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Keywords:

  • Alaska;
  • foraging behaviour;
  • geographic information system;
  • oceanography;
  • otariid;
  • pinniped;
  • remote sensing;
  • satellite telemetry;
  • satellite tracking

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Current flow and bathymetry in the Aleutian Islands define unique habitats that influence prey distribution and foraging behaviour of top-level predators. We explored whether oceanographic features and bathymetry influenced the diving activity of 30 immature sea lions (ages 5–21 months) equipped with satellite-linked depth recorders in the eastern Aleutian Islands (EAI) during 2000–02. Sea surface temperature (SST) and chlorophyll a concentrations were obtained from remote sensing satellite imagery and associated with locations where sea lion diving was recorded. Most locations associated with diving to >4 m were within 10 nautical miles (nm) of shore and associated with onshelf waters <100 m deep. Use of offshore and deeper waters in the Bering Sea increased during May, as did trip durations. General movements at that time were generally northwesterly from the North Pacific Ocean to the Bering Sea. Diving activity varied coincidently with increases in SST and chlorophyll a concentrations, but also with sea lion age. Associations with habitat features did not consistently explain variability in dive count, time at depth, dive focus or focal depth. Nearshore diving tended to be influenced by distance from shore or seafloor depth, whereas increased SST coincided with activity of sea lions diving >30 nm offshore. Immature sea lions developing into independent foragers in the relatively shallow pass areas of the EAI do so at a time of rapid changes in oceanography and prey availability.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

The ocean surrounding the Aleutian Island archipelago is spatially and temporally dynamic with distinct habitats characterized by current flow and bathymetry (Stabeno and Reed, 1994; Stabeno et al., 1999, 2002; Ladd et al., 2005a). The Alaska Coastal Current (ACC), characterized by relatively warm, fresh waters and low-nutrient levels, dominates the eastern passes, whereas the cooler, saltier waters of the Alaska Stream carry higher nutrient concentrations to deeper passes west of Samalga Pass (Fig. 1; Ladd et al., 2005a). Productivity of the relatively shallow eastern passes (e.g. Unimak Pass) is limited by complete mixing within the water column, but nutrient mixing through the deeper passes contributes to seasonally increased productivity northward in the Bering Sea (Ladd et al., 2005a). Distributions of many pelagic and demersal fish species along the Aleutian Island chain are subsequently influenced by these features, with less species richness west of Samalga Pass but also pockets of higher biomass within several passes (Sinclair and Stabeno, 2002; Logerwell et al., 2005). Distributions and foraging behavior of top-level predators are likewise affected (Springer et al., 1996; Hunt et al., 1998; Ladd et al., 2005b). Steller sea lion (SSL) population trends (York et al., 1996; Loughlin and York, 2000), diet (Merrick et al., 1997; Sinclair and Zeppelin, 2002), and ecologic associations of rookeries and haul-outs (Call and Loughlin, 2005) also vary along the Aleutian Island chain. In this diverse region, oceanographic variability may influence SSL foraging behavior, and consequently the growth and survival of naive sea lions as they develop foraging skills during the transition from maternal dependence.

image

Figure 1. General map showing Aleutian Islands study area of 162°W longitude, identifying capture locations (underscored), island landmarks, and ocean currents (ACC, Alaska Coastal Current), and regions referred to in the text (CAI, central Aleutian Islands; EAI, eastern Aleutian Islands; WGOA, western Gulf of Alaska; CGOA, central Gulf of Alaska). Bathymetric contours indicate 100 (light dashed) and 500 m (dark). Most tagging in the EAI occurred within the Krenitzen Island group, forming the western boundary of Unimak Pass.

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Steller sea lions give birth from late May through to July (Merrick et al., 1995; Pitcher et al., 2001). Precise weaning dates have not been determined, but weaning is thought to occur when pups reach about 10–12 months of age (Pitcher and Calkins, 1981; Porter, 1997), although suckling may occur in juveniles up to 3 yr old (Pitcher and Calkins, 1981). By 10–12 months of age, juvenile sea lions dive on average to 17 m, but maximum dive depths range between 63 and 288 m (Loughlin et al., 2003). Diving ability develops throughout the first year of life because of ontogenetic changes in diving ability, weaning, learned behavior, or in response to seasonal environmental fluctuations (Merrick and Loughlin, 1997; Loughlin et al., 2003; Richmond, 2004). Previous analyses of SSL dive and travel behaviour have not specifically examined links between diving activity and detailed habitat characteristics, and the relationship between diving behaviour and oceanographic and bathymetric features has not been quantified. All studies of otariids published to date reporting significant relationships between dive behaviour and habitat have been conducted on lactating southern hemisphere fur seals during pup rearing (McCafferty et al., 1998; Georges et al., 2000; Guinet et al., 2001; Lea and Dubroca, 2003) or adult northern fur seals during winter migration (Ream et al., 2005). In this context, a critical gap exists in our knowledge of how environmental variability may affect naive pinniped foragers as they transition to nutritional independence.

Steller sea lion populations in parts of Alaska declined by 80% since 1959 (Loughlin et al., 1992), prompting a threatened listing in 1991 under the US Endangered Species Act for the species as a whole and an endangered listing in 1997 for the genetically distinct stock west of 144°W longitude (Bickham et al., 1996; Loughlin, 1997). The western stock declined at about 4% per year during 1991–2002, although since 2000 the decline may have abated in the central (CAI) and eastern Aleutian Islands (EAI; Sease and Gudmundson, 2002). Models suggesting decreased survival of ages 1–4 yr during the early 1980s (York, 1994; York and Holmes, 2003) generated hypotheses for the decline that include chronic nutritional stress of juveniles because of inadequate prey availability or quality that could arise from indirect commercial fishery effects, environmental change (Loughlin and Merrick, 1989; Alverson, 1992) or both factors. Because of their endangered status and concern over prey availability, management measures were enacted to reduce spatial overlap of fisheries with presumed foraging areas of SSL. This analysis explores the relationship between immature SSL diving activity and habitat features in the Aleutian Islands to better characterize potential foraging habitats.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Captures and instrument deployment

Thirty immature sea lions were captured at or near haul-out sites in the northern Gulf of Alaska and Aleutian Islands during 2000–02 (Table 1; Fig. 1) using land or scuba capture techniques (McAllister et al., 2001; Loughlin et al., 2003). Captures occurred during February or March of each year and during November of 2001. Dive data from sea lions captured in 2000 were included in diving analyses conducted by Loughlin et al. (2003).

Table 1.  Capture and deployment data for 30 immature Steller sea lions transmitting from the Aleutian Island archipelago west of 162°W longitude during 2000–02.
IDSexMass (kg)Age coverage (months)Capture location Region*Capture dateDate of last transmissionDeployment period (days)
  1. *CAI, central Aleutian Islands; EAI, eastern Aleutian Islands; CGOA, central Gulf of Alaska.

  2. Sea lions included in stepwise multiple regression model.

6295F87.09–11SeguamCAIFebruary 29, 2000April 29, 200060
6296F85.89–11SeguamCAIFebruary 29, 2000April 21, 200052
6297F76.29–11SeguamCAIFebruary 29, 2000April 23, 200054
6298M109.09–12SeguamCAIFebruary 29, 2000June 11, 2000103
6299F100.29–10AiktakEAIMarch 9, 2000April 7, 200029
6300M79.69–12AiktakEAIMarch 9, 2000June 14, 200098
6303M132.021–23AkutanEAIFebruary 26, 2001May 7, 200170
6304F101.29–11AiktakEAIMarch 1, 2001April 28, 200158
6305F105.89–12UgamakEAIMarch 1, 2001June 1, 200192
6306F102.821–22TigaldaEAIMarch 3, 2001April 24, 200152
6307M86.69–10TigaldaEAIMarch 3, 2001April 6, 200134
6308F87.09–13AiktakEAIMarch 3, 2001July 29, 2001148
6309F107.09–11AiktakEAIMarch 3, 2001May 19, 200177
6310F99.49–12AiktakEAIMarch 3, 2001July 1, 2001120
6311F152.021–23AkunEAIMarch 4, 2001May 6, 200163
6312F116.09–11AkunEAIMarch 4, 2001April 30, 200157
6466F85.85–6UgamakEAINovember 13, 2001January 4, 200252
8238F83.85–7UgamakEAINovember 13, 2001January 24, 200272
8239F107.617–23AiktakEAINovember 14, 2001May 14, 2002181
6475M124.09–12AiktakEAIMarch 12, 2002July 7, 2002117
7469M94.69–12Long Is.CGOAMarch 2, 2002June 16, 2002106
7481F102.09–10BasaltEAIMarch 10, 2002April 15, 200236
7482F71.89–11AiktakEAIMarch 11, 2002May 10, 200260
7483M81.89–12AiktakEAIMarch 11, 2002July 4, 2002115
7484M114.69–11AiktakEAIMarch 11, 2002June 4, 200285
7485M122.89–13AiktakEAIMarch 11, 2002August 5, 2002147
7486M127.89–11AiktakEAIMarch 11, 2002May 3, 200253
7487F85.69–12AiktakEAIMarch 11, 2002June 14, 200295
7488M135.09–11AiktakEAIMarch 12, 2002May 31, 200280
7489F118.69–10AiktakEAIMarch 12, 2002May 7, 200256

Animals captured on land were physically restrained or given an intramuscular injection of diazepam (approximately 1.5 mg kg−1). All sea lions captured at sea were anaesthetized with inhalable isoflurane delivered with oxygen via a facemask or endotracheal tube from a field portable anaesthesia machine (Heath et al., 1996). Once a sea lion was restrained, morphometric measurements were taken and instruments attached. Mass was measured to ±0.1 kg with an electronic load cell, and dorsal standard length was measured to ±1 cm. Instruments were attached to the dorsal pelage near the shoulders using quick-setting epoxy. Age was estimated assuming a mid-June birth date (Pitcher et al., 2001) and was based on capture date, tooth eruption, and sea lion size (Calkins and Pitcher, 1982). However, because of the size overlap between 9 and 21 month olds during March, some may have been misclassified. Sea lions were monitored while recovering from the effect of anesthesia whether on land or on a research vessel, then allowed to voluntarily return to the water.

Dive activity and location

We used two types of 0.25-W satellite dive recorders (SDRs) packaged by Wildlife Computers, Redmond, WA (ST10 in 2000, SDR-T16 in 2001 and 2002) and programmed to record and transmit data as described in Loughlin et al. (2003). Briefly, both models transmitted data on transmitter status (wet or dry), maximum dive depth, and time at depth (TAD) summarized within four 6-h periods (21.00–02.59; 03.00–08.59; 09.00–14.59; and 15.00–20.59 hours). Depths were sampled every 10 s with a resolution of 2 m, and the maximum depth reached for each dive was recorded into one of 14 data bins: ≤4, >4–6, >6–10, >10–20, >20–34, >34–50, >50–74, >74–100, >100–124, >124–150, >150–174, >174–200, >200–250, and >250 m. Thus, dives were recorded once the sea lion was >4 m below the surface. TAD recorded the proportion of time spent diving in a depth bin for the time at sea during a 6-h period. We calculated TAD as the total proportion of time spent diving within a 6-h period to >4 m (e.g. if a sea lion spent half of a 6-h period at sea, and spent half its dive time at ≤4 m, one quarter at >4–6 m and one quarter at >6–10 m, the TAD would be 25%).

Diving activity was described directly by the number of dives to each depth bin (dive count) and the TAD from SDR bin data, and by indices derived from bin data: dive rate (number of dives per time spent at sea within a 6-h period), mean dive depth (Merrick and Loughlin, 1997; Loughlin et al., 2003), dive focus (DF), and focal depth bin (Frost et al., 2001). To calculate DF and focal depth, histogram dive count data were condensed into six bins of 4–10, >10–20, >20–34, >34–50, >50–100, and >100–174 m. Dive focus is based on Simpson's Diversity Index and reflects diving variability by quantifying dive dispersion among the six bins (Frost et al., 2001; Hastings et al., 2004). Diving occurred to mainly one bin if DF > 0.5, and equally among all bins if DF = 0.167 (Frost et al., 2001). Focal depth indicates the dominant depth bin (DF > 0.5) to which dives were made.

Sea lion locations were calculated by Service-Argos, Inc. (Largos, MD, USA) from satellite-derived position fixes based on the Doppler shift of uplinks between the SDR and polar orbiting satellites (Fancy et al., 1988). A hierarchical location class (LC) reflecting position accuracy for each fix was assigned by Service-Argos, with LC3 being the most accurate. By comparing satellite fixes to GPS ship locations during predeployment trials, we estimated mean (±SD) accuracies of 0.4 km (±0.3) for LC3, 0.7 km (±0.6) for LC2, 1.5 km (±1.5) for LC1, 4.9 km (±5.3) for LC0, 2.9 km (±5.2) for LCA, and 17.4 km (±26.2) for LCB. Because locations are not sent by the transmitter, locations calculated by Service-Argos may not coincide exactly with dive data, and not all dive data types may be received during a 6-h sampling interval. Thus, additional processing was required to match dive histogram data with location data. Locations were iteratively sorted based on maximum swim speed and the Keating Index, a geometric measure of location accuracy (Keating, 1994). If swim speeds between two successive locations exceeded 3 m s−1 (Merrick and Loughlin, 1997; Loughlin et al., 2003), the poorer quality (based on LC) location was removed. If location qualities were equivalent, the location with the lower Keating Index was retained. LCA and LC0 locations were considered equivalent when filtering based on location quality, and ranked higher than LCB. Locations received from land that had no associated dive data were eliminated, and dive data for which no location could be assigned were likewise removed. Locations received during dry periods (based on surface-timeline data) were summarized as a single location based on the highest quality location during a dry period. Gross outliers were removed during the last stage of the filtering process by rejecting locations with a Keating Index >20 km. One location was then selected from each 6-h binned dive data-sampling period based on LC. This final filtering stage provided representative temporal coverage across sampling periods (i.e. bias associated with obtaining more locations during optimal uplink periods was diminished), and reduced autocorrelation among locations used to quantify sea lion diving behavior with respect to location. However, if sea lions were more likely to be at the surface near haul-outs than offshore (with a higher probability of obtaining a better LC), locations assigned to diving activity may have been slightly biased shoreward. For analyses associating dive activity with spatially specific environmental variables [bathymetry, sea surface temperature (SST) and chlorophyll concentration], only dive data linked to at-sea locations (transmissions received while SDR was wet) were used.

Habitat data

Habitat was characterized using bathymetric and oceanographic features. Bathymetry was calculated from National Imaging and Mapping Agency (NIMA) digital data of all soundings found on National Oceanic and Atmospheric Administration (NOAA) nautical charts in the area. Each sea lion location was spatially matched to the closest sounding and assigned that bathymetry value. Distances to nearest soundings were relatively short (88% of locations were <1 km from a sounding, 95% were <5.5 km from a sounding), except around Amlia Island where there were almost no soundings from a depth of 80 m to the shoreline. The minimum distance from each location to the nearest shoreline (not instrument deployment site or point of departure for a trip) was calculated in arcmapTM 8.2 (ESRI, CA, USA). Locations were classified as being on either the Bering Sea or North Pacific Ocean side of the Aleutian Island chain. The SST (daytime 11-μm sensor) and chlorophyll a (SeaWiFS analog) data were obtained from the Moderate Resolution Imaging Spectrophotometer (MODIS) carried aboard the Terra satellite. Monthly averages of 4.89 km2 grids (MODIS Level 3 mapped product) were obtained corresponding to periods of telemetry coverage during 2000–02 for 161–177°W longitude and 51–57°N latitude. Although some ability to detect frontal structures was lost, monthly resolution was chosen because it maximized the resultant number of data cells, which were limited on shorter time scales because of cloud cover. MODIS data were filtered for the best data quality (class 0) based on accompanying data quality files. Data in 2000 and after March 2002 were classified as provisional (partially validated), and data for 2001 through March 2002 were validated.

All data were combined in an arcgis® geographic information system (ESRI, CA, USA) software. Each location with accompanying dive data was linked with data on SST, chlorophyll a concentration, seafloor depth, and distance to shore through the arcgis spatial analyst module. Associations between habitat variables and locations of sea lion diving activity were examined using Statistical Package for Social Sciences (spss, version 11) software. Mean monthly sea lion movement bearings and distances were determined from average monthly locations for individual sea lions using at-sea locations only, and following statistical techniques for circular data (Zar, 1984).

Of the 30 instrumented animals, effects of habitat type on dive activity were explored in more detail for sea lions that provided continuous telemetry data during March–June in any of the 3-yr study. Of the nine meeting that criterion, one was excluded because of a lack of SST data associated with calculated locations. All eight sea lions were estimated to be 9–12 months old during this period (Table 1). Dive count, TAD, DF, and focal depth distributions were normalized by applying a square-root transformation, then standardized by subtracting the mean from each value and dividing by the standard deviation (normal deviate Z-score; Zar, 1984). Normal deviates were input as dependent variables in a stepwise multiple regression model with time period, month, distance to shore, seafloor depth, region (Bering Sea or North Pacific Ocean), and SST as independent variables. Variables were included in the model if significance of F < 0.05, and rejected if F > 0.1. The model was run independently for each sea lion to explore individual behavioural differences.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Captured sea lions (11 males, 19 females; Table 1) weighed 72–152 kg. Duration of data collection was between 29 and 181 days (Table 1), with a median duration of 71 days. Most sea lions (25 of 30) were captured in the EAI, although one sea lion captured near Kodiak Island entered the area during the study period. The common period of data coverage among years was between March and June (Table 2).

Table 2.  Monthly coverage (number of sea lions transmitting during at least half of month) of 30 immature Steller sea lions within the Aleutian Islands during 2000–02.
YearJanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember
2000  6422      
2001  109421   33
2002211212751     
Total212825159200033

Removing duplicate dry locations reduced an initial sample size from 13 796 to 7582 locations. When filters for swim speed and location quality were applied and duplicate at-sea locations removed, 3263 locations remained associated with dive data. When locations not exhibiting evidence of diving to >4 m were removed, the sample size was 2626 locations, or about 19% of the initial Argos position fixes. This contained 143 149 dives and 1991.5 h of diving to >4 m. Selecting locations when the SDR was wet (removing dive data transmitted from a haul-out location) reduced the available sample to 1151 with either dive count or TAD data, and 820 locations with both dive data types during 763 trips. Of these locations, 38 (3.3%) were obtained from two sea lions 5 months old at capture, 1013 (88.0%) from 24 sea lions 8–9 months old at capture, and 100 (8.8%) from four sea lions 17–21 months old at capture. These data were utilized for comparisons of dive location and activity with bathymetric and oceanographic features.

Diving locations and trip durations

Habitat use indexed by proportion of locations associated with diving to >4 m (Table 3) varied significantly with distance to shore [ANOVA on angular-transformed data, F(2,229) = 702.2, P < 0.001] and bathymetry [F(3,151) = 52.2, P < 0.001]. There was a significant interaction effect between season and distance to shore (F(4,229) = 0.148, P < 0.001) but not between season and bathymetry [F(6,151) = 0.865, P = 0.522]. Most locations associated with diving to >4 m were within a 5–10 nautical mile (nm; 1 km = 0.540 nm) straight-line distance of shore and in waters <100 m deep (Table 3). All locations were within 15 nm of shore during November–January, but only three sea lions were tracked during that period. During May–July, the proportion of locations within 5 nm decreased (to about 85%), and 13% were >10 nm from shore (Table 3). Summary proportions were likely slightly biased nearshore because the filter selected higher quality locations when making a choice between a set of mixed LCs. Poor quality LCA and LCB locations comprised 27.3% of locations <5 nm, but 61.5% of locations between 5 and 10 nm.

Table 3.  Percentages of locations (associated with diving to >4 m) stratified by distance to shore and seafloor depth in the eastern and central Aleutian Islands combined.
SeasonSeafloor depth (m)Distance to shore (nm)Pooled
<55–10>10
  1. Values are mean (±1 SE) of individually stratified proportions for three sea lions during November–January, 26 during February–April, and nine during May–July.

November–January<5063.4 (1.6)0.9 (0.9)0.0 (0.0)64.3 (1.3)
50–10032.3 (3.6)1.7 (1.7)0.9 (0.9)34.9 (1.5)
100–1500.9 (0.9)0.0 (0.0)0.0 (0.0)0.9 (0.9)
>1500.0 (0.0)0.0 (0.0)0.0 (0.0)0.0 (0.0)
Pooled96.6 (3.4)2.6 (2.6)0.9 (0.9) 
February–April<5068.7 (5.2)0.7 (0.4)0.0 (0.0)69.5 (5.3)
50–10021.2 (3.7)2.7 (1.0)0.3 (0.2)24.3 (3.8)
100–1504.8 (3.6)1.0 (0.5)0.0 (0.0)5.8 (3.6)
>1500.1 (0.1)0.3 (0.3)0.0 (0.0)0.4 (0.3)
Pooled94.9 (1.5)4.8 (1.4)0.3 (0.2) 
May–July<5063.3 (8.6)0.2 (0.2)0.0 (0.0)63.5 (8.6)
50–10020.5 (6.5)1.5 (0.6)1.2 (1.2)23.2 (6.0)
100–1500.5 (0.3)0.7 (0.5)1.0 (1.0)2.1 (1.4)
>1500.2 (0.2)0.2 (0.2)10.8 (8.2)11.2 (8.2)
Pooled84.5 (8.4)2.6 (1.0)12.9 (8.3) 
All seasons 92.5 (2.3)4.1 (1.0)0.8 (0.5) 
<50   67.7 (4.1)
50–100   24.8 (3.0)
100–150   4.6 (2.5)
>150   2.9 (2.0)

Locations >30 nm offshore were located in the Bering Sea and included waters >200 m off the continental shelf (Fig. 2), whereas the most distant offshore locations into the North Pacific Ocean were <30 nm offshore and associated with shelf waters <200 m deep south of Unimak Island and Unimak Pass (Fig. 2). The longest duration trips and greatest distances offshore during the May–July period (Fig. 2) occurred during May. Mean maximum trip distances to shore of locations associated with diving to >4 m varied by trimester [ANOVA on log-transformed distances, F(2,760) = 16.478, P < 0.0001], and were significantly smaller during February–April (0.3 nm, 95% CI: 0.3–0.4 nm, n = 478) than during May–July (0.7 nm, 95% CI: 0.5–0.8 nm, n = 231; Bonferroni P < 0.05), but did not differ from November to January (0.6 nm, 95% CI: 0.4–0.9 nm, n = 54). Of the 30 instruments deployed, 17 were operational during May when most offshore (>20 nm) diving locations were recorded (Fig. 2). Of those active in May, about 23% (CI: 5–67% assuming a binomial distribution) of the instrumented sea lions indicated offshore diving behavior (one of two in 2000, one of four in 2001, and one of eight in 2002). Mean trip durations also varied by trimester [ANOVA on log-transformed durations, F(2,760) = 17.348, P < 0.0001]. Mean trip duration during February–April (0.37 day, 95% CI: 0.35–0.39 day, n = 478) was significantly shorter than during May–July (0.52 day, 95% CI: 0.47–0.58 day, n = 231; Bonferroni P < 0.05), but did not differ with durations during November–January (0.42 day, 95% CI: 0.34–0.52 day, n = 54).

image

Figure 2. Filtered locations (dots) of diving to >4 m by 30 immature Steller sea lions west of 162°W longitude during 2000–02 (n = 1151 locations), grouped by seasons (November–January, February–April, and May–July). Isobaths are 100 (light) and 500 m (dark). Dive locations in November–January are represented by the following animals: 6466, 8238, and 8239; in February–April by: 6295–6300, 6303, 6304–6312, 8239, 6475, 7469, and 7481–7489; and in May–July by: 6298, 6300, 6303, 6305, 6309, 6310, 6311, 8239, 6475, 7469, 7482, 7483, 7484, 7485, 7486, 7487, 7488, and 7489.

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General movements among areas indicated by the compass direction between mean monthly locations for sea lions east of Samalga Pass (calculated as the mean monthly latitude and longitude for an individual) did not indicate a significant orientation during February–April (Table 4). However, movements were significantly oriented toward a bearing of 293° during May–June (Table 4). Direction bearings of February–April and April–May travel for sea lions relocating >10 nm between months tended to orient N-NE (although not statistically significant, P = 0.100). May–June movements was associated with travel toward Unimak Pass, or from Unimak Pass area north and west through the Krenitzen Islands. This directed movement was shown by sea lions regardless of their initial location, and was coincidental with seasonally changing environmental conditions. Distances between monthly mean locations varied by month. May–June displacements were significantly greater than February–March distances (Table 4).

Table 4.  Bearing and distance of general movements between monthly mean locations for immature Steller sea lions tracked in the eastern Aleutian Islands during 2000–02*.
 Bearing (°; ±CI)rP-valueDistance (nm)n
  1. Length of mean vector (r) and Rayleigh test for significance calculated following Zar (1984). CI for non-significant bearings is ±90%.

  2. *Sea lion #7469 was excluded because it had previously undertaken a westward movement from near Kodiak Island to Unimak Pass in May and stayed near that area in June.

  3. CI approximated using methods of Zar (1984).

  4. Significant difference among months (ANOVA, P = 0.036) owing to the February/March and June/July contrast (Bonferroni P < 0.05).

All distances
 February/March470.198ns8.4 (3.5)24
 April3280.115ns10.0 (3.0)21
 May293 (33)0.6170.00213.1 (4.6)15
 June/July2190.393ns27.4 (9.4)12
Distances >10 nm
 February/March190.567ns 3
 April230.425ns 6
 May273 (20)0.969<0.005 5
 June/July2240.504ns 7

Effects of age on diving activity

Most dives (as a proportion of total dives) were made to depths <20 m, although some were to as deep as 100–124 m (Fig. 3). Diving activity, as indexed by dive rate, TAD, mean depth of dives, and DF changed with sea lion age (Fig. 4). Dive rate and TAD both increased throughout the first 12 months of age, while mean dive depths became deeper up to 18 months of age (Fig. 4). Dive rate and TAD declined after 17 months of age. Dive focus varied inversely with TAD, and as TAD increased through the first 14 months, dives became spread over more depth bins (indicated by focus values of <0.5, Fig. 4). When translated to time of year, age differences in diving activity become particularly evident during winter months of November–January (corresponding to ages 5–7 and 17–19 months), when juveniles dived more frequently, deeper, and spent more TAD than did pups.

image

Figure 3. Mean (±SD) proportion of dives to >4 m by depth bin for 30 immature Steller sea lions west of 162°W longitude during 2000–02. Dive count data (n = 143 139) from both wet and dry satellite telemeter transmissions are included.

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image

Figure 4. Relationships between mean (±SE) dive rate, time at depth (TAD), mean dive depth, and dive focus by estimated age for 30 Steller sea lions diving to >4 m west of 162°W longitude during 2000–02. Sample sizes vary from n = 5 dives for 7 month olds to n = 331 dives for 8 and 9 month olds. Results are based on dives performed by the number of sea lions within each age category as shown in Table 2.

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Diving activity and oceanography

Monthly averages of SST associated with diving locations indicated substantial changes in regional thermal structure in the study area (Fig. 5). Sea surface temperatures associated with diving locations cooled during November–March, then warmed progressively each month during March–June [ANOVA, F(8,716) = 172.8, P < 0.0001]. By May, increased chlorophyll a concentrations were evident over the study area (Fig. 5), with significant differences in concentrations among December, March (0.49 ± 0.02 mg m−3, n = 19) through April (0.55 ± 0.03 mg m−3, n = 29), and May (2.20 ± 0.24 mg m−3, n = 58) through June (1.51 ± 0.39 mg m−3, n = 16; P < 0.05, Tamhane multiple comparison test for unequal variances).

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Figure 5. Mean (±SE) sea surface temperatures (SST, top; n = 29 sea lions) and chlorophyll a concentrations (bottom; n = 18 sea lions) associated with locations of diving to >4 m by juvenile Steller sea lions in the Aleutian Islands during 2000–02. SSTs and chlorophyll a concentrations were estimated from satellite imagery data.

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Diving activity did not vary with chlorophyll a concentration (ANOVA for dive rate, median depth, and DF all P > 0.10), likely due to limited sample sizes in 2.0–4.0 (n = 7) and >4.0 mg m−3 (n = 10) categories. Dive activity did vary with SST [ANOVA, dive rate F(5,613) = 2.61, P = 0.024; median depth F(5,716) = 2.277, P < 0.045; DF F(5,831) = 2.275, P < 0.0001; Fig. 6]. As temperatures increased, dive rate and median depth of dive increased, and maximum depths were more dispersed through the water column (as indicated by decreased DF; Fig. 6).

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Figure 6. Mean (±SE) dive activity indices (dive rate, median dive depth, dive focus, and focal depth bin) associated with sea surface temperature (SST; n = 27 sea lions) associated with locations of diving to >4 m by juvenile Steller sea lions ≥8 months old in the Aleutian Islands during 2000–02. SSTs and chlorophyll a concentrations were estimated from satellite imagery data.

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Association of habitat variables and diving activity

Up to three variables accounted for 6–89% of variability in dive activity (Tables 5 and 6), although no variable was common as an explanatory factor in all sea lions. Only two sea lions (6308 and 7485) had variability accounted for in all four dive activity indices by the environmental variables considered (Tables 5 and 6). Dive count and TAD were greatest during two periods, 21.00–02.59 and 15.00–20.59 hours (ANOVA, Bonferroni P < 0.05), and focal depths tended to be deeper in daylight hours. Dive focus was relatively unaffected by time of day. Time of day was a common influence for dive count and TAD, and somewhat less for focal depth and DF. Month in which diving occurred was a significant positive factor for two sea lions, but had a negative influence on TAD for one animal. Sea lions diving on the North Pacific Ocean side of the Aleutian Islands tended to make fewer dives than when on the Bering Sea side, although there was an effect on TAD for only one individual (as indicated by the ‘region’ factor, Table 5). Seafloor depth influenced TAD in three of seven sea lions, the number of dives for one sea lion, but was not of a consistent sign of effect. Sea surface temperature also influenced proportion of time spent at depth for two sea lions, but did not appear to affect the number of dives performed.

Table 5.  Results of stepwise multiple regression between number of dives or TAD to >4 m (as Z-score of square-root transformed number) with temporal and environmental variables for eight immature Steller sea lions during March–June of 2000 (n = 2), 2001 (n = 2), and 2002 (n = 4).
Animal IDSignificant factorsnR2P-value
  1. Significant independent factors, sign of the relationship, sample size, and adjusted R2 and significance of model are presented by individual sea lion.

  2. SST, sea surface temperature; TAD, time at depth.

Dive count
 6298Period (−), region (−)170.4560.006
 6300 35ns
 6308Period (−), region (−)570.337<0.001
 6310Seafloor depth (+)590.0570.039
 6475Month (+), shore distance (−)260.498<0.001
 7483Period (−), region (−)950.1310.001
 7485Period (−)160.639<0.001
 7487 17ns
TAD
 6298Period (−), month (+)220.3440.007
 6300 37ns
 6308Period (−), SST (+)570.250<0.001
 6310Region (+), seafloor depth (+)600.1650.002
 6475Month (+), shore distance (−)260.480<0.001
 7483Month (−), SST (+)920.1320.001
 7485Period (−), seafloor depth (−)190.889<0.001
 7487Seafloor depth (+)150.2180.045
Table 6.  Results of stepwise multiple regression between dive focus or focal depth bin (as normal deviates) and temporal and environmental variables for eight immature Steller sea lions during March–June of 2000 (n = 2), 2001 (n = 2), and 2002 (n = 4).
Animal IDSignificant factorsnR2P-value
  1. Significant independent factors, sign of the relationship, sample size, and adjusted R2 and significance of model are presented by individual sea lion.

  2. SST, sea surface temperature.

Dive focus
 6298 25ns
 6300SST (−), shore distance (−)400.471<0.001
 6308Shore distance (−)700.167<0.001
 6310 68ns
 6475 30ns
 7483Month (+), SST (−), shore distance (−)1040.244<0.001
 7485Period (+)190.2030.030
 7487 18 ns
Focal depth bin
 6298Month (−)170.2520.023
 6300 35  
 6308Month (+), SST (−)570.1670.003
 6310Period (+), month (+), SST (−)590.258<0.001
 6475 26  
 7483 95  
 7485Period (+), region (+)160.5200.003
 7487 17  

Dive locations of five sea lions whose dive count or TAD was influenced by distance from shore or seafloor depth were clustered among the nearshore areas of the Krenitzen Islands, Unalaska Island and Bogoslof Island. Median dive depths did not vary during March–June, although one individual (#6310) showed tendencies for deeper diving after May, while another (#6300) made fewer deeper dives. In contrast, the three sea lions whose diving was influenced by month or SST ranged widely throughout the EAI, and undertook offshore trips (distinguishable in Fig. 2, May–July north of the Aleutian Islands). All three exhibited relationships between date and median depth of dives, although one (#7483) was opposite to that of the others such that the deeper dives were made during March while in the northern Pacific Ocean.

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

In the EAI, juvenile SSL developed foraging skills mostly within nearshore habitats 5–10 nm from shore in waters ≤100 m deep. This is similar to findings of Raum-Suryan et al. (2004) that 90% of juvenile sea lion trips in Prince William Sound and Southeast Alaska were within 15 km (8 nm) round trip distance from a haul-out, and Loughlin et al. (2003) that measured a mean trip distance (for round or between haul-out trips) of 17 km (9.1 nm). Trip distance in both of those studies, however, was the distance actually traveled by the sea lion from a haul-out, rather than the distance from shore of locations associated with diving determined in our study. Distance from shore of diving locations provides a somewhat different perspective of habitat use and one way of evaluating the utility of managed protection areas. That is, while juvenile SSL made trips of up to 447 km (241 nm; Loughlin et al., 2003) or round trips from haul-outs of up to 111 km (60 nm; Raum-Suryan et al., 2004), we found that most diving locations during November–April in the EAI region were <5–10 nm offshore. Diving in more distant waters off the Bering Sea shelf increased during May–June, and May locations tended to be northwest of April locations, indicative of general movements downstream of the ACC or up to the Bering Sea (Fig. 2; Table 4). These general patterns of juvenile SSL distributions and diving activity may have been related to changes in development with ontogeny, or to seasonal changes in physical habitats or prey availability.

Evaluation of the influence of ontogenetic versus environmental effects depends largely upon assumptions regarding juvenile nutritional status. Otariids have adopted strategies of extended lactation periods (Oftedahl et al., 1987), and weaning in pinnipeds generally begins when maternal input cannot meet maintenance and growth needs of the pup (Lee et al., 1991). Because of their relatively large body mass, SSL require close proximity to abundant prey resources to maintain a positive energy balance of mother and pup (Boyd, 1998), and pups accompany mothers to multiple haul-out sites after leaving rookeries in late summer. Gradual weaning provides opportunities for pups to develop swimming, diving and foraging skills while receiving nutrition from maternal milk, buffering changes in prey availability (Trillmich, 1996). While pups may begin ingesting solid food as early as 3 months of age (Raum-Suryan et al., 2004), mean trip durations of <0.75 days during November–May were consistent with maternal dependency, being within a range of trip durations measured for adult females presumed to be supporting pups during winter [0.75 day (Merrick and Loughlin, 1997) to about 2.5 days (Trites and Porter, 2002)]. By May, trips of many immature sea lions exceeded this duration and were farther offshore, a possible indication of nutritional independence (Loughlin et al., 2003; Raum-Suryan et al., 2004).

Previous studies found that diving ability of young-of-the-year SSL, expressed as increased dive rates and deeper dive depths, progressively developed between winter and summer (Merrick and Loughlin, 1997; Loughlin et al., 2003). Our findings confirm development in diving ability through 12 months of age, and found that in winter, juveniles dived more, spent more time underwater, and utilized more of the water column than pups in the same areas. Between 1 and 2 yr of age, however, there was an apparent leveling of diving ability as measured by dive rate and TAD. This may be related to developmental changes in mass-specific oxygen storage capacity, which were shown by Richmond (2004) to plateau between 9 and 17 months of age in SSL, or could have been due to environmental interactions. Changes in diving activity may result from increased knowledge of prey locations (Merrick and Loughlin, 1997), changes or differences in foraging habitat (Loughlin et al., 2003), or changes in prey distribution and availability.

Seasonal and spatial variability of prey may play an important role in foraging success and survival of immature sea lions developing foraging skills during the transition to nutritional dependence. Successful foraging of immature sea lions could lead to earlier and more rapid development of their physiologic capacity to increase diving ability (Richmond, 2004). The greater diet diversity of sea lions in the EAI area is presumed to reflect local prey abundance and concentrating features of the habitat (Sinclair and Zeppelin, 2002), and thus extensive use of demersal habitats <100 m in the eastern pass areas may provide access to this prey diversity. Winter (December–April) diets of sea lions in the EAI are dominated by pollock (Theragra chalcogramma) and Atka mackerel (Pleurogrammus monopterygius), but also include a number of forage fish species (Sinclair and Zeppelin, 2002). Summer (May–September) diets are dominated by pollock, Pacific salmon (Onchorhyncus spp.), herring (Clupea pallasi), and Atka mackerel, but also include squid and octopus (class Cephalopoda). Large aggregations of pollock are found throughout the eastern Bering Sea and in the Unimak Pass and Unalaska areas during summer (Yanagimoto et al., 2002; Logerwell et al., 2005), and salmon seasonally migrate along the Aleutian Islands and through passes (Pearcy, 1992). Pacific herring migrate from winter grounds offshore over the eastern Bering Sea slope inshore to coastal spawning areas (including the Alaska Peninsula and Unimak Pass area), where they remain to feed during summer (Wespestad, 1991).

These prey species occupy depths shown to be exploited by juvenile sea lions in the present study. Juvenile pollock inhabit depths of 30–110 m in the daytime and move within 40 m of the surface at night (Brodeur et al., 1999; Schabetsberger et al., 2000). Capelin (Mallotus villosus) spawn along shore at night in the eastern Bering Sea during mid-May to late-July, and during the rest of the year are found at depths of 20–90 m over seafloor depths of 90–125 m (Naumenko, 1996; Brodeur et al., 1999). Most dives by sea lions measured in the present study were to <50 m, but deeper diving also occurred (Fig. 3).

Unfortunately, data on seasonal, geographic, and depth distributions of sea lion prey are not available for direct comparison with dive locations of our instrumented animals. However, it may be reasonable to assume that the distributions of some fish prey respond to changes in the physical environment. Associations with frontal features or specific oceanographic habitats have been identified for adult lactating sub-Antarctic fur seals (Georges et al., 2000) and Antarctic fur seals (McCafferty et al., 1998; Guinet et al., 2001). Oceanographic features associated with SSL diving locations tracked seasonal changes in SST and primary productivity (Fig. 5). Use of Bering Sea off-shelf waters by juvenile SSL, and the tendency for immature sea lions to move with a northwesterly bearing during May was concurrent with a period of rapid changes in SST and chlorophyll a concentrations (Ladd et al., 2005a). These movements could thus have been as a response of the juvenile (or its mother) to prey shifting in response to this greater productivity north of the Aleutian Islands. Although we found diving activity to vary with SST, temperature may have been less influential than physiologic development. Sea surface temperatures increased rapidly during March–July (Fig. 5), a period corresponding to rapid increases in dive rate and TAD of 9–13 month olds (Fig. 4). There was not a similarly strong relationship between SST and dive activity (Fig. 6). However, diving activity during offshore trips of three sea lions into the Bering Sea was related to SST (Tables 5 and 6), and off-shelf trips may be more appropriate for examining associations with oceanographic features at the spatial and temporal scales used in this study.

Off-shore trips may also be potentially associated with eddies that propagate from the Aleutian passes and are important frontal features of the Bering Sea basin and outer shelf (Stabeno et al., 1999), with consequences for nutrient and biota mixing (Okkonen, 2001) and prey concentration (Springer et al., 1996). Winter migrating adult male (Loughlin et al., 1999) and adult female (Ream et al., 2005) northern fur seals utilized surface currents in the North Pacific and Gulf of Alaska to facilitate travel, but also foraged in areas associated with eddies (Ream et al., 2005).

Beyond associations with broad seasonal changes and some individual results, we did not detect strong environmental associations with changes in diving activity. The explanatory power of environmental variables on diving activity was high for some sea lions but not others in the regression analysis, and there were not consistent relationships between oceanographic features and diving activity among individuals. Similar to the present study, McCafferty et al. (1998) found significant individual variation in accounting for dive activity, and Guinet et al. (2001) found more variation in diving activity was accounted for by environmental variables when examined on larger spatial scales (incorporating spatial trends that smoothed local variability). Sampling limitations and ecologic factors may have independently or collectively contributed to this result in the present study.

Associations could have been obscured because of disparate measurement scales of satellite imagery data and telemetry data, or to animal behavior. Because each location represented dive activity within a 6-h period to minimize pseudoreplication in testing for habitat associations, precise diving locations could not be resolved with this instrumentation. We found location accuracies varied, but were generally within 0.4–4.9 km. Using a single location to represent activity within a 6-h period could potentially represent diving activity within a maximum diameter of 13–45 km (7–24 nm) because surface swimming velocities for otariids range from 0.6 to 2.1 m s−1 (Ponganis et al., 1990; Rosen and Trites, 2002). If dive rate is inversely related to surface swimming speeds (Crocker et al., 2001), the error radius was likely less than or at the lower end of that range. Satellite imagery of SST and chlorophyll concentration was resolved to 4.89 km2 and averaged monthly. Thus, activity associated with a single location may have only broadly represented dive behaviour associated with a spatial location and habitat feature. This combination of techniques did not provide the resolution to detect finer scale associations such as might exist with tidally generated fronts, shown to be an important habitat feature for foraging seabirds in the Aleutian Islands (Hunt et al., 1998; Ladd et al., 2005b). Because of persistent cloud cover and extent of water column mixing in Aleutian passes (Ladd et al., 2005a), satellite imagery was not optimal for detecting associations among diving activity and habitat type for nearshore divers, but was likely more appropriate for sea lions diving farther offshore.

Behavioral variability might also obscure otherwise significant relationships when pooled for analyses, and naive foragers may not have well-defined responses that vary significantly with habitat features. Similarly, associations would be obscured if diving activity were not related to foraging, but rather in response to changing storm directions (suggested by Sease and York, 2003 to explain changes in haul-out use) or predator avoidance. Satellite depth recorders deployed on immature sea lions thus provide data for foraging trips, relocations, and activity while a pup is awaiting mother's return. Without other data that determine foraging activity directly, foraging must be inferred or assumed from behavioural data, and it is difficult to interpret whether movements and habitat use reflect maternal or juvenile responses to prey availability or other factors. The approach used in this study was thus adequate to examine general associations between diving location or activity and bathymetric and oceanographic features. Additional modelling could be undertaken to examine habitat selection, presuming appropriate assumptions are made regarding accessibility of habitats. Relationships with nearshore oceanographic features that may be related to prey abundance will require sampling at finer scales than were available for this study.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Authors thank T. Loughlin, J. Thomason, T. Zeppelin, S. Norman, J. Sease, R. Towell, R. Ream, K. Raum-Suryan, J. Benson, L. Snoddy, D. Nickless, K. Bell (and the crew of the US Fish and Wildlife Service vessel Tiglax), and G. Edwards (and the crew of the Big Valley) for contributions to this project. Partial support for the research was provided by NOAA Coastal Ocean Grant NA16OP1164 via the Joint Institute for Marine Observations to George Hunt. Remote sensing sea surface temperature and chlorophyll a data were acquired as part of the NASA's Earth Science Enterprise. Algorithms were developed by the MODIS Science Teams, and data were processed by the MODIS Adaptive Processing System (MODAPS) and Goddard Distributed Active Archive Center (DAAC), archived and distributed by the Goddard DAAC. We also thank Kristin Laidre, Lowell Fritz, Tom Loughlin, and two anonymous reviewers for comments that improved the manuscript. Steller sea lion field work was authorized under NOAA Fisheries Marine Mammal Protection Act and Endangered Species Act Permit 782-1532 (00, 01, 02), and within the Alaska National Maritime Refuge by Special Use Permit from the US Fish and Wildlife Service.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  • Alverson, D.L. (1992) A review of commercial fisheries and the Steller sea lion Eumetopias jubatus: the conflict arena. Rev. Aquat. Sci. 63: 203256.
  • Bickham, J.W. , Patton, J.C. and Loughlin, T.R. (1996) High variability for control-region sequences in a marine mammal: implications for conservation and biogeography of Steller sea lions (Eumetopias jubatus). J. Mammal. 77: 95108.
  • Boyd, I.L. (1998) Time and energy constraints in pinniped lactation. Am. Nat. 152: 717728.
  • Brodeur, R.D. , Wilson, M.T. and Walters, G.E. (1999) Forage fishes in the Bering Sea: distribution, species associations, and biomass trends. In: Dynamics of the Bering Sea. T.R.Loughlin & K.Ohtani (eds ) Fairbanks, AK, USA: University of Alaska Sea Grant Program, Rep. 99-06, pp . 509536.
  • Calkins, D.G. and Pitcher, K.W. (1982) Population assessment, ecology and trophic relationships of Steller sea lions in the Gulf of Alaska. Environmental Assessment of the Alaskan Continental Shelf. Final Reports 19: 455546.
  • Call, K.A. and Loughlin, T.R. (2005) An ecological classification of Alaskan Steller sea lion (Eumetopias jubatus) rookeries. Fish. Oceanogr. 14 (Suppl. 1):212222.
  • Crocker, D.E. , Gales, N.J. and Costa, D.P. (2001) Swimming speed and foraging strategies of New Zealand sea lions (Phocarctos hookeri). J. Zool. 254: 267277.
  • Fancy, S.G. , Pank, L.F. , Douglas, D.C. et al. (1988) Satellite telemetry: a new tool for wildlife research and management. US Fish Wildl. Serv. Resour. Publ. 172: 154.
  • Frost, K.J. , Simpkins, M.A. and Lowry, L.F. (2001) Diving behavior of subadult and adult harbor seals in Prince William Sound, Alaska. Mar. Mamm. Sci. 17: 813834.
  • Georges, J. , Bonadonna, F. and Guinet, C. (2000) Foraging habitat and diving activity of lactating sub-Antarctic fur seals in relation to sea-surface temperatures at Amsterdam Island. Mar. Ecol. Prog. Ser. 196: 291304.
  • Guinet, C. , Dubroca, L. , Lea, M.A. et al. (2001) Spatial distribution of foraging in female Antarctic fur seals Arctocephalus gazella in relation to oceanographic variables: a scale-dependent approach to using geographic information systems. Mar. Ecol. Prog. Ser. 219: 251264.
  • Hastings, K.K. , Frost, K.J. , Simpkins, M.A. , Pendleton, G.W. , Swain, U.G. and Small, R.J. (2004) Regional differences in diving behavior of harbor seals in the Gulf of Alaska. Can. J. Zool. 82: 17551773.
  • Heath, R.B. , Calkins, D. , McAllister, D. , Taylor, W. and Spraker, T. (1996) Telazol and isoflurane field anesthesia in free-ranging Steller's sea lions (Eumetopias jubatus). J. Zoo. Wildl. Med. 27: 3543.
  • Hunt, G.L. Jr , Russell, R.W. , Coyle, K.O. and Weingartner, T. (1998) Comparative foraging ecology of planktivorous auklets in relation to ocean physics and prey availability. Mar. Ecol. Prog. Ser. 167: 241259.
  • Keating, K.A. (1994) An alternative index of satellite telemetry location error. J. Wildl. Manage. 58: 414421.
  • Ladd, C. , Hunt, G. Jr , Mordy, C. , Salo, S. and Stabeno, P. (2005a) Marine environment of the central and eastern Aleutian Islands: physical mechanisms, nutrient availability and primary production. Fish. Oceanogr. 14 (Suppl. 1):2238.
  • Ladd, C. , Jahncke, J. , Hunt, G.L. Jr , Coyle, K.O. and Stabeno, P.J. (2005b) Hydrographic features and seabird foraging in Aleutian Passes. Fish. Oceanogr. 14 (Suppl. 1):178195.
  • Lea, M.-A. and Dubroca, L. (2003) Fine-scale linkages between the diving behavior of Antarctic fur seals and oceanographic features in the southern Indian Ocean. ICES J. Mar. Sci. 60: 9901002.
  • Lee, P.C. , Majluf, P. and Gordon, I.J. (1991) Growth, weaning and maternal investment from a comparative perspective. J. Zool. 225: 99114.
  • Logerwell, E.A. , Aydin, K. , Barbeaux, S. et al. (2005) Geographic patterns in the demersal ichthyofauna of the Aleutian Islands shelf. Fish. Oceanogr. 14 (Suppl. 1):93112.
  • Loughlin, T.R. (1997) Using the phylogeographic method to identify Steller sea lion stocks. In: Molecular Genetics of Marine Mammals. A.Dizon , S.J.Chivers & W.F.Perrin (eds ) Lawrence, KS, USA: Soc. Mar. Mammal. Spec. Publ. 3, pp . 159171.
  • Loughlin, T.R. and Merrick, R.L. (1989) Comparison of commercial harvest of walleye pollock and northern sea lion abundance in the Bering Sea and Gulf of Alaska. In: Proceedings of the International Symposium on the Biology and Management of Walleye Pollock. Fairbanks, AK, USA: Alaska Sea Grant Program, Rep. 89-01, pp . 679700.
  • Loughlin, T.R. and York, A.E. (2000) An accounting of the sources of Steller sea lion, Eumetopias jubatus, mortality. Mar. Fish. Rev. 62: 4045.
  • Loughlin, T.R. , Perlov, A.S. and Vladirimov, V.A. (1992) Range-wide survey and estimation of total abundance of Steller sea lions in 1989. Mar. Mamm. Sci. 8: 220239.
  • Loughlin, T.R. , Ingraham, W.J. Jr , Baba, N. and Robson, B.W. (1999) Use of a surface-current model and satellite telemetry to assess marine mammal movements in the Bering Sea. In: Dynamics of the Bering Sea. T.R.Loughlin & K.Ohtani (eds ) Fairbanks, AK, USA: University of Alaska Sea Grant Program, Rep. 99-03, pp . 615630.
  • Loughlin, T.R. , Sterling, J.T. , Merrick, R.L. , Sease, J.L. and York, A.E. (2003) Immature Steller sea lion diving behavior. Fish. Bull. 101: 566582.
  • McAllister, D.C. , Calkins, D.G. and Pitcher, K.W. (2001) Underwater capture of juvenile Steller sea lions with SCUBA: a narrated video presentation. In: Cold Water Diving for Science. S.J.Jewett (ed. ) Fairbanks, USA: University of Alaska Sea Grant Program, Rep. 01-06, pp . 5355.
  • McCafferty, D.J. , Boyd, I.L. , Walker, T.R. and Taylor, R.I. (1998) Foraging responses of Antarctic fur seals to changes in the marine environment. Mar. Ecol. Prog. Ser. 166: 285299.
  • Merrick, R.L. and Loughlin, T.R. (1997) Foraging behavior of adult female and young-of-the-year Steller sea lions in Alaskan waters. Can. J. Zool. 75: 776786.
  • Merrick, R.L. , Brown, R. , Calkins, D.G. and Loughlin, T.R. (1995) A comparison of Steller sea lion, Eumetopias jubatus, pup masses between rookeries with increasing and decreasing populations. Fish. Bull. 93: 753758.
  • Merrick, R.L. , Chumbley, M.K. and Byrd, G.V. (1997) Diet diversity of Steller sea lions (Eumetopias jubatus) and their population decline in Alaska: a potential relationship. Can. J. Fish. Aquat. Sci. 54: 13421348.
  • Naumenko, E.A. (1996) Distribution, biological condition, and abundance of capelin (Mallotus villosus socialis) in the Bering Sea. In: Ecology of the Bering Sea: A Review of Russian Literature. O.A.Mathisen & K.O.Coyle (eds ) Fairbanks, USA: University of Alaska Sea Grant Program, Rep. 96-01, pp . 237256.
  • Oftedahl, O.T. , Boness, D.J. and Tedman, R.A. (1987) The behavior, physiology, and anatomy of lactation in the Pinnipedia. Curr. Mammal. 1: 175245.
  • Okkonen, S.R. (2001) Altimeter observations of the Bering Slope Current eddy field. J. Geophys. Res. 106: 24652746.
  • Pearcy, W.G. (1992) Ocean Ecology of North Pacific Salmonids. Seattle, USA: University of Washington Press, 179 pp .
  • Pitcher, K.W. and Calkins, D. (1981) Reproductive biology of Steller sea lions in the Gulf of Alaska. J. Mammal. 62: 599605.
  • Pitcher, K.W. , Burkanov, V.N. , Calkins, D.G. et al. (2001) Spatial and temporal variation in the timing of births of Steller sea lions. J. Mammal. 82: 10471053.
  • Ponganis, P.J. , Ponganis, E.P. , Ponganis, K.V. , Kooyman, G.L. , Gentry, R.L. and Trillmich, F. (1990) Swimming velocities in otariids. Can. J. Zool. 68: 21052112.
  • Porter, B. (1997) Winter ecology of Steller sea lions (Eumetopias jubatus) in Alaska. MS thesis, University of British Columbia, British Columbia, USA, 84 pp .
  • Raum-Suryan, K.L. , Rehberg, M.J. , Pendleton, G.W. , Pitcher, K.W. and Gelatt, T.S. (2004) Development of dispersal, movement patterns, and haul-out use by pup and juvenile Steller sea lions (Eumetopias jubatus) in Alaska. Mar. Mamm. Sci. 20: 823850.
  • Ream, R.R. , Sterling, J.T. and Loughlin, T.R. (2005) Oceanographic features related to northern fur seal migratory movements. Deep-sea Res. II 52: 823843.
  • Richmond, J.P. (2004) Ontogeny of total body oxygen stores and aerobic dive potential in the Steller sea lion (Eumetopias jubatus). MS thesis, University of Alaska, Alaska, USA, 114 pp .
  • Rosen, D.A.S. and Trites, A.W. (2002) Cost of transport in Steller sea lions, Eumetopias jubatus. Mar. Mamm. Sci. 18: 513524.
  • Schabetsberger, R. , Brodeur, R.D. , Cianelli, L. , Napp, J.M. and Swartzman, G.L. (2000) Diel vertical migration and interaction of zooplankton and juvenile walleye pollock (Theragra chalcogramma) at a frontal region near the Pribilof Islands, Bering Sea. ICES J. Mar. Sci. 57: 12831295.
  • Sease, J.L. and Gudmundson, C.J. (2002) Aerial and Land-based Surveys of Steller Sea Lions (Eumetopias jubatus) from the Western Stock in Alaska, June and July 2001 and 2002. NOAA Tech. Memo., NMFS-AFSC-131 , 45 pp .
  • Sease, J.L. and York, A.E. (2003) Seasonal distribution of Steller's sea lions at rookeries and haul-out sites in Alaska. Mar. Mamm. Sci. 19: 745763.
  • Sinclair, E.H. and Stabeno, P.J. (2002) Mesopelagic nekton and associated physics of the southeastern Bering Sea. Deep-sea Res. II 49: 61276145.
  • Sinclair, E.H. and Zeppelin, T.K. (2002) Seasonal and spatial differences in diet in the western stock of Steller sea lions (Eumetopias jubatus). J. Mammal. 83: 973990.
  • Springer, A.M. , McRoy, C.P. and Flint, M.V. (1996) The Bering Sea green belt: shelf-edge processes and ecosystem production. Fish. Oceanogr. 5: 223250.
  • Stabeno, P.J. and Reed, R.K. (1994) Circulation in the Bering Sea basin observed by satellite-tracked drifters: 1986–1993. J. Phys. Oceanogr. 24: 848854.
  • Stabeno, P.J. , Schumacher, J.D. and Ohtani, K. (1999) The physical oceanography of the Bering Sea. In: Dynamics of the Bering Sea. T.R.Loughlin & K.Ohtani (eds ) Fairbanks, AK, USA: University of Alaska Sea Grant Program, Rep. 99-06, pp . 128.
  • Stabeno, P.J. , Reed, R.K. and Napp, J.M. (2002) Transport through Unimak Pass, Alaska. Deep-sea Res. II 49: 59195930.
  • Trillmich, F. (1996) Parental investment in pinnipeds. In: Parental Care: Evolution, Mechanisms, and Adaptive Significance. A Volume in Advances in the Study of Behavior, Vol. 25 . J.S.Rosenblatt & C.T.Snowdon (eds ) San Diego, USA: Academic Press, pp . 533577.
  • Trites, A.W. and Porter, B.T. (2002) Attendance patterns of Steller sea lions (Eumetopias jubatus) and their young during winter. J. Zool. 256: 547556.
  • Wespestad, V.G. (1991) Pacific herring population dynamics, early life history, and recruitment variation relative to eastern Bering Sea oceanographic factors. PhD thesis, University of Washington, Washington, USA, 237 pp .
  • Yanagimoto, T. , Nishimura, A. , Mito, K. , Takao, Y. and Williamson, N.J. (2002) Interannual changes of biological properties of walleye pollock Theragra chalcogramma in the central Bering Sea. Prog. Oceanogr. 55: 195208.
  • York, A.E. (1994) The population dynamics of northern sea lions, 1975–1985. Mar. Mamm. Sci. 10: 3851.
  • York, A.E. and Holmes, E.E. (2003) Using age structure to detect impacts on threatened populations: a case study using Steller sea lions. Conserv. Biol. 17: 17941806.
  • York, A.E. , Merrick, R.L. and Loughlin, T.R. (1996) An analysis of the Steller sea lion metapopulation in Alaska. In: Metapopulations and Wildlife Conservation. D.R.McCullough (ed. ) Covelo: Island Press, pp . 259292.
  • Zar, J.H. (1984) Biostatistical Analysis. Englewood Cliffs: Prentice Hall, 718 pp .