Modelling phenology using ordered categorical generalized additive models

One form of data collected in ecology is phenological, describing the timing of life stages. It can be tempting to analyze such data using a continuous distribution or to model individual transitions via probit/logit models. Such simplifications can lead to incorrect inference in various ways, all of which stem from ignoring the natural structure of the data. This paper presents a flexible approach to modelling ordered categorical data using the popular R package mgcv. An example analysis of saxifrage phenology in Greenland including useful plots, model checking and derived quantities is included.