Summary. We propose a general framework for the analysis of animal telemetry data through the use of weighted distributions. It is shown that several interpretations of resource selection functions arise when constructed from the ratio of a use and availability distribution. Through the proposed general framework, several popular resource selection models are shown to be special cases of the general model by making assumptions about animal movement and behavior. The weighted distribution framework is shown to be easily extended to readily account for telemetry data that are highly autocorrelated; as is typical with use of new technology such as global positioning systems animal relocations. An analysis of simulated data using several models constructed within the proposed framework is also presented to illustrate the possible gains from the flexible modeling framework. The proposed model is applied to a brown bear data set from southeast Alaska.

The purposes of this study were (a) to develop a test of complex song appraisal that would be suitable for use with adults who use a cochlear implant (assistive hearing device) and (b) to compare the appraisal ratings (liking) of complex songs by adults who use cochlear implants (n = 66) with a comparison group of adults with normal hearing (n = 36). The article describes the development of a computerized test for appraisal, with emphasis on its theoretical basis and the process for item selection of naturalistic stimuli. The appraisal test was administered to the 2 groups to determine the effects of prior song familiarity and subjective complexity on complex song appraisal. Comparison of the 2 groups indicates that the implant users rate 2 of 3 musical genres (country western, pop) as significantly more complex than do normal hearing adults, and give significantly less positive ratings to classical music than do normal hearing adults. Appraisal responses of implant recipients were examined in relation to hearing history, age, performance on speech perception and cognitive tests, and musical background.

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).

Distance sampling is a widely used method to estimate animal population size. Most distance sampling models utilize a monotonically decreasing detection function such as a half-normal. Recent advances in distance sampling modeling allow for the incorporation of covariates into the distance model, and the elimination of the assumption of perfect detection at some fixed distance (usually the transect line) with the use of double-observer models. The assumption of full observer independence in the double-observer model is problematic, but can be addressed by using the point independence assumption which assumes there is one distance, the apex of the detection function, where the 2 observers are assumed independent. Aerially collected distance sampling data can have a unimodal shape and have been successfully modeled with a gamma detection function. Covariates in gamma detection models cause the apex of detection to shift depending upon covariate levels, making this model incompatible with the point independence assumption when using double-observer data. This paper reports a unimodal detection model based on a two-piece normal distribution that allows covariates, has only one apex, and is consistent with the point independence assumption when double-observer data are utilized. An aerial line-transect survey of black bears in Alaska illustrate how this method can be applied.

This paper describes the listening habits and musical enjoyment of postlingually deafened adults who use cochlear implants. Sixty-five implant recipients (35 females, 30 males) participated in a survey containing questions about musical background, prior involvement in music, and audiologic success with the implant in various listening circumstances. Responses were correlated with measures of cognition and speech recognition. Sixty-seven implant recipients completed daily diaries (7 consecutive days) in which they reported hours spent in specific music activities. Results indicate a wide range of success with music. In general, people enjoy music less postimplantation than prior to hearing loss. Musical enjoyment is influenced by the listening environment (e.g., a quiet room) and features of the music. Abbreviations: HIGH = high school, POST = adult education, PRIM = primary school, SCT = Sequence Completion Test, SE = standard error, TERT = tertiary, VMT = Visual Monitoring Task, VMT1 = Visual Monitoring Task one per second rate, VMT2 = Visual Monitoring Task two per second rate.