Modeling dragonfly population data with a Bayesian bivariate geometric mixed-effects model.

We develop a generalized linear mixed model (GLMM) for bivariate count responses for statistically analyzing dragonfly population data from the Northern Netherlands. The populations of the threatened dragonfly species were counted in the years 2015-2018 at 17 different locations (ponds and ditches). Two different widely applied population size measures were used to quantify the population sizes, namely the number of found exoskeletons ('exuviae') and the number of spotted egg-laying females were counted.