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Steller sea lions (SSL; Eumetopias jubatus) grow their vibrissae continually, providing a multiyear record suitable for ecological and physiological studies based on stable isotopes. An accurate age‐specific vibrissae growth rate is essential for registering a chronology along the length of the record, and for interpreting the timing of ecologically important events. We utilized four methods to estimate the growth rate of vibrissae in fetal, rookery pup, young‐of‐the‐year (YOY), yearling, subadult, and adult SSL. The majority of vibrissae were collected from SSL live‐captured in Alaska and Russia between 2000 and 2013 (n = 1,115), however, vibrissae were also collected from six adult SSL found dead on haul‐outs and rookeries during field excursions to increase the sample size of this underrepresented age group. Growth rates of vibrissae were generally slower in adult (0.44 ± 0.15 cm/mo) and subadult (0.61 ± 0.10 cm/mo) SSL than in YOY (0.87 ± 0.28 cm/mo) and fetal (0.73 ± 0.05 cm/mo) animals, but there was high individual variability in these growth rates within each age group. Some variability in vibrissae growth rates was attributed to the somatic growth rate of YOY sea lions between capture events (P = 0.014, r2 = 0.206, n = 29).

A technique was developed to estimate morphometrics and body mass of Steller sea lions (Eumetopias jubatus) using three-dimensional (3D) photogrammetry. 3D photogrammetry reduces many of the problems associated with camera and body position encountered with two-dimensional photogrammetric techniques, allowing body mass estimation of free-ranging, active sea lions, without sedation, heavy weighing equipment, and disturbance. 3D computer wireframes of 53 Steller sea lions of various age classes were generated from multiple time-synchronous digital photos and used to estimate length, girth, and volume. Average estimates of standard length and axillary girth were within ±2.5% and ±4.0% of physically measured dimensions, respectively. Average estimates of standard length and axillary girth using only wireframes based on ideal body postures were within ±1.7% and ±3.1% of physically measured dimensions, respectively. Regressions of physically measured mass on photogrammetrically estimated body volume yielded a predictive model. Body mass estimates using this model were on average within 9.0% (95% confidence interval = ±1.7%) of the physically measured mass. This technique was also successfully applied to reptiles and fish.

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During the breeding seasons of 2000-2003 we collected 1,724 scats from seven rookeries and eighteen haul-outs on the Kamchatka Peninsula and in the Kuril Islands, Okhotsk Sea, and Commander Islands to analyze the diet of Steller sea lions (Eumetopias jubatus) in the Russian Far-East. The most frequently encountered prey items in all scats combined were Atka mackerel (Pleurogrammus monopterygius), walleye pollock (Theragra chalcogramma), salmon (Oncorhynchus sp.), sculpins (Cottidae), cephalopods, Pacific sand lance (Ammodytes hexapterus), Pacific herring (Clupea pallasii), Northern smoothtongue (Leuroglossus stilbius), snailfish (Liparidae), and Pacific cod (Gadus macrocephalus). Spatial differences were analyzed by comparing frequency of occurrence (FO) values on a site-by-site basis for each year and all years combined. Breeding-season collection sites were grouped into seven geographic regions based on FO similarities using cluster analysis. Diet diversity was calculated for each of these geographic regions. No significant relationship was found between diet diversity and population trend (P = 0.886). Significant differences in diet composition were found between geographic regions (P < 0.001 for all regions). Significant seasonal differences were also detected at two haul-outs on the Kamchatka Peninsula from which an additional 93 scats were collected during the fall molt (P < 0.001 for both locations).

Estimating population abundance of wolves (Canis lupus) in densely forested landscapes is challenging because reduced visibility lowers the success of methods such as aerial surveys and enumeration of group size using radiotelemetry. However, regular population estimates of wolves are necessary for population monitoring and sustainable management. We used noninvasive hair snaring and spatially explicit capture-recapture (SECR) to estimate wolf abundance on Prince of Wales Island (POW), Alaska, USA, during 2012-2015. We monitored 36-82 hair-snare stations weekly for 9-11 weeks during autumn. The noninvasive study area covered 1,683 km 2 during 2012-2013 and was expanded to 3,281 km 2 during 2014-2015. We identified 57 individual wolves during the study period using DNA from hair follicles genotyped at 10 microsatellite loci. We used population density estimates using SECR (2013: 24.5 wolves/1,000 km 2 [95% CI ¼ 14.4-41.9 wolves/1,000 km 2 ], 2014: 9.9 wolves/1,000 km 2 [95% CI ¼ 5.5-17.7/1,000 km 2 ], 2015: 11.9 wolves/1,000 km 2 [95% CI ¼ 7.7-18.5 wolves/1,000 km 2 ]) to predict the autumn population for the POW management unit (2013: 221.1 wolves [95% CI ¼ 130-378]; 2014: 89.1 wolves [95% CI ¼ 49.8-159.4]; 2015: 107.5 wolves [95% CI ¼ 69-167]). We detected and redetected more wolves and increased the precision of the density estimate after increasing the hair sampling intensity and sampling area in 2014-2015.Our results demonstrate that estimating wolf abundance using noninvasive sampling and SECR was feasible and reliably applied producing a statistically robust population estimate for monitoring wolf populations in densely forested areas. These methods have promise for application to widely ranging carnivores at population-level scales and may be especially useful when regular density estimates are necessary for management and conservation. Ó

Approximately 1 000 Steller sea lions ( Eumetopias jubatus (Schreber, 1776); SSL) and 14 000 northern fur seals ( Callorhinus ursinus (L., 1758); NFS) breed sympatrically on Lovushki Island in the Russian Far East, creating the potential for interspecific competition for prey. An additional 13 000 – 14 000 juvenile NFS are present during the breeding season. The diets of breeding SSL and both breeding and juvenile NFS were examined through analysis of scats and spews collected during the breeding seasons of 2003, 2005, and 2007–2008. There were significant overlaps in the prey species and size selection of SSL and juvenile NFS. There were significant differences between the diets of SSL and breeding NFS. SSL and juvenile NFS fed primarily on Atka mackerel ( Pleurogrammus monopterygius (Pallas, 1810)), while breeding NFS fed on cephalopods, salmon (genus Oncorhynchus Suckley, 1861), Atka mackerel, and northern smoothtongue ( Leuroglossus schmidti Rass, 1955). The partitioning of resources between breeding animals has allowed both species to coexist within the same region and likely reflected differences in foraging abilities and provisioning strategies of the adults and the fasting abilities of their pups. However, continued growth of the NFS population may lead to the exclusion of SSL owing to interspecific competition for prey.

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