  This work proposes an adjacent-category autoregressive model for time series
of ordinal variables. We apply this model to dendrochronological records to
study the effect of climate on the intensity of spruce budworm defoliation
during outbreaks in two sites in eastern Canada. The model's parameters are
estimated using the maximum likelihood approach. We show that this estimator is
consistent and asymptotically Gaussian distributed. We also propose a
Portemanteau test for goodness-of-fit. Our study shows that the seasonal ranges
of maximum daily temperatures in the spring and summer have a significant
quadratic effect on defoliation. The study reveals that for both regions, a
greater range of summer daily maximum temperatures is associated with lower
levels of defoliation up to a threshold estimated at 22.7C (CI of 0-39.7C at
95%) in T\'emiscamingue and 21.8C (CI of 0-54.2C at 95%) for Matawinie. For
Matawinie, a greater range in spring daily maximum temperatures increased
defoliation, up to a threshold of 32.5C (CI of 0-80.0C). We also present a
statistical test to compare the autoregressive parameter values between
different fits of the model, which allows us to detect changes in the
defoliation dynamics between the study sites in terms of their respective
autoregression structures.
