Bayesian data analysis is increasingly used in ecology, but prior specification remains
focused on choosing non‐informative priors (eg, flat or vague priors). One barrier to
choosing more informative priors is that priors must be specified on model parameters (eg,
intercepts, slopes, and sigmas), but prior knowledge often exists on the level of the response
variable. This is particularly true for common models in ecology, like generalized linear
mixed models that have a link function and potentially dozens of parameters, each of which …