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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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