6 | TABLES AND FIGURES
Table 1. Model results from linear regression modelling explaining
variation in δ 13C values in brown bear hair
from south-central Sweden 1995-2020 (n = 669). We tested for linear
patterns as well as log-linear (ln) relationships between response and
explanatory variables. We also tested whether stable isotope values
responded to food availability in the same year hair was grown, or to
food availability in the year prior, i.e., with a 1-year time lag;
(lagged), bur the time lag was no supported inδ 13C values (Table S2). Explanatory variables
included an annual index of bilberry production (Bilberry), annual
number of moose (Alces alces ) calves produced based on hunter
observations after accounting for observation effort (Calf), the annual
number of moose harvested, and bear age and sex. We used the difference
in AICc scores (ΔAICc ) and
model weights (wi ) to determine the most
parsimonious model. Beta estimates (\(\widehat{\beta}\)) and 95%
confidence intervals (LCI, UCI) are provided for each explanatory
variable in competitive models.