7/e0.5 = 25 

times more likely to enter the water than a 

seal approached at 500 m. Beyond about 

600 m, there appeared to be very little effect 

of the ship’s approach, though the 

confidence intervals expanded rapidly 

because of the relatively small number of 

observations at large distances. 

Figure 9 shows the effect of 

variations in bearing angle on the risk of 

seals entering the water. Relative to a base 

risk of e0 = 1 when a seal was directly 

17
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

Log Haz

ard 

-2 

4

2

0

-4

-6

0 500 1000 1500 2000 

Distance (m) 

Figure 8. Relative risk, expressed as the logarithm of the hazard, of a harbor seal entering the water 

(abandoning its ice haul-out platform) in response to varying distances of approach by cruise vessels 

in Disenchantment Bay, Alaska. Approximate 95% confidence limits are shown by the thin curves. 

The observation distances are marked by the “rug fibers” plotted at the bottom. 

abeam of the observer (90 degrees), the risk 

of a seal entering the water when 

approached dead ahead of the vessel was 

about e1.3 = 3.7 times greater. The risk 

appeared to be considerably lower for seals 

observed aft of the observer’s position on 

the bow, but again the confidence intervals 

increased rapidly because of small sample 

size. 

Because of the potential for 

interactions between distance and bearing 

angle (i.e., the response to distance may vary 

with the bearing), we investigated the shape 

of the response surface over the two 

variables simultaneously. This was not 

possible to do within the Cox regression 

framework alone. Instead, we fit a Cox 

regression with no explanatory variables and 

then used a generalized additive regression 

(Hastie and Tibshirani 1990) to explore the 

relationship between distance, bearing angle, 

and the residuals from the Cox regression. 

We found there to be no significant 

interaction between distance and bearing. 

That is, the increase in the risk of a seal 

entering the water with decreasing bearing 

(from 90°[abeam] to 0°[ahead]) was the 

same across the range of distances (from 0 

to 1,000 m). This indicated that seals 

responded to the approach of the ship, rather 

than how visible it was; for example, a ship 

viewed from directly in front would appear 

smaller (and be less visible) than one viewed 

from abeam. That is, seals entered the water 

at shorter distances when ships were bearing 

down even though the ships appeared 

smaller. 

18
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

1 

0

Log Hazard -1 

-2 

-3 

0 15 30 45 60 75 90 105 120 

Bearing (degrees from dead ahead) 

Figure 9. Relative risk, expressed as the logarithm of the hazard, of a harbor seal entering the 

water (abandoning its glacial ice haul-out platform) in response to varying bearing angles during

approach by cruise vessels in Disenchantment Bay, Alaska. Approximate 95% confidence limits are 

shown by the thin curves. The observation bearings are marked by the “rug fibers” plotted at the 

bottom, which were jittered to better illustrate the relative sampling densities at the 15 degree 

measurement increments. 

Figure 10 shows estimates of the 

proportions of seals that entered the water, 

in 10 distance bins of 100 m width. These 

estimates were derived from the 526 seals 

(279 groups) that either entered the water 

during observation or passed abeam of the 

ship while still on the ice; seals that were 

lost to observation for other reasons (e.g., 

ship stopped moving) were not included. 

Each proportion was calculated as the 

simple ratio of the number of seals that 

entered the water at distances that fell within

the 100 m-wide bin, divided by the total 

number of seals that were observed at 

distances within the bin. These values

provide a means of translating the purely 

relative (i.e., without units) values of the 

Cox regression into an absolute measure of 

the risk of water entry as a function of 

approach distance. Still, we emphasize that 

these measures are only approximations 

because they do not account explicitly for 

the censored nature of the proportion data 

(i.e., the seals that passed abeam of the ship 

and those that were lost to observation do 

not contribute to the measure), they do not 

adjust for the simultaneous effect of bearing

angle, and they do not account for the 

amount of time the seals were “exposed” to 

the ship in each distance bin. Despite this

approximation, the estimates in Figure 10 

were qualitatively similar to the results of

19
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

Proportio

n enterin

g w

ater Proportio

n enterin

g w

ater

1.0

0.8

0.6

0.4

0.2

0.0

0 100 200 300 400 500 600 700 800 900 1000

Distance (m) 

Figure 10. Estimates of the proportions of harbor seals entering the water in response to varying 

approach distances (in 100 m bins) by cruise ships in Disenchantment Bay, Alaska. Approximate 

95% confidence limits (Agresti and Coull 1998) are shown. Note that a given proportion 

represents only the fraction of seals that entered the water (of those observed) within the relevant 

distance bin (i.e., a proportion does not represent the number of seals that have accumulated 

from bins of greater approach distances). The 100 m bins are represented at the midpoint (i.e., 

the symbol for the 100-200 m bin is plotted at 150 m). 

the Cox regression for distance (Fig. 8). In 

general, there appeared to be little waterentry response by seals to vessels at 

distances greater than about 500 m, but there 

was a strong increase in the probability that 

a seal would enter the water when 

approached at distances of less than 400 m. 

That the absolute response by seals appeared 

to occur at smaller distances than the 

relative response may be a reflection of the 

smoothing parameter used in the Cox 

regression, as well as a reflection of the 

aforementioned limitations for 

approximating absolute risks. 

Because the estimated proportions of 

seals entering the water when approached 

within 100-200 m neared 0.75 (Fig. 8), we 

conclude that a clear majority of seals 

approached by ships at 200 m or less were 

sufficiently disturbed to enter the water. 

3.1.3 Discussion 

The analyses of the fine-scale studies 

presented here indicate that harbor seals in 

Disenchantment Bay respond to the 

presence of cruise ships. Harbor seals 

altered their normal behavior in the 

immediate presence of ships by vacating ice 

floes with increasing frequency at approach 

distances less than 500 m (± 100 m). 

Mothers and pups showed no differences in 

the distance or bearing to vessels at which 

they were disturbed compared to other seals. 

Further analysis of the data collected in 

2002 will be used to explore the suite of 

covariates that may influence the potential 

responses of seals to vessels, including 

weather conditions and recent patterns of 

vessel traffic in Disenchantment Bay. 

Inclusion of these other covariates may alter 

slightly the values or functional form of the 

20
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

covariates analyzed in this report. The 

qualitative form and the general magnitude 

of the influence of approach distance, 

however, are likely to be robust features that 

will not change significantly under 

refinements to the analysis. At the medium 

and large scales, we expect that the 

abundance and spatial analyses planned for 

the aerial survey data will address what 

proportion of the population is likely to be 

disturbed by ships and whether or not these 

seals (both within and outside the ship 

traffic corridor) respond by hauling out less 

often or by altering their distribution. 

The results presented here are 

consistent with Calambokidis et al. 1985 

(unpub. ms.) who found that an increasing 

proportion of harbor seals in Glacier Bay 

vacated ice floes with decreasing distance to 

cruise ships under 500 m. On average, more 

than 50% of the seals entered the water at 

distances to ships of less than about 300 m, 

surpassing 90% disturbance at less than 100 

m – similar to our estimates. Speed of 

cruise ships and weather showed no obvious 

effect, though seals appeared to respond to 

ships at greater distances on clear, sunny 

days. Streveler (1979), reporting on eight 

summers in Glacier Bay, Alaska, was the 

first to document human disturbance of 

harbor seals inhabiting tidewater glacial 

fjords. He focused attention on the potential 

for disturbance to cause separation between 

mothers and their dependent pups, which 

has been shown to be a significant source of 

pup mortality at terrestrial sites, whether 

natural or human-induced (Johnson 1977). 

Although we observed mothers and 

pups responding to vessels – showing they 

had similar rates of water entry compared to 

other animals – the additional information 

necessary to document impacts on pup 

survival was not possible to obtain from 

shipboard platforms. Still, a general 

behavioral pattern, similar to Calambokidis 

et al. 1985 (unpub. ms.), was noted by 

observers: the mother and pup would enter 

the water usually within a minute of each 

other, or if the pup was hesitant, the mother 

would maintain visual contact until the pup 

entered some minutes later. The observation 

would end as the pair became obscured 

among the floating ice (and the observer 

focused on finding another group). We did 

not observe the sudden “crash dives” and 

lack of mother-pup coordination observed 

by Streveler (1979) in response to close 

approaches (< 150 m) by small boats or 

extremely low-flying (< 61 m) aircraft. 

These previous findings and our 

results indicate that cruise ships disturb the 

immediate behavior of individual seals (or 

groups), but evaluating the impacts of such 

disturbance on individual fitness – and 

ultimately population vital rates – is more 

difficult. If seals are compelled to spend 

more time in the water, then it is important 

to understand the possible long-term 

consequences. Pinnipeds begin life on land 

or ice and subsequently haul out on these 

substrates. Though all species of pinniped 

haul out, some do so only to reproduce and 

molt whereas others, like harbor seals, haul 

out throughout the year. The propensity to 

haul out differs relative to environmental 

conditions (e.g., solar angle and tide height) 

and across populations (Boveng et al. 2003). 

For example, harbor seals at terrestrial sites 

appear to respond primarily to tidal and diel 

light cycles (Watts 1996), whereas those on 

floating ice may respond mostly to the latter. 

Harbor seals in Alaskan glacial fjords 

exhibit a distinct diel rhythm with peak 

numbers on ice floes at solar noon (Glacier 

Bay, Calambokidis et al. 1987) or in the 

early afternoon (Aialik Bay, Hoover 1983, 

Withrow and Cesarone 1999a; Tracy Arm, 

Jansen et al. 2001). In Tracy Arm, prior to 

the tour boat and cruise ship season, radiotagging studies estimated that 90% of seals 

hauled out at some point daily, with an 

average 50-70% hauling out for some period 

21
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

between 1000 and 1700 h (ADT) (Jansen et 

al. 2001). At Glacier Bay, visual counts 

indicated that 70-90% of seals hauled out 

daily over the same period (Calambokidis et 

al. 1987). Such diel patterns, with numbers 

of hauled out seals peaking by day and 

diminishing at night, have been described 

widely and have been attributed to nocturnal 

foraging (see Watts 1996). Though nighttime feeding is supported by studies 

examining directly the foraging behavior of 

Alaska harbor seals (Frost et al. 2001), as 

Watts (1996) states: “this begs the basic 

question of why seals should [haul out] 

when they are not foraging”. 

The reasons why seals spend time 

out of the water are poorly understood but 

two theories predominate: 1) immersion in 

water is energetically costly; and 2) the 

threat of being eaten by a marine predator is 

significant (Watts 1996). It has been 

suggested that harbor seals are thermally 

neutral when active in the water (reviewed 

in Watts 1992). That is, heat production 

from metabolism approximately equals heat 

loss. During periods of inactivity, however 

– as during periods of required rest or sleep 

– there is likely an energetic cost to staying 

warm if seals are compelled to remain in the 

water and do not haul out (Watts 1992). 

Even while resting, seals must sustain a 

higher metabolism to maintain body 

temperature, termed low-temperature stress. 

However, a recent study of harbor 

seal pups at terrestrial sites suggests that 

low-temperature stress is unavoidable when 

water temperature falls below 4°C (39°F), an 

effect that is increasingly critical in smaller 

seals during winter (Harding et al. 2005). 

The smallest pups, that necessarily had the 

least insulation, faced low-temperature 

stress at less than 10° C (50°F). At their 

study site, temperature varied seasonally 

between 3° and 17°C (37-63°F). At the 

coldest temperatures, a 17 kg (37 lb) seal 

would have to consume an extra 0.5 kg (1.1 

lb) of prey daily compared to a 32 kg (71 lb) 

seal in order to break even energetically. 

The researchers predicted that if heat loss 

was not balanced with increased food intake, 

starvation would occur, and higher mortality 

during winter would be expected. Not 

surprisingly, then, the researchers 

documented a ca. 30% decrease in overwinter survival in the lightest pups when 

compared to the heaviest. 

These findings are particularly 

relevant to Disenchantment Bay because 

water temperature, due to melting ice and 

runoff in the warmer months, remains 

relatively low throughout the year. Water 

temperature in the upper 30 m probably 

rarely exceeds 5-7° C (41-45° F), as 

suggested by conductivity-depthtemperature (CTD) sampling at a similar 

glacier fjord (Tracy Arm Fjord, NMML, 

unpublished data) and measurements of seasurface temperatures (SST) near Yakutat. 

Even south in Yakutat Bay, where relatively 

little ice persists, summer SSTs rarely 

exceed 12° C (54° F) and are commonly 

below 10° C (University of Alaska 

SALMON Project 2005). It therefore stands 

to reason that a significant increase in time 

that young harbor seals, especially pups, 

spend submerged, or an interruption of 

nursing causing lower weaning mass, could 

have profound effects on energy balance, 

insulation, and over-winter survival. 

The threat of predation to harbor 

seals has not been rigorously examined, 

though predation on pinnipeds by killer 

whales (Orcinus orca) and sharks is well 

documented (Jefferson et al. 1991; Watts 

1996; Lucas and Stobo 2000). 

Calambokidis et al. (1987) reported 

numerous kills and attempts on harbor seals 

by killer whales near terrestrial haul-outs in 

Glacier Bay, and observed them traveling 

frequently in central and lower parts of the 

bay. Interestingly, they did not observe any 

killer whales in ice-filled, seal haul-out areas 

22
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

despite 7 months of continued presence (i.e., 

observation camps) over 3 summers. 

Similarly, Streveler (1979) indicated that 

“killer whales have never been reported in 

Muir or Johns Hopkins’ icepacks” in his 

experience in Glacier Bay over 8 years. 

Moreover, even though cetaceans (i.e., 

harbor porpoise and beluga) were observed 

on numerous occasions during the extensive 

surveys flown for this study, killer whales 

were not among them. But there have been 

observations of killer whales moving 

through loose brash ice in glacial fjords, 

albeit few. In upper Glacier Bay, two pods 

(8 and 22 animals) were observed during 9 

daylong vessel surveys (1991-1993); the 

larger pod was a resident group which is 

believed to feed exclusively on squid and 

fish (M. Dahlheim, NMML, pers. comm); in 

Aialik Bay, only one pod (two animals) was 

observed in 3 weeks (D. Withrow, NMML, 

pers. comm.). Similarly, killer whales were 

seen on one occasion in outer Yakutat Bay 

among dispersed ice floes on which several 

harbor seals were resting (Yakutat Tlingit 

Tribe, pers. comm.). Still, the notable 

absence of accounts of killer whales in 

densely-packed ice where seals occur in 

highest concentrations supports the view 

that such seals benefit from a lower risk of 

predation. The Inuit have long known that 

Arctic seals (and narwhals, Monodon 

monoceros) will enter scattered to dense 

pack ice when pursued by killer whales 

(Campbell et al. 1988). 

The incidence of seals vacating ice 

floes clearly diminished with ship distance 

out to at least 400 m, perhaps as far as 600 

m. At greater distances, the effect of ship 

approaches starts to level off suggesting that 

the frequency of seals entering the water at 

those distances is nearing ambient levels 

(i.e., levels expected in seals behaving 

naturally). However, along with the 

seeming diminution of responses at greater 

distances is a sizable increase in the error 

margins (i.e., 95% confidence limits). This 

result is an unavoidable consequence of 

smaller samples resulting from the 

decreasing detectability of seals with 

increasing distance from ships. Still, if the 

inference is correct that the frequency of the 

most overt response to ships (i.e., seals 

entering the water) reaches zero at about 500 

m, it is logical to predict that harbor seals 

may respond in other ways (e.g., increased 

alertness or agitation) at greater distances 

since these less overt behaviors are usually 

precursors to entering the water. 

3.2 Medium Scale: Weekly Aerial 

Surveys of Seal Distribution and 

Relative Abundance in 

Disenchantment Bay 

3.2.1 Methods 

Aerial surveys of relative seal 

abundance and distribution were conducted 

3-4 times weekly from 2 to 25 May 2002, 

beginning 12 days prior to the first entry of 

cruise ships into the bay. Daily surveys 

were conducted from 12 to 16 May (except 

15 May) to gather additional samples 

immediately preceding and following the 

first cruise ship visit of the year (14 May). 

Subsequent surveys were conducted twice 

weekly, weather permitting, starting 27 May 

and ending on 4 August, after the 

completion of pup rearing. These surveys 

were timed to facilitate a comparison of seal 

abundance and distribution between periods 

of low and high ship visitation. Thus, the 

first survey in the week was attempted on 

Sunday or Monday, following a period of 

reduced ship visitation, and the second on 

Thursday or Friday, following a period of 

increased visitation (Fig. 5). Surveys were 

flown between 1300 - 1500 h (ADT) to 

coincide with the daily peak in numbers of 

seals hauling out (Hoover 1983; Calambokidis et al. 1987; Withrow and Cesarone 

1999a; Jansen et al. 2001). A single engine 

23
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

aircraft (Cessna 206; Yakutat Coastal 

Airways Inc., Yakutat, AK) was flown at a 

target speed of 90-100 knots and altitude of 

305 m (1,000 ft). Two survey methods were 

employed simultaneously during overflights 

of the haul-out areas: observer line-transect 

and video strip-transect. A standard grid of 

14 transects, oriented along the longest axis 

of the bay and separated by 400 m, was 

flown over Disenchantment Bay (Fig. 11); a 

fifteenth transect was added in June to 

quantify the distribution of animals in 

southern Disenchantment Bay and northern 

Yakutat Bay as seals were sometimes 

observed there in low densities. 

For the observer line-transect 

method, two 50-m strips to the left side of 

the plane were delineated using a Plexiglass 

sighting board attached to the aircraft's 

window (Fig. 12). The observer’s eye 

position relative to the marks was fixed by 

visually aligning a pair of marks on the 

sighting board like a gunsight. The sighting 

board allowed quick measurement of 

distance intervals so the observer could 

remain focused on the ice and reduce missed 

seals. Normally, seals were counted within 

both of the two 50-m strips; however, when 

high seal density made accurate counting 

difficult, the observer focused attention just 

within the nearest strip. Effort data, time, 

and geographic position were recorded 

throughout the survey via a portable GPS 

unit. Environmental data – such as ice 

conditions, visibility, and weather – were 

also recorded by the observer. The single 

observer surveyed out the port side of the 

aircraft, recording seal counts, presence of 

vessels, and conditions in real time on the 

audio track of the video tape. 

For the video survey, a video camera 

was mounted vertically on the starboard 

wing strut with the zoom lens preset to 

record a 70-m strip directly beneath the 

plane. Time and GPS coordinates were 

initially imprinted on the tape as an aid in 

H u b b a r d 

G l a c i e r T u r

G

n e r

l a c i e r 

Pt. LaTouche 100 m

200 m

­

0 1 2 4

km 

Figure 11. Map of Disenchantment Bay

study area (outlined in red). The aerial 

transect grid for video and visual surveys 

is shown. The location of the face of

Hubbard Glacier was mapped in early

June 2002 (D. Seagars, USFWS). Bottom

contours are shown in black. 

mapping seal and ice distribution during the 

analysis phase. In June, we discontinued 

imprinting to optimize the viewing area 

during playback analysis, then matching the 

local time of seal sightings (visible in a 

smaller area on the screen) with locational 

fixes from the GPS unit using its associated 

local times. The medium-scale aerial 

surveys were flown on 23 days comprising 

nearly 40 hours of observation and 60 hours 

of flight time. 

Videotapes were played back and 

analyzed on a 13-inch video monitor (Sony 

Trinitron, Model PVM1344Q) by a single 

observer (S. Dahle). Harbor seals hauled out 

24
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

Figure 12. Vertical angle measurements of 

perpendicular distance of the two sighting bins 

from the survey aircraft. 

on ice were counted as they passed a 

horizontal line drawn across the bottom third 

of the screen. This ensured that the virtual 

width of the survey strip (70 m) was kept 

constant even though the plane (and the 

camera) may have rocked side to side and 

thus recorded, if only briefly, seals that were 

just outside the strip. This method also 

standardized the position on the screen, and 

thus the survey time, at which seals were 

sighted. Observations were communicated 

to a separate recorder who entered the 

number of seals on individual ice floes and 

the local time (which was related to 

geographical position), as well as a 

qualitative estimate of ice coverage (within 

the frame containing the seals) to the nearest 

tenth for ice greater than or equal to 2 m at 

its longest axis. Pups were also identified 

based on relative size (less than two-thirds 

the size of the adjacent seal) and proximity 

(less than the adjacent seal’s body length 

away). In addition, ice coverage was 

estimated at 15-second intervals when seals 

were not sighted. Depending on the speed 

of the plane, this provided a minimum of 

0.75 - 1 km × 400 m resolution of ice 

conditions thus creating intermittent gaps in 

ice data for the 400 × 400 m grid cells. 

Due to electronic problems and 

condensation, the video camera 

malfunctioned or produced less than optimal 

quality video during several surveys. Video 

recordings that were considered poor were 

excluded from the analysis (two surveys). 

Other recordings where the camera stopped 

operating over areas of typically high 

densities of seals were also excluded (five 

surveys). On four other surveys, the camera 

stopped recording during the last two to four 

transects at the western side of the bay, just 

offshore and south of Turner Glacier where 

few seals are typically sighted. An absence 

of seals on those transects was visually 

confirmed on two of those surveys (23 and 

25 May 2002); on the other two (16 May 

and 18 July 2002), the distribution of seals 

and ice on adjacent surveys made it unlikely 

that a significant number of seals was 

missed. Due to condensation, the video 

taken on 16 June was of marginal quality; 

thus, seal sightings could be negatively 

biased though counts were comparable to 

the preceding and following surveys. 

3.2.1.1 GIS Analyses 

The video analysis yielded 8,938 

distinct observations of seals and/or ice 

conditions which were mapped into a 

geographic information system (GIS) as 

separate point layers. The ice and seal point 

data were each summarized into a lattice of 

400 × 400 m cells for the entire study area 

(41 × 19 cells). Ice cover observations were 

averaged when multiple points fell within 

cell boundaries; seal count observations 

were summed. Indices of potential cruise 

ship effect were calculated on the basis of 

number of visits, ship distance, and activity. 

The number of visits was determined for the 

3 days leading up to and including the day 

of an aerial survey, and assigned to all cells 

(i.e., a global variable). Ship distance was 

defined as the closest approach of a cruise 

ship to the centroid of each cell containing 

25
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

seal groups (i.e., a cell-specific variable). 

Ship activity was defined as the amount of 

time that ships spent within a 1 km radius of 

the point of closest approach to a seal group. 

For the distance and activity calculations, 

we used ship tracks – for those cruise ships 

that penetrated north of Point LaTouche – 

that were recorded on the day of the aerial 

survey and the day prior. It was necessary 

to use a 2-day window in order to acquire an 

adequate number of sampling days with 

ships. There were seven aerial surveys (of 

18 total) which coincided with cruise ship 

visits: two on the same day, three with 

coinciding ship visits on the same and 

previous day, and two with coinciding visits 

only on the previous day. Ships’ tracks 

were used to calculate ship activity for a 

given survey provided they reached their 

turn-around point (i.e., the deepest 

penetration into the bay) prior to the end of 

the survey. The ship that visited on 3 

August, one day prior to a survey, was not 

tracked and thus we assumed that it 

followed a path similar to the most recent 

ship three days prior. From 23 July to 1 

August, reduced ice caused ships to follow 

very similar routes through the middle of the 

bay to within about 1 km of Hubbard 

Glacier. 

3.2.1.2 Statistical Analyses 

3.2.1.2.1 Time Series of Relative 

Abundance 

Because the daily sampling coverage 

was standardized, the total number of seals 

sighted during surveys provided a relative 

measure of abundance from which to 

examine seasonal trends. Using S-PLUS, 

Version 6.2 (Insightful Corp., Seattle, WA) 

we fit a generalized additive model (GAM; 

Hastie and Tibshirani 1990) to the counts of 

seals to assess seasonal variation in 

abundance. The GAM was implemented 

using a log-link function, a spline smooth 

term, and a Poisson error distribution. We 

evaluated the effect of date separately 

because the spatial-temporal models 

discussed below (Section 3.2.1.2.2) sought 

to remove date effects which could have 

confounded the effects of other covariates 

that varied by date. GAMs are nonparametric and do not impose a functional 

expectation on the data, therefore allowing 

the data themselves to suggest a functional 

form. This is often necessary for ecological 

data where complicated functions may be 

expected (Barry and Welch 2002). 

3.2.1.2.2 Space-Time Modeling of 

Covariate Effects on Seal Counts 

Based on the traditional ecological 

knowledge (TEK) of the Yakutat Tlingit 

Tribe (pers. comm.), we expected (and 

generally observed) that harbor seals in 

Disenchantment Bay form a clustered 

distribution, tending to aggregate to the west 

and north of Egg (Haenke) Island. This 

clustering was confirmed during exploratory 

analysis of the spatial distribution of seal 

counts. The tendency for seal counts in 

adjacent cells to be more similar than distant 

cells, termed spatial autocorrelation (SAC), 

presents challenges for inference from 

conventional statistical tests which assume 

that samples are independent. Assuming 

independence when SAC exists 

overestimates the degrees of freedom, biases 

the coefficients and their standard errors, 

and can cause the coefficients to be 

considered significantly different from zero 

when they are not. It was therefore 

necessary to model the pair-wise 

correlations between all seal cell counts to 

account for the effects of SAC while 

simultaneously testing for covariate effects 

on those counts. 

Observations can also be correlated 

in time. As with SAC, assuming temporal 

independence of serial observations can 

inflate the actual degrees of freedom 

26
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

resulting in a higher risk of concluding a 

significant effect when one does not exist. 

To account for temporal autocorrelation, the 

effects on seal counts of the global 

covariates (which varied temporally but not 

spatially [e.g., wind, rain, and number of 

ships visiting]) and local covariates (which 

varied spatially and temporally [e.g., ice 

cover, closest ship approach]) were modeled 

separately but simultaneously using a firstorder autoregressive model (AR1; see 

Appendix 1). 

A frequent characteristic of largescale survey data is a large number of zero 

observations. The seal counts in this study 

were no exception, with seals occupying less 

than a third, on average, of the cells 

containing ice on a given day. Such zeroinflated count data, a form of overdispersion 

(McCullagh and Nelder 1994), if modeled 

conventionally can also lead to incorrect 

inference and biased parameters. The 

recommended approach, adopted in this 

study, is to model the zero-inflated data in 

two steps: 1) model the absence-presence 

component of the data (using a Bernoulli 

distribution) and 2) model the observed 

abundance conditional on the response being 

greater than zero (using a Poisson 

distribution; Mullahy 1986; Heilbron 1994; 

Welsh et al. 1996). The zero-inflated, 

space-time regression was fitted using 

Markov Chain Monte Carlo (MCMC) in 

WinBUGS software (Version 1.4, Imperial 

College & MRC, UK). Details of the 

regression model used here are provided in 

Appendix 1. Using this model, our goal was 

to describe the empirical relationship 

between the distribution (presence) and 

abundance (counts) of seals and 

environmental covariates, such as measures 

of cruise ship presence, distance, and 

activity. 

3.2.2 Results 

3.2.2.1 Potential Biases in Seal 

Abundance 

Despite having standardized daily 

coverage during the aerial surveys, there 

were potential sources of bias and 

imprecision. Firstly, we could not 

distinguish between seals that left the study 

area and seals that were present but opted 

not to haul out during the survey period on a 

given day. However, because other studies 

of glacial-fjord seals support a stereotyped 

behavior of hauling out daily in the early 

afternoon (see Section 3.2.1) we expect that 

seals in Disenchantment Bay have a similar 

propensity. Also, other studies in glacial 

fjords have shown that when seals were 

present near the haul-out area they nearly 

always hauled out (i.e., if they missed 

hauling out it was because they had left the 

fjord)(Jansen et al. 2001). We therefore 

assumed that shifts in seal abundance were 

caused largely by departures from and 

arrivals to Disenchantment Bay. 

Secondly, researchers have shown 

that harbor seals in glacial fjords tend to 

form small groups which in turn form 

larger-scale aggregations (i.e., seals are not 

randomly distributed; Bengtson et al. 2004; 

Simpkins et al. 2005). These aggregations 

change in size and location across days. In 

our study, distinct aggregations of seals and 

the degree to which those aggregations were 

not sampled equally across days would 

cause variability, or imprecision, in the 

estimated abundance. Clustering of seals 

means that some surveys might miss a 

significant portion of the population 

(negative bias), whereas others might oversample areas of high density (positive bias). 

The pronounced trends exhibited in the time 

series of seal abundance suggest strongly 

that our sampling frequency was adequate to 

detect real signals in the data thus 

overwhelming any possible noise generated 

27
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

by this imprecision. We are currently 

assessing the efficiency of the sampling 

design used in this study by comparing the 

relative abundance with a “known” 

abundance as estimated by the high-altitude 

photogrammetry. 

Sightings of mother-pup pairs may 

be biased as there is evidence from Aialik 

Bay that mothers and pups occur in peak 

numbers on the ice a few hours earlier in the 

day compared to other seals (Hoover 1983). 

However, recent findings from Glacier Bay 

showed that the proportions of mothers and 

pups hauled out varied by less than 5% over 

a 15-hour daylight period (Mathews and 

Pendleton 2006). In our study, the number 

of mother-pup pairs showed no relationship 

with the start time of surveys, which ranged 

from 1300 to 1500 h (ADT). Based on this 

information, we assumed that mothers and 

pups had haul-out behaviors similar to other 

seals. 

3.2.2.2 Visual Sampling of Harbor 

Seals 

The visual observations from the two 

50-m strips to the side of the plane showed 

substantial variation across days and 

between observers in the probability of 

sighting seals. Using the seals mapped by 

video during each survey (see Section 

3.2.2.2 below), we calculated the “known” 

seal density for the 70-m video strip and 

compared it to what would be expected – 

given comparable densities – in the two 50 

m visual strips. We assumed that the 

sighting probability did not vary between the 

video strip directly under the plane and the 

visual strips starting at 264 m to the side of 

the plane. 

Compared to video sightings, visual 

observers consistently underestimated seal 

densities. This bias varied between 

observers with average factors ranging from 

0.49 to 0.63. Within observers, factors 

ranged as wide as 0.16 to 0.83 across days 

compared to the video sightings. The 

reduced probability of detecting a seal in the 

visual strips versus on video may have been 

due to a swamping effect, such that when 

seal densities were high observers had 

difficulty counting seals particularly those 

that were closer and passing relatively 

faster. Sighting probability could also have 

been reduced by visual interference caused 

by the plane’s landing gear which was 

positioned immediately inboard of the 

closest strip. These observer biases, though 

expected, were quite variable across days 

and warrant further investigation. Because 

dense aggregations of seals were fairly 

common in the study area, it may be that 

visual sighting techniques are impractical 

here. Because the sightings from the video 

analysis were largely unbiased (i.e., a single 

observer made the seal and ice observations 

and there was no swamping effect), and they 

provide a verifiable record of observations, 

we are currently using only the video 

sighting data to address hypotheses in the 

medium-scale study. 

3.2.2.3 Video Sampling of Harbor 

Seals 

3.2.2.3.1 Time Series of Total 

Abundance 

The fitted GAM model showed that 

abundance varied significantly by date (P < 

0.01; Fig. 13) revealing several pronounced 

shifts during the study. On 3 May, seal 

abundance appeared to be near peak levels 

(though prior abundance was unknown) but 

then declined precipitously to a minimum by 

mid-May. The decline may have occurred 

in two stages with a drop of about one-third 

of the seals followed by a brief pause from 

6-13 May and then another steep decline 

(50%) from 14 to 16 May. The entire 

decline amounted to a 75% reduction in 

abundance. Seal numbers remained well 

below maximum levels until late June when 

28
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

300 50 

Number of all seals 

200 

all seals 

pups only 

Spline fit 

25 

100 

0 0 

Number of pups 

May Jun Jul Aug 

Date 

Figure 13. Numbers of all seals and pups, counted in video surveys, in relation to date. The 

spline curve is the best fit according to the GAM using date as the only covariate on seal 

and pup counts. 

they again peaked and remained high until 

the last survey on 4 August. 

Interestingly, there was a modest rise 

in seal numbers in early June and then a 

slight decline before the actual peak count 

on 23 June. It was during this secondary 

rise in total seals that numbers of pups 

showed a steady increase before also 

peaking on 23 June. Though the peak in 

total seals and pups coincided, the combined 

number of mothers and pups contributed 

only about 20% (10% each) to the total sum. 

These coinciding peaks suggest that the 

increase in number of mother-pup pairs 

occurred in conjunction with increases in the 

general population. The subsequent rapid 

drop in sightings of mother-pup pairs in 

early July, despite high numbers of seals, 

suggests that weaning was underway and 

mothers and/or pups were spending more 

time in the water, or at least were not 

associating as closely. 

3.2.2.3.2 General Patterns in Seal 

Distribution 

There was considerable daily 

variation in the spatial distribution of seals 

hauled out in Disenchantment Bay (Figs. 14-

19). Overall, seals hauled out in the highest 

frequency north and west of Egg (Haenke) 

Island. Seals frequently occurred in smaller 

numbers south of Egg (Haenke) Island, 

occasionally even south of Point LaTouche 

when ice conditions permitted. Distinct 

aggregations of seals were almost always 

apparent but the spatial extent and location 

of higher density areas varied. For example, 

prior to and during the decline in abundance 

in early May, seals were confined to a 

relatively small area to the northwest of Egg 

(Haenke) Island (Figs. 14-15). In late May, 

immediately after the minimum in 

abundance and as seal numbers were 

rebounding, seals were more dispersed 

particularly in areas to the south. By June, 

as seals continued to arrive, they were 

29
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

scattered almost equally in the western half 

of the bay, north and south of Egg (Haenke) 

Island. The more scattered distribution of 

seals in June occurred as ice was reaching 

maximum coverage. As ice cover steadily 

declined from late June through early 

August, seals were increasingly more 

aggregated in areas closest to the Hubbard 

Glacier. Their narrowest distribution 

occurred during the last survey, on 4 

August, when seals were in the 

northernmost area of the bay (Fig. 19). 

3.2.2.3.3 Seal Abundance in Relation 

to Ice Cover 

There was no apparent relationship 

between total seal counts and the overall 

availability of ice cover in the bay. Seal 

numbers were high in early May (the first 

survey) when the ice-covered area (ICA) 

was reduced and intermediate to dense ice 

was nearly absent. The steep decline in seal 

numbers (in the first half of May) occurred 

as the total ICA varied around intermediate 

levels and areas of denser ice became more 

prevalent. Seal numbers reached a 

minimum during a brief drop in ice coverage 

(16 May), but comparable drops coincided 

with high numbers of seals. By 23 May, the 

ICA, which consisted mostly of intermediate 

and scattered ice, reached its highest level to 

that point and seal counts remained low. 

Moreover, as seal numbers increased later in 

the season, ice steadily declined to a 

minimum. By July, with ice cover at less 

than 50% of the peak – declining to 5% by 

August – seal abundance had mostly 

stabilized at high levels. Still, a response by 

seals to ice availability may only occur at 

specific “checkpoints” during the year, such 

as related to life-history constraints. For 

example, a seal just arriving to 

Disenchantment Bay may assess conditions 

and decide whether or not to stay, whereas a 

seal already in the midst of pupping or 

molting may not have the same flexibility to 

respond to changes in ice availability (i.e., 

depart if conditions turn unfavorable). 

Despite no apparent relationship 

between abundance and total ice availability, 

seals did appear to vary their use of different 

types of ice cover through the season, 

possibly in response to shifts in availability 

(Fig. 20). On 3 May, virtually all seals 

occupied the scattered ice zone, as there 

were scant areas of denser ice. As areas of 

intermediate and dense ice increased 

through May, seals shifted 

disproportionately to these zones despite a 

consistently high availability of scattered ice 

(~50% of the study area). By mid-May, 

when abundance was at a low, seals had 

mostly abandoned scattered ice in favor of 

intermediate ice cover. As abundance 

gradually rebounded (through late-May and 

June), seals began using the scattered ice 

zone in greater numbers, though still far less 

than would be expected by random 

selection. Interestingly, as seal abundance 

increased in late June to early July, the zone 

of highest abundance shifted from scattered 

to intermediate ice (Fig. 20). We speculate 

that this dramatic shift in the use of different 

ice zones reflects a pulse of new arrivals in 

the scattered ice followed by a gradual 

movement into denser ice (Fig. 20). 

Seasonal changes in spatial distribution of 

seals support this hypothesis: seals were 

more dispersed when abundance was 

increasing, and in turn used the scattered-ice 

zone more frequently, particularly south of 

Egg (Haenke) Island (Fig. 16-18). At the 

end of July, the use of the scattered-ice zone 

again peaked, but in this case (as in early 

May) the intermediate- and dense-ice zones 

were severely limited. On the last day of the 

study, as denser ice again became available 

(and ICA was less than 5% of the peak), 

seals shifted back to intermediate or dense 

ice leaving only 20% of the seals in 

scattered ice (Fig. 20). 

30
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

Figure 14. Spatial distribution of harbor seals, ice cover zones, and maximum penetration of cruise ships on the day of surveys 

() and the previous day ( ) for 3, 6, and 7 May 2002. The range of seal counts summed per grid cell is shown in three levels: 

small dot (< 5 seals), medium dot (5-20 seals), large dot (> 20 seals). Increasing ice cover is represented by a gradient in shading: 

scattered (light gray), intermediate (medium gray), dense (black). The incidence of at least one mother-pup pair within a grid cell 

is shown by a white dot. The time of day that ships reached their maximum penetration appears near the location symbol. For this graphic, if cells with no ice data (see Section 3.2.1) were bounded on three sides by cells with ice measures, the average of 

neighboring cells was used as an estimate. 

31
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

Figure 15. Spatial distribution of harbor seals, ice cover zones, and maximum penetration of cruise ships on the day of surveys 

() and the previous day () for 12, 13, and 16 May 2002. The range of seal counts summed per grid cell is shown in three 

levels: small dot (< 5 seals), medium dot (5-20 seals), large dot (> 20 seals). Increasing ice cover is represented by a gradient in 

shading: scattered (light gray), intermediate (medium gray), dense (black). The incidence of at least one mother-pup pair within a grid cell is shown by a white dot. The time of day that ships reached their maximum penetration appears near the location 

symbol. For this graphic, if cells with no ice data (see Section 3.2.1) were bounded on three sides by cells with ice measures, the 

average of neighboring cells was used as an estimate. 

32
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

Figure 16. Spatial distribution of harbor seals, ice cover zones, and maximum penetration of cruise ships on the day of surveys 

() and the previous day () for 23, 25, and 27 May 2002. The range of seal counts summed per grid cell is shown in three 

levels: small dot (< 5 seals), medium dot (5-20 seals), large dot (> 20 seals). Increasing ice cover is represented by a gradient in 

shading: scattered (light gray), intermediate (medium gray), dense (black). The incidence of at least one mother-pup pair within a grid cell is shown by a white dot. The time of day that ships reached their maximum penetration appears near the location 

symbol. For this graphic, if cells with no ice data (see Section 3.2.1) were bounded on three sides by cells with ice measures, the 

average of neighboring cells was used as an estimate. 

33
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

Figure 17. Spatial distribution of harbor seals, ice cover zones, and maximum penetration of cruise ships on the day of surveys 

() and the previous day () for 31 May, 6 and 16 June 2002. The range of seal counts summed per grid cell is shown in three 

levels: small dot (< 5 seals), medium dot (5-20 seals), large dot (> 20 seals). Increasing ice cover is represented by a gradient in shading: scattered (light gray), intermediate (medium gray), dense (black). The incidence of at least one mother-pup pair within a grid cell is shown by a white dot. The time of day that ships reached their maximum penetration appears near the location symbol. For this graphic, if cells with no ice data (see Section 3.2.1) were bounded on three sides by cells with ice measures, the 

average of neighboring cells was used as an estimate. 

34
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

Figure 18. Spatial distribution of harbor seals, ice cover zones, and maximum penetration of cruise ships on the day of surveys 

() and the previous day () for 20 and 23 June, and 8 July 2002. The range of seal counts summed per grid cell is shown in 

three levels: small dot (< 5 seals), medium dot (5-20 seals), large dot (> 20 seals). Increasing ice cover is represented by a 

gradient in shading: scattered (light gray), intermediate (medium gray), dense (black). The incidence of at least one mother-pup pair within a grid cell is shown by a white dot. The time of day that ships reached their maximum penetration appears near the 

location symbol. For this graphic, if cells with no ice data (see Section 3.2.1) were bounded on three sides by cells with ice 

measures, the average of neighboring cells was used as an estimate. 

35
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

1620 

Figure 19. Spatial distribution of harbor seals, ice cover zones, and maximum penetration of cruise ships on the day of surveys 

() and the previous day () for 18 and 28 July, and 4 August 2002. The range of seal counts summed per grid cell is shown in 

three levels: small dot (< 5 seals), medium dot (5-20 seals), large dot (> 20 seals). Increasing ice cover is represented by a 

gradient in shading: scattered (light gray), intermediate (medium gray), dense (black). The incidence of at least one mother-pup pair within a grid cell is shown by a white dot. The time of day that ships reached their maximum penetration appears near the 

location symbol. For this graphic, if cells with no ice data (see Section 3.2.1) were bounded on three sides by cells with ice 

measures, the average of neighboring cells was used as an estimate. 

36
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

Number of seals

350 

300 

250 

200 

150 

100 

50 

0 

scattered 

intermediate 

dense 

May Jun Jul Aug 

Date 

Figure 20. Numbers of harbor seals counted in video surveys within the three ice 

zones: scattered, intermediate, and dense (see legend), from 3 May to 4 August 2002 

in Disenchantment Bay. 

Overall, seals used the scattered and 

intermediate ice zones at similar frequencies 

even though the latter zone represented less 

than half of the proportional area of the 

former (Fig. 4). With the exception of two 

surveys, the use of areas of dense ice was 

markedly lower than that of scattered or 

intermediate ice. This suggests a non-linear 

relationship between seal abundance and the 

density of ice cover, with seals showing a 

preference for intermediate ice. These 

hypotheses were supported in statistical tests 

that examined ice cover as a covariate in 

modeling seal counts (see Section 3.2.2.3.4). 

3.2.2.3.4 Space-Time Model of 

Seal Counts 

The first stage of the space-time 

regression model, which examined the 

binary response of absence/presence 

(incidence) of seals in each cell of the 

lattice, indicated that the effect of ice cover 

was statistically significant and was the 

dominant factor explaining the spatial 

distribution of harbor seals (P < 0.05; 

Appendix 1). Coefficients for individual 

classes of ice cover were significantly 

greater than zero for scattered (1-3 tenths 

coverage) and intermediate ice (4-6 tenths), 

and for 7 tenths ice cover. The 95% 

confidence intervals for the densest ice 

cover (8 and 9-tenths) included zero so were 

not deemed significant (Appendix 1). Those 

coefficients that were significant gradually 

increased from 1 to 5-tenths ice cover, 

before declining (Fig. 21), indicating a 

slightly higher incidence of seals in 

intermediate versus scattered ice cover. 

Variation in the occurrence of denser ice 

cover (i.e., 8 and 9 tenths) had no significant 

effect on the distribution of seals. Overall, 

this suggests a modest preference by seals 

37
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

for more intermediate ice cover. Other 

natural variables, precipitation, wind speed, 

and total ICA (ice-covered area), did not 

have a significant effect on the distribution 

of seals in the lattice (Appendix 1). 

The occurrence of mother-pup pairs 

exhibited several patterns but exceedingly 

small samples and large confidence intervals 

made inference more difficult. As with the 

pooled seals, mother-pup pairs showed a 

peak incidence associated with intermediate 

ice cover (6-tenths), though there was no 

indication of a gradually increasing 

preference with increasing ice cover (Fig. 

21). Coefficients for 1-5 tenths, and 8-9 

tenths, ice cover were not significant and 

were highly erratic, suggesting that either 

sample size was inadequate for a reliable 

estimate or that mothers more specifically 

target intermediate ice than the pooled 

population (Appendix 1). Other natural 

variables (i.e., precipitation, wind speed, and 

ICA) did not have a significant effect on the 

distribution of mothers and pups in the bay. 

The effects of distance and activity 

of cruise ships on the incidence of harbor 

seals were assessed simultaneously in the 

same models (Appendix 1). The presence of 

ships on the survey day and the number of 

ship visits over the last 3 days did not have 

an effect on the overall incidence 

(distribution) of seals in Disenchantment 

Bay. The closest approach distance of ships 

was negatively related to the incidence of 

0.00 0.05 0.10 0.15 0.20 0.25 

Standar

diz

e

d S

election Coefficients 

2 4 6 8 

Ice Coverage Class 

Figure 21. Standardized selection coefficient for ice cover class for the Bernoulli part of the 

ZIP model (i.e., for the cell-based spatial distribution of seals). The black, solid line is for all 

seals, and the dashed line is for mother-pup pairs (see Appendix 1) 

38
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

seals, so that closer approaches were 

associated with higher incidence of seals. 

This is likely an artifact of ships using 

corridors that overlap closely with peak seal 

densities rather than seals selectively 

aggregating closer to ships. The lack of a 

positive effect (i.e., a lesser incidence of 

seals related to closer approaches) suggests 

that harbor seals were not adjusting their 

distribution based on the relative locations 

of ships within the bay. However, greater 

ship activity did have a significant negative 

effect on the incidence of harbor seals (P < 

0.05; Appendix 1), such that there were 

fewer grid cells containing seals with 

increases in the combined time that ships 

spent within 1 km of a closest approach. 

The incidence of mothers and pups 

was not related to any of the measures of 

ship distance or activity. As noted above, 

sightings of mothers and pups were 

relatively rare making statistical inference 

difficult. At present, the findings indicate 

that mothers and pups do not respond any 

differently to cruise ships compared to the 

pooled population. 

The second stage of the space-time 

model, which examined the actual counts in 

cells where seals occurred (abundance), 

confirmed that the effect of ice cover was a 

dominant factor (P < 0.05; Appendix 1). 

Coefficients for ice-coverage classes of 3-7-

tenths were statistically significant, though 

the greatest effect was detected in 5-7-tenths 

0.0 

0.1 0.2 0.3 0.4 

Standardized Selection Coefficients 

2 4 6 8 

Ice Coverage Class 

Figure 22. Standardized selection coefficient for ice cover class for the Poisson part of 

the ZIP model (i.e., for the cell-based abundance of seals). The black, solid line is for 

all seals, and the dashed line is for mother-pup pairs (see Appendix 1) 

39 
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

ice coverage (Fig. 22). This further supports 

the contention that intermediate ice cover 

supports the highest abundance of seals. 

Other natural variables (i.e., precipitation, 

wind speed, and ICA) did not have a 

detectable effect on the abundance of seals. 

Similar to the first stage of the regression, 

the ships’ closest approach distance was 

negatively related to seal abundance, which, 

as noted above, was likely a function of a 

close proximity of ships’ transit corridors to 

the preferred seal haul-out area. None of the 

other cruise ship factors, including ship 

activity, were related to seal abundance. 

The abundance of mothers and pups 

was also related to ice cover (P < 0.05; 

Appendix 1), though the pattern differed 

slightly in comparison to their overall 

distribution (incidence). For example, 

significant coefficients occurred in the 2-6-

tenths ice classes (with peak values in 3 and 

5-tenths; Fig. 22). This suggests that 

mother-pup abundance peaked in the upperscattered to intermediate ice despite the 

indication in the first stage of the model that 

overall mother-pup presence was centered 

on slightly denser ice (6-tenths). Again, 

higher variation in the coefficients compared 

to the pooled seals, and larger confidence 

intervals, point to the need to exercise 

caution when drawing conclusions regarding 

mother-pup sightings. The abundance of 

mothers and pups was not statistically 

related to any of the measures of ship 

distance or activity (Appendix 1), suggesting 

that their attendance in Disenchantment Bay 

is not affected (in the short-term) by ships – 

similar to the pooled population. 

3.2.3 Discussion 

3.2.3.1 Seasonal Patterns in Daily 

Abundance 

The cause of the decline in seal 

abundance just before pupping is currently 

unknown. There is no indication that a 

profound, extended change in the weather 

caused seals to change their haul-out 

behavior (Fig. 3). Wind speed and 

precipitation were below levels, particularly 

on survey days, where harbor seals in other 

studies have reduced their frequency of 

hauling out (Hoover 1983; Boveng et al. 

2003). There are also few indications that 

inadequate ice cover could have caused seals 

to leave the bay in such large proportions 

over a short period. Although total ice cover 

may have been slightly reduced in mid-May, 

coinciding with a local minima in seal 

abundance, the seasonal decline of ice cover 

in late June and July occurred as seal 

abundance reached its highest levels. At the 

end of surveys in early August, when seal 

abundance was at near-peak levels, ice cover 

was at the absolute minimum with nearly 

10-fold less ice than mid-June. It is perhaps 

not surprising that ice is most available 

during peak pup-rearing in mid-June, and 

mothers are increasingly selective about 

finding a platform for birthing and nursing 

(Hoover 1983). But there is no evidence 

that ice availability during pup-rearing or 

breeding (mid-spring to mid-summer) is a 

constraint that regulates population size. 

The first cruise ship entered 

Disenchantment Bay on 14 May, at a 

midpoint of the overall decline in seal 

abundance. Due to thick ice and poor 

visibility, this first ship stopped just north of 

Point LaTouche, barely within the study 

area and before any seals were within 

spotting range (ca. 1 km). The next ship 

entered the bay on 18 May, after the decline 

had stabilized. It is therefore unlikely that 

cruise ships initiated or influenced the 

decline observed from 13 to 16 May, even 

less so the earlier decline from 3 to 6 May. 

Assuming that the distribution of seals on 14 

May, when the first ship entered the bay, 

was similar to that on adjacent dates (13 or 

16 May), the nearest seals to the ship (of 

group size > 1) would have been at a 

40
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

distance of more than 12 km (7.5 mi; Fig. 

15). Direct observations of harbor seals 

from cruise ships in our study – that were 

limited to less than 1 km – showed that seals 

did not enter the water with any greater 

frequency when ships were 600 m, or more, 

away. If a significant number of seals on 14 

May entered the water and then abandoned 

the haul-out area for 2-3 weeks due to a 

single vessel at 12 km, then it is difficult to 

explain why seal abundance later in the 

season steadily increased when ship 

encounters also increased – rather 

dramatically, in terms of ships per day 

(reaching 5), number of ship-days per week 

(reaching 5), and deeper penetration into the 

bay with diminishing ice cover (Fig. 7). 

Alternatively, seals could have left 

the bay in response to natural factors not 

measured in this study, such as the 

abundance and distribution of prey. Harbor 

seals are commonly seen milling in large 

numbers in nearby river systems during peak 

runs of eulachon (Thaleichthys pacificus), 

especially near the mouths of the Situk (70 

km from Disenchantment Bay), Lost (70 

km), Ahrnklin (80 km), Akwe (110 km), and 

Alsek Rivers (140 km). Steller sea lions 

(Eumetopias jubatus) aggregate in the Alsek 

River in large numbers (up to 1,700) in midMarch when spawning eulachon are 

migrating upriver (Catterson 2005). Harbor 

seals have been observed hauled out nearby 

at the same time in numbers exceeding that 

of the Steller sea lions (J. Capra, Dry Bay 

Ranger, National Park Service, Yakutat 

Office, pers. comm.). 

In the Situk/Lost/Ahrnklin River 

System, one of the closest to 

Disenchantment Bay, the eulachon run 

reportedly occurs between March and midJune (Estes 1994) with estimates as high as 

500,000 fish (D. Gillikan, Fishery Biologist, 

U.S. Forest Service, Yakutat District, pers. 

comm.). A latitudinal cline in the timing of 

spawning, from Berners Bay in Southeast 

(mid-April to early May) to the Copper 

River near Prince William Sound (late May 

to early June), suggests that peak runs in the 

Situk Estuary would be expected in midMay. But large runs have only been 

recorded from mid-March through April, 

when eulachon surveys end (D. Gillikan, 

pers. comm.). However, on 14 May 2002, 

when seal numbers were nearing the 

minimum, eulachon were reported to be 

staging for migration upstream in the Situk 

Estuary, as indicated by large feeding flocks 

of seabirds (D. Russell, pilot, Yakutat 

Coastal Airways, pers. comm.). The size of 

the run was unknown. Earlier that spring on 

the Situk River, during the normal peak in 

eulachon spawning, unusually low numbers 

of fish were observed (D. Gillikan, pers. 

comm.). A delay in the peak migration 

outside the sampling period (i.e., in May) 

could explain these observations. 

Eulachon have been observed within 

the mouths of all rivers along the Yakutat 

Forelands, yet the variable timing, pulsed 

nature, and size of runs have not been 

systematically examined. Current eulachon 

surveys, though informative, are focused in 

the early spring, vary with personnel 

availability, and are not standardized. The 

occurrence of eulachon runs in May and 

June, though supported by local knowledge, 

has not been rigorously documented. 

Exploitation of these local eulachon runs by 

harbor seals can be inferred from anecdotal 

observations of seals milling in the river 

mouths, but the overall significance of 

eulachon to the energy budget of seals 

inhabiting Disenchantment Bay is unknown. 

Though not as concentrated and predictable 

in space as eulachon, other potential prey 

occur in the area during May: Pacific 

herring (Clupea pallasi) are spawning in 

Yakutat Bay, Chinook salmon (Oncorhynchus tshawytscha) are migrating southward 

along the coast, and steelhead (Oncorhynchus mykiss)are spawning in the Situk River. 

41
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

The reduced abundance of seals in 

Disenchantment Bay at the onset of pupping 

is similar to that observed in Aialik Bay, 

another Alaskan tidewater glacial fjord. 

Hoover (1983) conducted the first seasonal 

counts of seals in Aialik Bay near an 

apparent minimum in mid-May, similar to 

Disenchantment Bay. Seal numbers then 

steadily increased until peak pupping in 

mid-June. But, in contrast to our study, 

counts declined through July to levels 

comparable to mid-May, and then 

rebounded by early August. Seal numbers at 

Disenchantment Bay seem to be stable from 

late-June to early August with only a brief 

decline in mid-July. In Aialik, the steady 

rise in abundance during pupping coincided 

with a pronounced decline in the estimated 

number of juveniles. This apparent exodus 

of younger animals was more than offset by 

an influx of adults causing a peak in overall 

abundance which coincided with the peak 

number of pups (Hoover 1983), similar to 

Disenchantment Bay. A similar departure of 

juveniles occurred in Tracy Arm Fjord 

where radio-tagged seals (N = seven 

juveniles and two adults) left at the onset of 

pupping (Jansen et al. 2001). The higher 

resolution imagery collected in 2004 and 

2005 will allow examining for potential 

shifts in population structure in 

Disenchantment Bay (see Appendix 2). 

Despite some similarities in timing, 

there are apparent differences between 

Disenchantment Bay and other pupping sites 

in terms of productivity. At peak pupping in 

Disenchantment Bay, the proportion of pups 

relative to the total abundance was 10%, a 

figure less than half that observed at other 

glacial haulouts (Aialik Bay: 26% [1980]; 

John Hopkins Inlet: 25-31% [1975-78], 34-

36% [1994-1999]; Muir Inlet: 22-30% 

[1975-78] and terrestrial haul outs (Tugidak 

Island: 23% [1976], 27% [1996](Streveler 

1979; Hoover 1983; Jemison and Kelly 

2001; Mathews and Pendleton 2006). 

Hypotheses that may explain a lower 

proportion of females with pups include 

lower rates of conception (e.g., via 

disruption of breeding), fewer females 

implanting and carrying pups to term (e.g., 

via physiological stress), or a population 

structure skewed toward other sex and age 

groups compared to other sites (e.g., via 

emigration of females or immigration of 

juveniles). 

Though the video imagery in this 

study was not ideal for distinguishing pups, 

we believe it unlikely that a negative bias in 

identifying pups could have caused 

productivity estimates so dramatically 

reduced compared to other sites. Based on 

findings here and at Glacier Bay (Mathews 

and Pendleton 2006), it is also unlikely there 

was enough diel variation in mother-pup 

pairs hauling out – compared to the rest of 

the population – to bias significantly our 

estimates of relative productivity. Still, this 

uncertainty will be addressed further 

through analyses of the improved imagery 

collected in 2004 and 2005. The enhanced 

resolution will aid in determining whether 

pup productivity in Disenchantment Bay is 

unusually low, particularly in comparison to 

nearby Icy Bay. 

3.2.3.2 Cell-based Seal Counts in 

Relation to Environmental Covariates 

It was not surprising that ice cover 

was a key factor affecting seal abundance 

and distribution because the ability of seals 

to haul out in these areas, and indeed the 

haul-out area itself, is defined by ice cover. 

It is interesting, however, that seals tended 

to haul out, and in highest abundance, in 

areas of more intermediate rather than 

denser ice coverage. This pattern could 

have resulted from several scenarios: 1) 

seals may have first hauled out on denser ice 

which may have then dispersed southward, 

later being characterized as less dense 

during our mid-afternoon surveys; 2) harbor 

42
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

seals may prefer some minimum open water 

to provide greater ease in breathing, 

swimming at the surface, or “spy-hopping” 

to find aggregations of animals; and 3) the 

densest ice may be less desirable because it 

most often occurs in the northernmost area 

of the bay (i.e., more distant), very often in 

close proximity to the calving Hubbard 

Glacier (i.e., more hazardous). 

It was also not surprising that the 

meteorological measures (i.e., rain and 

wind) had no measurable effect on seal 

presence or abundance, particularly since the 

aerial surveys were constrained by weather. 

In modeling these covariates, we examined 

the more immediate effects of weather on 

the seals’ propensity to haul out (e.g., 6 

hours prior to a survey). Though beyond the 

scope of this study, large-scale weather 

patterns, such as those associated with the 

migration of entire weather systems (e.g., 

atmospheric pressure cells), could influence 

decisions by seals regarding whether to 

travel, forage or rest. Hoover (1983) 

suggested that harbor seals on ice in Aialik 

Bay avoided hauling out from the day before 

to the day after a storm. Still, from early 

May to early August 2002, significant 

weather events in the greater Yakutat area 

were few and overall conditions were 

generally mild. Maximum wind gusts were 

usually less than 10 knots and exceeded 15 

knots on only 3 days (including one survey 

day). Wind speed never approached levels 

shown to affect seal haul-out behavior 

(> 20-25 knots; Hoover 1983; Boveng et al. 

2003). Though precipitation has also been 

suggested to reduce the propensity of seals 

to haul out (Pauli and Terhune 1987; 

Olesiuk et al. 1990; Boveng et al. 2003), 

rain during the study was minimal with most 

survey days seeing no rain and only a few 

seeing trace amounts. There were two rain 

events, however, which shortly preceded 

surveys and could have influenced seal 

abundance: 1) on 15 May, during the 36 

hours preceding the latter phase of the 

decline in seal abundance it rained about an 

inch, but the initial phase of the decline 

occurred between 3 and 6 May when there 

was no measurable rain (Figs. 3 and 13); and 

2) from 23 to 25 July, it rained more than 3 

inches but our next survey 3 days later (28 

July) showed that abundance had increased. 

It should be noted that the 

precipitation data used in this study (from 

the Yakutat Airport near the coast) may 

have overestimated the conditions in the 

study area. Disenchantment Bay, being a 

deep glacial fjord, is afforded some 

protection from inclement weather by the St. 

Elias Range (3,000-5,500 m) due to 

blocking and upslope flow (Papineau 2000). 

This causes the majority of precipitation to 

fall along the Yakutat Forelands closer to 

the outer coast. Prevailing coastal winds 

also appear to be moderated in 

Disenchantment Bay: for the days that the 

weather station on Egg (Haenke) Island was 

operational, maximum gusts exceeding 15 

knots occurred on 7% of the days compared 

to 47% of the days reported at the Yakutat 

airport (NOAA-NCDC 2002). Moreover, 

wind gusts never exceeded 20 knots in 

Disenchantment Bay though such winds 

were recorded on several days at the airport, 

at times exceeding 25 knots. 

The finding that higher incidence 

and abundance of harbor seals occurred in 

close proximity to ship corridors seemingly 

conflicts with the shipboard observations of 

seal disturbance. These results from the 

aerial surveys suggested that areas closer to 

ships were more regularly occupied by seals 

(and higher numbers of seals) than those 

more distant from ships. Ships generally 

favored the middle of the bay, as ice cover 

permitted, and would often navigate through 

open water or scattered ice that was 

immediately adjacent to denser ice (i.e., 

along an ice edge). If this were a regular 

occurrence, it would tend to put ships in 

43
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

close proximity to areas of denser ice 

favored by harbor seals and may explain the 

increasing seal density at decreasing 

distances to ship corridors. Moreover, it is 

worth noting that these surveys were 

designed, and the covariates measured, to 

examine seal responses at a larger spatiotemporal scale than the shipboard 

observations. Thus, the resulting seal and 

covariate measures were intended to test the 

responses of seals across multiple ship visits 

and days rather than those triggered by one 

cruise ship on one day. For example, a total 

of seven surveys were conducted on days 

when ships were present, or had been 

present earlier that day, or the previous day. 

So, the statistical model tested whether 

harbor seals integrated information to 

decide whether to haul out in an area close 

to where cruise ships had traveled 

previously. Testing the “real-time” 

reactions of seals to ships within the short 

time frame of a cruise ship visit, and over 

the whole of the bay, would require more 

intensive transect sampling on days when 

cruise ships were present. The studies in 

2004 and 2005 were designed to address 

these shorter-term responses (see Appendix 

2). Based on the current analysis, we 

conclude that harbor seals were not actively 

avoiding the general areas where cruise 

ships traveled in Disenchantment Bay, nor 

were they distributed at greater distances 

from these general areas when cruise ships 

were present. Possible avoidance of ship 

corridors across years (e.g., a long-term 

habituation) was not measured in this study. 

As with approach distance, the 

potential effect on seal abundance of the 

number of ships visiting over the preceding 

3-day period was expected to integrate any 

disturbance seals were experiencing across 

multiple days. The 3-day periods roughly 

corresponded to the weekly pulses 

(Tuesday-Thursday) and lulls (FridayMonday) in ship visits. Our findings 

showed that the number of vessels that 

ventured inside the bay was not a predictor 

of the cell counts of seals (i.e., abundance). 

This is supported by seasonal patterns in the 

total relative abundance of seals which were 

not clearly linked to the onset of, or to 

increases in, ship traffic. These were most 

likely driven by either life-history 

constraints or other more local 

environmental factors, such as prey 

availability (see Section 3.2.3.1). 

In conjunction with these findings, 

the negative effect of ship activity on seal 

distribution suggests that the area occupied 

by seals decreased with increases in the time 

ships spent at the closest approach, 

irrespective of distance. This apparent 

response did not include a concomitant 

decrease in abundance. That is, the 

expected numbers of seals simply occupied 

less area with increased ship presence in the 

bay. We conclude that seals were 

aggregating more closely in response to ship 

presence. A similar response has been 

observed in bottlenose and Hector’s 

dolphins, which form tighter aggregations in 

the presence of boats (Bejder et al. 1999; 

Buckstaff 2004). The formation of denser 

aggregations with increased ship presence 

was probably the result of disturbances of 

seals both in the path of moving vessels 

(e.g., within 500 m), and of seals at greater 

distances that may be more sensitive (e.g., 

more isolated solitary animals or smaller 

groups). That we did not see a negative 

effect of ship distance on seal distribution 

supports the conclusion that the aggregation 

effect was experienced by seals regardless of 

proximity to ships (i.e., seals were 

responding to ships at distances on the scale 

of kilometers). It is unknown if increased 

seal densities occurred: 1) when seals were 

first deciding when and where to haul out 

(assuming a ship was already present); 2) 

when seals were approached directly by 

ships and relocated; or 3) at some point 

44
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

later, as individual-seal thresholds for ship 

presence were gradually reached and seals 

entered the water to relocate. Whatever the 

case, such responses could result in greater 

time submerged – either initially finding a 

desirable area or re-entering the water later 

to do so – and higher energy expenditures 

compared to undisturbed seals hauling out in 

areas where, or on days when, ships are 

absent. The potential consequences to 

survival of increased time in the water are 

discussed in Section 3.1.3. 

3.3 Large Scale: Monthly Aerial 

Photographs of Regional Seal 

Distribution and Total Abundance at 

Disenchantment and Icy Bays 

3.3.1 Methods 

Disenchantment and Icy Bays were 

surveyed using large-format (9 in × 9 in) 

vertical aerial photography four times at 

approximately monthly intervals during the 

study (Fig. 2). The photogrammetric 

surveys (AeroMap, Inc., Anchorage, AK) 

were designed to provide complete coverage 

of the ice-filled regions of each bay, with 

20% endlap and 40% sidelap between 

neighboring photographs. The surveys were 

flown at 3000 ft, providing photographs at 

1:6000 scale. The surveys were initiated at 

1100-1600 h (ADT); the duration of surveys 

in Disenchantment and Icy Bays was 1-2 

hours and 2.5-3 hours, respectively. A total 

of eight large-scale photographic surveys 

producing 1,267 images was flown. 

Photographic negatives from the largeformat photographic surveys were scanned 

at high resolution (1600 dpi), and harbor 

seals in the resulting digital images were 

counted using image-processing software 

(ERDAS Imagine, Version 8.7, Leica 

Geosystems LLC, Norcross, GA. USA). 

These counts should be regarded as 

minimum abundance estimates because a 

correction factor (to account for the animals 

that were in the water and not counted) was 

not applied. These aerial surveys required 

better conditions than the medium-scale 

surveys (i.e., a 3000 ft ceiling and good 

visibility), so it seems unlikely that the 

minimal variation in weather conditions 

across days would have led to any 

differences in the propensity of the seals to 

haul out. 

Cruise ships visited Disenchantment 

Bay on the day of a survey only during 

August: there were three visits by cruise 

ships on 14 August and a total of eight over 

the previous 3 days. In Icy Bay, cruise ships 

were not observed during any survey and 

reportedly only rarely visit the area. 

Kayakers are fairly common during the 

summer months, with up to fifty groups 

estimated in 1995 (Kozie et al. 1996). 

3.3.2 Results 

3.3.2.1 Potential Sources of Error in 

High-Altitude Photogrammetry 

Aerial surveys provide the only 

tractable means of observing an entire ice 

haul-out area in the largest of glacial fjords. 

Even in smaller fjords, where seals are 

observable from shore, an aerial perspective 

is important to eliminate obscuring of seals 

by ice and land and reduced sightability with 

distance. Images also provide a permanent 

record that allow for detailed analyses of 

distribution in relation to environmental 

factors. Still, there were potential errors 

related to identifying and counting seals in 

high-altitude images that were unavoidable. 

The quality of the imagery taken at 

3,000 ft varied with atmospheric conditions 

(e.g., haze reduced contrast) and lighting 

(e.g., low solar angle produced shadows). 

Low contrast and shadows in images 

increased the misidentification of seals, 

particularly when dirty ice was present. 

Even under optimal conditions, seals in 

images appeared as dark shapes on a light 

45
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

background, lacking finer detail and usually 

color. Thus, the definition of a seal was 

based largely on shape which did not always 

set it apart from similar-looking shadows or 

patches of substrate on the ice. Because 

identification was partly subjective, what 

defined a seal varied between observers, and 

within observers as they gained experience. 

For example, observers with experience 

tended to be more conservative in declaring 

a seal. Future work will include quantifying 

these biases and correcting for them. 

Another potential bias was related to 

the sequence and timing of images. Because 

several transects were required, and each 

took up to 15 minutes to complete, the ice 

field – which was constantly shifting – 

differed in overlapping areas of images from 

adjacent transects. So, it was not possible to 

create an accurate mosaic of the entire area 

as the seams between transects did not 

match. Thus, from one transect to the next, 

we expected that seals would sometimes 

move from photographed to soon-to-be 

photographed areas (seals would be counted 

twice), and vice versa (seals would be 

missed). Observers attempted to match up 

ice floes with seals that occurred in both 

overlap zones of two adjoining images to 

reduce under- or over-counting. 

In the end, biases related to image 

quality were likely both positive (dirty ice 

and shadows were mistaken for seals) and 

negative (seals were mistaken for dirty ice 

and shadows). Similarly, if ice moved 

randomly across transects, the biases related 

to the timing of images would be both 

positive and negative. In 2005, the mediumand large-scale photogrammetry surveys 

were flown simultaneously on 3 days to 

compare seal sightings in order to estimate 

these biases. Pending that analysis, we 

assumed that the positive and negative 

biases discussed above were balanced. Still, 

it appears that these counts provide the best 

available estimate of seal abundance in the 

large, shifting ice fields that characterize 

tidewater glacial fjords. 

3.3.2.2 Seal Counts from 

Photogrammetry 

Table 1 lists the estimated number of 

harbor seals at both Disenchantment and Icy 

Bays for the eight high-altitude surveys 

flown in 2002. Overall, seal counts for Icy 

Bay were higher than those for 

Disenchantment Bay, with the exception of 

during early pup-rearing when seal 

abundance in Disenchantment Bay was 

about 50% greater than that at Icy Bay. This 

difference diminished by mid-pupping 

(June) when Disenchantment Bay had 18% 

fewer seals than Icy Bay. From early to 

mid-pupping, Disenchantment Bay 

increased 39% and Icy Bay counts more 

than doubled. From mid-pupping on, the 

two sites had divergent trends: counts at Icy 

Bay increased, whereas those at 

Disenchantment Bay decreased. By the 

pup-weaning period (July), Disenchantment 

Bay had 43% fewer seals than Icy Bay and 

67% fewer by molting (August). During the 

entire study, from early May to mid-August, 

abundance estimates at Icy Bay increased 

more than 400% (100% from mid-pupping) 

compared to 15% at Disenchantment Bay. 

It should be noted that the 

extraordinarily low count in May at Icy Bay 

could have been influenced by limiting the 

survey to northern areas of the bay closest to 

Guyot Glacier. Due to flight constraints, 

areas of scattered ice south of Kichyatt Point 

were not surveyed (Fig. 2). Though not 

apparent at the time of the survey, the areas 

closest to the glacier were then dominated 

by fast ice and thus less accessible to seals. 

For example, in May, images showed that 

ice cover that appeared virtually solid 

extended 3.3 km (1.8 nm) south from Guyot 

Glacier (Fig. 2) and the first scattered, small 

groups of harbor seals were observed at 

about 2 km (1.1 nm) from the face. This 

46
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

Table 1. Summary of harbor seal counts (uncorrected) from the high-altitude photogrammetry in 2002. 

Dates and start times are presented for each survey for Disenchantment (Dbay) and Icy Bay (Icy). The 

minimum abundance estimates marked with an asterisk may be negatively biased: at Icy Bay in May, there 

was lesser coverage of scattered to intermediate ice zones; at Disenchantment Bay in August, the survey was 

conducted late in the day when fewer seals may have been hauled out. The mean of counts (by site) and 

coefficients of variation (CV) are shown. 

Date 

(Dbay/Icy) 

Seal Phenology 

(Dbay) 

Time (ADT) 

(Dbay/Icy) 

Counts 

Dbay Icy 

2/4 May Early Pupping 1208/1357 1,544 1,011* 

7 June Mid-pupping 1152/1407 2,149 2,543 

7 July Weaning/Breeding 1147/1436 1,786 3,566 

14/15 August Molting 1557/1318 1,778* 5,435 

Mean 1,814 3,142 

CV 0.14 0.59 

contrasts conditions in August when seals 

were within 0.6 km (0.3 nm) of the glacier 

in areas of scattered ice. For the one survey 

in May, it is unknown how many seals may 

have been missed in areas we were unable to 

survey. The few reconnaissance flights 

conducted south of Kichyatt Point when 

significant ice was present (in 2004) 

estimated between less than 100 to 300 

seals. It is interesting to note that fast ice 

apparently does not form in Disenchantment 

Bay in the winter – when calving is at a 

minimum – nor has it been noted in regard 

to other tidewater glacial haulouts for 

Alaska harbor seals. 

The seal count in August at 

Disenchantment Bay may also have been 

biased low as that survey took place later in 

the day (1557 h ADT) than in previous 

surveys (~1200 h ADT). As noted above, 

patterns at other glacial sites (see Fig. 6) 

suggest that haul-out frequency peaks in the 

early afternoon and starts declining some 

time after 1600 to 1700 h (ADT). Based on 

this pattern, at most 15% of the seals may 

have entered the water during the 1.2 hour 

survey, bringing the potential count for 14 

August up to 2,134 seals. 

3.3.3 Discussion 

These findings suggest differences in 

the seasonal use of the two glacial sites, 

and/or in the annual timing of life-history 

events, such as pup rearing and molting. 

The comparatively low count at Icy Bay in 

early pupping (May) could be attributed to a 

survey bias, as detailed above, or to an 

actual reduction in the number of seals using 

the bay in the early pupping stages, such as 

observed in Disenchantment Bay. If the 

latter, the early May survey of Icy Bay 

might have occurred just after the decline 

47
3.0 Three Spatio-Temporal Scales for Studying Harbor Seals 

rather than before as in Disenchantment 

Bay; Icy Bay was surveyed 2 days after 

Disenchantment Bay. If a survey had been 

flown in late April, seal counts might have 

been considerably higher, as they were in 

Disenchantment Bay before its decline. In 

this case, these seemingly large differences 

in abundance – by comparing the use of the 

haul outs at one point in time – may have 

resulted simply from differences in the 

timing of seal movements in response to 

various factors. If seals were migrating in 

response to localized conditions, like prey 

availability, the timing of distributional 

shifts between feeding and haul-out areas 

would likely differ, perhaps even 

significantly, between Icy and 

Disenchantment Bays. Such variation in 

seal movements across relatively small 

scales would be consistent with the variable 

location, timing, and magnitude of prey 

aggregations reported for the Yakutat 

Forelands (see section 3.2.3.1). 

Alternatively, if seals were migrating 

largely to accommodate life-history 

constraints, such as a synchronization of 

male and female movements during 

breeding, one might expect less variation in 

the timing of movements when comparing 

these nearby glacial fjords. For example, 

reproductive synchronization in wild and 

captive female harbor seals has been shown 

to be affected by the photoperiod just prior 

to blastocyst implantation (Temte 1994). 

Females at a given location (i.e., latitude), 

provided they are in adequate condition, are 

likely to begin gestation at about the same 

time (± 2-3 weeks) and thus parturition will 

be similarly synchronized. This explains the 

latitudinal gradient in the timing of pupping 

observed along the West Coast of North 

America, from Mexico (mid-March; 30° N) 

to Washington State, U.S.A. (late May/early 

June on the outer coast; 48° N; Newby 1973; 

Johnson and Jeffries 1977; Temte et al. 

1991). However, because pupping at 

Disenchantment Bay (60° N) occurs at about 

the same time as the outer coast of 

Washington State, local or regional factors 

must at times mediate intrinsic factors, as 

proposed by Temte (1994). In Washington 

State, harbor seals located in the shelter of 

Puget Sound initiate pup rearing at least a 

month later than those on the outer coast 

(Bigg 1969; Newby 1973; Calambokidis et 

al. 1978). In the Gulf of Alaska, the timing 

of peak pup rearing, from Glacier Bay to the 

Alaska Peninsula, is consistently around late 

May to mid-June (Bishop 1967; Burns 1970; 

Pitcher 1975; Pitcher and Calkins 1979; 

Streveler 1979; Hoover 1983; this study). 

Across multiple years at a single site, the 

peak of pupping has also been shown to vary 

within about a two-week period (Tugidak 

Island, Alaska [56° N]; Jemison and Kelly 

2001). 

Therefore, based on the similar 

environments and photoperiods, and close 

proximity of Icy and Disenchantment Bays, 

we would not expect large differences in the 

peak timing of parturition between sites, and 

therefore in the seasonal use of floating ice 

by pregnant females. Attendance of adult 

males at glacial sites is also anchored 

seasonally because females enter estrous a 

few days after weaning pups (Bigg and 

Fisher 1974). Juvenile seals, however, do 

not participate directly in pup-rearing or 

breeding and are thus not expected to have 

the same constraints. So, younger seals are 

likely to be more flexible in responding to 

variations in local conditions, such as prey 

availability and human disturbance. 

Moreover, juveniles may compose at least a 

third to half of the seals present on the ice 

when averaged over the entire period from 

May to August (Aialik Bay; Hoover 1983). 

We thus hypothesize that even modest 

variation in the attendance patterns of 

juvenile seals alone could cause large 

differences when comparing seal abundance 

between neighboring areas. More 

48
specifically, we suspect that it was 

differences in the timing of juvenile seal 

movements between Icy and 

Disenchantment Bays that caused the 

contrasting counts during early pupping. 

Such movements, as noted above (see 

Section 3.2.3.1), are consistent with 

observed fluctuations in the number of 

juvenile seals present from May to August 

in Aialik Bay (Hoover 1983). The mediumscale surveys conducted at both sites in 2004 

and 2005 during pupping and molting will 

likely shed light on these hypotheses. 

The abundance of hauled out Alaska 

harbor seals is believed to peak during puprearing and molting (Glacier Bay: 

Calambokidis et al. 1987; Tugidak Island: 

Jemison and Kelly 2001). In our study, 

Disenchantment Bay showed a modestly 

elevated seal count during pup-rearing – but 

not during molting – and Icy Bay exhibited a 

pronounced peak during molting – but not 

during pup-rearing. It should be noted that 

the monthly resolution of our surveys may 

have missed finer-scale patterns. Still, the 

extraordinary increase from May to August 

at Icy Bay – to more than twice the level 

observed during pup-rearing – suggests an 

influx of animals from outlying areas. It 

may be that Icy Bay serves as a molting site 

for seals over a broader area though nearby 

haul outs are scarce due to the exposed 

coastline southeast to Yakutat Bay (115 km) 

and west to Seal River/Bering Glacier (120 

km) and Kayak Island (160 km). It could 

also be that a significant segment of the 

local population at Icy Bay, possibly 

juveniles, hauls out less frequently or at less 

predictable times most of the year except 

during the annual molt. 

It is interesting that counts at nearby 

Disenchantment Bay did not show a similar 

(pronounced) peak in August (e.g., seal 

numbers appeared unchanged from July and 

may have dropped slightly from June). As 

noted above, the diel timing of the survey on 

4.0 Conclusions 

14 August was delayed compared to earlier 

surveys but this possible bias alone cannot 

account for the striking contrast with the 

peak during molting at Icy Bay. It is worth 

noting that ice coverage in Disenchantment 

Bay on 14 August reflected an increase 

since the minimum had been reached for the 

medium-scale surveys on 4 August (< 5% of 

the maximum ICA) and seals were confined 

to the northernmost part of the bay (Fig. 19). 

On 14 August, seals were on large patches 

of denser ice (> 1 km2) that were distributed 

as far south as Egg (Haenke) Island. It 

therefore appears unlikely that ice cover was 

a factor limiting the abundance of seals 

during this mid-August survey. 

Though the findings at the medium 

scale indicate that seals do not abandon the 

haul-out area as a shorter-term response (1-3 

days) to the number, proximity, or visit 

duration of cruise ships, the data collected 

here cannot address directly a possible 

avoidance of ships by seals over longer 

temporal scales. For example, if seals were 

incurring a direct, constant, even small, 

energetic cost due to cruise ship disturbance, 

they may decide over the course of months 

to years to emigrate to a different area, or 

adjust their seasonal use patterns to include 

new areas. Due to a suite of factors, 

disturbance perhaps among them, some sites 

may be more suitable for molting, whereas 

others may be better for pup-rearing or 

breeding. 

4.0 Conclusions 

Our results show that harbor seals 

are sensitive to cruise ships that approach 

within 500 m – to which they respond by 

abandoning ice floes – and to the amount of 

time cruise ships are present in the bay – to 

which they respond by forming denser 

aggregations with increasing ship presence. 

It does not appear that seals change their use 

of the haul-out area within a season in 

49
relation to the movement corridors of cruise 

ships, or limit their attendance in the bay 

due to seasonal and weekly patterns of 

cruise ship visits. Further analyses on the 

2004 and 2005 data will be used to confirm 

these relationships, and test within-day, 

larger-scale responses to ships. 

The comparison with Icy Bay, which 

had no known visits by cruise ships, points 

to some differences that deserve further 

attention. Both the declining abundance at 

Disenchantment Bay from pupping to 

molting, and the opposite trend at Icy Bay 

over the same period, were unexpected. The 

resulting three-fold difference in abundance 

between sites during molting highlights the 

general pattern that Icy Bay attracts many 

more seals than Disenchantment Bay 

throughout late spring and summer. More 

standardized comparisons – which would 

include environmental measures, such as 

habitat availability – will be made using data 

from the 2004 and 2005 field seasons. 

Nevertheless, a possible movement of seals 

from Disenchantment Bay to Icy Bay prior 

to molting should be examined in relation to 

natural and anthropogenic covariates. It is 

also notable that pup productivity in 

Disenchantment Bay appears to be low 

when compared to other glacial and 

terrestrial sites. Here again, more detailed 

comparisons with Icy Bay using data from 

2004 and 2005 will shed more light on 

differences in productivity between the 

neighboring glacial sites. 

Our findings that harbor seal 

occurrence and behavior in Disenchantment 

Bay are modified in the presence of cruise 

ships point to certain demographic 

mechanisms that could lead to a decline in 

seal abundance, as has been a concern of the 

Yakutat Tlingit Tribe and was the impetus 

for this study. Such mechanisms include: 

1) reduced natality due to avoidance of the 

area by females, disruption of breeding, or 

poor female condition during implantation 

4.0 Conclusions 

or gestation; 2) shifts in the seasonal-use 

patterns of harbor seals in the greater 

Yakutat/Icy/Dry Bay Area; 3) emigration of 

adult males or juveniles due to cumulative 

disturbance; and 4) reduced survival of 

seals, especially younger animals, due to 

altered haul-out behavior and energy 

balance. Some of these hypotheses will be 

addressed through analyses of existing data 

(i.e., for 2004 and 2005) but comprehensive 

hypothesis testing will require additional 

data collection, particularly on haul-out 

behavior and seasonal habitat use of a 

sample of tagged individuals. 

It is also possible that the population 

decline perceived by some in the Yakutat 

Tlingit Tribe could have resulted, at least in 

part, from a reduction in availability of seals 

to hunters without an actual drop in seal 

abundance. A shift toward tighter 

aggregations in response to ships, especially 

where small groups and individuals at the 

periphery move inward, could effectively 

reduce the availability (i.e., perceived 

abundance) of harbor seals to subsistence 

hunters. If seals show a pattern of clustering 

within, or shifting toward, denser ice as a 

short- or long-term response to cruise ships, 

we would expect fewer encounters with 

Native hunters who have to push through the 

ice in small boats. Seal harvesting in 1992 

to 1994 in Disenchantment Bay reportedly 

occurred predominantly south of Turner 

Glacier where ice is less dense than north 

between the two glaciers (Davis 1999). 

Continued monitoring of abundance will be 

helpful in determining whether an actual 

population decline is currently underway. 

Our focus has been to document the 

more proximate effects of cruise ships (e.g., 

avoidance reactions within a season) while 

establishing baseline seal abundance for 

monitoring trends. Gaining these 

perspectives is a critical first step to 

formulating timely management strategies 

and testable hypotheses for longer-term 

50
studies of the ultimate impacts of 

disturbance (e.g., shifts in demography 

across years). Future study of the possible 

causes of a population decline in 

Disenchantment Bay should include other 

environmental stressors, such as variation in 

prey availability and subsistence hunting. 

Combined with the TEK of the 

Yakutat Tlingit Tribe, this study sought to 

characterize the harbor seals in Ateix’ 

(Disenchantment Bay) and their range of 

interactions with the environment, in 

particular with cruise ships. The study 

design was improved by considering the 

Tlingit Tribe’s knowledge and rich history 

regarding the harbor seal population that has 

been part of the local culture for probably 

more than a thousand years. The future 

conservation of these harbor seals relies on 

what the Tlingit refer to as “Haa Kusteeyi” 

(our way of life), which is to say that respect 

for and wise use of the resources in Ateix’ 

will ensure that future generations will have 

the same opportunities. 

5.0 Acknowledgments 

We thank the following people for 

helping to observe seals from cruise ships: 

Marc Basterretche (Southwest Fisheries 

Science Center, NOAA), Michael Cameron 

(AFSC/NMML), Alana Phillips 

(AFSC/NMML), Dana Seagars (U.S. Fish 

and Wildlife Service), Jim Wilder (U.S. 

National Park Service), and Dave Withrow 

(AFSC/NMML). We are grateful for the 

traditional ecological knowledge passed on 

to us during discussions with Bert Adams 

Sr., Bert Adams Jr., Victoria Demmert, 

Sheldon James, George Ramos, David 

Ramos, Ray Sensmeier, and other Tribal 

elders and members of the Yakutat Tlingit 

Tribe. The profound extent of their 

traditional knowledge, and the Tribe’s long 

history in the area, was most acutely 

demonstrated during guided trips around 

their ancestral lands and waters. These 

discussions with the local Native community 

were very important to the formulation of 

the working hypotheses. We also thank the 

Yakutat Tlingit Tribe, particularly Bert 

Adams Jr., for help in arranging logistics, 

for providing office space, and for 

sponsoring two very helpful and insightful 

student interns, Derek James and Lori Vale, 

whose dedication and hard work contributed 

much to the project’s success. We 

appreciate the support of John Hanson, 

president of the NorthWest CruiseShip 

Association (NWCA), and the NWCA 

members’ interest in working with the 

Yakutat Tlingit Tribe and NMML to 

enhance the understanding of harbor seals 

and cruise ships. In addition to partly 

funding this study, NWCA provided 

transportation, via Cruise Line Agencies of 

Alaska (CLAA), for our observers to and 

from cruise ships. David Eley (NWCA), 

Rick Erickson (CLAA), and Judee Mettler 

(CLAA) were helpful liaisons to the cruise 

line industry, especially regarding the 

logistics for boarding cruise ships. We 

thank John Nylen and the crew of the M/V 

Survey Point for safely getting observers out 

to cruise ships and back. Mary Kralovec, 

Mary Beth Moss, Mason Reid, Devi Sharp, 

and others at the U.S. National Park Service 

generously provided significant financial 

support for the large-format photography 

surveys, as well as personnel for field work. 

We thank Kaja Brix, of NOAA-NMFS’ 

Alaska Regional Office, for her help in 

bringing together various parties interested 

in studying harbor seal disturbance at 

Disenchantment Bay so that this research 

could be undertaken. Jack Endicott and the 

Yakutat Office of NOAA’s National 

Weather Service kindly offered use of an 

apartment as a base of operations for both 

working and living. Lead ranger, Tricia 

O’Connor, and numerous other employees 

of the Yakutat District of the U. S. Forest 

51
Service (USFS), were instrumental in 

getting the study off the ground and keeping 

it moving. In particular, USFS personnel 

Bill Lucey, Dan Gillikin, and Ian Colvert 

each provided their wise perspectives and 

expertise to enhance the study and the 

overall enjoyment of working in a place of 

remarkable beauty. We are especially 

obliged to Bill Lucey for lending his skills in 

wildlife surveying to the aerial seal surveys, 

and for sharing his diverse knowledge of the 

Yakutat area. In enabling us to maintain and 

download the weather station at Egg 

(Haenke) Island, we thank Paul Wescott and 

Scott Chadwick (City of Yakutat) for the use 

of the M/V Y-Sam, and Bob Johnson 

(Alaska Department of Fish and Game) and 

Bert Adams Sr. (Yakutat Tlingit Tribe) for 

going “just a little farther” through thick ice 

in their respective boats. The 

professionalism of Dave, Charlie, and 

Janeen Russell of Yakutat Coastal Airways 

instilled confidence that we would have a 

safe and productive aerial survey; we were 

particularly impressed with their ceaseless 

flexibility and eagerness to make surveys 

successful – even if it meant re-engineering 

a video camera mount designed by 

biologists. Pamela Bergeret of Ashbury 

International Group Inc. generously loaned 

us an extra pair of Leica rangefinder 

binoculars which proved indispensable. We 

also extend our gratitude to Dana Seagars 

who devoted extra time helping to update 

GIS coverages by remapping the face of 

Hubbard Glacier and by providing valuable 

assistance in setting up a GIS database. 

Lastly, we are grateful for the patience and 

constancy of Alana Phillips, Kerry Logan, 

Rajit Patankar, and Luciana Santos when 

counting seals from the large-scale 

photogrammetry, and to Mike Simpkins for 

coordinating the logistics and analysis of the 

imagery. 

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59

Appendices 

Appendix 1. Details of the 

Space-Time Model 

A1.1 Zero-Inflated Poisson 

Regression Model 

Let the data be denoted 

yij = 0,1,2,K, for the observation at the jth 

location at the ith time period. We will 

assume that the observed data follow a zeroinflated Poisson regression model, 

yij | xij ~ 

⎩

⎨

⎧

Poi

0

(λij ) 

if

if 

x

x

ij

ij 

=

=1

0 

xij ~ Bin(1, pij ) , 

where Poi(•) is a Poisson distribution, 

Bin(1,•) is a Bernoulli distribution, and 

logit( pij ) = μi + s′

ij α +δ ij , 

log(λij ) =ν i + s′

ij β + ε ij . 

A1.1.1 Spatial Effects 

There were three covariates that 

varied spatially within a given time period; 

ice cover type, distance to ship, and ship 

activity. The values for these three 

covariates were contained in the vector s′

ij 

for the jth location in the ith time period, and 

we allowed a separate mean response for the 

Bernoulli distribution ( pij ) and the Poisson 

distribution ( λij ). We denoted α as a 

vector of parameters for the Bernoulli 

distribution, and β as a vector of parameters 

for the Poisson distribution. 

A1.2 Spatial Conditional 

Autoregressive Model 

We also allowed for spatiallyautocorrelated random effects for each mean 

response. Let δi be a set of random effects 

Appendix 1. Details of the Space-Time Model 

at spatial locations for the ith time period. 

We assumed that δi follows a conditional 

autoregressive model (CAR) as described in 

Cressie (1993, pg. 407), 

δi ~ Gau(0,σ δ

2

(I − ρδC)

−1

M) 

where Gau(•,•) is a (multivariate) Gaussian 

(normal) distribution. We defined a 

neighbor of a sample as any other sample 

with its centroid within 1 km. The weights 

in C were row-standardized (Haining 1990, 

pg. 82); that is, each row in C contained all 

zeros except for columns that indicate a 

neighbor, and these values were the inverse 

of the number of neighbors for that sample. 

The diagonal elements of M also contained 

the inverse of the number of neighbors. 

Similarly, let εi be a set of random effects at 

spatial locations for the ith time period. We 

assumed that εi followed a CAR model, as 

for δi , except it has its own parameters σ ε

2 

and ρε ; 

εi ~ Gau(0,σ ε

2

(I − ρεC)

−1

M) . 

For both δi and εi , we assumed that they 

were independent from each other and 

across time periods. 

A1.2.1 Time Effects 

There were five covariates that 

varied temporally, but not spatially: 

presence of a cruise ship, number of cruise 

ships in previous 3 days, precipitation, wind, 

and number of samples with ice; that is, 

these covariates operated for all locations at 

a given time. Thus, we let the intercept for 

each time period be a function of these 

covariates, 

μi = μ0 + wi γ + τi , 

63
Appendix 1. Details of the Space-Time Model 

ν i =ν 0 + wi η+ξ i . 

The values for these 5 covariates are 

contained in the vector wi for the ith time 

period, and γ is a vector of parameters for 

the Bernoulli distribution, and η is a vector 

of parameters for the Poisson distribution. 

A1.3 Temporal AR1 Model 

We allowed for temporallyautocorrelated random effects for each mean 

response. Let τ be a set of random effects 

for all time periods past the first one. We 

assumed that τ followed a first order 

autoregressive model (AR1) as described in 

Hamilton (1994, pg. 53), 

τ i = φττ i−1 +στZi ; i > 1, 

where τ 1 = 0 and Zi ~ Gau(0,1) are 

independent. This yielded a multivariate 

normal distribution 

τ ~ Gau(0,στ

2

Ω(φτ ) ), 

where the correlation matrix Ω(φτ ) has a 

special structure (Hamilton 1994, pg. 120), 

and depends on the parameter φτ . Likewise, 

let ξ be a set of random effects for all time 

periods past the first one. We assumed that 

ξ also follows a first order autoregressive 

model (AR1), 

ξi = φξξi−1 +σ ξZi ; i > 1, 

where ξ1 = 0 and Zi ~ Gau(0,1) are 

independent. This again yields a 

multivariate normal distribution 

ξ ~ Gau(0,σ ξ

2

Ω(φξ ) ). 

A1.3.1 Prior Distributions 

We put diffuse priors on all 

regression parameters: α , β , γ , η. 

Because these were modeled on a log scale, 

there are computation instabilities if they are 

allowed to get too large, so we let each 

regression parameter have a normally 

distributed prior with a variance of 10. The 

autoregression parameters for both space, 

( ρδ and ρε ) and time (φτ and φξ ) are 

bounded from -1 to 1, but we did not expect 

any negative autocorrelation, so we used 

uniform priors from 0 to 1. For the variance 

parameters of the random effects 

(σ δ

2 ,σ ε2 στ2 ,σ ξ

2 ), we let the square root be 

uniformly distributed between 0 and 10; 

again, to keep the random effects from 

becoming too large and causing numerical 

instability. 

A1.3.2 Standardized Selection 

Coefficients 

When working with categorical 

covariates in logistic regression, coefficients 

are often interpreted on the logit scale, and 

referred to as “log odds.” However, this 

only facilitates comparing to a single 

category for a single model. In this study, 

we wanted to compare the relative 

importance between categories, and within 

categories for all seals versus mother-pup 

pairs. Hence, we created standardized 

selection coefficients (Manley et al. 2002, 

pg. 51). These are most easily interpreted 

back on their original scale. For example, 

for the 9 categories of ice cover for the 

Poisson part of the model, we obtain the 

posterior distribution of, 

β[ k ] 

β

~[k ] = e 1 

1 9 

∑eβ1

[ k ] 

k=1 

where β[k ] 

m is the coefficient for the kth

64
Appendix 1. Details of the Space-Time Model 

category for the mth variable. Because this be interpreted as the relative importance of 

is just a function of the β m 

[k ] , it is easy to each category, where the categories sum to 

obtain its posterior distribution through the one. 

use of Markov Chain Monte Carlo 

(MCMC). Likewise, for the Bernoulli part A1.4 Computation 

of the model, Models were fit using MCMC in the 

WinBUGS software. We used a burn-in of 

e

α[ k ] 

/(1+ e

α[ k ] 

) 100,000 iterations, and then used 500,000 

α

~[k ] = 1 1 iterations for estimates and credibility 1 9 [ k ] [ k ]

∑(e

α /(1+ eα )) intervals on all parameters and functions of 1 1 

parameters. k=1 

The standardized selection coefficients can 

A1.5 Results 

Table 2. Bernoulli regression estimates for the zero-inflated, space-time Poisson model to examine the cellbased absence/presence (i.e., spatial distribution) of pooled seals. Factors with a * are significantly different 

from 0. 

Bernoulli Regression 

Factor Coefficient Estimate 2.5% CI 97.5% CI 

Ice Cover Type*-1/10th – 2/10th [1] α1 0 - -

2/10th – 3/10th [2] α1 1.061 0.384 1.742 

3/10th – 4/10th [3] α1 1.179 0.427 1.935 

4/10th – 5/10th [4] α1 1.860 1.045 2.747 

5/10th – 6/10th [5] α1 2.161 1.180 3.282 

6/10th – 7/10th [6] α1 2.086 0.839 3.501 

7/10th – 8/10th [7] α1 1.889 0.557 3.392 

8/10th – 9/10th [8] α1 2.456 -1.153 7.176 

9/10th – 10/10th [9] α1 3.481 -0.132 7.855 

Distance to Nearest Ship* α 2 -2.750 -4.792 -0.930 

Ship Activity* α3 -0.449 -1.113 -0.329 

Presence of Ship γ 1 -1.006 -4.586 2.606 

Precipitation (Last 6 Hours) γ 2 -0.291 -1.593 0.928 

Wind (Last 6 Hours) γ 3 -0.499 -1.594 0.499 

Number Samples with Ice γ 4 -0.632 -2.369 0.947 

Number Ships (Last 3 Days) γ 5 -1.352 -3.501 0.972 

65
Appendix 1. Details of the Space-Time Model 

Table 3. Poisson regression estimates for the zero-inflated, space-time Poisson model to examine the cellbased abundance of pooled seals. Factors with a * are significantly different from 0. 

Poisson Regression 

Ice Cover Type*-1/10th – 2/10th [1] β1 0 - -

2/10th – 3/10th [2] β1 0.491 -0.057 1.061 

3/10th – 4/10th [3] β1 1.090 0.474 1.704 

4/10th – 5/10th [4] β1 1.026 0.368 1.696 

5/10th – 6/10th [5] α1 1.390 0.639 2.148 

6/10th – 7/10th [6] β1 1.694 0.823 2.547 

7/10th – 8/10th [7] β1 1.447 0.530 2.377 

8/10th – 9/10th [8] β1 -0.249 -1.634 1.383 

9/10th – 10/10th [9] β1 -1.279 -3.183 0.522 

Distance to Nearest Ship* β 2 -1.774 -3.590 -0.155 

Ship Activity β3 -0.007 -0.443 0.409 

Presence of Ship η1 -1.082 -4.062 1.617 

Precipitation (Last 6 Hours) η2 -0.363 -1.142 0.435 

Wind (Last 6 Hours) η3 0.183 -0.612 0.995 

Number Samples with Ice η4 -0.049 -0.909 0.837 

Number Ships (Last 3 Days) η5 -0.515 -1.913 0.788 

Table 4. Bernoulli regression estimates for the zero-inflated, space-time Poisson model to examine the cellbased absence/presence (i.e., spatial distribution) of mother-pup pairs. Factors with a * are significantly 

different from 0. 

Bernoulli Regression 

Factor Coefficient Estimate 2.5% CI 97.5% CI 

Ice Cover Type*-1/10th – 2/10th [1] α1 0 - -

2/10th – 3/10th [2] α1 -0.539 -2.998 1.538 

3/10th – 4/10th [3] α1 -1.633 -4.792 0.880 

4/10th – 5/10th [4] α1 1.159 -1.446 4.153 

5/10th – 6/10th [5] α1 0.055 -2.806 3.263 

6/10th – 7/10th [6] α1 3.508 0.313 7.418 

7/10th – 8/10th [7] α1 3.402 0.305 7.462 

8/10th – 9/10th [8] α1 1.919 -2.392 6.834 

9/10th – 10/10th [9] α1 -0.510 -6.612 5.842 

66
Appendix 1. Details of the Space-Time Model 

Bernoulli Regression 

Factor Coefficient Estimate 2.5% CI 97.5% CI 

Distance to Nearest Ship α 2 0.394 -2.490 4.262 

Ship Activity α3 1.103 -1.255 3.320 

Presence of Ship γ 1 -0.860 -5.959 3.958 

Precipitation (Last 6 Hours) γ 2 2.469 -0.106 6.097 

Wind (Last 6 Hours) γ 3 -0.723 -2.880 1.397 

Number Samples with Ice γ 4 -0.839 -3.418 1.548 

Number Ships (Last 3 Days) γ 5 -0.736 -3.760 2.782 

Table 5. Poisson regression estimates for the zero-inflated, space-time Poisson model to examine the cellbased abundance of mother-pup pairs. Factors with a * are significantly different from 0. 

Poisson Regression 

Ice Cover Type*-1/10th – 2/10th [1] β1 0 - -

2/10th – 3/10th [2] β1 1.518 0.557 2.477 

3/10th – 4/10th [3] β1 2.541 1.430 3.608 

4/10th – 5/10th [4] β1 0.943 -0.209 1.983 

5/10th – 6/10th [5] α1 2.312 1.094 3.442 

6/10th – 7/10th [6] β1 1.328 0.120 2.444 

7/10th – 8/10th [7] β1 1.121 -0.147 2.308 

8/10th – 9/10th [8] β1 -0.457 -3.199 1.769 

9/10th – 10/10th [9] β1 -1.387 -6.716 3.327 

Distance to Nearest Ship β 2 -1.740 -3.594 0.072 

Ship Activity β3 0.039 -0.435 0.463 

Presence of Ship η1 0.490 -2.937 3.956 

Precipitation (Last 6 Hours) η2 -0.674 -1.544 0.210 

Wind (Last 6 Hours) η3 0.171 -1.014 1.301 

Number Samples with Ice η4 0.056 -0.899 1.173 

Number Ships (Last 3 Days) η5 -0.872 -2.609 0.756 

67

Appendix 2. Data Collection on Harbor Seals in 2004 

Appendix 2. Data Collection on 

Harbor Seals in 2004 

The Polar Ecosystems Program of 

the Alaska Fisheries Science Center’s 

National Marine Mammal Laboratory 

continued its research program in 2004 to 

examine in greater depth the factors 

affecting seal abundance and distribution in 

Disenchantment and Icy Bays. With 

funding from NOAA and logistical 

assistance from the Yakutat Tlingit Tribe 

(Yakutat Tlingit Tribe) and the NorthWest 

Cruiseship Association, data collection 

focused on four main elements: 1) Mediumscale aerial surveys were flown using an 

improved method for imaging and mapping 

seals. In addition to Disenchantment Bay, 

these surveys were expanded to include Icy 

Bay to allow for more detailed comparisons 

in areas with and without cruise ship traffic; 

2) Student interns from the Yakutat Tlingit 

Tribe continued boarding cruiseships to 

collect sighting data on seal groups; 3) 

Cruise ship movements in Disenchantment 

Bay were again tracked by Yakutat Tlingit 

Tribe’s interns and NMML biologists 

embarked on vessels; and 4) Large-format 

photogrammetry was again conducted at 

Disenchantment and Icy Bays during seal 

molting to extend the time series of total 

abundance counts (i.e., for 2001, 2002, 

2004) for examination of potential trends. 

A2.1 Fine-Scale Study 

Under the coordination of NWCA 

and Cruiseline Agencies of Alaska (CLAA), 

student interns from the Yakutat Tlingit 

Tribe and NMML biologists boarded cruise 

ships from 19 May to 20 July 2004 in 

conjunction with embarkations of pilots and 

cultural interpreters from Yakutat. Seal 

observers were positioned amidships to 

count harbor seal groups as they passed 

abeam of the ship and measured their 

distance from the ship using range finding 

binoculars (Leica VectorTM or GeovidTM, 

Ashbury International Group, Inc., Sterling, 

VA) or inclinometers when rain or fog 

hampered the use of the range-finders. 

These data will be used to calculate seal 

densities as a function of distance from ship. 

Observers also recorded the ship movement 

using portable GPS units (Garmin 76 or 90, 

Garmin International Inc., Olathe, KS). 

The first three cruise ship visits of 

the season in Disenchantment Bay (two on 

11 May, one on 12 May) did not embark a 

pilot or interpreters from Yakutat so 

observers were unable to board. These visits 

were instead monitored remotely from an 

observation camp on Egg (Haenke) Island in 

Disenchantment Bay. Observers used 

range-finding binoculars to measure distance 

and bearing to ships at ca. 5-minute intervals 

during their visits. Observers also recorded 

the behavior of harbor seals hauled out on 

ice when ships were both present and not. 

Using spotting scopes, seal groups were 

observed for 15 seconds each minute and 

were usually observed for 10 minutes. The 

behavioral state of each seal in a group was 

recorded using the same categories as the 

shipboard observations conducted in 2002 

(see methods above). Only the “highest” (or 

most disturbed) behavioral state was 

recorded if more than one state was 

exhibited during the observation. Mothers’ 

and pups’ behavior was recorded separately 

from others when it was discernable. 

Observers also estimated the longest axis of 

the ice on which groups were hauled out and 

the total ice concentration (to the nearest 

tenth) within 50 m of the seal group. 

Observers boarded 50 of the 83 

cruise ships that visited Disenchantment Bay 

during the study period, counting and 

measuring distances to a total of 2,182 

harbor seals in 1,221 groups (Fig. 23). 

Complete navigational tracks were obtained 

from ca. 40 ships; poor GPS coverage 

sometimes produced incomplete tracks. 

Observers on Egg (Haenke) Island recorded 

69
Appendix 2. Data Collection on Harbor Seals in 2004 

Figure 23. Distribution of cruise ship visits to Disenchantment Bay, with and without observers, and 

aerial surveys flown at both Disenchantment and Icy bays, 3 May to 20 July 2004. 

position data on three cruise ships and observations without cruise ships present 

collected behavioral data from 31 seal will provide useful baseline data of the 

groups, including 16 with and 15 without seals’ ambient (undisturbed) behavior. 

cruise ships present, respectively. The 

70
Appendix 2. Data Collection on Harbor Seals in 2004 

A2.2 Medium-Scale Study 

Aerial photographic surveys of 

harbor seal relative abundance and 

distribution were conducted in 

Disenchantment Bay from 3 May to 20 July 

2004. Four surveys were flown before the 

first entry of a cruise ship into the bay and 

two more were flown on the first 2 days 

thereafter. Thereafter, we timed the surveys 

according to the weekly pattern of cruise 

ship visitation, with one survey flown early 

in the week during a period of low cruise 

ship visitation and one survey (or sometimes 

two, during the pupping season) flown midweek during days of high cruise ship 

visitation (Fig. 23). As in 2002, surveys 

were flown between 1300 and 1500 h (local 

time) to coincide with the daily peak in 

number of seals hauled out (Hoover 1983; 

Calambodkidis et al. 1987; Jansen et al. 

2001). We used a different aircraft from the 

one used in 2002 (a DeHavilland DHC-2 

Beaver) to accommodate a new method of 

mapping seal distribution. The plane was 

flown at 90-95 knots at an altitude of 305 m 

(1,000 ft) along a standard grid of 14 

transects separated by 400 m (as in 2002; 

Fig. 11). Adjacent areas outside the study 

area (i.e., in northern Yakutat Bay and 

Russell Fjord) were again opportunistically 

surveyed for seals when they contained 

significant amounts of ice. 

During the aerial surveys, digital 

photos (3008 x 1960 pixel JPEGs) were 

taken of the area directly under the airplane 

using a vertically-aimed digital camera 

(Nikon D1x, Nikon Inc., Melville, NY) 

mounted to a platform in the airplane’s 

camera porthole. Using a 60 mm (90 mm 

digital equivalent) focal length lens at 1,000 

ft, each picture captured an area of 78 x 120 

m. This configuration provided high 

resolution photos for relatively easy seal 

identification and length measurement (Fig. 

24). 

Figure 24. An example of an aerial photograph with seal groups present. The pink crosshairs are 

used to standardize the method for estimating ice cover suitable for hauling out (see Methods) 

71
Appendix 2. Data Collection on Harbor Seals in 2004 

The camera was manually started and 

stopped at the beginning and end of each 

transect; during the transects the camera was 

programmed to take a picture every 2 

seconds using a laptop computer with 

camera-control software (Nikon Capture 4, 

Nikon Inc., Melville, NY). This resulted in 

ca. 80% photo coverage along the transects, 

with an approx. 15-20 m gap between 

photos. Non-overlapping photographs allow 

for greater efficiency in the analysis because 

there is no chance of counting the same seal 

twice in sequential photographs on the same 

transect, and a very low chance on adjacent 

transects. The camera was also manually 

stopped whenever the airplane flew over an 

area with no ice. Image files were streamed 

to the laptop’s hard drive using a FireWire® 

cable connection. The camera was also 

connected to a portable GPS unit (Garmin 

76S, Garmin International Inc., Olathe, KS) 

that embedded the airplane’s position within 

each JPEG file. This later allowed us to 

georeference the survey photos in a GIS 

(ArcGIS, ESRI, Inc., Redland, CA). As in 

2002, a digital video camera (Sony TRV900, Sony Electronics Inc., San Diego, CA) 

was mounted vertically in the porthole and 

used as a back up to the digital camera 

system. It was set to record a 70 m wide 

strip below the airplane and recording was 

switched on and off at the same times as the 

digital camera. 

Aerial surveys were also conducted 

in Icy Bay from 9 May to 16 June 2004 

using the same survey equipment and 

methods as in Disenchantment Bay, except 

that surveys were flown weekly (Fig. 23). 

The Icy Bay survey grid also contained 14 

transects that were aligned lengthwise with 

the main ice field flowing from the Guyot 

Glacier (Fig. 25). 

Figure 25. Map of the Icy Bay study area showing the aerial transect grid for the medium scale 

photogrammetric surveys. 

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Appendix 2. Data Collection on Harbor Seals in 2004 

Since Icy Bay does not receive visits from 

cruise ships, it was used as a “control” site 

from which to compare results from 

Disenchantment Bay. 

Once archived, the survey 

photographs were georeferenced using GIS 

software (ArcGIS 9, ESRI Inc., Redlands, 

CA)(i.e., overlaid on GIS covers of coastline 

in the actual location, orientation, and scale 

at which they were taken). The number and 

location of each seal group sampled was 

then recorded, along with the number of 

seals per group, the number of mother-pup 

pairs per group, and the longest axis of the 

iceberg each group is hauled out on. 

Mother-pup pairs were defined as two seals 

that were within an adult body-length of 

each other with the smaller seal being less 

than two-thirds the total length of the larger 

seal. This method will be refined as we 

explore the possibility of assessing 

population structure using body length. 

Finally, two different measures of ice cover 

were estimated in all photographs with seals 

and every 400 m along the transects when 

seals were not present, and for the first and 

last photographs of each transect. First, the 

area of ice cover (≥ 2 m longest axis) was 

estimated visually to the nearest tenth. 

Secondly, a more standardized ice cover was 

estimated by overlaying a 4 X 5 grid and 

counting the number of intersections (of 20 

total) at which ice greater than or equal to 2 

m overlaps (quadrat sampling; Fig. 24). In 

total, 23 aerial surveys were conducted in 

Disenchantment Bay and seven were 

conducted in Icy Bay. On average, 1,818 

photos were taken during Icy Bay surveys 

and 1,300 photos were taken during 

Disenchantment Bay surveys. The analysis 

of these photos is currently underway. 

A2.3 Large-Scale Study 

Large-format (9 x 9 in) aerial 

photogrammetric surveys were conducted in 

Disenchantment and Icy Bays on 9, 10, and 

23 August 2004 by AeroMap, Inc. 

(Anchorage, AK). 

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Appendix 3. Harbor Seal Behavioral Observation Guidelines

Appendix 3. Harbor Seal Behavioral Observation Guidelines 

(Instructions to observers on cruise ships for collecting behavioral data) 

1. Selecting an observation post: Each observer should perform their observations in one of the 

four quarters of the ship (i.e., some combination of port, starboard, bow, stern). For example, if 

you select the port bow post, observe seals from the time that you can first view them well until 

they pass abeam of the ship. If you select the starboard stern, you would begin your observations 

as the seals come aft of the ship’s beam, continuing your observations until you can no longer 

see the seals well. 

2. Selecting seal groups: At the beginning of the in-ice observation period, select a group of 

seals hauled out on ice. A “group” can be one or more seals on a single ice floe. Assign that 

group an ID number, from 1 through whatever number of groups you, as an individual, observe 

that day on that ship. Remember to include both small and large groups in your sample. Also 

include groups that are both close and far from the ship’s track. Number groups sequentially per 

ship visit (event), starting with 1. Use an observation position prefix for port bow (PB) port stern 

(PS), starboard bow (SB), and starboard stern (SS). Example: PB-1, PB-2, PB-3, etc. 

3. Mothers and pups: Whenever possible, select seal groups for observation that include 

mothers and pups. Don’t assume that all small seals are pups; yearlings can be nearly the same 

size as pups. Pups can be identified by their bright, shiny, fresh pelage (yearlings have duller 

pelage, which they will be molting in the coming weeks) and by close physical proximity to 

adult females. 

4. Observation sampling: This study’s experimental design calls for continuous monitoring, 

with independent observations of a seal group (or individual) being allotted into 15 seconds 

intervals, separated only by the amount of time necessary to record the data. Use a countdown 

timer to start and end the 15 second observation period. When the group passes out of your 

observation area (ship’s quarter), select another group when it becomes available. 

5. Recording observations: For each 15 second observation period, record the group ID 

number, the start time of the observation, and the group size (note that this may have changed 

since the last observation if seals entered the water). Record the number of seals that showed 

each level of excitement during the period. Score only the “highest” level of excitement for each 

seal during that period (head up is the least excited, entering the water is the most excited). For 

example, a seal that was resting at the beginning of a 15 second period, but then raised its head, 

moved across the ice, and then entered the water during that 15 seconds would be scored as 

“enter water.” Record counts for mothers, pups, and other seals separately. 

6. Distance and bearing: Estimate distance using the range-finding binoculars or inclinometer 

(record degrees of inclination for the latter). Also record the approximate relative bearing to the 

ship’s course in 15° increments. For example, straight off the bow would be 0° or 360°, the port 

beam is 270°, aft is 180°, the “2 o’clock” position is 60°, and the “7:30" position is 225°. 

7. Other covariates: For each seal group observed, enter estimates of ice coverage (in 10ths 

within a 50 m radius of group) and ice floe size (longest axis). Note weather conditions at the 

beginning of observations and then as significant changes occur. Note the incidence of other 

potential sources of disturbance (e.g., ships, boats) at the time they are first observed. 

75