†Present address: Bartomeu Rossello Porcel No. 11, Apt. 4 Iz. Palma de Mallorca 07014, Spain.
Immature Steller sea lion (Eumetopias jubatus) dive activity in relation to habitat features of the eastern Aleutian Islands
Article first published online: 27 SEP 2005
Volume 14, Issue Supplement s1, pages 243–258, November 2005
How to Cite
FADELY, B. S., ROBSON, B. W., STERLING, J. T., GREIG, A. and CALL, K. A. (2005), Immature Steller sea lion (Eumetopias jubatus) dive activity in relation to habitat features of the eastern Aleutian Islands. Fisheries Oceanography, 14: 243–258. doi: 10.1111/j.1365-2419.2005.00379.x
- Issue published online: 27 SEP 2005
- Article first published online: 27 SEP 2005
- Received 31 October 2003 Revised version accepted 21 June 2005
- foraging behaviour;
- geographic information system;
- remote sensing;
- satellite telemetry;
- satellite tracking
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.
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.
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.
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).
|ID||Sex||Mass (kg)||Age coverage (months)||Capture location||Region*||Capture date||Date of last transmission||Deployment period (days)|
|6295||F||87.0||9–11||Seguam||CAI||February 29, 2000||April 29, 2000||60|
|6296||F||85.8||9–11||Seguam||CAI||February 29, 2000||April 21, 2000||52|
|6297||F||76.2||9–11||Seguam||CAI||February 29, 2000||April 23, 2000||54|
|6298†||M||109.0||9–12||Seguam||CAI||February 29, 2000||June 11, 2000||103|
|6299||F||100.2||9–10||Aiktak||EAI||March 9, 2000||April 7, 2000||29|
|6300†||M||79.6||9–12||Aiktak||EAI||March 9, 2000||June 14, 2000||98|
|6303||M||132.0||21–23||Akutan||EAI||February 26, 2001||May 7, 2001||70|
|6304||F||101.2||9–11||Aiktak||EAI||March 1, 2001||April 28, 2001||58|
|6305||F||105.8||9–12||Ugamak||EAI||March 1, 2001||June 1, 2001||92|
|6306||F||102.8||21–22||Tigalda||EAI||March 3, 2001||April 24, 2001||52|
|6307||M||86.6||9–10||Tigalda||EAI||March 3, 2001||April 6, 2001||34|
|6308†||F||87.0||9–13||Aiktak||EAI||March 3, 2001||July 29, 2001||148|
|6309||F||107.0||9–11||Aiktak||EAI||March 3, 2001||May 19, 2001||77|
|6310†||F||99.4||9–12||Aiktak||EAI||March 3, 2001||July 1, 2001||120|
|6311||F||152.0||21–23||Akun||EAI||March 4, 2001||May 6, 2001||63|
|6312||F||116.0||9–11||Akun||EAI||March 4, 2001||April 30, 2001||57|
|6466||F||85.8||5–6||Ugamak||EAI||November 13, 2001||January 4, 2002||52|
|8238||F||83.8||5–7||Ugamak||EAI||November 13, 2001||January 24, 2002||72|
|8239||F||107.6||17–23||Aiktak||EAI||November 14, 2001||May 14, 2002||181|
|6475†||M||124.0||9–12||Aiktak||EAI||March 12, 2002||July 7, 2002||117|
|7469||M||94.6||9–12||Long Is.||CGOA||March 2, 2002||June 16, 2002||106|
|7481||F||102.0||9–10||Basalt||EAI||March 10, 2002||April 15, 2002||36|
|7482||F||71.8||9–11||Aiktak||EAI||March 11, 2002||May 10, 2002||60|
|7483†||M||81.8||9–12||Aiktak||EAI||March 11, 2002||July 4, 2002||115|
|7484||M||114.6||9–11||Aiktak||EAI||March 11, 2002||June 4, 2002||85|
|7485†||M||122.8||9–13||Aiktak||EAI||March 11, 2002||August 5, 2002||147|
|7486||M||127.8||9–11||Aiktak||EAI||March 11, 2002||May 3, 2002||53|
|7487†||F||85.6||9–12||Aiktak||EAI||March 11, 2002||June 14, 2002||95|
|7488||M||135.0||9–11||Aiktak||EAI||March 12, 2002||May 31, 2002||80|
|7489||F||118.6||9–10||Aiktak||EAI||March 12, 2002||May 7, 2002||56|
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 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.
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).
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.
|Season||Seafloor depth (m)||Distance to shore (nm)||Pooled|
|November–January||<50||63.4 (1.6)||0.9 (0.9)||0.0 (0.0)||64.3 (1.3)|
|50–100||32.3 (3.6)||1.7 (1.7)||0.9 (0.9)||34.9 (1.5)|
|100–150||0.9 (0.9)||0.0 (0.0)||0.0 (0.0)||0.9 (0.9)|
|>150||0.0 (0.0)||0.0 (0.0)||0.0 (0.0)||0.0 (0.0)|
|Pooled||96.6 (3.4)||2.6 (2.6)||0.9 (0.9)|
|February–April||<50||68.7 (5.2)||0.7 (0.4)||0.0 (0.0)||69.5 (5.3)|
|50–100||21.2 (3.7)||2.7 (1.0)||0.3 (0.2)||24.3 (3.8)|
|100–150||4.8 (3.6)||1.0 (0.5)||0.0 (0.0)||5.8 (3.6)|
|>150||0.1 (0.1)||0.3 (0.3)||0.0 (0.0)||0.4 (0.3)|
|Pooled||94.9 (1.5)||4.8 (1.4)||0.3 (0.2)|
|May–July||<50||63.3 (8.6)||0.2 (0.2)||0.0 (0.0)||63.5 (8.6)|
|50–100||20.5 (6.5)||1.5 (0.6)||1.2 (1.2)||23.2 (6.0)|
|100–150||0.5 (0.3)||0.7 (0.5)||1.0 (1.0)||2.1 (1.4)|
|>150||0.2 (0.2)||0.2 (0.2)||10.8 (8.2)||11.2 (8.2)|
|Pooled||84.5 (8.4)||2.6 (1.0)||12.9 (8.3)|
|All seasons||92.5 (2.3)||4.1 (1.0)||0.8 (0.5)|
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).
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).
|Bearing (°; ±CI)||r||P-value||Distance (nm)||n|
|May||293 (33)†||0.617||0.002||13.1 (4.6)||15|
|Distances >10 nm|
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.
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).
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).
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.
|Animal ID||Significant factors||n||R2||P-value|
|6298||Period (−), region (−)||17||0.456||0.006|
|6308||Period (−), region (−)||57||0.337||<0.001|
|6310||Seafloor depth (+)||59||0.057||0.039|
|6475||Month (+), shore distance (−)||26||0.498||<0.001|
|7483||Period (−), region (−)||95||0.131||0.001|
|6298||Period (−), month (+)||22||0.344||0.007|
|6308||Period (−), SST (+)||57||0.250||<0.001|
|6310||Region (+), seafloor depth (+)||60||0.165||0.002|
|6475||Month (+), shore distance (−)||26||0.480||<0.001|
|7483||Month (−), SST (+)||92||0.132||0.001|
|7485||Period (−), seafloor depth (−)||19||0.889||<0.001|
|7487||Seafloor depth (+)||15||0.218||0.045|
|Animal ID||Significant factors||n||R2||P-value|
|6300||SST (−), shore distance (−)||40||0.471||<0.001|
|6308||Shore distance (−)||70||0.167||<0.001|
|7483||Month (+), SST (−), shore distance (−)||104||0.244||<0.001|
|Focal depth bin|
|6308||Month (+), SST (−)||57||0.167||0.003|
|6310||Period (+), month (+), SST (−)||59||0.258||<0.001|
|7485||Period (+), region (+)||16||0.520||0.003|
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.
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.
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.
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