Stability in The Proportion of Harbor Seals Hauled Out Under Locally Ideal Conditions

We monitored the haul-out behavior of 68 radio-tagged harbor seals (Phoca vitulina) during the molt season at two Alaskan haul-out sites (Grand Island, August-September 1994; Nanvak Bay, August-September 2000). For each site, we created a statistical model of the proportion of seals hauled out as a function of date, time of day, tide, and weather covariates. Using these models, we identified the conditions that would result in the greatest proportion of seals hauled out. Although those “ideal conditions” differed between sites, the proportion of seals predicted to be hauled out under those conditions was very similar (81.3% for Grand Island and 85.7% for Nanvak Bay). The similar estimates for both sites suggest that haul-out proportions under locally ideal conditions may be constant between years and geographic regions, at least during the molt season.

The Abundance of Harbor Seals in the Gulf of Alaska

The abundance of harbor seals (Phoca vitulina richardii) has declined in recent decades at several Alaska locations. The causes of these declines are unknown, but there is concern about the status of the populations, especially in the Gulf of Alaska. To assess the status of harbor seals in the Gulf of Alaska, we conducted aerial surveys of seals on their haul-out sites in August-September 1996. Many factors influence the propensity of seals to haul out, including tides, weather, time of day, and time of year. Because these “covariates” cannot simultaneously be controlled through survey design, we used a regression model to adjust the counts to an estimate of the number of seals that would have been ashore during a hypothetical survey conducted under ideal conditions for hauling out. The regression, a generalized additive model, not only provided an adjustment for the covariates, but also confirmed the nature and shape of the covariate effects on haul-out behavior. The number of seals hauled out was greatest at the beginning of the surveys (mid-August). There was a broad daily peak from about 1100-1400 local solar time. The greatest numbers were hauled out at low tide on terrestrial sites. Tidal state made little difference in the numbers hauled out on glacial ice, where the area available to seals did not fluctuate with the tide. Adjusting the survey counts to the ideal state for each covariate produced an estimate of 30,035 seals, about 1.8 times the total of the unadjusted counts (16,355 seals). To the adjusted count, we applied a correction factor of 1.198 from a separate study of two haul-out sites elsewhere in Alaska, to produce a total abundance estimate of 35,981 (SE 1,833). This estimate accounts both for the effect of covariates on survey counts and for the proportion of seals that remained in the water even under ideal conditions for hauling out.

Provisioning Strategies of Antarctic Fur Seals and Chinstrap Penguins Produce Different Responses to Distribution of Common Prey and Habitat

Central-place foragers that must return to a breeding site to deliver food to offspring are faced with trade-offs between prey patch quality and distance from the colony. Among colonial animals, pinnipeds and seabirds may have different provisioning strategies, due to differences in their ability to travel and store energy. We compared the foraging areas of lactating Antarctic fur seals and chinstrap penguins breeding at Seal Island, Antarctica, to investigate whether they responded differently to the distribution of their prey (Antarctic krill and myctophid fish) and spatial heterogeneity in their habitat. Dense krill concentrations occurred in the shelf region near the colony. However, only brooding penguins, which are expected to be time-minimizers because they must return frequently with whole food for their chicks, foraged mainly in this proximal shelf region. Lactating fur seals and incubating penguins, which can make longer trips to increase energy gain per trip, and so are expected to be energy-maximizers, foraged in the more distant (>20 km from the island) slope and oceanic regions. The shelf region was characterized by more abundant, but lower-energy-content immature krill, whereas the slope and oceanic regions had less abundant but higher-energy-content gravid krill, as well as high-energy-content myctophids. Furthermore, krill in the shelf region undertook diurnal vertical migration, whereas those in the slope and oceanic regions stayed near the surface throughout the day, which may enhance the capture rate for visual predators. Therefore, we sug- gest that the energy-maximizers foraged in distant, but potentially more profitable feeding regions, while the time-minimizers foraged in closer, but potentially less profitable regions. Thus, time and energy constraints derived from different provisioning strategies may result in sympatric colonial predator species using different foraging areas, and as a result, some central-place foragers use sub- optimal foraging habitats, in terms of the quality or quantity of available prey.

Hunting and social behaviour of leopard seals (Hydrurga leptonyx) at Seal Island, South Shetland Islands, Antarctica

The hunting behavior of leopard seals Hydrurga leptonyx was monitored opportunistically at Seal Island, South Shetland Islands, during the austral summers from 1986/87 to 1994/95. Leopard seals used several methods to catch Antarctic fur seal pups Arctocephalus gazella and chinstrap penguins Pygoscelis antarctica, and individuals showed different hunting styles and hunting success. One to two leopard seals per year were responsible for an average of 60% of observed captures of fur seal pups. Leopard seals preyed on penguins throughout the summer, but preyed on fur seal pups only between late December and mid-February. Hunting behavior differed significantly between different locations on the island; fur seals were hunted only at one colony, and penguins were hunted in several areas. The relative abundance of prey types, size of prey in relation to predator, and specialization of individual leopard seals to hunt fur seal prey probably influence individual prey preferences among leopard seals. On five occasions, two leopard seals were seen together on Seal Island. Possible interpretations of the relationship between the interacting leopard seals included a mother-offspring relationship, a consorting male-female pair, and an adult leopard seal followed by an unrelated juvenile. In two incidents at Seal Island, two leopard seals were observed interacting while hunting: one seal captured fur seal pups and appeared to release them to the other seal. Observations of leopard seals interacting during hunting sessions were difficult to confirm as co-operative hunting, but they strongly implied that the two seals were not agonistic toward one another. The hunting success of individual leopard seals pursuing penguins or fur seals is probably high enough for co-operative hunting not to become a common hunting strategy; however, it may occur infrequently when it increases the hunting productivity of the seals.

Population Growth of Antarctic Fur Seals: Limitation by a Top Predator, The Leopard Seal?

Antarctic fur seals (Arctocephalus gazella) in the South Shetland Islands are recovering from 19th-century exploitation more slowly than the main population at South Georgia. To document demographic changes associated with the recovery in the South Shetlands, we monitored fur seal abundance and reproduction in the vicinity of Elephant Island during austral summers from 1986/1987 through 1994/1995. Total births, mean and variance of birth dates, and average daily mortality rates were estimated from daily live pup counts at North Cove (NC) and North Annex (NA) colonies on Seal Island. Sightings of leopard seals (Hydrurga leptonyx) and incidents of leopard seal predation on fur seal pups were recorded opportunistically during daily fur seal research at both sites. High mortality of fur seal pups, attributed to predation by leopard seals frequently observed at NC, caused pup numbers to decline rapidly between January and March (i.e., prior to weaning) each year and probably caused a long-term decline in the size of that colony. The NA colony, where leopard seals were never observed, increased in size during the study. Pup mortality from causes other than leopard seal predation appeared to be similar at the two sites. The number of pups counted at four locations in the Elephant Island vicinity increased slowly, at an annual rate of 3.8%, compared to rates as high as 11% at other locations in the South Shetland Islands. Several lines of circumstantial evidence are consistent with the hypothesis that leopard seal predators limit the growth of the fur seal population in the Elephant Island area and perhaps in the broader population in the South Shetland Islands. The sustained growth of this fur seal population over many decades rules out certain predator–prey models, allowing inference about the interaction between leopard seals and fur seals even though it is less thoroughly studied than predator–prey systems of terrestrial vertebrates of the northern hemisphere. Top-down forces should be included in hypotheses for future research on the factors shaping the recovery of the fur seal population in the South Shetland Islands.

Seasonal home ranges and fidelity to breeding sites among ringed seals

Population structure and patterns of habitat use among ringed seals (Phoca hispida) are poorly known, in part because seasonal movements have not been adequately documented. We monitored the movements of 98 ringed seals in the Beaufort and Chukchi seas between 1990 and 2006 using three forms of telemetry. In the winter—spring period (when the seals were occupying shorefast ice), we used radio and ultra-sonic tags to track movements above and below the ice, respectively. We used satellite-linked transmitters in summer and fall (when the seals ranged away from their winter sites) to track at-sea movements. In the shorefast ice habitat, the home ranges of 27 adult males ranged from\1 to 13.9 km2 (median = 0.628) while the home ranges of 28 adult females ranged from \1 to 27.9 km2 (median = 0.652). The 3-dimensional volumes used by 9 seals tracked acoustically under the ice averaged 0.07 (SD = 0.04) km3 for subadults and adult males and 0.13 (SD = 0.04) km3 for adult females. Three of the radio-tracked seals and 9 tracked by satellite ranged up to 1,800 km from their winter/spring home ranges in summer but returned to the same small (1–2 km2) sites during the ice-bound months in the following year. The restricted movements of ringed seals during the ice-bound season— including the breeding season—limits their foraging activities for most of the year and may minimize gene flow within the species.

Space–time zero-inflated count models of Harbor seals

Environmental data are spatial, temporal, and often come with many zeros. In this paper, we included space–time random effects in zero-inflated Poisson (ZIP) and ‘hurdle’ models to investigate haulout patterns of harbor seals on glacial ice. The data consisted of counts, for 18 dates on a lattice grid of samples, of harbor seals hauled out on glacial ice in Disenchantment Bay, near Yakutat, Alaska. A hurdle model is similar to a ZIP model except it does not mix zeros from the binary and count processes. Both models can be used for zero-inflated data, and we compared space–time ZIP and hurdle models in a Bayesian hierarchical model. Space–time ZIP and hurdle models were constructed by using spatial conditional autoregressive (CAR) models and temporal first-order autoregressive (AR(1)) models as random effects in ZIP and hurdle regression models. We created maps of smoothed predictions for harbor seal counts based on ice density, other covariates, and spatio-temporal random effects. For both models predictions around the edges appeared to be positively biased. The linex loss function is an asymmetric loss function that penalizes overprediction more than underprediction, and we used it to correct for prediction bias to get the best map for space–time ZIP and hurdle models.

Health Assessment of Weddell Seals, Leptonychotes weddellii, in McMurdo Sound, Antarctica

The demography of Weddell seals in eastern McMurdo Sound, Antarctica, has been well studied during the past three decades (e.g. Stirling 1971; Siniff et al. 1977; Testa and Siniff 1987; Hastings and Testa 1998; Gelatt et al. 2001). Detailed life-history data are available on thousands of seals tagged as pups in McMurdo Sound, making this population a rich resource for wildlife health studies because health parameters can be evaluated in the light of reproductive histories and genetic relationships of several generations of tagged seals. Recently, evidence of exposure to diseases generally associated with domestic animals and feral wildlife has been detected in Antarctic wildlife (Austin and Webster 1993; Olsen et al. 1996; Gardner et al. 1997; Retamal et al. 2000; Foster et al. 2002) and this has generated concern and debate regarding the risks of disease introduction to Antarctic wildlife. Antibodies to viruses that have caused large die-offs in phocids in other areas of the world have been detected in Weddell seals (Bengtson et al. 1991), and there is a historical report of a mass die-off of crabeater seals that may have had a viral etiology (Laws and Taylor 1957).

History and fate of a small isolated population of Weddell seals at White Island, Antarctica

Weddell seals (Leptonychotes weddellii Lesson) at White Island, Antarctica form a small, completely enclosed, natural population hypothesized to be of recent origin, likely founded by individuals from nearby Erebus Bay. This population constitutes an ideal model to document a founder event and ensuing genetic drift, with implications for conservation. Here we combined historical accounts, census and tagging data since the late 1960s, and genetic data (41 microsatellite loci and mitochondrial DNA sequences) from 84 individuals representing nearly all individuals present between 1990 and 2000 to investigate the history of the founding of the White Island population, document its population dynamics and evaluate possible future threats. We fully resolved parental relationships over three overlapping generations. Cytonuclear disequilibrium among the first generation suggested that it comprised the direct descendants of a founding group. We estimated that the White Island population was founded by a small group of individuals that accessed the island during a brief break in the surrounding sea ice in the mid-1950s, consistent with historical accounts. Direct and indirect methods of calculating effective population size were highly congruent and suggested a minimum founding group consisting of three females and two males. The White Island population showed altered reproductive dynamics compared to Erebus Bay, including highly skewed sex ratio, documented inbred mating events, and the oldest known reproducing Weddell seals. A comparison with the putative source population showed that the White Island population has an effective inbreeding coefficient (Fe) of 0.29. Based on a pedigree analysis including the hypothesized founding group, 86% of the individuals for whom parents were known had inbreeding coefficients ranging 0.09–0.31. This high level of inbreeding was correlated with reduced pup survival. Seals at White Island therefore face the combined effects of low genetic variability, lack of immigration, and inbreeding depression. Ultimately, this study provides evidence of the effects of natural isolation on a large, long-lived vertebrate and can provide clues to the potential effects of anthropogenic- caused isolation of similar taxa.

Ringed and bearded seal densities in the eastern Chukchi Sea, 1999–2000

Aerial surveys were conducted in 1999 and 2000 to estimate the densities of ringed (Phoca hispida) and bearded (Erignathus barbatus) seals in the eastern Chukchi Sea. Survey lines were focused mainly on the coastal zone within 37 km of the shoreline, with additional lines flown 148–185 km offshore to assess how densities of seals changed as a function of distance from shore. Satellite-linked time-depth recorders were attached to ringed seals in both years to evaluate the time spent basking on the ice surface. Haulout patterns indicated that ringed seals transitioned to basking behavior in late May and early June, and that the largest proportion of seals (60–68%) was hauled out between 0830 and 1530 local solar time. Ringed seals were relatively common in nearshore fast ice and pack ice, with lower densities in offshore pack ice. The average density of ringed seals was 1.91 seals km-2 in 1999 (range 0.37– 16.32) and 1.62 seals km-2 in 2000 (range 0.42–19.4), with the highest densities of ringed seals found in coastal waters south of Kivalina and near Kotzebue Sound. The estimated abundance of ringed seals for the entire study area was similar in 1999 (252,488 seals, SE=47,204) and 2000 (208,857 seals, SE=25,502). Bearded seals were generally more common in offshore pack ice, with the exception of high bearded seal numbers observed near the shore south of Kivalina. Bearded seal densities were not adjusted for haulout behavior, and therefore, abundance was not estimated. Unadjusted average bearded seal density was 0.07 seals km-2 in 1999 (range 0.011–0.393) and 0.14 seals km-2 in 2000 (range 0.009– 0.652). Levels of primary productivity, benthic biomass, and fast ice distribution may influence the distributions of ringed and bearded seals in the Chukchi Sea. Information on movement and haulout behavior of ringed and bearded seals would be very useful for designing future surveys.

Monitoring the Prey-Field of Marine Predators: Combining Digital Imaging With Datalogging Tags

There is increasing interest in the diving behavior of marine mammals. However, identifying foraging among recorded dives often requires several assumptions. The simultaneous acquisition of images of the prey encountered, together with records of diving behavior will allow researchers to more fully investigate the nature of subsurface behavior. We tested a novel digital camera linked to a time-depth recorder on Antarctic fur seals (Arctocephalus gazella). During the austral summer 2000-2001, this system was deployed on six lactating female fur seals at Bird Island, South Georgia, each for a single foraging trip. The camera was triggered at depths greater than 10 m. Five deployments recorded still images (640 x 480 pixels) at 3-sec intervals (total 8,288 images), the other recorded movie images at 0.2-sec intervals (total 7,598 frames). Memory limitation (64 MB) restricted sampling to approximately 1.5 d of 5-7 d foraging trips. An average of 8.5% of still pictures (2.4%-11.6%) showed krill (Euphausia superba) distinctly, while at least half the images in each deployment were empty, the remainder containing blurred or indistinct prey. In one deployment krill images were recorded within 2.5 h (16 km, assuming 1.8 m/sec travel speed) of leaving the beach. Five of the six deployments also showed other fur seals foraging in conjunction with the study animal. This system is likely to generate exciting new avenues for interpretation of diving behavior.

Modeling Age-Specific Mortality For Marine Mammal Populations

A method is presented for estimating age-specific mortality based on minimal information: a model life table and an estimate of longevity. This approach uses expected patterns of mammalian survivorship to define a general model of age-specific mortality rates. One such model life table is based on data for northern fur seals (Callorhinus ursinus) using Siler’s (1979) 5-parameter competing risk model. Alternative model life tables are based on historical data for human females and on a published model for Old World monkeys. Survival rates for a marine mammal species are then calculated by scaling these models by the longevity of that species. By using a realistic model (instead of assuming constant mortality), one can see more easily the real biological limits to population growth. The mortality estimation procedure is illustrated with examples of spotted dolphins (Stenella attenuata) and harbor porpoise (Phocoena phocoena).

Taking account of dependent species in management of the Southern Ocean krill fishery: estimating crabeater seal abundance off east Antarctica

1. The crabeater seal Lobodon carcinophaga is considered to be a key species in the krill-based food web of the Southern Ocean. Reliable estimates of the abundance of this species are necessary to allow the development of multispecies, predator–prey models as a basis for management of the krill fishery in the Southern Ocean. 2. A survey of crabeater seal abundance was undertaken in 1500 000 km2 of pack-ice off east Antarctica between longitudes 64–150° E during the austral summer of 1999/2000. Sighting surveys, using double observer line transect methods, were conducted from an icebreaker and two helicopters to estimate the density of seals hauled out on the ice in survey strips. Satellite-linked dive recorders were deployed on a sample of seals to estimate the probability of seals being hauled out on the ice at the times of day when sighting surveys were conducted. Model-based inference, involving fitting a density surface, was used to infer densities in the entire survey region from estimates in the surveyed areas. 3. Crabeater seal abundance was estimated to be between 0.7 and 1.4 million animals (with 95% confidence), with the most likely estimate slightly less than 1 million. 4. Synthesis and applications. The estimation of crabeater seal abundance in Convention for the Conservation of Antarctic Marine Living Resources (CCAMLR) management areas off east Antarctic where krill biomass has also been estimated recently provides the data necessary to begin extending from single-species to multispecies management of the krill fishery. Incorporation of all major sources of uncertainty allows a precautionary interpretation of crabeater abundance and demand for krill in keeping with CCAMLR’s precautionary approach to management. While this study focuses on the crabeater seal and management of living resources in the Southern Ocean, it has also led to technical and theoretical developments in survey methodology that have widespread potential application in ecological and resource management studies, and will contribute to a more fundamental understanding of the structure and function of the Southern Ocean ecosystem.

Killer Whales and Marine Mammal Trends in The North Pacific—A Re-Examination of Evidence for Sequential Megafauna Collapse and the Prey-Switching Hypothesis

Springer et al. (2003) contend that sequential declines occurred in North Pacific populations of harbor and fur seals, Steller sea lions, and sea otters. They hypothesize that these were due to increased predation by killer whales, when industrial whaling’s removal of large whales as a supposed primary food source precipitated a prey switch. Using a regional approach, we reexamined whale catch data, killer whale predation observations, and the current biomass and trends of potential prey, and found little support for the prey-switching hypothesis. Large whale biomass in the Bering Sea did not decline as much as suggested by Springer et al., and much of the reduction occurred 50–100 yr ago, well before the declines of pinnipeds and sea otters began; thus, the need to switch prey starting in the 1970s is doubtful. With the sole exception that the sea otter decline followed the decline of pinnipeds, the reported declines were not in fact sequential. Given this, it is unlikely that a sequential megafaunal collapse from whales to sea otters occurred. The spatial and temporal patterns of pinniped and sea otter population trends are more complex than Springer et al. suggest, and are often inconsistent with their hypothesis. Populations remained stable or increased in many areas, despite extensive historical whaling and high killer whale abundance. Furthermore, observed killer whale predation has largely involved pinnipeds and small cetaceans; there is little evidence that large whales were ever a major prey item in high latitudes. Small cetaceans (ignored by Springer et al.) were likely abundant throughout the period. Overall, we suggest that the Springer et al. hypothesis represents a misleading and simplistic view of events and trophic relationships within this complex marine ecosystem.