A simple difference equation model was used to provide a perspective on demographic changes in a Columbian black-tailed deer (Odocoileus hemionus columbianus) population prior to and during wolf (Canis lupus) control on northern Vancouver Island. The model reconstructed spring (pre-fawning) deer numbers and adult survival rates from an annual abundance index, the proportion of the population consisting of juveniles 10–11 months of age, and hunter harvest. The actual (λ) and potential (λp, in the absence of hunting) rates of deer population change, adult nonhunting survival (Sn), adult hunting mortality (Mh) and recruitment (R) rates were estimated for three growth periods: (1) predecline (1970–1976), wolf numbers low but increasing, λ = 1.02, λp = 1.13, Sn = 0.90, Mh = 0.09, R = 0.22; (2) decline (1976–1983), wolves abundant, λ = 0.81, λp = 0.85, Sn = 0.76, Mh = 0.05, R = 0.09; and (3) recovery (1983–1990), wolves reduced, λ = 1.17, λp = 1.24, Sn = 0.94, Mh = 0.03, R = 0.23. The recruitment (Rs) required to balance adult mortality (λ = 1.00) was ~16%. Sensitivity analyses using plausible extremes in demographic rates suggested that changes in juvenile survival had the greatest impact on recruitment. Rate of population change appeared to be most sensitive to juvenile survival and adult nonhunting survival.

The sustainability of the grizzly bear (Ursus arctos) hunt in British Columbia, Canada has been questioned and is a high profile issue, particularly in the media. To investigate the hypothesis that the hunt is unsustainable, we examined the sustainable human‐caused mortality rate for grizzly bears using recent data on vital rates and population projection models and compare these to rates used by the management agency; examined the age and sex ratio of the kill and how the sex ratio changes with age for the entire province, each population unit, and cohorts born each year between 1977 and 1990; summarized population density estimates in hunted population units in British Columbia and compared these to unhunted areas in adjacent jurisdictions; and reviewed case studies of population units that have been highlighted as most likely to have had unsustainable kill levels. Because the natural mortality rate of adult grizzly bears is 1–2% and lower than was estimated when sustainable human‐caused mortality targets were developed, estimated sustainable kill rates are 4–10%, and generally higher than the 4–6% used in British Columbia. We estimated that males have been 3–4 times more vulnerable to being killed by hunters than females, yet males dominate the kill at all ages and the proportion of males increased with age, which is opposite of what is predicted for a heavily hunted population. The average age of female and male grizzly bears killed by hunters increased from 7.1 years and 7.4 years, respectively, in the 1980s to 7.7 years and 8.7 years, respectively, in the 2000s. An average of 107.4 females and 204.9 males per cohort born between 1977 and 1990 were eventually killed by people and recorded, suggesting that many more females than males died for unknown reasons. There have been more population inventories of grizzly bears in British Columbia than in any other jurisdiction. The average density estimate of 21 inventories in hunted areas without salmon (Oncorhynchus spp.) in British Columbia (31.2 bears/1,000 km2) was as high as or higher than nearby unhunted areas. The case studies had the highest kill densities or among the highest kill rates in the province and hunting targets were commonly exceeded and seasons closed or the hunter kill target reduced. Although population inventories in these areas found moderate or even high densities of bears, some are now in decline. Hunter kill data from declining populations had a high proportion of males and these were older, demonstrating that these indices of kill rates are sometimes unreliable. Although more population density, trend, and vital rate measurements would be beneficial, the hypothesis that the grizzly bear hunt has been unsustainable was not supported by our investigation of available information. © 2016 The Wildlife Society.

Management of wolves (Canis lupus) in British Columbia, as with most other Canadian provinces, is conducted on a regional scale (38,776 km 2 ), yet there is no standardized, cost-effective methodology for providing reliable estimates of wolf abundance at this scale. Therefore, we used periodic estimates of ungulate abundance and incorporated them into an ungulate biomass regression model to estimate wolf abundance on a regional and provincial (900,402 km 2 ) scale over a 12-year period (2000-2011). In 2011, the provincial estimate was 8,688 (95% CI ¼ 5,898-11,760) wolves (7-13 wolves/1,000 km 2 ), while regional wolf abundance estimates ranged from 149 (95% CI ¼ 100-205) to 2,693 (95% CI ¼ 1,818-3,608) with differences related to regional scale (km 2 ) rather than wolf densities (4-15 wolves/1,000 km 2 ). We suggest the ungulate biomass regression model is useful to estimate the abundance of wolves for management purposes when precise estimates are not required and wolf populations are not heavily exploited or recovering.

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We used an integrated Bayesian state‐space population model to assess whether management objectives were met before (1995–2003), during (2004–2010), and after (2011–2013) antlerless permits to harvest mule deer (Odocoileus hemionus) were increased in response to stakeholder concerns in central British Columbia, Canada. Data inputs included 19 years of harvest data, 7 years of autumn age–sex composition data, 17 years of spring age–sex composition data, and 15 years of a population index. Management objectives were to maintain a spring population of 7,000–9,000 deer and a posthunt adult sex ratio of 20–30 males:100 females. An 8.5‐fold increase in antlerless permits raised the antlerless harvest rates from 1.0% (1995–2003) to 4.8% (2004–2010). Antlerless harvest rates decreased to 2.8% following a 53% decrease in permits from 2011 to 2013. Population projections from 2014 to 2018 fell within the bounds of the management objectives, but 95% credibility intervals revealed great uncertainty in population size and composition. We recommend a structured, adaptive approach to mule deer management that includes annual adjustment of harvests, monitoring, and modeling, with an open‐ended stakeholder engagement process to ensure objectives remain relevant, measurable, and achievable. © 2017 The Wildlife Society.