Nest success is an important parameter affecting population fluctuations of wild turkeys (Meleagris gallopavo). Factors influencing mammalian predation on turkey nests are complicated and not well understood. Therefore, we assessed nest hazard risk by testing competing hypotheses of Merriam's turkey (M. g. merriami) nest survival in a ponderosa pine (Pinus ponderosa) ecosystem during 2001–2003. We collected nesting information on 83 female Merriam's turkeys; annual nest success averaged 50% for adult females (range = 45–59%) and 83% for yearling females (range = 75–100%). Proportional hazard modeling indicated that precipitation increased the hazard of nest mortality. However, estimated hazard of nest predation was lowered when incubating females had greater shrub cover and visual obstruction around nests. Coyotes (Canis latrans) were the primary predator on turkey nests. We hypothesize that precipitation is the best predictor of nest survival for first nests because coyotes use olfaction effectively to find nesting females during wet periods. Temporally, as the nesting season progressed, precipitation declined and vegetation cover increased and coyotes may have more difficulty detecting nests under these conditions later in the nesting period. The interaction of concealment cover with precipitation indicated that nest hazard risk from daily precipitation was reduced with greater shrub cover. Management activities that promote greater shrub cover may partially offset the negative effects of greater precipitation events.

Wildfire and mountain pine beetle infestations are naturally occurring disturbances in western North American forests. Black-backed woodpeckers (Picoides arcticus) are emblematic of the role these disturbances play in creating wildlife habitat, since they are strongly associated with recently-killed forests. However, management practices aimed at reducing the economic impact of natural disturbances can result in habitat loss for this species. Although black-backed woodpeckers occupy habitats created by wildfire, prescribed fire, and mountain pine beetle infestations, the relative value of these habitats remains unknown. We studied habitat-specific adult and juvenile survival probabilities and reproductive rates between April 2008 and August 2012 in the Black Hills, South Dakota. We estimated habitat-specific adult and juvenile survival probability with Bayesian multi-state models and habitat-specific reproductive success with Bayesian nest survival models. We calculated asymptotic population growth rates from estimated demographic rates with matrix projection models. Adult and juvenile survival and nest success were highest in habitat created by summer wildfire, intermediate in MPB infestations, and lowest in habitat created by fall prescribed fire. Mean posterior distributions of population growth rates indicated growing populations in habitat created by summer wildfire and declining populations in fall prescribed fire and mountain pine beetle infestations. Our finding that population growth rates were positive only in habitat created by summer wildfire underscores the need to maintain early post-wildfire habitat across the landscape. The lower growth rates in fall prescribed fire and MPB infestations may be attributed to differences in predator communities and food resources relative to summer wildfire.

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Summary 1.A common sampling design in resource selection studies involves measuring resource attributes at sample units used by an animal and at sample units considered available for use. Few models can estimate the absolute probability of using a sample unit from such data, but such approaches are generally preferred over statistical methods that estimate a relative probability of use. 2. The case-control model that allows for contaminated controls, proposed by Lancaster & Imbens (1996) and Lele (2009), can estimate the absolute probability of using a sample unit from use-availability data. However, numerous misconceptions have likely prevented the widespread application of this model to resource selection studies. We address common misconceptions regarding the case-control model with contaminated controls and demonstrate its ability to estimate the absolute probability of use, prevalence and parameters associated with categorical covariates from use-availability data. 3. We fit the case-control model with contaminated controls to simulated data with varying prevalence (defined as the average probability of use across all sample units) and sample sizes (n 1 = 500 used and n a = 500 available samples; n 1 = 1000 used and n a = 1000 available samples). We then applied this model to estimate the probability Ozark hellbenders (Cryptobranchus alleganiensis bishopi) would use a location within a stream as a function of covariates. 4. The case-control model with contaminated controls provided unbiased estimates of all parameters at N = 2000 sample size simulation scenarios, particularly at low prevalence. However, this model produced increasingly variable maximum likelihood estimates of parameters as prevalence increased, particularly at N = 1000 sample size scenarios. We thus recommend at least 500-1000 used samples when fitting the case-control model with contaminated controls to use-availability data. Our application to hellbender data revealed selection for locations with coarse substrate that are close to potential sources of cover. 5. This study unites a disparate literature, addresses and clarifies many commonly held misconceptions and demonstrates that the case-control model with contaminated controls is a viable alternative for estimating the absolute probability of use from use-availability data.