Table 4.

Lists estimated $\mathrm{\beta }$‐parameters and supporting evidence for the variables included cumulative effects wolverine distribution model. Evidence ratios (ER) describe the relative likelihood of support for inclusion of one variable (or a group of variables) compared to the exclusion of the variable(s) in a global model (Burham and Anderson 1998). Example: The ER for the set of landcover variables shows 19 times more support in explaining wolverine‐habitat selection relative to other set(s) of variables

Parameter	Estimate	SE	z‐value	Pr (z)	ER
Intercept	−1.218	0.381	−3.201	0.001
DENSE	0.605	0.200	3.023	0.002
MIXED	−0.929	0.450	−2.062	0.039
SHRUB	0.338	0.120	2.811	0.005
HERB	0.363	0.230	1.579	0.114
REGEN	−0.003	0.507	−0.005	0.996
SNOW.ICE	0.048	0.026	1.842	0.065	19.00
BLOCKURB	0.002	0.112	0.022	0.983
LINRECL	1.056	0.653	1.617	0.106
LININD	−1.243	0.648	−1.919	0.055	6.33
SP.SNOW	0.409	0.320	1.279	0.201	0.86
RED FOX	−0.170	0.162	−1.051	0.293
COYOTE	−0.306	0.297	−1.030	0.303	0.35