Twenty years of dynamic occupancy models: a review of applications and look to the future

Understanding patterns of species occupancy across landscapes and throughout time is a long-standing objective of ecological research that has inspired the development of numerous quantitative modelling approaches. However, estimating occupancy can be a challenge, particularly when contending with issues like imperfect detection and shifting distributions. Dynamic occupancy models (DOMs) offer a framework for occupancy estimation that explicitly accounts for observation error while capturing the mechanisms driving occupancy dynamics by estimating colonisation and local extinction processes. In light of increasing interest in more process-explicit models for understanding species occurrence, here we examine how DOMs have been applied to field ecological data in the two decades since their introduction. Following a general introduction to the model, we present the results of a systematic review exploring where and how DOMs have been applied. We interrogate how authors have built their models, with particular emphasis on how covariates are incorporated to describe variation in occupancy dynamics. Our findings indicate that DOMs are a flexible tool readily applied to diverse study systems and data types, with their usage expanding in recent years as more studies apply them to make spatial and temporal predictions of species occupancy. DOMs are also amenable to extension, further broadening their utility. However, model complexity in DOMs tends to be low; most studies consider relatively few covariates and these are typically represented as simple linear relationships. Approaches to covariate selection also vary considerably, and there remains little research 1on how these choices may influence model performance. Furthermore, only a fraction of articles report evaluating DOMs and little guidance exists on how to approach this task. These uncertainties in the modelling process should be key priorities for future research on DOMs given their increasing use in applied ecological research.