In many practical applications snow depth is known, but snow water equivalent (SWE) is needed as well. Measuring SWE takes ;20 times as long as measuring depth, which in part is why depth measurements outnumber SWE measurements worldwide. Here a method of estimating snow bulk density is presented and then used to convert snow depth to SWE. The method is grounded in the fact that depth varies over a range that is many times greater than that of bulk density. Consequently, estimates derived from measured depths and modeled densities generally fall close to measured values of SWE. Knowledge of snow climate classes is used to improve the accuracy of the estimation procedure. A statistical model based on a Bayesian analysis of a set of 25 688 depth-density-SWE data collected in the United States, Canada, and Switzerland takes snow depth, day of the year, and the climate class of snow at a selected location from which it produces a local bulk density estimate. When converted to SWE and tested against two continental-scale datasets, 90% of the computed SWE values fell within 68 cm of the measured values, with most estimates falling much closer.

We studied moose (Alces alces) survival, physical condition, and abundance in a 3-predator system in western Interior Alaska, USA, during 2001USA, during -2007 Our objective was to quantify the effects of predator treatments on moose population dynamics by investigating changes in survival while evaluating the contribution of potentially confounding covariates. In May 2003 and 2004, we reduced black bear (Ursus americanus) and brown bear (U. arctos) numbers by translocating bears !240 km from the study area. Aircraft-assisted take reduced wolf (Canis lupus) numbers markedly in the study area during 2004-2007. We estimated black bears were reduced by approximately 96% by June 2004 and recovered to within 27% of untreated numbers by May 2007. Brown bears were reduced approximately 50% by June 2004. Late-winter wolf numbers were reduced by 75% by 2005 and likely remained at these levels through 2007. In addition to predator treatments, moose hunting closures during 2004-2007 reduced harvests of male moose by 60% in the study area. Predator treatments resulted in increased calf survival rates during summer (primarily from reduced black bear predation) and autumn (primarily from reduced wolf predation). Predator treatments had little influence on survival of moose calves during winter; instead, calf survival was influenced by snow depth and possibly temperature. Increased survival of moose calves during summer and autumn combined with relatively constant winter survival in most years led to a corresponding increase in annual survival of calves following predator treatments. Nonpredation mortalities of calves increased following predator treatments; however, this increase provided little compensation to the decrease in predation mortalities resulting from treatments. Thus, predator-induced calf mortality was primarily additive. Summer survival of moose calves was positively related to calf mass (b > 0.07, SE ¼ 0.073) during treated years and lower (b ¼ À0.82, SE ¼ 0.247) for twins than singletons during all years. Following predator treatments, survival of yearling moose increased 8.7% for females and 21.4% for males during summer and 2.2% for females and 15.6% for males during autumn. Annual survival of adult (!2 yr old) female moose also increased in treated years and was negatively (b ¼ À0.21, SE ¼ 0.078) related to age. Moose density increased 45%, from 0.38 moose/ km 2 in 2001 to 0.55 moose/km 2 in 2007, which resulted from annual increases in overall survival of moose, not increases in reproductive rates. Indices of nutritional status remained constant throughout our study despite increased moose density. This information can be used by wildlife managers and policymakers to better understand the outcomes of predator treatments in Alaska and similar environments. ß 2011 The Wildlife Society.

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Studies of predator feeding ecology commonly focus on energy intake. However, captive predators have been documented to selectively feed to optimize macronutrient intake. As many apex predators experience environmental changes that affect prey availability, limitations on selective feeding can affect energetics and health. We estimated the protein:fat ratio of diets consumed by wild polar bears using a novel isotope-based approach, measured protein:fat ratios selected by zoo polar bears offered dietary choice and examined potential energetic and health consequences of overconsuming protein. Dietary protein levels selected by wild and zoo polar bears were low and similar to selection observed in omnivorous brown bears, which reduced energy intake requirements by 70% compared with lean meat diets. Higher-protein diets fed to zoo polar bears during normal care were concurrent with high rates of mortality from kidney disease and liver cancer. Our results suggest that polar bears have low protein requirements and that limitations on selective consumption of marine mammal blubber consequent to climate change could meaningfully increase their energetic costs. Although bear protein requirements appear lower than those of other carnivores, the energetic and health consequences of protein overconsumption identified in this study have the potential to affect a wide range of taxa.

We report on a method of visually classifying Pacific walruses (Odobenus rosmarus) to sex and age class with the goal of estimating calf:cow ratios. Development of this method began in 1958 by Dr. F. H. Fay and was used during six surveys in the Chukchi Sea between 1981 and 1999. We estimate calf:cow ratios using beta‐binomial models to allow for overdispersion and use Monte Carlo simulations to assess the reliability of prior surveys and quantify sample sizes required for future surveys. Calf:cow ratios did not vary by region, date, or by the number of cows in a group. However, higher ratios were observed in the morning and evening than during the day, indicating haul out behavior of cows varies by reproductive status. Adjusted for solar noon, few calves were observed in 1981 (3:100), 1984 (6:100), and 1998 (5:100), while substantially more were observed in 1982 (15:100) and 1999 (13:100). Classifying between 200 and 300 groups with cows (~1,600–2,300 individual cows) will yield calf:cow ratios with ~20%–30% relative precision. Tagging studies that examine hauling‐out behavior of cows with and without calves relative to time‐of‐day are necessary to better understand how to interpret calf:cow ratios.

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