Resource metrics used to assess resource use of white-tailed deer (<i>Odocoileus virginianus</i>) fawns, Upper Peninsula of Michigan, USA, 2009–2011.

<p>Resource metrics used to assess resource use of white-tailed deer (<i>Odocoileus virginianus</i>) fawns, Upper Peninsula of Michigan, USA, 2009–2011.</p

Spatially-predicted probability of resource use, composite predation risk, and non-ideal resource use for white-tailed deer fawns (<i>Odocoileus virginianus</i>; ≤14 weeks old; <i>n</i> = 129) captured as neonates during the post-partum period (25 May–31 August), Upper Peninsula of Michigan, USA, 2009–2011.

<p>Composite predation risk was estimated from the summed probability of resource selection of bobcats (<i>Lynx rufus</i>), American black bears (<i>Ursus americanus</i>), coyotes (<i>Canis latrans</i>), and gray wolves (<i>C. lupus</i>).</p

Generalized linear mixed-effect models assessing third order resource selection of white-tailed deer fawns (≤14 weeks of age; <i>Odocoileus virginianus</i>; <i>n</i> = 129) during the post-partum period (14 May–31 Aug), Upper Peninsula of Michigan, USA, 2009–2011.

<p>Models used radiolocations (1; <i>n</i> = 2713) and random points (0) as the binomial response variable and individual resources were used as a fixed effect with individual fawn and year as random effects on the intercept. Model prediction error was estimated using <i>k</i>-fold cross validation using 5 folds.</p

Location (black polygon) of white-tailed deer (<i>Odocoileus virginianus</i>) resource use and predation risk study, Upper Peninsula of Michigan, USA, 2009–2011.

<p>Location (black polygon) of white-tailed deer (<i>Odocoileus virginianus</i>) resource use and predation risk study, Upper Peninsula of Michigan, USA, 2009–2011.</p

Cox-proportional hazards mixed-effects models assessing the effects of resource use, predation risk, birth body mass, winter severity, and vegetation hiding cover on the daily survival of white-tailed deer fawns (≤14 weeks of age; <i>Odocoileus virginianus</i>; <i>n</i> = 129) during the post-partum period (14 May–31 Aug), Upper Peninsula of Michigan, USA, 2009–2011.

<p>Models included individual fawn and year as random effects on the intercept. Models presented with standardized parameter estimates, standard errors (SE), probability values, degrees of freedom (<i>df</i>), and estimated hazard ratio parameter probability values, and percent integrated deviance explained indicating the reduction in the log-likelihood from the null model. Percent deviance explained was used to rank models. Model fit was assessed using a Chi-square test of log-likelihood of a given model (Log-likelihood <i>X</i>²) compared to the null model.</p

Comparison of best performing models explaining trends in wolf depredation on bear-hunting dogs in the Wisconsin and Michigan, USA, by Akaike’s information criterion & weight.

*<p>Encounter = the ratio of bear hunting permits sold per wolf (see methods). Numbers in parenthesis under explanatory factors are <i>p</i>-values for the five best-performing models.</p>a<p>AIC_C is Akaike’s information criterion, corrected for small sample size.</p>b<p>ΔAIC_C is AIC_C for the model of interest minus the smallest AIC_C for the set of models being considered. We only considered models with ΔAIC_C ≤2.</p>c<p>W is the Akaike’s weight of each model. The ratio of one model’s weight to another estimates how many times more support the data provide for that model over the other.</p

Wolf conflict and the duration of bear-baiting in the upper Great Lakes region, USA.

<p>Predicted probability of a wolf depredation on bear-hunting dogs (<i>y-axis</i>) versus the number of days since training with bait began (<i>x-axis</i>) in Wisconsin (<i>upper line</i>) and Michigan (<i>lower line</i>). Each point represents a day since training with bait began in Wisconsin (<i>closed symbols</i>) and Michigan (<i>open symbols</i>). Note that open symbols for Michigan are offset from (0) and (1) probability so as to not overlap symbols for Wisconsin. The odds of a depredation event occurring in Wisconsin were 3.57× greater than the odds in Michigan; a relative depredation risk 2.12–7.22× greater in Wisconsin.</p

Logistic regression analysis of the probability of wolf depredation on hunting dogs in relation to time since training with bait in Wisconsin and Michigan, USA.

<p><i>Note</i>. NA = not applicable.</p

Bobcat occupancy probability (and corresponding standard deviations) (A & B) and snowshoe hare occupancy (and corresponding standard deviations) (C & D) averaged over weeks for each cell, Upper Peninsula Michigan, December 2012–February 2013.

<p>Roads and streams are represented by grey and blue lines, respectively.</p

Bobcat occupancy probability when snowshoe hare are present (A) and absent (B), Upper Peninsula Michigan, December 2012–February 2013.

<p>Roads and streams are represented by grey and blue lines, respectively.</p